From 5b8ed68ddb415b42160ad3821b0c045f68c0e70c Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Wed, 2 Nov 2022 14:06:46 +0000 Subject: [PATCH 01/25] updating readNoise class estimating covariance matrices for different regions of chip, now returning both estimated readnoise fraction and full covariance matrices --- makefile | 12 +- python/arcticpy/read_noise.py | 335 +- python/arcticpy/wrapper.cpp | 9158 +++++++++++++++++++++++++++++++++ 3 files changed, 9454 insertions(+), 51 deletions(-) create mode 100644 python/arcticpy/wrapper.cpp diff --git a/makefile b/makefile index 8236998..a18d762 100644 --- a/makefile +++ b/makefile @@ -67,11 +67,11 @@ DIR_INC := $(DIR_ROOT)/include DIR_TEST := $(DIR_ROOT)/test #DIR_GSL ?= /cosma/local/gsl/2.5/lib #DIR_OMP ?= /cosma/local/openmpi/gnu_11.1.0/4.1.4/lib -#DIR_GSL ?= $(DIR_HOMEBREW) -#DIR_OMP ?= $(DIR_HOMEBREW) +DIR_GSL ?= $(DIR_HOMEBREW) +DIR_OMP ?= $(DIR_HOMEBREW) #DIR_OMP ?= $(DIR_MACPORTS)/libomp -DIR_OMP ?= $(DIR_MACPORTS) -DIR_GSL ?= $(DIR_MACPORTS) +#DIR_OMP ?= $(DIR_MACPORTS) +#DIR_GSL ?= $(DIR_MACPORTS) # Fallback self-installing GSL #DIR_GSL ?= $(DIR_ROOT)/gsl DIR_WRAPPER := $(DIR_ROOT)/python/arcticpy @@ -99,9 +99,9 @@ LIBARCTIC := -L $(DIR_ROOT) -Wl,-rpath,$(DIR_ROOT) -l$(TARGET) # Add multithreading to reduce runtime (requires OpenMP to have been installed) CXXFLAGS += -Xpreprocessor -fopenmp # Use this on a mac -# LIBS += -L $(DIR_OMP)/lib -lomp + LIBS += -L $(DIR_OMP)/lib -lomp # Use the following on cosma (can also use with macports) -LIBS += -L $(DIR_OMP)/lib -lgomp +#LIBS += -L $(DIR_OMP)/lib -lgomp diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 34baa03..208fdad 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -1,4 +1,6 @@ import numpy as np +import arcticpy as ac +from scipy.optimize import curve_fit """ CTI correction moves trailed electrons back to their proper location, but also @@ -16,8 +18,9 @@ def __init__( adjacency=0.3, noise_model_scaling=1.0, # originally 0.75 amplitude_scale=0.2, # originally 0.33 - n_iter=200 - serial=True + n_iter=200, + serial=True, + **kwargs ): self.sigmaRN = sigma_readnoise @@ -166,6 +169,7 @@ def estimate_read_noise_model_from_image(self, image): nrmsGlobal = 0. smoother = 1 + print('iter','model_rms','target_rms','residual') for s in range(self.n_iter): oldchk = ampReadNoise-rmsGlobal imageAdj= self.determine_noise_model(imageIn,imageOut) @@ -182,7 +186,8 @@ def estimate_read_noise_model_from_image(self, image): nrmsGlobal = noiseImage[cond].size rmsGlobal = np.sqrt(rmsGlobal/nrmsGlobal) - print(s,rmsGlobal, (ampReadNoise-rmsGlobal)) + print("\033[K",end='\r') + print('%4d %f %5.2f %f'%(s,rmsGlobal, self.sigmaRN, (ampReadNoise-rmsGlobal)),end='') chk = ampReadNoise-rmsGlobal if chk*oldchk < 0: @@ -200,22 +205,24 @@ def estimate_read_noise_model_from_image(self, image): ############### ############### def estimate_residual_covariance( - self, - background_level, - # Parallel - parallel_ccd=None, #can we do this with **kwargs ? I'm not sure in python - parallel_roe=None, - parallel_traps=None, - parallel_express=0, - parallel_window_offset=0, - parallel_window_start=0, - parallel_window_stop=-1, - parallel_time_start=0, - parallel_time_stop=-1, - parallel_prune_n_electrons=1e-10, - parallel_prune_frequency=20, - # Serial - if self.smoothCol: #should be more agnostic about direction or rows/cols (for variable names...) + self, + background_level, + background_sigma=None, + chip_size=2048, #size, in pixels, of CCD (assumes square) + matrix_size=5, #size of covariance grid, in pixels (also assumes square) + # Parallel + parallel_ccd=None, #can we do this with **kwargs ? I'm not sure in python + parallel_roe=None, + parallel_traps=None, + parallel_express=0, + parallel_window_offset=0, + parallel_window_start=0, + parallel_window_stop=-1, + parallel_time_start=0, + parallel_time_stop=-1, + parallel_prune_n_electrons=1e-10, + parallel_prune_frequency=20, + # Serial serial_ccd=None, serial_roe=None, serial_traps=None, @@ -232,17 +239,154 @@ def estimate_residual_covariance( # Output verbosity=1, ): - - raise NotImplementedError + if background_sigma==None: + background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) + + #create sky frame + skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) + #add CTI effects + ctiTrailedFrame = ac.add_cti(skyFrame,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + #add read noise + noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) + readNoiseAddedFrame = ctiTrailedFrame + noiseFrame + #do S+R routine + sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) + #clean CTI from S frame + ctiCorrectedFrame = ac.remove_cti(sFrame,1,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + #re-add R frame to correction + outputFrame = ctiCorrectedFrame + rFrame + + #determine covariance FOMs + fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) + fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) + fomDiff = fomSR - fomBenchmark + + return fomDiff + + #raise NotImplementedError + #return np.array([[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]) + + ############### + ############### + def _estimate_residual_covariance_for_opt( + self, + background_level, + sr_fraction, + background_sigma=None, + chip_size=500, #size, in pixels, of CCD (assumes square) + matrix_size=5, #size of covariance grid, in pixels (also assumes square) + **kwargs + ### Parallel + ##parallel_ccd=None, #can we do this with **kwargs ? I'm not sure in python + ##parallel_roe=None, + ##parallel_traps=None, + ##parallel_express=0, + ##parallel_window_offset=0, + ##parallel_window_start=0, + ##parallel_window_stop=-1, + ##parallel_time_start=0, + ##parallel_time_stop=-1, + ##parallel_prune_n_electrons=1e-10, + ##parallel_prune_frequency=20, + ### Serial + ##serial_ccd=None, + ##serial_roe=None, + ##serial_traps=None, + ##serial_express=0, + ##serial_window_offset=0, + ##serial_window_start=0, + ##serial_window_stop=-1, + ##serial_time_start=0, + ##serial_time_stop=-1, + ##serial_prune_n_electrons=1e-10, + ##serial_prune_frequency=20, + ### Pixel bounce + ##pixel_bounce=None, + ### Output + ##verbosity=1, + ): + if background_sigma==None: + background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) + + if 'parallel_roe' in kwargs: + parallel_roe = kwargs['parallel_roe'] + else: + parallel_roe = None + + if 'parallel_ccd' in kwargs: + parallel_ccd = kwargs['parallel_ccd'] + else: + parallel_ccd = None + + if 'parallel_traps' in kwargs: + parallel_traps = kwargs['parallel_traps'] + else: + parallel_traps = None + + if 'parallel_express' in kwargs: + parallel_express = kwargs['parallel_express'] + else: + parallel_express = 0 + + if 'serial_roe' in kwargs: + serial_roe = kwargs['serial_roe'] + else: + serial_roe = None + + if 'serial_ccd' in kwargs: + serial_ccd = kwargs['serial_ccd'] + else: + serial_ccd = None + + if 'serial_traps' in kwargs: + serial_traps = kwargs['serial_traps'] + else: + serial_traps = None + + if 'serial_express' in kwargs: + serial_express = kwargs['serial_express'] + else: + serial_express = 0 + + + #create sky frame + skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) + #add CTI effects + ctiTrailedFrame = ac.add_cti(skyFrame,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + #add read noise + noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) + readNoiseAddedFrame = ctiTrailedFrame + noiseFrame + #do S+R routine + sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) + #rescale S+R correction to a fractional value (for optimization) + sFrame+=rFrame + rFrame*=sr_fraction + sFrame-=rFrame + #clean CTI from S frame + ctiCorrectedFrame = ac.remove_cti(sFrame,1,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + #re-add R frame to correction + outputFrame = ctiCorrectedFrame + rFrame + + #determine covariance FOMs + fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) + fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) + fomDiff = fomSR - fomBenchmark + return fomDiff + ############### + ############### + def _fitter_function(self,x,intercept,slope): + y = intercept + slope * x + return y + ############### ############### - ############### def optimise_parameters( self, - image, background_level, - #figure_of_merit=figure_of_merit(), # should probably pass a function here - **kwargs + **kwargs + #chip_size=500, + #matrix_size=5, + ##figure_of_merit=figure_of_merit(), # should probably pass a function here ## Parallel #parallel_ccd=None, #again, should do this with **kwargs #parallel_roe=None, @@ -272,43 +416,144 @@ def optimise_parameters( ## Output #verbosity=1, ): - #things to compare over iterations - outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) - covar = self.covariance_matrix_from_image(image) - raise NotImplementedError + matrix_size = kwargs['matrix_size'] + optVals = {} + + if 'parallel_traps' in kwargs: + if kwargs['parallel_traps'] is not None: + kwargs_parallel = kwargs.copy() + kwargs_parallel['serial_traps']=None #make a parallel-only quadrant + #things to compare over iterations + result_array = np.array([]) + matrix_array = np.zeros((11,matrix_size,matrix_size)) + sr_frac = np.arange(0,1.01,0.1) + for frac in sr_frac: + correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) + matrix_array[int(frac*10)] = correction_matrix + result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters + result_array = np.append(result_array,result) + + a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) + m = a_fit[1] + b = a_fit[0] + xint = -b/m + + lo = np.floor(xint*10).astype(int) + hi = np.ceil(xint*10).astype(int) + mean_grid = (matrix_array[lo]+matrix_array[hi])/2 + + optVals['parallelQuadMatrix'] = mean_grid + optVals['parallelQuadFrac'] = xint + + if 'serial_traps' in kwargs: + if kwargs['serial_traps'] is not None: + kwargs_serial = kwargs.copy() + kwargs_serial['parallel_traps']=None #make a seriial-only quadrant + #things to compare over iterations + result_array = np.array([]) + matrix_array = np.zeros((11,matrix_size,matrix_size)) + sr_frac = np.arange(0,1.01,0.1) + for frac in sr_frac: + correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_serial) + matrix_array[int(frac*10)] = correction_matrix + result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters + result_array = np.append(result_array,result) + + a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) + m = a_fit[1] + b = a_fit[0] + xint = -b/m + + lo = np.floor(xint*10).astype(int) + hi = np.ceil(xint*10).astype(int) + mean_grid = (matrix_array[lo]+matrix_array[hi])/2 + + optVals['serialQuadMatrix'] = mean_grid + optVals['serialQuadFrac'] = xint + + if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): + if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): + #things to compare over iterations + result_array = np.array([]) + matrix_array = np.zeros((11,matrix_size,matrix_size)) + sr_frac = np.arange(0,1.01,0.1) + for frac in sr_frac: + correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) + matrix_array[int(frac*10)] = correction_matrix + result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters + result_array = np.append(result_array,result) + + a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) + m = a_fit[1] + b = a_fit[0] + xint = -b/m + + lo = np.floor(xint*10).astype(int) + hi = np.ceil(xint*10).astype(int) + mean_grid = (matrix_array[lo]+matrix_array[hi])/2 + + optVals['combinedQuadMatrix'] = mean_grid + optVals['combinedQuadFrac'] = xint + + + return optVals + + ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) + ##covar = self.covariance_matrix_from_image(image) ############### ############### - def figure_of_merit(self,covariance_matrix): - xlen = covariance_matrix.shape[1]//2 - ylen = covariance matrix.shape[0]//2 - fullsum = np.sum(covariance_matrix) #sum over all cells - rowsum = np.sum(covariance_matrix[ylen,:]) #sum over central row (for serial CTI) - colsum = np.sum(covariance_matrix[:,xlen]) #sum over central column (for parallel CTI) - raise NotImplementedError - return fullsum,rowsum,colsum + def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None): + ''' + function for estimating the covariance figure of merit: the average value over some section of a covariance matrix + if method == 'box' take a square region around the central pixel; 'row' is along the central row; column is along the central column + if subgrid size is selected, use only an NxN subset of pixels in the matrix, starting from the center outward + ''' + xlen = covariance_matrix.shape[1] + ylen = covariance_matrix.shape[0] + xcenter = xlen//2 + ycenter = ylen//2 + xstart,xend = 0,xlen + ystart,yend = 0,ylen + if subgrid_size is not None: + xdiff = (xlen-subgrid_size)//2 + ydiff = (ylen-subgrid_size)//2 + xstart+=xdiff + xend-=xdiff + ystart+=ydiff + yend-=ydiff + + if fom_method == 'box': + result_sum = np.sum(covariance_matrix[ystart:yend,xstart:xend]) #sum over central box + if fom_method == 'row': + result_sum = np.sum(covariance_matrix[ycenter,xstart:xend]) #sum over central row (for serial CTI) + if fom_method == 'column': + result_sum = np.sum(covariance_matrix[ystart:yend,xcenter]) #sum over central column (for parallel CTI) + #raise NotImplementedError + return result_sum ############### ############### - def covariance_matrix_from_image(self, image, n_pixels=5): - raise NotImplementedError - covariance_matrix = np.zeros(n_pixels,n_pixels) + def covariance_matrix_from_image(self, image, matrix_size=5): + + covariance_matrix = np.zeros((matrix_size,matrix_size)) #calcluate mean stats on image x = image.flatten() xbar = np.mean(x) #roll image to get cross correlation - matRange= n_pixels//2 + matRange= matrix_size//2 for i in range(-matRange,matRange+1,1): for j in range(-matRange,matRange+1,1): - y = np.roll(img,(-j,-i),axis=(0,1)).flatten() + y = np.roll(image,(-j,-i),axis=(0,1)).flatten() ybar = np.mean(y) #calculate covariance - covar = np.sum((x-xbar)*(y-ybar))/(pl.std(x-xbar)*pl.std(y-ybar))/(x.size) + covar = np.sum((x-xbar)*(y-ybar))/(np.std(x-xbar)*np.std(y-ybar))/(x.size) #populate matrix cells - covariance_matrix[i+2,j+2] = covar - + covariance_matrix[i+matRange,j+matRange] = covar + covariance_matrix[matRange,matRange] = 0 + return covariance_matrix diff --git a/python/arcticpy/wrapper.cpp b/python/arcticpy/wrapper.cpp new file mode 100644 index 0000000..30ea314 --- /dev/null +++ b/python/arcticpy/wrapper.cpp @@ -0,0 +1,9158 @@ +/* Generated by Cython 0.29.28 */ + +/* BEGIN: Cython Metadata +{ + "distutils": { + "define_macros": [ + [ + "NPY_NO_DEPRECATED_API", + 0 + ] + ], + "depends": [ + "/usr/local/lib/python3.9/site-packages/numpy/core/include/numpy/arrayobject.h", + "/usr/local/lib/python3.9/site-packages/numpy/core/include/numpy/arrayscalars.h", + "/usr/local/lib/python3.9/site-packages/numpy/core/include/numpy/ndarrayobject.h", + "/usr/local/lib/python3.9/site-packages/numpy/core/include/numpy/ndarraytypes.h", + "/usr/local/lib/python3.9/site-packages/numpy/core/include/numpy/ufuncobject.h", + "include/util.hpp", + "python/arcticpy/include/interface.hpp" + ], + "extra_compile_args": [ + "-std=c++17", + "-O3" + ], + "include_dirs": [ + "./include/", + "/usr/local/lib/python3.9/site-packages/numpy/core/include", + "./python/arcticpy/include/", + "/usr/local/include/" + ], + "language": "c++", + "libraries": [ + "arctic" + ], + "library_dirs": [ + "./", + "/usr/local/lib/" + ], + "name": "wrapper", + "runtime_library_dirs": [ + "./", + "/usr/local/lib/" + ], + "sources": [ + "./python/arcticpy/wrapper.pyx", + "./python/arcticpy/src/interface.cpp" + ] + }, + "module_name": "wrapper" +} +END: Cython Metadata */ + +#ifndef PY_SSIZE_T_CLEAN +#define PY_SSIZE_T_CLEAN +#endif /* PY_SSIZE_T_CLEAN */ +#include "Python.h" +#ifndef Py_PYTHON_H + #error Python headers needed to compile C extensions, please install development version of Python. +#elif PY_VERSION_HEX < 0x02060000 || (0x03000000 <= PY_VERSION_HEX && PY_VERSION_HEX < 0x03030000) + #error Cython requires Python 2.6+ or Python 3.3+. +#else +#define CYTHON_ABI "0_29_28" +#define CYTHON_HEX_VERSION 0x001D1CF0 +#define CYTHON_FUTURE_DIVISION 1 +#include +#ifndef offsetof + #define offsetof(type, member) ( (size_t) & ((type*)0) -> member ) +#endif +#if !defined(WIN32) && !defined(MS_WINDOWS) + #ifndef __stdcall + #define __stdcall + #endif + #ifndef __cdecl + #define __cdecl + #endif + #ifndef __fastcall + #define __fastcall + #endif +#endif +#ifndef DL_IMPORT + #define DL_IMPORT(t) t +#endif +#ifndef DL_EXPORT + #define DL_EXPORT(t) t +#endif +#define __PYX_COMMA , +#ifndef HAVE_LONG_LONG + #if PY_VERSION_HEX >= 0x02070000 + #define HAVE_LONG_LONG + #endif +#endif +#ifndef PY_LONG_LONG + #define PY_LONG_LONG LONG_LONG +#endif +#ifndef Py_HUGE_VAL + #define Py_HUGE_VAL HUGE_VAL +#endif +#ifdef PYPY_VERSION + #define CYTHON_COMPILING_IN_PYPY 1 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #undef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 0 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #if PY_VERSION_HEX < 0x03050000 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #undef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 0 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #undef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 1 + #undef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 0 + #undef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 0 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#elif defined(PYSTON_VERSION) + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 1 + #define CYTHON_COMPILING_IN_CPYTHON 0 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #undef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 0 + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #undef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL 0 + #undef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT 0 + #undef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE 0 + #undef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS 0 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 +#else + #define CYTHON_COMPILING_IN_PYPY 0 + #define CYTHON_COMPILING_IN_PYSTON 0 + #define CYTHON_COMPILING_IN_CPYTHON 1 + #ifndef CYTHON_USE_TYPE_SLOTS + #define CYTHON_USE_TYPE_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYTYPE_LOOKUP + #define CYTHON_USE_PYTYPE_LOOKUP 0 + #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) + #define CYTHON_USE_PYTYPE_LOOKUP 1 + #endif + #if PY_MAJOR_VERSION < 3 + #undef CYTHON_USE_ASYNC_SLOTS + #define CYTHON_USE_ASYNC_SLOTS 0 + #elif !defined(CYTHON_USE_ASYNC_SLOTS) + #define CYTHON_USE_ASYNC_SLOTS 1 + #endif + #if PY_VERSION_HEX < 0x02070000 + #undef CYTHON_USE_PYLONG_INTERNALS + #define CYTHON_USE_PYLONG_INTERNALS 0 + #elif !defined(CYTHON_USE_PYLONG_INTERNALS) + #define CYTHON_USE_PYLONG_INTERNALS 1 + #endif + #ifndef CYTHON_USE_PYLIST_INTERNALS + #define CYTHON_USE_PYLIST_INTERNALS 1 + #endif + #ifndef CYTHON_USE_UNICODE_INTERNALS + #define CYTHON_USE_UNICODE_INTERNALS 1 + #endif + #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2 + #undef CYTHON_USE_UNICODE_WRITER + #define CYTHON_USE_UNICODE_WRITER 0 + #elif !defined(CYTHON_USE_UNICODE_WRITER) + #define CYTHON_USE_UNICODE_WRITER 1 + #endif + #ifndef CYTHON_AVOID_BORROWED_REFS + #define CYTHON_AVOID_BORROWED_REFS 0 + #endif + #ifndef CYTHON_ASSUME_SAFE_MACROS + #define CYTHON_ASSUME_SAFE_MACROS 1 + #endif + #ifndef CYTHON_UNPACK_METHODS + #define CYTHON_UNPACK_METHODS 1 + #endif + #if PY_VERSION_HEX >= 0x030B00A4 + #undef CYTHON_FAST_THREAD_STATE + #define CYTHON_FAST_THREAD_STATE 0 + #elif !defined(CYTHON_FAST_THREAD_STATE) + #define CYTHON_FAST_THREAD_STATE 1 + #endif + #ifndef CYTHON_FAST_PYCALL + #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030B00A1) + #endif + #ifndef CYTHON_PEP489_MULTI_PHASE_INIT + #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) + #endif + #ifndef CYTHON_USE_TP_FINALIZE + #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) + #endif + #ifndef CYTHON_USE_DICT_VERSIONS + #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) + #endif + #if PY_VERSION_HEX >= 0x030B00A4 + #undef CYTHON_USE_EXC_INFO_STACK + #define CYTHON_USE_EXC_INFO_STACK 0 + #elif !defined(CYTHON_USE_EXC_INFO_STACK) + #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) + #endif +#endif +#if !defined(CYTHON_FAST_PYCCALL) +#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) +#endif +#if CYTHON_USE_PYLONG_INTERNALS + #if PY_MAJOR_VERSION < 3 + #include "longintrepr.h" + #endif + #undef SHIFT + #undef BASE + #undef MASK + #ifdef SIZEOF_VOID_P + enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; + #endif +#endif +#ifndef __has_attribute + #define __has_attribute(x) 0 +#endif +#ifndef __has_cpp_attribute + #define __has_cpp_attribute(x) 0 +#endif +#ifndef CYTHON_RESTRICT + #if defined(__GNUC__) + #define CYTHON_RESTRICT __restrict__ + #elif defined(_MSC_VER) && _MSC_VER >= 1400 + #define CYTHON_RESTRICT __restrict + #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define CYTHON_RESTRICT restrict + #else + #define CYTHON_RESTRICT + #endif +#endif +#ifndef CYTHON_UNUSED +# if defined(__GNUC__) +# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) +# define CYTHON_UNUSED __attribute__ ((__unused__)) +# else +# define CYTHON_UNUSED +# endif +#endif +#ifndef CYTHON_MAYBE_UNUSED_VAR +# if defined(__cplusplus) + template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } +# else +# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) +# endif +#endif +#ifndef CYTHON_NCP_UNUSED +# if CYTHON_COMPILING_IN_CPYTHON +# define CYTHON_NCP_UNUSED +# else +# define CYTHON_NCP_UNUSED CYTHON_UNUSED +# endif +#endif +#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) +#ifdef _MSC_VER + #ifndef _MSC_STDINT_H_ + #if _MSC_VER < 1300 + typedef unsigned char uint8_t; + typedef unsigned int uint32_t; + #else + typedef unsigned __int8 uint8_t; + typedef unsigned __int32 uint32_t; + #endif + #endif +#else + #include +#endif +#ifndef CYTHON_FALLTHROUGH + #if defined(__cplusplus) && __cplusplus >= 201103L + #if __has_cpp_attribute(fallthrough) + #define CYTHON_FALLTHROUGH [[fallthrough]] + #elif __has_cpp_attribute(clang::fallthrough) + #define CYTHON_FALLTHROUGH [[clang::fallthrough]] + #elif __has_cpp_attribute(gnu::fallthrough) + #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] + #endif + #endif + #ifndef CYTHON_FALLTHROUGH + #if __has_attribute(fallthrough) + #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) + #else + #define CYTHON_FALLTHROUGH + #endif + #endif + #if defined(__clang__ ) && defined(__apple_build_version__) + #if __apple_build_version__ < 7000000 + #undef CYTHON_FALLTHROUGH + #define CYTHON_FALLTHROUGH + #endif + #endif +#endif + +#ifndef __cplusplus + #error "Cython files generated with the C++ option must be compiled with a C++ compiler." +#endif +#ifndef CYTHON_INLINE + #if defined(__clang__) + #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) + #else + #define CYTHON_INLINE inline + #endif +#endif +template +void __Pyx_call_destructor(T& x) { + x.~T(); +} +template +class __Pyx_FakeReference { + public: + __Pyx_FakeReference() : ptr(NULL) { } + __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } + T *operator->() { return ptr; } + T *operator&() { return ptr; } + operator T&() { return *ptr; } + template bool operator ==(U other) { return *ptr == other; } + template bool operator !=(U other) { return *ptr != other; } + private: + T *ptr; +}; + +#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) + #define Py_OptimizeFlag 0 +#endif +#define __PYX_BUILD_PY_SSIZE_T "n" +#define CYTHON_FORMAT_SSIZE_T "z" +#if PY_MAJOR_VERSION < 3 + #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) + #define __Pyx_DefaultClassType PyClass_Type +#else + #define __Pyx_BUILTIN_MODULE_NAME "builtins" + #define __Pyx_DefaultClassType PyType_Type +#if PY_VERSION_HEX >= 0x030B00A1 + static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f, + PyObject *code, PyObject *c, PyObject* n, PyObject *v, + PyObject *fv, PyObject *cell, PyObject* fn, + PyObject *name, int fline, PyObject *lnos) { + PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL; + PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL; + const char *fn_cstr=NULL; + const char *name_cstr=NULL; + PyCodeObject* co=NULL; + PyObject *type, *value, *traceback; + PyErr_Fetch(&type, &value, &traceback); + if (!(kwds=PyDict_New())) goto end; + if (!(argcount=PyLong_FromLong(a))) goto end; + if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end; + if (!(posonlyargcount=PyLong_FromLong(0))) goto end; + if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end; + if (!(kwonlyargcount=PyLong_FromLong(k))) goto end; + if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end; + if (!(nlocals=PyLong_FromLong(l))) goto end; + if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end; + if (!(stacksize=PyLong_FromLong(s))) goto end; + if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end; + if (!(flags=PyLong_FromLong(f))) goto end; + if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end; + if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end; + if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end; + if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end; + if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end; + if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too; + if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here + if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too; + Py_XDECREF((PyObject*)co); + co = (PyCodeObject*)call_result; + call_result = NULL; + if (0) { + cleanup_code_too: + Py_XDECREF((PyObject*)co); + co = NULL; + } + end: + Py_XDECREF(kwds); + Py_XDECREF(argcount); + Py_XDECREF(posonlyargcount); + Py_XDECREF(kwonlyargcount); + Py_XDECREF(nlocals); + Py_XDECREF(stacksize); + Py_XDECREF(replace); + Py_XDECREF(call_result); + Py_XDECREF(empty); + if (type) { + PyErr_Restore(type, value, traceback); + } + return co; + } +#else + #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ + PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) +#endif + #define __Pyx_DefaultClassType PyType_Type +#endif +#ifndef Py_TPFLAGS_CHECKTYPES + #define Py_TPFLAGS_CHECKTYPES 0 +#endif +#ifndef Py_TPFLAGS_HAVE_INDEX + #define Py_TPFLAGS_HAVE_INDEX 0 +#endif +#ifndef Py_TPFLAGS_HAVE_NEWBUFFER + #define Py_TPFLAGS_HAVE_NEWBUFFER 0 +#endif +#ifndef Py_TPFLAGS_HAVE_FINALIZE + #define Py_TPFLAGS_HAVE_FINALIZE 0 +#endif +#ifndef METH_STACKLESS + #define METH_STACKLESS 0 +#endif +#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) + #ifndef METH_FASTCALL + #define METH_FASTCALL 0x80 + #endif + typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); + typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, + Py_ssize_t nargs, PyObject *kwnames); +#else + #define __Pyx_PyCFunctionFast _PyCFunctionFast + #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords +#endif +#if CYTHON_FAST_PYCCALL +#define __Pyx_PyFastCFunction_Check(func)\ + ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) +#else +#define __Pyx_PyFastCFunction_Check(func) 0 +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) + #define PyObject_Malloc(s) PyMem_Malloc(s) + #define PyObject_Free(p) PyMem_Free(p) + #define PyObject_Realloc(p) PyMem_Realloc(p) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 + #define PyMem_RawMalloc(n) PyMem_Malloc(n) + #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) + #define PyMem_RawFree(p) PyMem_Free(p) +#endif +#if CYTHON_COMPILING_IN_PYSTON + #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) +#else + #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) + #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) +#endif +#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#elif PY_VERSION_HEX >= 0x03060000 + #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() +#elif PY_VERSION_HEX >= 0x03000000 + #define __Pyx_PyThreadState_Current PyThreadState_GET() +#else + #define __Pyx_PyThreadState_Current _PyThreadState_Current +#endif +#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) +#include "pythread.h" +#define Py_tss_NEEDS_INIT 0 +typedef int Py_tss_t; +static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { + *key = PyThread_create_key(); + return 0; +} +static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { + Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); + *key = Py_tss_NEEDS_INIT; + return key; +} +static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { + PyObject_Free(key); +} +static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { + return *key != Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { + PyThread_delete_key(*key); + *key = Py_tss_NEEDS_INIT; +} +static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { + return PyThread_set_key_value(*key, value); +} +static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { + return PyThread_get_key_value(*key); +} +#endif +#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) +#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) +#else +#define __Pyx_PyDict_NewPresized(n) PyDict_New() +#endif +#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION + #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) +#else + #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) + #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) +#endif +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS +#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) +#else +#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) +#endif +#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) + #define CYTHON_PEP393_ENABLED 1 + #if defined(PyUnicode_IS_READY) + #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ + 0 : _PyUnicode_Ready((PyObject *)(op))) + #else + #define __Pyx_PyUnicode_READY(op) (0) + #endif + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) + #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) + #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) + #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) + #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) + #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000 + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length)) + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) + #endif + #else + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) + #endif +#else + #define CYTHON_PEP393_ENABLED 0 + #define PyUnicode_1BYTE_KIND 1 + #define PyUnicode_2BYTE_KIND 2 + #define PyUnicode_4BYTE_KIND 4 + #define __Pyx_PyUnicode_READY(op) (0) + #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) + #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) + #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) + #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) + #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) + #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) + #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) + #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) +#endif +#if CYTHON_COMPILING_IN_PYPY + #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) +#else + #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) + #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ + PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) + #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) + #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) +#endif +#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) + #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) +#endif +#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) +#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? PyNumber_Remainder(a, b) : PyUnicode_Format(a, b)) +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyString_Format(a, b) PyUnicode_Format(a, b) +#else + #define __Pyx_PyString_Format(a, b) PyString_Format(a, b) +#endif +#if PY_MAJOR_VERSION < 3 && !defined(PyObject_ASCII) + #define PyObject_ASCII(o) PyObject_Repr(o) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBaseString_Type PyUnicode_Type + #define PyStringObject PyUnicodeObject + #define PyString_Type PyUnicode_Type + #define PyString_Check PyUnicode_Check + #define PyString_CheckExact PyUnicode_CheckExact +#ifndef PyObject_Unicode + #define PyObject_Unicode PyObject_Str +#endif +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyBaseString_Check(obj) PyUnicode_Check(obj) + #define __Pyx_PyBaseString_CheckExact(obj) PyUnicode_CheckExact(obj) +#else + #define __Pyx_PyBaseString_Check(obj) (PyString_Check(obj) || PyUnicode_Check(obj)) + #define __Pyx_PyBaseString_CheckExact(obj) (PyString_CheckExact(obj) || PyUnicode_CheckExact(obj)) +#endif +#ifndef PySet_CheckExact + #define PySet_CheckExact(obj) (Py_TYPE(obj) == &PySet_Type) +#endif +#if PY_VERSION_HEX >= 0x030900A4 + #define __Pyx_SET_REFCNT(obj, refcnt) Py_SET_REFCNT(obj, refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SET_SIZE(obj, size) +#else + #define __Pyx_SET_REFCNT(obj, refcnt) Py_REFCNT(obj) = (refcnt) + #define __Pyx_SET_SIZE(obj, size) Py_SIZE(obj) = (size) +#endif +#if CYTHON_ASSUME_SAFE_MACROS + #define __Pyx_PySequence_SIZE(seq) Py_SIZE(seq) +#else + #define __Pyx_PySequence_SIZE(seq) PySequence_Size(seq) +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyIntObject PyLongObject + #define PyInt_Type PyLong_Type + #define PyInt_Check(op) PyLong_Check(op) + #define PyInt_CheckExact(op) PyLong_CheckExact(op) + #define PyInt_FromString PyLong_FromString + #define PyInt_FromUnicode PyLong_FromUnicode + #define PyInt_FromLong PyLong_FromLong + #define PyInt_FromSize_t PyLong_FromSize_t + #define PyInt_FromSsize_t PyLong_FromSsize_t + #define PyInt_AsLong PyLong_AsLong + #define PyInt_AS_LONG PyLong_AS_LONG + #define PyInt_AsSsize_t PyLong_AsSsize_t + #define PyInt_AsUnsignedLongMask PyLong_AsUnsignedLongMask + #define PyInt_AsUnsignedLongLongMask PyLong_AsUnsignedLongLongMask + #define PyNumber_Int PyNumber_Long +#endif +#if PY_MAJOR_VERSION >= 3 + #define PyBoolObject PyLongObject +#endif +#if PY_MAJOR_VERSION >= 3 && CYTHON_COMPILING_IN_PYPY + #ifndef PyUnicode_InternFromString + #define PyUnicode_InternFromString(s) PyUnicode_FromString(s) + #endif +#endif +#if PY_VERSION_HEX < 0x030200A4 + typedef long Py_hash_t; + #define __Pyx_PyInt_FromHash_t PyInt_FromLong + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsHash_t +#else + #define __Pyx_PyInt_FromHash_t PyInt_FromSsize_t + #define __Pyx_PyInt_AsHash_t __Pyx_PyIndex_AsSsize_t +#endif +#if PY_MAJOR_VERSION >= 3 + #define __Pyx_PyMethod_New(func, self, klass) ((self) ? ((void)(klass), PyMethod_New(func, self)) : __Pyx_NewRef(func)) +#else + #define __Pyx_PyMethod_New(func, self, klass) PyMethod_New(func, self, klass) +#endif +#if CYTHON_USE_ASYNC_SLOTS + #if PY_VERSION_HEX >= 0x030500B1 + #define __Pyx_PyAsyncMethodsStruct PyAsyncMethods + #define __Pyx_PyType_AsAsync(obj) (Py_TYPE(obj)->tp_as_async) + #else + #define __Pyx_PyType_AsAsync(obj) ((__Pyx_PyAsyncMethodsStruct*) (Py_TYPE(obj)->tp_reserved)) + #endif +#else + #define __Pyx_PyType_AsAsync(obj) NULL +#endif +#ifndef __Pyx_PyAsyncMethodsStruct + typedef struct { + unaryfunc am_await; + unaryfunc am_aiter; + unaryfunc am_anext; + } __Pyx_PyAsyncMethodsStruct; +#endif + +#if defined(WIN32) || defined(MS_WINDOWS) + #define _USE_MATH_DEFINES +#endif +#include +#ifdef NAN +#define __PYX_NAN() ((float) NAN) +#else +static CYTHON_INLINE float __PYX_NAN() { + float value; + memset(&value, 0xFF, sizeof(value)); + return value; +} +#endif +#if defined(__CYGWIN__) && defined(_LDBL_EQ_DBL) +#define __Pyx_truncl trunc +#else +#define __Pyx_truncl truncl +#endif + +#define __PYX_MARK_ERR_POS(f_index, lineno) \ + { __pyx_filename = __pyx_f[f_index]; (void)__pyx_filename; __pyx_lineno = lineno; (void)__pyx_lineno; __pyx_clineno = __LINE__; (void)__pyx_clineno; } +#define __PYX_ERR(f_index, lineno, Ln_error) \ + { __PYX_MARK_ERR_POS(f_index, lineno) goto Ln_error; } + +#ifndef __PYX_EXTERN_C + #ifdef __cplusplus + #define __PYX_EXTERN_C extern "C" + #else + #define __PYX_EXTERN_C extern + #endif +#endif + +#define __PYX_HAVE__wrapper +#define __PYX_HAVE_API__wrapper +/* Early includes */ +#include +#include +#include "numpy/arrayobject.h" +#include "numpy/ndarrayobject.h" +#include "numpy/ndarraytypes.h" +#include "numpy/arrayscalars.h" +#include "numpy/ufuncobject.h" + + /* NumPy API declarations from "numpy/__init__.pxd" */ + +#include +#include "ios" +#include "new" +#include "stdexcept" +#include "typeinfo" +#include "util.hpp" +#include "interface.hpp" +#ifdef _OPENMP +#include +#endif /* _OPENMP */ + +#if defined(PYREX_WITHOUT_ASSERTIONS) && !defined(CYTHON_WITHOUT_ASSERTIONS) +#define CYTHON_WITHOUT_ASSERTIONS +#endif + +typedef struct {PyObject **p; const char *s; const Py_ssize_t n; const char* encoding; + const char is_unicode; const char is_str; const char intern; } __Pyx_StringTabEntry; + +#define __PYX_DEFAULT_STRING_ENCODING_IS_ASCII 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_UTF8 0 +#define __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT (PY_MAJOR_VERSION >= 3 && __PYX_DEFAULT_STRING_ENCODING_IS_UTF8) +#define __PYX_DEFAULT_STRING_ENCODING "" +#define __Pyx_PyObject_FromString __Pyx_PyBytes_FromString +#define __Pyx_PyObject_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#define __Pyx_uchar_cast(c) ((unsigned char)c) +#define __Pyx_long_cast(x) ((long)x) +#define __Pyx_fits_Py_ssize_t(v, type, is_signed) (\ + (sizeof(type) < sizeof(Py_ssize_t)) ||\ + (sizeof(type) > sizeof(Py_ssize_t) &&\ + likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX) &&\ + (!is_signed || likely(v > (type)PY_SSIZE_T_MIN ||\ + v == (type)PY_SSIZE_T_MIN))) ||\ + (sizeof(type) == sizeof(Py_ssize_t) &&\ + (is_signed || likely(v < (type)PY_SSIZE_T_MAX ||\ + v == (type)PY_SSIZE_T_MAX))) ) +static CYTHON_INLINE int __Pyx_is_valid_index(Py_ssize_t i, Py_ssize_t limit) { + return (size_t) i < (size_t) limit; +} +#if defined (__cplusplus) && __cplusplus >= 201103L + #include + #define __Pyx_sst_abs(value) std::abs(value) +#elif SIZEOF_INT >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) abs(value) +#elif SIZEOF_LONG >= SIZEOF_SIZE_T + #define __Pyx_sst_abs(value) labs(value) +#elif defined (_MSC_VER) + #define __Pyx_sst_abs(value) ((Py_ssize_t)_abs64(value)) +#elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L + #define __Pyx_sst_abs(value) llabs(value) +#elif defined (__GNUC__) + #define __Pyx_sst_abs(value) __builtin_llabs(value) +#else + #define __Pyx_sst_abs(value) ((value<0) ? -value : value) +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); +#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) +#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) +#define __Pyx_PyBytes_FromString PyBytes_FromString +#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); +#if PY_MAJOR_VERSION < 3 + #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize +#else + #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString + #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize +#endif +#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) +#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) +#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) +#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) +#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) +#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) +#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) +static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { + const Py_UNICODE *u_end = u; + while (*u_end++) ; + return (size_t)(u_end - u - 1); +} +#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) +#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode +#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode +#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) +#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); +#define __Pyx_PySequence_Tuple(obj)\ + (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*); +#if CYTHON_ASSUME_SAFE_MACROS +#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) +#else +#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) +#endif +#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) +#if PY_MAJOR_VERSION >= 3 +#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) +#else +#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) +#endif +#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII +static int __Pyx_sys_getdefaultencoding_not_ascii; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + PyObject* ascii_chars_u = NULL; + PyObject* ascii_chars_b = NULL; + const char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + if (strcmp(default_encoding_c, "ascii") == 0) { + __Pyx_sys_getdefaultencoding_not_ascii = 0; + } else { + char ascii_chars[128]; + int c; + for (c = 0; c < 128; c++) { + ascii_chars[c] = c; + } + __Pyx_sys_getdefaultencoding_not_ascii = 1; + ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); + if (!ascii_chars_u) goto bad; + ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); + if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { + PyErr_Format( + PyExc_ValueError, + "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", + default_encoding_c); + goto bad; + } + Py_DECREF(ascii_chars_u); + Py_DECREF(ascii_chars_b); + } + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + Py_XDECREF(ascii_chars_u); + Py_XDECREF(ascii_chars_b); + return -1; +} +#endif +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT && PY_MAJOR_VERSION >= 3 +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_DecodeUTF8(c_str, size, NULL) +#else +#define __Pyx_PyUnicode_FromStringAndSize(c_str, size) PyUnicode_Decode(c_str, size, __PYX_DEFAULT_STRING_ENCODING, NULL) +#if __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +static char* __PYX_DEFAULT_STRING_ENCODING; +static int __Pyx_init_sys_getdefaultencoding_params(void) { + PyObject* sys; + PyObject* default_encoding = NULL; + char* default_encoding_c; + sys = PyImport_ImportModule("sys"); + if (!sys) goto bad; + default_encoding = PyObject_CallMethod(sys, (char*) (const char*) "getdefaultencoding", NULL); + Py_DECREF(sys); + if (!default_encoding) goto bad; + default_encoding_c = PyBytes_AsString(default_encoding); + if (!default_encoding_c) goto bad; + __PYX_DEFAULT_STRING_ENCODING = (char*) malloc(strlen(default_encoding_c) + 1); + if (!__PYX_DEFAULT_STRING_ENCODING) goto bad; + strcpy(__PYX_DEFAULT_STRING_ENCODING, default_encoding_c); + Py_DECREF(default_encoding); + return 0; +bad: + Py_XDECREF(default_encoding); + return -1; +} +#endif +#endif + + +/* Test for GCC > 2.95 */ +#if defined(__GNUC__) && (__GNUC__ > 2 || (__GNUC__ == 2 && (__GNUC_MINOR__ > 95))) + #define likely(x) __builtin_expect(!!(x), 1) + #define unlikely(x) __builtin_expect(!!(x), 0) +#else /* !__GNUC__ or GCC < 2.95 */ + #define likely(x) (x) + #define unlikely(x) (x) +#endif /* __GNUC__ */ +static CYTHON_INLINE void __Pyx_pretend_to_initialize(void* ptr) { (void)ptr; } + +static PyObject *__pyx_m = NULL; +static PyObject *__pyx_d; +static PyObject *__pyx_b; +static PyObject *__pyx_cython_runtime = NULL; +static PyObject *__pyx_empty_tuple; +static PyObject *__pyx_empty_bytes; +static PyObject *__pyx_empty_unicode; +static int __pyx_lineno; +static int __pyx_clineno = 0; +static const char * __pyx_cfilenm= __FILE__; +static const char *__pyx_filename; + +/* Header.proto */ +#if !defined(CYTHON_CCOMPLEX) + #if defined(__cplusplus) + #define CYTHON_CCOMPLEX 1 + #elif defined(_Complex_I) + #define CYTHON_CCOMPLEX 1 + #else + #define CYTHON_CCOMPLEX 0 + #endif +#endif +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #include + #else + #include + #endif +#endif +#if CYTHON_CCOMPLEX && !defined(__cplusplus) && defined(__sun__) && defined(__GNUC__) + #undef _Complex_I + #define _Complex_I 1.0fj +#endif + + +static const char *__pyx_f[] = { + "python/arcticpy/wrapper.pyx", + "__init__.pxd", + "stringsource", + "type.pxd", +}; +/* BufferFormatStructs.proto */ +#define IS_UNSIGNED(type) (((type) -1) > 0) +struct __Pyx_StructField_; +#define __PYX_BUF_FLAGS_PACKED_STRUCT (1 << 0) +typedef struct { + const char* name; + struct __Pyx_StructField_* fields; + size_t size; + size_t arraysize[8]; + int ndim; + char typegroup; + char is_unsigned; + int flags; +} __Pyx_TypeInfo; +typedef struct __Pyx_StructField_ { + __Pyx_TypeInfo* type; + const char* name; + size_t offset; +} __Pyx_StructField; +typedef struct { + __Pyx_StructField* field; + size_t parent_offset; +} __Pyx_BufFmt_StackElem; +typedef struct { + __Pyx_StructField root; + __Pyx_BufFmt_StackElem* head; + size_t fmt_offset; + size_t new_count, enc_count; + size_t struct_alignment; + int is_complex; + char enc_type; + char new_packmode; + char enc_packmode; + char is_valid_array; +} __Pyx_BufFmt_Context; + + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":689 + * # in Cython to enable them only on the right systems. + * + * ctypedef npy_int8 int8_t # <<<<<<<<<<<<<< + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + */ +typedef npy_int8 __pyx_t_5numpy_int8_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":690 + * + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t # <<<<<<<<<<<<<< + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t + */ +typedef npy_int16 __pyx_t_5numpy_int16_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":691 + * ctypedef npy_int8 int8_t + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t # <<<<<<<<<<<<<< + * ctypedef npy_int64 int64_t + * #ctypedef npy_int96 int96_t + */ +typedef npy_int32 __pyx_t_5numpy_int32_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":692 + * ctypedef npy_int16 int16_t + * ctypedef npy_int32 int32_t + * ctypedef npy_int64 int64_t # <<<<<<<<<<<<<< + * #ctypedef npy_int96 int96_t + * #ctypedef npy_int128 int128_t + */ +typedef npy_int64 __pyx_t_5numpy_int64_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":696 + * #ctypedef npy_int128 int128_t + * + * ctypedef npy_uint8 uint8_t # <<<<<<<<<<<<<< + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + */ +typedef npy_uint8 __pyx_t_5numpy_uint8_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":697 + * + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t # <<<<<<<<<<<<<< + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t + */ +typedef npy_uint16 __pyx_t_5numpy_uint16_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":698 + * ctypedef npy_uint8 uint8_t + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t # <<<<<<<<<<<<<< + * ctypedef npy_uint64 uint64_t + * #ctypedef npy_uint96 uint96_t + */ +typedef npy_uint32 __pyx_t_5numpy_uint32_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":699 + * ctypedef npy_uint16 uint16_t + * ctypedef npy_uint32 uint32_t + * ctypedef npy_uint64 uint64_t # <<<<<<<<<<<<<< + * #ctypedef npy_uint96 uint96_t + * #ctypedef npy_uint128 uint128_t + */ +typedef npy_uint64 __pyx_t_5numpy_uint64_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":703 + * #ctypedef npy_uint128 uint128_t + * + * ctypedef npy_float32 float32_t # <<<<<<<<<<<<<< + * ctypedef npy_float64 float64_t + * #ctypedef npy_float80 float80_t + */ +typedef npy_float32 __pyx_t_5numpy_float32_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":704 + * + * ctypedef npy_float32 float32_t + * ctypedef npy_float64 float64_t # <<<<<<<<<<<<<< + * #ctypedef npy_float80 float80_t + * #ctypedef npy_float128 float128_t + */ +typedef npy_float64 __pyx_t_5numpy_float64_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":713 + * # The int types are mapped a bit surprising -- + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t + */ +typedef npy_long __pyx_t_5numpy_int_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":714 + * # numpy.int corresponds to 'l' and numpy.long to 'q' + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t # <<<<<<<<<<<<<< + * ctypedef npy_longlong longlong_t + * + */ +typedef npy_longlong __pyx_t_5numpy_long_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":715 + * ctypedef npy_long int_t + * ctypedef npy_longlong long_t + * ctypedef npy_longlong longlong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_ulong uint_t + */ +typedef npy_longlong __pyx_t_5numpy_longlong_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":717 + * ctypedef npy_longlong longlong_t + * + * ctypedef npy_ulong uint_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t + */ +typedef npy_ulong __pyx_t_5numpy_uint_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":718 + * + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t # <<<<<<<<<<<<<< + * ctypedef npy_ulonglong ulonglong_t + * + */ +typedef npy_ulonglong __pyx_t_5numpy_ulong_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":719 + * ctypedef npy_ulong uint_t + * ctypedef npy_ulonglong ulong_t + * ctypedef npy_ulonglong ulonglong_t # <<<<<<<<<<<<<< + * + * ctypedef npy_intp intp_t + */ +typedef npy_ulonglong __pyx_t_5numpy_ulonglong_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":721 + * ctypedef npy_ulonglong ulonglong_t + * + * ctypedef npy_intp intp_t # <<<<<<<<<<<<<< + * ctypedef npy_uintp uintp_t + * + */ +typedef npy_intp __pyx_t_5numpy_intp_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":722 + * + * ctypedef npy_intp intp_t + * ctypedef npy_uintp uintp_t # <<<<<<<<<<<<<< + * + * ctypedef npy_double float_t + */ +typedef npy_uintp __pyx_t_5numpy_uintp_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":724 + * ctypedef npy_uintp uintp_t + * + * ctypedef npy_double float_t # <<<<<<<<<<<<<< + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t + */ +typedef npy_double __pyx_t_5numpy_float_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":725 + * + * ctypedef npy_double float_t + * ctypedef npy_double double_t # <<<<<<<<<<<<<< + * ctypedef npy_longdouble longdouble_t + * + */ +typedef npy_double __pyx_t_5numpy_double_t; + +/* "../../../usr/local/lib/python3.9/site-packages/numpy/__init__.pxd":726 + * ctypedef npy_double float_t + * ctypedef npy_double double_t + * ctypedef npy_longdouble longdouble_t # <<<<<<<<<<<<<< + * + * ctypedef npy_cfloat cfloat_t + */ +typedef npy_longdouble __pyx_t_5numpy_longdouble_t; 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r = NULL; __Pyx_DECREF(tmp);}} while(0) + +/* IncludeCppStringH.proto */ +#include + +/* decode_c_string_utf16.proto */ +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 0; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16LE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = -1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} +static CYTHON_INLINE PyObject *__Pyx_PyUnicode_DecodeUTF16BE(const char *s, Py_ssize_t size, const char *errors) { + int byteorder = 1; + return PyUnicode_DecodeUTF16(s, size, errors, &byteorder); +} + +/* decode_c_bytes.