Add test case to compare files and fix Travis complaints

.gitignore

@@ -37,3 +37,5 @@ Theano.suo
 .ipynb_checkpoints
 .pydevproject
 doc/library/d3viz/GSoC/
+theano/d3viz/tests/data/test_d3viz/*/d3viz/
+

doc/library/d3viz/index.ipynb

@@ -35,7 +35,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "`d3viz` extends Theano’s [printing module](http://deeplearning.net/software/theano/library/printing.html) to interactively visualize compute graphs. Instead of creating a static picture, it creates an HTML file, which can be opened with any web-browser. `d3viz` allows\n",
+    "`d3viz` extends Theano’s [printing module](http://deeplearning.net/software/theano/library/printing.html) to interactively visualize compute graphs. Instead of creating a static picture, it creates an HTML file, which can be opened with current web-browsers. `d3viz` allows\n",
     "\n",
     "* to zoom to different regions and to move graphs via drag and drop,\n",
     "* to position nodes both manually and automatically,\n",

doc/library/d3viz/index.txt

@@ -29,8 +29,8 @@ Overview
 ``d3viz`` extends Theano’s `printing
 module <http://deeplearning.net/software/theano/library/printing.html>`__
 to interactively visualize compute graphs. Instead of creating a static
-picture, it creates an HTML file, which can be opened with any
-web-browser. ``d3viz`` allows
+picture, it creates an HTML file, which can be opened with current
+web-browsers. ``d3viz`` allows
 
 -  to zoom to different regions and to move graphs via drag and drop,
 -  to position nodes both manually and automatically,
@@ -166,7 +166,7 @@ language <http://www.graphviz.org/>`__, using the
 `pydot <https://pypi.python.org/pypi/pydot>`__ package, and defines a
 front-end based on the `d3.js <http://d3js.org/>`__ library to visualize
 it. However, any other Graphviz front-end can be used, which allows to
-export graps to different formats.
+export graphs to different formats.
 
 .. code:: python
 

theano/d3viz/__init__.py

-from d3viz import *
+from theano.d3viz.d3viz import d3viz, d3write

theano/d3viz/d3viz.py

@@ -26,7 +26,7 @@ def escape_quotes(s):
     return s
 
 
-def d3viz(fct, outfile,  copy_deps=True, *args, **kwargs):
+def d3viz(fct, outfile, copy_deps=True, *args, **kwargs):
     """Create HTML file with dynamic visualizing of a Theano function graph.
 
     :param fct: A compiled Theano function, variable, apply or a list of

theano/d3viz/formatting.py

@@ -5,8 +5,8 @@ Author: Christof Angermueller <cangermueller@gmail.com>
 
 import numpy as np
 import logging
-import re
 import os.path as pt
+from functools import reduce
 
 try:
     import pydot as pd
@@ -121,7 +121,7 @@ class PyDotFormatter(object):
             nparams['label'] = apply_label(node)
             nparams['profile'] = apply_profile(node, profile)
             nparams['node_type'] = 'apply'
-            nparams['apply_op'] = apply_op(node)
+            nparams['apply_op'] = nparams['label']
             nparams['shape'] = self.shapes['apply']
 
             use_color = None
@@ -175,7 +175,7 @@ class PyDotFormatter(object):
                                  **edge_params)
                 graph.add_edge(pdedge)
 
-            # Loop over ouput nodes
+            # Loop over output nodes
             for id, var in enumerate(node.outputs):
                 var_id = self.__node_id(var)
 
@@ -201,7 +201,7 @@ class PyDotFormatter(object):
                     graph.add_edge(pd.Edge(__node_id, var_id,
                                            label=vparams['dtype']))
 
-            # Create sub-groph for OpFromGraph nodes
+            # Create sub-graph for OpFromGraph nodes
             if isinstance(node.op, builders.OpFromGraph):
                 subgraph = pd.Cluster(__node_id)
                 gf = PyDotFormatter()
@@ -277,14 +277,6 @@ def apply_label(node):
     return node.op.__class__.__name__
 
 
-def apply_op(node):
-    """Return apply operation."""
-    name = str(node.op).replace(':', '_')
-    name = re.sub('^<', '', name)
-    name = re.sub('>$', '', name)
-    return name
-
-
 def apply_profile(node, profile):
     """Return apply profiling informaton."""
     if not profile or profile.fct_call_time == 0:

theano/d3viz/html/template.html

@@ -35,18 +35,14 @@
 		var profileColors = ["#fff5f0","#fee0d2","#fcbba1","#fc9272","#fb6a4a","#ef3b2c","#cb181d","#a50f15"];
 		var pad = 10;
 		var isEditNode = false; // true if node is edited
-    	var menuItems = [
+		var menuItems = [
 			{
 				title: 'Edit',
-				action: function(elm, d, i) {
-					editNode(elm, d);
-				}
+				action: function(elm, d, i) { editNode(elm, d); }
 			},
 			{
 				title: 'Release',
-				action: function(elm, d, i) {
-					releaseNode(d);
-				}
+				action: function(elm, d, i) { releaseNode(d); }
 			}
 		];
 

