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@rionbr
rionbr committed Feb 19, 2018
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272 changes: 272 additions & 0 deletions tutorials/Tutorial - Canalization - BioModels - LUT.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"metadata": {
"collapsed": true
},
"source": [
"# Tutorial - Plotting LUT\n",
"This tutorial shows how to plot Prime Implicants (F') and Two-Symbol (F'') schematas"
]
},
{
"cell_type": "code",
"execution_count": 46,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import os\n",
"import numpy as np\n",
"import matplotlib as mpl\n",
"import matplotlib.style\n",
"mpl.style.use('classic')\n",
"import matplotlib.pyplot as plt\n",
"from matplotlib.text import Text\n",
"from matplotlib.patches import Circle, Rectangle, RegularPolygon\n",
"from matplotlib.collections import PatchCollection\n",
"from copy import copy"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"from cana.datasets.bio import THALIANA, DROSOPHILA, BUDDING_YEAST"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"<BNetwork(Name='Arabidopsis Thaliana', N=15, Nodes=['AP3', 'UFO', 'FUL', 'FT', 'AP1', 'EMF1', 'LFY', 'AP2', 'WUS', 'AG', 'LUG', 'CLF', 'TFL1', 'PI', 'SEP'])>\n"
]
}
],
"source": [
"N = THALIANA()\n",
"#N = DROSOPHILA()\n",
"#N = BUDDING_YEAST()\n",
"print N"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"if N.name == 'Arabidopsis Thaliana':\n",
" foldername = 'thaliana'\n",
"elif N.name == 'Drosophila Melanogaster':\n",
" foldername = 'drosophila'\n",
"elif N.name == 'Budding Yeast Cell Cycle':\n",
" foldername = 'yeast'"
]
},
{
"cell_type": "code",
"execution_count": 75,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [],
"source": [
"def plot_look_up_table(nid, n):\n",
" # Init values from BooleanNode\n",
" k = n.k if n.k>=1 else 1\n",
" inputs = n.inputs if not n.constant else [n.name]\n",
" LUT = n.look_up_table().sort_index(ascending=False)\n",
" # Count number of F in the LUT\n",
" n_fs = LUT.shape[0]\n",
" # Schemata Cell Width and spacing\n",
" cwidth = 60.\n",
" cxspace = 0\n",
" cyspace = 6\n",
" border = 1\n",
" sepcxspace = 21\n",
" sepcyspace = 15\n",
" dpi = 150.\n",
" # Margins\n",
" top, right, bottom, left, hs = 120, 25, 25, 60, 25\n",
" # Axes Width & Height\n",
" ax1width = ((k*(cwidth+cxspace))+sepcxspace+(cwidth))\n",
" ax1height = (n_fs*(cwidth+cyspace)-cyspace)\n",
" # Figure Width & Height\n",
" fwidth = (left + ax1width + hs + right)\n",
" fheight = (bottom + ax1height + top)\n",
" # Percentages for Axes location\n",
" _ax1w = ((ax1width*100) / fwidth) / 100\n",
" _ax1h = ((ax1height*100) / fheight) / 100\n",
" _bottom = ((bottom*100) / fheight) / 100\n",
" _left = ((left*100) / fwidth) / 100\n",
" _hs = ((hs*100) / fwidth) / 100\n",
" # Init Figure\n",
" fig = plt.figure(figsize=(fwidth/dpi,fheight/dpi), dpi=dpi)\n",
" ax1 = fig.add_axes((_left,_bottom,_ax1w,_ax1h), aspect=1, label='LUT')\n",
"\n",
" ### LUT Plot ###\n",
"\n",
" yticks = []\n",
" patches = []\n",
" x,y = 0.,0.\n",
" #\n",
" for i,r in LUT.iterrows():\n",
" ins = str(r['In:'])\n",
" out = r['Out:']\n",
" x = 0.\n",
" xticks = []\n",
" for input in ins:\n",
" if input == '0':\n",
" facecolor = 'white'\n",
" textcolor = 'black'\n",
" elif input == '1':\n",
" facecolor = 'black'\n",
" textcolor = 'white' \n",
" text = '%s'%(input)\n",
" ax1.add_artist(Text(x+cwidth/2,y+cwidth/10*4, text=text, color=textcolor, va='center', ha='center',fontsize=14,family='serif'))\n",
" r = Rectangle((x,y), width=cwidth, height=cwidth, facecolor=facecolor, edgecolor='black')\n",
" patches.append(r)\n",
" xticks.append(x+cwidth/2)\n",
" x += cwidth + cxspace\n",
"\n",
" x += sepcxspace\n",
