how to create hyperlink in piechart_问答_开发者

I want to do a pie chart in matplotlib.

This pie chart will be a representation of two variables: male and female.

That's easy to do :)

What I would like to do next, I'm not even sure if it's possible to do with matplotlib, I would like to make these two variables clickable so if I click on male, I would see another page with information about this, same thing with female.

Image map isn't a solution since this variables may change in the future.

Anyone has any 开发者_如何学Goidea how to do this? If it's possible with matplotlib or what program would you recommend.

Thank you!

While it's not really in a workably stable state yet, have a look at the html5 canvas backend for matplotlib. It looks interesting, anyway, and will probably be the best way to do this sort of thing (interactive webpage with a matplotlib plot) in the future.

In the meantime, as @Mark suggested, it's not too hard to dynamically generate an imagemap for the wedges of a pie plot.

Here's a rough example, that I'm sure you could adapt to whatever web framework you're using.

import matplotlib.pyplot as plt

def main():
    # Make an example pie plot
    fig = plt.figure()
    ax = fig.add_subplot(111)

    labels = ['Beans', 'Squash', 'Corn']
    wedges, plt_labels = ax.pie([20, 40, 60], labels=labels)
    ax.axis('equal')

    make_image_map(fig, wedges, labels, 'temp.html')

def make_image_map(fig, wedges, labels, html_filename):
    """Makes an example static html page with a image map of a pie chart.."""
    #-- Save the figure as an image and get image size ------------------------
    # Be sure to explictly set the dpi when saving the figure
    im_filename = 'temp.png'
    fig.savefig(im_filename, dpi=fig.dpi)

    # Get figure size...
    _, _, fig_width, fig_height = fig.bbox.bounds

    #-- Get the coordinates of each wedge as a string of x1,y2,x2,y2... -------
    coords = []
    for wedge in wedges:
        xy = wedge.get_verts() 

        # Transform to pixel coords
        xy = fig.get_transform().transform(xy) 

        # Format into coord string and convert to <0,0> in top left...
        xy = ', '.join(['%0.2f,%0.2f' % (x, fig_height - y) for x, y in xy])
        coords.append(xy)

    #-- Build web page --------------------------------------------------------
    header = """
    <html>
    <body>
    <img src="{0}" alt="Pie Chart" usemap="#pie_map" width="{1}" height="{2}" />
    """.format(im_filename, fig_width, fig_height)

    # Make the image map
    map = '<map name="pie_map">\n'
    for label, xy in zip(labels, coords):
        href = 'http://images.google.com/images?q={0}'.format(label)
        area = '<area shape="poly" coords="{0}" href="{1}" alt="{2}" />'
        area = area.format(xy, href, label)
        map += '    ' + area + '\n'
    map += '</map>\n'

    footer = """
    </body>
    </html>"""

    # Write to a file...
    with file(html_filename, 'w') as outfile:
        outfile.write(header + map + footer)

if __name__ == '__main__':
    main()

Edit: I just realized that you might not be referring to embedding the plot into a web page... (I assumed that you were from the "display another page" bit in your question.) If you want more of a desktop app, without having to mess with a "full" gui toolkit, you can do something like this:

import matplotlib.pyplot as plt

def main():
    # Make an example pie plot
    fig = plt.figure()
    ax = fig.add_subplot(111)

    labels = ['Beans', 'Squash', 'Corn']
    wedges, plt_labels = ax.pie([20, 40, 60], labels=labels)
    ax.axis('equal')

    make_picker(fig, wedges)
    plt.show()

def make_picker(fig, wedges):
    import webbrowser
    def on_pick(event):
        wedge = event.artist
        label = wedge.get_label()
        webbrowser.open('http://images.google.com/images?q={0}'.format(label))

    # Make wedges selectable
    for wedge in wedges:
        wedge.set_picker(True)

    fig.canvas.mpl_connect('pick_event', on_pick)

if __name__ == '__main__':
    main()

Which opens a browser window for a google image search of whatever the wedge is labeled as...

You can do this with an imagemap or HTML element overlay controlled by JavaScript/jQuery.

Essentially, send your chart data to the page along with the chart image, and use JS to create the elements with the links according to the specification of the data.

It's a bit harder than the bar graphs I've done this to before, but should work fine.