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generate_graphs.py
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#!/usr/bin/env python3
import os
import webbrowser
import altair as alt
import pandas as pd
html_start = """
<!DOCTYPE html>
<head>
<meta charset="utf-8">
<script src="https://cdn.jsdelivr.net/npm/vega@5"></script>
<script src="https://cdn.jsdelivr.net/npm/vega-lite@3"></script>
<script src="https://cdn.jsdelivr.net/npm/vega-embed@4"></script>
<style>
body {font-family: Arial, Helvetica, sans-serif;}
.modal {
display: none;
position: fixed;
z-index: 1;
padding-top: 100px;
left: 0;
top: 0;
width: 100%;
height: 100%;
overflow: auto;
background-color: rgb(0,0,0);
background-color: rgba(0,0,0,0.4);
}
.modal-content {
background-color: #fefefe;
margin: auto;
padding: 20px;
border: 1px solid #888;
width: 80%;
}
.close {
color: #aaaaaa;
float: right;
font-size: 28px;
font-weight: bold;
}
.close:hover,
.close:focus {
color: #000;
text-decoration: none;
cursor: pointer;
}
.button {
background-color: #4CAF50; /* Green */
border: none;
color: white;
padding: 15px 32px;
text-align: center;
text-decoration: none;
display: inline-block;
font-size: 16px;
}
.grid-container {
display: grid;
grid-template-columns: auto auto auto auto auto auto;
padding: 10px;
grid-row-gap: 10px;
grid-column-gap: 10px;
}
.grid-item {
background-color: #4CAF50; /* Green */
border: none;
color: white;
padding: 15px 32px;
text-align: center;
text-decoration: none;
display: inline-block;
font-size: 16px;
}
h1 {
text-align:center;
}
.loader {
display: inline-block;
border: 16px solid #f3f3f3;
border-radius: 50%;
border-top: 16px solid #3498db;
width: 120px;
height: 120px;
-webkit-animation: spin 2s linear infinite; /* Safari */
animation: spin 2s linear infinite;
}
/* Safari */
@-webkit-keyframes spin {
0% { -webkit-transform: rotate(0deg); }
100% { -webkit-transform: rotate(360deg); }
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
</style>
</head>
<body>
"""
html_comparison_graph_template = """
<div id="vis_{class_name}" style="text-align:center;"> <div class="loader"></div> </div>
<script type="text/javascript">
var spec = "https://raw.githubusercontent.com/H00N24/PV251-Visualization-project/master/json/{class_name}.json";
vegaEmbed('#vis_{class_name}', spec).then(function(result) {{
}}).catch(console.error);
</script>
"""
html_graph_template = """
<div class="grid-item">
<button class="button" id="btn_{class_name}">{class_name}</button>
<div id="modal_{class_name}" class="modal">
<div class="modal-content" >
<div id="vis_{class_name}" style="text-align:center;"><div class="loader"></div> </div>
</div>
</div>
<script type="text/javascript">
var spec{id} = "https://raw.githubusercontent.com/H00N24/PV251-Visualization-project/master/json/dataset-{class_name}.json";
vegaEmbed('#vis_{class_name}', spec{id}).then(function(result) {{
}}).catch(console.error);
var modal{id} = document.getElementById("modal_{class_name}");
var btn{id} = document.getElementById("btn_{class_name}");
var opened_modal = null;
btn{id} .onclick = function() {{
modal{id}.style.display = "block";
opened_modal = modal{id};
}}
window.onclick = function(event) {{
if (event.target == opened_modal) {{
opened_modal.style.display = "None";
opened_modal = null;
}}
}}
</script>
</div>
"""
html_end = "</div></body>\n</html>"
results = pd.read_csv("data/classifiers-comparison.csv")
selection = alt.selection_multi(fields=["Classifier"])
domain = results["Classifier"].unique()
range_ = [
"#e6194b",
"#3cb44b",
"#4363d8",
"#f58231",
"#911eb4",
"#46f0f0",
"#f032e6",
"#bcf60c",
"#fabebe",
"#008080",
"#e6beff",
"#9a6324",
"#800000",
"#aaffc3",
"#808000",
"#000075",
]
scale = alt.Scale(domain=domain.tolist(), range=range_)
color = alt.condition(
selection,
alt.Color("Classifier:N", legend=None, scale=scale),
alt.value("lightgray"),
)
opacity = alt.condition(selection, alt.value(1), alt.value(0.2))
points = (
alt.Chart()
.mark_line(point=True)
.encode(
x=alt.X("Dataset"),
y=alt.Y("Test accuracy:Q", scale=alt.Scale(domain=(0, 1))),
color=color,
opacity=opacity,
tooltip=[
"Classifier:N",
alt.Text("Test accuracy:Q", title="Accuracy", format=".3f"),
"Dataset:N",
],
)
.add_selection(selection)
.properties(width=1000, height=300, title="Comparison of classifiers")
)
legend = (
alt.Chart()
.mark_point()
.encode(
y=alt.Y("Classifier:N", axis=alt.Axis(orient="right"), title=""), color=color
)
.add_selection(selection)
.properties(title="Classifier")
)
bars = (
alt.Chart()
.mark_bar()
.encode(
y=alt.Y(
"Classifier:N",
sort=alt.EncodingSortField(
field="Test accuracy", op="mean", order="descending"
),
title="",
),
color=color,
tooltip=[
"Classifier:N",
alt.Text(
"average(Test accuracy):Q", title="Average accuracy", format=".3f"
),
],
x=alt.X("average(Test accuracy):Q", scale=alt.Scale(domain=(0, 1))),
)
.add_selection(selection)
.properties(width=1000, height=200)
)
compare_chart = alt.vconcat(
alt.hconcat(points, legend, data=results), bars, data=results
)
# compare_chart.save("html/comparison.html")
compare_chart.save("json/comparison.json")
compare_chart_html = html_comparison_graph_template.format(class_name="comparison")
data_dir = "data"
data_files = [x for x in os.listdir(data_dir) if x != "classifiers-comparison.csv"]
chart_htmls = []
for index, data_file in enumerate(data_files):
dataframe = pd.read_csv(os.path.join(data_dir, data_file))
name = data_file.replace(".csv", "")
scale = alt.Scale(domain=(-0.1, 1.1))
selection = alt.selection_multi(fields=["Class"])
color = alt.condition(
selection,
alt.Color("Class:N", legend=None, scale=alt.Scale(range=range_)),
alt.value("lightgray"),
)
opacity = alt.condition(selection, alt.value(1), alt.value(0.2))
chart = (
alt.Chart(dataframe)
.mark_circle()
.encode(
x=alt.X("X:Q", title="", axis=alt.Axis(labels=False), scale=scale),
y=alt.X("Y:Q", title="", axis=alt.Axis(labels=False), scale=scale),
column=alt.Column("Method:N", title="Dataset: " + name),
color=color,
opacity=opacity,
tooltip=["Class:N"],
)
.add_selection(selection)
.interactive()
)
chart_htmls.append(html_graph_template.format(class_name=name, id=index))
# chart.save("html/dataset-" + name + ".html")
chart.save("json/dataset-" + name + ".json")
with open("index.html", "w") as html_file:
html_file.write(html_start)
html_file.write("<h1>Comparison of classifiers</h1>")
html_file.write(compare_chart_html)
html_file.write("<h1>Comparison of dimension reduction methods</h1>")
html_file.write('<div class="grid-container">\n')
for chart_html in chart_htmls:
html_file.write(chart_html)
html_file.write(html_end)
webbrowser.open_new_tab("index.html")