import numpy as np
import matplotlib.pyplot as plt
# Evenly sampled time at 200ms intervals
t = np.arange(0.0, 5.0, 0.2)
# plot() can plot several lines in the same figure. To seperate the different lines
# from eachother, we may change the line style and format strings.
# See the plot() documentation for a complete list of line styles and format strings.
# The following lines have red dashes, blue squares and green triangles
plt.plot(t, t, 'r--', label='Linear line')
plt.plot(t, t**2, color='blue', linestyle='none', marker='s', label='Second degree polynom')
plt.plot(t, t**3, 'g^', label='Third degree polynom')
# To describe our plot even more detailed we can draw the labels we previously gave our lines using legend.
plt.legend(loc='upper left')
# The function axis() sets the axis sizes, and takes the argument [xmin, xmax, ymin, ymax]
plt.axis([0, 5, 0, 100])
plt.show() |