AttributeError: object 'module' does not have attribute 'cm'

Question

I am using Python2.7. This is a feature of the Udacity Intro to Machine Learning course. When a function is called, a graph is displayed. However, suppose that colored areas are also shown, and they are not shown.

When I run a script that calls this function, a digit opens. When I close the shape, I see this message:

Traceback (most recent call last):
  File "your_algorithm.py", line 45, in <module>
    prettyPicture(clf, features_test, labels_test)
  File "e:\Projects\Udacity\Intro to Machine Learning\ud120-projects\choose_your_own\class_vis.py", line 22, in prettyPicture
    plt.pcolormesh(xx, yy, Z, cmap=pl.cm.seismic)
AttributeError: 'module' object has no attribute 'cm'

It seemed to me that cmis an attribute matplotlibfrom matplotlib cm . So I changed plto 'plt`. This eliminates the error message, but the colored areas are still not displayed in the plot. Thus, I am less convinced that this is correct.

Why are color areas not displayed?

Here is the prettyPicture function code:

import numpy as np
import matplotlib.pyplot as plt
import pylab as pl

def prettyPicture(clf, X_test, y_test):
    x_min = 0.0; x_max = 1.0
    y_min = 0.0; y_max = 1.0

    # Plot the decision boundary. For that, we will assign a color to each
    # point in the mesh [x_min, m_max]x[y_min, y_max].
    h = .01  # step size in the mesh
    xx, yy = np.meshgrid(np.arange(x_min, x_max, h), np.arange(y_min, y_max, h))
    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])

    # Put the result into a color plot
    Z = Z.reshape(xx.shape)
    plt.xlim(xx.min(), xx.max())
    plt.ylim(yy.min(), yy.max())

    plt.pcolormesh(xx, yy, Z, cmap=pl.cm.seismic)

    # Plot also the test points
    grade_sig = [X_test[ii][0] for ii in range(0, len(X_test)) if y_test[ii]==0]
    bumpy_sig = [X_test[ii][1] for ii in range(0, len(X_test)) if y_test[ii]==0]
    grade_bkg = [X_test[ii][0] for ii in range(0, len(X_test)) if y_test[ii]==1]
    bumpy_bkg = [X_test[ii][1] for ii in range(0, len(X_test)) if y_test[ii]==1]

    plt.scatter(grade_sig, bumpy_sig, color = "b", label="fast")
    plt.scatter(grade_bkg, bumpy_bkg, color = "r", label="slow")
    plt.legend()
    plt.xlabel("bumpiness")
    plt.ylabel("grade")

    plt.savefig("test.png")

Answer 1

cmap=pl.cm.seismic cmap=plt.cm.seismic

plt.savefig("your_image.png")

figure = plt.gcf()
plt.show()
plt.draw()
figure.savefig("your_image.png", dpi=100)