" r = Rectangle((x,y), width=cwidth, height=cwidth, facecolor='black' if (out==1) else 'white', edgecolor='black')\n",
" ax1.add_artist(Text(x-(sepcxspace/2)-(cxspace/2),y+cwidth/10*4, text=':', color='black', va='center', ha='center',fontsize=14,weight='bold',family='serif'))\n",
" ax1.add_artist(Text(x+(cwidth/2),y+cwidth/10*4, text=out, color='white' if (out==1) else 'black', va='center', ha='center',fontsize=14,family='serif'))\n",
" patches.append(r)\n",
" xticks.append(x+cwidth/2)\n",
" yticks.append(y+cwidth/2)\n",
" y += cwidth + cyspace\n",
"\n",
" #y += sepcyspace\n",
"\n",
" ax1.add_collection(PatchCollection(patches,match_original=True))\n",
" #\n",
" ax1.set_yticks(yticks)\n",
" ax1.set_yticklabels([r\"$f_{%d}$\"%(i+1) for i in range(n_fs)[::-1]], fontsize=14)\n",
" ax1.set_xticks(xticks)\n",
" ax1.set_xticklabels(inputs + ['%s'%(n.name)], rotation=90, fontsize=14)\n",
" #\n",
" ax1.xaxis.tick_top()\n",
" # Remove Tick\n",
" ax1.tick_params(which='major',pad=7)\n",
" for tic in ax1.xaxis.get_major_ticks():\n",
" tic.tick1On = tic.tick2On = False\n",
" for tic in ax1.yaxis.get_major_ticks():\n",
" tic.tick1On = tic.tick2On = False\n",
" # Remove Border\n",
" ax1.spines['top'].set_visible(False)\n",
" ax1.spines['right'].set_visible(False)\n",
" ax1.spines['bottom'].set_visible(False)\n",
" ax1.spines['left'].set_visible(False)\n",
" # Limits\n",
" ax1.set_xlim(-border,ax1width+border)\n",
" ax1.set_ylim(-border,ax1height+border)\n",
" #ax1.invert_yaxis() \n",
"\n",
" # FileName\n",
" filename = n.name\n",
" filename = filename.replace('/','_')\n",
" filename = filename.replace(',','_')\n",
" ### SAVE to FILE ###\n",
" plt.savefig('%s/../experiments/2017 - BioModels/%s/LUT/%s-%s' % (os.getcwd(), foldername, nid, filename), dpi=dpi)\n",
" plt.close()"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Plotting: 0 - CellSize\n",
"Plotting: 1 - Cln3\n",
"Plotting: 2 - SBF\n",
"Plotting: 3 - MBF\n",
"Plotting: 4 - Cln1,2\n",
"Plotting: 5 - Sic1\n",
"Plotting: 6 - Clb5,6\n",
"Plotting: 7 - Cdh1\n",
"Plotting: 8 - Clb1,2\n",
"Plotting: 9 - Mcm1/SFF\n",
"Plotting: 10 - Cdc20/14\n",
"Plotting: 11 - Swi5\n"
]
}
],
"source": [
"for nid,n in enumerate(N.nodes):\n",
" print 'Plotting: %s - %s' % (nid,n.name)\n",
" # Plot\n",
" plot_look_up_table(nid,n)"
]
},
{
"cell_type": "code",
"execution_count": 76,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"nid = 12\n",
"n = N.nodes[nid]\n",
"plot_look_up_table(nid,n)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.11"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
12 changes: 4 additions & 8 deletions tutorials/Tutorial - Canalization - BioModels - Schematas.ipynb
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Expand Up @@ -80,7 +80,7 @@
},
{
"cell_type": "code",
"execution_count": 14,
"execution_count": null,
"metadata": {
"collapsed": false
},
Expand Down Expand Up @@ -271,8 +271,7 @@
" ax2.set_ylim(-border,ax2height+border)\n",
"\n",
" # FileName\n",
" filename = n.name\n",
" filename = filename.replace('/','_')\n",
" filename = n.name.replace('/','_')\n",
" filename = filename.replace(',','_')\n",
" ### SAVE to FILE ###\n",
" plt.savefig('%s/../experiments/2017 - BioModels/%s/schematas/%s-%s' % (os.getcwd(), foldername, nid, filename), dpi=dpi)\n",
Expand All @@ -281,7 +280,7 @@
},
{
"cell_type": "code",
"execution_count": 15,
"execution_count": null,
"metadata": {
"collapsed": false,
"scrolled": false
Expand All @@ -299,10 +298,7 @@
"Plotting: 5 - Sic1\n",
"Plotting: 6 - Clb5,6\n",
"Plotting: 7 - Cdh1\n",
"Plotting: 8 - Clb1,2\n",
"Plotting: 9 - Mcm1/SFF\n",
"Plotting: 10 - Cdc20/14\n",
"Plotting: 11 - Swi5\n"
"Plotting: 8 - Clb1,2"
]
}
],
Expand Down
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