theano/d3viz/tests/data/test_d3viz/make.py

+#!/usr/bin/env python
+
+"""Creates reference files for testing d3viz module.
+Used in tests/test_d3viz.py.
+
+Author: Christof Angermueller <cangermueller@gmail.com>
+"""
+
+import theano as th
+import theano.d3viz as d3v
+from theano.d3viz.tests import models
+
+
+model = models.Mlp()
+f = th.function(model.inputs, model.outputs)
+d3v.d3viz(f, 'mlp/index.html')
+
+model = models.Ofg()
+f = th.function(model.inputs, model.outputs)
+d3v.d3viz(f, 'ofg/index.html')
+
+model = models.OfgNested()
+f = th.function(model.inputs, model.outputs)
+d3v.d3viz(f, 'ofg_nested/index.html')

theano/d3viz/tests/data/test_d3viz/mlp/index.html

+<!DOCTYPE html>
+<html>
+<head>
+	<link rel="stylesheet" href="d3viz/css/d3viz.css"/>
+	<link rel="stylesheet" href="d3viz/css/d3-context-menu.css"/>
+	<script type="text/javascript" src="d3viz/js/d3viz.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3.v3.min.js"></script>
+	<script type="text/javascript" src="d3viz/js/dagre-d3.js"></script>
+	<script type="text/javascript" src="d3viz/js/graphlib-dot.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3-context-menu.js"></script>
+</head>
+<body>
+	<div id='menu' class='menuBar'>
+	    <input name="resetNodes" 
+	           type="button" 
+	           value="Reset nodes"
+	           onclick="resetNodes()"/>
+	    <input name="releaseNodes" 
+	           type="button" 
+	           value="Release nodes"
+	           onclick="releaseNodes()"/>
+	</div>
+
+	<script type="text/javascript">
+		// Backend graph in DOT format
+		var dotGraph = graphlibDot.read("digraph G {	graph [bb=\"0,0,272,476\"];	node [label=\"\N\"];	n1	 [apply_op=DimShuffle,		height=0.5,		label=DimShuffle,		node_type=apply,		pos=\"219,370\",		shape=ellipse,		width=1.4763];	n8	 [apply_op=Elemwise,		fillcolor=\"#FFAABB\",		height=0.5,		label=Elemwise,		node_type=apply,		pos=\"170,282\",		shape=ellipse,		style=filled,		type=colored,		width=1.2888];	n1 -> n8	 [label=\"1 dmatrix\",		lp=\"225.5,326\",		pos=\"e,179.49,299.66 209.32,352.01 202.23,339.56 192.48,322.45 184.47,308.39\"];	n2	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"219,458\",		shape=box,		style=filled,		width=0.80556];	n2 -> n1	 [color=dodgerblue,		label=dvector,		lp=\"240,414\",		pos=\"e,219,388.08 219,439.6 219,427.75 219,411.82 219,398.29\"];	n4	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"114,370\",		shape=ellipse,		width=0.92774];	n4 -> n8	 [color=red,		label=\"0 dmatrix\",		lp=\"158.5,326\",		pos=\"e,148.95,298.37 117.35,351.95 119.93,341.54 124.24,328.3 131,318 133.92,313.55 137.54,309.31 141.39,305.41\"];	n5	 [dtype=dmatrix,		fillcolor=limegreen,		height=0.5,		label=x,		node_type=input,		pos=\"50,458\",		shape=box,		style=filled,		width=0.75];	n5 -> n4	 [label=\"0 dmatrix\",		lp=\"88.5,414\",		pos=\"e,89.174,382.09 50.492,439.64 51.537,429.12 54.251,415.87 61,406 66.011,398.67 73.111,392.49 80.491,387.46\"];	n6	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"128,458\",		shape=box,		style=filled,		width=0.83333];	n6 -> n4	 [label=\"1 dmatrix\",		lp=\"149.5,414\",		pos=\"e,116.78,388.08 125.17,439.6 123.24,427.75 120.64,411.82 118.44,398.29\"];	n10	 [apply_op=Dot22,		height=0.5,		label=Dot22,		node_type=apply,		pos=\"118,194\",		shape=ellipse,		width=0.92774];	n8 -> n10	 [label=\"0 dmatrix\",		lp=\"175.5,238\",		pos=\"e,127.82,211.24 159.97,264.42 152.37,251.85 