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_c_bytes( + const char* cstring, Py_ssize_t length, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)); + +/* decode_cpp_string.proto */ +static CYTHON_INLINE PyObject* __Pyx_decode_cpp_string( + std::string cppstring, Py_ssize_t start, Py_ssize_t stop, + const char* encoding, const char* errors, + PyObject* (*decode_func)(const char *s, Py_ssize_t size, const char *errors)) { + return __Pyx_decode_c_bytes( + cppstring.data(), cppstring.size(), start, stop, encoding, errors, decode_func); +} + +/* PyObjectGetAttrStr.proto */ +#if CYTHON_USE_TYPE_SLOTS +static CYTHON_INLINE PyObject* __Pyx_PyObject_GetAttrStr(PyObject* obj, PyObject* attr_name); +#else +#define __Pyx_PyObject_GetAttrStr(o,n) PyObject_GetAttr(o,n) +#endif + +/* DictGetItem.proto */ +#if PY_MAJOR_VERSION >= 3 && !CYTHON_COMPILING_IN_PYPY +static PyObject *__Pyx_PyDict_GetItem(PyObject *d, PyObject* key); +#define __Pyx_PyObject_Dict_GetItem(obj, name)\ + (likely(PyDict_CheckExact(obj)) ?\ + __Pyx_PyDict_GetItem(obj, name) : PyObject_GetItem(obj, name)) +#else +#define __Pyx_PyDict_GetItem(d, key) PyObject_GetItem(d, key) +#define __Pyx_PyObject_Dict_GetItem(obj, name) PyObject_GetItem(obj, name) +#endif + +/* GetBuiltinName.proto */ +static PyObject *__Pyx_GetBuiltinName(PyObject *name); + +/* PyDictVersioning.proto */ +#if CYTHON_USE_DICT_VERSIONS && CYTHON_USE_TYPE_SLOTS +#define __PYX_DICT_VERSION_INIT ((PY_UINT64_T) -1) +#define __PYX_GET_DICT_VERSION(dict) (((PyDictObject*)(dict))->ma_version_tag) +#define __PYX_UPDATE_DICT_CACHE(dict, value, cache_var, version_var)\ + (version_var) = __PYX_GET_DICT_VERSION(dict);\ + (cache_var) = (value); +#define __PYX_PY_DICT_LOOKUP_IF_MODIFIED(VAR, DICT, LOOKUP) {\ + static PY_UINT64_T __pyx_dict_version = 0;\ + static PyObject *__pyx_dict_cached_value = NULL;\ + if (likely(__PYX_GET_DICT_VERSION(DICT) == __pyx_dict_version)) {\ + (VAR) = __pyx_dict_cached_value;\ + } else {\ + (VAR) = __pyx_dict_cached_value = (LOOKUP);\ + __pyx_dict_version = __PYX_GET_DICT_VERSION(DICT);\ + }\ +} +static CYTHON_INLINE PY_UINT64_T __Pyx_get_tp_dict_version(PyObject *obj); +static CYTHON_INLINE PY_UINT64_T __Pyx_get_object_dict_version(PyObject *obj); +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version); 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+#else +#define __Pyx_GetModuleGlobalName(var, name) (var) = __Pyx__GetModuleGlobalName(name) +#define __Pyx_GetModuleGlobalNameUncached(var, name) (var) = __Pyx__GetModuleGlobalName(name) +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name); +#endif + +/* PyCFunctionFastCall.proto */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject *__Pyx_PyCFunction_FastCall(PyObject *func, PyObject **args, Py_ssize_t nargs); +#else +#define __Pyx_PyCFunction_FastCall(func, args, nargs) (assert(0), NULL) +#endif + +/* PyFunctionFastCall.proto */ +#if CYTHON_FAST_PYCALL +#define __Pyx_PyFunction_FastCall(func, args, nargs)\ + __Pyx_PyFunction_FastCallDict((func), (args), (nargs), NULL) +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs); +#else +#define __Pyx_PyFunction_FastCallDict(func, args, nargs, kwargs) _PyFunction_FastCallDict(func, args, nargs, kwargs) +#endif +#define __Pyx_BUILD_ASSERT_EXPR(cond)\ + (sizeof(char [1 - 2*!(cond)]) - 1) +#ifndef Py_MEMBER_SIZE +#define Py_MEMBER_SIZE(type, member) sizeof(((type *)0)->member) +#endif +#if CYTHON_FAST_PYCALL + static size_t __pyx_pyframe_localsplus_offset = 0; + #include "frameobject.h" + #define __Pxy_PyFrame_Initialize_Offsets()\ + ((void)__Pyx_BUILD_ASSERT_EXPR(sizeof(PyFrameObject) == offsetof(PyFrameObject, f_localsplus) + Py_MEMBER_SIZE(PyFrameObject, f_localsplus)),\ + (void)(__pyx_pyframe_localsplus_offset = ((size_t)PyFrame_Type.tp_basicsize) - Py_MEMBER_SIZE(PyFrameObject, f_localsplus))) + #define __Pyx_PyFrame_GetLocalsplus(frame)\ + (assert(__pyx_pyframe_localsplus_offset), (PyObject **)(((char *)(frame)) + __pyx_pyframe_localsplus_offset)) +#endif // CYTHON_FAST_PYCALL +#endif + +/* PyObjectCall.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw); +#else +#define __Pyx_PyObject_Call(func, arg, kw) PyObject_Call(func, arg, kw) +#endif + +/* PyObjectCall2Args.proto */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2); + +/* PyObjectCallMethO.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg); +#endif + +/* PyObjectCallOneArg.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg); + +/* ArgTypeTest.proto */ +#define __Pyx_ArgTypeTest(obj, type, none_allowed, name, exact)\ + ((likely((Py_TYPE(obj) == type) | (none_allowed && (obj == Py_None)))) ? 1 :\ + __Pyx__ArgTypeTest(obj, type, name, exact)) +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact); + +/* IsLittleEndian.proto */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void); + +/* BufferFormatCheck.proto */ +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts); +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type); + +/* BufferGetAndValidate.proto */ +#define __Pyx_GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)\ + ((obj == Py_None || obj == NULL) ?\ + (__Pyx_ZeroBuffer(buf), 0) :\ + __Pyx__GetBufferAndValidate(buf, obj, dtype, flags, nd, cast, stack)) +static int __Pyx__GetBufferAndValidate(Py_buffer* buf, PyObject* obj, + __Pyx_TypeInfo* dtype, int flags, int nd, int cast, __Pyx_BufFmt_StackElem* stack); +static void __Pyx_ZeroBuffer(Py_buffer* buf); +static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info); +static Py_ssize_t __Pyx_minusones[] = { -1, -1, -1, -1, -1, -1, -1, -1 }; +static Py_ssize_t __Pyx_zeros[] = { 0, 0, 0, 0, 0, 0, 0, 0 }; + +/* ExtTypeTest.proto */ +static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type); + +/* BufferFallbackError.proto */ +static void __Pyx_RaiseBufferFallbackError(void); + +/* BufferIndexError.proto */ +static void __Pyx_RaiseBufferIndexError(int axis); + +#define __Pyx_BufPtrStrided1d(type, buf, i0, s0) (type)((char*)buf + i0 * s0) +/* PyThreadStateGet.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyThreadState_declare PyThreadState *__pyx_tstate; +#define __Pyx_PyThreadState_assign __pyx_tstate = __Pyx_PyThreadState_Current; +#define __Pyx_PyErr_Occurred() __pyx_tstate->curexc_type +#else +#define __Pyx_PyThreadState_declare +#define __Pyx_PyThreadState_assign +#define __Pyx_PyErr_Occurred() PyErr_Occurred() +#endif + +/* PyErrFetchRestore.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_Clear() __Pyx_ErrRestore(NULL, NULL, NULL) +#define __Pyx_ErrRestoreWithState(type, value, tb) __Pyx_ErrRestoreInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) __Pyx_ErrFetchInState(PyThreadState_GET(), type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) __Pyx_ErrRestoreInState(__pyx_tstate, type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) __Pyx_ErrFetchInState(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) +#else +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#endif +#else +#define __Pyx_PyErr_Clear() PyErr_Clear() +#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) +#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) +#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) +#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) +#endif + +#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) +/* RaiseArgTupleInvalid.proto */ +static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, + Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); + +/* RaiseDoubleKeywords.proto */ +static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); + +/* ParseKeywords.proto */ +static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ + PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ + const char* function_name); + +/* GetTopmostException.proto */ +#if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); +#endif + +/* SaveResetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); +#else +#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) +#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) +#endif + +/* PyErrExceptionMatches.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) +static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); +#else +#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) +#endif + +/* GetException.proto */ +#if CYTHON_FAST_THREAD_STATE +#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); +#endif + +/* RaiseException.proto */ +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); + +/* TypeImport.proto */ +#ifndef __PYX_HAVE_RT_ImportType_proto +#define __PYX_HAVE_RT_ImportType_proto +enum __Pyx_ImportType_CheckSize { + __Pyx_ImportType_CheckSize_Error = 0, + __Pyx_ImportType_CheckSize_Warn = 1, + __Pyx_ImportType_CheckSize_Ignore = 2 +}; +static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); +#endif + +/* Import.proto */ +static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); + +/* CLineInTraceback.proto */ +#ifdef CYTHON_CLINE_IN_TRACEBACK +#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) +#else +static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); +#endif + +/* CodeObjectCache.proto */ +typedef struct { + PyCodeObject* code_object; + int code_line; +} __Pyx_CodeObjectCacheEntry; +struct __Pyx_CodeObjectCache { + int count; + int max_count; + __Pyx_CodeObjectCacheEntry* entries; +}; +static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; +static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); +static PyCodeObject *__pyx_find_code_object(int code_line); +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); + +/* AddTraceback.proto */ +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename); + +/* BufferStructDeclare.proto */ +typedef struct { + Py_ssize_t shape, strides, suboffsets; +} __Pyx_Buf_DimInfo; +typedef struct { + size_t refcount; + Py_buffer pybuffer; +} __Pyx_Buffer; +typedef struct { + __Pyx_Buffer *rcbuffer; + char *data; + __Pyx_Buf_DimInfo diminfo[8]; +} __Pyx_LocalBuf_ND; + +#if PY_MAJOR_VERSION < 3 + static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); + static void __Pyx_ReleaseBuffer(Py_buffer *view); +#else + #define __Pyx_GetBuffer PyObject_GetBuffer + #define __Pyx_ReleaseBuffer PyBuffer_Release +#endif + + +/* GCCDiagnostics.proto */ +#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) +#define __Pyx_HAS_GCC_DIAGNOSTIC +#endif + +/* RealImag.proto */ +#if CYTHON_CCOMPLEX + #ifdef __cplusplus + #define __Pyx_CREAL(z) ((z).real()) + #define __Pyx_CIMAG(z) ((z).imag()) + #else + #define __Pyx_CREAL(z) (__real__(z)) + #define __Pyx_CIMAG(z) (__imag__(z)) + #endif +#else + #define __Pyx_CREAL(z) ((z).real) + #define __Pyx_CIMAG(z) ((z).imag) +#endif +#if defined(__cplusplus) && CYTHON_CCOMPLEX\ + && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) + #define __Pyx_SET_CREAL(z,x) ((z).real(x)) + #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) +#else + #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) + #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_float(a, b) ((a)==(b)) + #define __Pyx_c_sum_float(a, b) ((a)+(b)) + #define __Pyx_c_diff_float(a, b) ((a)-(b)) + #define __Pyx_c_prod_float(a, b) ((a)*(b)) + #define __Pyx_c_quot_float(a, b) ((a)/(b)) + #define __Pyx_c_neg_float(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_float(z) ((z)==(float)0) + #define __Pyx_c_conj_float(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_float(z) (::std::abs(z)) + #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_float(z) ((z)==0) + #define __Pyx_c_conj_float(z) (conjf(z)) + #if 1 + #define __Pyx_c_abs_float(z) (cabsf(z)) + #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); + #endif +#endif + +/* Arithmetic.proto */ +#if CYTHON_CCOMPLEX + #define __Pyx_c_eq_double(a, b) ((a)==(b)) + #define __Pyx_c_sum_double(a, b) ((a)+(b)) + #define __Pyx_c_diff_double(a, b) ((a)-(b)) + #define __Pyx_c_prod_double(a, b) ((a)*(b)) + #define __Pyx_c_quot_double(a, b) ((a)/(b)) + #define __Pyx_c_neg_double(a) (-(a)) + #ifdef __cplusplus + #define __Pyx_c_is_zero_double(z) ((z)==(double)0) + #define __Pyx_c_conj_double(z) (::std::conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (::std::abs(z)) + #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) + #endif + #else + #define __Pyx_c_is_zero_double(z) ((z)==0) + #define __Pyx_c_conj_double(z) (conj(z)) + #if 1 + #define __Pyx_c_abs_double(z) (cabs(z)) + #define __Pyx_c_pow_double(a, b) (cpow(a, b)) + #endif + #endif +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); + #endif +#endif + +/* CIntFromPy.proto */ +static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); + +/* CIntToPy.proto */ +static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); + +/* CIntFromPy.proto */ +static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); + +/* FastTypeChecks.proto */ +#if CYTHON_COMPILING_IN_CPYTHON +#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); +static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); +#else +#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) +#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) +#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) +#endif +#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) + +/* CheckBinaryVersion.proto */ +static int __Pyx_check_binary_version(void); + +/* InitStrings.proto */ +static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); + + +/* Module declarations from 'cpython.buffer' */ + +/* Module declarations from 'libc.string' */ + +/* Module declarations from 'libc.stdio' */ + +/* Module declarations from '__builtin__' */ + +/* Module declarations from 'cpython.type' */ +static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; + +/* Module declarations from 'cpython' */ + +/* Module declarations from 'cpython.object' */ + +/* Module declarations from 'cpython.ref' */ + +/* Module declarations from 'cpython.mem' */ + +/* Module declarations from 'numpy' */ + +/* Module declarations from 'numpy' */ +static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; +static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; +static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; +static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; +static PyTypeObject *__pyx_ptype_5numpy_generic = 0; +static PyTypeObject *__pyx_ptype_5numpy_number = 0; +static PyTypeObject *__pyx_ptype_5numpy_integer = 0; +static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; +static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; +static PyTypeObject *__pyx_ptype_5numpy_floating = 0; +static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; +static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; +static PyTypeObject *__pyx_ptype_5numpy_character = 0; +static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; + +/* Module declarations from 'libcpp.string' */ + +/* Module declarations from 'wrapper' */ +static CYTHON_INLINE PyObject *__pyx_convert_PyObject_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyUnicode_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyStr_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyBytes_string_to_py_std__in_string(std::string const &); /*proto*/ +static CYTHON_INLINE PyObject *__pyx_convert_PyByteArray_string_to_py_std__in_string(std::string const &); /*proto*/ +static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_double_t = { "double_t", NULL, sizeof(__pyx_t_5numpy_double_t), { 0 }, 0, 'R', 0, 0 }; +#define __Pyx_MODULE_NAME "wrapper" +extern int __pyx_module_is_main_wrapper; +int __pyx_module_is_main_wrapper = 0; + +/* Implementation of 'wrapper' */ +static PyObject *__pyx_builtin_ImportError; +static const char __pyx_k_np[] = "np"; +static const char __pyx_k_main[] = "__main__"; +static const char __pyx_k_name[] = "__name__"; +static const char __pyx_k_test[] = "__test__"; +static const char __pyx_k_array[] = "array"; +static const char __pyx_k_flags[] = "flags"; +static const char __pyx_k_image[] = "image"; +static const char __pyx_k_numpy[] = "numpy"; +static const char __pyx_k_import[] = "__import__"; +static const char __pyx_k_wrapper[] = "wrapper"; +static const char __pyx_k_iteration[] = "iteration"; +static const char __pyx_k_verbosity[] = "verbosity"; +static const char __pyx_k_cy_add_cti[] = "cy_add_cti"; +static const char __pyx_k_ImportError[] = "ImportError"; +static const char __pyx_k_C_CONTIGUOUS[] = "C_CONTIGUOUS"; +static const char __pyx_k_cy_print_array[] = "cy_print_array"; +static const char __pyx_k_serial_express[] = "serial_express"; +static const char __pyx_k_serial_n_pumps[] = "serial_n_pumps"; +static const char __pyx_k_serial_roe_type[] = "serial_roe_type"; +static const char __pyx_k_check_contiguous[] = "check_contiguous"; +static const char __pyx_k_cy_print_version[] = "cy_print_version"; +static const char __pyx_k_parallel_express[] = "parallel_express"; +static const char __pyx_k_parallel_n_pumps[] = "parallel_n_pumps"; +static const char __pyx_k_serial_time_stop[] = "serial_time_stop"; +static const char __pyx_k_ascontiguousarray[] = "ascontiguousarray"; +static const char __pyx_k_cy_print_array_2D[] = "cy_print_array_2D"; +static const char __pyx_k_cy_version_arctic[] = "cy_version_arctic"; +static const char __pyx_k_parallel_roe_type[] = "parallel_roe_type"; +static const char __pyx_k_serial_n_traps_ic[] = "serial_n_traps_ic"; +static const char __pyx_k_serial_n_traps_sc[] = "serial_n_traps_sc"; +static const char __pyx_k_serial_time_start[] = "serial_time_start"; +static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; +static const char __pyx_k_parallel_time_stop[] = "parallel_time_stop"; +static const char __pyx_k_serial_dwell_times[] = "serial_dwell_times"; +static const char __pyx_k_serial_window_stop[] = "serial_window_stop"; +static const char __pyx_k_parallel_n_traps_ic[] = "parallel_n_traps_ic"; +static const char __pyx_k_parallel_n_traps_sc[] = "parallel_n_traps_sc"; +static const char __pyx_k_parallel_time_start[] = "parallel_time_start"; +static const char __pyx_k_serial_window_start[] = "serial_window_start"; +static const char __pyx_k_parallel_dwell_times[] = "parallel_dwell_times"; +static const char __pyx_k_parallel_window_stop[] = "parallel_window_stop"; +static const char __pyx_k_serial_n_traps_ic_co[] = "serial_n_traps_ic_co"; +static const char __pyx_k_serial_n_traps_sc_co[] = "serial_n_traps_sc_co"; +static const char __pyx_k_serial_window_offset[] = "serial_window_offset"; +static const char __pyx_k_parallel_window_start[] = "parallel_window_start"; +static const char __pyx_k_serial_overscan_start[] = "serial_overscan_start"; +static const char __pyx_k_serial_prescan_offset[] = "serial_prescan_offset"; +static const char __pyx_k_serial_trap_densities[] = "serial_trap_densities"; +static const char __pyx_k_parallel_n_traps_ic_co[] = "parallel_n_traps_ic_co"; +static const char __pyx_k_parallel_n_traps_sc_co[] = "parallel_n_traps_sc_co"; +static const char __pyx_k_parallel_window_offset[] = "parallel_window_offset"; +static const char __pyx_k_serial_prune_frequency[] = "serial_prune_frequency"; +static const char __pyx_k_parallel_overscan_start[] = "parallel_overscan_start"; +static const char __pyx_k_parallel_prescan_offset[] = "parallel_prescan_offset"; +static const char __pyx_k_parallel_trap_densities[] = "parallel_trap_densities"; +static const char __pyx_k_serial_full_well_depths[] = "serial_full_well_depths"; +static const char __pyx_k_serial_well_fill_powers[] = "serial_well_fill_powers"; +static const char __pyx_k_parallel_prune_frequency[] = "parallel_prune_frequency"; +static const char __pyx_k_serial_prune_n_electrons[] = "serial_prune_n_electrons"; +static const char __pyx_k_serial_trap_third_params[] = "serial_trap_third_params"; +static const char __pyx_k_serial_well_notch_depths[] = "serial_well_notch_depths"; +static const char __pyx_k_parallel_full_well_depths[] = "parallel_full_well_depths"; +static const char __pyx_k_parallel_well_fill_powers[] = "parallel_well_fill_powers"; +static const char __pyx_k_serial_trap_fourth_params[] = "serial_trap_fourth_params"; +static const char __pyx_k_parallel_prune_n_electrons[] = "parallel_prune_n_electrons"; +static const char __pyx_k_parallel_trap_third_params[] = "parallel_trap_third_params"; +static const char __pyx_k_parallel_well_notch_depths[] = "parallel_well_notch_depths"; +static const char __pyx_k_parallel_trap_fourth_params[] = "parallel_trap_fourth_params"; 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__pyx_v_serial_empty_traps_for_first_transfers; + int __pyx_v_serial_force_release_away_from_readout; + int __pyx_v_serial_use_integer_express_matrix; + int __pyx_v_serial_n_pumps; + int __pyx_v_serial_roe_type; + PyArrayObject *__pyx_v_serial_fraction_of_traps_per_phase = 0; + PyArrayObject *__pyx_v_serial_full_well_depths = 0; + PyArrayObject *__pyx_v_serial_well_notch_depths = 0; + PyArrayObject *__pyx_v_serial_well_fill_powers = 0; + PyArrayObject *__pyx_v_serial_trap_densities = 0; + PyArrayObject *__pyx_v_serial_trap_release_timescales = 0; + PyArrayObject *__pyx_v_serial_trap_third_params = 0; + PyArrayObject *__pyx_v_serial_trap_fourth_params = 0; + int __pyx_v_serial_n_traps_ic; + int __pyx_v_serial_n_traps_sc; + int __pyx_v_serial_n_traps_ic_co; + int __pyx_v_serial_n_traps_sc_co; + int __pyx_v_serial_express; + int __pyx_v_serial_window_offset; + int __pyx_v_serial_window_start; + int __pyx_v_serial_window_stop; + int __pyx_v_serial_time_start; + int __pyx_v_serial_time_stop; + PyArrayObject *__pyx_v_serial_prune_n_electrons = 0; + int __pyx_v_serial_prune_frequency; + int __pyx_v_verbosity; + int __pyx_v_iteration; + int __pyx_lineno = 0; + const char *__pyx_filename = NULL; + int __pyx_clineno = 0; + PyObject *__pyx_r = 0; + __Pyx_RefNannyDeclarations + __Pyx_RefNannySetupContext("cy_add_cti (wrapper)", 0); + { + static PyObject **__pyx_pyargnames[] = 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CYTHON_FALLTHROUGH; + case 52: values[51] = PyTuple_GET_ITEM(__pyx_args, 51); + CYTHON_FALLTHROUGH; + case 51: values[50] = PyTuple_GET_ITEM(__pyx_args, 50); + CYTHON_FALLTHROUGH; + case 50: values[49] = PyTuple_GET_ITEM(__pyx_args, 49); + CYTHON_FALLTHROUGH; + case 49: values[48] = PyTuple_GET_ITEM(__pyx_args, 48); + CYTHON_FALLTHROUGH; + case 48: values[47] = PyTuple_GET_ITEM(__pyx_args, 47); + CYTHON_FALLTHROUGH; + case 47: values[46] = PyTuple_GET_ITEM(__pyx_args, 46); + CYTHON_FALLTHROUGH; + case 46: values[45] = PyTuple_GET_ITEM(__pyx_args, 45); + CYTHON_FALLTHROUGH; + case 45: values[44] = PyTuple_GET_ITEM(__pyx_args, 44); + CYTHON_FALLTHROUGH; + case 44: values[43] = PyTuple_GET_ITEM(__pyx_args, 43); + CYTHON_FALLTHROUGH; + case 43: values[42] = PyTuple_GET_ITEM(__pyx_args, 42); + CYTHON_FALLTHROUGH; + case 42: values[41] = PyTuple_GET_ITEM(__pyx_args, 41); + CYTHON_FALLTHROUGH; + case 41: values[40] = PyTuple_GET_ITEM(__pyx_args, 40); + CYTHON_FALLTHROUGH; + case 40: values[39] = PyTuple_GET_ITEM(__pyx_args, 39); + CYTHON_FALLTHROUGH; + case 39: values[38] = PyTuple_GET_ITEM(__pyx_args, 38); + CYTHON_FALLTHROUGH; + case 38: values[37] = PyTuple_GET_ITEM(__pyx_args, 37); + CYTHON_FALLTHROUGH; + case 37: values[36] = PyTuple_GET_ITEM(__pyx_args, 36); + CYTHON_FALLTHROUGH; + case 36: values[35] = PyTuple_GET_ITEM(__pyx_args, 35); + CYTHON_FALLTHROUGH; + case 35: values[34] = PyTuple_GET_ITEM(__pyx_args, 34); + CYTHON_FALLTHROUGH; + case 34: values[33] = PyTuple_GET_ITEM(__pyx_args, 33); + CYTHON_FALLTHROUGH; + case 33: values[32] = PyTuple_GET_ITEM(__pyx_args, 32); + CYTHON_FALLTHROUGH; + case 32: values[31] = PyTuple_GET_ITEM(__pyx_args, 31); + CYTHON_FALLTHROUGH; + case 31: values[30] = PyTuple_GET_ITEM(__pyx_args, 30); + CYTHON_FALLTHROUGH; + case 30: values[29] = PyTuple_GET_ITEM(__pyx_args, 29); + CYTHON_FALLTHROUGH; + case 29: values[28] = PyTuple_GET_ITEM(__pyx_args, 28); + CYTHON_FALLTHROUGH; + case 28: values[27] = PyTuple_GET_ITEM(__pyx_args, 27); + CYTHON_FALLTHROUGH; + case 27: values[26] = PyTuple_GET_ITEM(__pyx_args, 26); + CYTHON_FALLTHROUGH; + case 26: values[25] = PyTuple_GET_ITEM(__pyx_args, 25); + CYTHON_FALLTHROUGH; + case 25: values[24] = PyTuple_GET_ITEM(__pyx_args, 24); + CYTHON_FALLTHROUGH; + case 24: values[23] = PyTuple_GET_ITEM(__pyx_args, 23); + CYTHON_FALLTHROUGH; + case 23: values[22] = PyTuple_GET_ITEM(__pyx_args, 22); + CYTHON_FALLTHROUGH; + case 22: values[21] = PyTuple_GET_ITEM(__pyx_args, 21); + CYTHON_FALLTHROUGH; + case 21: values[20] = PyTuple_GET_ITEM(__pyx_args, 20); + CYTHON_FALLTHROUGH; + case 20: values[19] = PyTuple_GET_ITEM(__pyx_args, 19); + CYTHON_FALLTHROUGH; + case 19: values[18] = PyTuple_GET_ITEM(__pyx_args, 18); + CYTHON_FALLTHROUGH; + case 18: values[17] = PyTuple_GET_ITEM(__pyx_args, 17); + CYTHON_FALLTHROUGH; + case 17: values[16] = PyTuple_GET_ITEM(__pyx_args, 16); + CYTHON_FALLTHROUGH; + case 16: values[15] = PyTuple_GET_ITEM(__pyx_args, 15); + 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(PyObject **) ((char *)obj + offset) : _PyObject_GetDictPtr(obj); +#else + dictptr = _PyObject_GetDictPtr(obj); +#endif + } + return (dictptr && *dictptr) ? __PYX_GET_DICT_VERSION(*dictptr) : 0; +} +static CYTHON_INLINE int __Pyx_object_dict_version_matches(PyObject* obj, PY_UINT64_T tp_dict_version, PY_UINT64_T obj_dict_version) { + PyObject *dict = Py_TYPE(obj)->tp_dict; + if (unlikely(!dict) || unlikely(tp_dict_version != __PYX_GET_DICT_VERSION(dict))) + return 0; + return obj_dict_version == __Pyx_get_object_dict_version(obj); +} +#endif + +/* GetModuleGlobalName */ +#if CYTHON_USE_DICT_VERSIONS +static PyObject *__Pyx__GetModuleGlobalName(PyObject *name, PY_UINT64_T *dict_version, PyObject **dict_cached_value) +#else +static CYTHON_INLINE PyObject *__Pyx__GetModuleGlobalName(PyObject *name) +#endif +{ + PyObject *result; +#if !CYTHON_AVOID_BORROWED_REFS +#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 + result = _PyDict_GetItem_KnownHash(__pyx_d, name, ((PyASCIIObject *) name)->hash); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } else if (unlikely(PyErr_Occurred())) { + return NULL; + } +#else + result = PyDict_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } +#endif +#else + result = PyObject_GetItem(__pyx_d, name); + __PYX_UPDATE_DICT_CACHE(__pyx_d, result, *dict_cached_value, *dict_version) + if (likely(result)) { + return __Pyx_NewRef(result); + } + PyErr_Clear(); +#endif + return __Pyx_GetBuiltinName(name); +} + +/* PyCFunctionFastCall */ +#if CYTHON_FAST_PYCCALL +static CYTHON_INLINE PyObject * __Pyx_PyCFunction_FastCall(PyObject *func_obj, PyObject **args, Py_ssize_t nargs) { + PyCFunctionObject *func = (PyCFunctionObject*)func_obj; + PyCFunction meth = PyCFunction_GET_FUNCTION(func); + PyObject *self = PyCFunction_GET_SELF(func); + int flags = PyCFunction_GET_FLAGS(func); + assert(PyCFunction_Check(func)); + assert(METH_FASTCALL == (flags & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))); + assert(nargs >= 0); + assert(nargs == 0 || args != NULL); + /* _PyCFunction_FastCallDict() must not be called with an exception set, + because it may clear it (directly or indirectly) and so the + caller loses its exception */ + assert(!PyErr_Occurred()); + if ((PY_VERSION_HEX < 0x030700A0) || unlikely(flags & METH_KEYWORDS)) { + return (*((__Pyx_PyCFunctionFastWithKeywords)(void*)meth)) (self, args, nargs, NULL); + } else { + return (*((__Pyx_PyCFunctionFast)(void*)meth)) (self, args, nargs); + } +} +#endif + +/* PyFunctionFastCall */ +#if CYTHON_FAST_PYCALL +static PyObject* __Pyx_PyFunction_FastCallNoKw(PyCodeObject *co, PyObject **args, Py_ssize_t na, + PyObject *globals) { + PyFrameObject *f; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject **fastlocals; + Py_ssize_t i; + PyObject *result; + assert(globals != NULL); + /* XXX Perhaps we should create a specialized + PyFrame_New() that doesn't take locals, but does + take builtins without sanity checking them. + */ + assert(tstate != NULL); + f = PyFrame_New(tstate, co, globals, NULL); + if (f == NULL) { + return NULL; + } + fastlocals = __Pyx_PyFrame_GetLocalsplus(f); + for (i = 0; i < na; i++) { + Py_INCREF(*args); + fastlocals[i] = *args++; + } + result = PyEval_EvalFrameEx(f,0); + ++tstate->recursion_depth; + Py_DECREF(f); + --tstate->recursion_depth; + return result; +} +#if 1 || PY_VERSION_HEX < 0x030600B1 +static PyObject *__Pyx_PyFunction_FastCallDict(PyObject *func, PyObject **args, Py_ssize_t nargs, PyObject *kwargs) { + PyCodeObject *co = (PyCodeObject *)PyFunction_GET_CODE(func); + PyObject *globals = PyFunction_GET_GLOBALS(func); + PyObject *argdefs = PyFunction_GET_DEFAULTS(func); + PyObject *closure; +#if PY_MAJOR_VERSION >= 3 + PyObject *kwdefs; +#endif + PyObject *kwtuple, **k; + PyObject **d; + Py_ssize_t nd; + Py_ssize_t nk; + PyObject *result; + assert(kwargs == NULL || PyDict_Check(kwargs)); + nk = kwargs ? PyDict_Size(kwargs) : 0; + if (Py_EnterRecursiveCall((char*)" while calling a Python object")) { + return NULL; + } + if ( +#if PY_MAJOR_VERSION >= 3 + co->co_kwonlyargcount == 0 && +#endif + likely(kwargs == NULL || nk == 0) && + co->co_flags == (CO_OPTIMIZED | CO_NEWLOCALS | CO_NOFREE)) { + if (argdefs == NULL && co->co_argcount == nargs) { + result = __Pyx_PyFunction_FastCallNoKw(co, args, nargs, globals); + goto done; + } + else if (nargs == 0 && argdefs != NULL + && co->co_argcount == Py_SIZE(argdefs)) { + /* function called with no arguments, but all parameters have + a default value: use default values as arguments .*/ + args = &PyTuple_GET_ITEM(argdefs, 0); + result =__Pyx_PyFunction_FastCallNoKw(co, args, Py_SIZE(argdefs), globals); + goto done; + } + } + if (kwargs != NULL) { + Py_ssize_t pos, i; + kwtuple = PyTuple_New(2 * nk); + if (kwtuple == NULL) { + result = NULL; + goto done; + } + k = &PyTuple_GET_ITEM(kwtuple, 0); + pos = i = 0; + while (PyDict_Next(kwargs, &pos, &k[i], &k[i+1])) { + Py_INCREF(k[i]); + Py_INCREF(k[i+1]); + i += 2; + } + nk = i / 2; + } + else { + kwtuple = NULL; + k = NULL; + } + closure = PyFunction_GET_CLOSURE(func); +#if PY_MAJOR_VERSION >= 3 + kwdefs = PyFunction_GET_KW_DEFAULTS(func); +#endif + if (argdefs != NULL) { + d = &PyTuple_GET_ITEM(argdefs, 0); + nd = Py_SIZE(argdefs); + } + else { + d = NULL; + nd = 0; + } +#if PY_MAJOR_VERSION >= 3 + result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, kwdefs, closure); +#else + result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, + args, (int)nargs, + k, (int)nk, + d, (int)nd, closure); +#endif + Py_XDECREF(kwtuple); +done: + Py_LeaveRecursiveCall(); + return result; +} +#endif +#endif + +/* PyObjectCall */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { + PyObject *result; + ternaryfunc call = Py_TYPE(func)->tp_call; + if (unlikely(!call)) + return PyObject_Call(func, arg, kw); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = (*call)(func, arg, kw); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCall2Args */ +static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { + PyObject *args, *result = NULL; + #if CYTHON_FAST_PYCALL + if (PyFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyFunction_FastCall(function, args, 2); + } + #endif + #if CYTHON_FAST_PYCCALL + if (__Pyx_PyFastCFunction_Check(function)) { + PyObject *args[2] = {arg1, arg2}; + return __Pyx_PyCFunction_FastCall(function, args, 2); + } + #endif + args = PyTuple_New(2); + if (unlikely(!args)) goto done; + Py_INCREF(arg1); + PyTuple_SET_ITEM(args, 0, arg1); + Py_INCREF(arg2); + PyTuple_SET_ITEM(args, 1, arg2); + Py_INCREF(function); + result = __Pyx_PyObject_Call(function, args, NULL); + Py_DECREF(args); + Py_DECREF(function); +done: + return result; +} + +/* PyObjectCallMethO */ +#if CYTHON_COMPILING_IN_CPYTHON +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { + PyObject *self, *result; + PyCFunction cfunc; + cfunc = PyCFunction_GET_FUNCTION(func); + self = PyCFunction_GET_SELF(func); + if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) + return NULL; + result = cfunc(self, arg); + Py_LeaveRecursiveCall(); + if (unlikely(!result) && unlikely(!PyErr_Occurred())) { + PyErr_SetString( + PyExc_SystemError, + "NULL result without error in PyObject_Call"); + } + return result; +} +#endif + +/* PyObjectCallOneArg */ +#if CYTHON_COMPILING_IN_CPYTHON +static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_New(1); + if (unlikely(!args)) return NULL; + Py_INCREF(arg); + PyTuple_SET_ITEM(args, 0, arg); + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { +#if CYTHON_FAST_PYCALL + if (PyFunction_Check(func)) { + return __Pyx_PyFunction_FastCall(func, &arg, 1); + } +#endif + if (likely(PyCFunction_Check(func))) { + if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { + return __Pyx_PyObject_CallMethO(func, arg); +#if CYTHON_FAST_PYCCALL + } else if (__Pyx_PyFastCFunction_Check(func)) { + return __Pyx_PyCFunction_FastCall(func, &arg, 1); +#endif + } + } + return __Pyx__PyObject_CallOneArg(func, arg); +} +#else +static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { + PyObject *result; + PyObject *args = PyTuple_Pack(1, arg); + if (unlikely(!args)) return NULL; + result = __Pyx_PyObject_Call(func, args, NULL); + Py_DECREF(args); + return result; +} +#endif + +/* ArgTypeTest */ +static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) +{ + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + else if (exact) { + #if PY_MAJOR_VERSION == 2 + if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; + #endif + } + else { + if (likely(__Pyx_TypeCheck(obj, type))) return 1; + } + PyErr_Format(PyExc_TypeError, + "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", + name, type->tp_name, Py_TYPE(obj)->tp_name); + return 0; +} + +/* IsLittleEndian */ +static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) +{ + union { + uint32_t u32; + uint8_t u8[4]; + } S; + S.u32 = 0x01020304; + return S.u8[0] == 4; +} + +/* BufferFormatCheck */ +static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, + __Pyx_BufFmt_StackElem* stack, + __Pyx_TypeInfo* type) { + stack[0].field = &ctx->root; + stack[0].parent_offset = 0; + ctx->root.type = type; + ctx->root.name = "buffer dtype"; + ctx->root.offset = 0; + ctx->head = stack; + ctx->head->field = &ctx->root; + ctx->fmt_offset = 0; + ctx->head->parent_offset = 0; + ctx->new_packmode = '@'; + ctx->enc_packmode = '@'; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->is_complex = 0; + ctx->is_valid_array = 0; + ctx->struct_alignment = 0; + while (type->typegroup == 'S') { + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = 0; + type = type->fields->type; + } +} +static int __Pyx_BufFmt_ParseNumber(const char** ts) { + int count; + const char* t = *ts; + if (*t < '0' || *t > '9') { + return -1; + } else { + count = *t++ - '0'; + while (*t >= '0' && *t <= '9') { + count *= 10; + count += *t++ - '0'; + } + } + *ts = t; + return count; +} +static int __Pyx_BufFmt_ExpectNumber(const char **ts) { + int number = __Pyx_BufFmt_ParseNumber(ts); + if (number == -1) + PyErr_Format(PyExc_ValueError,\ + "Does not understand character buffer dtype format string ('%c')", **ts); + return number; +} +static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { + PyErr_Format(PyExc_ValueError, + "Unexpected format string character: '%c'", ch); +} +static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { + switch (ch) { + case '?': return "'bool'"; + case 'c': return "'char'"; + case 'b': return "'signed char'"; + case 'B': return "'unsigned char'"; + case 'h': return "'short'"; + case 'H': return "'unsigned short'"; + case 'i': return "'int'"; + case 'I': return "'unsigned int'"; + case 'l': return "'long'"; + case 'L': return "'unsigned long'"; + case 'q': return "'long long'"; + case 'Q': return "'unsigned long long'"; + case 'f': return (is_complex ? "'complex float'" : "'float'"); + case 'd': return (is_complex ? "'complex double'" : "'double'"); + case 'g': return (is_complex ? "'complex long double'" : "'long double'"); + case 'T': return "a struct"; + case 'O': return "Python object"; + case 'P': return "a pointer"; + case 's': case 'p': return "a string"; + case 0: return "end"; + default: return "unparseable format string"; + } +} +static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return 2; + case 'i': case 'I': case 'l': case 'L': return 4; + case 'q': case 'Q': return 8; + case 'f': return (is_complex ? 8 : 4); + case 'd': return (is_complex ? 16 : 8); + case 'g': { + PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); + return 0; + } + case 'O': case 'P': return sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(short); + case 'i': case 'I': return sizeof(int); + case 'l': case 'L': return sizeof(long); + #ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(PY_LONG_LONG); + #endif + case 'f': return sizeof(float) * (is_complex ? 2 : 1); + case 'd': return sizeof(double) * (is_complex ? 2 : 1); + case 'g': return sizeof(long double) * (is_complex ? 2 : 1); + case 'O': case 'P': return sizeof(void*); + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +typedef struct { char c; short x; } __Pyx_st_short; +typedef struct { char c; int x; } __Pyx_st_int; +typedef struct { char c; long x; } __Pyx_st_long; +typedef struct { char c; float x; } __Pyx_st_float; +typedef struct { char c; double x; } __Pyx_st_double; +typedef struct { char c; long double x; } __Pyx_st_longdouble; +typedef struct { char c; void *x; } __Pyx_st_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_st_float) - sizeof(float); + case 'd': return sizeof(__Pyx_st_double) - sizeof(double); + case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +/* These are for computing the padding at the end of the struct to align + on the first member of the struct. This will probably the same as above, + but we don't have any guarantees. + */ +typedef struct { short x; char c; } __Pyx_pad_short; +typedef struct { int x; char c; } __Pyx_pad_int; +typedef struct { long x; char c; } __Pyx_pad_long; +typedef struct { float x; char c; } __Pyx_pad_float; +typedef struct { double x; char c; } __Pyx_pad_double; +typedef struct { long double x; char c; } __Pyx_pad_longdouble; +typedef struct { void *x; char c; } __Pyx_pad_void_p; +#ifdef HAVE_LONG_LONG +typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; +#endif +static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { + switch (ch) { + case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; + case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); + case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); + case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); +#ifdef HAVE_LONG_LONG + case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); +#endif + case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); + case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); + case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); + case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); + default: + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } +} +static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { + switch (ch) { + case 'c': + return 'H'; + case 'b': case 'h': case 'i': + case 'l': case 'q': case 's': case 'p': + return 'I'; + case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': + return 'U'; + case 'f': case 'd': case 'g': + return (is_complex ? 'C' : 'R'); + case 'O': + return 'O'; + case 'P': + return 'P'; + default: { + __Pyx_BufFmt_RaiseUnexpectedChar(ch); + return 0; + } + } +} +static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { + if (ctx->head == NULL || ctx->head->field == &ctx->root) { + const char* expected; + const char* quote; + if (ctx->head == NULL) { + expected = "end"; + quote = ""; + } else { + expected = ctx->head->field->type->name; + quote = "'"; + } + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected %s%s%s but got %s", + quote, expected, quote, + __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); + } else { + __Pyx_StructField* field = ctx->head->field; + __Pyx_StructField* parent = (ctx->head - 1)->field; + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", + field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), + parent->type->name, field->name); + } +} +static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { + char group; + size_t size, offset, arraysize = 1; + if (ctx->enc_type == 0) return 0; + if (ctx->head->field->type->arraysize[0]) { + int i, ndim = 0; + if (ctx->enc_type == 's' || ctx->enc_type == 'p') { + ctx->is_valid_array = ctx->head->field->type->ndim == 1; + ndim = 1; + if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { + PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %zu", + ctx->head->field->type->arraysize[0], ctx->enc_count); + return -1; + } + } + if (!ctx->is_valid_array) { + PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", + ctx->head->field->type->ndim, ndim); + return -1; + } + for (i = 0; i < ctx->head->field->type->ndim; i++) { + arraysize *= ctx->head->field->type->arraysize[i]; + } + ctx->is_valid_array = 0; + ctx->enc_count = 1; + } + group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); + do { + __Pyx_StructField* field = ctx->head->field; + __Pyx_TypeInfo* type = field->type; + if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { + size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); + } else { + size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); + } + if (ctx->enc_packmode == '@') { + size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); + size_t align_mod_offset; + if (align_at == 0) return -1; + align_mod_offset = ctx->fmt_offset % align_at; + if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; + if (ctx->struct_alignment == 0) + ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, + ctx->is_complex); + } + if (type->size != size || type->typegroup != group) { + if (type->typegroup == 'C' && type->fields != NULL) { + size_t parent_offset = ctx->head->parent_offset + field->offset; + ++ctx->head; + ctx->head->field = type->fields; + ctx->head->parent_offset = parent_offset; + continue; + } + if ((type->typegroup == 'H' || group == 'H') && type->size == size) { + } else { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + } + offset = ctx->head->parent_offset + field->offset; + if (ctx->fmt_offset != offset) { + PyErr_Format(PyExc_ValueError, + "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", + (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); + return -1; + } + ctx->fmt_offset += size; + if (arraysize) + ctx->fmt_offset += (arraysize - 1) * size; + --ctx->enc_count; + while (1) { + if (field == &ctx->root) { + ctx->head = NULL; + if (ctx->enc_count != 0) { + __Pyx_BufFmt_RaiseExpected(ctx); + return -1; + } + break; + } + ctx->head->field = ++field; + if (field->type == NULL) { + --ctx->head; + field = ctx->head->field; + continue; + } else if (field->type->typegroup == 'S') { + size_t parent_offset = ctx->head->parent_offset + field->offset; + if (field->type->fields->type == NULL) continue; + field = field->type->fields; + ++ctx->head; + ctx->head->field = field; + ctx->head->parent_offset = parent_offset; + break; + } else { + break; + } + } + } while (ctx->enc_count); + ctx->enc_type = 0; + ctx->is_complex = 0; + return 0; +} +static PyObject * +__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) +{ + const char *ts = *tsp; + int i = 0, number, ndim; + ++ts; + if (ctx->new_count != 1) { + PyErr_SetString(PyExc_ValueError, + "Cannot handle repeated arrays in format string"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ndim = ctx->head->field->type->ndim; + while (*ts && *ts != ')') { + switch (*ts) { + case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; + default: break; + } + number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) + return PyErr_Format(PyExc_ValueError, + "Expected a dimension of size %zu, got %d", + ctx->head->field->type->arraysize[i], number); + if (*ts != ',' && *ts != ')') + return PyErr_Format(PyExc_ValueError, + "Expected a comma in format string, got '%c'", *ts); + if (*ts == ',') ts++; + i++; + } + if (i != ndim) + return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", + ctx->head->field->type->ndim, i); + if (!*ts) { + PyErr_SetString(PyExc_ValueError, + "Unexpected end of format string, expected ')'"); + return NULL; + } + ctx->is_valid_array = 1; + ctx->new_count = 1; + *tsp = ++ts; + return Py_None; +} +static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { + int got_Z = 0; + while (1) { + switch(*ts) { + case 0: + if (ctx->enc_type != 0 && ctx->head == NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + if (ctx->head != NULL) { + __Pyx_BufFmt_RaiseExpected(ctx); + return NULL; + } + return ts; + case ' ': + case '\r': + case '\n': + ++ts; + break; + case '<': + if (!