From eda860455df3efb287776f5110f2f24e187a6ea3 Mon Sep 17 00:00:00 2001
From: Benoit GAUZERE <benoit.gauzere@insa-rouen.fr>
Date: Fri, 17 Nov 2017 10:45:52 +0100
Subject: [PATCH] Re structuration of project

---
 notebooks/py-graph_test.ipynb             | 1185 +++++++++++++++++++++++++++++
 notebooks/test_lib.ipynb                  |  175 -----
 README.md => pygraph/README.md            |    0
 pygraph/__init__.py                       |   28 +
 {c_ext => pygraph/c_ext}/Makefile         |    0
 pygraph/c_ext/README.md                   |    6 +
 {c_ext => pygraph/c_ext}/lsap.cpp         |    0
 {c_ext => pygraph/c_ext}/lsape_binders.py |    0
 {ged => pygraph/ged}/GED.py               |    0
 {ged => pygraph/ged}/bipartiteGED.py      |    0
 {ged => pygraph/ged}/costfunctions.py     |    0
 {kernels => pygraph/kernels}/.gitignore   |    0
 {utils => pygraph/utils}/graphfiles.py    |    0
 {utils => pygraph/utils}/utils.py         |    0
 14 files changed, 1219 insertions(+), 175 deletions(-)
 delete mode 100644 notebooks/test_lib.ipynb
 rename README.md => pygraph/README.md (100%)
 create mode 100644 pygraph/__init__.py
 rename {c_ext => pygraph/c_ext}/Makefile (100%)
 create mode 100644 pygraph/c_ext/README.md
 rename {c_ext => pygraph/c_ext}/lsap.cpp (100%)
 rename {c_ext => pygraph/c_ext}/lsape_binders.py (100%)
 rename {ged => pygraph/ged}/GED.py (100%)
 rename {ged => pygraph/ged}/bipartiteGED.py (100%)
 rename {ged => pygraph/ged}/costfunctions.py (100%)
 rename {kernels => pygraph/kernels}/.gitignore (100%)
 rename {utils => pygraph/utils}/graphfiles.py (100%)
 rename {utils => pygraph/utils}/utils.py (100%)

diff --git a/notebooks/py-graph_test.ipynb b/notebooks/py-graph_test.ipynb
index ea50015..f090a59 100644
--- a/notebooks/py-graph_test.ipynb
+++ b/notebooks/py-graph_test.ipynb
@@ -447,6 +447,1191 @@
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      ]
+    },
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+     ]
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+     ]
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diff --git a/notebooks/test_lib.ipynb b/notebooks/test_lib.ipynb
deleted file mode 100644
index 653a43b..0000000
--- a/notebooks/test_lib.ipynb
+++ /dev/null
@@ -1,175 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "\n",
-    "import paths\n",
-    "\n",
-    "from ged.GED import ged\n",
-    "from utils.graphfiles import loadDataset\n",
-    "from ged.costfunctions import RiesenCostFunction, BasicCostFunction\n",
-    "from ged.bipartiteGED import computeBipartiteCostMatrix, getOptimalMapping"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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12N8BegM3A7+qvjI9HV59FTIjfsZFAiWm57mb2Y1mttfMis3svjDrzzKzp0Pr\nXzOzLvUvWYLk0ksvZdq0abzxxhts3bqVHj16nL537K233sqaNWs4OW+eNxRTi4lAraPrFRXeGL2I\nhBUx3M2sBbAcGARcBowxs8uqNbsNOOyc+wrwc+BnsS5UklfXrl2555572Lx5M2+99Rbf+MY3WL14\nMcfXrat1jP0p4DxgYG0bdQ7Wr4eysjhVLZLcoum59weKnXP7nXOf4/3dDa/WZjiwKvT7s8BAay6T\niku9XHTRRUycOJH8YcM4q1WrsG0+BmYAiyNtzMw7bVJEaogm3C8GDlR5XBJaFraNc+4EUA6cH4sC\nJaB27MCqnO5Y1f14XwU7RtpGRQXs3BnjwkSCIZqrQcL1wKt/l46mDWY2HhgP0KlTpyheWgKrvDzs\n4u3Ay8Cb0W7n8OEYFSQSLNGEewlndqI6AAdraVNiZi2BDOAf1TfknFsJrATvbJmGFCwBUcs87H8E\n3gMq/+n/FDgJ7AbeCPeENm1iXppIEEQzLFMIdDOzrmaWCowG1lVrsw74Qej3m4HfO7/OsZTk0KcP\nhBlzHw/sw+vBbwfuAIYAG8NtIy0NeveOY5EiyStiuIfG0O/E+/vaAzzjnNtlZnPM7KZQs/8PnG9m\nxcDdQI3TJUXOMG5c2MXpwAVVfs4BWgHtwjV2rtbtiDR3Uc3A5JxbD6yvtmxGld+PAt+LbWkSaO3b\nw6BBsGZNnVMOzKpthRkMHgztwsa+SLOnm3WIf3JyvKGVhkhL854vImEp3MU//fp5c8Skp9fveZVz\ny2jqAZFaaWJs8Vfl5F9RzAqJmddj16RhIhGp5y7+y872JgEbMcI7g6b6UE1amrd8xAivnYJdJCL1\n3CUxZGZCfr43V0xennfl6eHD3nnsvXt7Z8Xo4KlI1BTukljatYMpU/yuQiTpaVhGRCSAFO4iIgGk\ncBcRCSCFu4hIACncRUQCSOEuIhJACncRkQBSuIuIBJD5dU8NMysD/tbEL9sW+HsTv6YftJ/B0Rz2\nEbSf9dHZORfxcm3fwt0PZlbknAv8VILaz+BoDvsI2s940LCMiEgAKdxFRAKouYX7Sr8LaCLaz+Bo\nDvsI2s+Ya1Zj7iIizUVz67mLiDQLgQx3M7vRzPaaWbGZ3Rdm/Vlm9nRo/Wtm1qXpq2y8KPbzbjPb\nbWY7zOwVM+vsR52NEWkfq7S72cycmSXlGRfR7KeZjQq9n7vM7NdNXWMsRPGZ7WRmfzCzN0Of28F+\n1NkYZvYUS70MAAADKUlEQVRLMys1s7dqWW9m9nDo/8EOM/taXApxzgXqB2gB7AMuAVKBvwCXVWsz\nAXgk9Pto4Gm/647Tfn4LSA/9np1s+xnNPobanQv8F7AVyPS77ji9l92AN4E2ocft/a47Tvu5EsgO\n/X4Z8J7fdTdgP68Bvga8Vcv6wcAGwIArgdfiUUcQe+79gWLn3H7n3OfAU8Dwam2GA6tCvz8LDDQz\na8IaYyHifjrn/uCcOxJ6uBXo0MQ1NlY07yXAXOBB4GhTFhdD0ezn7cBy59xhAOdcaRPXGAvR7KcD\nWod+zwAONmF9MeGc+y/gH3U0GQ484TxbgfPM7MJY1xHEcL8YOFDlcUloWdg2zrkTQDlwfpNUFzvR\n7GdVt+H1FpJJxH00syuAjs653zVlYTEWzXvZHehuZpvNbKuZ3dhk1cVONPs5CxhrZiXAemBS05TW\npOr7t9sgQbyHargeePVTgqJpk+ii3gczGwtkAt+Ma0WxV+c+mlkK8HNgXFMVFCfRvJct8YZmrsX7\nBrbJzL7qnPsozrXFUjT7OQbIc84tNrOrgNWh/TwV//KaTJPkTxB77iVAxyqPO1Dzq93pNmbWEu/r\nX11foxJRNPuJmV0PTANucs4da6LaYiXSPp4LfBX4o5m9hzd+uS4JD6pG+5ld65w77px7F9iLF/bJ\nJJr9vA14BsA5twVohTcfS5BE9bfbWEEM90Kgm5l1NbNUvAOm66q1WQf8IPT7zcDvXehIRxKJuJ+h\nIYtH8YI9Gcdo69xH51y5c66tc66Lc64L3nGFm5xzRf6U22DRfGbX4B0gx8za4g3T7G/SKhsvmv38\nb2AggJldihfuZU1aZfytA24NnTVzJVDunDsU81fx+8hynI5WDwbexjsyPy20bA7eHz54H5jfAsXA\n68Alftccp/18GfgA2B76Wed3zbHex2pt/0gSni0T5XtpwBJgN7ATGO13zXHaz8uAzXhn0mwHbvC7\n5gbs42+AQ8BxvF76bcAdwB1V3svlof8HO+P1mdUVqiIiARTEYRkRkWZP4S4iEkAKdxGRAFK4i4gE\nkMJdRCSAFO4iIgGkcBcRCSCFu4hIAP0v8ncXPBCruC4AAAAASUVORK5CYII=\n",
-      "text/plain": [
-       "<matplotlib.figure.Figure at 0x7f61fed58cc0>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "[0, 1, 4]\n"
-     ]
-    }
-   ],
-   "source": [
-    "import networkx as nx\n",
-    "import numpy as np\n",
-    "import matplotlib.pyplot  as plt\n",
-    "dataset, y = loadDataset(\"/home/bgauzere/work/Datasets/Acyclic/dataset_bps.ds\")\n",
-    "nx.draw_networkx(dataset[12])\n",
-    "plt.show()\n",
-    "print(list(dataset[12][3]))"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [],
-   "source": [
-    "cf = BasicCostFunction(1,3,1,3)\n",
-    "N=len(dataset)\n",
-    "N=10\n",
-    "ged_distances = np.zeros((N,N))\n",
-    "for i in range(0,N):\n",
-    "    for j in range(i,N):\n",
-    "          ged_distances[j,i] = ged_distances[i,j] = ged(dataset[i],dataset[j],cf=cf, method='Riesen')[0]\n",
-    "        \n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n",
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n",
-      "(0, array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]), array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))\n"
-     ]
-    }
-   ],
-   "source": [
-    "G1=dataset[12]\n",
-    "G2=dataset[12]\n",
-    "\n",
-    "print(ged(G1,G2))\n",
-    "print(ged(G1,G2,method='Basic'))\n",
-    "print(ged(G1,G2,method='Riesen'))\n"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "metadata": {
-    "autoscroll": false,
-    "ein.tags": "worksheet-0",
-    "slideshow": {
-     "slide_type": "-"
-    }
