matplotlib 如何将背景颜色从折线图添加到折线图的线段

zi8p0yeb  于 2023-10-24  发布在  其他
关注(0)|答案(1)|浏览(145)

我有一个框架如下，并希望得到一个情节与线和背景颜色要么红色或白色（取决于颜色的值_var）。

  1. line_var color_var
  2. datetime        
  3. 2023-04-20 13:45    3     1
  4. 2023-04-20 14:00    4     0
  5. 2023-04-20 15:00    5     0
  6. 2023-04-20 15:15    4     1
  7. 2023-04-20 15:45    3     1
  8. 2023-04-20 16:00    5     1
  9. 2023-04-20 16:45    6     0
  10. 2023-04-20 17:45    7     0
  11. 2023-04-20 18:00    5     0
  12. 2023-04-20 18:45    6     1
  13. 2023-04-20 19:45    8     1
  14. 2023-04-21 13:45    9     0

下面的代码

  1. import pandas as pd
  2. import numpy as np
  3. from matplotlib import dates as mdates
  4. from matplotlib.colors import ListedColormap
  5. import matplotlib.pyplot as plt
  7. df = pd.DataFrame({'datetime':['2023-04-20 13:45','2023-04-20 14:00','2023-04-20 15:00',
  8. '2023-04-20 15:15','2023-04-20 15:45','2023-04-20 16:00','2023-04-20 16:45','2023-04-20 17:45','2023-04-20 18:00','2023-04-20 18:45','2023-04-20 19:45','2023-04-21 13:45'],
  9. 'line_var':[3,4,5,4,3,5,6,7,5,6,8,9], 
  10. 'color_var':[1,0,0,1,1,1,0,0,0,1,1,0]})
  12. df = df.assign(datetime=pd.to_datetime(df.datetime))
  13. df = df.set_index('datetime')
  15. cmap = ListedColormap(['white','red'])
  17. fig = plt.figure(figsize=(50,10))
  18. ax = fig.add_subplot()
  20. ax.plot(df['line_var'])
  21. ax.set_xlabel('')
  23. plt.xticks(rotation = 30)
  24. ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
  26. #this gives an error
  27. ax.pcolor(df.index, ax.get_ylim(), 
  28.            df['color_var'].values[np.newaxis].T, 
  29.            cmap = cmap, alpha = 0.4, 
  30.            linewidth=0, antialiased=True, shading='nearest')
  31. plt.axhline(y = 0, color = 'black')
  32. plt.tight_layout()

抛出错误

  1. ---------------------------------------------------------------------------
  2. TypeError                                 Traceback (most recent call last)
  3. Cell In[21], line 21
  4.      18 ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
  5.      20 #this gives an error
  6. ---> 21 ax.pcolor(df.index, ax.get_ylim(), 
  7.      22            df['color_var'].values[np.newaxis].T, 
  8.      23            cmap = cmap, alpha = 0.4, 
  9.      24            linewidth=0, antialiased=True, shading='nearest')
  10.      25 plt.axhline(y = 0, color = 'black')
  11.      26 plt.tight_layout()
  13. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\__init__.py:1442, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs)
  14.    1439 @functools.wraps(func)
  15.    1440 def inner(ax, *args, data=None, **kwargs):
  16.    1441     if data is None:
  17. -> 1442         return func(ax, *map(sanitize_sequence, args), **kwargs)
  18.    1444     bound = new_sig.bind(ax, *args, **kwargs)
  19.    1445     auto_label = (bound.arguments.get(label_namer)
  20.    1446                   or bound.kwargs.get(label_namer))
  22. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_axes.py:5946, in Axes.pcolor(self, shading, alpha, norm, cmap, vmin, vmax, *args, **kwargs)
  23.    5944     shading = mpl.rcParams['pcolor.shading']
  24.    5945 shading = shading.lower()
  25. -> 5946 X, Y, C, shading = self._pcolorargs('pcolor', *args, shading=shading,
  26.    5947                                     kwargs=kwargs)
  27.    5948 Ny, Nx = X.shape
  28.    5950 # convert to MA, if necessary.
  30. File ~\anaconda3\envs\py11\Lib\site-packages\matplotlib\axes\_axes.py:5757, in Axes._pcolorargs(self, funcname, shading, *args, **kwargs)
  31.    5755 else:    # ['nearest', 'gouraud']:
  32.    5756     if (Nx, Ny) != (ncols, nrows):
  33. -> 5757         raise TypeError('Dimensions of C %s are incompatible with'
  34.    5758                         ' X (%d) and/or Y (%d); see help(%s)' % (
  35.    5759                             C.shape, Nx, Ny, funcname))
  36.    5760     if shading == 'nearest':
  37.    5761         # grid is specified at the center, so define corners
  38.    5762         # at the midpoints between the grid centers and then use the
  39.    5763         # flat algorithm.
  40.    5764         def _interp_grid(X):
  41.    5765             # helper for below
  43. TypeError: Dimensions of C (12, 1) are incompatible with X (12) and/or Y (2); see help(pcolor)