141.8,234.35 133.16,220.07\"];	n13	 [apply_op=SoftmaxWithBias,		height=0.5,		label=SoftmaxWithBias,		node_type=apply,		pos=\"76,106\",		shape=ellipse,		width=2.1117];	n10 -> n13	 [label=\"0 dmatrix\",		lp=\"128.5,150\",		pos=\"e,84.361,124.12 109.9,176.42 103.94,164.2 95.704,147.35 88.845,133.3\"];	n11	 [dtype=dmatrix,		fillcolor=YellowGreen,		height=0.5,		label=dmatrix,		node_type=shared_input,		pos=\"75,282\",		shape=box,		style=filled,		width=0.83333];	n11 -> n10	 [label=\"1 dmatrix\",		lp=\"111.5,238\",		pos=\"e,100.16,209.41 75.526,263.66 76.44,253.4 78.677,240.41 84,230 86.398,225.31 89.636,220.84 93.164,216.75\"];	n15	 [dtype=dmatrix,		fillcolor=dodgerblue,		height=0.5,		label=dmatrix,		node_type=output,		pos=\"76,18\",		shape=box,		style=filled,		width=0.83333];	n13 -> n15	 [label=dmatrix,		lp=\"98,62\",		pos=\"e,76,36.084 76,87.597 76,75.746 76,59.817 76,46.292\"];	n14	 [dtype=dvector,		fillcolor=YellowGreen,		height=0.5,		label=dvector,		node_type=shared_input,		pos=\"37,194\",		shape=box,		style=filled,		width=0.80556];	n14 -> n13	 [label=\"1 dvector\",		lp=\"66.5,150\",		pos=\"e,53.961,123.42 34.978,175.72 34.504,165.47 35.203,152.48 40,142 41.795,138.08 44.242,134.36 47.022,130.92\"];}");
+		// Frontend graph for visualization
+		var graph = {};
+		
+		var forceLayout;
+		var isProfiled = false; // true if profiling information available
+		var useProfileColors = false;
+		var fixOnInit = true; // fix nodes on initialization
+		var maxProfilePer = 0;
+		var profileColors = ["#fff5f0","#fee0d2","#fcbba1","#fc9272","#fb6a4a","#ef3b2c","#cb181d","#a50f15"];
+		var pad = 10;
+		var isEditNode = false; // true if node is edited
+		var menuItems = [
+			{
+				title: 'Edit',
+				action: function(elm, d, i) { editNode(elm, d); }
+			},
+			{
+				title: 'Release',
+				action: function(elm, d, i) { releaseNode(d); }
+			}
+		];
+
+		// Create main panel
+		d3.select('body').select('svg').remove();
+		var svg = d3.select('body').append('svg')
+			.attr('width', '100%')
+			.attr('height', '95%');
+		var pane = svg.append('g');
+		
+		// Zoom behaviour
+		var zoom = d3.behavior.zoom()
+			.scaleExtent([0.2, 8])
+			.on('zoom', function(d) {
+				var trans = d3.event.translate;
+				trans[0] += 300;
+				trans[1] += 100;
+				pane.attr('transform', 'translate(' + trans + ') scale(' + d3.event.scale + ')');
+			});
+		svg.call(zoom);
+		zoom.event(svg);
+		svg.on("dblclick.zoom", null);
+		
+		// Edges
+		var edgeDiv = d3.select('body').append('div')
+			.attr('class', 'edgeTooltip')
+			.style('opacity', 0.0);
+		
+		// Div for node details	
+		var nodeInfo = d3.select('body').append('div')
+			.attr('class', 'nodeInfo')
+			.style('opacity', 0.0);
+		
+		// Definition head of edges
+		var markerData = [
+			{'id': 'n', 'color': 'black'},
+			{'id': 'r', 'color': 'red'},
+			{'id': 'b', 'color': 'dodgerblue'}];
+		svg.append("defs").selectAll('marker').data(markerData).enter().append("marker")
+		    .attr("id", function(d) { return 'edgeArrow_' + d.id;})
+		    .attr("markerWidth", 4)
+		    .attr("markerHeight", 4)
+		    .attr("refX", 2)
+		    .attr("refY", 2)
+		    .attr("orient", "auto")
+		  	.append("path")
+		    .attr("d", "M0,0 L4,2 L0,4 Z")
+		    .attr('fill', function(d) { return d.color;});
+	
+		// Initialize graph
+		processDotGraph(dotGraph);		
+		graph = frontEndGraph(dotGraph);
+		drawGraph();
+	</script>
+</body>
+</html>