__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '>': + case '!': + if (__Pyx_Is_Little_Endian()) { + PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); + return NULL; + } + ctx->new_packmode = '='; + ++ts; + break; + case '=': + case '@': + case '^': + ctx->new_packmode = *ts++; + break; + case 'T': + { + const char* ts_after_sub; + size_t i, struct_count = ctx->new_count; + size_t struct_alignment = ctx->struct_alignment; + ctx->new_count = 1; + ++ts; + if (*ts != '{') { + PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); + return NULL; + } + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + ctx->enc_count = 0; + ctx->struct_alignment = 0; + ++ts; + ts_after_sub = ts; + for (i = 0; i != struct_count; ++i) { + ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); + if (!ts_after_sub) return NULL; + } + ts = ts_after_sub; + if (struct_alignment) ctx->struct_alignment = struct_alignment; + } + break; + case '}': + { + size_t alignment = ctx->struct_alignment; + ++ts; + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_type = 0; + if (alignment && ctx->fmt_offset % alignment) { + ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); + } + } + return ts; + case 'x': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->fmt_offset += ctx->new_count; + ctx->new_count = 1; + ctx->enc_count = 0; + ctx->enc_type = 0; + ctx->enc_packmode = ctx->new_packmode; + ++ts; + break; + case 'Z': + got_Z = 1; + ++ts; + if (*ts != 'f' && *ts != 'd' && *ts != 'g') { + __Pyx_BufFmt_RaiseUnexpectedChar('Z'); + return NULL; + } + CYTHON_FALLTHROUGH; + case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': + case 'l': case 'L': case 'q': case 'Q': + case 'f': case 'd': case 'g': + case 'O': case 'p': + if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && + (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { + ctx->enc_count += ctx->new_count; + ctx->new_count = 1; + got_Z = 0; + ++ts; + break; + } + CYTHON_FALLTHROUGH; + case 's': + if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; + ctx->enc_count = ctx->new_count; + ctx->enc_packmode = ctx->new_packmode; + ctx->enc_type = *ts; + ctx->is_complex = got_Z; + ++ts; + ctx->new_count = 1; + got_Z = 0; + break; + case ':': + ++ts; + while(*ts != ':') ++ts; + ++ts; + break; + case '(': + if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; + break; + default: + { + int number = __Pyx_BufFmt_ExpectNumber(&ts); + if (number == -1) return NULL; + ctx->new_count = (size_t)number; + } + } + } +} + +/* BufferGetAndValidate */ + static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { + if (unlikely(info->buf == NULL)) return; + if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; + __Pyx_ReleaseBuffer(info); +} +static void __Pyx_ZeroBuffer(Py_buffer* buf) { + buf->buf = NULL; + buf->obj = NULL; + buf->strides = __Pyx_zeros; + buf->shape = __Pyx_zeros; + buf->suboffsets = __Pyx_minusones; +} +static int __Pyx__GetBufferAndValidate( + Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, + int nd, int cast, __Pyx_BufFmt_StackElem* stack) +{ + buf->buf = NULL; + if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { + __Pyx_ZeroBuffer(buf); + return -1; + } + if (unlikely(buf->ndim != nd)) { + PyErr_Format(PyExc_ValueError, + "Buffer has wrong number of dimensions (expected %d, got %d)", + nd, buf->ndim); + goto fail; + } + if (!cast) { + __Pyx_BufFmt_Context ctx; + __Pyx_BufFmt_Init(&ctx, stack, dtype); + if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; + } + if (unlikely((size_t)buf->itemsize != dtype->size)) { + PyErr_Format(PyExc_ValueError, + "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", + buf->itemsize, (buf->itemsize > 1) ? "s" : "", + dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); + goto fail; + } + if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; + return 0; +fail:; + __Pyx_SafeReleaseBuffer(buf); + return -1; +} + +/* ExtTypeTest */ + static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { + if (unlikely(!type)) { + PyErr_SetString(PyExc_SystemError, "Missing type object"); + return 0; + } + if (likely(__Pyx_TypeCheck(obj, type))) + return 1; + PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", + Py_TYPE(obj)->tp_name, type->tp_name); + return 0; +} + +/* BufferFallbackError */ + static void __Pyx_RaiseBufferFallbackError(void) { + PyErr_SetString(PyExc_ValueError, + "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); +} + +/* BufferIndexError */ + static void __Pyx_RaiseBufferIndexError(int axis) { + PyErr_Format(PyExc_IndexError, + "Out of bounds on buffer access (axis %d)", axis); +} + +/* PyErrFetchRestore */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + tmp_type = tstate->curexc_type; + tmp_value = tstate->curexc_value; + tmp_tb = tstate->curexc_traceback; + tstate->curexc_type = type; + tstate->curexc_value = value; + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + *type = tstate->curexc_type; + *value = tstate->curexc_value; + *tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +} +#endif + +/* RaiseArgTupleInvalid */ + static void __Pyx_RaiseArgtupleInvalid( + const char* func_name, + int exact, + Py_ssize_t num_min, + Py_ssize_t num_max, + Py_ssize_t num_found) +{ + Py_ssize_t num_expected; + const char *more_or_less; + if (num_found < num_min) { + num_expected = num_min; + more_or_less = "at least"; + } else { + num_expected = num_max; + more_or_less = "at most"; + } + if (exact) { + more_or_less = "exactly"; + } + PyErr_Format(PyExc_TypeError, + "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", + func_name, more_or_less, num_expected, + (num_expected == 1) ? "" : "s", num_found); +} + +/* RaiseDoubleKeywords */ + static void __Pyx_RaiseDoubleKeywordsError( + const char* func_name, + PyObject* kw_name) +{ + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION >= 3 + "%s() got multiple values for keyword argument '%U'", func_name, kw_name); + #else + "%s() got multiple values for keyword argument '%s'", func_name, + PyString_AsString(kw_name)); + #endif +} + +/* ParseKeywords */ + static int __Pyx_ParseOptionalKeywords( + PyObject *kwds, + PyObject **argnames[], + PyObject *kwds2, + PyObject *values[], + Py_ssize_t num_pos_args, + const char* function_name) +{ + PyObject *key = 0, *value = 0; + Py_ssize_t pos = 0; + PyObject*** name; + PyObject*** first_kw_arg = argnames + num_pos_args; + while (PyDict_Next(kwds, &pos, &key, &value)) { + name = first_kw_arg; + while (*name && (**name != key)) name++; + if (*name) { + values[name-argnames] = value; + continue; + } + name = first_kw_arg; + #if PY_MAJOR_VERSION < 3 + if (likely(PyString_Check(key))) { + while (*name) { + if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) + && _PyString_Eq(**name, key)) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + if ((**argname == key) || ( + (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) + && _PyString_Eq(**argname, key))) { + goto arg_passed_twice; + } + argname++; + } + } + } else + #endif + if (likely(PyUnicode_Check(key))) { + while (*name) { + int cmp = (**name == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**name, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) { + values[name-argnames] = value; + break; + } + name++; + } + if (*name) continue; + else { + PyObject*** argname = argnames; + while (argname != first_kw_arg) { + int cmp = (**argname == key) ? 0 : + #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 + (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : + #endif + PyUnicode_Compare(**argname, key); + if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; + if (cmp == 0) goto arg_passed_twice; + argname++; + } + } + } else + goto invalid_keyword_type; + if (kwds2) { + if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; + } else { + goto invalid_keyword; + } + } + return 0; +arg_passed_twice: + __Pyx_RaiseDoubleKeywordsError(function_name, key); + goto bad; +invalid_keyword_type: + PyErr_Format(PyExc_TypeError, + "%.200s() keywords must be strings", function_name); + goto bad; +invalid_keyword: + PyErr_Format(PyExc_TypeError, + #if PY_MAJOR_VERSION < 3 + "%.200s() got an unexpected keyword argument '%.200s'", + function_name, PyString_AsString(key)); + #else + "%s() got an unexpected keyword argument '%U'", + function_name, key); + #endif +bad: + return -1; +} + +/* GetTopmostException */ + #if CYTHON_USE_EXC_INFO_STACK +static _PyErr_StackItem * +__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) +{ + _PyErr_StackItem *exc_info = tstate->exc_info; + while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && + exc_info->previous_item != NULL) + { + exc_info = exc_info->previous_item; + } + return exc_info; +} +#endif + +/* SaveResetException */ + #if CYTHON_FAST_THREAD_STATE +static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); + *type = exc_info->exc_type; + *value = exc_info->exc_value; + *tb = exc_info->exc_traceback; + #else + *type = tstate->exc_type; + *value = tstate->exc_value; + *tb = tstate->exc_traceback; + #endif + Py_XINCREF(*type); + Py_XINCREF(*value); + Py_XINCREF(*tb); +} +static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { + PyObject *tmp_type, *tmp_value, *tmp_tb; + #if CYTHON_USE_EXC_INFO_STACK + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = type; + exc_info->exc_value = value; + exc_info->exc_traceback = tb; + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = type; + tstate->exc_value = value; + tstate->exc_traceback = tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +} +#endif + +/* PyErrExceptionMatches */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; icurexc_type; + if (exc_type == err) return 1; + if (unlikely(!exc_type)) return 0; + if (unlikely(PyTuple_Check(err))) + return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); + return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); +} +#endif + +/* GetException */ + #if CYTHON_FAST_THREAD_STATE +static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) +#else +static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) +#endif +{ + PyObject *local_type, *local_value, *local_tb; +#if CYTHON_FAST_THREAD_STATE + PyObject *tmp_type, *tmp_value, *tmp_tb; + local_type = tstate->curexc_type; + local_value = tstate->curexc_value; + local_tb = tstate->curexc_traceback; + tstate->curexc_type = 0; + tstate->curexc_value = 0; + tstate->curexc_traceback = 0; +#else + PyErr_Fetch(&local_type, &local_value, &local_tb); +#endif + PyErr_NormalizeException(&local_type, &local_value, &local_tb); +#if CYTHON_FAST_THREAD_STATE + if (unlikely(tstate->curexc_type)) +#else + if (unlikely(PyErr_Occurred())) +#endif + goto bad; + #if PY_MAJOR_VERSION >= 3 + if (local_tb) { + if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) + goto bad; + } + #endif + Py_XINCREF(local_tb); + Py_XINCREF(local_type); + Py_XINCREF(local_value); + *type = local_type; + *value = local_value; + *tb = local_tb; +#if CYTHON_FAST_THREAD_STATE + #if CYTHON_USE_EXC_INFO_STACK + { + _PyErr_StackItem *exc_info = tstate->exc_info; + tmp_type = exc_info->exc_type; + tmp_value = exc_info->exc_value; + tmp_tb = exc_info->exc_traceback; + exc_info->exc_type = local_type; + exc_info->exc_value = local_value; + exc_info->exc_traceback = local_tb; + } + #else + tmp_type = tstate->exc_type; + tmp_value = tstate->exc_value; + tmp_tb = tstate->exc_traceback; + tstate->exc_type = local_type; + tstate->exc_value = local_value; + tstate->exc_traceback = local_tb; + #endif + Py_XDECREF(tmp_type); + Py_XDECREF(tmp_value); + Py_XDECREF(tmp_tb); +#else + PyErr_SetExcInfo(local_type, local_value, local_tb); +#endif + return 0; +bad: + *type = 0; + *value = 0; + *tb = 0; + Py_XDECREF(local_type); + Py_XDECREF(local_value); + Py_XDECREF(local_tb); + return -1; +} + +/* RaiseException */ + #if PY_MAJOR_VERSION < 3 +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, + CYTHON_UNUSED PyObject *cause) { + __Pyx_PyThreadState_declare + Py_XINCREF(type); + if (!value || value == Py_None) + value = NULL; + else + Py_INCREF(value); + if (!tb || tb == Py_None) + tb = NULL; + else { + Py_INCREF(tb); + if (!PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto raise_error; + } + } + if (PyType_Check(type)) { +#if CYTHON_COMPILING_IN_PYPY + if (!value) { + Py_INCREF(Py_None); + value = Py_None; + } +#endif + PyErr_NormalizeException(&type, &value, &tb); + } else { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto raise_error; + } + value = type; + type = (PyObject*) Py_TYPE(type); + Py_INCREF(type); + if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto raise_error; + } + } + __Pyx_PyThreadState_assign + __Pyx_ErrRestore(type, value, tb); + return; +raise_error: + Py_XDECREF(value); + Py_XDECREF(type); + Py_XDECREF(tb); + return; +} +#else +static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { + PyObject* owned_instance = NULL; + if (tb == Py_None) { + tb = 0; + } else if (tb && !PyTraceBack_Check(tb)) { + PyErr_SetString(PyExc_TypeError, + "raise: arg 3 must be a traceback or None"); + goto bad; + } + if (value == Py_None) + value = 0; + if (PyExceptionInstance_Check(type)) { + if (value) { + PyErr_SetString(PyExc_TypeError, + "instance exception may not have a separate value"); + goto bad; + } + value = type; + type = (PyObject*) Py_TYPE(value); + } else if (PyExceptionClass_Check(type)) { + PyObject *instance_class = NULL; + if (value && PyExceptionInstance_Check(value)) { + instance_class = (PyObject*) Py_TYPE(value); + if (instance_class != type) { + int is_subclass = PyObject_IsSubclass(instance_class, type); + if (!is_subclass) { + instance_class = NULL; + } else if (unlikely(is_subclass == -1)) { + goto bad; + } else { + type = instance_class; + } + } + } + if (!instance_class) { + PyObject *args; + if (!value) + args = PyTuple_New(0); + else if (PyTuple_Check(value)) { + Py_INCREF(value); + args = value; + } else + args = PyTuple_Pack(1, value); + if (!args) + goto bad; + owned_instance = PyObject_Call(type, args, NULL); + Py_DECREF(args); + if (!owned_instance) + goto bad; + value = owned_instance; + if (!PyExceptionInstance_Check(value)) { + PyErr_Format(PyExc_TypeError, + "calling %R should have returned an instance of " + "BaseException, not %R", + type, Py_TYPE(value)); + goto bad; + } + } + } else { + PyErr_SetString(PyExc_TypeError, + "raise: exception class must be a subclass of BaseException"); + goto bad; + } + if (cause) { + PyObject *fixed_cause; + if (cause == Py_None) { + fixed_cause = NULL; + } else if (PyExceptionClass_Check(cause)) { + fixed_cause = PyObject_CallObject(cause, NULL); + if (fixed_cause == NULL) + goto bad; + } else if (PyExceptionInstance_Check(cause)) { + fixed_cause = cause; + Py_INCREF(fixed_cause); + } else { + PyErr_SetString(PyExc_TypeError, + "exception causes must derive from " + "BaseException"); + goto bad; + } + PyException_SetCause(value, fixed_cause); + } + PyErr_SetObject(type, value); + if (tb) { +#if CYTHON_COMPILING_IN_PYPY + PyObject *tmp_type, *tmp_value, *tmp_tb; + PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); + Py_INCREF(tb); + PyErr_Restore(tmp_type, tmp_value, tb); + Py_XDECREF(tmp_tb); +#else + PyThreadState *tstate = __Pyx_PyThreadState_Current; + PyObject* tmp_tb = tstate->curexc_traceback; + if (tb != tmp_tb) { + Py_INCREF(tb); + tstate->curexc_traceback = tb; + Py_XDECREF(tmp_tb); + } +#endif + } +bad: + Py_XDECREF(owned_instance); + return; +} +#endif + +/* TypeImport */ + #ifndef __PYX_HAVE_RT_ImportType +#define __PYX_HAVE_RT_ImportType +static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, + size_t size, enum __Pyx_ImportType_CheckSize check_size) +{ + PyObject *result = 0; + char warning[200]; + Py_ssize_t basicsize; +#ifdef Py_LIMITED_API + PyObject *py_basicsize; +#endif + result = PyObject_GetAttrString(module, class_name); + if (!result) + goto bad; + if (!PyType_Check(result)) { + PyErr_Format(PyExc_TypeError, + "%.200s.%.200s is not a type object", + module_name, class_name); + goto bad; + } +#ifndef Py_LIMITED_API + basicsize = ((PyTypeObject *)result)->tp_basicsize; +#else + py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); + if (!py_basicsize) + goto bad; + basicsize = PyLong_AsSsize_t(py_basicsize); + Py_DECREF(py_basicsize); + py_basicsize = 0; + if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) + goto bad; +#endif + if ((size_t)basicsize < size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { + PyErr_Format(PyExc_ValueError, + "%.200s.%.200s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + goto bad; + } + else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { + PyOS_snprintf(warning, sizeof(warning), + "%s.%s size changed, may indicate binary incompatibility. " + "Expected %zd from C header, got %zd from PyObject", + module_name, class_name, size, basicsize); + if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; + } + return (PyTypeObject *)result; +bad: + Py_XDECREF(result); + return NULL; +} +#endif + +/* Import */ + static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { + PyObject *empty_list = 0; + PyObject *module = 0; + PyObject *global_dict = 0; + PyObject *empty_dict = 0; + PyObject *list; + #if PY_MAJOR_VERSION < 3 + PyObject *py_import; + py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); + if (!py_import) + goto bad; + #endif + if (from_list) + list = from_list; + else { + empty_list = PyList_New(0); + if (!empty_list) + goto bad; + list = empty_list; + } + global_dict = PyModule_GetDict(__pyx_m); + if (!global_dict) + goto bad; + empty_dict = PyDict_New(); + if (!empty_dict) + goto bad; + { + #if PY_MAJOR_VERSION >= 3 + if (level == -1) { + if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, 1); + if (!module) { + if (!PyErr_ExceptionMatches(PyExc_ImportError)) + goto bad; + PyErr_Clear(); + } + } + level = 0; + } + #endif + if (!module) { + #if PY_MAJOR_VERSION < 3 + PyObject *py_level = PyInt_FromLong(level); + if (!py_level) + goto bad; + module = PyObject_CallFunctionObjArgs(py_import, + name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); + Py_DECREF(py_level); + #else + module = PyImport_ImportModuleLevelObject( + name, global_dict, empty_dict, list, level); + #endif + } + } +bad: + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_import); + #endif + Py_XDECREF(empty_list); + Py_XDECREF(empty_dict); + return module; +} + +/* CLineInTraceback */ + #ifndef CYTHON_CLINE_IN_TRACEBACK +static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { + PyObject *use_cline; + PyObject *ptype, *pvalue, *ptraceback; +#if CYTHON_COMPILING_IN_CPYTHON + PyObject **cython_runtime_dict; +#endif + if (unlikely(!__pyx_cython_runtime)) { + return c_line; + } + __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); +#if CYTHON_COMPILING_IN_CPYTHON + cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); + if (likely(cython_runtime_dict)) { + __PYX_PY_DICT_LOOKUP_IF_MODIFIED( + use_cline, *cython_runtime_dict, + __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) + } else +#endif + { + PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); + if (use_cline_obj) { + use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; + Py_DECREF(use_cline_obj); + } else { + PyErr_Clear(); + use_cline = NULL; + } + } + if (!use_cline) { + c_line = 0; + (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); + } + else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { + c_line = 0; + } + __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); + return c_line; +} +#endif + +/* CodeObjectCache */ + static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { + int start = 0, mid = 0, end = count - 1; + if (end >= 0 && code_line > entries[end].code_line) { + return count; + } + while (start < end) { + mid = start + (end - start) / 2; + if (code_line < entries[mid].code_line) { + end = mid; + } else if (code_line > entries[mid].code_line) { + start = mid + 1; + } else { + return mid; + } + } + if (code_line <= entries[mid].code_line) { + return mid; + } else { + return mid + 1; + } +} +static PyCodeObject *__pyx_find_code_object(int code_line) { + PyCodeObject* code_object; + int pos; + if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { + return NULL; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { + return NULL; + } + code_object = __pyx_code_cache.entries[pos].code_object; + Py_INCREF(code_object); + return code_object; +} +static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { + int pos, i; + __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; + if (unlikely(!code_line)) { + return; + } + if (unlikely(!entries)) { + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); + if (likely(entries)) { + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = 64; + __pyx_code_cache.count = 1; + entries[0].code_line = code_line; + entries[0].code_object = code_object; + Py_INCREF(code_object); + } + return; + } + pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); + if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { + PyCodeObject* tmp = entries[pos].code_object; + entries[pos].code_object = code_object; + Py_DECREF(tmp); + return; + } + if (__pyx_code_cache.count == __pyx_code_cache.max_count) { + int new_max = __pyx_code_cache.max_count + 64; + entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( + __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); + if (unlikely(!entries)) { + return; + } + __pyx_code_cache.entries = entries; + __pyx_code_cache.max_count = new_max; + } + for (i=__pyx_code_cache.count; i>pos; i--) { + entries[i] = entries[i-1]; + } + entries[pos].code_line = code_line; + entries[pos].code_object = code_object; + __pyx_code_cache.count++; + Py_INCREF(code_object); +} + +/* AddTraceback */ + #include "compile.h" +#include "frameobject.h" +#include "traceback.h" +static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( + const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = NULL; + PyObject *py_funcname = NULL; + #if PY_MAJOR_VERSION < 3 + PyObject *py_srcfile = NULL; + py_srcfile = PyString_FromString(filename); + if (!py_srcfile) goto bad; + #endif + if (c_line) { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + #else + py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); + if (!py_funcname) goto bad; + funcname = PyUnicode_AsUTF8(py_funcname); + if (!funcname) goto bad; + #endif + } + else { + #if PY_MAJOR_VERSION < 3 + py_funcname = PyString_FromString(funcname); + if (!py_funcname) goto bad; + #endif + } + #if PY_MAJOR_VERSION < 3 + py_code = __Pyx_PyCode_New( + 0, + 0, + 0, + 0, + 0, + __pyx_empty_bytes, /*PyObject *code,*/ + __pyx_empty_tuple, /*PyObject *consts,*/ + __pyx_empty_tuple, /*PyObject *names,*/ + __pyx_empty_tuple, /*PyObject *varnames,*/ + __pyx_empty_tuple, /*PyObject *freevars,*/ + __pyx_empty_tuple, /*PyObject *cellvars,*/ + py_srcfile, /*PyObject *filename,*/ + py_funcname, /*PyObject *name,*/ + py_line, + __pyx_empty_bytes /*PyObject *lnotab*/ + ); + Py_DECREF(py_srcfile); + #else + py_code = PyCode_NewEmpty(filename, funcname, py_line); + #endif + Py_XDECREF(py_funcname); // XDECREF since it's only set on Py3 if cline + return py_code; +bad: + Py_XDECREF(py_funcname); + #if PY_MAJOR_VERSION < 3 + Py_XDECREF(py_srcfile); + #endif + return NULL; +} +static void __Pyx_AddTraceback(const char *funcname, int c_line, + int py_line, const char *filename) { + PyCodeObject *py_code = 0; + PyFrameObject *py_frame = 0; + PyThreadState *tstate = __Pyx_PyThreadState_Current; + if (c_line) { + c_line = __Pyx_CLineForTraceback(tstate, c_line); + } + py_code = __pyx_find_code_object(c_line ? -c_line : py_line); + if (!py_code) { + py_code = __Pyx_CreateCodeObjectForTraceback( + funcname, c_line, py_line, filename); + if (!py_code) goto bad; + __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); + } + py_frame = PyFrame_New( + tstate, /*PyThreadState *tstate,*/ + py_code, /*PyCodeObject *code,*/ + __pyx_d, /*PyObject *globals,*/ + 0 /*PyObject *locals*/ + ); + if (!py_frame) goto bad; + __Pyx_PyFrame_SetLineNumber(py_frame, py_line); + PyTraceBack_Here(py_frame); +bad: + Py_XDECREF(py_code); + Py_XDECREF(py_frame); +} + +#if PY_MAJOR_VERSION < 3 +static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { + if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); + PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); + return -1; +} +static void __Pyx_ReleaseBuffer(Py_buffer *view) { + PyObject *obj = view->obj; + if (!obj) return; + if (PyObject_CheckBuffer(obj)) { + PyBuffer_Release(view); + return; + } + if ((0)) {} + view->obj = NULL; + Py_DECREF(obj); +} +#endif + + + /* CIntFromPyVerify */ + #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) +#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ + __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) +#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ + {\ + func_type value = func_value;\ + if (sizeof(target_type) < sizeof(func_type)) {\ + if (unlikely(value != (func_type) (target_type) value)) {\ + func_type zero = 0;\ + if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ + return (target_type) -1;\ + if (is_unsigned && unlikely(value < zero))\ + goto raise_neg_overflow;\ + else\ + goto raise_overflow;\ + }\ + }\ + return (target_type) value;\ + } + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return ::std::complex< float >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + return x + y*(__pyx_t_float_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { + __pyx_t_float_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabsf(b.real) >= fabsf(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + float r = b.imag / b.real; + float s = (float)(1.0) / (b.real + b.imag * r); + return __pyx_t_float_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + float r = b.real / b.imag; + float s = (float)(1.0) / (b.imag + b.real * r); + return __pyx_t_float_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + if (b.imag == 0) { + return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + float denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_float_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { + __pyx_t_float_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrtf(z.real*z.real + z.imag*z.imag); + #else + return hypotf(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { + __pyx_t_float_complex z; + float r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + float denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_float(a, a); + case 3: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, a); + case 4: + z = __Pyx_c_prod_float(a, a); + return __Pyx_c_prod_float(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = powf(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2f(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_float(a); + theta = atan2f(a.imag, a.real); + } + lnr = logf(r); + z_r = expf(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cosf(z_theta); + z.imag = z_r * sinf(z_theta); + return z; + } + #endif +#endif + +/* Declarations */ + #if CYTHON_CCOMPLEX + #ifdef __cplusplus + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return ::std::complex< double >(x, y); + } + #else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + return x + y*(__pyx_t_double_complex)_Complex_I; + } + #endif +#else + static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { + __pyx_t_double_complex z; + z.real = x; + z.imag = y; + return z; + } +#endif + +/* Arithmetic */ + #if CYTHON_CCOMPLEX +#else + static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + return (a.real == b.real) && (a.imag == b.imag); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real + b.real; + z.imag = a.imag + b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real - b.real; + z.imag = a.imag - b.imag; + return z; + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + z.real = a.real * b.real - a.imag * b.imag; + z.imag = a.real * b.imag + a.imag * b.real; + return z; + } + #if 1 + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else if (fabs(b.real) >= fabs(b.imag)) { + if (b.real == 0 && b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); + } else { + double r = b.imag / b.real; + double s = (double)(1.0) / (b.real + b.imag * r); + return __pyx_t_double_complex_from_parts( + (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); + } + } else { + double r = b.real / b.imag; + double s = (double)(1.0) / (b.imag + b.real * r); + return __pyx_t_double_complex_from_parts( + (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); + } + } + #else + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + if (b.imag == 0) { + return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); + } else { + double denom = b.real * b.real + b.imag * b.imag; + return __pyx_t_double_complex_from_parts( + (a.real * b.real + a.imag * b.imag) / denom, + (a.imag * b.real - a.real * b.imag) / denom); + } + } + #endif + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = -a.real; + z.imag = -a.imag; + return z; + } + static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { + return (a.real == 0) && (a.imag == 0); + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { + __pyx_t_double_complex z; + z.real = a.real; + z.imag = -a.imag; + return z; + } + #if 1 + static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { + #if !defined(HAVE_HYPOT) || defined(_MSC_VER) + return sqrt(z.real*z.real + z.imag*z.imag); + #else + return hypot(z.real, z.imag); + #endif + } + static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { + __pyx_t_double_complex z; + double r, lnr, theta, z_r, z_theta; + if (b.imag == 0 && b.real == (int)b.real) { + if (b.real < 0) { + double denom = a.real * a.real + a.imag * a.imag; + a.real = a.real / denom; + a.imag = -a.imag / denom; + b.real = -b.real; + } + switch ((int)b.real) { + case 0: + z.real = 1; + z.imag = 0; + return z; + case 1: + return a; + case 2: + return __Pyx_c_prod_double(a, a); + case 3: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, a); + case 4: + z = __Pyx_c_prod_double(a, a); + return __Pyx_c_prod_double(z, z); + } + } + if (a.imag == 0) { + if (a.real == 0) { + return a; + } else if (b.imag == 0) { + z.real = pow(a.real, b.real); + z.imag = 0; + return z; + } else if (a.real > 0) { + r = a.real; + theta = 0; + } else { + r = -a.real; + theta = atan2(0.0, -1.0); + } + } else { + r = __Pyx_c_abs_double(a); + theta = atan2(a.imag, a.real); + } + lnr = log(r); + z_r = exp(lnr * b.real - theta * b.imag); + z_theta = theta * b.real + lnr * b.imag; + z.real = z_r * cos(z_theta); + z.imag = z_r * sin(z_theta); + return z; + } + #endif +#endif + +/* CIntFromPy */ + static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const int neg_one = (int) -1, const_zero = (int) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(int) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (int) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { + return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { + return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { + return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (int) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(int) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (int) 0; + case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) + case -2: + if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(int) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(int) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(int) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { + return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); + } + } + break; + } +#endif + if (sizeof(int) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + int val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (int) -1; + } + } else { + int val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (int) -1; + val = __Pyx_PyInt_As_int(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to int"); + return (int) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to int"); + return (int) -1; +} + +/* CIntToPy */ + static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; + if (is_unsigned) { + if (sizeof(long) < sizeof(long)) { + return PyInt_FromLong((long) value); + } else if (sizeof(long) <= sizeof(unsigned long)) { + return PyLong_FromUnsignedLong((unsigned long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); +#endif + } + } else { + if (sizeof(long) <= sizeof(long)) { + return PyInt_FromLong((long) value); +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + return PyLong_FromLongLong((PY_LONG_LONG) value); +#endif + } + } + { + int one = 1; int little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&value; + return _PyLong_FromByteArray(bytes, sizeof(long), + little, !is_unsigned); + } +} + +/* CIntFromPy */ + static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic push +#pragma GCC diagnostic ignored "-Wconversion" +#endif + const long neg_one = (long) -1, const_zero = (long) 0; +#ifdef __Pyx_HAS_GCC_DIAGNOSTIC +#pragma GCC diagnostic pop +#endif + const int is_unsigned = neg_one > const_zero; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x))) { + if (sizeof(long) < sizeof(long)) { + __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) + } else { + long val = PyInt_AS_LONG(x); + if (is_unsigned && unlikely(val < 0)) { + goto raise_neg_overflow; + } + return (long) val; + } + } else +#endif + if (likely(PyLong_Check(x))) { + if (is_unsigned) { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { + return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { + return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { + return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); + } + } + break; + } +#endif +#if CYTHON_COMPILING_IN_CPYTHON + if (unlikely(Py_SIZE(x) < 0)) { + goto raise_neg_overflow; + } +#else + { + int result = PyObject_RichCompareBool(x, Py_False, Py_LT); + if (unlikely(result < 0)) + return (long) -1; + if (unlikely(result == 1)) + goto raise_neg_overflow; + } +#endif + if (sizeof(long) <= sizeof(unsigned long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) +#endif + } + } else { +#if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)x)->ob_digit; + switch (Py_SIZE(x)) { + case 0: return (long) 0; + case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) + case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) + case -2: + if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 2: + if (8 * sizeof(long) > 1 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -3: + if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 3: + if (8 * sizeof(long) > 2 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case -4: + if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + case 4: + if (8 * sizeof(long) > 3 * PyLong_SHIFT) { + if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { + __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) + } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { + return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); + } + } + break; + } +#endif + if (sizeof(long) <= sizeof(long)) { + __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) +#ifdef HAVE_LONG_LONG + } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { + __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) +#endif + } + } + { +#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) + PyErr_SetString(PyExc_RuntimeError, + "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); +#else + long val; + PyObject *v = __Pyx_PyNumber_IntOrLong(x); + #if PY_MAJOR_VERSION < 3 + if (likely(v) && !PyLong_Check(v)) { + PyObject *tmp = v; + v = PyNumber_Long(tmp); + Py_DECREF(tmp); + } + #endif + if (likely(v)) { + int one = 1; int is_little = (int)*(unsigned char *)&one; + unsigned char *bytes = (unsigned char *)&val; + int ret = _PyLong_AsByteArray((PyLongObject *)v, + bytes, sizeof(val), + is_little, !is_unsigned); + Py_DECREF(v); + if (likely(!ret)) + return val; + } +#endif + return (long) -1; + } + } else { + long val; + PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); + if (!tmp) return (long) -1; + val = __Pyx_PyInt_As_long(tmp); + Py_DECREF(tmp); + return val; + } +raise_overflow: + PyErr_SetString(PyExc_OverflowError, + "value too large to convert to long"); + return (long) -1; +raise_neg_overflow: + PyErr_SetString(PyExc_OverflowError, + "can't convert negative value to long"); + return (long) -1; +} + +/* FastTypeChecks */ + #if CYTHON_COMPILING_IN_CPYTHON +static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { + while (a) { + a = a->tp_base; + if (a == b) + return 1; + } + return b == &PyBaseObject_Type; +} +static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { + PyObject *mro; + if (a == b) return 1; + mro = a->tp_mro; + if (likely(mro)) { + Py_ssize_t i, n; + n = PyTuple_GET_SIZE(mro); + for (i = 0; i < n; i++) { + if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) + return 1; + } + return 0; + } + return __Pyx_InBases(a, b); +} +#if PY_MAJOR_VERSION == 2 +static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { + PyObject *exception, *value, *tb; + int res; + __Pyx_PyThreadState_declare + __Pyx_PyThreadState_assign + __Pyx_ErrFetch(&exception, &value, &tb); + res = exc_type1 ? PyObject_IsSubclass(err, exc_type1) : 0; + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + if (!res) { + res = PyObject_IsSubclass(err, exc_type2); + if (unlikely(res == -1)) { + PyErr_WriteUnraisable(err); + res = 0; + } + } + __Pyx_ErrRestore(exception, value, tb); + return res; +} +#else +static CYTHON_INLINE int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject *exc_type2) { + int res = exc_type1 ? __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type1) : 0; + if (!res) { + res = __Pyx_IsSubtype((PyTypeObject*)err, (PyTypeObject*)exc_type2); + } + return res; +} +#endif +static int __Pyx_PyErr_GivenExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { + Py_ssize_t i, n; + assert(PyExceptionClass_Check(exc_type)); + n = PyTuple_GET_SIZE(tuple); +#if PY_MAJOR_VERSION >= 3 + for (i=0; ip) { + #if PY_MAJOR_VERSION < 3 + if (t->is_unicode) { + *t->p = PyUnicode_DecodeUTF8(t->s, t->n - 1, NULL); + } else if (t->intern) { + *t->p = PyString_InternFromString(t->s); + } else { + *t->p = PyString_FromStringAndSize(t->s, t->n - 1); + } + #else + if (t->is_unicode | t->is_str) { + if (t->intern) { + *t->p = PyUnicode_InternFromString(t->s); + } else if (t->encoding) { + *t->p = PyUnicode_Decode(t->s, t->n - 1, t->encoding, NULL); + } else { + *t->p = PyUnicode_FromStringAndSize(t->s, t->n - 1); + } + } else { + *t->p = PyBytes_FromStringAndSize(t->s, t->n - 1); + } + #endif + if (!*t->p) + return -1; + if (PyObject_Hash(*t->p) == -1) + return -1; + ++t; + } + return 0; +} + +static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char* c_str) { + return __Pyx_PyUnicode_FromStringAndSize(c_str, (Py_ssize_t)strlen(c_str)); +} +static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject* o) { + Py_ssize_t ignore; + return __Pyx_PyObject_AsStringAndSize(o, &ignore); +} +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT +#if !CYTHON_PEP393_ENABLED +static const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + char* defenc_c; + PyObject* defenc = _PyUnicode_AsDefaultEncodedString(o, NULL); + if (!defenc) return NULL; + defenc_c = PyBytes_AS_STRING(defenc); +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + { + char* end = defenc_c + PyBytes_GET_SIZE(defenc); + char* c; + for (c = defenc_c; c < end; c++) { + if ((unsigned char) (*c) >= 128) { + PyUnicode_AsASCIIString(o); + return NULL; + } + } + } +#endif + *length = PyBytes_GET_SIZE(defenc); + return defenc_c; +} +#else +static CYTHON_INLINE const char* __Pyx_PyUnicode_AsStringAndSize(PyObject* o, Py_ssize_t *length) { + if (unlikely(__Pyx_PyUnicode_READY(o) == -1)) return NULL; +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + if (likely(PyUnicode_IS_ASCII(o))) { + *length = PyUnicode_GET_LENGTH(o); + return PyUnicode_AsUTF8(o); + } else { + PyUnicode_AsASCIIString(o); + return NULL; + } +#else + return PyUnicode_AsUTF8AndSize(o, length); +#endif +} +#endif +#endif +static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject* o, Py_ssize_t *length) { +#if __PYX_DEFAULT_STRING_ENCODING_IS_ASCII || __PYX_DEFAULT_STRING_ENCODING_IS_DEFAULT + if ( +#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII + __Pyx_sys_getdefaultencoding_not_ascii && +#endif + PyUnicode_Check(o)) { + return __Pyx_PyUnicode_AsStringAndSize(o, length); + } else +#endif +#if (!CYTHON_COMPILING_IN_PYPY) || (defined(PyByteArray_AS_STRING) && defined(PyByteArray_GET_SIZE)) + if (PyByteArray_Check(o)) { + *length = PyByteArray_GET_SIZE(o); + return PyByteArray_AS_STRING(o); + } else +#endif + { + char* result; + int r = PyBytes_AsStringAndSize(o, &result, length); + if (unlikely(r < 0)) { + return NULL; + } else { + return result; + } + } +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject* x) { + int is_true = x == Py_True; + if (is_true | (x == Py_False) | (x == Py_None)) return is_true; + else return PyObject_IsTrue(x); +} +static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject* x) { + int retval; + if (unlikely(!x)) return -1; + retval = __Pyx_PyObject_IsTrue(x); + Py_DECREF(x); + return retval; +} +static PyObject* __Pyx_PyNumber_IntOrLongWrongResultType(PyObject* result, const char* type_name) { +#if PY_MAJOR_VERSION >= 3 + if (PyLong_Check(result)) { + if (PyErr_WarnFormat(PyExc_DeprecationWarning, 1, + "__int__ returned non-int (type %.200s). " + "The ability to return an instance of a strict subclass of int " + "is deprecated, and may be removed in a future version of Python.", + Py_TYPE(result)->tp_name)) { + Py_DECREF(result); + return NULL; + } + return result; + } +#endif + PyErr_Format(PyExc_TypeError, + "__%.4s__ returned non-%.4s (type %.200s)", + type_name, type_name, Py_TYPE(result)->tp_name); + Py_DECREF(result); + return NULL; +} +static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x) { +#if CYTHON_USE_TYPE_SLOTS + PyNumberMethods *m; +#endif + const char *name = NULL; + PyObject *res = NULL; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_Check(x) || PyLong_Check(x))) +#else + if (likely(PyLong_Check(x))) +#endif + return __Pyx_NewRef(x); +#if CYTHON_USE_TYPE_SLOTS + m = Py_TYPE(x)->tp_as_number; + #if PY_MAJOR_VERSION < 3 + if (m && m->nb_int) { + name = "int"; + res = m->nb_int(x); + } + else if (m && m->nb_long) { + name = "long"; + res = m->nb_long(x); + } + #else + if (likely(m && m->nb_int)) { + name = "int"; + res = m->nb_int(x); + } + #endif +#else + if (!PyBytes_CheckExact(x) && !PyUnicode_CheckExact(x)) { + res = PyNumber_Int(x); + } +#endif + if (likely(res)) { +#if PY_MAJOR_VERSION < 3 + if (unlikely(!PyInt_Check(res) && !PyLong_Check(res))) { +#else + if (unlikely(!PyLong_CheckExact(res))) { +#endif + return __Pyx_PyNumber_IntOrLongWrongResultType(res, name); + } + } + else if (!PyErr_Occurred()) { + PyErr_SetString(PyExc_TypeError, + "an integer is required"); + } + return res; +} +static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject* b) { + Py_ssize_t ival; + PyObject *x; +#if PY_MAJOR_VERSION < 3 + if (likely(PyInt_CheckExact(b))) { + if (sizeof(Py_ssize_t) >= sizeof(long)) + return PyInt_AS_LONG(b); + else + return PyInt_AsSsize_t(b); + } +#endif + if (likely(PyLong_CheckExact(b))) { + #if CYTHON_USE_PYLONG_INTERNALS + const digit* digits = ((PyLongObject*)b)->ob_digit; + const Py_ssize_t size = Py_SIZE(b); + if (likely(__Pyx_sst_abs(size) <= 1)) { + ival = likely(size) ? digits[0] : 0; + if (size == -1) ival = -ival; + return ival; + } else { + switch (size) { + case 2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return (Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -2: + if (8 * sizeof(Py_ssize_t) > 2 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -3: + if (8 * sizeof(Py_ssize_t) > 3 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case 4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return (Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + case -4: + if (8 * sizeof(Py_ssize_t) > 4 * PyLong_SHIFT) { + return -(Py_ssize_t) (((((((((size_t)digits[3]) << PyLong_SHIFT) | (size_t)digits[2]) << PyLong_SHIFT) | (size_t)digits[1]) << PyLong_SHIFT) | (size_t)digits[0])); + } + break; + } + } + #endif + return PyLong_AsSsize_t(b); + } + x = PyNumber_Index(b); + if (!x) return -1; + ival = PyInt_AsSsize_t(x); + Py_DECREF(x); + return ival; +} +static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject* o) { + if (sizeof(Py_hash_t) == sizeof(Py_ssize_t)) { + return (Py_hash_t) __Pyx_PyIndex_AsSsize_t(o); +#if PY_MAJOR_VERSION < 3 + } else if (likely(PyInt_CheckExact(o))) { + return PyInt_AS_LONG(o); +#endif + } else { + Py_ssize_t ival; + PyObject *x; + x = PyNumber_Index(o); + if (!x) return -1; + ival = PyInt_AsLong(x); + Py_DECREF(x); + return ival; + } +} +static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b) { + return b ? __Pyx_NewRef(Py_True) : __Pyx_NewRef(Py_False); +} +static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t ival) { + return PyInt_FromSize_t(ival); +} + + +#endif /* Py_PYTHON_H */ From fd5c2da0e04da426152ce546e02e81672f723a0d Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 7 Nov 2022 15:27:03 +0000 Subject: [PATCH 02/25] Update read_noise.py Adding quick comment, checking to see if git push works automatically now --- python/arcticpy/read_noise.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 208fdad..444ad79 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -45,6 +45,9 @@ def sigma(self, value): ############### ############### def determine_noise_model(self, imageIn, imageOut): + ''' + Method for estimating readnoise on image (in S+R fashion) + ''' readNoiseAmp = self.sigmaRN dval0 = imageIn - imageOut From c3a4e24a3cec7d9f353e239fa0dc0cb6af9a6171 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 7 Nov 2022 15:59:02 +0000 Subject: [PATCH 03/25] Update .gitignore excluding wrapper.cpp --- .gitignore | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/.gitignore b/.gitignore index eaa66aa..d2cd122 100644 --- a/.gitignore +++ b/.gitignore @@ -4,7 +4,7 @@ test_arctic libarctic.so *.cpython*.so lib_test -arcticpy/src/wrapper.cpp +python/arcticpy/wrapper.cpp __pycache__/ build/ gsl/ From 96778e7477b9ad8b0c17146c4a34edad3ca15dfe Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 7 Nov 2022 16:01:33 +0000 Subject: [PATCH 04/25] Update read_noise.py commenting --- python/arcticpy/read_noise.py | 1 + 1 file changed, 1 insertion(+) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 444ad79..28bd52c 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -47,6 +47,7 @@ def sigma(self, value): def determine_noise_model(self, imageIn, imageOut): ''' Method for estimating readnoise on image (in S+R fashion) + assumes parallel+serial by default ''' readNoiseAmp = self.sigmaRN From ca592fdde604c8e5128d030c0ef28fe95dd82fcb Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 7 Nov 2022 16:17:10 +0000 Subject: [PATCH 05/25] Update read_noise.py refining covariance matrix calculation --- python/arcticpy/read_noise.