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📚 The CoCalc Library - books, templates and other resources

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def plot_logistic_regression_graph():

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    import graphviz

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    lr_graph = graphviz.Digraph(node_attr={'shape': 'circle', 'fixedsize': 'True'},

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                                graph_attr={'rankdir': 'LR', 'splines': 'line'})

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    inputs = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_0")

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    output = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_2")

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    for i in range(4):

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        inputs.node("x[%d]" % i, labelloc="c")

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    inputs.body.append('label = "inputs"')

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    inputs.body.append('color = "white"')

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    lr_graph.subgraph(inputs)

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    output.body.append('label = "output"')

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    output.body.append('color = "white"')

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    output.node("y")

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    lr_graph.subgraph(output)

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    for i in range(4):

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        lr_graph.edge("x[%d]" % i, "y", label="w[%d]" % i)

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    return lr_graph

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def plot_single_hidden_layer_graph():

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    import graphviz

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    nn_graph = graphviz.Digraph(node_attr={'shape': 'circle', 'fixedsize': 'True'},

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                                graph_attr={'rankdir': 'LR', 'splines': 'line'})

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    inputs = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_0")

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    hidden = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_1")

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    output = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_2")

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    for i in range(4):

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        inputs.node("x[%d]" % i)

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    inputs.body.append('label = "inputs"')

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    inputs.body.append('color = "white"')

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    hidden.body.append('label = "hidden layer"')

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    hidden.body.append('color = "white"')

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    for i in range(3):

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        hidden.node("h%d" % i, label="h[%d]" % i)

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    output.node("y")

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    output.body.append('label = "output"')

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    output.body.append('color = "white"')

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    nn_graph.subgraph(inputs)

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    nn_graph.subgraph(hidden)

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    nn_graph.subgraph(output)

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    for i in range(4):

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        for j in range(3):

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            nn_graph.edge("x[%d]" % i, "h%d" % j)

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    for i in range(3):

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        nn_graph.edge("h%d" % i, "y")

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    return nn_graph

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def plot_two_hidden_layer_graph():

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    import graphviz

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    nn_graph = graphviz.Digraph(node_attr={'shape': 'circle', 'fixedsize': 'True'},

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                                graph_attr={'rankdir': 'LR', 'splines': 'line'})

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    inputs = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_0")

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    hidden = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_1")

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    hidden2 = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_2")

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    output = graphviz.Digraph(node_attr={'shape': 'circle'}, name="cluster_3")

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    for i in range(4):

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        inputs.node("x[%d]" % i)

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    inputs.body.append('label = "inputs"')

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    inputs.body.append('color = "white"')

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    for i in range(3):

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        hidden.node("h1[%d]" % i)

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    for i in range(3):

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        hidden2.node("h2[%d]" % i)

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    hidden.body.append('label = "hidden layer 1"')

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    hidden.body.append('color = "white"')

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    hidden2.body.append('label = "hidden layer 2"')

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    hidden2.body.append('color = "white"')

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    output.node("y")

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    output.body.append('label = "output"')

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    output.body.append('color = "white"')

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    nn_graph.subgraph(inputs)

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    nn_graph.subgraph(hidden)

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    nn_graph.subgraph(hidden2)

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    nn_graph.subgraph(output)

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    for i in range(4):

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        for j in range(3):

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            nn_graph.edge("x[%d]" % i, "h1[%d]" % j, label="")

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    for i in range(3):

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        for j in range(3):

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            nn_graph.edge("h1[%d]" % i, "h2[%d]" % j, label="")

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    for i in range(3):

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        nn_graph.edge("h2[%d]" % i, "y", label="")

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    return nn_graph

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