.. _user_interfaces-histogram_demo_canvasagg:

user_interfaces example code: histogram_demo_canvasagg.py
=========================================================

[`source code <histogram_demo_canvasagg.py>`_]

::

    """
    This is an example that shows you how to work directly with the agg
    figure canvas to create a figure using the pythonic API.
    
    In this example, the contents of the agg canvas are extracted to a
    string, which can in turn be passed off to PIL or put in a numeric
    array
    
    
    """
    from matplotlib.backends.backend_agg import FigureCanvasAgg
    from matplotlib.figure import Figure
    from matplotlib.mlab import normpdf
    from numpy.random import randn
    import numpy
    
    fig = Figure(figsize=(5, 4), dpi=100)
    ax = fig.add_subplot(111)
    
    canvas = FigureCanvasAgg(fig)
    
    mu, sigma = 100, 15
    x = mu + sigma*randn(10000)
    
    # the histogram of the data
    n, bins, patches = ax.hist(x, 50, normed=1)
    
    # add a 'best fit' line
    y = normpdf(bins, mu, sigma)
    line, = ax.plot(bins, y, 'r--')
    line.set_linewidth(1)
    
    ax.set_xlabel('Smarts')
    ax.set_ylabel('Probability')
    ax.set_title(r'$\mathrm{Histogram of IQ: }\mu=100, \sigma=15$')
    
    ax.set_xlim((40, 160))
    ax.set_ylim((0, 0.03))
    
    canvas.draw()
    
    s = canvas.tostring_rgb()  # save this and convert to bitmap as needed
    
    # get the figure dimensions for creating bitmaps or numpy arrays,
    # etc.
    l, b, w, h = fig.bbox.bounds
    w, h = int(w), int(h)
    
    if 0:
        # convert to a numpy array
        X = numpy.fromstring(s, numpy.uint8)
        X.shape = h, w, 3
    
    if 0:
        # pass off to PIL
        from PIL import Image
        im = Image.fromstring("RGB", (w, h), s)
        im.show()
    

Keywords: python, matplotlib, pylab, example, codex (see :ref:`how-to-search-examples`)