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 28bd52c..6ff8aeb 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -553,11 +553,11 @@ def covariance_matrix_from_image(self, image, matrix_size=5): ybar = np.mean(y) #calculate covariance - covar = np.sum((x-xbar)*(y-ybar))/(np.std(x-xbar)*np.std(y-ybar))/(x.size) + covar = np.sum((x-xbar)*(y-ybar))/x.size #/(np.std(x-xbar)*np.std(y-ybar))/(x.size) #removing noise-level normalization #populate matrix cells covariance_matrix[i+matRange,j+matRange] = covar - covariance_matrix[matRange,matRange] = 0 + #covariance_matrix[matRange,matRange] = 0 switch this normalization to plotting return covariance_matrix From f366443dbaf2202a0dba8ca40196f5ced8931c6d Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Thu, 8 Dec 2022 17:33:51 +0000 Subject: [PATCH 06/25] Update read_noise.py Refactored/optimized readnoise process --- python/arcticpy/read_noise.py | 456 ++++++++++++++++++++++------------ 1 file changed, 302 insertions(+), 154 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 6ff8aeb..3ceb93a 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -212,36 +212,9 @@ def estimate_residual_covariance( self, background_level, background_sigma=None, - chip_size=2048, #size, in pixels, of CCD (assumes square) + chip_size=500, #size, in pixels, of CCD (assumes square) matrix_size=5, #size of covariance grid, in pixels (also assumes square) - # Parallel - parallel_ccd=None, #can we do this with **kwargs ? I'm not sure in python - parallel_roe=None, - parallel_traps=None, - parallel_express=0, - parallel_window_offset=0, - parallel_window_start=0, - parallel_window_stop=-1, - parallel_time_start=0, - parallel_time_stop=-1, - parallel_prune_n_electrons=1e-10, - parallel_prune_frequency=20, - # Serial - serial_ccd=None, - serial_roe=None, - serial_traps=None, - serial_express=0, - serial_window_offset=0, - serial_window_start=0, - serial_window_stop=-1, - serial_time_start=0, - serial_time_stop=-1, - serial_prune_n_electrons=1e-10, - serial_prune_frequency=20, - # Pixel bounce - pixel_bounce=None, - # Output - verbosity=1, + **kwargs ): if background_sigma==None: background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) @@ -249,14 +222,14 @@ def estimate_residual_covariance( #create sky frame skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) #add CTI effects - ctiTrailedFrame = ac.add_cti(skyFrame,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) #add read noise noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) readNoiseAddedFrame = ctiTrailedFrame + noiseFrame #do S+R routine sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) #re-add R frame to correction outputFrame = ctiCorrectedFrame + rFrame @@ -265,7 +238,7 @@ def estimate_residual_covariance( fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) fomDiff = fomSR - fomBenchmark - return fomDiff + return fomSR,fomDiff #raise NotImplementedError #return np.array([[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]) @@ -280,83 +253,14 @@ def _estimate_residual_covariance_for_opt( chip_size=500, #size, in pixels, of CCD (assumes square) matrix_size=5, #size of covariance grid, in pixels (also assumes square) **kwargs - ### Parallel - ##parallel_ccd=None, #can we do this with **kwargs ? I'm not sure in python - ##parallel_roe=None, - ##parallel_traps=None, - ##parallel_express=0, - ##parallel_window_offset=0, - ##parallel_window_start=0, - ##parallel_window_stop=-1, - ##parallel_time_start=0, - ##parallel_time_stop=-1, - ##parallel_prune_n_electrons=1e-10, - ##parallel_prune_frequency=20, - ### Serial - ##serial_ccd=None, - ##serial_roe=None, - ##serial_traps=None, - ##serial_express=0, - ##serial_window_offset=0, - ##serial_window_start=0, - ##serial_window_stop=-1, - ##serial_time_start=0, - ##serial_time_stop=-1, - ##serial_prune_n_electrons=1e-10, - ##serial_prune_frequency=20, - ### Pixel bounce - ##pixel_bounce=None, - ### Output - ##verbosity=1, ): if background_sigma==None: background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) - - if 'parallel_roe' in kwargs: - parallel_roe = kwargs['parallel_roe'] - else: - parallel_roe = None - - if 'parallel_ccd' in kwargs: - parallel_ccd = kwargs['parallel_ccd'] - else: - parallel_ccd = None - - if 'parallel_traps' in kwargs: - parallel_traps = kwargs['parallel_traps'] - else: - parallel_traps = None - - if 'parallel_express' in kwargs: - parallel_express = kwargs['parallel_express'] - else: - parallel_express = 0 - - if 'serial_roe' in kwargs: - serial_roe = kwargs['serial_roe'] - else: - serial_roe = None - - if 'serial_ccd' in kwargs: - serial_ccd = kwargs['serial_ccd'] - else: - serial_ccd = None - - if 'serial_traps' in kwargs: - serial_traps = kwargs['serial_traps'] - else: - serial_traps = None - - if 'serial_express' in kwargs: - serial_express = kwargs['serial_express'] - else: - serial_express = 0 - - + #create sky frame skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) #add CTI effects - ctiTrailedFrame = ac.add_cti(skyFrame,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) #add read noise noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) readNoiseAddedFrame = ctiTrailedFrame + noiseFrame @@ -367,7 +271,7 @@ def _estimate_residual_covariance_for_opt( rFrame*=sr_fraction sFrame-=rFrame #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,parallel_roe=parallel_roe,parallel_ccd=parallel_ccd,parallel_traps=parallel_traps,parallel_express=parallel_express,serial_roe=serial_roe,serial_ccd=serial_ccd,serial_traps=serial_traps,serial_express=serial_express) + ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) #re-add R frame to correction outputFrame = ctiCorrectedFrame + rFrame @@ -376,63 +280,299 @@ def _estimate_residual_covariance_for_opt( fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) fomDiff = fomSR - fomBenchmark - return fomDiff + return fomSR,fomDiff ############### ############### + def _create_initial_sim_images( + self, + background_level, + background_sigma, + image_size=500 + ): + ''' + subroutine to generate sky_background and readnoise frames for S+R simulations + These will stay fixed in each simulation, to control random noise fluctuations + ''' + + #if background_sigma==None: + # background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) + + #create sky frame + skyFrame = np.random.normal(background_level, background_sigma, (image_size,image_size)) + #create readnoise_frame + noiseFrame = np.random.normal(0, self.sigmaRN, (image_size,image_size)) + + return skyFrame,noiseFrame + + ############### + def _estimate_residual_covariance_for_opt_premade( + self, + skyFrame, + noiseFrame, + sr_fraction, + matrix_size=5, #size of covariance grid, in pixels (also assumes square) + **kwargs + ): + ''' + Estimate a covariance matrix for an optimising simulation, assuming the sky/noise frames have already been created + ''' + #add CTI effects to skyFrame + ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) + #add read noise to STI-trailed image + readNoiseAddedFrame = ctiTrailedFrame + noiseFrame + #do S+R routine + sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) + #rescale S+R correction to a fractional value (for optimization) + sFrame+=rFrame + rFrame*=sr_fraction + sFrame-=rFrame + #clean CTI from S frame + ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) + #re-add R frame to correction + outputFrame = ctiCorrectedFrame + rFrame + + #determine covariance FOMs + fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) + fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) + fomDiff = fomSR - fomBenchmark + + return fomSR,fomDiff + ############### def _fitter_function(self,x,intercept,slope): y = intercept + slope * x return y ############### - ############### def optimise_parameters( + self, + background_level, + background_sigma=None, + chip_size=2048, #the size of the entire CCD over which the procedure will be run + subchip_size=500, #size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) + matrix_size=5, #covariance matrix size (NxN array) + **kwargs + ): + ''' + S+R optimisation routine. Given a specified set of CTI trap parameters, this routine calculates the optimum S+R fraction to minimise image correlations during correction + ''' + + #if sky sigma is not set, assume sqrt(N) + if background_sigma==None: + background_sigma = np.sqrt(background_level) + + #set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) + if 'parallel_roe' in kwargs: + kwargs['parallel_roe'].prescan_offset = chip_size+(subchip_size//2) + if 'serial_roe' in kwargs: + kwargs['serial_roe'].prescan_offset = chip_size+(subchip_size//2) + + #container for optimised values + optVals = {} + + #pre-make the sky background and readnoise images, keep these constant over all quadrants + skyFrame, readNoiseFrame = self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) + + #run S+R routine at 0% and 100% S+R fraction + result_array = np.array([]) + matrix_array = np.zeros((2,matrix_size,matrix_size)) + sr_frac = np.array([0.0,1.0]) + for frac in sr_frac: + raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac,matrix_size=matrix_size,**kwargs) + matrix_array[int(frac)] = correction_matrix + result = self.figure_of_merit(correction_matrix) #TODO: check to see if changing subgrid_size actually matters + result_array = np.append(result_array,result) + print('both progression:',result_array) + #interpolate between the results to determine the point of minimum residual covariance + a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) + m = a_fit[1] + b = a_fit[0] + xint = -b/m + + frac_opt = xint #set the optimized S+R fraction + + #re-run the S+R routine with the optimised level + raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs) + + #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise + kwargs_noCTI = kwargs.copy() + kwargs_noCTI['parallel_traps']=None + kwargs_noCTI['serial_traps']=None + #effectively, we are removing the effects of CTI, but still calculating a covariance matrix + raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) + + #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) + #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated + benchmark_matrix = raw_matrix_opt_noCTI*0 + centrePix = matrix_size//2 + benchmark_matrix[centrePix,centrePix] = self.sigmaRN**2 + background_sigma**2 + #calculate the simulation-noise residual + residual_benchmark_matrix = raw_matrix_opt_noCTI - benchmark_matrix + + #Finally, if both parallel and serial CTI are present, calculate covariances of the "cross-region" chip quadrants (far from serial readout but close to parallel readout, and vice-versa) + if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): + if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): + kwargs_parallelOnly = kwargs.copy() + kwargs_parallelOnly['serial_traps']=None #make a parallel-only quadrant + kwargs_serialOnly = kwargs.copy() + kwargs_serialOnly['parallel_traps']=None #make a serial-only quadrant + + raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) + + #package all relevant quantities into optVals and return + optVals['optSRfrac'] = frac_opt + optVals['combinedQuadMatrix'] = raw_matrix_opt + optVals['combinedQuadMatrix_diff'] = correction_matrix_opt + optVals['parallelQuadMatrix'] = raw_matrix_opt_parallel + optVals['parallelQuadMatrix_diff'] = correction_matrix_opt_parallel + optVals['serialQuadMatrix'] = raw_matrix_opt_serial + optVals['serialQuadMatrix_diff'] = correction_matrix_opt_serial + optVals['noCTIQuadMatrix'] = raw_matrix_opt_noCTI + optVals['noCTIQuadMatrix_diff'] = correction_matrix_opt_noCTI + optVals['benchmark'] = benchmark_matrix + optVals['benchmark_resid'] = residual_benchmark_matrix + + return optVals + ############### +# ############### +# def optimise_parameters( +# self, +# background_level, +# chip_size=500, +# matrix_size=5, +# **kwargs +# ##figure_of_merit=figure_of_merit(), # should probably pass a function here +# ): +# ''' +# S+R optimisation routine. Given a specified set of CTI trap parameters, this routine calculates the optimum S+R fraction to minimise image correlations during correction +# ''' +# optVals = {} +# +# kwargs['parallel_roe'].prescan_offset = 1900 +# kwargs['serial_roe'].prescan_offset = 1900 +# +# if 'parallel_traps' in kwargs: +# if kwargs['parallel_traps'] is not None: +# kwargs_parallel = kwargs.copy() +# kwargs_parallel['serial_traps']=None #make a parallel-only quadrant +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## +# for frac in sr_frac: +# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs_parallel) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# print('parallel progression:',result_array) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['parallelQuadMatrix'] = mean_grid +# optVals['parallelQuadFrac'] = xint +# +# if 'serial_traps' in kwargs: +# if kwargs['serial_traps'] is not None: +# kwargs_serial = kwargs.copy() +# kwargs_serial['parallel_traps']=None #make a serial-only quadrant +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## +# for frac in sr_frac: +# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs_serial) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# print('serial progression:',result_array) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['serialQuadMatrix'] = mean_grid +# optVals['serialQuadFrac'] = xint +# +# if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): +# if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## +# for frac in sr_frac: +# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# print('both progression:',result_array) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['combinedQuadMatrix'] = mean_grid +# optVals['combinedQuadFrac'] = xint +# +# +# return optVals +# +# ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) +# ##covar = self.covariance_matrix_from_image(image) +# +# ############### + ############### + def optimise_parameters_from_image( self, - background_level, + image, + background_level=None, + chip_size=500, + matrix_size=5, **kwargs - #chip_size=500, - #matrix_size=5, - ##figure_of_merit=figure_of_merit(), # should probably pass a function here - ## Parallel - #parallel_ccd=None, #again, should do this with **kwargs - #parallel_roe=None, - #parallel_traps=None, - #parallel_express=0, - #parallel_window_offset=0, - #parallel_window_start=0, - #parallel_window_stop=-1, - #parallel_time_start=0, - #parallel_time_stop=-1, - #parallel_prune_n_electrons=1e-10, - #parallel_prune_frequency=20, - ## Serial - #serial_ccd=None, - #serial_roe=None, - #serial_traps=None, - #serial_express=0, - #serial_window_offset=0, - #serial_window_start=0, - #serial_window_stop=-1, - #serial_time_start=0, - #serial_time_stop=-1, - #serial_prune_n_electrons=1e-10, - #serial_prune_frequency=20, - ## Pixel bounce - #pixel_bounce=None, - ## Output - #verbosity=1, ): - matrix_size = kwargs['matrix_size'] + ''' + version of the S+R optimiser routine, but parameters can be determined from a supplied image rather than manually specified + ''' optVals = {} + image_nrows = image.shape[0] + image_ncols = image.shape[1] + + #use CTI prescan offset to ensure sample region is at the far edge of the full chip + kwargs['parallel_roe'].prescan_offset = kwargs['parallel_roe'].prescan_offset + image_nrows - chip_size//2 + kwargs['serial_roe'].prescan_offset = kwargs['serial_roe'].prescan_offset + image_ncols - chip_size//2 + + #if background nevel is not specified, estimate using the median pixel value + if background_level == None: + background_level = np.median(image) + if 'parallel_traps' in kwargs: if kwargs['parallel_traps'] is not None: kwargs_parallel = kwargs.copy() kwargs_parallel['serial_traps']=None #make a parallel-only quadrant + ###use CTI prescan offset to ensure sample region is at the far edge of the full chip + ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 #things to compare over iterations result_array = np.array([]) matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.arange(0,1.01,0.1) + sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) for frac in sr_frac: - correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) + correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_parallel) matrix_array[int(frac*10)] = correction_matrix result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters result_array = np.append(result_array,result) @@ -452,11 +592,13 @@ def optimise_parameters( if 'serial_traps' in kwargs: if kwargs['serial_traps'] is not None: kwargs_serial = kwargs.copy() - kwargs_serial['parallel_traps']=None #make a seriial-only quadrant + kwargs_serial['parallel_traps']=None #make a serial-only quadrant + ###use CTI prescan offset to ensure sample region is at the far edge of the full chip + ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 #things to compare over iterations result_array = np.array([]) matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.arange(0,1.01,0.1) + sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) for frac in sr_frac: correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_serial) matrix_array[int(frac*10)] = correction_matrix @@ -477,10 +619,13 @@ def optimise_parameters( if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): + ###use CTI prescan offset to ensure sample region is at the far edge of the full chip + ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 + ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 #things to compare over iterations result_array = np.array([]) matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.arange(0,1.01,0.1) + sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) for frac in sr_frac: correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) matrix_array[int(frac*10)] = correction_matrix @@ -505,7 +650,7 @@ def optimise_parameters( ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) ##covar = self.covariance_matrix_from_image(image) - ############### + ############### ############### def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None): ''' @@ -526,15 +671,17 @@ def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None) xend-=xdiff ystart+=ydiff yend-=ydiff - + + covariance_matrix[ycenter,xcenter] = 0 #supress autocorrelation pixel + if fom_method == 'box': - result_sum = np.sum(covariance_matrix[ystart:yend,xstart:xend]) #sum over central box + result_mean = (np.sum(covariance_matrix[ystart:yend,xstart:xend]) - covariance_matrix[ycenter,xcenter])/8 #average over central box if fom_method == 'row': - result_sum = np.sum(covariance_matrix[ycenter,xstart:xend]) #sum over central row (for serial CTI) + result_mean = (np.sum(covariance_matrix[ycenter,xstart:xend]) - covariance_matrix[ycenter,xcenter])/4 #average over central row (for serial CTI) if fom_method == 'column': - result_sum = np.sum(covariance_matrix[ystart:yend,xcenter]) #sum over central column (for parallel CTI) + result_mean = (np.sum(covariance_matrix[ystart:yend,xcenter]) - covariance_matrix[ycenter,xcenter])/4 #sum over central column (for parallel CTI) #raise NotImplementedError - return result_sum + return result_mean ############### ############### @@ -542,22 +689,23 @@ def covariance_matrix_from_image(self, image, matrix_size=5): covariance_matrix = np.zeros((matrix_size,matrix_size)) #calcluate mean stats on image - x = image.flatten() + image2 = image[5:,5:] #remove FPR decrement + x = image2.flatten() xbar = np.mean(x) #roll image to get cross correlation matRange= matrix_size//2 for i in range(-matRange,matRange+1,1): for j in range(-matRange,matRange+1,1): - y = np.roll(image,(-j,-i),axis=(0,1)).flatten() + y = np.roll(image2,(-j,-i),axis=(0,1)).flatten() ybar = np.mean(y) #calculate covariance covar = np.sum((x-xbar)*(y-ybar))/x.size #/(np.std(x-xbar)*np.std(y-ybar))/(x.size) #removing noise-level normalization - + #covar = np.sum((x-xbar)*(y-ybar))/(np.std(x-xbar)*np.std(y-ybar))/(x.size) #populate matrix cells covariance_matrix[i+matRange,j+matRange] = covar - #covariance_matrix[matRange,matRange] = 0 switch this normalization to plotting + #covariance_matrix[matRange,matRange] = 0 #switch this normalization to plotting return covariance_matrix From a300a682a373b400afc11f58ff0000d76ccf0f70 Mon Sep 17 00:00:00 2001 From: Richard Massey Date: Tue, 24 Jan 2023 12:59:52 +0000 Subject: [PATCH 07/25] updated readme --- python/arcticpy/wrapper.cpp | 9158 ----------------------------------- 1 file changed, 9158 deletions(-) delete mode 100644 python/arcticpy/wrapper.cpp diff --git a/python/arcticpy/wrapper.cpp b/python/arcticpy/wrapper.cpp deleted file mode 100644 index 30ea314..0000000 --- a/python/arcticpy/wrapper.cpp +++ /dev/null @@ -1,9158 +0,0 @@ -/* Generated by Cython 0.29.28 */ - 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#define DL_EXPORT(t) t -#endif -#define __PYX_COMMA , -#ifndef HAVE_LONG_LONG - #if PY_VERSION_HEX >= 0x02070000 - #define HAVE_LONG_LONG - #endif -#endif -#ifndef PY_LONG_LONG - #define PY_LONG_LONG LONG_LONG -#endif -#ifndef Py_HUGE_VAL - #define Py_HUGE_VAL HUGE_VAL -#endif -#ifdef PYPY_VERSION - #define CYTHON_COMPILING_IN_PYPY 1 - #define CYTHON_COMPILING_IN_PYSTON 0 - #define CYTHON_COMPILING_IN_CPYTHON 0 - #undef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 0 - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #if PY_VERSION_HEX < 0x03050000 - #undef CYTHON_USE_ASYNC_SLOTS - #define CYTHON_USE_ASYNC_SLOTS 0 - #elif !defined(CYTHON_USE_ASYNC_SLOTS) - #define CYTHON_USE_ASYNC_SLOTS 1 - #endif - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #undef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 0 - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #undef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 1 - #undef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 0 - #undef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 0 - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #undef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 0 - #undef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 0 - #undef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE 0 - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 0 -#elif defined(PYSTON_VERSION) - #define CYTHON_COMPILING_IN_PYPY 0 - #define CYTHON_COMPILING_IN_PYSTON 1 - #define CYTHON_COMPILING_IN_CPYTHON 0 - #ifndef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 1 - #endif - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #undef CYTHON_USE_ASYNC_SLOTS - #define CYTHON_USE_ASYNC_SLOTS 0 - #undef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 0 - #ifndef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 1 - #endif - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #ifndef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 0 - #endif - #ifndef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 1 - #endif - #ifndef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 1 - #endif - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #undef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL 0 - #undef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT 0 - #undef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE 0 - #undef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS 0 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 0 -#else - #define CYTHON_COMPILING_IN_PYPY 0 - #define CYTHON_COMPILING_IN_PYSTON 0 - #define CYTHON_COMPILING_IN_CPYTHON 1 - #ifndef CYTHON_USE_TYPE_SLOTS - #define CYTHON_USE_TYPE_SLOTS 1 - #endif - #if PY_VERSION_HEX < 0x02070000 - #undef CYTHON_USE_PYTYPE_LOOKUP - #define CYTHON_USE_PYTYPE_LOOKUP 0 - #elif !defined(CYTHON_USE_PYTYPE_LOOKUP) - #define CYTHON_USE_PYTYPE_LOOKUP 1 - #endif - #if PY_MAJOR_VERSION < 3 - #undef CYTHON_USE_ASYNC_SLOTS - #define CYTHON_USE_ASYNC_SLOTS 0 - #elif !defined(CYTHON_USE_ASYNC_SLOTS) - #define CYTHON_USE_ASYNC_SLOTS 1 - #endif - #if PY_VERSION_HEX < 0x02070000 - #undef CYTHON_USE_PYLONG_INTERNALS - #define CYTHON_USE_PYLONG_INTERNALS 0 - #elif !defined(CYTHON_USE_PYLONG_INTERNALS) - #define CYTHON_USE_PYLONG_INTERNALS 1 - #endif - #ifndef CYTHON_USE_PYLIST_INTERNALS - #define CYTHON_USE_PYLIST_INTERNALS 1 - #endif - #ifndef CYTHON_USE_UNICODE_INTERNALS - #define CYTHON_USE_UNICODE_INTERNALS 1 - #endif - #if PY_VERSION_HEX < 0x030300F0 || PY_VERSION_HEX >= 0x030B00A2 - #undef CYTHON_USE_UNICODE_WRITER - #define CYTHON_USE_UNICODE_WRITER 0 - #elif !defined(CYTHON_USE_UNICODE_WRITER) - #define CYTHON_USE_UNICODE_WRITER 1 - #endif - #ifndef CYTHON_AVOID_BORROWED_REFS - #define CYTHON_AVOID_BORROWED_REFS 0 - #endif - #ifndef CYTHON_ASSUME_SAFE_MACROS - #define CYTHON_ASSUME_SAFE_MACROS 1 - #endif - #ifndef CYTHON_UNPACK_METHODS - #define CYTHON_UNPACK_METHODS 1 - #endif - #if PY_VERSION_HEX >= 0x030B00A4 - #undef CYTHON_FAST_THREAD_STATE - #define CYTHON_FAST_THREAD_STATE 0 - #elif !defined(CYTHON_FAST_THREAD_STATE) - #define CYTHON_FAST_THREAD_STATE 1 - #endif - #ifndef CYTHON_FAST_PYCALL - #define CYTHON_FAST_PYCALL (PY_VERSION_HEX < 0x030B00A1) - #endif - #ifndef CYTHON_PEP489_MULTI_PHASE_INIT - #define CYTHON_PEP489_MULTI_PHASE_INIT (PY_VERSION_HEX >= 0x03050000) - #endif - #ifndef CYTHON_USE_TP_FINALIZE - #define CYTHON_USE_TP_FINALIZE (PY_VERSION_HEX >= 0x030400a1) - #endif - #ifndef CYTHON_USE_DICT_VERSIONS - #define CYTHON_USE_DICT_VERSIONS (PY_VERSION_HEX >= 0x030600B1) - #endif - #if PY_VERSION_HEX >= 0x030B00A4 - #undef CYTHON_USE_EXC_INFO_STACK - #define CYTHON_USE_EXC_INFO_STACK 0 - #elif !defined(CYTHON_USE_EXC_INFO_STACK) - #define CYTHON_USE_EXC_INFO_STACK (PY_VERSION_HEX >= 0x030700A3) - #endif -#endif -#if !defined(CYTHON_FAST_PYCCALL) -#define CYTHON_FAST_PYCCALL (CYTHON_FAST_PYCALL && PY_VERSION_HEX >= 0x030600B1) -#endif -#if CYTHON_USE_PYLONG_INTERNALS - #if PY_MAJOR_VERSION < 3 - #include "longintrepr.h" - #endif - #undef SHIFT - #undef BASE - #undef MASK - #ifdef SIZEOF_VOID_P - enum { __pyx_check_sizeof_voidp = 1 / (int)(SIZEOF_VOID_P == sizeof(void*)) }; - #endif -#endif -#ifndef __has_attribute - #define __has_attribute(x) 0 -#endif -#ifndef __has_cpp_attribute - #define __has_cpp_attribute(x) 0 -#endif -#ifndef CYTHON_RESTRICT - #if defined(__GNUC__) - #define CYTHON_RESTRICT __restrict__ - #elif defined(_MSC_VER) && _MSC_VER >= 1400 - #define CYTHON_RESTRICT __restrict - #elif defined (__STDC_VERSION__) && __STDC_VERSION__ >= 199901L - #define CYTHON_RESTRICT restrict - #else - #define CYTHON_RESTRICT - #endif -#endif -#ifndef CYTHON_UNUSED -# if defined(__GNUC__) -# if !(defined(__cplusplus)) || (__GNUC__ > 3 || (__GNUC__ == 3 && __GNUC_MINOR__ >= 4)) -# define CYTHON_UNUSED __attribute__ ((__unused__)) -# else -# define CYTHON_UNUSED -# endif -# elif defined(__ICC) || (defined(__INTEL_COMPILER) && !defined(_MSC_VER)) -# define CYTHON_UNUSED __attribute__ ((__unused__)) -# else -# define CYTHON_UNUSED -# endif -#endif -#ifndef CYTHON_MAYBE_UNUSED_VAR -# if defined(__cplusplus) - template void CYTHON_MAYBE_UNUSED_VAR( const T& ) { } -# else -# define CYTHON_MAYBE_UNUSED_VAR(x) (void)(x) -# endif -#endif -#ifndef CYTHON_NCP_UNUSED -# if CYTHON_COMPILING_IN_CPYTHON -# define CYTHON_NCP_UNUSED -# else -# define CYTHON_NCP_UNUSED CYTHON_UNUSED -# endif -#endif -#define __Pyx_void_to_None(void_result) ((void)(void_result), Py_INCREF(Py_None), Py_None) -#ifdef _MSC_VER - #ifndef _MSC_STDINT_H_ - #if _MSC_VER < 1300 - typedef unsigned char uint8_t; - typedef unsigned int uint32_t; - #else - typedef unsigned __int8 uint8_t; - typedef unsigned __int32 uint32_t; - #endif - #endif -#else - #include -#endif -#ifndef CYTHON_FALLTHROUGH - #if defined(__cplusplus) && __cplusplus >= 201103L - #if __has_cpp_attribute(fallthrough) - #define CYTHON_FALLTHROUGH [[fallthrough]] - #elif __has_cpp_attribute(clang::fallthrough) - #define CYTHON_FALLTHROUGH [[clang::fallthrough]] - #elif __has_cpp_attribute(gnu::fallthrough) - #define CYTHON_FALLTHROUGH [[gnu::fallthrough]] - #endif - #endif - #ifndef CYTHON_FALLTHROUGH - #if __has_attribute(fallthrough) - #define CYTHON_FALLTHROUGH __attribute__((fallthrough)) - #else - #define CYTHON_FALLTHROUGH - #endif - #endif - #if defined(__clang__ ) && defined(__apple_build_version__) - #if __apple_build_version__ < 7000000 - #undef CYTHON_FALLTHROUGH - #define CYTHON_FALLTHROUGH - #endif - #endif -#endif - -#ifndef __cplusplus - #error "Cython files generated with the C++ option must be compiled with a C++ compiler." -#endif -#ifndef CYTHON_INLINE - #if defined(__clang__) - #define CYTHON_INLINE __inline__ __attribute__ ((__unused__)) - #else - #define CYTHON_INLINE inline - #endif -#endif -template -void __Pyx_call_destructor(T& x) { - x.~T(); -} -template -class __Pyx_FakeReference { - public: - __Pyx_FakeReference() : ptr(NULL) { } - __Pyx_FakeReference(const T& ref) : ptr(const_cast(&ref)) { } - T *operator->() { return ptr; } - T *operator&() { return ptr; } - operator T&() { return *ptr; } - template bool operator ==(U other) { return *ptr == other; } - template bool operator !=(U other) { return *ptr != other; } - private: - T *ptr; -}; - -#if CYTHON_COMPILING_IN_PYPY && PY_VERSION_HEX < 0x02070600 && !defined(Py_OptimizeFlag) - #define Py_OptimizeFlag 0 -#endif -#define __PYX_BUILD_PY_SSIZE_T "n" -#define CYTHON_FORMAT_SSIZE_T "z" -#if PY_MAJOR_VERSION < 3 - #define __Pyx_BUILTIN_MODULE_NAME "__builtin__" - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ - PyCode_New(a+k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) - #define __Pyx_DefaultClassType PyClass_Type -#else - #define __Pyx_BUILTIN_MODULE_NAME "builtins" - #define __Pyx_DefaultClassType PyType_Type -#if PY_VERSION_HEX >= 0x030B00A1 - static CYTHON_INLINE PyCodeObject* __Pyx_PyCode_New(int a, int k, int l, int s, int f, - PyObject *code, PyObject *c, PyObject* n, PyObject *v, - PyObject *fv, PyObject *cell, PyObject* fn, - PyObject *name, int fline, PyObject *lnos) { - PyObject *kwds=NULL, *argcount=NULL, *posonlyargcount=NULL, *kwonlyargcount=NULL; - PyObject *nlocals=NULL, *stacksize=NULL, *flags=NULL, *replace=NULL, *call_result=NULL, *empty=NULL; - const char *fn_cstr=NULL; - const char *name_cstr=NULL; - PyCodeObject* co=NULL; - PyObject *type, *value, *traceback; - PyErr_Fetch(&type, &value, &traceback); - if (!(kwds=PyDict_New())) goto end; - if (!(argcount=PyLong_FromLong(a))) goto end; - if (PyDict_SetItemString(kwds, "co_argcount", argcount) != 0) goto end; - if (!(posonlyargcount=PyLong_FromLong(0))) goto end; - if (PyDict_SetItemString(kwds, "co_posonlyargcount", posonlyargcount) != 0) goto end; - if (!(kwonlyargcount=PyLong_FromLong(k))) goto end; - if (PyDict_SetItemString(kwds, "co_kwonlyargcount", kwonlyargcount) != 0) goto end; - if (!(nlocals=PyLong_FromLong(l))) goto end; - if (PyDict_SetItemString(kwds, "co_nlocals", nlocals) != 0) goto end; - if (!(stacksize=PyLong_FromLong(s))) goto end; - if (PyDict_SetItemString(kwds, "co_stacksize", stacksize) != 0) goto end; - if (!(flags=PyLong_FromLong(f))) goto end; - if (PyDict_SetItemString(kwds, "co_flags", flags) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_code", code) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_consts", c) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_names", n) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_varnames", v) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_freevars", fv) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_cellvars", cell) != 0) goto end; - if (PyDict_SetItemString(kwds, "co_linetable", lnos) != 0) goto end; - if (!(fn_cstr=PyUnicode_AsUTF8AndSize(fn, NULL))) goto end; - if (!(name_cstr=PyUnicode_AsUTF8AndSize(name, NULL))) goto end; - if (!(co = PyCode_NewEmpty(fn_cstr, name_cstr, fline))) goto end; - if (!(replace = PyObject_GetAttrString((PyObject*)co, "replace"))) goto cleanup_code_too; - if (!(empty = PyTuple_New(0))) goto cleanup_code_too; // unfortunately __pyx_empty_tuple isn't available here - if (!(call_result = PyObject_Call(replace, empty, kwds))) goto cleanup_code_too; - Py_XDECREF((PyObject*)co); - co = (PyCodeObject*)call_result; - call_result = NULL; - if (0) { - cleanup_code_too: - Py_XDECREF((PyObject*)co); - co = NULL; - } - end: - Py_XDECREF(kwds); - Py_XDECREF(argcount); - Py_XDECREF(posonlyargcount); - Py_XDECREF(kwonlyargcount); - Py_XDECREF(nlocals); - Py_XDECREF(stacksize); - Py_XDECREF(replace); - Py_XDECREF(call_result); - Py_XDECREF(empty); - if (type) { - PyErr_Restore(type, value, traceback); - } - return co; - } -#else - #define __Pyx_PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos)\ - PyCode_New(a, k, l, s, f, code, c, n, v, fv, cell, fn, name, fline, lnos) -#endif - #define __Pyx_DefaultClassType PyType_Type -#endif -#ifndef Py_TPFLAGS_CHECKTYPES - #define Py_TPFLAGS_CHECKTYPES 0 -#endif -#ifndef Py_TPFLAGS_HAVE_INDEX - #define Py_TPFLAGS_HAVE_INDEX 0 -#endif -#ifndef Py_TPFLAGS_HAVE_NEWBUFFER - #define Py_TPFLAGS_HAVE_NEWBUFFER 0 -#endif -#ifndef Py_TPFLAGS_HAVE_FINALIZE - #define Py_TPFLAGS_HAVE_FINALIZE 0 -#endif -#ifndef METH_STACKLESS - #define METH_STACKLESS 0 -#endif -#if PY_VERSION_HEX <= 0x030700A3 || !defined(METH_FASTCALL) - #ifndef METH_FASTCALL - #define METH_FASTCALL 0x80 - #endif - typedef PyObject *(*__Pyx_PyCFunctionFast) (PyObject *self, PyObject *const *args, Py_ssize_t nargs); - typedef PyObject *(*__Pyx_PyCFunctionFastWithKeywords) (PyObject *self, PyObject *const *args, - Py_ssize_t nargs, PyObject *kwnames); -#else - #define __Pyx_PyCFunctionFast _PyCFunctionFast - #define __Pyx_PyCFunctionFastWithKeywords _PyCFunctionFastWithKeywords -#endif -#if CYTHON_FAST_PYCCALL -#define __Pyx_PyFastCFunction_Check(func)\ - ((PyCFunction_Check(func) && (METH_FASTCALL == (PyCFunction_GET_FLAGS(func) & ~(METH_CLASS | METH_STATIC | METH_COEXIST | METH_KEYWORDS | METH_STACKLESS))))) -#else -#define __Pyx_PyFastCFunction_Check(func) 0 -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Malloc) - #define PyObject_Malloc(s) PyMem_Malloc(s) - #define PyObject_Free(p) PyMem_Free(p) - #define PyObject_Realloc(p) PyMem_Realloc(p) -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX < 0x030400A1 - #define PyMem_RawMalloc(n) PyMem_Malloc(n) - #define PyMem_RawRealloc(p, n) PyMem_Realloc(p, n) - #define PyMem_RawFree(p) PyMem_Free(p) -#endif -#if CYTHON_COMPILING_IN_PYSTON - #define __Pyx_PyCode_HasFreeVars(co) PyCode_HasFreeVars(co) - #define __Pyx_PyFrame_SetLineNumber(frame, lineno) PyFrame_SetLineNumber(frame, lineno) -#else - #define __Pyx_PyCode_HasFreeVars(co) (PyCode_GetNumFree(co) > 0) - #define __Pyx_PyFrame_SetLineNumber(frame, lineno) (frame)->f_lineno = (lineno) -#endif -#if !CYTHON_FAST_THREAD_STATE || PY_VERSION_HEX < 0x02070000 - #define __Pyx_PyThreadState_Current PyThreadState_GET() -#elif PY_VERSION_HEX >= 0x03060000 - #define __Pyx_PyThreadState_Current _PyThreadState_UncheckedGet() -#elif PY_VERSION_HEX >= 0x03000000 - #define __Pyx_PyThreadState_Current PyThreadState_GET() -#else - #define __Pyx_PyThreadState_Current _PyThreadState_Current -#endif -#if PY_VERSION_HEX < 0x030700A2 && !defined(PyThread_tss_create) && !defined(Py_tss_NEEDS_INIT) -#include "pythread.h" -#define Py_tss_NEEDS_INIT 0 -typedef int Py_tss_t; -static CYTHON_INLINE int PyThread_tss_create(Py_tss_t *key) { - *key = PyThread_create_key(); - return 0; -} -static CYTHON_INLINE Py_tss_t * PyThread_tss_alloc(void) { - Py_tss_t *key = (Py_tss_t *)PyObject_Malloc(sizeof(Py_tss_t)); - *key = Py_tss_NEEDS_INIT; - return key; -} -static CYTHON_INLINE void PyThread_tss_free(Py_tss_t *key) { - PyObject_Free(key); -} -static CYTHON_INLINE int PyThread_tss_is_created(Py_tss_t *key) { - return *key != Py_tss_NEEDS_INIT; -} -static CYTHON_INLINE void PyThread_tss_delete(Py_tss_t *key) { - PyThread_delete_key(*key); - *key = Py_tss_NEEDS_INIT; -} -static CYTHON_INLINE int PyThread_tss_set(Py_tss_t *key, void *value) { - return PyThread_set_key_value(*key, value); -} -static CYTHON_INLINE void * PyThread_tss_get(Py_tss_t *key) { - return PyThread_get_key_value(*key); -} -#endif -#if CYTHON_COMPILING_IN_CPYTHON || defined(_PyDict_NewPresized) -#define __Pyx_PyDict_NewPresized(n) ((n <= 8) ? PyDict_New() : _PyDict_NewPresized(n)) -#else -#define __Pyx_PyDict_NewPresized(n) PyDict_New() -#endif -#if PY_MAJOR_VERSION >= 3 || CYTHON_FUTURE_DIVISION - #define __Pyx_PyNumber_Divide(x,y) PyNumber_TrueDivide(x,y) - #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceTrueDivide(x,y) -#else - #define __Pyx_PyNumber_Divide(x,y) PyNumber_Divide(x,y) - #define __Pyx_PyNumber_InPlaceDivide(x,y) PyNumber_InPlaceDivide(x,y) -#endif -#if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x030500A1 && CYTHON_USE_UNICODE_INTERNALS -#define __Pyx_PyDict_GetItemStr(dict, name) _PyDict_GetItem_KnownHash(dict, name, ((PyASCIIObject *) name)->hash) -#else -#define __Pyx_PyDict_GetItemStr(dict, name) PyDict_GetItem(dict, name) -#endif -#if PY_VERSION_HEX > 0x03030000 && defined(PyUnicode_KIND) - #define CYTHON_PEP393_ENABLED 1 - #if defined(PyUnicode_IS_READY) - #define __Pyx_PyUnicode_READY(op) (likely(PyUnicode_IS_READY(op)) ?\ - 0 : _PyUnicode_Ready((PyObject *)(op))) - #else - #define __Pyx_PyUnicode_READY(op) (0) - #endif - #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_LENGTH(u) - #define __Pyx_PyUnicode_READ_CHAR(u, i) PyUnicode_READ_CHAR(u, i) - #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) PyUnicode_MAX_CHAR_VALUE(u) - #define __Pyx_PyUnicode_KIND(u) PyUnicode_KIND(u) - #define __Pyx_PyUnicode_DATA(u) PyUnicode_DATA(u) - #define __Pyx_PyUnicode_READ(k, d, i) PyUnicode_READ(k, d, i) - #define __Pyx_PyUnicode_WRITE(k, d, i, ch) PyUnicode_WRITE(k, d, i, ch) - #if defined(PyUnicode_IS_READY) && defined(PyUnicode_GET_SIZE) - #if CYTHON_COMPILING_IN_CPYTHON && PY_VERSION_HEX >= 0x03090000 - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : ((PyCompactUnicodeObject *)(u))->wstr_length)) - #else - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != (likely(PyUnicode_IS_READY(u)) ? PyUnicode_GET_LENGTH(u) : PyUnicode_GET_SIZE(u))) - #endif - #else - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_LENGTH(u)) - #endif -#else - #define CYTHON_PEP393_ENABLED 0 - #define PyUnicode_1BYTE_KIND 1 - #define PyUnicode_2BYTE_KIND 2 - #define PyUnicode_4BYTE_KIND 4 - #define __Pyx_PyUnicode_READY(op) (0) - #define __Pyx_PyUnicode_GET_LENGTH(u) PyUnicode_GET_SIZE(u) - #define __Pyx_PyUnicode_READ_CHAR(u, i) ((Py_UCS4)(PyUnicode_AS_UNICODE(u)[i])) - #define __Pyx_PyUnicode_MAX_CHAR_VALUE(u) ((sizeof(Py_UNICODE) == 2) ? 65535 : 1114111) - #define __Pyx_PyUnicode_KIND(u) (sizeof(Py_UNICODE)) - #define __Pyx_PyUnicode_DATA(u) ((void*)PyUnicode_AS_UNICODE(u)) - #define __Pyx_PyUnicode_READ(k, d, i) ((void)(k), (Py_UCS4)(((Py_UNICODE*)d)[i])) - #define __Pyx_PyUnicode_WRITE(k, d, i, ch) (((void)(k)), ((Py_UNICODE*)d)[i] = ch) - #define __Pyx_PyUnicode_IS_TRUE(u) (0 != PyUnicode_GET_SIZE(u)) -#endif -#if CYTHON_COMPILING_IN_PYPY - #define __Pyx_PyUnicode_Concat(a, b) PyNumber_Add(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) PyNumber_Add(a, b) -#else - #define __Pyx_PyUnicode_Concat(a, b) PyUnicode_Concat(a, b) - #define __Pyx_PyUnicode_ConcatSafe(a, b) ((unlikely((a) == Py_None) || unlikely((b) == Py_None)) ?\ - PyNumber_Add(a, b) : __Pyx_PyUnicode_Concat(a, b)) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyUnicode_Contains) - #define PyUnicode_Contains(u, s) PySequence_Contains(u, s) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyByteArray_Check) - #define PyByteArray_Check(obj) PyObject_TypeCheck(obj, &PyByteArray_Type) -#endif -#if CYTHON_COMPILING_IN_PYPY && !defined(PyObject_Format) - #define PyObject_Format(obj, fmt) PyObject_CallMethod(obj, "__format__", "O", fmt) -#endif -#define __Pyx_PyString_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyString_Check(b) && !PyString_CheckExact(b)))) ? PyNumber_Remainder(a, b) : __Pyx_PyString_Format(a, b)) -#define __Pyx_PyUnicode_FormatSafe(a, b) ((unlikely((a) == Py_None || (PyUnicode_Check(b) && !PyUnicode_CheckExact(b)))) ? 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-value : value) -#endif -static CYTHON_INLINE const char* __Pyx_PyObject_AsString(PyObject*); -static CYTHON_INLINE const char* __Pyx_PyObject_AsStringAndSize(PyObject*, Py_ssize_t* length); -#define __Pyx_PyByteArray_FromString(s) PyByteArray_FromStringAndSize((const char*)s, strlen((const char*)s)) -#define __Pyx_PyByteArray_FromStringAndSize(s, l) PyByteArray_FromStringAndSize((const char*)s, l) -#define __Pyx_PyBytes_FromString PyBytes_FromString -#define __Pyx_PyBytes_FromStringAndSize PyBytes_FromStringAndSize -static CYTHON_INLINE PyObject* __Pyx_PyUnicode_FromString(const char*); -#if PY_MAJOR_VERSION < 3 - #define __Pyx_PyStr_FromString __Pyx_PyBytes_FromString - #define __Pyx_PyStr_FromStringAndSize __Pyx_PyBytes_FromStringAndSize -#else - #define __Pyx_PyStr_FromString __Pyx_PyUnicode_FromString - #define __Pyx_PyStr_FromStringAndSize __Pyx_PyUnicode_FromStringAndSize -#endif -#define __Pyx_PyBytes_AsWritableString(s) ((char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsWritableSString(s) ((signed char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsWritableUString(s) ((unsigned char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsString(s) ((const char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsSString(s) ((const signed char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyBytes_AsUString(s) ((const unsigned char*) PyBytes_AS_STRING(s)) -#define __Pyx_PyObject_AsWritableString(s) ((char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsWritableSString(s) ((signed char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsWritableUString(s) ((unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsSString(s) ((const signed char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_AsUString(s) ((const unsigned char*) __Pyx_PyObject_AsString(s)) -#define __Pyx_PyObject_FromCString(s) __Pyx_PyObject_FromString((const char*)s) -#define __Pyx_PyBytes_FromCString(s) __Pyx_PyBytes_FromString((const char*)s) -#define __Pyx_PyByteArray_FromCString(s) __Pyx_PyByteArray_FromString((const char*)s) -#define __Pyx_PyStr_FromCString(s) __Pyx_PyStr_FromString((const char*)s) -#define __Pyx_PyUnicode_FromCString(s) __Pyx_PyUnicode_FromString((const char*)s) -static CYTHON_INLINE size_t __Pyx_Py_UNICODE_strlen(const Py_UNICODE *u) { - const Py_UNICODE *u_end = u; - while (*u_end++) ; - return (size_t)(u_end - u - 1); -} -#define __Pyx_PyUnicode_FromUnicode(u) PyUnicode_FromUnicode(u, __Pyx_Py_UNICODE_strlen(u)) -#define __Pyx_PyUnicode_FromUnicodeAndLength PyUnicode_FromUnicode -#define __Pyx_PyUnicode_AsUnicode PyUnicode_AsUnicode -#define __Pyx_NewRef(obj) (Py_INCREF(obj), obj) -#define __Pyx_Owned_Py_None(b) __Pyx_NewRef(Py_None) -static CYTHON_INLINE PyObject * __Pyx_PyBool_FromLong(long b); -static CYTHON_INLINE int __Pyx_PyObject_IsTrue(PyObject*); -static CYTHON_INLINE int __Pyx_PyObject_IsTrueAndDecref(PyObject*); -static CYTHON_INLINE PyObject* __Pyx_PyNumber_IntOrLong(PyObject* x); -#define __Pyx_PySequence_Tuple(obj)\ - (likely(PyTuple_CheckExact(obj)) ? __Pyx_NewRef(obj) : PySequence_Tuple(obj)) -static CYTHON_INLINE Py_ssize_t __Pyx_PyIndex_AsSsize_t(PyObject*); -static CYTHON_INLINE PyObject * __Pyx_PyInt_FromSize_t(size_t); -static CYTHON_INLINE Py_hash_t __Pyx_PyIndex_AsHash_t(PyObject*); -#if CYTHON_ASSUME_SAFE_MACROS -#define __pyx_PyFloat_AsDouble(x) (PyFloat_CheckExact(x) ? PyFloat_AS_DOUBLE(x) : PyFloat_AsDouble(x)) -#else -#define __pyx_PyFloat_AsDouble(x) PyFloat_AsDouble(x) -#endif -#define __pyx_PyFloat_AsFloat(x) ((float) __pyx_PyFloat_AsDouble(x)) -#if PY_MAJOR_VERSION >= 3 -#define __Pyx_PyNumber_Int(x) (PyLong_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Long(x)) -#else -#define __Pyx_PyNumber_Int(x) (PyInt_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Int(x)) -#endif -#define __Pyx_PyNumber_Float(x) (PyFloat_CheckExact(x) ? __Pyx_NewRef(x) : PyNumber_Float(x)) -#if PY_MAJOR_VERSION < 3 && __PYX_DEFAULT_STRING_ENCODING_IS_ASCII -static int __Pyx_sys_getdefaultencoding_not_ascii; -static int __Pyx_init_sys_getdefaultencoding_params(void) { - PyObject* sys; - PyObject* default_encoding = NULL; - PyObject* ascii_chars_u = NULL; - PyObject* ascii_chars_b = NULL; - const char* default_encoding_c; - sys = PyImport_ImportModule("sys"); - if (!sys) goto bad; - default_encoding = PyObject_CallMethod(sys, (char*) "getdefaultencoding", NULL); - Py_DECREF(sys); - if (!default_encoding) goto bad; - default_encoding_c = PyBytes_AsString(default_encoding); - if (!default_encoding_c) goto bad; - if (strcmp(default_encoding_c, "ascii") == 0) { - __Pyx_sys_getdefaultencoding_not_ascii = 0; - } else { - char ascii_chars[128]; - int c; - for (c = 0; c < 128; c++) { - ascii_chars[c] = c; - } - __Pyx_sys_getdefaultencoding_not_ascii = 1; - ascii_chars_u = PyUnicode_DecodeASCII(ascii_chars, 128, NULL); - if (!ascii_chars_u) goto bad; - ascii_chars_b = PyUnicode_AsEncodedString(ascii_chars_u, default_encoding_c, NULL); - if (!ascii_chars_b || !PyBytes_Check(ascii_chars_b) || memcmp(ascii_chars, PyBytes_AS_STRING(ascii_chars_b), 128) != 0) { - PyErr_Format( - PyExc_ValueError, - "This module compiled with c_string_encoding=ascii, but default encoding '%.200s' is not a superset of ascii.", - default_encoding_c); - goto bad; - } - Py_DECREF(ascii_chars_u); - Py_DECREF(ascii_chars_b); - } - Py_DECREF(default_encoding); - return 0; -bad: - Py_XDECREF(default_encoding); - Py_XDECREF(ascii_chars_u); 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-static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_PyErr_SetNone(exc) (Py_INCREF(exc), __Pyx_ErrRestore((exc), NULL, NULL)) -#else -#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) -#endif -#else -#define __Pyx_PyErr_Clear() PyErr_Clear() -#define __Pyx_PyErr_SetNone(exc) PyErr_SetNone(exc) -#define __Pyx_ErrRestoreWithState(type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetchWithState(type, value, tb) PyErr_Fetch(type, value, tb) -#define __Pyx_ErrRestoreInState(tstate, type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetchInState(tstate, type, value, tb) PyErr_Fetch(type, value, tb) -#define __Pyx_ErrRestore(type, value, tb) PyErr_Restore(type, value, tb) -#define __Pyx_ErrFetch(type, value, tb) PyErr_Fetch(type, value, tb) -#endif - -#define __Pyx_BufPtrStrided2d(type, buf, i0, s0, i1, s1) (type)((char*)buf + i0 * s0 + i1 * s1) -/* RaiseArgTupleInvalid.proto */ -static void __Pyx_RaiseArgtupleInvalid(const char* func_name, int exact, - Py_ssize_t num_min, Py_ssize_t num_max, Py_ssize_t num_found); - -/* RaiseDoubleKeywords.proto */ -static void __Pyx_RaiseDoubleKeywordsError(const char* func_name, PyObject* kw_name); - -/* ParseKeywords.proto */ -static int __Pyx_ParseOptionalKeywords(PyObject *kwds, PyObject **argnames[],\ - PyObject *kwds2, PyObject *values[], Py_ssize_t num_pos_args,\ - const char* function_name); - -/* GetTopmostException.proto */ -#if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * __Pyx_PyErr_GetTopmostException(PyThreadState *tstate); -#endif - -/* SaveResetException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_ExceptionSave(type, value, tb) __Pyx__ExceptionSave(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#define __Pyx_ExceptionReset(type, value, tb) __Pyx__ExceptionReset(__pyx_tstate, type, value, tb) -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb); -#else -#define __Pyx_ExceptionSave(type, value, tb) PyErr_GetExcInfo(type, value, tb) -#define __Pyx_ExceptionReset(type, value, tb) PyErr_SetExcInfo(type, value, tb) -#endif - -/* PyErrExceptionMatches.