theano/d3viz/tests/data/test_d3viz/ofg/index.html

+<!DOCTYPE html>
+<html>
+<head>
+	<link rel="stylesheet" href="d3viz/css/d3viz.css"/>
+	<link rel="stylesheet" href="d3viz/css/d3-context-menu.css"/>
+	<script type="text/javascript" src="d3viz/js/d3viz.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3.v3.min.js"></script>
+	<script type="text/javascript" src="d3viz/js/dagre-d3.js"></script>
+	<script type="text/javascript" src="d3viz/js/graphlib-dot.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3-context-menu.js"></script>
+</head>
+<body>
+	<div id='menu' class='menuBar'>
+	    <input name="resetNodes" 
+	           type="button" 
+	           value="Reset nodes"
+	           onclick="resetNodes()"/>
+	    <input name="releaseNodes" 
+	           type="button" 
+	           value="Release nodes"
+	           onclick="releaseNodes()"/>
+	</div>
+
+	<script type="text/javascript">
+		// Backend graph in DOT format
+		var dotGraph = graphlibDot.read("digraph G {	graph [bb=\"0,0,877.01,316\"];	node [label=\"\N\"];	subgraph cluster_n1 {		graph [bb=\"413.01,80,637.01,308\"];		n11		 [apply_op=Elemwise,			fillcolor=\"#FFAABB\",			height=0.5,			label=Elemwise,			node_type=apply,			pos=\"510.01,194\",			shape=ellipse,			style=filled,			type=colored,			width=1.2888];		n15		 [dtype=fscalar,			fillcolor=dodgerblue,			height=0.5,			label=fscalar,			node_type=output,			pos=\"510.01,106\",			shape=box,			style=filled,			width=0.75];		n11 -> n15		 [label=fscalar,			lp=\"529.01,150\",			pos=\"e,510.01,124.08 510.01,175.6 510.01,163.75 510.01,147.82 510.01,134.29\"];		n12		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=z,			node_type=input,			pos=\"592.01,282\",			shape=box,			style=filled,			width=0.75];		n12 -> n11		 [label=\"0 fscalar\",			lp=\"596.01,238\",			pos=\"e,534.12,209.56 583.05,263.78 577.09,253.31 568.62,240.07 559.01,230 554.11,224.87 548.36,220 542.56,215.61\"];		n13		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=x,			node_type=input,			pos=\"520.01,282\",			shape=box,			style=filled,			width=0.75];		n13 -> n11		 [label=\"1 fscalar\",			lp=\"535.01,238\",			pos=\"e,509.36,212.08 514.71,263.71 513.23,258.11 511.8,251.84 511.01,246 509.95,238.28 509.51,229.84 509.37,222.09\"];		n14		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=y,			node_type=input,			pos=\"448.01,282\",			shape=box,			style=filled,			width=0.75];		n14 -> n11		 [label=\"2 fscalar\",			lp=\"482.01,238\",			pos=\"e,481.77,208.39 448.14,263.68 448.97,253.17 451.42,239.92 458.01,230 462.06,223.89 467.58,218.57 473.52,214.05\"];	}	subgraph cluster_n7 {		graph [bb=\"645.01,80,869.01,308\"];		n71		 [apply_op=Elemwise,			fillcolor=\"#FFAABB\",			height=0.5,			label=Elemwise,			node_type=apply,			pos=\"742.01,194\",			shape=ellipse,			style=filled,			type=colored,			width=1.2888];		n75		 [dtype=fscalar,			fillcolor=dodgerblue,			height=0.5,			label=fscalar,			node_type=output,			pos=\"742.01,106\",			shape=box,			style=filled,			width=0.75];		n71 -> n75		 [label=fscalar,			lp=\"761.01,150\",			pos=\"e,742.01,124.08 742.01,175.6 742.01,163.75 742.01,147.82 742.01,134.29\"];		n72		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=z,			node_type=input,			pos=\"824.01,282\",			shape=box,			style=filled,			width=0.75];		n72 -> n71		 [label=\"0 fscalar\",			lp=\"828.01,238\",			pos=\"e,766.12,209.56 815.05,263.78 809.09,253.31 800.62,240.07 791.01,230 786.11,224.87 780.36,220 774.56,215.61\"];		n73		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=x,			node_type=input,			pos=\"752.01,282\",			shape=box,			style=filled,			width=0.75];		n73 -> n71		 [label=\"1 fscalar\",			lp=\"767.01,238\",			pos=\"e,741.36,212.08 746.71,263.71 745.23,258.11 743.8,251.84 743.01,246 741.95,238.28 741.51,229.84 741.37,222.09\"];		n74		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=y,			node_type=input,			pos=\"680.01,282\",			shape=box,			style=filled,			width=0.75];		n74 -> n71		 [label=\"2 fscalar\",			lp=\"714.01,238\",			pos=\"e,713.77,208.39 680.14,263.68 680.97,253.17 683.42,239.92 690.01,230 694.06,223.89 699.58,218.57 705.52,214.05\"];	}	n1	 [apply_op=OpFromGraph,		height=0.5,		label=OpFromGraph,		node_type=apply,		pos=\"217.01,194\",		shape=ellipse,		subg=cluster_n1,		subg_map_inputs=\"[[\'n2\', \'n13\'], [\'n3\', \'n14\'], [\'n4\', \'n12\']]\",		subg_map_outputs=\"[[\'n15\', \'n6\']]\",		width=1.7826];	n6	 [apply_op=Elemwise,		fillcolor=\"#FFAABB\",		height=0.5,		label=Elemwise,		node_type=apply,		pos=\"153.01,106\",		shape=ellipse,		