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{0: {0: [0], 3: [0, 3], 1: [0, 3, 1], 4: [0, 3, 4], 2: [0, 3, 4, 2]}, 1: {1: [1], 3: [1, 3], 0: [1, 3, 0], 4: [1, 3, 4], 2: [1, 3, 4, 2]}, 2: {2: [2], 4: [2, 4], 3: [2, 4, 3], 0: [2, 4, 3, 0], 1: [2, 4, 3, 1]}, 3: {3: [3], 0: [3, 0], 1: [3, 1], 4: [3, 4], 2: [3, 4, 2]}, 4: {4: [4], 2: [4, 2], 3: [4, 3], 0: [4, 3, 0], 1: [4, 3, 1]}}\n",
-      "[[ 0.  2.  3.  1.  2.]\n",
-      " [ 2.  0.  3.  1.  2.]\n",
-      " [ 3.  3.  0.  2.  1.]\n",
-      " [ 1.  1.  2.  0.  1.]\n",
-      " [ 2.  2.  1.  1.  0.]]\n"
-     ]
-    }
-   ],
-   "source": [
-    "l = nx.shortest_path(G1)\n",
-    "print(l)\n",
-    "\n",
-    "distances = np.zeros((G1.number_of_nodes(),G1.number_of_nodes()))\n",
-    "for i in l.keys():\n",
-    "    for j in l[i].keys():\n",
-    "        distances[i,j] = len(l[i][j])-1\n",
-    "\n",
-    "print(distances)\n"
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "Python 3",
-   "language": "python",
-   "name": "python3"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.2"
-  },
-  "name": "test_lib.ipynb"
- },
- "nbformat": 4,
- "nbformat_minor": 2
-}
diff --git a/README.md b/pygraph/README.md
similarity index 100%
rename from README.md
rename to pygraph/README.md
diff --git a/pygraph/__init__.py b/pygraph/__init__.py
new file mode 100644
index 0000000..42f83b5
--- /dev/null
+++ b/pygraph/__init__.py
@@ -0,0 +1,28 @@
+# -*-coding:utf-8 -*-
+
+"""
+Pygraph
+
+This  package contains 4 sub  packages :
+        * c_ext : binders to C++ code
+        * ged : allows to compute graph edit distance between networkX graphs
+        * kernels : computation of graph kernels, ie graph similarity measure compatible with SVM
+        * notebooks : examples of code using this library
+        * utils : Diverse computation on graphs
+ 
+je vous passe le blabla
+ 
+"""
+ 
+# info
+__version__ = "0.1"
+__author__  = "Benoit Gaüzère"
+__date__    = "November 2017"
+ 
+# import sub modules
+from c_ext import lsape_binders
+from ged import bipartiteGED
+from ged import costfunctions
+from ged import GED
+from utils import graphfiles
+from utils import utils
diff --git a/c_ext/Makefile b/pygraph/c_ext/Makefile
similarity index 100%
rename from c_ext/Makefile
rename to pygraph/c_ext/Makefile
diff --git a/pygraph/c_ext/README.md b/pygraph/c_ext/README.md
new file mode 100644
index 0000000..f1aa549
--- /dev/null
+++ b/pygraph/c_ext/README.md
@@ -0,0 +1,6 @@
+Python wrapper for lsape method
+
+Specify your LSAPE_DIR env variable with the location of the source
+code to compile
+
+source code : https://bougleux.users.greyc.fr/lsape/
diff --git a/c_ext/lsap.cpp b/pygraph/c_ext/lsap.cpp
similarity index 100%
rename from c_ext/lsap.cpp
rename to pygraph/c_ext/lsap.cpp
diff --git a/c_ext/lsape_binders.py b/pygraph/c_ext/lsape_binders.py
similarity index 100%
rename from c_ext/lsape_binders.py
rename to pygraph/c_ext/lsape_binders.py
diff --git a/ged/GED.py b/pygraph/ged/GED.py
similarity index 100%
rename from ged/GED.py
rename to pygraph/ged/GED.py
diff --git a/ged/bipartiteGED.py b/pygraph/ged/bipartiteGED.py
similarity index 100%
rename from ged/bipartiteGED.py
rename to pygraph/ged/bipartiteGED.py
diff --git a/ged/costfunctions.py b/pygraph/ged/costfunctions.py
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diff --git a/utils/graphfiles.py b/pygraph/utils/graphfiles.py
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