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_PyErr_ExceptionMatches(err) __Pyx_PyErr_ExceptionMatchesInState(__pyx_tstate, err) -static CYTHON_INLINE int __Pyx_PyErr_ExceptionMatchesInState(PyThreadState* tstate, PyObject* err); -#else -#define __Pyx_PyErr_ExceptionMatches(err) PyErr_ExceptionMatches(err) -#endif - -/* GetException.proto */ -#if CYTHON_FAST_THREAD_STATE -#define __Pyx_GetException(type, value, tb) __Pyx__GetException(__pyx_tstate, type, value, tb) -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb); -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb); -#endif - -/* RaiseException.proto */ -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause); - -/* TypeImport.proto */ -#ifndef __PYX_HAVE_RT_ImportType_proto -#define __PYX_HAVE_RT_ImportType_proto -enum __Pyx_ImportType_CheckSize { - __Pyx_ImportType_CheckSize_Error = 0, - __Pyx_ImportType_CheckSize_Warn = 1, - __Pyx_ImportType_CheckSize_Ignore = 2 -}; -static PyTypeObject *__Pyx_ImportType(PyObject* module, const char *module_name, const char *class_name, size_t size, enum __Pyx_ImportType_CheckSize check_size); -#endif - -/* Import.proto */ -static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level); - -/* CLineInTraceback.proto */ -#ifdef CYTHON_CLINE_IN_TRACEBACK -#define __Pyx_CLineForTraceback(tstate, c_line) (((CYTHON_CLINE_IN_TRACEBACK)) ? c_line : 0) -#else -static int __Pyx_CLineForTraceback(PyThreadState *tstate, int c_line); -#endif - -/* CodeObjectCache.proto */ -typedef struct { - PyCodeObject* code_object; - int code_line; -} __Pyx_CodeObjectCacheEntry; -struct __Pyx_CodeObjectCache { - int count; - int max_count; - __Pyx_CodeObjectCacheEntry* entries; -}; -static struct __Pyx_CodeObjectCache __pyx_code_cache = {0,0,NULL}; -static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line); -static PyCodeObject *__pyx_find_code_object(int code_line); -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object); - -/* AddTraceback.proto */ -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename); - -/* BufferStructDeclare.proto */ -typedef struct { - Py_ssize_t shape, strides, suboffsets; -} __Pyx_Buf_DimInfo; -typedef struct { - size_t refcount; - Py_buffer pybuffer; -} __Pyx_Buffer; -typedef struct { - __Pyx_Buffer *rcbuffer; - char *data; - __Pyx_Buf_DimInfo diminfo[8]; -} __Pyx_LocalBuf_ND; - -#if PY_MAJOR_VERSION < 3 - static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags); - static void __Pyx_ReleaseBuffer(Py_buffer *view); -#else - #define __Pyx_GetBuffer PyObject_GetBuffer - #define __Pyx_ReleaseBuffer PyBuffer_Release -#endif - - -/* GCCDiagnostics.proto */ -#if defined(__GNUC__) && (__GNUC__ > 4 || (__GNUC__ == 4 && __GNUC_MINOR__ >= 6)) -#define __Pyx_HAS_GCC_DIAGNOSTIC -#endif - -/* RealImag.proto */ -#if CYTHON_CCOMPLEX - #ifdef __cplusplus - #define __Pyx_CREAL(z) ((z).real()) - #define __Pyx_CIMAG(z) ((z).imag()) - #else - #define __Pyx_CREAL(z) (__real__(z)) - #define __Pyx_CIMAG(z) (__imag__(z)) - #endif -#else - #define __Pyx_CREAL(z) ((z).real) - #define __Pyx_CIMAG(z) ((z).imag) -#endif -#if defined(__cplusplus) && CYTHON_CCOMPLEX\ - && (defined(_WIN32) || defined(__clang__) || (defined(__GNUC__) && (__GNUC__ >= 5 || __GNUC__ == 4 && __GNUC_MINOR__ >= 4 )) || __cplusplus >= 201103) - #define __Pyx_SET_CREAL(z,x) ((z).real(x)) - #define __Pyx_SET_CIMAG(z,y) ((z).imag(y)) -#else - #define __Pyx_SET_CREAL(z,x) __Pyx_CREAL(z) = (x) - #define __Pyx_SET_CIMAG(z,y) __Pyx_CIMAG(z) = (y) -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_float(a, b) ((a)==(b)) - #define __Pyx_c_sum_float(a, b) ((a)+(b)) - #define __Pyx_c_diff_float(a, b) ((a)-(b)) - #define __Pyx_c_prod_float(a, b) ((a)*(b)) - #define __Pyx_c_quot_float(a, b) ((a)/(b)) - #define __Pyx_c_neg_float(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_float(z) ((z)==(float)0) - #define __Pyx_c_conj_float(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_float(z) (::std::abs(z)) - #define __Pyx_c_pow_float(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_float(z) ((z)==0) - #define __Pyx_c_conj_float(z) (conjf(z)) - #if 1 - #define __Pyx_c_abs_float(z) (cabsf(z)) - #define __Pyx_c_pow_float(a, b) (cpowf(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex, __pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex); - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex); - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex, __pyx_t_float_complex); - #endif -#endif - -/* Arithmetic.proto */ -#if CYTHON_CCOMPLEX - #define __Pyx_c_eq_double(a, b) ((a)==(b)) - #define __Pyx_c_sum_double(a, b) ((a)+(b)) - #define __Pyx_c_diff_double(a, b) ((a)-(b)) - #define __Pyx_c_prod_double(a, b) ((a)*(b)) - #define __Pyx_c_quot_double(a, b) ((a)/(b)) - #define __Pyx_c_neg_double(a) (-(a)) - #ifdef __cplusplus - #define __Pyx_c_is_zero_double(z) ((z)==(double)0) - #define __Pyx_c_conj_double(z) (::std::conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (::std::abs(z)) - #define __Pyx_c_pow_double(a, b) (::std::pow(a, b)) - #endif - #else - #define __Pyx_c_is_zero_double(z) ((z)==0) - #define __Pyx_c_conj_double(z) (conj(z)) - #if 1 - #define __Pyx_c_abs_double(z) (cabs(z)) - #define __Pyx_c_pow_double(a, b) (cpow(a, b)) - #endif - #endif -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex, __pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex); - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex); - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex); - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex, __pyx_t_double_complex); - #endif -#endif - -/* CIntFromPy.proto */ -static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *); - -/* CIntToPy.proto */ -static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value); - -/* CIntFromPy.proto */ -static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *); - -/* FastTypeChecks.proto */ -#if CYTHON_COMPILING_IN_CPYTHON -#define __Pyx_TypeCheck(obj, type) __Pyx_IsSubtype(Py_TYPE(obj), (PyTypeObject *)type) -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches(PyObject *err, PyObject *type); -static CYTHON_INLINE int __Pyx_PyErr_GivenExceptionMatches2(PyObject *err, PyObject *type1, PyObject *type2); -#else -#define __Pyx_TypeCheck(obj, type) PyObject_TypeCheck(obj, (PyTypeObject *)type) -#define __Pyx_PyErr_GivenExceptionMatches(err, type) PyErr_GivenExceptionMatches(err, type) -#define __Pyx_PyErr_GivenExceptionMatches2(err, type1, type2) (PyErr_GivenExceptionMatches(err, type1) || PyErr_GivenExceptionMatches(err, type2)) -#endif -#define __Pyx_PyException_Check(obj) __Pyx_TypeCheck(obj, PyExc_Exception) - -/* CheckBinaryVersion.proto */ -static int __Pyx_check_binary_version(void); - -/* InitStrings.proto */ -static int __Pyx_InitStrings(__Pyx_StringTabEntry *t); - - -/* Module declarations from 'cpython.buffer' */ - -/* Module declarations from 'libc.string' */ - -/* Module declarations from 'libc.stdio' */ - -/* Module declarations from '__builtin__' */ - -/* Module declarations from 'cpython.type' */ -static PyTypeObject *__pyx_ptype_7cpython_4type_type = 0; - -/* Module declarations from 'cpython' */ - -/* Module declarations from 'cpython.object' */ - -/* Module declarations from 'cpython.ref' */ - -/* Module declarations from 'cpython.mem' */ - -/* Module declarations from 'numpy' */ - -/* Module declarations from 'numpy' */ -static PyTypeObject *__pyx_ptype_5numpy_dtype = 0; -static PyTypeObject *__pyx_ptype_5numpy_flatiter = 0; -static PyTypeObject *__pyx_ptype_5numpy_broadcast = 0; -static PyTypeObject *__pyx_ptype_5numpy_ndarray = 0; -static PyTypeObject *__pyx_ptype_5numpy_generic = 0; -static PyTypeObject *__pyx_ptype_5numpy_number = 0; -static PyTypeObject *__pyx_ptype_5numpy_integer = 0; -static PyTypeObject *__pyx_ptype_5numpy_signedinteger = 0; -static PyTypeObject *__pyx_ptype_5numpy_unsignedinteger = 0; -static PyTypeObject *__pyx_ptype_5numpy_inexact = 0; -static PyTypeObject *__pyx_ptype_5numpy_floating = 0; -static PyTypeObject *__pyx_ptype_5numpy_complexfloating = 0; -static PyTypeObject *__pyx_ptype_5numpy_flexible = 0; -static PyTypeObject *__pyx_ptype_5numpy_character = 0; -static PyTypeObject *__pyx_ptype_5numpy_ufunc = 0; - -/* Module declarations from 'libcpp.string' */ - -/* Module declarations from 'wrapper' */ -static CYTHON_INLINE PyObject *__pyx_convert_PyObject_string_to_py_std__in_string(std::string const &); /*proto*/ -static CYTHON_INLINE PyObject *__pyx_convert_PyUnicode_string_to_py_std__in_string(std::string const &); /*proto*/ -static CYTHON_INLINE PyObject *__pyx_convert_PyStr_string_to_py_std__in_string(std::string const &); /*proto*/ -static CYTHON_INLINE PyObject *__pyx_convert_PyBytes_string_to_py_std__in_string(std::string const &); /*proto*/ -static CYTHON_INLINE PyObject *__pyx_convert_PyByteArray_string_to_py_std__in_string(std::string const &); /*proto*/ -static __Pyx_TypeInfo __Pyx_TypeInfo_nn___pyx_t_5numpy_double_t = { "double_t", NULL, sizeof(__pyx_t_5numpy_double_t), { 0 }, 0, 'R', 0, 0 }; -#define __Pyx_MODULE_NAME "wrapper" -extern int __pyx_module_is_main_wrapper; -int __pyx_module_is_main_wrapper = 0; - -/* Implementation of 'wrapper' */ -static PyObject *__pyx_builtin_ImportError; -static const char __pyx_k_np[] = "np"; -static const char __pyx_k_main[] = "__main__"; -static const char __pyx_k_name[] = "__name__"; -static const char __pyx_k_test[] = "__test__"; -static const char __pyx_k_array[] = "array"; -static const char __pyx_k_flags[] = "flags"; -static const char __pyx_k_image[] = "image"; -static const char __pyx_k_numpy[] = "numpy"; -static const char __pyx_k_import[] = "__import__"; -static const char __pyx_k_wrapper[] = "wrapper"; -static const char __pyx_k_iteration[] = "iteration"; -static const char __pyx_k_verbosity[] = "verbosity"; -static const char __pyx_k_cy_add_cti[] = "cy_add_cti"; -static const char __pyx_k_ImportError[] = "ImportError"; -static const char __pyx_k_C_CONTIGUOUS[] = "C_CONTIGUOUS"; -static const char __pyx_k_cy_print_array[] = "cy_print_array"; -static const char __pyx_k_serial_express[] = "serial_express"; -static const char __pyx_k_serial_n_pumps[] = "serial_n_pumps"; -static const char __pyx_k_serial_roe_type[] = "serial_roe_type"; -static const char __pyx_k_check_contiguous[] = "check_contiguous"; -static const char __pyx_k_cy_print_version[] = "cy_print_version"; -static const char __pyx_k_parallel_express[] = "parallel_express"; -static const char __pyx_k_parallel_n_pumps[] = "parallel_n_pumps"; -static const char __pyx_k_serial_time_stop[] = "serial_time_stop"; -static const char __pyx_k_ascontiguousarray[] = "ascontiguousarray"; -static const char __pyx_k_cy_print_array_2D[] = "cy_print_array_2D"; -static const char __pyx_k_cy_version_arctic[] = "cy_version_arctic"; -static const char __pyx_k_parallel_roe_type[] = "parallel_roe_type"; -static const char __pyx_k_serial_n_traps_ic[] = "serial_n_traps_ic"; -static const char __pyx_k_serial_n_traps_sc[] = "serial_n_traps_sc"; -static const char __pyx_k_serial_time_start[] = "serial_time_start"; -static const char __pyx_k_cline_in_traceback[] = "cline_in_traceback"; -static const char __pyx_k_parallel_time_stop[] = "parallel_time_stop"; -static const char __pyx_k_serial_dwell_times[] = "serial_dwell_times"; -static const char __pyx_k_serial_window_stop[] = "serial_window_stop"; -static const char __pyx_k_parallel_n_traps_ic[] = "parallel_n_traps_ic"; -static const char __pyx_k_parallel_n_traps_sc[] = "parallel_n_traps_sc"; -static const char __pyx_k_parallel_time_start[] = "parallel_time_start"; -static const char __pyx_k_serial_window_start[] = "serial_window_start"; -static const char __pyx_k_parallel_dwell_times[] = "parallel_dwell_times"; -static const char __pyx_k_parallel_window_stop[] = "parallel_window_stop"; -static const char __pyx_k_serial_n_traps_ic_co[] = "serial_n_traps_ic_co"; -static const char __pyx_k_serial_n_traps_sc_co[] = "serial_n_traps_sc_co"; 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- Py_INCREF(k[i+1]); - i += 2; - } - nk = i / 2; - } - else { - kwtuple = NULL; - k = NULL; - } - closure = PyFunction_GET_CLOSURE(func); -#if PY_MAJOR_VERSION >= 3 - kwdefs = PyFunction_GET_KW_DEFAULTS(func); -#endif - if (argdefs != NULL) { - d = &PyTuple_GET_ITEM(argdefs, 0); - nd = Py_SIZE(argdefs); - } - else { - d = NULL; - nd = 0; - } -#if PY_MAJOR_VERSION >= 3 - result = PyEval_EvalCodeEx((PyObject*)co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, kwdefs, closure); -#else - result = PyEval_EvalCodeEx(co, globals, (PyObject *)NULL, - args, (int)nargs, - k, (int)nk, - d, (int)nd, closure); -#endif - Py_XDECREF(kwtuple); -done: - Py_LeaveRecursiveCall(); - return result; -} -#endif -#endif - -/* PyObjectCall */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) { - PyObject *result; - ternaryfunc call = Py_TYPE(func)->tp_call; - if (unlikely(!call)) - return PyObject_Call(func, arg, kw); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = (*call)(func, arg, kw); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCall2Args */ -static CYTHON_UNUSED PyObject* __Pyx_PyObject_Call2Args(PyObject* function, PyObject* arg1, PyObject* arg2) { - PyObject *args, *result = NULL; - #if CYTHON_FAST_PYCALL - if (PyFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyFunction_FastCall(function, args, 2); - } - #endif - #if CYTHON_FAST_PYCCALL - if (__Pyx_PyFastCFunction_Check(function)) { - PyObject *args[2] = {arg1, arg2}; - return __Pyx_PyCFunction_FastCall(function, args, 2); - } - #endif - args = PyTuple_New(2); - if (unlikely(!args)) goto done; - Py_INCREF(arg1); - PyTuple_SET_ITEM(args, 0, arg1); - Py_INCREF(arg2); - PyTuple_SET_ITEM(args, 1, arg2); - Py_INCREF(function); - result = __Pyx_PyObject_Call(function, args, NULL); - Py_DECREF(args); - Py_DECREF(function); -done: - return result; -} - -/* PyObjectCallMethO */ -#if CYTHON_COMPILING_IN_CPYTHON -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallMethO(PyObject *func, PyObject *arg) { - PyObject *self, *result; - PyCFunction cfunc; - cfunc = PyCFunction_GET_FUNCTION(func); - self = PyCFunction_GET_SELF(func); - if (unlikely(Py_EnterRecursiveCall((char*)" while calling a Python object"))) - return NULL; - result = cfunc(self, arg); - Py_LeaveRecursiveCall(); - if (unlikely(!result) && unlikely(!PyErr_Occurred())) { - PyErr_SetString( - PyExc_SystemError, - "NULL result without error in PyObject_Call"); - } - return result; -} -#endif - -/* PyObjectCallOneArg */ -#if CYTHON_COMPILING_IN_CPYTHON -static PyObject* __Pyx__PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_New(1); - if (unlikely(!args)) return NULL; - Py_INCREF(arg); - PyTuple_SET_ITEM(args, 0, arg); - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { -#if CYTHON_FAST_PYCALL - if (PyFunction_Check(func)) { - return __Pyx_PyFunction_FastCall(func, &arg, 1); - } -#endif - if (likely(PyCFunction_Check(func))) { - if (likely(PyCFunction_GET_FLAGS(func) & METH_O)) { - return __Pyx_PyObject_CallMethO(func, arg); -#if CYTHON_FAST_PYCCALL - } else if (__Pyx_PyFastCFunction_Check(func)) { - return __Pyx_PyCFunction_FastCall(func, &arg, 1); -#endif - } - } - return __Pyx__PyObject_CallOneArg(func, arg); -} -#else -static CYTHON_INLINE PyObject* __Pyx_PyObject_CallOneArg(PyObject *func, PyObject *arg) { - PyObject *result; - PyObject *args = PyTuple_Pack(1, arg); - if (unlikely(!args)) return NULL; - result = __Pyx_PyObject_Call(func, args, NULL); - Py_DECREF(args); - return result; -} -#endif - -/* ArgTypeTest */ -static int __Pyx__ArgTypeTest(PyObject *obj, PyTypeObject *type, const char *name, int exact) -{ - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - else if (exact) { - #if PY_MAJOR_VERSION == 2 - if ((type == &PyBaseString_Type) && likely(__Pyx_PyBaseString_CheckExact(obj))) return 1; - #endif - } - else { - if (likely(__Pyx_TypeCheck(obj, type))) return 1; - } - PyErr_Format(PyExc_TypeError, - "Argument '%.200s' has incorrect type (expected %.200s, got %.200s)", - name, type->tp_name, Py_TYPE(obj)->tp_name); - return 0; -} - -/* IsLittleEndian */ -static CYTHON_INLINE int __Pyx_Is_Little_Endian(void) -{ - union { - uint32_t u32; - uint8_t u8[4]; - } S; - S.u32 = 0x01020304; - return S.u8[0] == 4; -} - -/* BufferFormatCheck */ -static void __Pyx_BufFmt_Init(__Pyx_BufFmt_Context* ctx, - __Pyx_BufFmt_StackElem* stack, - __Pyx_TypeInfo* type) { - stack[0].field = &ctx->root; - stack[0].parent_offset = 0; - ctx->root.type = type; - ctx->root.name = "buffer dtype"; - ctx->root.offset = 0; - ctx->head = stack; - ctx->head->field = &ctx->root; - ctx->fmt_offset = 0; - ctx->head->parent_offset = 0; - ctx->new_packmode = '@'; - ctx->enc_packmode = '@'; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->is_complex = 0; - ctx->is_valid_array = 0; - ctx->struct_alignment = 0; - while (type->typegroup == 'S') { - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = 0; - type = type->fields->type; - } -} -static int __Pyx_BufFmt_ParseNumber(const char** ts) { - int count; - const char* t = *ts; - if (*t < '0' || *t > '9') { - return -1; - } else { - count = *t++ - '0'; - while (*t >= '0' && *t <= '9') { - count *= 10; - count += *t++ - '0'; - } - } - *ts = t; - return count; -} -static int __Pyx_BufFmt_ExpectNumber(const char **ts) { - int number = __Pyx_BufFmt_ParseNumber(ts); - if (number == -1) - PyErr_Format(PyExc_ValueError,\ - "Does not understand character buffer dtype format string ('%c')", **ts); - return number; -} -static void __Pyx_BufFmt_RaiseUnexpectedChar(char ch) { - PyErr_Format(PyExc_ValueError, - "Unexpected format string character: '%c'", ch); -} -static const char* __Pyx_BufFmt_DescribeTypeChar(char ch, int is_complex) { - switch (ch) { - case '?': return "'bool'"; - case 'c': return "'char'"; - case 'b': return "'signed char'"; - case 'B': return "'unsigned char'"; - case 'h': return "'short'"; - case 'H': return "'unsigned short'"; - case 'i': return "'int'"; - case 'I': return "'unsigned int'"; - case 'l': return "'long'"; - case 'L': return "'unsigned long'"; - case 'q': return "'long long'"; - case 'Q': return "'unsigned long long'"; - case 'f': return (is_complex ? "'complex float'" : "'float'"); - case 'd': return (is_complex ? "'complex double'" : "'double'"); - case 'g': return (is_complex ? "'complex long double'" : "'long double'"); - case 'T': return "a struct"; - case 'O': return "Python object"; - case 'P': return "a pointer"; - case 's': case 'p': return "a string"; - case 0: return "end"; - default: return "unparseable format string"; - } -} -static size_t __Pyx_BufFmt_TypeCharToStandardSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return 2; - case 'i': case 'I': case 'l': case 'L': return 4; - case 'q': case 'Q': return 8; - case 'f': return (is_complex ? 8 : 4); - case 'd': return (is_complex ? 16 : 8); - case 'g': { - PyErr_SetString(PyExc_ValueError, "Python does not define a standard format string size for long double ('g').."); - return 0; - } - case 'O': case 'P': return sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static size_t __Pyx_BufFmt_TypeCharToNativeSize(char ch, int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(short); - case 'i': case 'I': return sizeof(int); - case 'l': case 'L': return sizeof(long); - #ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(PY_LONG_LONG); - #endif - case 'f': return sizeof(float) * (is_complex ? 2 : 1); - case 'd': return sizeof(double) * (is_complex ? 2 : 1); - case 'g': return sizeof(long double) * (is_complex ? 2 : 1); - case 'O': case 'P': return sizeof(void*); - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -typedef struct { char c; short x; } __Pyx_st_short; -typedef struct { char c; int x; } __Pyx_st_int; -typedef struct { char c; long x; } __Pyx_st_long; -typedef struct { char c; float x; } __Pyx_st_float; -typedef struct { char c; double x; } __Pyx_st_double; -typedef struct { char c; long double x; } __Pyx_st_longdouble; -typedef struct { char c; void *x; } __Pyx_st_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { char c; PY_LONG_LONG x; } __Pyx_st_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToAlignment(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_st_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_st_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_st_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_st_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_st_float) - sizeof(float); - case 'd': return sizeof(__Pyx_st_double) - sizeof(double); - case 'g': return sizeof(__Pyx_st_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_st_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -/* These are for computing the padding at the end of the struct to align - on the first member of the struct. This will probably the same as above, - but we don't have any guarantees. - */ -typedef struct { short x; char c; } __Pyx_pad_short; -typedef struct { int x; char c; } __Pyx_pad_int; -typedef struct { long x; char c; } __Pyx_pad_long; -typedef struct { float x; char c; } __Pyx_pad_float; -typedef struct { double x; char c; } __Pyx_pad_double; -typedef struct { long double x; char c; } __Pyx_pad_longdouble; -typedef struct { void *x; char c; } __Pyx_pad_void_p; -#ifdef HAVE_LONG_LONG -typedef struct { PY_LONG_LONG x; char c; } __Pyx_pad_longlong; -#endif -static size_t __Pyx_BufFmt_TypeCharToPadding(char ch, CYTHON_UNUSED int is_complex) { - switch (ch) { - case '?': case 'c': case 'b': case 'B': case 's': case 'p': return 1; - case 'h': case 'H': return sizeof(__Pyx_pad_short) - sizeof(short); - case 'i': case 'I': return sizeof(__Pyx_pad_int) - sizeof(int); - case 'l': case 'L': return sizeof(__Pyx_pad_long) - sizeof(long); -#ifdef HAVE_LONG_LONG - case 'q': case 'Q': return sizeof(__Pyx_pad_longlong) - sizeof(PY_LONG_LONG); -#endif - case 'f': return sizeof(__Pyx_pad_float) - sizeof(float); - case 'd': return sizeof(__Pyx_pad_double) - sizeof(double); - case 'g': return sizeof(__Pyx_pad_longdouble) - sizeof(long double); - case 'P': case 'O': return sizeof(__Pyx_pad_void_p) - sizeof(void*); - default: - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } -} -static char __Pyx_BufFmt_TypeCharToGroup(char ch, int is_complex) { - switch (ch) { - case 'c': - return 'H'; - case 'b': case 'h': case 'i': - case 'l': case 'q': case 's': case 'p': - return 'I'; - case '?': case 'B': case 'H': case 'I': case 'L': case 'Q': - return 'U'; - case 'f': case 'd': case 'g': - return (is_complex ? 'C' : 'R'); - case 'O': - return 'O'; - case 'P': - return 'P'; - default: { - __Pyx_BufFmt_RaiseUnexpectedChar(ch); - return 0; - } - } -} -static void __Pyx_BufFmt_RaiseExpected(__Pyx_BufFmt_Context* ctx) { - if (ctx->head == NULL || ctx->head->field == &ctx->root) { - const char* expected; - const char* quote; - if (ctx->head == NULL) { - expected = "end"; - quote = ""; - } else { - expected = ctx->head->field->type->name; - quote = "'"; - } - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected %s%s%s but got %s", - quote, expected, quote, - __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex)); - } else { - __Pyx_StructField* field = ctx->head->field; - __Pyx_StructField* parent = (ctx->head - 1)->field; - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch, expected '%s' but got %s in '%s.%s'", - field->type->name, __Pyx_BufFmt_DescribeTypeChar(ctx->enc_type, ctx->is_complex), - parent->type->name, field->name); - } -} -static int __Pyx_BufFmt_ProcessTypeChunk(__Pyx_BufFmt_Context* ctx) { - char group; - size_t size, offset, arraysize = 1; - if (ctx->enc_type == 0) return 0; - if (ctx->head->field->type->arraysize[0]) { - int i, ndim = 0; - if (ctx->enc_type == 's' || ctx->enc_type == 'p') { - ctx->is_valid_array = ctx->head->field->type->ndim == 1; - ndim = 1; - if (ctx->enc_count != ctx->head->field->type->arraysize[0]) { - PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %zu", - ctx->head->field->type->arraysize[0], ctx->enc_count); - return -1; - } - } - if (!ctx->is_valid_array) { - PyErr_Format(PyExc_ValueError, "Expected %d dimensions, got %d", - ctx->head->field->type->ndim, ndim); - return -1; - } - for (i = 0; i < ctx->head->field->type->ndim; i++) { - arraysize *= ctx->head->field->type->arraysize[i]; - } - ctx->is_valid_array = 0; - ctx->enc_count = 1; - } - group = __Pyx_BufFmt_TypeCharToGroup(ctx->enc_type, ctx->is_complex); - do { - __Pyx_StructField* field = ctx->head->field; - __Pyx_TypeInfo* type = field->type; - if (ctx->enc_packmode == '@' || ctx->enc_packmode == '^') { - size = __Pyx_BufFmt_TypeCharToNativeSize(ctx->enc_type, ctx->is_complex); - } else { - size = __Pyx_BufFmt_TypeCharToStandardSize(ctx->enc_type, ctx->is_complex); - } - if (ctx->enc_packmode == '@') { - size_t align_at = __Pyx_BufFmt_TypeCharToAlignment(ctx->enc_type, ctx->is_complex); - size_t align_mod_offset; - if (align_at == 0) return -1; - align_mod_offset = ctx->fmt_offset % align_at; - if (align_mod_offset > 0) ctx->fmt_offset += align_at - align_mod_offset; - if (ctx->struct_alignment == 0) - ctx->struct_alignment = __Pyx_BufFmt_TypeCharToPadding(ctx->enc_type, - ctx->is_complex); - } - if (type->size != size || type->typegroup != group) { - if (type->typegroup == 'C' && type->fields != NULL) { - size_t parent_offset = ctx->head->parent_offset + field->offset; - ++ctx->head; - ctx->head->field = type->fields; - ctx->head->parent_offset = parent_offset; - continue; - } - if ((type->typegroup == 'H' || group == 'H') && type->size == size) { - } else { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - } - offset = ctx->head->parent_offset + field->offset; - if (ctx->fmt_offset != offset) { - PyErr_Format(PyExc_ValueError, - "Buffer dtype mismatch; next field is at offset %" CYTHON_FORMAT_SSIZE_T "d but %" CYTHON_FORMAT_SSIZE_T "d expected", - (Py_ssize_t)ctx->fmt_offset, (Py_ssize_t)offset); - return -1; - } - ctx->fmt_offset += size; - if (arraysize) - ctx->fmt_offset += (arraysize - 1) * size; - --ctx->enc_count; - while (1) { - if (field == &ctx->root) { - ctx->head = NULL; - if (ctx->enc_count != 0) { - __Pyx_BufFmt_RaiseExpected(ctx); - return -1; - } - break; - } - ctx->head->field = ++field; - if (field->type == NULL) { - --ctx->head; - field = ctx->head->field; - continue; - } else if (field->type->typegroup == 'S') { - size_t parent_offset = ctx->head->parent_offset + field->offset; - if (field->type->fields->type == NULL) continue; - field = field->type->fields; - ++ctx->head; - ctx->head->field = field; - ctx->head->parent_offset = parent_offset; - break; - } else { - break; - } - } - } while (ctx->enc_count); - ctx->enc_type = 0; - ctx->is_complex = 0; - return 0; -} -static PyObject * -__pyx_buffmt_parse_array(__Pyx_BufFmt_Context* ctx, const char** tsp) -{ - const char *ts = *tsp; - int i = 0, number, ndim; - ++ts; - if (ctx->new_count != 1) { - PyErr_SetString(PyExc_ValueError, - "Cannot handle repeated arrays in format string"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ndim = ctx->head->field->type->ndim; - while (*ts && *ts != ')') { - switch (*ts) { - case ' ': case '\f': case '\r': case '\n': case '\t': case '\v': continue; - default: break; - } - number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - if (i < ndim && (size_t) number != ctx->head->field->type->arraysize[i]) - return PyErr_Format(PyExc_ValueError, - "Expected a dimension of size %zu, got %d", - ctx->head->field->type->arraysize[i], number); - if (*ts != ',' && *ts != ')') - return PyErr_Format(PyExc_ValueError, - "Expected a comma in format string, got '%c'", *ts); - if (*ts == ',') ts++; - i++; - } - if (i != ndim) - return PyErr_Format(PyExc_ValueError, "Expected %d dimension(s), got %d", - ctx->head->field->type->ndim, i); - if (!*ts) { - PyErr_SetString(PyExc_ValueError, - "Unexpected end of format string, expected ')'"); - return NULL; - } - ctx->is_valid_array = 1; - ctx->new_count = 1; - *tsp = ++ts; - return Py_None; -} -static const char* __Pyx_BufFmt_CheckString(__Pyx_BufFmt_Context* ctx, const char* ts) { - int got_Z = 0; - while (1) { - switch(*ts) { - case 0: - if (ctx->enc_type != 0 && ctx->head == NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - if (ctx->head != NULL) { - __Pyx_BufFmt_RaiseExpected(ctx); - return NULL; - } - return ts; - case ' ': - case '\r': - case '\n': - ++ts; - break; - case '<': - if (!__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Little-endian buffer not supported on big-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '>': - case '!': - if (__Pyx_Is_Little_Endian()) { - PyErr_SetString(PyExc_ValueError, "Big-endian buffer not supported on little-endian compiler"); - return NULL; - } - ctx->new_packmode = '='; - ++ts; - break; - case '=': - case '@': - case '^': - ctx->new_packmode = *ts++; - break; - case 'T': - { - const char* ts_after_sub; - size_t i, struct_count = ctx->new_count; - size_t struct_alignment = ctx->struct_alignment; - ctx->new_count = 1; - ++ts; - if (*ts != '{') { - PyErr_SetString(PyExc_ValueError, "Buffer acquisition: Expected '{' after 'T'"); - return NULL; - } - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - ctx->enc_count = 0; - ctx->struct_alignment = 0; - ++ts; - ts_after_sub = ts; - for (i = 0; i != struct_count; ++i) { - ts_after_sub = __Pyx_BufFmt_CheckString(ctx, ts); - if (!ts_after_sub) return NULL; - } - ts = ts_after_sub; - if (struct_alignment) ctx->struct_alignment = struct_alignment; - } - break; - case '}': - { - size_t alignment = ctx->struct_alignment; - ++ts; - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_type = 0; - if (alignment && ctx->fmt_offset % alignment) { - ctx->fmt_offset += alignment - (ctx->fmt_offset % alignment); - } - } - return ts; - case 'x': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->fmt_offset += ctx->new_count; - ctx->new_count = 1; - ctx->enc_count = 0; - ctx->enc_type = 0; - ctx->enc_packmode = ctx->new_packmode; - ++ts; - break; - case 'Z': - got_Z = 1; - ++ts; - if (*ts != 'f' && *ts != 'd' && *ts != 'g') { - __Pyx_BufFmt_RaiseUnexpectedChar('Z'); - return NULL; - } - CYTHON_FALLTHROUGH; - case '?': case 'c': case 'b': case 'B': case 'h': case 'H': case 'i': case 'I': - case 'l': case 'L': case 'q': case 'Q': - case 'f': case 'd': case 'g': - case 'O': case 'p': - if ((ctx->enc_type == *ts) && (got_Z == ctx->is_complex) && - (ctx->enc_packmode == ctx->new_packmode) && (!ctx->is_valid_array)) { - ctx->enc_count += ctx->new_count; - ctx->new_count = 1; - got_Z = 0; - ++ts; - break; - } - CYTHON_FALLTHROUGH; - case 's': - if (__Pyx_BufFmt_ProcessTypeChunk(ctx) == -1) return NULL; - ctx->enc_count = ctx->new_count; - ctx->enc_packmode = ctx->new_packmode; - ctx->enc_type = *ts; - ctx->is_complex = got_Z; - ++ts; - ctx->new_count = 1; - got_Z = 0; - break; - case ':': - ++ts; - while(*ts != ':') ++ts; - ++ts; - break; - case '(': - if (!__pyx_buffmt_parse_array(ctx, &ts)) return NULL; - break; - default: - { - int number = __Pyx_BufFmt_ExpectNumber(&ts); - if (number == -1) return NULL; - ctx->new_count = (size_t)number; - } - } - } -} - -/* BufferGetAndValidate */ - static CYTHON_INLINE void __Pyx_SafeReleaseBuffer(Py_buffer* info) { - if (unlikely(info->buf == NULL)) return; - if (info->suboffsets == __Pyx_minusones) info->suboffsets = NULL; - __Pyx_ReleaseBuffer(info); -} -static void __Pyx_ZeroBuffer(Py_buffer* buf) { - buf->buf = NULL; - buf->obj = NULL; - buf->strides = __Pyx_zeros; - buf->shape = __Pyx_zeros; - buf->suboffsets = __Pyx_minusones; -} -static int __Pyx__GetBufferAndValidate( - Py_buffer* buf, PyObject* obj, __Pyx_TypeInfo* dtype, int flags, - int nd, int cast, __Pyx_BufFmt_StackElem* stack) -{ - buf->buf = NULL; - if (unlikely(__Pyx_GetBuffer(obj, buf, flags) == -1)) { - __Pyx_ZeroBuffer(buf); - return -1; - } - if (unlikely(buf->ndim != nd)) { - PyErr_Format(PyExc_ValueError, - "Buffer has wrong number of dimensions (expected %d, got %d)", - nd, buf->ndim); - goto fail; - } - if (!cast) { - __Pyx_BufFmt_Context ctx; - __Pyx_BufFmt_Init(&ctx, stack, dtype); - if (!__Pyx_BufFmt_CheckString(&ctx, buf->format)) goto fail; - } - if (unlikely((size_t)buf->itemsize != dtype->size)) { - PyErr_Format(PyExc_ValueError, - "Item size of buffer (%" CYTHON_FORMAT_SSIZE_T "d byte%s) does not match size of '%s' (%" CYTHON_FORMAT_SSIZE_T "d byte%s)", - buf->itemsize, (buf->itemsize > 1) ? "s" : "", - dtype->name, (Py_ssize_t)dtype->size, (dtype->size > 1) ? "s" : ""); - goto fail; - } - if (buf->suboffsets == NULL) buf->suboffsets = __Pyx_minusones; - return 0; -fail:; - __Pyx_SafeReleaseBuffer(buf); - return -1; -} - -/* ExtTypeTest */ - static CYTHON_INLINE int __Pyx_TypeTest(PyObject *obj, PyTypeObject *type) { - if (unlikely(!type)) { - PyErr_SetString(PyExc_SystemError, "Missing type object"); - return 0; - } - if (likely(__Pyx_TypeCheck(obj, type))) - return 1; - PyErr_Format(PyExc_TypeError, "Cannot convert %.200s to %.200s", - Py_TYPE(obj)->tp_name, type->tp_name); - return 0; -} - -/* BufferFallbackError */ - static void __Pyx_RaiseBufferFallbackError(void) { - PyErr_SetString(PyExc_ValueError, - "Buffer acquisition failed on assignment; and then reacquiring the old buffer failed too!"); -} - -/* BufferIndexError */ - static void __Pyx_RaiseBufferIndexError(int axis) { - PyErr_Format(PyExc_IndexError, - "Out of bounds on buffer access (axis %d)", axis); -} - -/* PyErrFetchRestore */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx_ErrRestoreInState(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - tmp_type = tstate->curexc_type; - tmp_value = tstate->curexc_value; - tmp_tb = tstate->curexc_traceback; - tstate->curexc_type = type; - tstate->curexc_value = value; - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -static CYTHON_INLINE void __Pyx_ErrFetchInState(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - *type = tstate->curexc_type; - *value = tstate->curexc_value; - *tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -} -#endif - -/* RaiseArgTupleInvalid */ - static void __Pyx_RaiseArgtupleInvalid( - const char* func_name, - int exact, - Py_ssize_t num_min, - Py_ssize_t num_max, - Py_ssize_t num_found) -{ - Py_ssize_t num_expected; - const char *more_or_less; - if (num_found < num_min) { - num_expected = num_min; - more_or_less = "at least"; - } else { - num_expected = num_max; - more_or_less = "at most"; - } - if (exact) { - more_or_less = "exactly"; - } - PyErr_Format(PyExc_TypeError, - "%.200s() takes %.8s %" CYTHON_FORMAT_SSIZE_T "d positional argument%.1s (%" CYTHON_FORMAT_SSIZE_T "d given)", - func_name, more_or_less, num_expected, - (num_expected == 1) ? "" : "s", num_found); -} - -/* RaiseDoubleKeywords */ - static void __Pyx_RaiseDoubleKeywordsError( - const char* func_name, - PyObject* kw_name) -{ - PyErr_Format(PyExc_TypeError, - #if PY_MAJOR_VERSION >= 3 - "%s() got multiple values for keyword argument '%U'", func_name, kw_name); - #else - "%s() got multiple values for keyword argument '%s'", func_name, - PyString_AsString(kw_name)); - #endif -} - -/* ParseKeywords */ - static int __Pyx_ParseOptionalKeywords( - PyObject *kwds, - PyObject **argnames[], - PyObject *kwds2, - PyObject *values[], - Py_ssize_t num_pos_args, - const char* function_name) -{ - PyObject *key = 0, *value = 0; - Py_ssize_t pos = 0; - PyObject*** name; - PyObject*** first_kw_arg = argnames + num_pos_args; - while (PyDict_Next(kwds, &pos, &key, &value)) { - name = first_kw_arg; - while (*name && (**name != key)) name++; - if (*name) { - values[name-argnames] = value; - continue; - } - name = first_kw_arg; - #if PY_MAJOR_VERSION < 3 - if (likely(PyString_Check(key))) { - while (*name) { - if ((CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**name) == PyString_GET_SIZE(key)) - && _PyString_Eq(**name, key)) { - values[name-argnames] = value; - break; - } - name++; - } - if (*name) continue; - else { - PyObject*** argname = argnames; - while (argname != first_kw_arg) { - if ((**argname == key) || ( - (CYTHON_COMPILING_IN_PYPY || PyString_GET_SIZE(**argname) == PyString_GET_SIZE(key)) - && _PyString_Eq(**argname, key))) { - goto arg_passed_twice; - } - argname++; - } - } - } else - #endif - if (likely(PyUnicode_Check(key))) { - while (*name) { - int cmp = (**name == key) ? 0 : - #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (__Pyx_PyUnicode_GET_LENGTH(**name) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : - #endif - PyUnicode_Compare(**name, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) { - values[name-argnames] = value; - break; - } - name++; - } - if (*name) continue; - else { - PyObject*** argname = argnames; - while (argname != first_kw_arg) { - int cmp = (**argname == key) ? 0 : - #if !CYTHON_COMPILING_IN_PYPY && PY_MAJOR_VERSION >= 3 - (__Pyx_PyUnicode_GET_LENGTH(**argname) != __Pyx_PyUnicode_GET_LENGTH(key)) ? 1 : - #endif - PyUnicode_Compare(**argname, key); - if (cmp < 0 && unlikely(PyErr_Occurred())) goto bad; - if (cmp == 0) goto arg_passed_twice; - argname++; - } - } - } else - goto invalid_keyword_type; - if (kwds2) { - if (unlikely(PyDict_SetItem(kwds2, key, value))) goto bad; - } else { - goto invalid_keyword; - } - } - return 0; -arg_passed_twice: - __Pyx_RaiseDoubleKeywordsError(function_name, key); - goto bad; -invalid_keyword_type: - PyErr_Format(PyExc_TypeError, - "%.200s() keywords must be strings", function_name); - goto bad; -invalid_keyword: - PyErr_Format(PyExc_TypeError, - #if PY_MAJOR_VERSION < 3 - "%.200s() got an unexpected keyword argument '%.200s'", - function_name, PyString_AsString(key)); - #else - "%s() got an unexpected keyword argument '%U'", - function_name, key); - #endif -bad: - return -1; -} - -/* GetTopmostException */ - #if CYTHON_USE_EXC_INFO_STACK -static _PyErr_StackItem * -__Pyx_PyErr_GetTopmostException(PyThreadState *tstate) -{ - _PyErr_StackItem *exc_info = tstate->exc_info; - while ((exc_info->exc_type == NULL || exc_info->exc_type == Py_None) && - exc_info->previous_item != NULL) - { - exc_info = exc_info->previous_item; - } - return exc_info; -} -#endif - -/* SaveResetException */ - #if CYTHON_FAST_THREAD_STATE -static CYTHON_INLINE void __Pyx__ExceptionSave(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) { - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = __Pyx_PyErr_GetTopmostException(tstate); - *type = exc_info->exc_type; - *value = exc_info->exc_value; - *tb = exc_info->exc_traceback; - #else - *type = tstate->exc_type; - *value = tstate->exc_value; - *tb = tstate->exc_traceback; - #endif - Py_XINCREF(*type); - Py_XINCREF(*value); - Py_XINCREF(*tb); -} -static CYTHON_INLINE void __Pyx__ExceptionReset(PyThreadState *tstate, PyObject *type, PyObject *value, PyObject *tb) { - PyObject *tmp_type, *tmp_value, *tmp_tb; - #if CYTHON_USE_EXC_INFO_STACK - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = type; - exc_info->exc_value = value; - exc_info->exc_traceback = tb; - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = type; - tstate->exc_value = value; - tstate->exc_traceback = tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -} -#endif - -/* PyErrExceptionMatches */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx_PyErr_ExceptionMatchesTuple(PyObject *exc_type, PyObject *tuple) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(tuple); -#if PY_MAJOR_VERSION >= 3 - for (i=0; icurexc_type; - if (exc_type == err) return 1; - if (unlikely(!exc_type)) return 0; - if (unlikely(PyTuple_Check(err))) - return __Pyx_PyErr_ExceptionMatchesTuple(exc_type, err); - return __Pyx_PyErr_GivenExceptionMatches(exc_type, err); -} -#endif - -/* GetException */ - #if CYTHON_FAST_THREAD_STATE -static int __Pyx__GetException(PyThreadState *tstate, PyObject **type, PyObject **value, PyObject **tb) -#else -static int __Pyx_GetException(PyObject **type, PyObject **value, PyObject **tb) -#endif -{ - PyObject *local_type, *local_value, *local_tb; -#if CYTHON_FAST_THREAD_STATE - PyObject *tmp_type, *tmp_value, *tmp_tb; - local_type = tstate->curexc_type; - local_value = tstate->curexc_value; - local_tb = tstate->curexc_traceback; - tstate->curexc_type = 0; - tstate->curexc_value = 0; - tstate->curexc_traceback = 0; -#else - PyErr_Fetch(&local_type, &local_value, &local_tb); -#endif - PyErr_NormalizeException(&local_type, &local_value, &local_tb); -#if CYTHON_FAST_THREAD_STATE - if (unlikely(tstate->curexc_type)) -#else - if (unlikely(PyErr_Occurred())) -#endif - goto bad; - #if PY_MAJOR_VERSION >= 3 - if (local_tb) { - if (unlikely(PyException_SetTraceback(local_value, local_tb) < 0)) - goto bad; - } - #endif - Py_XINCREF(local_tb); - Py_XINCREF(local_type); - Py_XINCREF(local_value); - *type = local_type; - *value = local_value; - *tb = local_tb; -#if CYTHON_FAST_THREAD_STATE - #if CYTHON_USE_EXC_INFO_STACK - { - _PyErr_StackItem *exc_info = tstate->exc_info; - tmp_type = exc_info->exc_type; - tmp_value = exc_info->exc_value; - tmp_tb = exc_info->exc_traceback; - exc_info->exc_type = local_type; - exc_info->exc_value = local_value; - exc_info->exc_traceback = local_tb; - } - #else - tmp_type = tstate->exc_type; - tmp_value = tstate->exc_value; - tmp_tb = tstate->exc_traceback; - tstate->exc_type = local_type; - tstate->exc_value = local_value; - tstate->exc_traceback = local_tb; - #endif - Py_XDECREF(tmp_type); - Py_XDECREF(tmp_value); - Py_XDECREF(tmp_tb); -#else - PyErr_SetExcInfo(local_type, local_value, local_tb); -#endif - return 0; -bad: - *type = 0; - *value = 0; - *tb = 0; - Py_XDECREF(local_type); - Py_XDECREF(local_value); - Py_XDECREF(local_tb); - return -1; -} - -/* RaiseException */ - #if PY_MAJOR_VERSION < 3 -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, - CYTHON_UNUSED PyObject *cause) { - __Pyx_PyThreadState_declare - Py_XINCREF(type); - if (!value || value == Py_None) - value = NULL; - else - Py_INCREF(value); - if (!tb || tb == Py_None) - tb = NULL; - else { - Py_INCREF(tb); - if (!PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto raise_error; - } - } - if (PyType_Check(type)) { -#if CYTHON_COMPILING_IN_PYPY - if (!value) { - Py_INCREF(Py_None); - value = Py_None; - } -#endif - PyErr_NormalizeException(&type, &value, &tb); - } else { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto raise_error; - } - value = type; - type = (PyObject*) Py_TYPE(type); - Py_INCREF(type); - if (!PyType_IsSubtype((PyTypeObject *)type, (PyTypeObject *)PyExc_BaseException)) { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto raise_error; - } - } - __Pyx_PyThreadState_assign - __Pyx_ErrRestore(type, value, tb); - return; -raise_error: - Py_XDECREF(value); - Py_XDECREF(type); - Py_XDECREF(tb); - return; -} -#else -static void __Pyx_Raise(PyObject *type, PyObject *value, PyObject *tb, PyObject *cause) { - PyObject* owned_instance = NULL; - if (tb == Py_None) { - tb = 0; - } else if (tb && !PyTraceBack_Check(tb)) { - PyErr_SetString(PyExc_TypeError, - "raise: arg 3 must be a traceback or None"); - goto bad; - } - if (value == Py_None) - value = 0; - if (PyExceptionInstance_Check(type)) { - if (value) { - PyErr_SetString(PyExc_TypeError, - "instance exception may not have a separate value"); - goto bad; - } - value = type; - type = (PyObject*) Py_TYPE(value); - } else if (PyExceptionClass_Check(type)) { - PyObject *instance_class = NULL; - if (value && PyExceptionInstance_Check(value)) { - instance_class = (PyObject*) Py_TYPE(value); - if (instance_class != type) { - int is_subclass = PyObject_IsSubclass(instance_class, type); - if (!is_subclass) { - instance_class = NULL; - } else if (unlikely(is_subclass == -1)) { - goto bad; - } else { - type = instance_class; - } - } - } - if (!instance_class) { - PyObject *args; - if (!value) - args = PyTuple_New(0); - else if (PyTuple_Check(value)) { - Py_INCREF(value); - args = value; - } else - args = PyTuple_Pack(1, value); - if (!args) - goto bad; - owned_instance = PyObject_Call(type, args, NULL); - Py_DECREF(args); - if (!owned_instance) - goto bad; - value = owned_instance; - if (!PyExceptionInstance_Check(value)) { - PyErr_Format(PyExc_TypeError, - "calling %R should have returned an instance of " - "BaseException, not %R", - type, Py_TYPE(value)); - goto bad; - } - } - } else { - PyErr_SetString(PyExc_TypeError, - "raise: exception class must be a subclass of BaseException"); - goto bad; - } - if (cause) { - PyObject *fixed_cause; - if (cause == Py_None) { - fixed_cause = NULL; - } else if (PyExceptionClass_Check(cause)) { - fixed_cause = PyObject_CallObject(cause, NULL); - if (fixed_cause == NULL) - goto bad; - } else if (PyExceptionInstance_Check(cause)) { - fixed_cause = cause; - Py_INCREF(fixed_cause); - } else { - PyErr_SetString(PyExc_TypeError, - "exception causes must derive from " - "BaseException"); - goto bad; - } - PyException_SetCause(value, fixed_cause); - } - PyErr_SetObject(type, value); - if (tb) { -#if CYTHON_COMPILING_IN_PYPY - PyObject *tmp_type, *tmp_value, *tmp_tb; - PyErr_Fetch(&tmp_type, &tmp_value, &tmp_tb); - Py_INCREF(tb); - PyErr_Restore(tmp_type, tmp_value, tb); - Py_XDECREF(tmp_tb); -#else - PyThreadState *tstate = __Pyx_PyThreadState_Current; - PyObject* tmp_tb = tstate->curexc_traceback; - if (tb != tmp_tb) { - Py_INCREF(tb); - tstate->curexc_traceback = tb; - Py_XDECREF(tmp_tb); - } -#endif - } -bad: - Py_XDECREF(owned_instance); - return; -} -#endif - -/* TypeImport */ - #ifndef __PYX_HAVE_RT_ImportType -#define __PYX_HAVE_RT_ImportType -static PyTypeObject *__Pyx_ImportType(PyObject *module, const char *module_name, const char *class_name, - size_t size, enum __Pyx_ImportType_CheckSize check_size) -{ - PyObject *result = 0; - char warning[200]; - Py_ssize_t basicsize; -#ifdef Py_LIMITED_API - PyObject *py_basicsize; -#endif - result = PyObject_GetAttrString(module, class_name); - if (!result) - goto bad; - if (!PyType_Check(result)) { - PyErr_Format(PyExc_TypeError, - "%.200s.%.200s is not a type object", - module_name, class_name); - goto bad; - } -#ifndef Py_LIMITED_API - basicsize = ((PyTypeObject *)result)->tp_basicsize; -#else - py_basicsize = PyObject_GetAttrString(result, "__basicsize__"); - if (!py_basicsize) - goto bad; - basicsize = PyLong_AsSsize_t(py_basicsize); - Py_DECREF(py_basicsize); - py_basicsize = 0; - if (basicsize == (Py_ssize_t)-1 && PyErr_Occurred()) - goto bad; -#endif - if ((size_t)basicsize < size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - if (check_size == __Pyx_ImportType_CheckSize_Error && (size_t)basicsize != size) { - PyErr_Format(PyExc_ValueError, - "%.200s.%.200s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - goto bad; - } - else if (check_size == __Pyx_ImportType_CheckSize_Warn && (size_t)basicsize > size) { - PyOS_snprintf(warning, sizeof(warning), - "%s.%s size changed, may indicate binary incompatibility. " - "Expected %zd from C header, got %zd from PyObject", - module_name, class_name, size, basicsize); - if (PyErr_WarnEx(NULL, warning, 0) < 0) goto bad; - } - return (PyTypeObject *)result; -bad: - Py_XDECREF(result); - return NULL; -} -#endif - -/* Import */ - static PyObject *__Pyx_Import(PyObject *name, PyObject *from_list, int level) { - PyObject *empty_list = 0; - PyObject *module = 0; - PyObject *global_dict = 0; - PyObject *empty_dict = 0; - PyObject *list; - #if PY_MAJOR_VERSION < 3 - PyObject *py_import; - py_import = __Pyx_PyObject_GetAttrStr(__pyx_b, __pyx_n_s_import); - if (!py_import) - goto bad; - #endif - if (from_list) - list = from_list; - else { - empty_list = PyList_New(0); - if (!empty_list) - goto bad; - list = empty_list; - } - global_dict = PyModule_GetDict(__pyx_m); - if (!global_dict) - goto bad; - empty_dict = PyDict_New(); - if (!empty_dict) - goto bad; - { - #if PY_MAJOR_VERSION >= 3 - if (level == -1) { - if ((1) && (strchr(__Pyx_MODULE_NAME, '.'))) { - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, 1); - if (!module) { - if (!PyErr_ExceptionMatches(PyExc_ImportError)) - goto bad; - PyErr_Clear(); - } - } - level = 0; - } - #endif - if (!module) { - #if PY_MAJOR_VERSION < 3 - PyObject *py_level = PyInt_FromLong(level); - if (!py_level) - goto bad; - module = PyObject_CallFunctionObjArgs(py_import, - name, global_dict, empty_dict, list, py_level, (PyObject *)NULL); - Py_DECREF(py_level); - #else - module = PyImport_ImportModuleLevelObject( - name, global_dict, empty_dict, list, level); - #endif - } - } -bad: - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(py_import); - #endif - Py_XDECREF(empty_list); - Py_XDECREF(empty_dict); - return module; -} - -/* CLineInTraceback */ - #ifndef CYTHON_CLINE_IN_TRACEBACK -static int __Pyx_CLineForTraceback(CYTHON_NCP_UNUSED PyThreadState *tstate, int c_line) { - PyObject *use_cline; - PyObject *ptype, *pvalue, *ptraceback; -#if CYTHON_COMPILING_IN_CPYTHON - PyObject **cython_runtime_dict; -#endif - if (unlikely(!__pyx_cython_runtime)) { - return c_line; - } - __Pyx_ErrFetchInState(tstate, &ptype, &pvalue, &ptraceback); -#if CYTHON_COMPILING_IN_CPYTHON - cython_runtime_dict = _PyObject_GetDictPtr(__pyx_cython_runtime); - if (likely(cython_runtime_dict)) { - __PYX_PY_DICT_LOOKUP_IF_MODIFIED( - use_cline, *cython_runtime_dict, - __Pyx_PyDict_GetItemStr(*cython_runtime_dict, __pyx_n_s_cline_in_traceback)) - } else -#endif - { - PyObject *use_cline_obj = __Pyx_PyObject_GetAttrStr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback); - if (use_cline_obj) { - use_cline = PyObject_Not(use_cline_obj) ? Py_False : Py_True; - Py_DECREF(use_cline_obj); - } else { - PyErr_Clear(); - use_cline = NULL; - } - } - if (!use_cline) { - c_line = 0; - (void) PyObject_SetAttr(__pyx_cython_runtime, __pyx_n_s_cline_in_traceback, Py_False); - } - else if (use_cline == Py_False || (use_cline != Py_True && PyObject_Not(use_cline) != 0)) { - c_line = 0; - } - __Pyx_ErrRestoreInState(tstate, ptype, pvalue, ptraceback); - return c_line; -} -#endif - -/* CodeObjectCache */ - static int __pyx_bisect_code_objects(__Pyx_CodeObjectCacheEntry* entries, int count, int code_line) { - int start = 0, mid = 0, end = count - 1; - if (end >= 0 && code_line > entries[end].code_line) { - return count; - } - while (start < end) { - mid = start + (end - start) / 2; - if (code_line < entries[mid].code_line) { - end = mid; - } else if (code_line > entries[mid].code_line) { - start = mid + 1; - } else { - return mid; - } - } - if (code_line <= entries[mid].code_line) { - return mid; - } else { - return mid + 1; - } -} -static PyCodeObject *__pyx_find_code_object(int code_line) { - PyCodeObject* code_object; - int pos; - if (unlikely(!code_line) || unlikely(!