style=filled,		type=colored,		width=1.2888];	n1 -> n6	 [label=\"1 fscalar\",		lp=\"215.01,150\",		pos=\"e,165.19,123.37 204.36,176.01 194.95,163.36 181.96,145.9 171.4,131.71\"];	n2	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=z,		node_type=input,		pos=\"55.007,282\",		shape=box,		style=filled,		width=0.75];	n2 -> n1	 [label=\"0 fscalar\",		lp=\"175.01,238\",		pos=\"e,188.78,210.26 82.101,266.93 94.312,260.57 108.9,252.94 122.01,246 141.17,235.85 162.43,224.45 179.98,215\"];	n7	 [apply_op=OpFromGraph,		height=0.5,		label=OpFromGraph,		node_type=apply,		pos=\"70.007,194\",		shape=ellipse,		subg=cluster_n7,		subg_map_inputs=\"[[\'n4\', \'n73\'], [\'n3\', \'n74\'], [\'n2\', \'n72\']]\",		subg_map_outputs=\"[[\'n75\', \'n6\']]\",		width=1.7826];	n2 -> n7	 [label=\"2 fscalar\",		lp=\"27.007,238\",		pos=\"e,28.697,207.85 27.721,268.8 10.72,259.37 -6.2971,245.36 3.007,230 7.1667,223.13 13.164,217.55 19.883,213.03\"];	n3	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=y,		node_type=input,		pos=\"304.01,282\",		shape=box,		style=filled,		width=0.75];	n3 -> n1	 [label=\"1 fscalar\",		lp=\"363.01,238\",		pos=\"e,279.27,198.73 325,263.94 334.94,253.78 343.06,240.79 335.01,230 323.95,215.19 306.9,206.39 289.16,201.24\"];	n3 -> n7	 [label=\"1 fscalar\",		lp=\"304.01,238\",		pos=\"e,116.87,206.31 294.23,263.96 286.68,252.44 275.15,237.94 261.01,230 215.13,204.25 195.68,221.9 144.01,212 138.37,210.92 132.5,209.72 \126.66,208.46\"];	n4	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=x,		node_type=input,		pos=\"197.01,282\",		shape=box,		style=filled,		width=0.75];	n4 -> n1	 [label=\"2 fscalar\",		lp=\"233.01,238\",		pos=\"e,213.03,212.08 201.05,263.6 203.84,251.63 207.59,235.5 210.75,221.89\"];	n4 -> n7	 [label=\"0 fscalar\",		lp=\"98.007,238\",		pos=\"e,66.731,212.43 169.97,281.61 141.33,280.65 97.14,274.26 74.007,246 68.707,239.52 66.766,230.91 66.43,222.6\"];	n7 -> n6	 [color=red,		label=\"0 fscalar\",		lp=\"143.01,150\",		pos=\"e,137.33,123.24 86.01,176.42 98.606,163.37 116.32,145.01 130.37,130.46\"];	n9	 [dtype=fscalar,		fillcolor=dodgerblue,		height=0.5,		label=fscalar,		node_type=output,		pos=\"153.01,18\",		shape=box,		style=filled,		width=0.75];	n6 -> n9	 [label=fscalar,		lp=\"172.01,62\",		pos=\"e,153.01,36.084 153.01,87.597 153.01,75.746 153.01,59.817 153.01,46.292\"];}");
+		// Frontend graph for visualization
+		var graph = {};
+		
+		var forceLayout;
+		var isProfiled = false; // true if profiling information available
+		var useProfileColors = false;
+		var fixOnInit = true; // fix nodes on initialization
+		var maxProfilePer = 0;
+		var profileColors = ["#fff5f0","#fee0d2","#fcbba1","#fc9272","#fb6a4a","#ef3b2c","#cb181d","#a50f15"];
+		var pad = 10;
+		var isEditNode = false; // true if node is edited
+		var menuItems = [
+			{
+				title: 'Edit',
+				action: function(elm, d, i) { editNode(elm, d); }
+			},
+			{
+				title: 'Release',
+				action: function(elm, d, i) { releaseNode(d); }
+			}
+		];
+
+		// Create main panel
+		d3.select('body').select('svg').remove();
+		var svg = d3.select('body').append('svg')
+			.attr('width', '100%')
+			.attr('height', '95%');
+		var pane = svg.append('g');
+		
+		// Zoom behaviour
+		var zoom = d3.behavior.zoom()
+			.scaleExtent([0.2, 8])
+			.on('zoom', function(d) {
+				var trans = d3.event.translate;
+				trans[0] += 300;
+				trans[1] += 100;
+				pane.attr('transform', 'translate(' + trans + ') scale(' + d3.event.scale + ')');
+			});
+		svg.call(zoom);
+		zoom.event(svg);
+		svg.on("dblclick.zoom", null);
+		
+		// Edges
+		var edgeDiv = d3.select('body').append('div')
+			.attr('class', 'edgeTooltip')
+			.style('opacity', 0.0);
+		
+		// Div for node details	
+		var nodeInfo = d3.select('body').append('div')
+			.attr('class', 'nodeInfo')
+			.style('opacity', 0.0);
+		
+		// Definition head of edges
+		var markerData = [
+			{'id': 'n', 'color': 'black'},
+			{'id': 'r', 'color': 'red'},
+			{'id': 'b', 'color': 'dodgerblue'}];
+		svg.append("defs").selectAll('marker').data(markerData).enter().append("marker")
+		    .attr("id", function(d) { return 'edgeArrow_' + d.id;})
+		    .attr("markerWidth", 4)
+		    .attr("markerHeight", 4)
+		    .attr("refX", 2)
+		    .attr("refY", 2)
+		    .attr("orient", "auto")
+		  	.append("path")
+		    .attr("d", "M0,0 L4,2 L0,4 Z")
+		    .attr('fill', function(d) { return d.color;});
+	
+		// Initialize graph
+		processDotGraph(dotGraph);		
+		graph = frontEndGraph(dotGraph);
+		drawGraph();
+	</script>
+</body>
+</html>

