matplotlib之histograms

mac2022-06-30 89

直方图笔记

1. 画直方图。

# create 2x2 grid of axis subplots fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex=True) axs = [ax1,ax2,ax3,ax4] # draw n = 10, 100, 1000, and 10000 samples from the normal distribution and plot corresponding histograms for n in range(0,len(axs)): sample_size = 10**(n+1) sample = np.random.normal(loc=0.0, scale=1.0, size=sample_size) axs[n].hist(sample) axs[n].set_title('n={}'.format(sample_size))

2.设置hist的bin值

如何选择bin的数目。

http://users.stat.umn.edu/~gmeeden/papers/hist.pdf

# repeat with number of bins set to 100 fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots(2, 2, sharex=True) axs = [ax1,ax2,ax3,ax4] for n in range(0,len(axs)): sample_size = 10**(n+1) sample = np.random.normal(loc=0.0, scale=1.0, size=sample_size) axs[n].hist(sample, bins=100) axs[n].set_title('n={}'.format(sample_size))

直方图显示

plt.figure() Y = np.random.normal(loc=0.0, scale=1.0, size=10000) X = np.random.random(size=10000) plt.scatter(X,Y)

4.使用matplotlib.gridspec作图

# use gridspec to partition the figure into subplots import matplotlib.gridspec as gridspec plt.figure() gspec = gridspec.GridSpec(3, 3) top_histogram = plt.subplot(gspec[0, 1:]) side_histogram = plt.subplot(gspec[1:, 0]) lower_right = plt.subplot(gspec[1:, 1:])

5. hist的orientation设置。

Y = np.random.normal(loc=0.0, scale=1.0, size=10000) X = np.random.random(size=10000) lower_right.scatter(X, Y) top_histogram.hist(X, bins=100) s = side_histogram.hist(Y, bins=100, orientation='horizontal')

6. clear()函数

# clear the histograms and plot normed histograms top_histogram.clear() top_histogram.hist(X, bins=100, normed=True) side_histogram.clear() side_histogram.hist(Y, bins=100, orientation='horizontal', normed=True) # flip the side histogram's x axis side_histogram.invert_xaxis()

7.坐标范围限制

# change axes limits for ax in [top_histogram, lower_right]: ax.set_xlim(0, 1) for ax in [side_histogram, lower_right]: ax.set_ylim(-5, 5)

转载于:https://www.cnblogs.com/Shinered/p/9530290.html