__pyx_code_cache.entries)) { - return NULL; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if (unlikely(pos >= __pyx_code_cache.count) || unlikely(__pyx_code_cache.entries[pos].code_line != code_line)) { - return NULL; - } - code_object = __pyx_code_cache.entries[pos].code_object; - Py_INCREF(code_object); - return code_object; -} -static void __pyx_insert_code_object(int code_line, PyCodeObject* code_object) { - int pos, i; - __Pyx_CodeObjectCacheEntry* entries = __pyx_code_cache.entries; - if (unlikely(!code_line)) { - return; - } - if (unlikely(!entries)) { - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Malloc(64*sizeof(__Pyx_CodeObjectCacheEntry)); - if (likely(entries)) { - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = 64; - __pyx_code_cache.count = 1; - entries[0].code_line = code_line; - entries[0].code_object = code_object; - Py_INCREF(code_object); - } - return; - } - pos = __pyx_bisect_code_objects(__pyx_code_cache.entries, __pyx_code_cache.count, code_line); - if ((pos < __pyx_code_cache.count) && unlikely(__pyx_code_cache.entries[pos].code_line == code_line)) { - PyCodeObject* tmp = entries[pos].code_object; - entries[pos].code_object = code_object; - Py_DECREF(tmp); - return; - } - if (__pyx_code_cache.count == __pyx_code_cache.max_count) { - int new_max = __pyx_code_cache.max_count + 64; - entries = (__Pyx_CodeObjectCacheEntry*)PyMem_Realloc( - __pyx_code_cache.entries, ((size_t)new_max) * sizeof(__Pyx_CodeObjectCacheEntry)); - if (unlikely(!entries)) { - return; - } - __pyx_code_cache.entries = entries; - __pyx_code_cache.max_count = new_max; - } - for (i=__pyx_code_cache.count; i>pos; i--) { - entries[i] = entries[i-1]; - } - entries[pos].code_line = code_line; - entries[pos].code_object = code_object; - __pyx_code_cache.count++; - Py_INCREF(code_object); -} - -/* AddTraceback */ - #include "compile.h" -#include "frameobject.h" -#include "traceback.h" -static PyCodeObject* __Pyx_CreateCodeObjectForTraceback( - const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = NULL; - PyObject *py_funcname = NULL; - #if PY_MAJOR_VERSION < 3 - PyObject *py_srcfile = NULL; - py_srcfile = PyString_FromString(filename); - if (!py_srcfile) goto bad; - #endif - if (c_line) { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - if (!py_funcname) goto bad; - #else - py_funcname = PyUnicode_FromFormat( "%s (%s:%d)", funcname, __pyx_cfilenm, c_line); - if (!py_funcname) goto bad; - funcname = PyUnicode_AsUTF8(py_funcname); - if (!funcname) goto bad; - #endif - } - else { - #if PY_MAJOR_VERSION < 3 - py_funcname = PyString_FromString(funcname); - if (!py_funcname) goto bad; - #endif - } - #if PY_MAJOR_VERSION < 3 - py_code = __Pyx_PyCode_New( - 0, - 0, - 0, - 0, - 0, - __pyx_empty_bytes, /*PyObject *code,*/ - __pyx_empty_tuple, /*PyObject *consts,*/ - __pyx_empty_tuple, /*PyObject *names,*/ - __pyx_empty_tuple, /*PyObject *varnames,*/ - __pyx_empty_tuple, /*PyObject *freevars,*/ - __pyx_empty_tuple, /*PyObject *cellvars,*/ - py_srcfile, /*PyObject *filename,*/ - py_funcname, /*PyObject *name,*/ - py_line, - __pyx_empty_bytes /*PyObject *lnotab*/ - ); - Py_DECREF(py_srcfile); - #else - py_code = PyCode_NewEmpty(filename, funcname, py_line); - #endif - Py_XDECREF(py_funcname); // XDECREF since it's only set on Py3 if cline - return py_code; -bad: - Py_XDECREF(py_funcname); - #if PY_MAJOR_VERSION < 3 - Py_XDECREF(py_srcfile); - #endif - return NULL; -} -static void __Pyx_AddTraceback(const char *funcname, int c_line, - int py_line, const char *filename) { - PyCodeObject *py_code = 0; - PyFrameObject *py_frame = 0; - PyThreadState *tstate = __Pyx_PyThreadState_Current; - if (c_line) { - c_line = __Pyx_CLineForTraceback(tstate, c_line); - } - py_code = __pyx_find_code_object(c_line ? -c_line : py_line); - if (!py_code) { - py_code = __Pyx_CreateCodeObjectForTraceback( - funcname, c_line, py_line, filename); - if (!py_code) goto bad; - __pyx_insert_code_object(c_line ? -c_line : py_line, py_code); - } - py_frame = PyFrame_New( - tstate, /*PyThreadState *tstate,*/ - py_code, /*PyCodeObject *code,*/ - __pyx_d, /*PyObject *globals,*/ - 0 /*PyObject *locals*/ - ); - if (!py_frame) goto bad; - __Pyx_PyFrame_SetLineNumber(py_frame, py_line); - PyTraceBack_Here(py_frame); -bad: - Py_XDECREF(py_code); - Py_XDECREF(py_frame); -} - -#if PY_MAJOR_VERSION < 3 -static int __Pyx_GetBuffer(PyObject *obj, Py_buffer *view, int flags) { - if (PyObject_CheckBuffer(obj)) return PyObject_GetBuffer(obj, view, flags); - PyErr_Format(PyExc_TypeError, "'%.200s' does not have the buffer interface", Py_TYPE(obj)->tp_name); - return -1; -} -static void __Pyx_ReleaseBuffer(Py_buffer *view) { - PyObject *obj = view->obj; - if (!obj) return; - if (PyObject_CheckBuffer(obj)) { - PyBuffer_Release(view); - return; - } - if ((0)) {} - view->obj = NULL; - Py_DECREF(obj); -} -#endif - - - /* CIntFromPyVerify */ - #define __PYX_VERIFY_RETURN_INT(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 0) -#define __PYX_VERIFY_RETURN_INT_EXC(target_type, func_type, func_value)\ - __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, 1) -#define __PYX__VERIFY_RETURN_INT(target_type, func_type, func_value, exc)\ - {\ - func_type value = func_value;\ - if (sizeof(target_type) < sizeof(func_type)) {\ - if (unlikely(value != (func_type) (target_type) value)) {\ - func_type zero = 0;\ - if (exc && unlikely(value == (func_type)-1 && PyErr_Occurred()))\ - return (target_type) -1;\ - if (is_unsigned && unlikely(value < zero))\ - goto raise_neg_overflow;\ - else\ - goto raise_overflow;\ - }\ - }\ - return (target_type) value;\ - } - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return ::std::complex< float >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - return x + y*(__pyx_t_float_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_float_complex __pyx_t_float_complex_from_parts(float x, float y) { - __pyx_t_float_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_sum_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_diff_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_prod_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabsf(b.real) >= fabsf(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - float r = b.imag / b.real; - float s = (float)(1.0) / (b.real + b.imag * r); - return __pyx_t_float_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - float r = b.real / b.imag; - float s = (float)(1.0) / (b.imag + b.real * r); - return __pyx_t_float_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_quot_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - if (b.imag == 0) { - return __pyx_t_float_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - float denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_float_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_neg_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_float(__pyx_t_float_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_conj_float(__pyx_t_float_complex a) { - __pyx_t_float_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE float __Pyx_c_abs_float(__pyx_t_float_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrtf(z.real*z.real + z.imag*z.imag); - #else - return hypotf(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_float_complex __Pyx_c_pow_float(__pyx_t_float_complex a, __pyx_t_float_complex b) { - __pyx_t_float_complex z; - float r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - float denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_float(a, a); - case 3: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, a); - case 4: - z = __Pyx_c_prod_float(a, a); - return __Pyx_c_prod_float(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = powf(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2f(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_float(a); - theta = atan2f(a.imag, a.real); - } - lnr = logf(r); - z_r = expf(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cosf(z_theta); - z.imag = z_r * sinf(z_theta); - return z; - } - #endif -#endif - -/* Declarations */ - #if CYTHON_CCOMPLEX - #ifdef __cplusplus - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return ::std::complex< double >(x, y); - } - #else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - return x + y*(__pyx_t_double_complex)_Complex_I; - } - #endif -#else - static CYTHON_INLINE __pyx_t_double_complex __pyx_t_double_complex_from_parts(double x, double y) { - __pyx_t_double_complex z; - z.real = x; - z.imag = y; - return z; - } -#endif - -/* Arithmetic */ - #if CYTHON_CCOMPLEX -#else - static CYTHON_INLINE int __Pyx_c_eq_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - return (a.real == b.real) && (a.imag == b.imag); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_sum_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real + b.real; - z.imag = a.imag + b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_diff_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real - b.real; - z.imag = a.imag - b.imag; - return z; - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_prod_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - z.real = a.real * b.real - a.imag * b.imag; - z.imag = a.real * b.imag + a.imag * b.real; - return z; - } - #if 1 - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else if (fabs(b.real) >= fabs(b.imag)) { - if (b.real == 0 && b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.imag); - } else { - double r = b.imag / b.real; - double s = (double)(1.0) / (b.real + b.imag * r); - return __pyx_t_double_complex_from_parts( - (a.real + a.imag * r) * s, (a.imag - a.real * r) * s); - } - } else { - double r = b.real / b.imag; - double s = (double)(1.0) / (b.imag + b.real * r); - return __pyx_t_double_complex_from_parts( - (a.real * r + a.imag) * s, (a.imag * r - a.real) * s); - } - } - #else - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_quot_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - if (b.imag == 0) { - return __pyx_t_double_complex_from_parts(a.real / b.real, a.imag / b.real); - } else { - double denom = b.real * b.real + b.imag * b.imag; - return __pyx_t_double_complex_from_parts( - (a.real * b.real + a.imag * b.imag) / denom, - (a.imag * b.real - a.real * b.imag) / denom); - } - } - #endif - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_neg_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = -a.real; - z.imag = -a.imag; - return z; - } - static CYTHON_INLINE int __Pyx_c_is_zero_double(__pyx_t_double_complex a) { - return (a.real == 0) && (a.imag == 0); - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_conj_double(__pyx_t_double_complex a) { - __pyx_t_double_complex z; - z.real = a.real; - z.imag = -a.imag; - return z; - } - #if 1 - static CYTHON_INLINE double __Pyx_c_abs_double(__pyx_t_double_complex z) { - #if !defined(HAVE_HYPOT) || defined(_MSC_VER) - return sqrt(z.real*z.real + z.imag*z.imag); - #else - return hypot(z.real, z.imag); - #endif - } - static CYTHON_INLINE __pyx_t_double_complex __Pyx_c_pow_double(__pyx_t_double_complex a, __pyx_t_double_complex b) { - __pyx_t_double_complex z; - double r, lnr, theta, z_r, z_theta; - if (b.imag == 0 && b.real == (int)b.real) { - if (b.real < 0) { - double denom = a.real * a.real + a.imag * a.imag; - a.real = a.real / denom; - a.imag = -a.imag / denom; - b.real = -b.real; - } - switch ((int)b.real) { - case 0: - z.real = 1; - z.imag = 0; - return z; - case 1: - return a; - case 2: - return __Pyx_c_prod_double(a, a); - case 3: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, a); - case 4: - z = __Pyx_c_prod_double(a, a); - return __Pyx_c_prod_double(z, z); - } - } - if (a.imag == 0) { - if (a.real == 0) { - return a; - } else if (b.imag == 0) { - z.real = pow(a.real, b.real); - z.imag = 0; - return z; - } else if (a.real > 0) { - r = a.real; - theta = 0; - } else { - r = -a.real; - theta = atan2(0.0, -1.0); - } - } else { - r = __Pyx_c_abs_double(a); - theta = atan2(a.imag, a.real); - } - lnr = log(r); - z_r = exp(lnr * b.real - theta * b.imag); - z_theta = theta * b.real + lnr * b.imag; - z.real = z_r * cos(z_theta); - z.imag = z_r * sin(z_theta); - return z; - } - #endif -#endif - -/* CIntFromPy */ - static CYTHON_INLINE int __Pyx_PyInt_As_int(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const int neg_one = (int) -1, const_zero = (int) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(int) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(int, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (int) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case 1: __PYX_VERIFY_RETURN_INT(int, digit, digits[0]) - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 2 * PyLong_SHIFT) { - return (int) (((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 3 * PyLong_SHIFT) { - return (int) (((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) >= 4 * PyLong_SHIFT) { - return (int) (((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (int) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(int) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (int) 0; - case -1: __PYX_VERIFY_RETURN_INT(int, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(int, digit, +digits[0]) - case -2: - if (8 * sizeof(int) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(int) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - return (int) ((((((int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(int) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(int) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - return (int) ((((((((int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(int) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) (((int)-1)*(((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(int) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(int, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(int) - 1 > 4 * PyLong_SHIFT) { - return (int) ((((((((((int)digits[3]) << PyLong_SHIFT) | (int)digits[2]) << PyLong_SHIFT) | (int)digits[1]) << PyLong_SHIFT) | (int)digits[0]))); - } - } - break; - } -#endif - if (sizeof(int) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(int, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(int) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(int, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - int val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (int) -1; - } - } else { - int val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (int) -1; - val = __Pyx_PyInt_As_int(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to int"); - return (int) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to int"); - return (int) -1; -} - -/* CIntToPy */ - static CYTHON_INLINE PyObject* __Pyx_PyInt_From_long(long value) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; - if (is_unsigned) { - if (sizeof(long) < sizeof(long)) { - return PyInt_FromLong((long) value); - } else if (sizeof(long) <= sizeof(unsigned long)) { - return PyLong_FromUnsignedLong((unsigned long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - return PyLong_FromUnsignedLongLong((unsigned PY_LONG_LONG) value); -#endif - } - } else { - if (sizeof(long) <= sizeof(long)) { - return PyInt_FromLong((long) value); -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - return PyLong_FromLongLong((PY_LONG_LONG) value); -#endif - } - } - { - int one = 1; int little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&value; - return _PyLong_FromByteArray(bytes, sizeof(long), - little, !is_unsigned); - } -} - -/* CIntFromPy */ - static CYTHON_INLINE long __Pyx_PyInt_As_long(PyObject *x) { -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic push -#pragma GCC diagnostic ignored "-Wconversion" -#endif - const long neg_one = (long) -1, const_zero = (long) 0; -#ifdef __Pyx_HAS_GCC_DIAGNOSTIC -#pragma GCC diagnostic pop -#endif - const int is_unsigned = neg_one > const_zero; -#if PY_MAJOR_VERSION < 3 - if (likely(PyInt_Check(x))) { - if (sizeof(long) < sizeof(long)) { - __PYX_VERIFY_RETURN_INT(long, long, PyInt_AS_LONG(x)) - } else { - long val = PyInt_AS_LONG(x); - if (is_unsigned && unlikely(val < 0)) { - goto raise_neg_overflow; - } - return (long) val; - } - } else -#endif - if (likely(PyLong_Check(x))) { - if (is_unsigned) { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case 1: __PYX_VERIFY_RETURN_INT(long, digit, digits[0]) - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 2 * PyLong_SHIFT) { - return (long) (((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 3 * PyLong_SHIFT) { - return (long) (((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) >= 4 * PyLong_SHIFT) { - return (long) (((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0])); - } - } - break; - } -#endif -#if CYTHON_COMPILING_IN_CPYTHON - if (unlikely(Py_SIZE(x) < 0)) { - goto raise_neg_overflow; - } -#else - { - int result = PyObject_RichCompareBool(x, Py_False, Py_LT); - if (unlikely(result < 0)) - return (long) -1; - if (unlikely(result == 1)) - goto raise_neg_overflow; - } -#endif - if (sizeof(long) <= sizeof(unsigned long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned long, PyLong_AsUnsignedLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(unsigned PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, unsigned PY_LONG_LONG, PyLong_AsUnsignedLongLong(x)) -#endif - } - } else { -#if CYTHON_USE_PYLONG_INTERNALS - const digit* digits = ((PyLongObject*)x)->ob_digit; - switch (Py_SIZE(x)) { - case 0: return (long) 0; - case -1: __PYX_VERIFY_RETURN_INT(long, sdigit, (sdigit) (-(sdigit)digits[0])) - case 1: __PYX_VERIFY_RETURN_INT(long, digit, +digits[0]) - case -2: - if (8 * sizeof(long) - 1 > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 2: - if (8 * sizeof(long) > 1 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 2 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - return (long) ((((((long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -3: - if (8 * sizeof(long) - 1 > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 3: - if (8 * sizeof(long) > 2 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 3 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - return (long) ((((((((long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case -4: - if (8 * sizeof(long) - 1 > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, long, -(long) (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) (((long)-1)*(((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - case 4: - if (8 * sizeof(long) > 3 * PyLong_SHIFT) { - if (8 * sizeof(unsigned long) > 4 * PyLong_SHIFT) { - __PYX_VERIFY_RETURN_INT(long, unsigned long, (((((((((unsigned long)digits[3]) << PyLong_SHIFT) | (unsigned long)digits[2]) << PyLong_SHIFT) | (unsigned long)digits[1]) << PyLong_SHIFT) | (unsigned long)digits[0]))) - } else if (8 * sizeof(long) - 1 > 4 * PyLong_SHIFT) { - return (long) ((((((((((long)digits[3]) << PyLong_SHIFT) | (long)digits[2]) << PyLong_SHIFT) | (long)digits[1]) << PyLong_SHIFT) | (long)digits[0]))); - } - } - break; - } -#endif - if (sizeof(long) <= sizeof(long)) { - __PYX_VERIFY_RETURN_INT_EXC(long, long, PyLong_AsLong(x)) -#ifdef HAVE_LONG_LONG - } else if (sizeof(long) <= sizeof(PY_LONG_LONG)) { - __PYX_VERIFY_RETURN_INT_EXC(long, PY_LONG_LONG, PyLong_AsLongLong(x)) -#endif - } - } - { -#if CYTHON_COMPILING_IN_PYPY && !defined(_PyLong_AsByteArray) - PyErr_SetString(PyExc_RuntimeError, - "_PyLong_AsByteArray() not available in PyPy, cannot convert large numbers"); -#else - long val; - PyObject *v = __Pyx_PyNumber_IntOrLong(x); - #if PY_MAJOR_VERSION < 3 - if (likely(v) && !PyLong_Check(v)) { - PyObject *tmp = v; - v = PyNumber_Long(tmp); - Py_DECREF(tmp); - } - #endif - if (likely(v)) { - int one = 1; int is_little = (int)*(unsigned char *)&one; - unsigned char *bytes = (unsigned char *)&val; - int ret = _PyLong_AsByteArray((PyLongObject *)v, - bytes, sizeof(val), - is_little, !is_unsigned); - Py_DECREF(v); - if (likely(!ret)) - return val; - } -#endif - return (long) -1; - } - } else { - long val; - PyObject *tmp = __Pyx_PyNumber_IntOrLong(x); - if (!tmp) return (long) -1; - val = __Pyx_PyInt_As_long(tmp); - Py_DECREF(tmp); - return val; - } -raise_overflow: - PyErr_SetString(PyExc_OverflowError, - "value too large to convert to long"); - return (long) -1; -raise_neg_overflow: - PyErr_SetString(PyExc_OverflowError, - "can't convert negative value to long"); - return (long) -1; -} - -/* FastTypeChecks */ - #if CYTHON_COMPILING_IN_CPYTHON -static int __Pyx_InBases(PyTypeObject *a, PyTypeObject *b) { - while (a) { - a = a->tp_base; - if (a == b) - return 1; - } - return b == &PyBaseObject_Type; -} -static CYTHON_INLINE int __Pyx_IsSubtype(PyTypeObject *a, PyTypeObject *b) { - PyObject *mro; - if (a == b) return 1; - mro = a->tp_mro; - if (likely(mro)) { - Py_ssize_t i, n; - n = PyTuple_GET_SIZE(mro); - for (i = 0; i < n; i++) { - if (PyTuple_GET_ITEM(mro, i) == (PyObject *)b) - return 1; - } - return 0; - } - return __Pyx_InBases(a, b); -} -#if PY_MAJOR_VERSION == 2 -static int __Pyx_inner_PyErr_GivenExceptionMatches2(PyObject *err, PyObject* exc_type1, PyObject* exc_type2) { - PyObject *exception, *value, *tb; - int res; - __Pyx_PyThreadState_declare - __Pyx_PyThreadState_assign - __Pyx_ErrFetch(&exception, &value, &tb); - res = exc_type1 ? 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return PyInt_FromSize_t(ival); -} - - -#endif /* Py_PYTHON_H */ From 169ceddf0cb2f64e254d276befe8b74648c1ac60 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Tue, 24 Jan 2023 15:52:13 +0000 Subject: [PATCH 08/25] Update read_noise.py added initial plotting function and cleaned covariance matrix --- python/arcticpy/read_noise.py | 296 +++++++++++++++++++--------------- 1 file changed, 162 insertions(+), 134 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 3ceb93a..cc1e41d 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -1,5 +1,6 @@ import numpy as np import arcticpy as ac +import matplotlib as mpl from scipy.optimize import curve_fit """ @@ -366,7 +367,7 @@ def optimise_parameters( kwargs['serial_roe'].prescan_offset = chip_size+(subchip_size//2) #container for optimised values - optVals = {} + self.optVals = {} #pre-make the sky background and readnoise images, keep these constant over all quadrants skyFrame, readNoiseFrame = self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) @@ -391,6 +392,7 @@ def optimise_parameters( #re-run the S+R routine with the optimised level raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs) + raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs) #this is dumb...do it better #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise kwargs_noCTI = kwargs.copy() @@ -398,6 +400,7 @@ def optimise_parameters( kwargs_noCTI['serial_traps']=None #effectively, we are removing the effects of CTI, but still calculating a covariance matrix raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_noCTI) #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated @@ -417,21 +420,31 @@ def optimise_parameters( raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_serialOnly) #package all relevant quantities into optVals and return - optVals['optSRfrac'] = frac_opt - optVals['combinedQuadMatrix'] = raw_matrix_opt - optVals['combinedQuadMatrix_diff'] = correction_matrix_opt - optVals['parallelQuadMatrix'] = raw_matrix_opt_parallel - optVals['parallelQuadMatrix_diff'] = correction_matrix_opt_parallel - optVals['serialQuadMatrix'] = raw_matrix_opt_serial - optVals['serialQuadMatrix_diff'] = correction_matrix_opt_serial - optVals['noCTIQuadMatrix'] = raw_matrix_opt_noCTI - optVals['noCTIQuadMatrix_diff'] = correction_matrix_opt_noCTI - optVals['benchmark'] = benchmark_matrix - optVals['benchmark_resid'] = residual_benchmark_matrix - - return optVals + self.optVals['optSRfrac'] = frac_opt + self.optVals['combinedQuadMatrix'] = raw_matrix_opt + self.optVals['combinedQuadMatrix_diff'] = correction_matrix_opt + self.optVals['combinedQuadMatrix_noSR'] = raw_matrix_opt_noSR + self.optVals['combinedQuadMatrix_noSR_diff'] = correction_matrix_opt_noSR + self.optVals['parallelQuadMatrix'] = raw_matrix_opt_parallel + self.optVals['parallelQuadMatrix_diff'] = correction_matrix_opt_parallel + self.optVals['parallelQuadMatrix_noSR'] = raw_matrix_opt_parallel_noSR + self.optVals['parallelQuadMatrix_noSR_diff'] = correction_matrix_opt_parallel_noSR + self.optVals['serialQuadMatrix'] = raw_matrix_opt_serial + self.optVals['serialQuadMatrix_diff'] = correction_matrix_opt_serial + self.optVals['serialQuadMatrix_noSR'] = raw_matrix_opt_serial_noSR + self.optVals['serialQuadMatrix_noSR_diff'] = correction_matrix_opt_serial_noSR + self.optVals['noCTIQuadMatrix'] = raw_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_diff'] = correction_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_noSR'] = raw_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_diff_noSR'] = correction_matrix_opt_noCTI + self.optVals['benchmark'] = benchmark_matrix + self.optVals['benchmark_resid'] = residual_benchmark_matrix + + #return optVals ############### # ############### # def optimise_parameters( @@ -536,121 +549,121 @@ def optimise_parameters( # ##covar = self.covariance_matrix_from_image(image) # # ############### - ############### - def optimise_parameters_from_image( - self, - image, - background_level=None, - chip_size=500, - matrix_size=5, - **kwargs - ): - ''' - version of the S+R optimiser routine, but parameters can be determined from a supplied image rather than manually specified - ''' - optVals = {} - image_nrows = image.shape[0] - image_ncols = image.shape[1] - - #use CTI prescan offset to ensure sample region is at the far edge of the full chip - kwargs['parallel_roe'].prescan_offset = kwargs['parallel_roe'].prescan_offset + image_nrows - chip_size//2 - kwargs['serial_roe'].prescan_offset = kwargs['serial_roe'].prescan_offset + image_ncols - chip_size//2 - - #if background nevel is not specified, estimate using the median pixel value - if background_level == None: - background_level = np.median(image) - - - if 'parallel_traps' in kwargs: - if kwargs['parallel_traps'] is not None: - kwargs_parallel = kwargs.copy() - kwargs_parallel['serial_traps']=None #make a parallel-only quadrant - ###use CTI prescan offset to ensure sample region is at the far edge of the full chip - ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 - #things to compare over iterations - result_array = np.array([]) - matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) - for frac in sr_frac: - correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_parallel) - matrix_array[int(frac*10)] = correction_matrix - result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters - result_array = np.append(result_array,result) - - a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) - m = a_fit[1] - b = a_fit[0] - xint = -b/m - - lo = np.floor(xint*10).astype(int) - hi = np.ceil(xint*10).astype(int) - mean_grid = (matrix_array[lo]+matrix_array[hi])/2 - - optVals['parallelQuadMatrix'] = mean_grid - optVals['parallelQuadFrac'] = xint - - if 'serial_traps' in kwargs: - if kwargs['serial_traps'] is not None: - kwargs_serial = kwargs.copy() - kwargs_serial['parallel_traps']=None #make a serial-only quadrant - ###use CTI prescan offset to ensure sample region is at the far edge of the full chip - ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 - #things to compare over iterations - result_array = np.array([]) - matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) - for frac in sr_frac: - correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_serial) - matrix_array[int(frac*10)] = correction_matrix - result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters - result_array = np.append(result_array,result) - - a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) - m = a_fit[1] - b = a_fit[0] - xint = -b/m - - lo = np.floor(xint*10).astype(int) - hi = np.ceil(xint*10).astype(int) - mean_grid = (matrix_array[lo]+matrix_array[hi])/2 - - optVals['serialQuadMatrix'] = mean_grid - optVals['serialQuadFrac'] = xint - - if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): - if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): - ###use CTI prescan offset to ensure sample region is at the far edge of the full chip - ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 - ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 - #things to compare over iterations - result_array = np.array([]) - matrix_array = np.zeros((11,matrix_size,matrix_size)) - sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) - for frac in sr_frac: - correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) - matrix_array[int(frac*10)] = correction_matrix - result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters - result_array = np.append(result_array,result) - - a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) - m = a_fit[1] - b = a_fit[0] - xint = -b/m - - lo = np.floor(xint*10).astype(int) - hi = np.ceil(xint*10).astype(int) - mean_grid = (matrix_array[lo]+matrix_array[hi])/2 - - optVals['combinedQuadMatrix'] = mean_grid - optVals['combinedQuadFrac'] = xint - - - return optVals - - ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) - ##covar = self.covariance_matrix_from_image(image) - - ############### +# ############### +# def optimise_parameters_from_image( +# self, +# image, +# background_level=None, +# chip_size=500, +# matrix_size=5, +# **kwargs +# ): +# ''' +# version of the S+R optimiser routine, but parameters can be determined from a supplied image rather than manually specified +# ''' +# optVals = {} +# image_nrows = image.shape[0] +# image_ncols = image.shape[1] +# +# #use CTI prescan offset to ensure sample region is at the far edge of the full chip +# kwargs['parallel_roe'].prescan_offset = kwargs['parallel_roe'].prescan_offset + image_nrows - chip_size//2 +# kwargs['serial_roe'].prescan_offset = kwargs['serial_roe'].prescan_offset + image_ncols - chip_size//2 +# +# #if background nevel is not specified, estimate using the median pixel value +# if background_level == None: +# background_level = np.median(image) +# +# +# if 'parallel_traps' in kwargs: +# if kwargs['parallel_traps'] is not None: +# kwargs_parallel = kwargs.copy() +# kwargs_parallel['serial_traps']=None #make a parallel-only quadrant +# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip +# ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) +# for frac in sr_frac: +# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_parallel) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['parallelQuadMatrix'] = mean_grid +# optVals['parallelQuadFrac'] = xint +# +# if 'serial_traps' in kwargs: +# if kwargs['serial_traps'] is not None: +# kwargs_serial = kwargs.copy() +# kwargs_serial['parallel_traps']=None #make a serial-only quadrant +# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip +# ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) +# for frac in sr_frac: +# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_serial) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['serialQuadMatrix'] = mean_grid +# optVals['serialQuadFrac'] = xint +# +# if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): +# if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): +# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip +# ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 +# ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 +# #things to compare over iterations +# result_array = np.array([]) +# matrix_array = np.zeros((11,matrix_size,matrix_size)) +# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) +# for frac in sr_frac: +# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) +# matrix_array[int(frac*10)] = correction_matrix +# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters +# result_array = np.append(result_array,result) +# +# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) +# m = a_fit[1] +# b = a_fit[0] +# xint = -b/m +# +# lo = np.floor(xint*10).astype(int) +# hi = np.ceil(xint*10).astype(int) +# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 +# +# optVals['combinedQuadMatrix'] = mean_grid +# optVals['combinedQuadFrac'] = xint +# +# +# return optVals +# +# ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) +# ##covar = self.covariance_matrix_from_image(image) +# +# ############### ############### def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None): ''' @@ -685,19 +698,20 @@ def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None) ############### ############### - def covariance_matrix_from_image(self, image, matrix_size=5): + def covariance_matrix_from_image(self, image, matrix_size=5,fprSize=5): + + matRange= matrix_size//2 #set positions of correlation pixels and set limits to remove "roll-over" region covariance_matrix = np.zeros((matrix_size,matrix_size)) #calcluate mean stats on image - image2 = image[5:,5:] #remove FPR decrement - x = image2.flatten() + image2 = image[fprSize:,fprSize:] #remove FPR decrement + x = image2[matRange:-matRange,matRange:-matRange].flatten() #remove possible roll-over region xbar = np.mean(x) #roll image to get cross correlation - matRange= matrix_size//2 for i in range(-matRange,matRange+1,1): for j in range(-matRange,matRange+1,1): - y = np.roll(image2,(-j,-i),axis=(0,1)).flatten() + y = np.roll(image2,(-j,-i),axis=(0,1))[2:-2,2:-2].flatten() ybar = np.mean(y) #calculate covariance @@ -708,4 +722,18 @@ def covariance_matrix_from_image(self, image, matrix_size=5): #covariance_matrix[matRange,matRange] = 0 #switch this normalization to plotting return covariance_matrix + ############### + ############### + def plot_matrix(self,covariance_matrix,supressCentralPix=True,title='MyPlotMatrix',**kwargs): + if supressCentralPix == True: + matrix = covariance_matrix.copy() + matrix_size = matrix.shape[0] + matrix[matrix_size//2,matrix_size//2] = 0 # set central pixel to zero, to better see correlation dynamic range + else: + matrix = covariance_matrix.copy() + mpl.pyplot.clf() + mpl.pyplot.imshow(matrix,cmap='bwr',**kwargs) + mpl.pyplot.colorbar() + mpl.pyplot.title(title) + mpl.pyplot.show() From 6a42b8b3f86747207f7ec1a09b40b24aabc14e33 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Tue, 24 Jan 2023 16:00:58 +0000 Subject: [PATCH 09/25] Update read_noise.py test --- python/arcticpy/read_noise.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index cc1e41d..0f5a956 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -1,7 +1,7 @@ import numpy as np import arcticpy as ac import matplotlib as mpl -from scipy.optimize import curve_fit +from scipy.optimize import curve_fit """ CTI correction moves trailed electrons back to their proper location, but also From e4470340a942406cd068010478aa9c9841300732 Mon Sep 17 00:00:00 2001 From: Richard Massey Date: Tue, 24 Jan 2023 19:31:52 +0000 Subject: [PATCH 10/25] comments added --- python/arcticpy/read_noise.py | 122 ++++++++++++++++++++++++++++++++-- 1 file changed, 117 insertions(+), 5 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 0f5a956..6252945 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -10,6 +10,43 @@ adjacent pixels. This class provides a set of routines to predict this effect, and counteract it. + +If you have an image as a 2D numpy array, image +and an arctic model with parameters parallel_roe, parallel_ccd, parallel_traps +run + +readnoise = arctic.ReadNoise(4.5) + + +[optionally] +[readnoise.optimise_parameters] + + +skyImage, readNoiseImage = readnoise.estimate_read_noise_model_from_image(image, sr_fraction=None, + parallel_roe, parallel_ccd, parallel_traps) + +image_corrected = arctic.cti_correct(skyImage, + parallel_roe, parallel_ccd, parallel_traps) + +image_corrected += readNoiseImage + + + +readnoise.covariance + + + + +covariance = readnoise.etimate_residual_covariance_from_image(image, + matrix_size=5, fprSize=5, + parallel_roe, parallel_ccd, parallel_traps) + +covariance = readnoise.etimate_residual_covariance(sky_level, sky_sigma, + matrix_size=5, fprSize=5, + parallel_roe, parallel_ccd, parallel_traps) + + + """ class ReadNoise: @@ -20,7 +57,9 @@ def __init__( noise_model_scaling=1.0, # originally 0.75 amplitude_scale=0.2, # originally 0.33 n_iter=200, + sr_fraction=None, serial=True, + covariance_matrices=None, **kwargs ): @@ -30,6 +69,35 @@ def __init__( self.outScale = noise_model_scaling self.n_iter = n_iter self.smoothCol = serial + self._skyFrame = None +# self._sr_fraction = sr_fraction +# self._sr_fraction_optimised = None + +# @property +# def sr_fraction(self): +# """ +# RMS value of read noise, in units of electrons +# """ +# if self._sr_fraction is not None: return self._sr_fraction +# #if self._sr_fraction_optimised is None: self.optimise_sr_fraction() +# return self._sr_fraction_optimised +# +# @sr_fraction.setter +# def sr_fraction(self, value): +# self._sr_fraction = value +# +# @property +# def sr_fraction_optimised(self, **kwargs): +# """ +# Value of S+R splitting fraction that will minimise pixel-to-pixel covariance +# after CTI correction +# """ +# if self._sr_fraction_optimised is None: self.optimise_sr_fraction(**kwargs) +# return self._sr_fraction_optimised +# +# @sr_fraction_optimised.setter +# def sr_fraction_optimised(self, value): +# self._sr_fraction_optimised = value @property def sigma(self): @@ -43,6 +111,7 @@ def sigma(self, value): if value < 0: value = 0. self._sigma = value + ############### ############### def determine_noise_model(self, imageIn, imageOut): @@ -158,6 +227,7 @@ def determine_noise_model(self, imageIn, imageOut): return (dval0u * w0 / 6) + (dval9u * w9 / 6) +(dmod1u * w1 / 6) + (dmod2u * w2 / 6) +(cmod1u * wc1 / 6) + (cmod2u * wc2 / 6) else: return (dval0u * w0 * 0.25) + (dval9u * w9 * 0.25) +(dmod1u * w1 * 0.25) + (dmod2u * w2 * 0.25) + ############### ############### def estimate_read_noise_model_from_image(self, image): @@ -207,6 +277,7 @@ def estimate_read_noise_model_from_image(self, image): return imageOut,noiseImage #raise NotImplementedError #return image + ############### ############### def estimate_residual_covariance( @@ -343,11 +414,38 @@ def _fitter_function(self,x,intercept,slope): y = intercept + slope * x return y ############### + """ + Adjust parameters of the S+R algorithm that estimates the read noise in an image. + The image itself is not required; merely its dimensions and sky level parameters. + + It works by simulating a subchip_size x subchip_size regions of the image, one + at each corner of the CCD, then tries to minimise the pixel-to-pixel covariance + after CTI correction in the most distant corner. + + This merely adjusts the self parameters contained within the ReadNoise instance. + + Parameters + ---------- + background_level : Float + The mean (sky) background level across the image. + + background_sigma : Float + The rms variation per pixel around the background level. + If not specified, it will assume sqrt(background_level) for shot noise. + + n_pixels : Float or (Float, Float) + The number of pixels in the CCD. If a single number is supplied, it assumes + the CCD is square. If two numbers are supplied, the assumed order is (n_y,n_x). + + subchip_size : Float + size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) + + """ def optimise_parameters( self, background_level, background_sigma=None, - chip_size=2048, #the size of the entire CCD over which the procedure will be run + n_pixels=2048, #the size of the entire CCD over which the procedure will be run subchip_size=500, #size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) matrix_size=5, #covariance matrix size (NxN array) **kwargs @@ -356,15 +454,17 @@ def optimise_parameters( S+R optimisation routine. Given a specified set of CTI trap parameters, this routine calculates the optimum S+R fraction to minimise image correlations during correction ''' - #if sky sigma is not set, assume sqrt(N) + # Parse inputs + if type(n_pixels) == int: n_pixels=(n_pixels,n_pixels) + chip_size = n_pixels if background_sigma==None: background_sigma = np.sqrt(background_level) #set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) if 'parallel_roe' in kwargs: - kwargs['parallel_roe'].prescan_offset = chip_size+(subchip_size//2) + kwargs['parallel_roe'].prescan_offset = n_pixels[0]+(subchip_size//2) if 'serial_roe' in kwargs: - kwargs['serial_roe'].prescan_offset = chip_size+(subchip_size//2) + kwargs['serial_roe'].prescan_offset = n_pixels[1]+(subchip_size//2) #container for optimised values self.optVals = {} @@ -555,7 +655,7 @@ def optimise_parameters( # image, # background_level=None, # chip_size=500, -# matrix_size=5, +# matrix_size=matrix_size, # **kwargs # ): # ''' @@ -573,6 +673,18 @@ def optimise_parameters( # if background_level == None: # background_level = np.median(image) # +# # +# optimise_parameters( +# self, +# background_level, +# background_sigma=None, +# chip_size=image_nrows, #the size of the entire CCD over which the procedure will be run +# subchip_size=500, #size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) +# matrix_size=5, #covariance matrix size (NxN array) +# **kwargs +# +# +# # # if 'parallel_traps' in kwargs: # if kwargs['parallel_traps'] is not None: From f9c3ec60a10b60f2435d568887c8eaa6eb500254 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Tue, 31 Jan 2023 16:03:57 +0000 Subject: [PATCH 11/25] update read_noise.py initial re-factoring / cleaning of the code to make the interface more user-friendly. Also added a convenience function (set_arctic_parameters) to save Arctic CTI parameters ahead of time, instead of user-inputting them in each analysis function --- python/arcticpy/read_noise.py | 419 ++++++++++------------------------ 1 file changed, 120 insertions(+), 299 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 6252945..7165b29 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -69,7 +69,10 @@ def __init__( self.outScale = noise_model_scaling self.n_iter = n_iter self.smoothCol = serial - self._skyFrame = None + self.sigmaSky = None + self.skyFrameSim = None + self.readnoiseFrameSim = None + self.arcKwargs = {} # self._sr_fraction = sr_fraction # self._sr_fraction_optimised = None @@ -114,6 +117,17 @@ def sigma(self, value): ############### ############### + def set_arctic_parameters( + self, + **kwargs + ): + ''' + Function for pre-setting arctic parameters (such as CCD, trap density, and ROE) + This is a convenience function to eliminate multiple, bulky keyword argument calls in other functions + ''' + self.arcKwargs = kwargs + ############### + ############### def determine_noise_model(self, imageIn, imageOut): ''' Method for estimating readnoise on image (in S+R fashion) @@ -276,8 +290,6 @@ def estimate_read_noise_model_from_image(self, image): break return imageOut,noiseImage #raise NotImplementedError - #return image - ############### ############### def estimate_residual_covariance( @@ -359,23 +371,24 @@ def _create_initial_sim_images( self, background_level, background_sigma, - image_size=500 + image_size=500, + overwrite=False ): ''' subroutine to generate sky_background and readnoise frames for S+R simulations These will stay fixed in each simulation, to control random noise fluctuations ''' - - #if background_sigma==None: - # background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) #create sky frame skyFrame = np.random.normal(background_level, background_sigma, (image_size,image_size)) + self.skyFrameSim = skyFrame + #create readnoise_frame noiseFrame = np.random.normal(0, self.sigmaRN, (image_size,image_size)) + self.readnoiseFrameSim = noiseFrame - return skyFrame,noiseFrame - + return + ############### ############### def _estimate_residual_covariance_for_opt_premade( self, @@ -390,7 +403,7 @@ def _estimate_residual_covariance_for_opt_premade( ''' #add CTI effects to skyFrame ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) - #add read noise to STI-trailed image + #add read noise to CTI-trailed image readNoiseAddedFrame = ctiTrailedFrame + noiseFrame #do S+R routine sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) @@ -408,57 +421,69 @@ def _estimate_residual_covariance_for_opt_premade( fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) fomDiff = fomSR - fomBenchmark - return fomSR,fomDiff + return fomSR,fomDiff + ############### ############### def _fitter_function(self,x,intercept,slope): y = intercept + slope * x return y ############### - """ - Adjust parameters of the S+R algorithm that estimates the read noise in an image. - The image itself is not required; merely its dimensions and sky level parameters. - - It works by simulating a subchip_size x subchip_size regions of the image, one - at each corner of the CCD, then tries to minimise the pixel-to-pixel covariance - after CTI correction in the most distant corner. - - This merely adjusts the self parameters contained within the ReadNoise instance. - - Parameters - ---------- - background_level : Float - The mean (sky) background level across the image. - - background_sigma : Float - The rms variation per pixel around the background level. - If not specified, it will assume sqrt(background_level) for shot noise. - - n_pixels : Float or (Float, Float) - The number of pixels in the CCD. If a single number is supplied, it assumes - the CCD is square. If two numbers are supplied, the assumed order is (n_y,n_x). - - subchip_size : Float - size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) - - """ - def optimise_parameters( + ############### + def optimise_SR_fraction( self, background_level, background_sigma=None, - n_pixels=2048, #the size of the entire CCD over which the procedure will be run - subchip_size=500, #size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) + n_pixels=2048, #the size of the entire CCD over which the procedure will be run + subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) matrix_size=5, #covariance matrix size (NxN array) + fom_method='box', **kwargs ): ''' - S+R optimisation routine. Given a specified set of CTI trap parameters, this routine calculates the optimum S+R fraction to minimise image correlations during correction + Adjust parameters of the S+R algorithm that estimates the read noise in an image. + The image itself is not required; merely its dimensions and sky level parameters. + + It works by simulating a subchip_size x subchip_size regions of the image, one + at each corner of the CCD, then tries to minimise the pixel-to-pixel covariance + after CTI correction in the most distant corner. + + This merely adjusts the self parameters contained within the ReadNoise instance. + + Parameters + ---------- + background_level : Float + The mean (sky) background level across the image. + + background_sigma : Float + The rms variation per pixel around the background level. + If not specified, it will assume sqrt(background_level) for shot noise. + + n_pixels : Float or (Float, Float) + The number of pixels in the CCD. If a single number is supplied, it assumes + the CCD is square. If two numbers are supplied, the assumed order is (n_y,n_x). + + subchip_size : Float + size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) + + matrix_size : Int + Size of covariance matrix used to estimate covariance. By default the program creates a 5x5 matrix + + fom_method : String + Method used to estimate mean covariance. Can be: + box : take a square (3x3) region around the central pixel + row : take all cells along the central row + column : take all cells along the central column + + **kwargs : parameters that characterise CTI features in Arctic (trap density, CCD, read out electronics (ROE) descriptions) ''' # Parse inputs - if type(n_pixels) == int: n_pixels=(n_pixels,n_pixels) + if type(n_pixels) == int: + n_pixels=(n_pixels,n_pixels) chip_size = n_pixels if