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我使用 matplotlib 创建直方图。仍然存在我无法自行解决或借助互联网解决的问题。

  1. 如何更改某些垃圾箱的颜色？具体来说，我想用以下方法更改垃圾箱的颜色：a.) value bin < 1.15 red，b.) value 1.15 < bin < 1.25 c.) value > 1.25 red？

  2. 如何不仅用带 1 个小数的数字而且用 2 个小数标记 X 轴（现在根本没有绘制）？

    import matplotlib.pyplot as plt
import numpy as np
import csv

thickness = []  #gets thickness from list
bins = [1.00,1.01,1.02,1.03,1.04,1.05,1.06,1.07,1.08,1.09,1.10,1.11,1.12,1.13,1.14,1.15,1.16,1.17,1.18,1.19,1.20,1.21,1.22,1.23,1.24,1.25,1.26,1.27,1.28,1.29,1.30,1.31,1.32,1.33,1.34,1.35,1.36,1.37,1.38,1.39,1.40,1.41,1.42,1.43,1.44,1.45,1.46,1.47,1.48,1.49,1.50
] #set bins manuelly

with open('control.txt','r') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
    #x.append(float(row[0]))
    thickness.append(float(row[1]))

plt.hist(thickness, bins, align='left', histtype='bar', rwidth=0.8, color='green')

plt.xlabel('thickness [mm]')
plt.ylabel('frequency')
plt.title('Histogram')
plt.show()

请参见下面绘制的直方图：

到目前为止的 plt.histogram

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1 回答 1

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像这样的东西（可能有一些错误）：

import matplotlib.pyplot as plt
import numpy as np
import csv
from matplotlib.ticker import FormatStrFormatter


thickness = []  #gets thickness from list
bins = [1.00,1.01,1.02,1.03,1.04,1.05,1.06,1.07,1.08,1.09,1.10,1.11,1.12,1.13,1.14,1.15,1.16,1.17,1.18,1.19,1.20,1.21,1.22,1.23,1.24,1.25,1.26,1.27,1.28,1.29,1.30,1.31,1.32,1.33,1.34,1.35,1.36,1.37,1.38,1.39,1.40,1.41,1.42,1.43,1.44,1.45,1.46,1.47,1.48,1.49,1.50
] #set bins manuelly

with open('control.txt','r') as csvfile:
plots = csv.reader(csvfile, delimiter=',')
for row in plots:
    #x.append(float(row[0]))
    thickness.append(float(row[1]))

h,bins = plt.hist(thickness, bins)
plt.clf()
fig, ax = plt.subplots()
ax.bar(bins[bins<1.2],h[bins<1.2],rwidth=0.8, color='red')
plt.bar(bins[np.logical_and(bins>1.2,bins<1.5)],h[np.logical_and(bins>1.2,bins<1.5)],rwidth=0.8, color='green')
ax.bar(bins[bins>1.5],h[bins>1.5],rwidth=0.8, color='red')

ax.set_xlabel('thickness [mm]')

ax.set_ylabel('frequency')
ax.set_title('Histogram')

ax.yaxis.set_major_formatter(FormatStrFormatter('%.2f'))  
plt.show()
于 2016-08-11T10:05:15.903 回答