CS231n-机器学习中matplotlib绘图基础.md

绘制函数

import numpy as npimport matplotlib.pyplot as plt# Compute the x and y coordinates for points on a sine curvex = np.arange(0, 3 * np.pi, 0.1)y = np.sin(x)# Plot the points using matplotlibplt.plot(x, y)plt.show()  # You must call plt.show() to make graphics appear.

增强函数绘制

import numpy as npimport matplotlib.pyplot as plt# Compute the x and y coordinates for points on sine and cosine curvesx = np.arange(0, 3 * np.pi, 0.1)y_sin = np.sin(x)y_cos = np.cos(x)# Plot the points using matplotlibplt.plot(x, y_sin)plt.plot(x, y_cos)plt.xlabel('x axis label')plt.ylabel('y axis label')plt.title('Sine and Cosine')plt.legend(['Sine', 'Cosine'])plt.show()

多图绘制

import numpy as npimport matplotlib.pyplot as plt# Compute the x and y coordinates for points on sine and cosine curvesx = np.arange(0, 3 * np.pi, 0.1)y_sin = np.sin(x)y_cos = np.cos(x)# Set up a subplot grid that has height 2 and width 1,# and set the first such subplot as active.plt.subplot(2, 1, 1)# Make the first plotplt.plot(x, y_sin)plt.title('Sine')# Set the second subplot as active, and make the second plot.plt.subplot(2, 1, 2)plt.plot(x, y_cos)plt.title('Cosine')# Show the figure.plt.show()

import numpy as npfrom scipy.misc import imread, imresizeimport matplotlib.pyplot as pltimg = imread('assets/cat.jpg')img_tinted = img * [1, 0.95, 0.9]# Show the original imageplt.subplot(1, 2, 1)plt.imshow(img)# Show the tinted imageplt.subplot(1, 2, 2)# A slight gotcha with imshow is that it might give strange results# if presented with data that is not uint8. To work around this, we# explicitly cast the image to uint8 before displaying it.plt.imshow(np.uint8(img_tinted))plt.show()