theano/d3viz/tests/data/test_d3viz/ofg_nested/index.html

+<!DOCTYPE html>
+<html>
+<head>
+	<link rel="stylesheet" href="d3viz/css/d3viz.css"/>
+	<link rel="stylesheet" href="d3viz/css/d3-context-menu.css"/>
+	<script type="text/javascript" src="d3viz/js/d3viz.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3.v3.min.js"></script>
+	<script type="text/javascript" src="d3viz/js/dagre-d3.js"></script>
+	<script type="text/javascript" src="d3viz/js/graphlib-dot.js"></script>
+	<script type="text/javascript" src="d3viz/js/d3-context-menu.js"></script>
+</head>
+<body>
+	<div id='menu' class='menuBar'>
+	    <input name="resetNodes" 
+	           type="button" 
+	           value="Reset nodes"
+	           onclick="resetNodes()"/>
+	    <input name="releaseNodes" 
+	           type="button" 
+	           value="Release nodes"
+	           onclick="releaseNodes()"/>
+	</div>
+
+	<script type="text/javascript">
+		// Backend graph in DOT format
+		var dotGraph = graphlibDot.read("digraph G {	graph [bb=\"0,0,636,340\"];	node [label=\"\N\"];	subgraph cluster_n1 {		graph [bb=\"251,8,628,332\"];		subgraph cluster_n11 {			graph [bb=\"467,96,620,324\"];			n111			 [apply_op=Elemwise,				fillcolor=\"#FFAABB\",				height=0.5,				label=Elemwise,				node_type=apply,				pos=\"544,210\",				shape=ellipse,				style=filled,				type=colored,				width=1.2888];			n114			 [dtype=fscalar,				fillcolor=dodgerblue,				height=0.5,				label=fscalar,				node_type=output,				pos=\"544,122\",				shape=box,				style=filled,				width=0.75];			n111 -> n114			 [label=fscalar,				lp=\"563,166\",				pos=\"e,544,140.08 544,191.6 544,179.75 544,163.82 544,150.29\"];			n112			 [dtype=fscalar,				fillcolor=limegreen,				height=0.5,				label=x,				node_type=input,				pos=\"574,298\",				shape=box,				style=filled,				width=0.75];			n112 -> n111			 [label=\"0 fscalar\",				lp=\"586,254\",				pos=\"e,549.96,228.08 567.93,279.6 563.75,267.63 558.13,251.5 553.38,237.89\"];			n113			 [dtype=fscalar,				fillcolor=limegreen,				height=0.5,				label=y,				node_type=input,				pos=\"502,298\",				shape=box,				style=filled,				width=0.75];			n113 -> n111			 [label=\"1 fscalar\",				lp=\"529,254\",				pos=\"e,521.37,226.05 499.83,279.65 499.3,269.38 499.99,256.39 505,246 507.26,241.31 510.46,236.96 514.07,233.04\"];		}		n11		 [apply_op=OpFromGraph,			height=0.5,			label=OpFromGraph,			node_type=apply,			pos=\"395,210\",			shape=ellipse,			subg=cluster_n11,			subg_map_inputs=\"[[\'n12\', \'n112\'], [\'n13\', \'n113\']]\",			subg_map_outputs=\"[[\'n114\', \'n15\']]\",			width=1.7826];		n15		 [apply_op=Elemwise,			fillcolor=\"#FFAABB\",			height=0.5,			label=Elemwise,			node_type=apply,			pos=\"345,122\",			shape=ellipse,			style=filled,			type=colored,			width=1.2888];		n11 -> n15		 [color=red,			label=\"0 fscalar\",			lp=\"399,166\",			pos=\"e,354.69,139.66 385.12,192.01 377.88,179.56 367.94,162.45 359.76,148.39\"];		n12		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=x,			node_type=input,			pos=\"404,298\",			shape=box,			style=filled,			width=0.75];		n12 -> n11		 [label=\"0 fscalar\",			lp=\"425,254\",			pos=\"e,396.79,228.08 402.18,279.6 400.94,267.75 399.27,251.82 397.86,238.29\"];		n13		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=y,			node_type=input,			pos=\"332,298\",			shape=box,			style=filled,			width=0.75];		n13 -> n11		 [label=\"1 fscalar\",			lp=\"371,254\",			pos=\"e,367.62,226.31 334.21,279.71 336.22,269.21 339.99,255.96 347,246 350.46,241.08 354.83,236.59 359.53,232.59\"];		n17		 [dtype=fscalar,			fillcolor=dodgerblue,			height=0.5,			label=fscalar,			node_type=output,			pos=\"345,34\",			shape=box,			style=filled,			width=0.75];		n15 -> n17		 [label=fscalar,			lp=\"364,78\",			pos=\"e,345,52.084 345,103.6 345,91.746 345,75.817 345,62.292\"];		n16		 [dtype=fscalar,			fillcolor=limegreen,			height=0.5,			label=z,			node_type=input,			pos=\"286,210\",			shape=box,			style=filled,			width=0.75];		n16 -> n15		 [label=\"1 fscalar\",			lp=\"338,166\",			pos=\"e,329.38,139.11 294.18,191.9 299.34,181.72 306.44,168.74 314,158 316.65,154.24 319.64,150.43 322.7,146.78\"];	