Graphviz by Example: Part Two

My previous post introduced the dot language and how it can be utilized to create flowcharts. For part two, I sought to partially reproduce a more demanding visualization to highlight how Graphviz could be used. The original graphic was taken from the website for the Python scikit library and provide a quick reference guide on working with estimation procedures. It can be found here.

digraph Cheat_Sheet {
 
    graph [fontsize=10 fontname="Verdana" compound=true];
    node [shape=record fontsize=10 fontname="Verdana"];
 
    A1 [label="START", shape=box, fontcolor=black, color=Yellow, style=filled]; 
    A2 [label=">50\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A3 [label="get\nmore\ndata", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A4 [label="predicting a\ncategory", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A5 [label="predicting a\nquantity", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A6 [label="do you have\nlabeled\ndata", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A7 [label="just\nlooking", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A8 [label="predicting\nstructure", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
    A9 [label="tough\nluck", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
 
    A1 -> A2 [color=yellow];
    A2 -> A3 [color=red, fontcolor=red, label="NO", fontsize=10];
    A2 -> A4 [color=green, fontcolor=green, label="YES", fontsize=10];
    A4 -> A5 [color=red, fontcolor=red, label="NO", fontsize=10];
    A4 -> A6 [color=green, fontcolor=green, label="YES", fontsize=10];
    A5 -> A7 [color=red, fontcolor=red, label="NO", fontsize=10];
    A7 -> A8 [color=red, fontcolor=red, label="NO", fontsize=10];
    A8 -> A9 [color=yellow];
    A6 -> H [color=green, fontcolor=green, label="YES", fontsize=10];
    A6 -> P [color=red, fontcolor=red, label="NO", fontsize=10];
    A5 -> B [color=green, fontcolor=green, label="YES", fontsize=10];
    R -> A9 [color=red, fontcolor=red, label="NO", fontsize=10];
    A7 -> X [color=green, fontcolor=green, label="YES", fontsize=10];
 
    subgraph cluster_1 {
	label=<<B>regression</B>>;
        color=lightgrey;
        style=filled;
 
	B [label="<100k\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        C [label="SGD\nRegressor", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        D [label="few features\nshould be\nimportant", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        E [label="ElasticNet\nLasso", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        F [label="Ridge Regression\nSVR\n(kernel='linear')", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	G [label="SVR(kernel='rbf')\nEnsembleRegressors", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
 
	B -> C [color=red, fontcolor=red, label="NO", fontsize=10];
	B -> D [color=green, fontcolor=green, label="YES", fontsize=10];
	D -> E [color=green, fontcolor=green, label="YES", fontsize=10];
	D -> F [color=red, fontcolor=red, label="NO", fontsize=10];
	F -> G [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];
    }
 
    subgraph cluster_2 {
        label=<<B>classification</B>>;
        color=lightgrey;
        style=filled;
 
        H [label="<100k\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        I [label="SGD\nClassifier", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        J [label="Linear\nSVC", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        K [label="Text\nData", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        L [label="KNeighbors\nClassifier", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	M [label="Naive\nBayes", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	N [label="kernal\napproximation", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	O [label="SVC\nEnsemble\nClassifiers", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
 
	H -> I [color=red, fontcolor=red, label="NO", fontsize=10];
	H -> J [color=green, fontcolor=green, label="YES", fontsize=10];
	J -> K [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];
	I -> N [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];
	K -> M [color=green, fontcolor=green, label="YES", fontsize=10];
	K -> L [color=red, fontcolor=red, label="NO", fontsize=10];
	L -> O [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];       
    }
 
    subgraph cluster_3 {
        label=<<B>clustering</B>>;
        color=lightgrey;
        style=filled;
 
        P [label="number of\ncategories\nknown", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	Q [label="<10k\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        R [label="<10k\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        S [label="MeanShift\nVBGMM", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        T [label="MiniBatch\nKMeans", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	U [label="KMeans", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	V [label="Spectral\nClustering\nGMM", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
 
	P -> Q [color=green, fontcolor=green, label="YES", fontsize=10];
	P -> R [color=red, fontcolor=red, label="NO", fontsize=10];
	R -> S [color=green, fontcolor=green, label="YES", fontsize=10];
	Q -> U [color=green, fontcolor=green, label="YES", fontsize=10];
	Q -> T [color=red, fontcolor=red, label="NO", fontsize=10];
	U -> V [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];       
    }
 
    subgraph cluster_4 {
        label=<<B>dimensionality reduction</B>>;
        color=lightgrey;
        style=filled;
 
	W [label="<10k\nsamples", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        X [label="Randomized\nPCA", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        Y [label="Isomap\nSpectral\nEmbedding", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
        Z [label="kernel\napproximation", shape=box, fontcolor=black, color=cadetblue2, style=filled]; 
	AA [label="LLE", shape=box, fontcolor=black, color=cadetblue2, style=filled];
 
	X -> W [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];       
	W -> Y [color=green, fontcolor=green, label="YES", fontsize=10];
	W -> Z [color=red, fontcolor=red, label="NO", fontsize=10];
	Y -> AA [color=yellow, fontcolor=yellow, label="NOT\nWORKING", fontsize=10];       
    }
 
}

Blog_Graphviz.dot

 

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Graphviz by Example: Part One

Introduction
GraphViz is an open-source software package developed by AT&T Labs for generating directed graphs and flowcharts. Outputs are created using Dot, a plain text graph description language that is part of the Graphviz package. GraphViz is a powerful application that allows users to create appealing flowcharts without getting hung up on the layout or positioning of the nodes. Graphs in GraphViz are comprosed of nodes and edges (lines), and can be directed (lines with arrows) or undirected (lines without arrows). To create flowcharts with dot, the user must specify the type of graph, the name of the plot, and then define the terms of the graph within braces.

Basics
To generate visualizations using Graphviz, a user must create a dot source file and save it with a .dot extension. In the terminal, set the current working directory to the location of that file and launch dot by running ‘dot -T png -O file_name.dot’.

Example One:

graph name1 {
     Node1 [label="Node_1"];
}

blog_one.dot

Example Two:

digraph name1 { 
      Node1 [label="Node_1"];
      Node2 [label="Node_2"];
      Node1 -> Node2;
}

blog_two.dot

Example Three:

digraph name1 { 
     Node1 [label="Node_1"];
     Node2 [label="Node_2"];
     Node3 [label="Node_3"];
     Node1 -> Node2 -> Node3;
     Node1 -> Node3;
     Node2 -> Node1;
}

blog_three.dot

Example Four:

digraph name1 { 
   Node1 [label="Node_1"];
   Node2 [label="Node_2", shape=diamond];
   Node3 [label="Node_3", color=Blue, fontcolor=Navy, shape=box, style=filled, 
               color="#d3edea"]; 
   Node4 [label="Node_4"];
   Node1 -> Node2 -> Node3;
   Node1 -> Node3 [color=red, label="Best Choice", fontsize=10];
   Node2 -> Node1;
   Node2 -> Node4;
}

blog_four.dot