Make repo installable with pip install -e

DeepSITH_testing.ipynb → notebooks/DeepSITH_testing.ipynb

@@ -11,14 +11,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<class 'torch.cuda.DoubleTensor'>\n"
+      "<class 'torch.DoubleTensor'>\n"
      ]
     }
    ],
@@ -38,7 +38,7 @@
     "from math import factorial\n",
     "ttype = torch.cuda.DoubleTensor if torch.cuda.is_available() else torch.DoubleTensor\n",
     "print(ttype)\n",
-    "from deep_isith import DeepSITH\n",
+    "from sith import DeepSITH\n",
     "from tqdm.notebook import tqdm\n",
     "import pickle\n",
     "sn.set_context(\"poster\")"
@@ -441,7 +441,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

DeepiSITH_testing.ipynb → notebooks/DeepiSITH_testing.ipynb

@@ -11,14 +11,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "<class 'torch.cuda.DoubleTensor'>\n"
+      "<class 'torch.DoubleTensor'>\n"
      ]
     }
    ],
@@ -40,7 +40,7 @@
     "print(ttype)\n",
     "\n",
     "# deep_iSITH is being used here, not deep_sith\n",
-    "from deep_isith import DeepSITH\n",
+    "from sith import DeepSITH\n",
     "from tqdm.notebook import tqdm\n",
     "import pickle\n",
     "sn.set_context(\"poster\")"
@@ -435,7 +435,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

Simple_Network_example.ipynb → notebooks/Simple_Network_example.ipynb

@@ -912,7 +912,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   },
   "toc": {
    "nav_menu": {},

Sith_Layer_Verification.ipynb → notebooks/Sith_Layer_Verification.ipynb

@@ -520,7 +520,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   },
   "toc": {
    "nav_menu": {},

iSITH_verifications.ipynb → notebooks/iSITH_verifications.ipynb

@@ -40,7 +40,7 @@
     "print(ttype)\n",
     "\n",
     "# deep_iSITH is being used here, not deep_sith\n",
-    "from isith import iSITH\n",
+    "from sith import iSITH\n",
     "from tqdm.notebook import tqdm\n",
     "import pickle\n",
     "sn.set_context(\"poster\")"
@@ -1035,7 +1035,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.6"
+   "version": "3.8.5"
   }
  },
  "nbformat": 4,

setup.cfg

@@ -0,0 +1,31 @@
+[metadata]
+author = Beeg Jacques
+author_email = beegjacques@yahoo.com
+classifiers =
+    Development Status :: 1 - Alpha
+    Intended Audience :: Science/Research
+    License :: OSI Approved :: GNU General Public License v3 (GPLv3)
+    Programming Language :: Python :: 3.7
+description = This repo contains code for the Scale Invariant Temporal History (SITH) module for use with PyTorch. It is build on a Laplace module that performs the Laplace transform of a temporal series.
+license_file = LICENSE
+project_urls =
+    GitHub = https://github.com/compmem/SITH_Layer
+url = https://github.com/compmem/SITH_Layer
+
+[options]
+python_requires = >= 3.7
+install_requires =
+    attrs
+    jinja2
+    matplotlib >= 2.2.0
+    packaging
+    pandas
+    scipy
+    seaborn
+    torch
+
+packages = find:
+
+[options.packages.find]
+exclude =
+    *.tests

setup.py

@@ -0,0 +1,26 @@
+
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+""" comppsychflows setup script """
+import sys
+from setuptools import setup
+
+# Use setup_requires to let setuptools complain if it's too old for a feature we need
+# 30.3.0 allows us to put most metadata in setup.cfg
+# 30.4.0 gives us options.packages.find
+# 40.8.0 includes license_file, reducing MANIFEST.in requirements
+#
+# To install, 30.4.0 is enough, but if we're building an sdist, require 40.8.0
+# This imposes a stricter rule on the maintainer than the user
+# Keep the installation version synchronized with pyproject.toml
+SETUP_REQUIRES = ['setuptools >= %s' % ("40.8.0" if "sdist" in sys.argv else "30.4.0")]
+
+# This enables setuptools to install wheel on-the-fly
+SETUP_REQUIRES += ['wheel'] if 'bdist_wheel' in sys.argv else []
+
+if __name__ == '__main__':
+    # Note that "name" is used by GitHub to determine what repository provides a package
+    # in building its dependency graph.
+    setup(name='SITH_Layer',
+          setup_requires=SETUP_REQUIRES,
+          )

sith/__init__.py

@@ -0,0 +1,6 @@
+from .sith import SITH
+from .isith import iSITH
+from .laplace import Laplace
+from .deep_isith import DeepSITH
+
+__all__ = [SITH, iSITH, Laplace, DeepSITH]

deep_isith.py → sith/deep_isith.py

@@ -4,7 +4,7 @@
 
 import torch
 from torch import nn
-from isith import iSITH
+from .isith import iSITH
 from torch.nn.utils import weight_norm
 
 

sith.py → sith/sith.py

@@ -4,7 +4,7 @@
 
 import torch
 from torch import nn as nn
-from laplace import Laplace
+from .laplace import Laplace
 from math import factorial