}	n1	 [apply_op=OpFromGraph,		height=0.5,		label=OpFromGraph,		node_type=apply,		pos=\"136,210\",		shape=ellipse,		subg=cluster_n1,		subg_map_inputs=\"[[\'n2\', \'n12\'], [\'n3\', \'n13\'], [\'n4\', \'n16\']]\",		subg_map_outputs=\"[[\'n17\', \'n6\']]\",		width=1.7826];	n6	 [apply_op=Elemwise,		fillcolor=\"#FFAABB\",		height=0.5,		label=Elemwise,		node_type=apply,		pos=\"46,122\",		shape=ellipse,		style=filled,		type=colored,		width=1.2888];	n1 -> n6	 [color=red,		label=\"0 fscalar\",		lp=\"124,166\",		pos=\"e,62.691,138.95 118.65,192.42 104.9,179.28 85.538,160.78 70.258,146.18\"];	n2	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=x,		node_type=input,		pos=\"123,298\",		shape=box,		style=filled,		width=0.75];	n2 -> n1	 [label=\"0 fscalar\",		lp=\"149,254\",		pos=\"e,129.59,228.22 122.55,279.88 122.56,269.92 123.06,257.17 125,246 125.46,243.33 126.08,240.57 126.78,237.84\"];	n3	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=y,		node_type=input,		pos=\"195,298\",		shape=box,		style=filled,		width=0.75];	n3 -> n1	 [label=\"1 fscalar\",		lp=\"207,254\",		pos=\"e,155.98,227.13 189.48,279.56 185.74,269.26 180.18,256.27 173,246 170.17,241.96 166.82,238.01 163.3,234.32\"];	n4	 [dtype=fscalar,		fillcolor=limegreen,		height=0.5,		label=z,		node_type=input,		pos=\"29,298\",		shape=box,		style=filled,		width=0.75];	n4 -> n1	 [label=\"2 fscalar\",		lp=\"96,254\",		pos=\"e,103.61,225.73 40.803,279.98 48.767,269.34 59.985,255.82 72,246 78.91,240.35 86.866,235.16 94.768,230.6\"];	n4 -> n6	 [label=\"1 fscalar\",		lp=\"39,210\",		pos=\"e,36.126,139.61 23.104,279.76 16.772,258.84 8.4483,222.57 15,192 18.224,176.96 24.988,161.23 31.378,148.6\"];	n7	 [dtype=fscalar,		fillcolor=dodgerblue,		height=0.5,		label=fscalar,		node_type=output,		pos=\"46,34\",		shape=box,		style=filled,		width=0.75];	n6 -> n7	 [label=fscalar,		lp=\"65,78\",		pos=\"e,46,52.084 46,103.6 46,91.746 46,75.817 46,62.292\"];}");
+		// Frontend graph for visualization
+		var graph = {};
+		
+		var forceLayout;
+		var isProfiled = false; // true if profiling information available
+		var useProfileColors = false;
+		var fixOnInit = true; // fix nodes on initialization
+		var maxProfilePer = 0;
+		var profileColors = ["#fff5f0","#fee0d2","#fcbba1","#fc9272","#fb6a4a","#ef3b2c","#cb181d","#a50f15"];
+		var pad = 10;
+		var isEditNode = false; // true if node is edited
+		var menuItems = [
+			{
+				title: 'Edit',
+				action: function(elm, d, i) { editNode(elm, d); }
+			},
+			{
+				title: 'Release',
+				action: function(elm, d, i) { releaseNode(d); }
+			}
+		];
+
+		// Create main panel
+		d3.select('body').select('svg').remove();
+		var svg = d3.select('body').append('svg')
+			.attr('width', '100%')
+			.attr('height', '95%');
+		var pane = svg.append('g');
+		
+		// Zoom behaviour
+		var zoom = d3.behavior.zoom()
+			.scaleExtent([0.2, 8])
+			.on('zoom', function(d) {
+				var trans = d3.event.translate;
+				trans[0] += 300;
+				trans[1] += 100;
+				pane.attr('transform', 'translate(' + trans + ') scale(' + d3.event.scale + ')');
+			});
+		svg.call(zoom);
+		zoom.event(svg);
+		svg.on("dblclick.zoom", null);
+		
+		// Edges
+		var edgeDiv = d3.select('body').append('div')
+			.attr('class', 'edgeTooltip')
+			.style('opacity', 0.0);
+		
+		// Div for node details	
+		var nodeInfo = d3.select('body').append('div')
+			.attr('class', 'nodeInfo')
+			.style('opacity', 0.0);
+		
+		// Definition head of edges
+		var markerData = [
+			{'id': 'n', 'color': 'black'},
+			{'id': 'r', 'color': 'red'},
+			{'id': 'b', 'color': 'dodgerblue'}];
+		svg.append("defs").selectAll('marker').data(markerData).enter().append("marker")
+		    .attr("id", function(d) { return 'edgeArrow_' + d.id;})
+		    .attr("markerWidth", 4)
+		    .attr("markerHeight", 4)
+		    .attr("refX", 2)
+		    .attr("refY", 2)
+		    .attr("orient", "auto")
+		  	.append("path")
+		    .attr("d", "M0,0 L4,2 L0,4 Z")
+		    .attr('fill', function(d) { return d.color;});
+	
+		// Initialize graph
+		processDotGraph(dotGraph);		
+		graph = frontEndGraph(dotGraph);
+		drawGraph();
+	</script>
+</body>
+</html>

