CIMP/PlotImage.py at develop · mmiesch/CIMP · GitHub

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import matplotlib.pyplot as plt
import numpy as np
import sunpy.map
import sunpy.visualization.colormaps as cm

from sunpy.io import fits
from skimage.measure import block_reduce

def downsample(im):
    return block_reduce(im, block_size = 2, func = np.nanmedian, cval = np.nanmin(im))


#dir = '/home/mark.miesch/data/lasco_monthly/c3/2012_04/'
#file = dir+'03/32295364.fts'
#file = dir+'02/daily_median.fts'

#dir = '/home/mark.miesch/data/anny/CME0/pos-30/dcmer_030W_bang_0000_fits/tB/'
#file = dir+'frame_0050.fits'
#file = dir+'frame_0000.fits'

# L1 STEREO data
dir='/home/mark.miesch/sunpy/data/secchi_cor2/L1/2012/09/07/'
#file = dir+'20120901_153900_14c2A.fts'
#file = dir+'20120907_163900_14c2A.fts'
file = dir+'daily_median.fts'
scale=(0,2.e-8)

dir='/home/mark.miesch/sunpy/data/secchi_cor2/L1/2012/09/'
file = dir+'background.fts'
scale=(0,2.e-8)

#dir = '/home/mark.miesch/data/lasco_monthly/c3/2012_04/'
#dir = '/home/mark.miesch/data/lasco_monthly/c3/2014_01/'
#file = dir+'background.fts'

#cmap_lasco_c2 = plt.get_cmap('soholasco2')
cmap_stereo_cor2 = plt.get_cmap('stereocor2')

data, header = fits.read(file)[0]

# needed only for the model field
#header['CUNIT1'] = 'arcsec'
#header['CUNIT2'] = 'arcsec'

#header['CDELT1'] = 30/float(nx)
#header['CDELT2'] = 30/float(ny)
#
#header['CRPIX1'] = 242.5
#header['CRPIX2'] = 242.5

#print(f"{header['CRPIX1']} {header['CRPIX2']}")

dmap = sunpy.map.Map(data, header)
#dmap.plot(cmap = cmap_stereo_cor2)
#plt.imshow(data, cmap = cmap_stereo_cor2,vmin=scale[0],vmax=scale[1])

d = downsample(data)

plt.figimage(d,cmap=cmap_stereo_cor2,vmin=scale[0],vmax=scale[1],resize=True,
             origin='lower')

print(f" minmax: {np.nanmin(data)} {np.nanmax(data)}")

plt.show()