Matplotlib

matplotlib.pyplot

• from matplotlib import pyplot

matplotlib.pyplot.figure

member functions

• ax = matplotlib.pyplot.figure.add_subplot( ... ) - returns instance of matplotlib.axes.AxesSubplot

plot([1,2,3], [1,2,3], 'go-', label='line 1', linewidth=2)
plot([1,2,3], [1,4,9], 'rs',  label='line 2')
axis([0, 4, 0, 10])
legend()

import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.imshow(np.rot90(Z), cmap=plt.cm.gist_earth_r, extent=[xmin, xmax, ymin, ymax])
ax.plot(m1, m2, 'k.', markersize=2)
ax.set_xlim([xmin, xmax])
ax.set_ylim([ymin, ymax])
plt.show()

matplotlib.axes

matplotlib.axes.AxesSubplot

• call ax.plot and ax.hist(...) ... the ax instance is what you garnish
• 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)
• ax.grid(True)

matplotlib artist

• Three layers to the matplotlib API in matplotlib.backend_bases
  1. FigureCanvas = the area onto which the figure is drawn
  2. Renderer = the object which knows how to draw on the FigureCanvas
  3. Artist = the object that knows how to use a renderer to paint onto the canvas
• FigureCanvas and Renderer abstract away the lowlevel calls to toolkits (PostScript, PDF Gtk+, or wxPython)
• Artist handles high level constructs
• 2 types of artists
  • primitives: Line2D, Rectangle, Text, AxesImage
  • containers: Axis, Axes, Figure

1. Create Figure instance
2. Use figure to create one or more axes or subplot instances
3. Use Axes instance helper methods to create the primitives

numpy.mgrid

• Specify a start, stop and the number of steps in between (expressed in complex notation),and get an array with all the values in between
• np.mgrid[1:100:100j] -- yields a list of numbers from 1 to 100
• X, Y = np.mgrid[xmin:xmax:100j, ymin:ymax:100j]

numpy.ravel

• return a flattened array, i.e., turns a matrix into an array.
• can also specify ravelling order, row-major, column-major or otherwise