theano/d3viz/tests/models.py

@@ -7,9 +7,11 @@ import theano.tensor as T
 class Mlp(object):
 
     def __init__(self, nfeatures=100, noutputs=10, nhiddens=50, rng=None):
+        if rng is None:
+            rng = 0
+        if isinstance(rng, int):
+            rng = np.random.RandomState(rng)
         self.rng = rng
-        if self.rng is None:
-            self.rng = np.random.RandomState(0)
         self.nfeatures = nfeatures
         self.noutputs = noutputs
         self.nhiddens = nhiddens

theano/d3viz/tests/test_d3viz.py

 import numpy as np
 import os.path as pt
-from tempfile import mkstemp
+import tempfile
 import unittest
+import filecmp
+import sys
 
 import theano as th
 import theano.d3viz as d3v
@@ -12,19 +14,25 @@ class TestD3Viz(unittest.TestCase):
 
     def setUp(self):
         self.rng = np.random.RandomState(0)
+        self.data_dir = pt.join('data', 'test_d3viz')
 
-    def check(self, f):
-        _, html_file = mkstemp('.html')
+    def check(self, f, reference=None, verbose=False):
+        tmp_dir = tempfile.mkdtemp()
+        html_file = pt.join(tmp_dir, 'index.html')
+        if verbose:
+            print(html_file)
         d3v.d3viz(f, html_file)
         assert pt.getsize(html_file) > 0
+        if reference:
+            assert filecmp.cmp(html_file, reference)
 
     def test_mlp(self):
-        m = models.Mlp(rng=self.rng)
+        m = models.Mlp()
         f = th.function(m.inputs, m.outputs)
-        self.check(f)
+        self.check(f, pt.join(self.data_dir, 'mlp', 'index.html'))
 
     def test_mlp_profiled(self):
-        m = models.Mlp(rng=self.rng)
+        m = models.Mlp()
         f = th.function(m.inputs, m.outputs, profile=True)
         x_val = self.rng.normal(0, 1, (1000, m.nfeatures))
         f(x_val)
@@ -33,9 +41,9 @@ class TestD3Viz(unittest.TestCase):
     def test_ofg(self):
         m = models.Ofg()
         f = th.function(m.inputs, m.outputs)
-        self.check(f)
+        self.check(f, pt.join(self.data_dir, 'ofg', 'index.html'))
 
     def test_ofg_nested(self):
         m = models.OfgNested()
         f = th.function(m.inputs, m.outputs)
-        self.check(f)
+        self.check(f, pt.join(self.data_dir, 'ofg_nested', 'index.html'))

theano/d3viz/tests/test_formatting.py

@@ -14,7 +14,7 @@ class TestPyDotFormatter(unittest.TestCase):
     def node_counts(self, graph):
         node_types = [node.get_attributes()['node_type']
                       for node in graph.get_nodes()]
-        a, b  = np.unique(node_types, return_counts=True)
+        a, b = np.unique(node_types, return_counts=True)
         nc = dict(zip(a, b))
         return nc