>>> """
============
Contour Demo
============

Illustrate simple contour plotting, contours on an image with
a colorbar for the contours, and labelled contours.

See also the :doc:`contour image example
</gallery/images_contours_and_fields/contour_image>`.
"""
... 
... import numpy as np
... import matplotlib.cm as cm
... import matplotlib.pyplot as plt
... 
... 
... delta = 0.025
... x = np.arange(-3.0, 3.0, delta)
... y = np.arange(-2.0, 2.0, delta)
... X, Y = np.meshgrid(x, y)
... Z1 = np.exp(-X**2 - Y**2)
... Z2 = np.exp(-(X - 1)**2 - (Y - 1)**2)
... Z = (Z1 - Z2) * 2
... 
... ###############################################################################
... # Create a simple contour plot with labels using default colors.  The inline
... # argument to clabel will control whether the labels are draw over the line
... # segments of the contour, removing the lines beneath the label.
... 
... fig, ax = plt.subplots()
... CS = ax.contour(X, Y, Z)
... ax.clabel(CS, inline=True, fontsize=10)
... ax.set_title('Simplest default with labels')
... 
... ###############################################################################
... # Contour labels can be placed manually by providing list of positions (in data
... # coordinate).  See :doc:`/gallery/event_handling/ginput_manual_clabel_sgskip`
... # for interactive placement.
... 
... fig, ax = plt.subplots()
... CS = ax.contour(X, Y, Z)
... manual_locations = [
...     (-1, -1.4), (-0.62, -0.7), (-2, 0.5), (1.7, 1.2), (2.0, 1.4), (2.4, 1.7)]
... ax.clabel(CS, inline=True, fontsize=10, manual=manual_locations)
... ax.set_title('labels at selected locations')
... 
... ###############################################################################
... # You can force all the contours to be the same color.
... 
... fig, ax = plt.subplots()
... CS = ax.contour(X, Y, Z, 6, colors='k')  # Negative contours default to dashed.
... ax.clabel(CS, fontsize=9, inline=True)
... ax.set_title('Single color - negative contours dashed')
... 
... ###############################################################################
... # You can set negative contours to be solid instead of dashed:
... 
... plt.rcParams['contour.negative_linestyle'] = 'solid'
... fig, ax = plt.subplots()
... CS = ax.contour(X, Y, Z, 6, colors='k')  # Negative contours default to dashed.
... ax.clabel(CS, fontsize=9, inline=True)
... ax.set_title('Single color - negative contours solid')
... 
... ###############################################################################
... # And you can manually specify the colors of the contour
... 
... fig, ax = plt.subplots()
... CS = ax.contour(X, Y, Z, 6,
...                 linewidths=np.arange(.5, 4, .5),
...                 colors=('r', 'green', 'blue', (1, 1, 0), '#afeeee', '0.5'),
...                 )
... ax.clabel(CS, fontsize=9, inline=True)
... ax.set_title('Crazy lines')
... 
... ###############################################################################
... # Or you can use a colormap to specify the colors; the default
... # colormap will be used for the contour lines
... 
... fig, ax = plt.subplots()
... im = ax.imshow(Z, interpolation='bilinear', origin='lower',
...                cmap=cm.gray, extent=(-3, 3, -2, 2))
... levels = np.arange(-1.2, 1.6, 0.2)
... CS = ax.contour(Z, levels, origin='lower', cmap='flag', extend='both',
...                 linewidths=2, extent=(-3, 3, -2, 2))
... 
... # Thicken the zero contour.
... CS.collections[6].set_linewidth(4)
... 
... ax.clabel(CS, levels[1::2],  # label every second level
...           inline=True, fmt='%1.1f', fontsize=14)
... 
... # make a colorbar for the contour lines
... CB = fig.colorbar(CS, shrink=0.8)
... 
... ax.set_title('Lines with colorbar')
... 
... # We can still add a colorbar for the image, too.
... CBI = fig.colorbar(im, orientation='horizontal', shrink=0.8)
... 
... # This makes the original colorbar look a bit out of place,
... # so let's improve its position.
... 
... l, b, w, h = ax.get_position().bounds
... ll, bb, ww, hh = CB.ax.get_position().bounds
... CB.ax.set_position([ll, b + 0.1*h, ww, h*0.8])
... 
... plt.show()
... 
... #############################################################################
... #
... # .. admonition:: References
... #
... #    The use of the following functions, methods, classes and modules is shown
... #    in this example:
... #
... #    - `matplotlib.axes.Axes.contour` / `matplotlib.pyplot.contour`
... #    - `matplotlib.figure.Figure.colorbar` / `matplotlib.pyplot.colorbar`
... #    - `matplotlib.axes.Axes.clabel` / `matplotlib.pyplot.clabel`
... #    - `matplotlib.axes.Axes.get_position`
... #    - `matplotlib.axes.Axes.set_position`
...