我在这里读到Numpy pcolormesh: TypeError: Dimensions of C are incompatible with X and/or Y，我应该转置我的数组，但它不起作用，或者我没有正确地这样做。

matplotlib

1条答案

按热度按时间
bn31dyow

bn31dyow1#

matplotlib的pcolor函数期望X、Y和C参数在特定的维度上，以在图中阴影区域。您遇到的问题是X、Y和C数组的维度不匹配。
当你为X提供df.index，为Y提供ax.get_ylim()时，你基本上是告诉pcolor考虑尺寸为（12，2）的矩形网格，因为df.index的长度为12，ax.get_ylim()的长度为2。
但是，df['color_var'].values[np.newaxis].T提供的C数组（颜色数据）的形状是（12，1），这与前面提到的网格不兼容。
解决这个问题的一种方法是将X和Y数组网格化以创建所需的网格，然后扩展C数组以匹配此网格的形状。

  1. import pandas as pd
  2. import numpy as np
  3. from matplotlib import dates as mdates
  4. from matplotlib.colors import ListedColormap
  5. import matplotlib.pyplot as plt
  7. df = pd.DataFrame({
  8.     'datetime': ['2023-04-20 13:45', '2023-04-20 14:00', '2023-04-20 15:00',
  9.                  '2023-04-20 15:15', '2023-04-20 15:45', '2023-04-20 16:00',
  10.                  '2023-04-20 16:45', '2023-04-20 17:45', '2023-04-20 18:00',
  11.                  '2023-04-20 18:45', '2023-04-20 19:45', '2023-04-21 13:45'],
  12.     'line_var': [3, 4, 5, 4, 3, 5, 6, 7, 5, 6, 8, 9],
  13.     'color_var': [1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0]
  14. })
  16. df = df.assign(datetime=pd.to_datetime(df.datetime))
  17. df = df.set_index('datetime')
  19. fig, ax = plt.subplots(figsize=(10, 6))
  21. # Plot the line
  22. ax.plot(df['line_var'], color='blue')
  24. # Fill background color based on color_var values
  25. for i in range(1, len(df)):
  26.     if df['color_var'].iloc[i] == 1:
  27.         ax.fill_between([df.index[i-1], df.index[i]], y1=ax.get_ylim()[0], y2=ax.get_ylim()[1], color='red', alpha=0.4)
  29. plt.xticks(rotation=30)
  30. ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
  31. plt.axhline(y=0, color='black')
  32. plt.tight_layout()
  33. plt.show()

更新：

  1. import pandas as pd
  2. import numpy as np
  3. from matplotlib import dates as mdates
  4. import matplotlib.pyplot as plt
  6. df = pd.DataFrame({
  7.     'datetime': ['2023-04-20 13:45', '2023-04-20 14:00', '2023-04-20 15:00',
  8.                  '2023-04-20 15:15', '2023-04-20 15:45', '2023-04-20 16:00',
  9.                  '2023-04-20 16:45', '2023-04-20 17:45', '2023-04-20 18:00',
  10.                  '2023-04-20 18:45', '2023-04-20 19:45', '2023-04-21 13:45'],
  11.     'line_var': [3, 4, 5, 4, 3, 5, 6, 7, 5, 6, 8, 9],
  12.     'color_var': [1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0]
  13. })
  15. df = df.assign(datetime=pd.to_datetime(df.datetime))
  16. df = df.set_index('datetime')
  18. fig, ax = plt.subplots(figsize=(10, 6))
  20. # Plot the line
  21. ax.plot(df['line_var'], color='blue')
  23. # Fill background color based on color_var values
  24. start_fill = None
  25. for i, (timestamp, value) in enumerate(df['color_var'].items()):
  26.     if value == 1 and start_fill is None:
  27.         start_fill = timestamp
  28.     elif value == 0 and start_fill is not None:
  29.         ax.fill_between([start_fill, timestamp], y1=ax.get_ylim()[0], y2=ax.get_ylim()[1], color='red', alpha=0.4)
  30.         start_fill = None
  32. # Handling the case if the last value in color_var is 1
  33. if start_fill is not None:
  34.     ax.fill_between([start_fill, df.index[-1]], y1=ax.get_ylim()[0], y2=ax.get_ylim()[1], color='red', alpha=0.4)
  36. plt.xticks(rotation=30)
  37. ax.xaxis.set_major_formatter(mdates.DateFormatter('%Y-%m-%d'))
  38. plt.axhline(y=0, color='black')
  39. plt.tight_layout()
  40. plt.show()

展开查看全部
赞(0）分享  回复(0）举报  2023-10-24
我来回答

相关问题

    查看更多

    热门标签

    更多
    JavaquerypythonNode开发语言requestUtil数据库Table后端算法LoggerMessageElementParser

    最新问答

    更多
    • 蜀ICP备13028337号-1 大数据知识库 https://www.saoniuhuo.com © All rights reserved
    • 本站内容来源互联网,如果侵犯您的权益请联系我们删除, 联系方式：448109455@qq.com