background_sigma==None: - background_sigma = np.sqrt(background_level) + background_sigma = np.sqrt(background_level) + self.sigmaSky = background_sigma #set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) if 'parallel_roe' in kwargs: @@ -469,62 +494,91 @@ def optimise_parameters( #container for optimised values self.optVals = {} - #pre-make the sky background and readnoise images, keep these constant over all quadrants - skyFrame, readNoiseFrame = self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) + #if they don't exist, make the sky background and readnoise images for the simulations + self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) #run S+R routine at 0% and 100% S+R fraction result_array = np.array([]) matrix_array = np.zeros((2,matrix_size,matrix_size)) sr_frac = np.array([0.0,1.0]) for frac in sr_frac: - raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac,matrix_size=matrix_size,**kwargs) + print('\nestimating S+R covariance at %d percent level'%(100*frac)) + raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac,matrix_size=matrix_size,**self.arcKwargs,**kwargs) matrix_array[int(frac)] = correction_matrix - result = self.figure_of_merit(correction_matrix) #TODO: check to see if changing subgrid_size actually matters + result = self.figure_of_merit(correction_matrix,fom_method=fom_method) #TODO: check to see if changing subgrid_size actually matters result_array = np.append(result_array,result) - print('both progression:',result_array) #interpolate between the results to determine the point of minimum residual covariance a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) m = a_fit[1] b = a_fit[0] - xint = -b/m + xint = -b/m #this intercept will be the optimised S+R fraction (where mean covariance=0) - frac_opt = xint #set the optimized S+R fraction + #store final optimised fraction as a class variable + self.optVals['optSRfrac'] = xint + ############### + ############### + def measure_covariance_quadrants( + self, + n_pixels=2048, #the size of the entire CCD over which the procedure will be run + subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) + matrix_size=5, #covariance matrix size (NxN array) + fom_method='box', + **kwargs + ): + ''' + Apply optimised S+R correction to the four quadrants of the CCD (close to readout, far from parallel register, far from serial register, far from both) + and estimate a covariance matrix for each quadrant. These matrices can be used to correct any residual covariance in weak lensing shapes. + ''' + + #update any keyword arguments + allKwargs = kwargs|self.arcKwargs + + frac_opt = self.optVals['optSRfrac'] #set the optimized S+R fraction + if type(n_pixels) == int: + n_pixels=(n_pixels,n_pixels) + chip_size = n_pixels + + ##set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) + #if 'parallel_roe' in allKwargs: + # kwargs['parallel_roe'].prescan_offset = n_pixels[0]+(subchip_size//2) + #if 'serial_roe' in allKwargs: + # kwargs['serial_roe'].prescan_offset = n_pixels[1]+(subchip_size//2) + #re-run the S+R routine with the optimised level - raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs) - raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs) #this is dumb...do it better + raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) + raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) #this is dumb...do it better #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise - kwargs_noCTI = kwargs.copy() + kwargs_noCTI = kwargs|self.arcKwargs kwargs_noCTI['parallel_traps']=None kwargs_noCTI['serial_traps']=None #effectively, we are removing the effects of CTI, but still calculating a covariance matrix - raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) - raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_noCTI) #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated benchmark_matrix = raw_matrix_opt_noCTI*0 centrePix = matrix_size//2 - benchmark_matrix[centrePix,centrePix] = self.sigmaRN**2 + background_sigma**2 + benchmark_matrix[centrePix,centrePix] = self.sigmaRN**2 + self.sigmaSky**2 #calculate the simulation-noise residual residual_benchmark_matrix = raw_matrix_opt_noCTI - benchmark_matrix #Finally, if both parallel and serial CTI are present, calculate covariances of the "cross-region" chip quadrants (far from serial readout but close to parallel readout, and vice-versa) - if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): - if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): - kwargs_parallelOnly = kwargs.copy() + if ('parallel_traps' in allKwargs)&('serial_traps' in allKwargs): + if (allKwargs['parallel_traps'] is not None)&(allKwargs['serial_traps'] is not None): + kwargs_parallelOnly = kwargs|self.arcKwargs kwargs_parallelOnly['serial_traps']=None #make a parallel-only quadrant - kwargs_serialOnly = kwargs.copy() + kwargs_serialOnly = kwargs|self.arcKwargs kwargs_serialOnly['parallel_traps']=None #make a serial-only quadrant - raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) - raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance_for_opt_premade(skyFrame,readNoiseFrame,0,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_serialOnly) #package all relevant quantities into optVals and return - self.optVals['optSRfrac'] = frac_opt self.optVals['combinedQuadMatrix'] = raw_matrix_opt self.optVals['combinedQuadMatrix_diff'] = correction_matrix_opt self.optVals['combinedQuadMatrix_noSR'] = raw_matrix_opt_noSR @@ -543,239 +597,7 @@ def optimise_parameters( self.optVals['noCTIQuadMatrix_diff_noSR'] = correction_matrix_opt_noCTI self.optVals['benchmark'] = benchmark_matrix self.optVals['benchmark_resid'] = residual_benchmark_matrix - - #return optVals ############### -# ############### -# def optimise_parameters( -# self, -# background_level, -# chip_size=500, -# matrix_size=5, -# **kwargs -# ##figure_of_merit=figure_of_merit(), # should probably pass a function here -# ): -# ''' -# S+R optimisation routine. Given a specified set of CTI trap parameters, this routine calculates the optimum S+R fraction to minimise image correlations during correction -# ''' -# optVals = {} -# -# kwargs['parallel_roe'].prescan_offset = 1900 -# kwargs['serial_roe'].prescan_offset = 1900 -# -# if 'parallel_traps' in kwargs: -# if kwargs['parallel_traps'] is not None: -# kwargs_parallel = kwargs.copy() -# kwargs_parallel['serial_traps']=None #make a parallel-only quadrant -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## -# for frac in sr_frac: -# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs_parallel) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# print('parallel progression:',result_array) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['parallelQuadMatrix'] = mean_grid -# optVals['parallelQuadFrac'] = xint -# -# if 'serial_traps' in kwargs: -# if kwargs['serial_traps'] is not None: -# kwargs_serial = kwargs.copy() -# kwargs_serial['parallel_traps']=None #make a serial-only quadrant -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## -# for frac in sr_frac: -# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs_serial) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# print('serial progression:',result_array) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['serialQuadMatrix'] = mean_grid -# optVals['serialQuadFrac'] = xint -# -# if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): -# if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.arange(0,1.01,0.1)##np.array([0.0,0.5,1.0])## -# for frac in sr_frac: -# raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,chip_size=chip_size,matrix_size=matrix_size,**kwargs) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# print('both progression:',result_array) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['combinedQuadMatrix'] = mean_grid -# optVals['combinedQuadFrac'] = xint -# -# -# return optVals -# -# ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) -# ##covar = self.covariance_matrix_from_image(image) -# -# ############### -# ############### -# def optimise_parameters_from_image( -# self, -# image, -# background_level=None, -# chip_size=500, -# matrix_size=matrix_size, -# **kwargs -# ): -# ''' -# version of the S+R optimiser routine, but parameters can be determined from a supplied image rather than manually specified -# ''' -# optVals = {} -# image_nrows = image.shape[0] -# image_ncols = image.shape[1] -# -# #use CTI prescan offset to ensure sample region is at the far edge of the full chip -# kwargs['parallel_roe'].prescan_offset = kwargs['parallel_roe'].prescan_offset + image_nrows - chip_size//2 -# kwargs['serial_roe'].prescan_offset = kwargs['serial_roe'].prescan_offset + image_ncols - chip_size//2 -# -# #if background nevel is not specified, estimate using the median pixel value -# if background_level == None: -# background_level = np.median(image) -# -# # -# optimise_parameters( -# self, -# background_level, -# background_sigma=None, -# chip_size=image_nrows, #the size of the entire CCD over which the procedure will be run -# subchip_size=500, #size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) -# matrix_size=5, #covariance matrix size (NxN array) -# **kwargs -# -# -# -# -# if 'parallel_traps' in kwargs: -# if kwargs['parallel_traps'] is not None: -# kwargs_parallel = kwargs.copy() -# kwargs_parallel['serial_traps']=None #make a parallel-only quadrant -# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip -# ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) -# for frac in sr_frac: -# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_parallel) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['parallelQuadMatrix'] = mean_grid -# optVals['parallelQuadFrac'] = xint -# -# if 'serial_traps' in kwargs: -# if kwargs['serial_traps'] is not None: -# kwargs_serial = kwargs.copy() -# kwargs_serial['parallel_traps']=None #make a serial-only quadrant -# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip -# ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) -# for frac in sr_frac: -# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs_serial) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['serialQuadMatrix'] = mean_grid -# optVals['serialQuadFrac'] = xint -# -# if ('parallel_traps' in kwargs)&('serial_traps' in kwargs): -# if (kwargs['parallel_traps'] is not None)&(kwargs['serial_traps'] is not None): -# ###use CTI prescan offset to ensure sample region is at the far edge of the full chip -# ##kwargs_parallel['parallel_roe'].prescan_offset = kwargs_parallel['parallel_roe'].prescan_offset + image_nrows - chip_size//2 -# ##kwargs_serial['serial_roe'].prescan_offset = kwargs_serial['serial_roe'].prescan_offset + image_ncols - chip_size//2 -# #things to compare over iterations -# result_array = np.array([]) -# matrix_array = np.zeros((11,matrix_size,matrix_size)) -# sr_frac = np.array([0.0,0.5,1.0])##np.arange(0,1.01,0.1) -# for frac in sr_frac: -# correction_matrix = self._estimate_residual_covariance_for_opt(background_level,frac,**kwargs) -# matrix_array[int(frac*10)] = correction_matrix -# result = self.figure_of_merit(correction_matrix) #see if changing subgrid_size actually matters -# result_array = np.append(result_array,result) -# -# a_fit,cov=curve_fit(self._fitter_function,sr_frac,result_array,absolute_sigma=True) -# m = a_fit[1] -# b = a_fit[0] -# xint = -b/m -# -# lo = np.floor(xint*10).astype(int) -# hi = np.ceil(xint*10).astype(int) -# mean_grid = (matrix_array[lo]+matrix_array[hi])/2 -# -# optVals['combinedQuadMatrix'] = mean_grid -# optVals['combinedQuadFrac'] = xint -# -# -# return optVals -# -# ##outputFrame,noiseFrame = self.estimate_read_noise_model_from_image(image) -# ##covar = self.covariance_matrix_from_image(image) -# -# ############### ############### def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None): ''' @@ -807,7 +629,6 @@ def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None) result_mean = (np.sum(covariance_matrix[ystart:yend,xcenter]) - covariance_matrix[ycenter,xcenter])/4 #sum over central column (for parallel CTI) #raise NotImplementedError return result_mean - ############### ############### def covariance_matrix_from_image(self, image, matrix_size=5,fprSize=5): From a8ce2dd73984ea852e4400ff9f77ca8a0f74e1ef Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Wed, 1 Feb 2023 01:17:49 +0000 Subject: [PATCH 12/25] Update read_noise.py more cleanup: removed redundant functions, added better comments Also included a function for running the S+R optimisation using an astronomical data frame instead of pure simulation --- python/arcticpy/read_noise.py | 152 ++++++++++++++-------------------- 1 file changed, 62 insertions(+), 90 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 7165b29..b185825 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -124,6 +124,7 @@ def set_arctic_parameters( ''' Function for pre-setting arctic parameters (such as CCD, trap density, and ROE) This is a convenience function to eliminate multiple, bulky keyword argument calls in other functions + If desired, the user can overwrite these values (on the fly) with explicit keyword arguments ''' self.arcKwargs = kwargs ############### @@ -131,7 +132,7 @@ def set_arctic_parameters( def determine_noise_model(self, imageIn, imageOut): ''' Method for estimating readnoise on image (in S+R fashion) - assumes parallel+serial by default + assumes parallel+serial CTI trailing by default ''' readNoiseAmp = self.sigmaRN @@ -292,91 +293,23 @@ def estimate_read_noise_model_from_image(self, image): #raise NotImplementedError ############### ############### - def estimate_residual_covariance( - self, - background_level, - background_sigma=None, - chip_size=500, #size, in pixels, of CCD (assumes square) - matrix_size=5, #size of covariance grid, in pixels (also assumes square) - **kwargs - ): - if background_sigma==None: - background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) - - #create sky frame - skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) - #add CTI effects - ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) - #add read noise - noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) - readNoiseAddedFrame = ctiTrailedFrame + noiseFrame - #do S+R routine - sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) - #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) - #re-add R frame to correction - outputFrame = ctiCorrectedFrame + rFrame - - #determine covariance FOMs - fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) - fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) - fomDiff = fomSR - fomBenchmark - - return fomSR,fomDiff - - #raise NotImplementedError - #return np.array([[0,0,0,0,0],[0,0,0,0,0],[0,0,1,0,0],[0,0,0,0,0],[0,0,0,0,0]]) - - ############### - ############### - def _estimate_residual_covariance_for_opt( - self, - background_level, - sr_fraction, - background_sigma=None, - chip_size=500, #size, in pixels, of CCD (assumes square) - matrix_size=5, #size of covariance grid, in pixels (also assumes square) - **kwargs - ): - if background_sigma==None: - background_sigma = np.sqrt(background_level) #if sky sigma is not set, assume sqrt(N) - - #create sky frame - skyFrame = np.random.normal(background_level, background_sigma, (chip_size,chip_size)) - #add CTI effects - ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) - #add read noise - noiseFrame = np.random.normal(0, self.sigmaRN, (chip_size,chip_size)) - readNoiseAddedFrame = ctiTrailedFrame + noiseFrame - #do S+R routine - sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) - #rescale S+R correction to a fractional value (for optimization) - sFrame+=rFrame - rFrame*=sr_fraction - sFrame-=rFrame - #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) - #re-add R frame to correction - outputFrame = ctiCorrectedFrame + rFrame - - #determine covariance FOMs - fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) - fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) - fomDiff = fomSR - fomBenchmark - - return fomSR,fomDiff - ############### - ############### def _create_initial_sim_images( self, background_level, background_sigma, image_size=500, - overwrite=False + overwrite=False #figure out how to implement this (it fails currently) ): ''' - subroutine to generate sky_background and readnoise frames for S+R simulations - These will stay fixed in each simulation, to control random noise fluctuations + A subroutine to generate sky_background and readnoise frames for S+R simulations + + These components will create a baseline "clean" image (sky + readnoise) that we + would expect to observe in the absence of CTI smearing effects + in each simulated quadrant. Keeping this fixed will control random noise fluctuations + ("simulation noise") when estimating covariances throughout the simulation. + + Note: This routine will be normally be called in + rather than through direct user input ''' #create sky frame @@ -387,10 +320,13 @@ def _create_initial_sim_images( noiseFrame = np.random.normal(0, self.sigmaRN, (image_size,image_size)) self.readnoiseFrameSim = noiseFrame + #generate covariance matrix from clean image + + return ############### ############### - def _estimate_residual_covariance_for_opt_premade( + def _estimate_residual_covariance( self, skyFrame, noiseFrame, @@ -425,6 +361,10 @@ def _estimate_residual_covariance_for_opt_premade( ############### ############### def _fitter_function(self,x,intercept,slope): + ''' + simple functional form to optimize a (linear) S+R fit using covariance matrix data + passed to python optiser in optimise_SR_fraction, not needed by the user + ''' y = intercept + slope * x return y ############### @@ -495,7 +435,18 @@ def optimise_SR_fraction( self.optVals = {} #if they don't exist, make the sky background and readnoise images for the simulations - self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) + if (self.skyFrameSim is None) & (self.readnoiseFrameSim is None): + self._create_initial_sim_images(background_level,background_sigma,image_size=subchip_size) + + #create "simulation noise" covariance matrix (estimated from the sky+readnoise image) + #in this case, the fpr decrement is set to zero, because there is no CTI trailing + sim_matrix = self.covariance_matrix_from_image(self.skyFrameSim+self.readnoiseFrameSim,matrix_size=matrix_size,fprSize=5) + + #ideally, the matrix should be all zeros except for the centre square (== sigmaSky**2 + sigmaReadnoise**2) + #therefore, subtracting this from sim_matrix will provide the simulation noise covariance + sim_matrix[matrix_size//2,matrix_size//2] -= (self.sigmaRN**2+self.sigmaSky**2) + + self.optVals['pre-benchmark'] = sim_matrix #run S+R routine at 0% and 100% S+R fraction result_array = np.array([]) @@ -503,7 +454,7 @@ def optimise_SR_fraction( sr_frac = np.array([0.0,1.0]) for frac in sr_frac: print('\nestimating S+R covariance at %d percent level'%(100*frac)) - raw_matrix,correction_matrix = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac,matrix_size=matrix_size,**self.arcKwargs,**kwargs) + raw_matrix,correction_matrix = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac,matrix_size=matrix_size,**self.arcKwargs,**kwargs) matrix_array[int(frac)] = correction_matrix result = self.figure_of_merit(correction_matrix,fom_method=fom_method) #TODO: check to see if changing subgrid_size actually matters result_array = np.append(result_array,result) @@ -517,6 +468,27 @@ def optimise_SR_fraction( self.optVals['optSRfrac'] = xint ############### ############### + def optimise_SR_from_data( + self, + image, + subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) + matrix_size=5, #covariance matrix size (NxN array) + fom_method='box', + **kwargs + ): + ''' + A wrapper function for running the S+R optimisation routine using a real astronomical image rather than theoretical values. + This routine still calls but the sky paramerters and image size are determined from the data itself. + ''' + + image_shape = image.shape + sky_level = np.median(image) + sky_back = np.sqrt(sky_level) #assume pure shot noise for now + + self.optimise_SR_fraction(sky_level,sky_back,image_shape,subchip_size,matrix_size,fom_method,**kwargs) + + ############### + ############### def measure_covariance_quadrants( self, n_pixels=2048, #the size of the entire CCD over which the procedure will be run @@ -546,16 +518,16 @@ def measure_covariance_quadrants( # kwargs['serial_roe'].prescan_offset = n_pixels[1]+(subchip_size//2) #re-run the S+R routine with the optimised level - raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) - raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) #this is dumb...do it better + raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) + raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**self.arcKwargs,**kwargs) #this is dumb...do it better #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise kwargs_noCTI = kwargs|self.arcKwargs kwargs_noCTI['parallel_traps']=None kwargs_noCTI['serial_traps']=None #effectively, we are removing the effects of CTI, but still calculating a covariance matrix - raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) - raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_noCTI) #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated @@ -573,10 +545,10 @@ def measure_covariance_quadrants( kwargs_serialOnly = kwargs|self.arcKwargs kwargs_serialOnly['parallel_traps']=None #make a serial-only quadrant - raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) - raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance_for_opt_premade(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_serialOnly) #package all relevant quantities into optVals and return self.optVals['combinedQuadMatrix'] = raw_matrix_opt From 38cee6ddfe6baaf8f2e199ebf2198f6c6c500d42 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 13 Feb 2023 04:38:14 +0000 Subject: [PATCH 13/25] Update read_noise.py Additional refactoring of the code, better specifying front-facing functions from back-end ones. Also improved documentation --- python/arcticpy/read_noise.py | 507 +++++++++++++++++++--------------- 1 file changed, 287 insertions(+), 220 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index b185825..2803b18 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -72,7 +72,11 @@ def __init__( self.sigmaSky = None self.skyFrameSim = None self.readnoiseFrameSim = None + self.optimised_SR_fraction = None self.arcKwargs = {} + self.covarianceMatrices = {} + self.dataFrames = {} + # self._sr_fraction = sr_fraction # self._sr_fraction_optimised = None @@ -116,136 +120,52 @@ def sigma(self, value): self._sigma = value ############### + # + #USER-FACING FUNCTIONS + # ############### def set_arctic_parameters( self, **kwargs ): ''' - Function for pre-setting arctic parameters (such as CCD, trap density, and ROE) + Function for pre-setting arCTIc parameters (such as CCD, trap density, and ROE) This is a convenience function to eliminate multiple, bulky keyword argument calls in other functions - If desired, the user can overwrite these values (on the fly) with explicit keyword arguments + If desired, the user can still specify or overwrite these values (on the fly) in the other functions + by explicitly calling the keyword arguments there. + + Parameters + ---------- + **kwargs : variables + Keyword arguments specifying arCTIc parameters ''' self.arcKwargs = kwargs - ############### ############### - def determine_noise_model(self, imageIn, imageOut): - ''' - Method for estimating readnoise on image (in S+R fashion) - assumes parallel+serial CTI trailing by default + ############### + def estimate_read_noise_model_from_image( + self, + image, + sr_fraction = 1.0 + ): ''' - readNoiseAmp = self.sigmaRN - - dval0 = imageIn - imageOut - dval0u = dval0.copy() - - dval0u[dval0u>1] = 1 - dval0u[dval0u<-1] = -1 - - dval9 = imageIn*0 - dcount = imageIn*0 - - dval9[:-1,:-1]+=(imageIn[1: ,1: ]-imageOut[1: ,1: ]); dcount[:-1,:-1]+=1 - dval9[:-1,: ]+=(imageIn[1: ,: ]-imageOut[1: ,: ]); dcount[:-1,: ]+=1 - dval9[:-1,1: ]+=(imageIn[1: ,:-1]-imageOut[1: ,:-1]); dcount[:-1,1: ]+=1 - dval9[: ,:-1]+=(imageIn[: ,1: ]-imageOut[: ,1: ]); dcount[: ,:-1]+=1 - dval9[: ,: ]+=(imageIn[: ,: ]-imageOut[: ,: ]); dcount[: ,: ]+=1 - dval9[: ,1: ]+=(imageIn[: ,:-1]-imageOut[: ,:-1]); dcount[: ,1: ]+=1 - dval9[1: ,:-1]+=(imageIn[:-1,1: ]-imageOut[:-1,1: ]); dcount[1: ,:-1]+=1 - dval9[1: ,: ]+=(imageIn[:-1,: ]-imageOut[:-1,: ]); dcount[1: ,: ]+=1 - dval9[1: ,1: ]+=(imageIn[:-1,:-1]-imageOut[:-1,:-1]); dcount[1: ,1: ]+=1 - - dval9/=dcount - - readNoiseAmpFraction = self.ampScale - dval9u = dval9.copy() - if type(readNoiseAmp)==np.ndarray: - dval9u = dval9u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dval9u > readNoiseAmp*readNoiseAmpFraction] - dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = (readNoiseAmp*-readNoiseAmpFraction)[dval9u < readNoiseAmp*-readNoiseAmpFraction] - dval9u = dval9u.reshape(imageIn.shape) - readNoiseAmp = readNoiseAmp.reshape(imageIn.shape) - else: - dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = readNoiseAmp*-readNoiseAmpFraction - - dmod1 = imageIn*0 - dmod1[1:,:] = imageOut[:-1,:] - imageOut[1:,:] - dmod2 = imageIn*0 - dmod2[:-1,:] = imageOut[1:,:] - imageOut[:-1,:] - - if self.smoothCol: - cmod1 = imageIn*0 - cmod1[:,1:] = imageOut[:,:-1] - imageOut[:,1:] - cmod2 = imageIn*0 - cmod2[:,:-1] = imageOut[:,1:] - imageOut[:,:-1] - - dmod1u = dmod1.copy() - if type(readNoiseAmp)==np.ndarray: - dmod1u = dmod1u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - dmod1u[dmod1u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod1u>readNoiseAmp*readNoiseAmpFraction] - dmod1u[dmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dmod1u[dmod1ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod2u>readNoiseAmp*readNoiseAmpFraction] - dmod2u[dmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dmod2u[dmod2ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod1u>readNoiseAmp*readNoiseAmpFraction] - cmod1u[cmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - cmod1u[cmod1ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod2u>readNoiseAmp*readNoiseAmpFraction] - cmod2u[cmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - cmod2u[cmod2u + + sr_fraction: float + scale fraction specifying what percentage of read noise should be separated into the R + frame. Default is 100%, but this can be changed based on other information (e.g., the + output of + + + ''' ampReadNoise = self.sigmaRN imageIn = image @@ -262,7 +182,7 @@ def estimate_read_noise_model_from_image(self, image): print('iter','model_rms','target_rms','residual') for s in range(self.n_iter): oldchk = ampReadNoise-rmsGlobal - imageAdj= self.determine_noise_model(imageIn,imageOut) + imageAdj= self._determine_noise_model(imageIn,imageOut) if (ampReadNoise-rmsGlobal) > 0: imageOut += imageAdj * self.outScale / smoother @@ -289,93 +209,23 @@ def estimate_read_noise_model_from_image(self, image): else: if abs(ampReadNoise - rmsGlobal) < 0.0001: break - return imageOut,noiseImage - #raise NotImplementedError - ############### - ############### - def _create_initial_sim_images( - self, - background_level, - background_sigma, - image_size=500, - overwrite=False #figure out how to implement this (it fails currently) - ): - ''' - A subroutine to generate sky_background and readnoise frames for S+R simulations - - These components will create a baseline "clean" image (sky + readnoise) that we - would expect to observe in the absence of CTI smearing effects - in each simulated quadrant. Keeping this fixed will control random noise fluctuations - ("simulation noise") when estimating covariances throughout the simulation. - Note: This routine will be normally be called in - rather than through direct user input - ''' - - #create sky frame - skyFrame = np.random.normal(background_level, background_sigma, (image_size,image_size)) - self.skyFrameSim = skyFrame - - #create readnoise_frame - noiseFrame = np.random.normal(0, self.sigmaRN, (image_size,image_size)) - self.readnoiseFrameSim = noiseFrame - - #generate covariance matrix from clean image - - - return - ############### + #scale the smooth and noise frames if != 1 + if sr_fraction !=1: + imageOut+=noiseImage + noiseImage*=sr_fraction + imageOut-=noiseImage + + return imageOut,noiseImage #These are the "S" and "R" frames, respectively ############### - def _estimate_residual_covariance( - self, - skyFrame, - noiseFrame, - sr_fraction, - matrix_size=5, #size of covariance grid, in pixels (also assumes square) - **kwargs - ): - ''' - Estimate a covariance matrix for an optimising simulation, assuming the sky/noise frames have already been created - ''' - #add CTI effects to skyFrame - ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) - #add read noise to CTI-trailed image - readNoiseAddedFrame = ctiTrailedFrame + noiseFrame - #do S+R routine - sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame) - #rescale S+R correction to a fractional value (for optimization) - sFrame+=rFrame - rFrame*=sr_fraction - sFrame-=rFrame - #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) - #re-add R frame to correction - outputFrame = ctiCorrectedFrame + rFrame - - #determine covariance FOMs - fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) - fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) - fomDiff = fomSR - fomBenchmark - - return fomSR,fomDiff - ############### - ############### - def _fitter_function(self,x,intercept,slope): - ''' - simple functional form to optimize a (linear) S+R fit using covariance matrix data - passed to python optiser in optimise_SR_fraction, not needed by the user - ''' - y = intercept + slope * x - return y - ############### ############### def optimise_SR_fraction( self, background_level, background_sigma=None, - n_pixels=2048, #the size of the entire CCD over which the procedure will be run - subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) - matrix_size=5, #covariance matrix size (NxN array) + n_pixels=2048, + subchip_size=500, + matrix_size=5, fom_method='box', **kwargs ): @@ -388,6 +238,7 @@ def optimise_SR_fraction( after CTI correction in the most distant corner. This merely adjusts the self parameters contained within the ReadNoise instance. + The final optimised S+R value is stored as the class variable Parameters ---------- @@ -409,12 +260,12 @@ def optimise_SR_fraction( Size of covariance matrix used to estimate covariance. By default the program creates a 5x5 matrix fom_method : String - Method used to estimate mean covariance. Can be: - box : take a square (3x3) region around the central pixel + Method used to estimate the mean value of a covariance matrix, for figure-of-merit purposes. Can be: + box : take a square (3x3) region around the central pixel [DEFAULT] row : take all cells along the central row column : take all cells along the central column - **kwargs : parameters that characterise CTI features in Arctic (trap density, CCD, read out electronics (ROE) descriptions) + **kwargs : parameters that characterise CTI features in arCTIc (trap density, CCD, read out electronics (ROE) descriptions) ''' # Parse inputs @@ -468,7 +319,7 @@ def optimise_SR_fraction( self.optVals['optSRfrac'] = xint ############### ############### - def optimise_SR_from_data( + def optimise_SR_fraction_from_data( self, image, subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) @@ -479,15 +330,34 @@ def optimise_SR_from_data( ''' A wrapper function for running the S+R optimisation routine using a real astronomical image rather than theoretical values. This routine still calls but the sky paramerters and image size are determined from the data itself. + + Parameters + ---------- + image : numpy array + 2D numpy array containing the pixel values of the image + + subchip_size : Float + size of the cutout region, to test CTI behaviour in different regimes (e.g. far from readout, close to readout, etc.) + + matrix_size : Int + Size of covariance matrix used to estimate covariance. By default the program creates a 5x5 matrix + + fom_method : String + Method used to estimate the mean value of a covariance matrix, for figure-of-merit purposes. Can be: + box : take a square (3x3) region around the central pixel [DEFAULT] + row : take all cells along the central row + column : take all cells along the central column + + **kwargs : parameters that characterise CTI features in arCTIc (trap density, CCD, read out electronics (ROE) descriptions) + ''' image_shape = image.shape sky_level = np.median(image) sky_back = np.sqrt(sky_level) #assume pure shot noise for now - self.optimise_SR_fraction(sky_level,sky_back,image_shape,subchip_size,matrix_size,fom_method,**kwargs) - - ############### + self.optimise_SR_fraction(sky_level,sky_back,image_shape,subchip_size,matrix_size,fom_method,**kwargs) + ############### ############### def measure_covariance_quadrants( self, @@ -569,6 +439,217 @@ def measure_covariance_quadrants( self.optVals['noCTIQuadMatrix_diff_noSR'] = correction_matrix_opt_noCTI self.optVals['benchmark'] = benchmark_matrix self.optVals['benchmark_resid'] = residual_benchmark_matrix + ############### + ############### + def plot_matrix(self,covariance_matrix,supressCentralPix=True,title='MyPlotMatrix',**kwargs): + if supressCentralPix == True: + matrix = covariance_matrix.copy() + matrix_size = matrix.shape[0] + matrix[matrix_size//2,matrix_size//2] = 0 # set central pixel to zero, to better see correlation dynamic range + else: + matrix = covariance_matrix.copy() + + mpl.pyplot.clf() + mpl.pyplot.imshow(matrix,cmap='bwr',**kwargs) + mpl.pyplot.colorbar() + mpl.pyplot.title(title) + mpl.pyplot.show() + ############### + ############### + # + #BACKGROUND FUNCTIONS + # + ############### + def _determine_noise_model(self, imageIn, imageOut): + ''' + Method for estimating readnoise on image (in S+R fashion) + assumes parallel+serial CTI trailing by default + ''' + readNoiseAmp = self.sigmaRN + + dval0 = imageIn - imageOut + dval0u = dval0.copy() + + dval0u[dval0u>1] = 1 + dval0u[dval0u<-1] = -1 + + dval9 = imageIn*0 + dcount = imageIn*0 + + dval9[:-1,:-1]+=(imageIn[1: ,1: ]-imageOut[1: ,1: ]); dcount[:-1,:-1]+=1 + dval9[:-1,: ]+=(imageIn[1: ,: ]-imageOut[1: ,: ]); dcount[:-1,: ]+=1 + dval9[:-1,1: ]+=(imageIn[1: ,:-1]-imageOut[1: ,:-1]); dcount[:-1,1: ]+=1 + dval9[: ,:-1]+=(imageIn[: ,1: ]-imageOut[: ,1: ]); dcount[: ,:-1]+=1 + dval9[: ,: ]+=(imageIn[: ,: ]-imageOut[: ,: ]); dcount[: ,: ]+=1 + dval9[: ,1: ]+=(imageIn[: ,:-1]-imageOut[: ,:-1]); dcount[: ,1: ]+=1 + dval9[1: ,:-1]+=(imageIn[:-1,1: ]-imageOut[:-1,1: ]); dcount[1: ,:-1]+=1 + dval9[1: ,: ]+=(imageIn[:-1,: ]-imageOut[:-1,: ]); dcount[1: ,: ]+=1 + dval9[1: ,1: ]+=(imageIn[:-1,:-1]-imageOut[:-1,:-1]); dcount[1: ,1: ]+=1 + + dval9/=dcount + + readNoiseAmpFraction = self.ampScale + dval9u = dval9.copy() + if type(readNoiseAmp)==np.ndarray: + dval9u = dval9u.flatten() + readNoiseAmp = readNoiseAmp.flatten() + dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dval9u > readNoiseAmp*readNoiseAmpFraction] + dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = (readNoiseAmp*-readNoiseAmpFraction)[dval9u < readNoiseAmp*-readNoiseAmpFraction] + dval9u = dval9u.reshape(imageIn.shape) + readNoiseAmp = readNoiseAmp.reshape(imageIn.shape) + else: + dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction + dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = readNoiseAmp*-readNoiseAmpFraction + + dmod1 = imageIn*0 + dmod1[1:,:] = imageOut[:-1,:] - imageOut[1:,:] + dmod2 = imageIn*0 + dmod2[:-1,:] = imageOut[1:,:] - imageOut[:-1,:] + + if self.smoothCol: + cmod1 = imageIn*0 + cmod1[:,1:] = imageOut[:,:-1] - imageOut[:,1:] + cmod2 = imageIn*0 + cmod2[:,:-1] = imageOut[:,1:] - imageOut[:,:-1] + + dmod1u = dmod1.copy() + if type(readNoiseAmp)==np.ndarray: + dmod1u = dmod1u.flatten() + readNoiseAmp = readNoiseAmp.flatten() + dmod1u[dmod1u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod1u>readNoiseAmp*readNoiseAmpFraction] + dmod1u[dmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction + dmod1u[dmod1ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod2u>readNoiseAmp*readNoiseAmpFraction] + dmod2u[dmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction + dmod2u[dmod2ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod1u>readNoiseAmp*readNoiseAmpFraction] + cmod1u[cmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction + cmod1u[cmod1ureadNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod2u>readNoiseAmp*readNoiseAmpFraction] + cmod2u[cmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction + cmod2u[cmod2u + rather than through direct user input + ''' + + #create sky frame + skyFrame = np.random.normal(background_level, background_sigma, (image_size,image_size)) + self.skyFrameSim = skyFrame + + #create readnoise_frame + noiseFrame = np.random.normal(0, self.sigmaRN, (image_size,image_size)) + self.readnoiseFrameSim = noiseFrame + + #generate covariance matrix from clean image + + + return + ############### + ############### + def _estimate_residual_covariance( + self, + skyFrame, + noiseFrame, + sr_fraction, + matrix_size=5, #size of covariance grid, in pixels (also assumes square) + **kwargs + ): + ''' + Estimate a covariance matrix for an optimising simulation, assuming the sky/noise frames have already been created + ''' + #add CTI effects to skyFrame + ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) + #add read noise to CTI-trailed image + readNoiseAddedFrame = ctiTrailedFrame + noiseFrame + #do S+R routine + sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame,sr_fraction) + ###rescale S+R correction to a fractional value (for optimization) + ##sFrame+=rFrame + ##rFrame*=sr_fraction + ##sFrame-=rFrame + #clean CTI from S frame + ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) + #re-add R frame to correction + outputFrame = ctiCorrectedFrame + rFrame + + #determine covariance FOMs + fomSR = self.covariance_matrix_from_image(outputFrame,matrix_size=matrix_size) + fomBenchmark = self.covariance_matrix_from_image(skyFrame+noiseFrame,matrix_size=matrix_size) + fomDiff = fomSR - fomBenchmark + + return fomSR,fomDiff + ############### + ############### + def _fitter_function(self,x,intercept,slope): + ''' + simple functional form to optimize a (linear) S+R fit using covariance matrix data + passed to python optiser in optimise_SR_fraction, not needed by the user + ''' + y = intercept + slope * x + return y ############### ############### def figure_of_merit(self, covariance_matrix, fom_method='box',subgrid_size=None): @@ -628,17 +709,3 @@ def covariance_matrix_from_image(self, image, matrix_size=5,fprSize=5): return covariance_matrix ############### - ############### - def plot_matrix(self,covariance_matrix,supressCentralPix=True,title='MyPlotMatrix',**kwargs): - if supressCentralPix == True: - matrix = covariance_matrix.copy() - matrix_size = matrix.shape[0] - matrix[matrix_size//2,matrix_size//2] = 0 # set central pixel to zero, to better see correlation dynamic range - else: - matrix = covariance_matrix.copy() - - mpl.pyplot.clf() - mpl.pyplot.imshow(matrix,cmap='bwr',**kwargs) - mpl.pyplot.colorbar() - mpl.pyplot.title(title) - mpl.pyplot.show() From feb457273e015da68f97a63590d75e53fea74e63 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Wed, 15 Feb 2023 15:56:40 +0000 Subject: [PATCH 14/25] Update read_noise.py refactoring code, adding example usage cases in documentation --- python/arcticpy/read_noise.py | 243 ++++++++++++++++++++-------------- 1 file changed, 145 insertions(+), 98 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 2803b18..d75499a 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -11,18 +11,38 @@ This class provides a set of routines to predict this effect, and counteract it. -If you have an image as a 2D numpy array, image -and an arctic model with parameters parallel_roe, parallel_ccd, parallel_traps -run +################# +SAMPLE USAGE CASE +################# -readnoise = arctic.ReadNoise(4.5) +If you have an image as a 2D numpy array and an arctic model (with parameters such as parallel_roe, +parallel_ccd, parallel_traps, etc...) run the following: +1.) readnoise = arctic.ReadNoise(4.5) + The argument sets the level of readnoise (in units of electrons) -[optionally] -[readnoise.optimise_parameters] +2.) [optional] readnoise.set_arctic_parameters(**kwargs) + Input each arctic parameter as a keyword argument. + These will then be passed to subsequent function calls automatically + (Note: these choices can always be overridden in functions, if desired) +3.) [optional] readnoise.optimise_SR_fraction_from_image(image) + Input your data image. The function will determine the optimum + fraction of S+R separation to apply to minimise CTI covariance -skyImage, readNoiseImage = readnoise.estimate_read_noise_model_from_image(image, sr_fraction=None, +4.) generate_SR_frames_from_image(image) + Do the actual S+R splitting on your science image. If the SR + optimisation routine is not run, assume a correction level of 100% + +5.) [optional] calculate_covariance_corners_from image(image) + +6.) [optional] plot_covariance_matrices() + + +################# +EXAMPLE COMMANDS +################# +skyImage, readNoiseImage = readnoise.generate_SR_frames_from_image(image, sr_fraction=None, parallel_roe, parallel_ccd, parallel_traps) image_corrected = arctic.cti_correct(skyImage, @@ -31,12 +51,10 @@ image_corrected += readNoiseImage +#to be updated readnoise.covariance - - - covariance = readnoise.etimate_residual_covariance_from_image(image, matrix_size=5, fprSize=5, parallel_roe, parallel_ccd, parallel_traps) @@ -72,7 +90,7 @@ def __init__( self.sigmaSky = None self.skyFrameSim = None self.readnoiseFrameSim = None - self.optimised_SR_fraction = None + self.SRfrac_optimised = None self.arcKwargs = {} self.covarianceMatrices = {} self.dataFrames = {} @@ -142,10 +160,10 @@ def set_arctic_parameters( self.arcKwargs = kwargs ############### ############### - def estimate_read_noise_model_from_image( + def generate_SR_frames_from_image( self, image, - sr_fraction = 1.0 + sr_fraction = self.SRfrac_optimised ): ''' Function for generating a model of read noise in an image, using the level specified in the @@ -161,13 +179,17 @@ def estimate_read_noise_model_from_image( sr_fraction: float scale fraction specifying what percentage of read noise should be separated into the R - frame. Default is 100%, but this can be changed based on other information (e.g., the - output of + frame. Default is set to the optimised value measured in , or 100% + if has not been previously run. ''' ampReadNoise = self.sigmaRN + #if sr_fraction is unset, default to 100% + if sr_fraction == None: + sr_fraction = 1.0 + imageIn = image imageAdj = np.zeros_like(imageIn) #adjustment image (for read noise modeling) imageOut = imageIn.copy() #output ("smoothed") image @@ -316,10 +338,11 @@ def optimise_SR_fraction( xint = -b/m #this intercept will be the optimised S+R fraction (where mean covariance=0) #store final optimised fraction as a class variable - self.optVals['optSRfrac'] = xint + self.SRfrac_optimised = xint + #self.optVals['optSRfrac'] = xint ############### ############### - def optimise_SR_fraction_from_data( + def optimise_SR_fraction_from_image( self, image, subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) @@ -359,89 +382,20 @@ def optimise_SR_fraction_from_data( self.optimise_SR_fraction(sky_level,sky_back,image_shape,subchip_size,matrix_size,fom_method,**kwargs) ############### ############### - def measure_covariance_quadrants( + def calculate_covariance_corners_from_image( self, - n_pixels=2048, #the size of the entire CCD over which the procedure will be run - subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) - matrix_size=5, #covariance matrix size (NxN array) - fom_method='box', - **kwargs + image, ): - ''' - Apply optimised S+R correction to the four quadrants of the CCD (close to readout, far from parallel register, far from serial register, far from both) - and estimate a covariance matrix for each quadrant. These matrices can be used to correct any residual covariance in weak lensing shapes. - ''' - - #update any keyword arguments - allKwargs = kwargs|self.arcKwargs - - frac_opt = self.optVals['optSRfrac'] #set the optimized S+R fraction - - if type(n_pixels) == int: - n_pixels=(n_pixels,n_pixels) - chip_size = n_pixels - - ##set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) - #if 'parallel_roe' in allKwargs: - # kwargs['parallel_roe'].prescan_offset = n_pixels[0]+(subchip_size//2) - #if 'serial_roe' in allKwargs: - # kwargs['serial_roe'].prescan_offset = n_pixels[1]+(subchip_size//2) - - #re-run the S+R routine with the optimised level - raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) - raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**self.arcKwargs,**kwargs) #this is dumb...do it better - - #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise - kwargs_noCTI = kwargs|self.arcKwargs - kwargs_noCTI['parallel_traps']=None - kwargs_noCTI['serial_traps']=None - #effectively, we are removing the effects of CTI, but still calculating a covariance matrix - raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) - raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_noCTI) - - #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) - #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated - benchmark_matrix = raw_matrix_opt_noCTI*0 - centrePix = matrix_size//2 - benchmark_matrix[centrePix,centrePix] = self.sigmaRN**2 + self.sigmaSky**2 - #calculate the simulation-noise residual - residual_benchmark_matrix = raw_matrix_opt_noCTI - benchmark_matrix - - #Finally, if both parallel and serial CTI are present, calculate covariances of the "cross-region" chip quadrants (far from serial readout but close to parallel readout, and vice-versa) - if ('parallel_traps' in allKwargs)&('serial_traps' in allKwargs): - if (allKwargs['parallel_traps'] is not None)&(allKwargs['serial_traps'] is not None): - kwargs_parallelOnly = kwargs|self.arcKwargs - kwargs_parallelOnly['serial_traps']=None #make a parallel-only quadrant - kwargs_serialOnly = kwargs|self.arcKwargs - kwargs_serialOnly['parallel_traps']=None #make a serial-only quadrant - - raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) - raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_parallelOnly) - raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_serialOnly) - - #package all relevant quantities into optVals and return - self.optVals['combinedQuadMatrix'] = raw_matrix_opt - self.optVals['combinedQuadMatrix_diff'] = correction_matrix_opt - self.optVals['combinedQuadMatrix_noSR'] = raw_matrix_opt_noSR - self.optVals['combinedQuadMatrix_noSR_diff'] = correction_matrix_opt_noSR - self.optVals['parallelQuadMatrix'] = raw_matrix_opt_parallel - self.optVals['parallelQuadMatrix_diff'] = correction_matrix_opt_parallel - self.optVals['parallelQuadMatrix_noSR'] = raw_matrix_opt_parallel_noSR - self.optVals['parallelQuadMatrix_noSR_diff'] = correction_matrix_opt_parallel_noSR - self.optVals['serialQuadMatrix'] = raw_matrix_opt_serial - self.optVals['serialQuadMatrix_diff'] = correction_matrix_opt_serial - self.optVals['serialQuadMatrix_noSR'] = raw_matrix_opt_serial_noSR - self.optVals['serialQuadMatrix_noSR_diff'] = correction_matrix_opt_serial_noSR - self.optVals['noCTIQuadMatrix'] = raw_matrix_opt_noCTI - self.optVals['noCTIQuadMatrix_diff'] = correction_matrix_opt_noCTI - self.optVals['noCTIQuadMatrix_noSR'] = raw_matrix_opt_noCTI - self.optVals['noCTIQuadMatrix_diff_noSR'] = correction_matrix_opt_noCTI - self.optVals['benchmark'] = benchmark_matrix - self.optVals['benchmark_resid'] = residual_benchmark_matrix + return ############### ############### - def plot_matrix(self,covariance_matrix,supressCentralPix=True,title='MyPlotMatrix',**kwargs): + def plot_matrix( + self, + covariance_matrix, + supressCentralPix=True, + title='MyPlotMatrix', + **kwargs + ): if supressCentralPix == True: matrix = covariance_matrix.copy() matrix_size = matrix.shape[0] @@ -455,6 +409,7 @@ def plot_matrix(self,covariance_matrix,supressCentralPix=True,title='MyPlotMatri mpl.pyplot.title(title) mpl.pyplot.show() ############### + ############### # #BACKGROUND FUNCTIONS @@ -588,7 +543,7 @@ def _create_initial_sim_images( These components will create a baseline "clean" image (sky + readnoise) that we would expect to observe in the absence of CTI smearing effects - in each simulated quadrant. Keeping this fixed will control random noise fluctuations + in each simulated corner. Keeping this fixed will control random noise fluctuations ("simulation noise") when estimating covariances throughout the simulation. Note: This routine will be normally be called in @@ -625,7 +580,7 @@ def _estimate_residual_covariance( #add read noise to CTI-trailed image readNoiseAddedFrame = ctiTrailedFrame + noiseFrame #do S+R routine - sFrame, rFrame = self.estimate_read_noise_model_from_image(readNoiseAddedFrame,sr_fraction) + sFrame, rFrame = self.generate_SR_frames_from_image(readNoiseAddedFrame,sr_fraction) ###rescale S+R correction to a fractional value (for optimization) ##sFrame+=rFrame ##rFrame*=sr_fraction @@ -709,3 +664,95 @@ def covariance_matrix_from_image(self, image, matrix_size=5,fprSize=5): return covariance_matrix ############### + + + + + ############### + # + # FUNCTIONS TO BE REFORMATTED / RETHOUGHT? (WORK IN PROGRESS) + # + ############### + def measure_simulated_covariance_corners( + self, + n_pixels=2048, #the size of the entire CCD over which the procedure will be run + subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) + matrix_size=5, #covariance matrix size (NxN array) + fom_method='box', + **kwargs + ): + ''' + Apply optimised S+R correction to the four corners of the CCD (close to readout, far from parallel register, far from serial register, far from both) + and estimate a covariance matrix for each corner. These matrices can be used to correct any residual covariance in weak lensing shapes. + ''' + + #update any keyword arguments + allKwargs = kwargs|self.arcKwargs + + frac_opt = self.SRfrac_optimised #self.optVals['optSRfrac'] #set the optimized S+R fraction + if frac_opt == None: + frac_opt = 1.0 + + if type(n_pixels) == int: + n_pixels=(n_pixels,n_pixels) + chip_size = n_pixels + + ##set prescan regions (this simulates the maximum possible CTI trailing, averaged at the far edge of the real CCD) + #if 'parallel_roe' in allKwargs: + # kwargs['parallel_roe'].prescan_offset = n_pixels[0]+(subchip_size//2) + #if 'serial_roe' in allKwargs: + # kwargs['serial_roe'].prescan_offset = n_pixels[1]+(subchip_size//2) + + #re-run the S+R routine with the optimised level + raw_matrix_opt,correction_matrix_opt = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**self.arcKwargs,**kwargs) + raw_matrix_opt_noSR,correction_matrix_opt_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**self.arcKwargs,**kwargs) #this is dumb...do it better + + #run a second S+R routine in the region close to the readout registers, to identify/remove stochastic simulation noise + kwargs_noCTI = kwargs|self.arcKwargs + kwargs_noCTI['parallel_traps']=None + kwargs_noCTI['serial_traps']=None + #effectively, we are removing the effects of CTI, but still calculating a covariance matrix + raw_matrix_opt_noCTI,correction_matrix_opt_noCTI = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_noCTI) + raw_matrix_opt_noCTI_noSR,correction_matrix_opt_noCTI_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_noCTI) + + #create the "benchmark" covariance matrix: a purely non-correlated array with the central pixel equal to (readnoise_sigma**2 + background_sigma**2) + #Any difference between this and "raw_matrix_opt_noCTI" is the simulation noise, and can be eliminated + benchmark_matrix = raw_matrix_opt_noCTI*0 + centrePix = matrix_size//2 + benchmark_matrix[centrePix,centrePix] = self.sigmaRN**2 + self.sigmaSky**2 + #calculate the simulation-noise residual + residual_benchmark_matrix = raw_matrix_opt_noCTI - benchmark_matrix + + #Finally, if both parallel and serial CTI are present, calculate covariances of the "cross-region" chip corners (far from serial readout but close to parallel readout, and vice-versa) + if ('parallel_traps' in allKwargs)&('serial_traps' in allKwargs): + if (allKwargs['parallel_traps'] is not None)&(allKwargs['serial_traps'] is not None): + kwargs_parallelOnly = kwargs|self.arcKwargs + kwargs_parallelOnly['serial_traps']=None #make a parallel-only corner + kwargs_serialOnly = kwargs|self.arcKwargs + kwargs_serialOnly['parallel_traps']=None #make a serial-only corner + + raw_matrix_opt_parallel,correction_matrix_opt_parallel = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial,correction_matrix_opt_serial = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,frac_opt,matrix_size=matrix_size,**kwargs_serialOnly) + raw_matrix_opt_parallel_noSR,correction_matrix_opt_parallel_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_parallelOnly) + raw_matrix_opt_serial_noSR,correction_matrix_opt_serial_noSR = self._estimate_residual_covariance(self.skyFrameSim,self.readnoiseFrameSim,0,matrix_size=matrix_size,**kwargs_serialOnly) + + #package all relevant quantities into optVals and return + self.optVals['combinedQuadMatrix'] = raw_matrix_opt + self.optVals['combinedQuadMatrix_diff'] = correction_matrix_opt + self.optVals['combinedQuadMatrix_noSR'] = raw_matrix_opt_noSR + self.optVals['combinedQuadMatrix_noSR_diff'] = correction_matrix_opt_noSR + self.optVals['parallelQuadMatrix'] = raw_matrix_opt_parallel + self.optVals['parallelQuadMatrix_diff'] = correction_matrix_opt_parallel + self.optVals['parallelQuadMatrix_noSR'] = raw_matrix_opt_parallel_noSR + self.optVals['parallelQuadMatrix_noSR_diff'] = correction_matrix_opt_parallel_noSR + self.optVals['serialQuadMatrix'] = raw_matrix_opt_serial + self.optVals['serialQuadMatrix_diff'] = correction_matrix_opt_serial + self.optVals['serialQuadMatrix_noSR'] = raw_matrix_opt_serial_noSR + self.optVals['serialQuadMatrix_noSR_diff'] = correction_matrix_opt_serial_noSR + self.optVals['noCTIQuadMatrix'] = raw_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_diff'] = correction_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_noSR'] = raw_matrix_opt_noCTI + self.optVals['noCTIQuadMatrix_diff_noSR'] = correction_matrix_opt_noCTI + self.optVals['benchmark'] = benchmark_matrix + self.optVals['benchmark_resid'] = residual_benchmark_matrix + ############### From 92d8aaf685ca573e59e727a937e8a8ec143cbffa Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Wed, 15 Feb 2023 16:14:21 +0000 Subject: [PATCH 15/25] Update read_noise.py fixed self-referential error --- python/arcticpy/read_noise.py | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index d75499a..1961ec2 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -163,7 +163,7 @@ def set_arctic_parameters( def generate_SR_frames_from_image( self, image, - sr_fraction = self.SRfrac_optimised + sr_fraction = None ): ''' Function for generating a model of read noise in an image, using the level specified in the @@ -186,9 +186,12 @@ def generate_SR_frames_from_image( ''' ampReadNoise = self.sigmaRN - #if sr_fraction is unset, default to 100% + #if sr_fraction is unset, use system value if sr_fraction == None: - sr_fraction = 1.0 + sr_fraction = self.SRfrac_optimised + # if optimisation is not set, default to 100% + if sr_fraction == None: + sr_fraction = 1.0 imageIn = image imageAdj = np.zeros_like(imageIn) #adjustment image (for read noise modeling) From 38d0aa8a41d85b6e5628452169a98e0fc46b29d1 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Wed, 15 Feb 2023 18:51:44 +0000 Subject: [PATCH 16/25] Update read_noise.py more refactoring, additional use-case comments --- python/arcticpy/read_noise.py | 36 ++++++++++++++++++++++++++++++----- 1 file changed, 31 insertions(+), 5 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 1961ec2..368cfe4 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -34,9 +34,18 @@ Do the actual S+R splitting on your science image. If the SR optimisation routine is not run, assume a correction level of 100% -5.) [optional] calculate_covariance_corners_from image(image) +5.) [optional] readnoise.measure_simulated_covariance_corners() + estimate the resulting covariance matrices in each ccd corner, using the optimised simulation -6.) [optional] plot_covariance_matrices() +######POSSIBLE ALTERNATIVE OPTION?##### +5.) [optional] readnoise.calculate_covariance_corners_from image(image) + measure covariance matrices using the real image data + (not yet implemented) +####################################### + +6.) [optional] readnoise.plot_covariance_matrices() + plot the covariance matrices of all four corners + (not fully implemented) ################# @@ -389,7 +398,7 @@ def calculate_covariance_corners_from_image( self, image, ): - return + raise NotImplementedError ############### ############### def plot_matrix( @@ -397,6 +406,7 @@ def plot_matrix( covariance_matrix, supressCentralPix=True, title='MyPlotMatrix', + clearFrame=True, **kwargs ): if supressCentralPix == True: @@ -406,12 +416,28 @@ def plot_matrix( else: matrix = covariance_matrix.copy() - mpl.pyplot.clf() + if clearFrame: + mpl.pyplot.clf() mpl.pyplot.imshow(matrix,cmap='bwr',**kwargs) mpl.pyplot.colorbar() mpl.pyplot.title(title) mpl.pyplot.show() ############### + ############### + def plot_optimised_covariance_matrices( + self + ): + mpl.pyplot.figure() + mpl.pyplot.subplot(221) + self.plot_matrix(self.optVals['noCTIQuadMatrix_diff'],title='Readout Corner',clearFrame=False,vmin=-0.01,vmax=0.01) + mpl.pyplot.subplot(222) + self.plot_matrix(self.optVals['serialQuadMatrix_diff'],title='Serial Corner',clearFrame=False,vmin=-0.01,vmax=0.01) + mpl.pyplot.subplot(223) + self.plot_matrix(self.optVals['parallelQuadMatrix_diff'],title='Parallel Corner',clearFrame=False,vmin=-0.01,vmax=0.01) + mpl.pyplot.subplot(224) + self.plot_matrix(self.optVals['combinedQuadMatrix_diff'],title='Combined Corner',clearFrame=False,vmin=-0.01,vmax=0.01) + ############### + ############### # @@ -678,7 +704,7 @@ def covariance_matrix_from_image(self, image, matrix_size=5,fprSize=5): ############### def measure_simulated_covariance_corners( self, - n_pixels=2048, #the size of the entire CCD over which the procedure will be run + n_pixels=None, #the size of the entire CCD over which the procedure will be run subchip_size=500, #size of the cutout region, to test CTI behaviour (a subset of pixels far form the readout) matrix_size=5, #covariance matrix size (NxN array) fom_method='box', From d867f99e69bd25e3ce582bfdf1a31691d8d53064 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 6 Mar 2023 12:14:25 +0200 Subject: [PATCH 17/25] updated read_noise.py and test_arcticpy.py cleaned read_noise.py, and added a first unit test for the read_noise class --- python/arcticpy/read_noise.py | 15 +++++++++++---- test/test_arcticpy.py | 28 ++++++++++++++++++++++++++++ 2 files changed, 39 insertions(+), 4 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 368cfe4..807ec83 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -1,5 +1,12 @@ import numpy as np -import arcticpy as ac +#import arcticpy as ac + +try: + from arcticpy import wrapper as w +except ImportError: + import wrapper as w + +from arcticpy.cti import add_cti,remove_cti import matplotlib as mpl from scipy.optimize import curve_fit @@ -177,7 +184,7 @@ def generate_SR_frames_from_image( ''' Function for generating a model of read noise in an image, using the level specified in the initial ReadNoise call. Once modeled, the read noise component is separated from the data, - leaving a smooth "S" component and a read-noise-only "R" component. The S somponent can then + leaving a smooth "S" component and a read-noise-only "R" component. The S component can then be CTI-corrected and recombined with the R model to minimise residual covariance in the image. Parameters @@ -605,7 +612,7 @@ def _estimate_residual_covariance( Estimate a covariance matrix for an optimising simulation, assuming the sky/noise frames have already been created ''' #add CTI effects to skyFrame - ctiTrailedFrame = ac.add_cti(skyFrame,**kwargs) + ctiTrailedFrame = add_cti(skyFrame,**kwargs) #add read noise to CTI-trailed image readNoiseAddedFrame = ctiTrailedFrame + noiseFrame #do S+R routine @@ -615,7 +622,7 @@ def _estimate_residual_covariance( ##rFrame*=sr_fraction ##sFrame-=rFrame #clean CTI from S frame - ctiCorrectedFrame = ac.remove_cti(sFrame,1,**kwargs) + ctiCorrectedFrame = remove_cti(sFrame,1,**kwargs) #re-add R frame to correction outputFrame = ctiCorrectedFrame + rFrame diff --git a/test/test_arcticpy.py b/test/test_arcticpy.py index bd817d0..43a7e5c 100644 --- a/test/test_arcticpy.py +++ b/test/test_arcticpy.py @@ -1091,3 +1091,31 @@ def print_help(): print_help() except IndexError: print_help() + +class testReadNoise: + + def test_noiseEstimation(): + #make simple "sky" and "noise" frames and combine them + sky = array([[104.62689576, 96.26344068, 102.05736548, 76.16124587, 107.55689551], + [ 96.87789779, 87.37248667, 110.70696472, 112.3185982 , 84.7109744 ], + [104.06312714, 99.2960313 , 105.16551541, 97.52700805, 104.66187477], + [100.90670311, 108.95078214, 100.96009345, 100.06043671, 92.82319682], + [ 87.42418643, 109.87867837, 108.59791761, 102.64102994, 77.73118275]]) + noise = np. array([[ 8.21416447, -4.40936237, -1.18755795, 0.06791093, -2.33996983], + [ 4.93207717, 6.17463103, -3.60709428, 7.50694942, -2.27221275], + [ 0.63142708, 4.19195127, 4.99175746, 6.83683726, -6.91249208], + [-1.50630185, 1.91698306, 6.03575168, 11.84120206, 1.78779769], + [ 0.21060601, 4.81669569, 2.89002324, -2.14453015, -1.87141227]]) + combo = sky+noise + + #create a read_noise object with sigma_noise == 4.5 electrons (matches input noise model) + testRN = cti.read_noise.ReadNoise(4.5) + + #separate combination into S ("smooth") + R ("readnoise") components + S,R = testRN.generate_SR_frames_from_image(combo) + + #check that S+R components are close to input images (within typical simulation noise limits) + assert abs(np.mean(R) - np.mean(noise)) < 2 + assert abs(np.std(R) - np.std(noise)) <= 0.0001 + assert abs(np.mean(S) - np.mean(sky)) < 2 + assert abs(np.std(S) - np.std(sky)) < 1 From dc67000112417903c65eadb6e9b7429bd7c1bdc2 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 6 Mar 2023 12:32:58 +0200 Subject: [PATCH 18/25] Update test_arcticpy.py fixed small syntax errors --- test/test_arcticpy.py | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/test/test_arcticpy.py b/test/test_arcticpy.py index 43a7e5c..47fe931 100644 --- a/test/test_arcticpy.py +++ b/test/test_arcticpy.py @@ -1092,20 +1092,20 @@ def print_help(): except IndexError: print_help() -class testReadNoise: +class TestReadNoise: def test_noiseEstimation(): #make simple "sky" and "noise" frames and combine them - sky = array([[104.62689576, 96.26344068, 102.05736548, 76.16124587, 107.55689551], + sky = np.array([[104.62689576, 96.26344068, 102.05736548, 76.16124587, 107.55689551], [ 96.87789779, 87.37248667, 110.70696472, 112.3185982 , 84.7109744 ], [104.06312714, 99.2960313 , 105.16551541, 97.52700805, 104.66187477], [100.90670311, 108.95078214, 100.96009345, 100.06043671, 92.82319682], [ 87.42418643, 109.87867837, 108.59791761, 102.64102994, 77.73118275]]) - noise = np. array([[ 8.21416447, -4.40936237, -1.18755795, 0.06791093, -2.33996983], - [ 4.93207717, 6.17463103, -3.60709428, 7.50694942, -2.27221275], - [ 0.63142708, 4.19195127, 4.99175746, 6.83683726, -6.91249208], - [-1.50630185, 1.91698306, 6.03575168, 11.84120206, 1.78779769], - [ 0.21060601, 4.81669569, 2.89002324, -2.14453015, -1.87141227]]) + noise = np.array([[ 8.21416447, -4.40936237, -1.18755795, 0.06791093, -2.33996983], + [ 4.93207717, 6.17463103, -3.60709428, 7.50694942, -2.27221275], + [ 0.63142708, 4.19195127, 4.99175746, 6.83683726, -6.91249208], + [-1.50630185, 1.91698306, 6.03575168, 11.84120206, 1.78779769], + [ 0.21060601, 4.81669569, 2.89002324, -2.14453015, -1.87141227]]) combo = sky+noise #create a read_noise object with sigma_noise == 4.5 electrons (matches input noise model) From 2948baeb52dc373e9f2ce2e2a86f401dbee91e53 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Mon, 6 Mar 2023 12:38:55 +0200 Subject: [PATCH 19/25] Update test_arcticpy.py changed sensitivity limts --- test/test_arcticpy.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/test/test_arcticpy.py b/test/test_arcticpy.py index 47fe931..aee21d5 100644 --- a/test/test_arcticpy.py +++ b/test/test_arcticpy.py @@ -1116,6 +1116,6 @@ def test_noiseEstimation(): #check that S+R components are close to input images (within typical simulation noise limits) assert abs(np.mean(R) - np.mean(noise)) < 2 - assert abs(np.std(R) - np.std(noise)) <= 0.0001 + assert abs(np.std(R) - np.std(noise)) <= 0.001 assert abs(np.mean(S) - np.mean(sky)) < 2 assert abs(np.std(S) - np.std(sky)) < 1 From 588c0baa013660e6fad4f7fee76ada869c0289b3 Mon Sep 17 00:00:00 2001 From: dlagattuta Date: Tue, 7 Mar 2023 00:14:03 +0200 Subject: [PATCH 20/25] Update read_noise.py added improved documentation to the S+R generator function _determine_noise_model --- python/arcticpy/read_noise.py | 148 +++++++++++++++++----------------- 1 file changed, 76 insertions(+), 72 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 807ec83..a934237 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -456,114 +456,118 @@ def _determine_noise_model(self, imageIn, imageOut): Method for estimating readnoise on image (in S+R fashion) assumes parallel+serial CTI trailing by default ''' + #set target read noise amplitude to be equal to the value specified in the input function readNoiseAmp = self.sigmaRN + + ''' + Define up the "comparison" variables for each S+R realisation. In every run, the current value of each pixel in the array is compared + to its neighbours; these comparisons will determine how much the pixel value will change in the next interation of the loop. There are + six such comparisons, some of which want the pixel to keep its current value, and others that want it to change. The result is a tug-of-war + between different modifiers, preventing the pixel value from varying by too much too quickly. + + The comparisons are: + dval0 -- compare the pixel to itself. This comparison tries to keep the pixel value unchanged + + dval9 -- compare the pixel to its "local" average (the block of pixels surrounding it). In most + cases this is a (3x3) block, but pixels at the edge of the array are appropriately truncated. + Once again, this comparison tries to keep the pixel value unchanged. + + dmod1 and dmod2 -- compare pixel to its upper (dmod1) and lower (dmod2) row reighbours. + These comparisons try to bring the pixel closer to the average of its neighbours + + cmod1 and cmod2 -- compare pixel to its right (cmod1) and left (cmod2) column reighbours. + These comparisons try to bring the pixel closer to the average of its neighbours + + Finally, each comparison has a "clipped" version (e.g., dval0u) which truncates the comparison difference + to be within some upper/lower limits. These clipped values will determine the actual pixel modification. + + Note: all of these comparisons *should* be done with python broadcasting tricks...but I'm not sure this is actually the case + ''' + #initialize dval0 comparison dval0 = imageIn - imageOut dval0u = dval0.copy() - + + #set the clipped dval0 comparison + #note, this clipping is more stringent than the others dval0u[dval0u>1] = 1 dval0u[dval0u<-1] = -1 - + + #initialize dval9 value and count (average will be (summed value)/(summed count)) dval9 = imageIn*0 dcount = imageIn*0 - - dval9[:-1,:-1]+=(imageIn[1: ,1: ]-imageOut[1: ,1: ]); dcount[:-1,:-1]+=1 - dval9[:-1,: ]+=(imageIn[1: ,: ]-imageOut[1: ,: ]); dcount[:-1,: ]+=1 - dval9[:-1,1: ]+=(imageIn[1: ,:-1]-imageOut[1: ,:-1]); dcount[:-1,1: ]+=1 - dval9[: ,:-1]+=(imageIn[: ,1: ]-imageOut[: ,1: ]); dcount[: ,:-1]+=1 - dval9[: ,: ]+=(imageIn[: ,: ]-imageOut[: ,: ]); dcount[: ,: ]+=1 - dval9[: ,1: ]+=(imageIn[: ,:-1]-imageOut[: ,:-1]); dcount[: ,1: ]+=1 - dval9[1: ,:-1]+=(imageIn[:-1,1: ]-imageOut[:-1,1: ]); dcount[1: ,:-1]+=1 - dval9[1: ,: ]+=(imageIn[:-1,: ]-imageOut[:-1,: ]); dcount[1: ,: ]+=1 - dval9[1: ,1: ]+=(imageIn[:-1,:-1]-imageOut[:-1,:-1]); dcount[1: ,1: ]+=1 - + + #do the dval9 calculation + dval9[:-1,:-1]+=(imageIn[1: ,1: ]-imageOut[1: ,1: ]); dcount[:-1,:-1]+=1 #comparison with bottom-left neighbour + dval9[:-1,: ]+=(imageIn[1: ,: ]-imageOut[1: ,: ]); dcount[:-1,: ]+=1 #comparison with bottom-central neighbour + dval9[:-1,1: ]+=(imageIn[1: ,:-1]-imageOut[1: ,:-1]); dcount[:-1,1: ]+=1 #comparison with bottom-right neighbour + dval9[: ,:-1]+=(imageIn[: ,1: ]-imageOut[: ,1: ]); dcount[: ,:-1]+=1 #comparison with middle-left neighbour + dval9[: ,: ]+=(imageIn[: ,: ]-imageOut[: ,: ]); dcount[: ,: ]+=1 #comparison with itself (middle-centre) + dval9[: ,1: ]+=(imageIn[: ,:-1]-imageOut[: ,:-1]); dcount[: ,1: ]+=1 #comparison with middle-right neighbour + dval9[1: ,:-1]+=(imageIn[:-1,1: ]-imageOut[:-1,1: ]); dcount[1: ,:-1]+=1 #comparison with top-left neighbour + dval9[1: ,: ]+=(imageIn[:-1,: ]-imageOut[:-1,: ]); dcount[1: ,: ]+=1 #comparison with top-central neighbour + dval9[1: ,1: ]+=(imageIn[:-1,:-1]-imageOut[:-1,:-1]); dcount[1: ,1: ]+=1 #comparison with top-right neighbour + + #get the dval9 average dval9/=dcount - + + #set the clipping modifier + #limit any difference to be at most the 1-sigma readnoise value (readNoiseAmp) scaled by a preset modifier (readNoiseAmpFraction) -- currently hard-coded to 0.2 readNoiseAmpFraction = self.ampScale + mod_clip = readNoiseAmp*readNoiseAmpFraction + + #set the clipped dval9 comparison dval9u = dval9.copy() - if type(readNoiseAmp)==np.ndarray: - dval9u = dval9u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dval9u > readNoiseAmp*readNoiseAmpFraction] - dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = (readNoiseAmp*-readNoiseAmpFraction)[dval9u < readNoiseAmp*-readNoiseAmpFraction] - dval9u = dval9u.reshape(imageIn.shape) - readNoiseAmp = readNoiseAmp.reshape(imageIn.shape) - else: - dval9u[dval9u > readNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dval9u[dval9u < readNoiseAmp*-readNoiseAmpFraction] = readNoiseAmp*-readNoiseAmpFraction - + dval9u[dval9u > mod_clip] = mod_clip + dval9u[dval9u < -mod_clip] = -mod_clip + + #initialise and set the dmod comparisons dmod1 = imageIn*0 dmod1[1:,:] = imageOut[:-1,:] - imageOut[1:,:] dmod2 = imageIn*0 dmod2[:-1,:] = imageOut[1:,:] - imageOut[:-1,:] - + + #if specified, also initialise and set the cmod comparions if self.smoothCol: cmod1 = imageIn*0 cmod1[:,1:] = imageOut[:,:-1] - imageOut[:,1:] cmod2 = imageIn*0 cmod2[:,:-1] = imageOut[:,1:] - imageOut[:,:-1] - + + #set the clipped dmod values dmod1u = dmod1.copy() - if type(readNoiseAmp)==np.ndarray: - dmod1u = dmod1u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - dmod1u[dmod1u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod1u>readNoiseAmp*readNoiseAmpFraction] - dmod1u[dmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dmod1u[dmod1umod_clip] = mod_clip + dmod1u[dmod1u<-mod_clip] = -mod_clip dmod2u = dmod2.copy() - if type(readNoiseAmp)==np.ndarray: - dmod2u = dmod2u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - dmod2u[dmod2u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[dmod2u>readNoiseAmp*readNoiseAmpFraction] - dmod2u[dmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - dmod2u[dmod2umod_clip] = mod_clip + dmod2u[dmod2u<-mod_clip] = -mod_clip + #if specified, also set the clipped cmod values if self.smoothCol: cmod1u = cmod1.copy() - if type(readNoiseAmp)==np.ndarray: - cmod1u = cmod1u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - cmod1u[cmod1u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod1u>readNoiseAmp*readNoiseAmpFraction] - cmod1u[cmod1ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - cmod1u[cmod1umod_clip] = mod_clip + cmod1u[cmod1u<-mod_clip] = -mod_clip cmod2u = cmod2.copy() - if type(readNoiseAmp)==np.ndarray: - cmod2u = cmod2u.flatten() - readNoiseAmp = readNoiseAmp.flatten() - cmod2u[cmod2u>readNoiseAmp*readNoiseAmpFraction] = (readNoiseAmp*readNoiseAmpFraction)[cmod2u>readNoiseAmp*readNoiseAmpFraction] - cmod2u[cmod2ureadNoiseAmp*readNoiseAmpFraction] = readNoiseAmp*readNoiseAmpFraction - cmod2u[cmod2umod_clip] = mod_clip + cmod2u[cmod2u<-mod_clip] = -mod_clip + + #calulate weight parameters for each comparison (these were taken from the STScI code) readNoiseAmp2 = readNoiseAmp**2 w0 = dval0 * dval0 / (dval0 * dval0 + 4.0 * readNoiseAmp2) w9 = dval9 * dval9 / (dval9 * dval9 + 18.0 * readNoiseAmp2) - w1 = 4 * readNoiseAmp2 / (dmod1 * dmod1 + 4.0 * readNoiseAmp2) - w2 = 4 * readNoiseAmp2 / (dmod2 * dmod2 + 4.0 * readNoiseAmp2) + wr1 = 4 * readNoiseAmp2 / (dmod1 * dmod1 + 4.0 * readNoiseAmp2) + wr2 = 4 * readNoiseAmp2 / (dmod2 * dmod2 + 4.0 * readNoiseAmp2) if self.smoothCol: wc1 = 4 * readNoiseAmp2 / (cmod1 * cmod1 + 4.0 * readNoiseAmp2) wc2 = 4 * readNoiseAmp2 / (cmod2 * cmod2 + 4.0 * readNoiseAmp2) - + + #return the appropriately-modified array (which can be sent to the next S+R iteration) if self.smoothCol: - return (dval0u * w0 / 6) + (dval9u * w9 / 6) +(dmod1u * w1 / 6) + (dmod2u * w2 / 6) +(cmod1u * wc1 / 6) + (cmod2u * wc2 / 6) + return (dval0u*w0 + dval9u*w9 + dmod1u*wr1 + dmod2u*wr2 + cmod1u*wc1 + cmod2u*wc2) / 6 else: - return (dval0u * w0 * 0.25) + (dval9u * w9 * 0.25) +(dmod1u * w1 * 0.25) + (dmod2u * w2 * 0.25) + return (dval0u*w0 + dval9u*w9 + dmod1u*wr1 + dmod2u*wr2) / 4 ############### ############### From a410659595da78ac49022450d18be844e6f9b5b7 Mon Sep 17 00:00:00 2001 From: Jascha S Date: Thu, 9 Mar 2023 18:47:13 +0000 Subject: [PATCH 21/25] speed ups for noise treatment --- python/arcticpy/read_noise.py | 87 +++++++++++++++++------------------ setup.py | 2 + 2 files changed, 43 insertions(+), 46 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index a934237..10b6a86 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -486,88 +486,83 @@ def _determine_noise_model(self, imageIn, imageOut): ''' #initialize dval0 comparison dval0 = imageIn - imageOut - dval0u = dval0.copy() #set the clipped dval0 comparison #note, this clipping is more stringent than the others - dval0u[dval0u>1] = 1 - dval0u[dval0u<-1] = -1 + dval0u = np.clip(dval0, -1, 1) #initialize dval9 value and count (average will be (summed value)/(summed count)) - dval9 = imageIn*0 - dcount = imageIn*0 - + dval9 = np.zeros(imageIn.shape) + #do the dval9 calculation - dval9[:-1,:-1]+=(imageIn[1: ,1: ]-imageOut[1: ,1: ]); dcount[:-1,:-1]+=1 #comparison with bottom-left neighbour - dval9[:-1,: ]+=(imageIn[1: ,: ]-imageOut[1: ,: ]); dcount[:-1,: ]+=1 #comparison with bottom-central neighbour - dval9[:-1,1: ]+=(imageIn[1: ,:-1]-imageOut[1: ,:-1]); dcount[:-1,1: ]+=1 #comparison with bottom-right neighbour - dval9[: ,:-1]+=(imageIn[: ,1: ]-imageOut[: ,1: ]); dcount[: ,:-1]+=1 #comparison with middle-left neighbour - dval9[: ,: ]+=(imageIn[: ,: ]-imageOut[: ,: ]); dcount[: ,: ]+=1 #comparison with itself (middle-centre) - dval9[: ,1: ]+=(imageIn[: ,:-1]-imageOut[: ,:-1]); dcount[: ,1: ]+=1 #comparison with middle-right neighbour - dval9[1: ,:-1]+=(imageIn[:-1,1: ]-imageOut[:-1,1: ]); dcount[1: ,:-1]+=1 #comparison with top-left neighbour - dval9[1: ,: ]+=(imageIn[:-1,: ]-imageOut[:-1,: ]); dcount[1: ,: ]+=1 #comparison with top-central neighbour - dval9[1: ,1: ]+=(imageIn[:-1,:-1]-imageOut[:-1,:-1]); dcount[1: ,1: ]+=1 #comparison with top-right neighbour + dval9[:-1,:-1]+=(dval0[1: ,1: ]) # comparison with bottom-left neighbour + dval9[:-1,: ]+=(dval0[1: ,: ]) # comparison with bottom-central neighbour + dval9[:-1,1: ]+=(dval0[1: ,:-1]) # comparison with bottom-right neighbour + dval9[: ,:-1]+=(dval0[: ,1: ]) # comparison with middle-left neighbour + dval9[: ,: ]+=(dval0[: ,: ]) # ... + dval9[: ,1: ]+=(dval0[: ,:-1]) + dval9[1: ,:-1]+=(dval0[:-1,1: ]) + dval9[1: ,: ]+=(dval0[:-1,: ]) + dval9[1: ,1: ]+=(dval0[:-1,:-1]) #get the dval9 average - dval9/=dcount + dval9[1:-1,1:-1] /= 9 + # edges (excl. corners) + dval9[1:-1,0] /= 6 + dval9[1:-1,-1] /= 6 + dval9[0,1:-1] /= 6 + dval9[-1,1:-1] /= 6 + # corners + dval9[0, 0] /= 4 + dval9[-1, 0] /= 4 + dval9[0, -1] /= 4 + dval9[-1, -1] /= 4 #set the clipping modifier #limit any difference to be at most the 1-sigma readnoise value (readNoiseAmp) scaled by a preset modifier (readNoiseAmpFraction) -- currently hard-coded to 0.2 readNoiseAmpFraction = self.ampScale - mod_clip = readNoiseAmp*readNoiseAmpFraction + mod_clip = readNoiseAmp * readNoiseAmpFraction #set the clipped dval9 comparison - dval9u = dval9.copy() - dval9u[dval9u > mod_clip] = mod_clip - dval9u[dval9u < -mod_clip] = -mod_clip + dval9u = np.clip(dval9, -mod_clip, mod_clip) #initialise and set the dmod comparisons - dmod1 = imageIn*0 + dmod1 = np.zeros(imageIn.shape) dmod1[1:,:] = imageOut[:-1,:] - imageOut[1:,:] - dmod2 = imageIn*0 + dmod2 = np.zeros(imageIn.shape) dmod2[:-1,:] = imageOut[1:,:] - imageOut[:-1,:] #if specified, also initialise and set the cmod comparions if self.smoothCol: - cmod1 = imageIn*0 + cmod1 = np.zeros(imageIn.shape) cmod1[:,1:] = imageOut[:,:-1] - imageOut[:,1:] - cmod2 = imageIn*0 + cmod2 = np.zeros(imageIn.shape) cmod2[:,:-1] = imageOut[:,1:] - imageOut[:,:-1] #set the clipped dmod values - dmod1u = dmod1.copy() - dmod1u[dmod1u>mod_clip] = mod_clip - dmod1u[dmod1u<-mod_clip] = -mod_clip - - dmod2u = dmod2.copy() - dmod2u[dmod2u>mod_clip] = mod_clip - dmod2u[dmod2u<-mod_clip] = -mod_clip + dmod1u = np.clip(dmod1, -mod_clip, mod_clip) + dmod2u = np.clip(dmod2, -mod_clip, mod_clip) #if specified, also set the clipped cmod values if self.smoothCol: - cmod1u = cmod1.copy() - cmod1u[cmod1u>mod_clip] = mod_clip - cmod1u[cmod1u<-mod_clip] = -mod_clip - - cmod2u = cmod2.copy() - cmod2u[cmod2u>mod_clip] = mod_clip - cmod2u[cmod2u<-mod_clip] = -mod_clip + cmod1u = np.clip(cmod1, -mod_clip, mod_clip) + cmod2u = np.clip(cmod2, -mod_clip, mod_clip) #calulate weight parameters for each comparison (these were taken from the STScI code) readNoiseAmp2 = readNoiseAmp**2 - w0 = dval0 * dval0 / (dval0 * dval0 + 4.0 * readNoiseAmp2) - w9 = dval9 * dval9 / (dval9 * dval9 + 18.0 * readNoiseAmp2) - wr1 = 4 * readNoiseAmp2 / (dmod1 * dmod1 + 4.0 * readNoiseAmp2) - wr2 = 4 * readNoiseAmp2 / (dmod2 * dmod2 + 4.0 * readNoiseAmp2) + dval0u *= np.square(dval0) / (np.square(dval0) + 4.0 * readNoiseAmp2) + dval9u *= np.square(dval9) / (np.square(dval9) + 18.0 * readNoiseAmp2) + dmod1u *= 4 * readNoiseAmp2 / (np.square(dmod1) + 4.0 * readNoiseAmp2) + dmod2u *= 4 * readNoiseAmp2 / (np.square(dmod2) + 4.0 * readNoiseAmp2) if self.smoothCol: - wc1 = 4 * readNoiseAmp2 / (cmod1 * cmod1 + 4.0 * readNoiseAmp2) - wc2 = 4 * readNoiseAmp2 / (cmod2 * cmod2 + 4.0 * readNoiseAmp2) + cmod1u = 4 * readNoiseAmp2 / (np.square(cmod1) + 4.0 * readNoiseAmp2) + cmod2u = 4 * readNoiseAmp2 / (np.square(cmod2) + 4.0 * readNoiseAmp2) #return the appropriately-modified array (which can be sent to the next S+R iteration) if self.smoothCol: - return (dval0u*w0 + dval9u*w9 + dmod1u*wr1 + dmod2u*wr2 + cmod1u*wc1 + cmod2u*wc2) / 6 + return (dval0u + dval9u + dmod1u + dmod2u + cmod1u + cmod2u) / 6 else: - return (dval0u*w0 + dval9u*w9 + dmod1u*wr1 + dmod2u*wr2) / 4 + return (dval0u + dval9u + dmod1u + dmod2u) / 4 ############### ############### diff --git a/setup.py b/setup.py index bbbdf5c..40fd359 100644 --- a/setup.py +++ b/setup.py @@ -56,5 +56,7 @@ extensions, compiler_directives={"language_level": "3"} ), + packages=['arcticpy'], + package_dir={'arcticpy': dir_wrapper}, headers=ext_headers, # currently ignored (?) ) From bea2521135d94a2c053fb64d322fbf75b731ebcf Mon Sep 17 00:00:00 2001 From: Jascha S Date: Thu, 9 Mar 2023 19:44:27 +0000 Subject: [PATCH 22/25] some type hints; further fixes --- python/arcticpy/read_noise.py | 54 +++++++++++++++++------------------ 1 file changed, 27 insertions(+), 27 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 10b6a86..6d0a630 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -8,6 +8,7 @@ from arcticpy.cti import add_cti,remove_cti import matplotlib as mpl +import numpy as np from scipy.optimize import curve_fit """ @@ -451,7 +452,7 @@ def plot_optimised_covariance_matrices( #BACKGROUND FUNCTIONS # ############### - def _determine_noise_model(self, imageIn, imageOut): + def _determine_noise_model(self, imageIn: np.ndarray, imageOut: np.ndarray): ''' Method for estimating readnoise on image (in S+R fashion) assumes parallel+serial CTI trailing by default @@ -484,28 +485,27 @@ def _determine_noise_model(self, imageIn, imageOut): Note: all of these comparisons *should* be done with python broadcasting tricks...but I'm not sure this is actually the case ''' - #initialize dval0 comparison + # initialize dval0 comparison dval0 = imageIn - imageOut - #set the clipped dval0 comparison - #note, this clipping is more stringent than the others + # set the clipped dval0 comparison + # note, this clipping is more stringent than the others dval0u = np.clip(dval0, -1, 1) - #initialize dval9 value and count (average will be (summed value)/(summed count)) - dval9 = np.zeros(imageIn.shape) + # initialize dval9 value and count (average will be (summed value)/(summed count)) + dval9 = dval0.copy() - #do the dval9 calculation - dval9[:-1,:-1]+=(dval0[1: ,1: ]) # comparison with bottom-left neighbour - dval9[:-1,: ]+=(dval0[1: ,: ]) # comparison with bottom-central neighbour - dval9[:-1,1: ]+=(dval0[1: ,:-1]) # comparison with bottom-right neighbour - dval9[: ,:-1]+=(dval0[: ,1: ]) # comparison with middle-left neighbour - dval9[: ,: ]+=(dval0[: ,: ]) # ... - dval9[: ,1: ]+=(dval0[: ,:-1]) - dval9[1: ,:-1]+=(dval0[:-1,1: ]) - dval9[1: ,: ]+=(dval0[:-1,: ]) - dval9[1: ,1: ]+=(dval0[:-1,:-1]) - - #get the dval9 average + # do the dval9 calculation + dval9[:-1, :-1] += dval0[1:, 1:] # comparison with bottom-left neighbour + dval9[:-1, :] += dval0[1: ,:] # comparison with bottom-central neighbour + dval9[:-1, 1:] += dval0[1:, :-1] # comparison with bottom-right neighbour + dval9[:, :-1] += dval0[:, 1:] # comparison with middle-left neighbour + dval9[:, 1:] += dval0[:, :-1] + dval9[1:, :-1] += dval0[:-1, 1:] + dval9[1:, :] += dval0[:-1, :] + dval9[1:, 1:] += dval0[:-1, :-1] + + # get the dval9 average dval9[1:-1,1:-1] /= 9 # edges (excl. corners) dval9[1:-1,0] /= 6 @@ -518,37 +518,37 @@ def _determine_noise_model(self, imageIn, imageOut): dval9[0, -1] /= 4 dval9[-1, -1] /= 4 - #set the clipping modifier - #limit any difference to be at most the 1-sigma readnoise value (readNoiseAmp) scaled by a preset modifier (readNoiseAmpFraction) -- currently hard-coded to 0.2 + # set the clipping modifier + # limit any difference to be at most the 1-sigma readnoise value (readNoiseAmp) scaled by a preset modifier (readNoiseAmpFraction) -- currently hard-coded to 0.2 readNoiseAmpFraction = self.ampScale mod_clip = readNoiseAmp * readNoiseAmpFraction - #set the clipped dval9 comparison + # set the clipped dval9 comparison dval9u = np.clip(dval9, -mod_clip, mod_clip) - #initialise and set the dmod comparisons + # initialise and set the dmod comparisons dmod1 = np.zeros(imageIn.shape) dmod1[1:,:] = imageOut[:-1,:] - imageOut[1:,:] dmod2 = np.zeros(imageIn.shape) dmod2[:-1,:] = imageOut[1:,:] - imageOut[:-1,:] - #if specified, also initialise and set the cmod comparions + # if specified, also initialise and set the cmod comparions if self.smoothCol: cmod1 = np.zeros(imageIn.shape) cmod1[:,1:] = imageOut[:,:-1] - imageOut[:,1:] cmod2 = np.zeros(imageIn.shape) cmod2[:,:-1] = imageOut[:,1:] - imageOut[:,:-1] - #set the clipped dmod values + # set the clipped dmod values dmod1u = np.clip(dmod1, -mod_clip, mod_clip) dmod2u = np.clip(dmod2, -mod_clip, mod_clip) - #if specified, also set the clipped cmod values + # if specified, also set the clipped cmod values if self.smoothCol: cmod1u = np.clip(cmod1, -mod_clip, mod_clip) cmod2u = np.clip(cmod2, -mod_clip, mod_clip) - #calulate weight parameters for each comparison (these were taken from the STScI code) + # calulate weight parameters for each comparison (these were taken from the STScI code) readNoiseAmp2 = readNoiseAmp**2 dval0u *= np.square(dval0) / (np.square(dval0) + 4.0 * readNoiseAmp2) dval9u *= np.square(dval9) / (np.square(dval9) + 18.0 * readNoiseAmp2) @@ -558,7 +558,7 @@ def _determine_noise_model(self, imageIn, imageOut): cmod1u = 4 * readNoiseAmp2 / (np.square(cmod1) + 4.0 * readNoiseAmp2) cmod2u = 4 * readNoiseAmp2 / (np.square(cmod2) + 4.0 * readNoiseAmp2) - #return the appropriately-modified array (which can be sent to the next S+R iteration) + # return the appropriately-modified array (which can be sent to the next S+R iteration) if self.smoothCol: return (dval0u + dval9u + dmod1u + dmod2u + cmod1u + cmod2u) / 6 else: From f1aa23be3e7de512121dd286798738e73bf832ff Mon Sep 17 00:00:00 2001 From: Jascha S Date: Fri, 10 Mar 2023 14:52:37 +0000 Subject: [PATCH 23/25] fixed typo --- python/arcticpy/read_noise.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 6d0a630..5c8f38c 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -555,8 +555,8 @@ def _determine_noise_model(self, imageIn: np.ndarray, imageOut: np.ndarray): dmod1u *= 4 * readNoiseAmp2 / (np.square(dmod1) + 4.0 * readNoiseAmp2) dmod2u *= 4 * readNoiseAmp2 / (np.square(dmod2) + 4.0 * readNoiseAmp2) if self.smoothCol: - cmod1u = 4 * readNoiseAmp2 / (np.square(cmod1) + 4.0 * readNoiseAmp2) - cmod2u = 4 * readNoiseAmp2 / (np.square(cmod2) + 4.0 * readNoiseAmp2) + cmod1u *= 4 * readNoiseAmp2 / (np.square(cmod1) + 4.0 * readNoiseAmp2) + cmod2u *= 4 * readNoiseAmp2 / (np.square(cmod2) + 4.0 * readNoiseAmp2) # return the appropriately-modified array (which can be sent to the next S+R iteration) if self.smoothCol: From f41fabf22c1cb298e2b72c38655986fe380ed96e Mon Sep 17 00:00:00 2001 From: Jascha S Date: Fri, 10 Mar 2023 20:22:32 +0000 Subject: [PATCH 24/25] added new c implementation; updated setup.py --- python/arcticpy/read_noise.c | 149 +++++++++++++++++++++++++ python/arcticpy/read_noise.py | 9 +- python/arcticpy/read_noise_wrapper.pyx | 12 ++ setup.py | 10 +- 4 files changed, 177 insertions(+), 3 deletions(-) create mode 100644 python/arcticpy/read_noise.c create mode 100644 python/arcticpy/read_noise_wrapper.pyx diff --git a/python/arcticpy/read_noise.c b/python/arcticpy/read_noise.c new file mode 100644 index 0000000..eb0d5e4 --- /dev/null +++ b/python/arcticpy/read_noise.c @@ -0,0 +1,149 @@ +#include +#include +#include + +#define SQUARE(x) ((x) * (x)) + +void determine_noise_model(const double* imageIn, const double* imageOut, const int rows, const int cols, const double readNoiseAmp, const double readNoiseAmpFraction, const int smoothCol, double* output) { + + double* dval0 = output; // using already allocated output buffer to temporarily store the results to avoid allocating more memory (safe as long as we do not modify output before storing dval0 there and not use dval0 after modifying output for the first time) + double* dval9 = (double*)malloc(rows * cols * sizeof(double)); + + double mod_clip = readNoiseAmp * readNoiseAmpFraction; + double readNoiseAmp2 = SQUARE(readNoiseAmp); + + int idx; + + for (int i = 0; i < rows * cols; i++) { + dval0[i] = imageIn[i] - imageOut[i]; + dval9[i] = dval0[i]; + } + + // get the dval9 average + // inner part + for (int i = 1; i < rows - 1; i++) { +#pragma omp parallel for private(idx) + for (int j = 1; j < cols - 1; j++) { + idx = i * cols + j; + dval9[idx] += dval0[idx + cols + 1]; // comparison with bottom-left neighbour + dval9[idx] += dval0[idx + cols]; // comparison with bottom-central neighbour + dval9[idx] += dval0[idx + cols - 1]; // comparison with bottom-right neighbour + dval9[idx] += dval0[idx + 1]; // comparison with middle-left neighbour + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] += dval0[idx - cols + 1]; // comparison with top-left neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] += dval0[idx - cols - 1]; // comparison with top-right neighbour + dval9[idx] /= 9; + } + } + // edges (excl. corners) +#pragma omp parallel for private(idx) + for (int i = 1; i < rows - 1; i++) { + // left edge (j=0) + idx = i * cols; + dval9[idx] += dval0[idx + cols + 1]; // comparison with bottom-left neighbour + dval9[idx] += dval0[idx + cols]; // comparison with bottom-central neighbour + dval9[idx] += dval0[idx + 1]; // comparison with middle-left neighbour + dval9[idx] += dval0[idx - cols + 1]; // comparison with top-left neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] /= 6.0; + // right edge (j=cols-1) + idx = (i + 1) * cols - 1; + dval9[idx] += dval0[idx + cols]; // comparison with bottom-central neighbour + dval9[idx] += dval0[idx + cols - 1]; // comparison with bottom-right neighbour + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] += dval0[idx - cols - 1]; // comparison with top-right neighbour + dval9[idx] /= 6.0; + } + +#pragma omp parallel for private(idx), shared(dval0, dval9) + for (int j = 1; j < cols - 1; j++) { + // top edge (i=0) + idx = j; + dval9[idx] += dval0[idx + cols + 1]; // comparison with bottom-left neighbour + dval9[idx] += dval0[idx + cols]; // comparison with bottom-central neighbour + dval9[idx] += dval0[idx + cols - 1]; // comparison with bottom-right neighbour + dval9[idx] += dval0[idx + 1]; // comparison with middle-left neighbour + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] /= 6.0; + // bottom edge (i=rows-1) + idx = (rows - 1) * cols + j; + dval9[idx] += dval0[idx + 1]; // comparison with middle-left neighbour + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] += dval0[idx - cols + 1]; // comparison with top-left neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] += dval0[idx - cols - 1]; // comparison with top-right neighbour + dval9[(rows - 1) * cols + j] /= 6.0; + } + // corners + dval9[0] += dval0[cols + 1]; // comparison with bottom-left neighbour + dval9[0] += dval0[cols]; // comparison with bottom-central neighbour + dval9[0] += dval0[1]; // comparison with middle-left neighbour + dval9[0] /= 4.0; + + idx = cols - 1; + dval9[idx] += dval0[idx + cols]; // comparison with bottom-central neighbour + dval9[idx] += dval0[idx + cols - 1]; // comparison with bottom-right neighbour + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] /= 4.0; + + idx = (rows - 1) * cols; + dval9[idx] += dval0[idx + 1]; // comparison with middle-left neighbour + dval9[idx] += dval0[idx - cols + 1]; // comparison with top-left neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] /= 4.0; + + idx = rows * cols - 1; + dval9[idx] += dval0[idx - 1]; // comparison with middle-right neighbour + dval9[idx] += dval0[idx - cols]; // comparison with top-central neighbour + dval9[idx] += dval0[idx - cols - 1]; // comparison with top-right neighbour + dval9[idx] /= 4.0; + +#pragma omp parallel for shared(output, dval0, dval9) + for (int i = 0; i < cols * rows; i++) { + + // setting dval0u to output + output[i] = fmin(1.0, fmax(-1.0, dval0[i])) * SQUARE(dval0[i]) / (SQUARE(dval0[i]) + 4.0 * readNoiseAmp2); + // adding dval9u to output + output[i] += fmax(fmin(dval9[i], mod_clip), -mod_clip) * SQUARE(dval9[i]) / (SQUARE(dval9[i]) + 18.0 * readNoiseAmp2); + + int rcol = i % cols; + double dmod1, dmod2; + if (i < cols) { // first row + dmod1 = 0.0; + } else { + dmod1 = imageOut[i - cols] - imageOut[i]; + } + output[i] += fmax(fmin(dmod1, mod_clip), -mod_clip) * 4 * readNoiseAmp2 / (SQUARE(dmod1) + 4.0 * readNoiseAmp2); + + if (i >= (rows - 1) * cols) { // last row + dmod2 = 0.0; + } else { + dmod2 = imageOut[i + cols] - imageOut[i]; + } + output[i] += fmax(fmin(dmod2, mod_clip), -mod_clip) * 4 * readNoiseAmp2 / (SQUARE(dmod2) + 4.0 * readNoiseAmp2); + + if (smoothCol) { + double cmod1, cmod2; + if (rcol == 0) { // first column + cmod1 = 0.0; + } else { + cmod1 = imageOut[i - 1] - imageOut[i]; + } + output[i] += fmax(fmin(cmod1, mod_clip), -mod_clip) * 4 * readNoiseAmp2 / (SQUARE(cmod1) + 4.0 * readNoiseAmp2); + if (rcol == cols - 1) { // last column + cmod2 = 0.0; + } else { + cmod2 = imageOut[i + 1] - imageOut[i]; + } + output[i] += fmax(fmin(cmod2, mod_clip), -mod_clip) * 4 * readNoiseAmp2 / (SQUARE(cmod2) + 4.0 * readNoiseAmp2); + + output[i] /= 6.0; + } else { + output[i] /= 4.0; + } + } + + free(dval9); +} diff --git a/python/arcticpy/read_noise.py b/python/arcticpy/read_noise.py index 5c8f38c..027326c 100644 --- a/python/arcticpy/read_noise.py +++ b/python/arcticpy/read_noise.py @@ -1,5 +1,6 @@ import numpy as np #import arcticpy as ac +from read_noise_c import determine_noise_model_c try: from arcticpy import wrapper as w @@ -9,7 +10,7 @@ from arcticpy.cti import add_cti,remove_cti import matplotlib as mpl import numpy as np -from scipy.optimize import curve_fit +from scipy.optimize import curve_fit """ CTI correction moves trailed electrons back to their proper location, but also @@ -457,9 +458,13 @@ def _determine_noise_model(self, imageIn: np.ndarray, imageOut: np.ndarray): Method for estimating readnoise on image (in S+R fashion) assumes parallel+serial CTI trailing by default ''' + + # the following line returns the result from the C implementation instead (comment out to switch back to native python code) + return determine_noise_model_c(imageIn, imageOut, self.sigmaRN, self.ampScale, self.smoothCol) + #set target read noise amplitude to be equal to the value specified in the input function readNoiseAmp = self.sigmaRN - + ''' Define up the "comparison" variables for each S+R realisation. In every run, the current value of each pixel in the array is compared to its neighbours; these comparisons will determine how much the pixel value will change in the next interation of the loop. There are diff --git a/python/arcticpy/read_noise_wrapper.pyx b/python/arcticpy/read_noise_wrapper.pyx new file mode 100644 index 0000000..a87e914 --- /dev/null +++ b/python/arcticpy/read_noise_wrapper.pyx @@ -0,0 +1,12 @@ +import numpy as np +cimport numpy as np +cimport cython + +cdef extern void determine_noise_model(const double* imageIn, const double* imageOut, const int rows, const int cols, const double readNoiseAmp, const double readNoiseAmpFraction, const int smoothCol, double* output); + +def determine_noise_model_c(np.ndarray[np.float64_t, ndim=2] arr1, np.ndarray[np.float64_t, ndim=2] arr2, readNoiseAmp, readNoiseAmpFraction, smoothCol): + cdef int rows = arr1.shape[0] + cdef int cols = arr1.shape[1] + cdef np.ndarray[np.float64_t, ndim=2] out = np.zeros((rows, cols), dtype=np.float64) + determine_noise_model(&arr1[0,0], &arr2[0,0], rows, cols, readNoiseAmp, readNoiseAmpFraction, smoothCol, &out[0,0]) + return out diff --git a/setup.py b/setup.py index 40fd359..33b277c 100644 --- a/setup.py +++ b/setup.py @@ -46,9 +46,17 @@ libraries=["gsl"], runtime_library_dirs=[dir_gsl_lib], include_dirs=[dir_wrapper_include, dir_include, np.get_include(), dir_gsl_include], - extra_compile_args=["-std=c++17", "-O3"], + extra_compile_args=["-std=c++17", "-O3", "-fopenmp"], + extra_link_args=["-fopenmp"], define_macros=[('NPY_NO_DEPRECATED_API', 0)], ), + Extension( + 'read_noise_c', + sources=[os.path.join(dir_wrapper, "read_noise_wrapper.pyx"), os.path.join(dir_wrapper, "read_noise.c")], + include_dirs=[np.get_include()], + extra_compile_args=["-O3", "-fopenmp"], + extra_link_args=["-fopenmp"] + ), ] setup( From 0db1946f60d6676c3fd42dd26eabcfcd0e6e11f7 Mon Sep 17 00:00:00 2001 From: Jascha S Date: Fri, 10 Mar 2023 21:33:09 +0000 Subject: [PATCH 25/25] fix to setup.py (g++ does not work for read_noise extension) --- setup.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/setup.py b/setup.py index 33b277c..ba5e088 100644 --- a/setup.py +++ b/setup.py @@ -32,8 +32,8 @@ os.remove(file) # Build -if "CC" not in os.environ: - os.environ["CC"] = "g++" +#if "CC" not in os.environ: +# os.environ["CC"] = "g++" ext_headers = [os.path.join(dir_include, header) for header in os.listdir(dir_include)] ext_sources = [os.path.join(dir_src, src) for src in os.listdir(dir_src)]