在plt.hist

Question

我正在根据气候模型制作降水率的直方图，并且直方图功能起作用，但x轴让我感到非常轻微。我想在每个箱子之间直接打勾，比如2.55。然而，一些蜱被关闭，主要在左侧。有什么办法可以让它们正确对齐吗？

x = np.arange(0.006,0.0345,0.0015)
print (x)

#Make historical (1979-2015) histogram
plt.figure(figsize=(11,7))
plt.hist(histmeans, 19, color='#808080')

#labels & axes
#plt.locator_params(nbins=19, axis='x')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.title('Precip. Flux Anomaly (1979-2015 means, CanESM2 Hist)',fontsize=20)
plt.xlabel('Precip. Flux Mean (mm/day)',fontsize=15)
plt.ylabel('Number of Members',fontsize=15)
plt.xticks(x)
plt.xlim(0.006,0.0345)

print (np.min(histmeans))
print (np.max(histmeans))

输出：

[ 0.006   0.0075  0.009   0.0105  0.012   0.0135  0.015   0.0165  0.018
  0.0195  0.021   0.0225  0.024   0.0255  0.027   0.0285  0.03    0.0315
  0.033   0.0345]

0.00612598903444

0.0344927479091

Answer 1

plt.hist选择bins选项，它可以是整数（在脚本中），也可以是bin边缘列表。因此，您可以使用已定义为x的bin边缘范围作为此bins选项，以设置您感兴趣的精确bin边缘。

x = np.arange(0.006,0.0345,0.0015)
plt.hist(histmeans, bins = x, color='#808080')

这是一个完整的脚本：

import matplotlib.pyplot as plt
import numpy as np

# random data in your range
hmin,hmax = 0.00612598903444, 0.0344927479091
histmeans = hmin + np.random.rand(50)*(hmax-hmin)

x = np.arange(0.006,0.0345,0.0015)
print (x)

#Make historical (1979-2015) histogram
plt.figure(figsize=(11,7))
n,bins,edges = plt.hist(histmeans, x, color='#808080',edgecolor='k')

#Check bins
print bins

#labels & axes
#plt.locator_params(nbins=19, axis='x')
plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0))
plt.title('Precip. Flux Anomaly (1979-2015 means, CanESM2 Hist)',fontsize=20)
plt.xlabel('Precip. Flux Mean (mm/day)',fontsize=15)
plt.ylabel('Number of Members',fontsize=15)
plt.xticks(x)
plt.xlim(0.006,0.0345)

print (np.min(histmeans))
print (np.max(histmeans))


plt.show()

这是输出：

[ 0.006   0.0075  0.009   0.0105  0.012   0.0135  0.015   0.0165  0.018
  0.0195  0.021   0.0225  0.024   0.0255  0.027   0.0285  0.03    0.0315
  0.033   0.0345]
[ 0.006   0.0075  0.009   0.0105  0.012   0.0135  0.015   0.0165  0.018
  0.0195  0.021   0.0225  0.024   0.0255  0.027   0.0285  0.03    0.0315
  0.033   0.0345]
0.00661096260281
0.0341882193394