python mpld3可视化mpld3.display()报错
print("网页显示开始*")
define custom toolbar location,网页动态可视化
class TopToolbar(mpld3.plugins.PluginBase):
"""Plugin for moving toolbar to top of figure"""
JAVASCRIPT = """
mpld3.register_plugin("toptoolbar", TopToolbar);
TopToolbar.prototype = Object.create(mpld3.Plugin.prototype);
TopToolbar.prototype.constructor = TopToolbar;
function TopToolbar(fig, props){
mpld3.Plugin.call(this, fig, props);
};
TopToolbar.prototype.draw = function(){
// the toolbar svg doesn't exist
// yet, so first draw it
this.fig.toolbar.draw();
// then change the y position to be
// at the top of the figure
this.fig.toolbar.toolbar.attr("x", 150);
this.fig.toolbar.toolbar.attr("y", 400);
// then remove the draw function,
// so that it is not called again
this.fig.toolbar.draw = function() {}
}
"""
def __init__(self):
self.dict_ = {"type": "toptoolbar"}
create data frame that has the result of the MDS plus the cluster numbers and titles
df = pd.DataFrame(dict(x=xs, y=ys, label=clusters, title=usernameList))
group by cluster
groups = df.groupby('label')
define custom css to format the font and to remove the axis labeling
css = """
text.mpld3-text, div.mpld3-tooltip {
font-family:Arial, Helvetica, sans-serif;
}
g.mpld3-xaxis, g.mpld3-yaxis {
display: none; }
"""
Plot
fig, ax = plt.subplots(figsize=(14, 6)) # set plot size
ax.margins(0.03) # Optional, just adds 5% padding to the autoscaling
iterate through groups to layer the plot
note that I use the cluster_name and cluster_color dicts with the 'name' lookup to return the appropriate color/label
for name, group in groups:
points = ax.plot(group.x, group.y, marker='o', linestyle='', ms=18, label=cluster_names[name], mec='none',
color=cluster_colors[name])
ax.set_aspect('auto')
labels = [i for i in group.title]
# set tooltip using points, labels and the already defined 'css'
tooltip = mpld3.plugins.PointHTMLTooltip(points[0], labels,
voffset=10, hoffset=10, css=css)
# connect tooltip to fig
mpld3.plugins.connect(fig, tooltip, TopToolbar())
# set tick marks as blank
ax.axes.get_xaxis().set_ticks([])
ax.axes.get_yaxis().set_ticks([])
# set axis as blank
ax.axes.get_xaxis().set_visible(False)
ax.axes.get_yaxis().set_visible(False)
ax.legend(numpoints=1) # show legend with only one dot
mpld3.display() # show the plot
uncomment the below to export to html
html = mpld3.fig_to_html(fig)
mpld3.save_html(fig,'clusters_dynamic.html')
print(html)
print("网页显示结束*")
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循环引用问题,已解决