seo提升排名技巧,东莞百度搜索排名优化,微信个人小程序,东莞网站推广优化公司这是直方图为了生成这个图,我做了#xff1a;bins np.array([0.03, 0.3, 2, 100])plt.hist(m, bins bins, weightsnp.zeros_like(m) 1. / m.size)但是,正如您所注意到的,我想绘制每个数据点的相对频率的直方图,只有3个不同大小的区间#xff1a;bin1 0.03 – 0.3bin…这是直方图为了生成这个图,我做了bins np.array([0.03, 0.3, 2, 100])plt.hist(m, bins bins, weightsnp.zeros_like(m) 1. / m.size)但是,正如您所注意到的,我想绘制每个数据点的相对频率的直方图,只有3个不同大小的区间bin1 0.03 – 0.3bin2 0.3 – 2bin3 2 – 100由于最后一个bin的大小相对于其他bin非常大,因此直方图看起来很难看.如何修复直方图我想改变箱子的宽度,但我不想改变每个箱子的范围.[email protected],这不再是直方图,但你可以用plt.bar和np.histogram来做你想要的.然后,您只需将xticklabels设置为描述bin边缘的字符串.例如import numpy as npimport matplotlib.pyplot as pltbins [0.03,0.3,2,100] # your binsdata [0.04,0.07,0.1,0.2,0.2,0.8,1,1.5,4,5,7,8,43,45,54,56,99] # random datahist, bin_edges np.histogram(data,bins) # make the histogramfig,ax plt.subplots()# Plot the histogram heights against integers on the x axisax.bar(range(len(hist)),hist,width1)# Set the ticks to the middle of the barsax.set_xticks([0.5i for i,j in enumerate(hist)])# Set the xticklabels to a string that tells us what the bin edges wereax.set_xticklabels([{} - {}.format(bins[i],bins[i1]) for i,j in enumerate(hist)])plt.show()编辑如果您更新到matplotlib v1.5.0,您会发现该栏现在需要一个kwarg tick_label,这可以使这个绘图更容易(see here)hist, bin_edges np.histogram(data,bins)ax.bar(range(len(hist)),hist,width1,aligncenter,tick_label[{} - {}.format(bins[i],bins[i1]) for i,j in enumerate(hist)])
