如何为 colorbar contourf matplotlib 设置刻度、颜色和标签的限制

How do I set limits on ticks, colors, and labels for colorbar contourf matplotlib

我有一个值的空间字段,我在一天中定期输出这些值。我正在用 contourf 绘图,我想在一天的数据过程中执行以下操作:

例如:

data = np.random.uniform(0, 5, size=(24,30,30))
data[3,:,:]=np.random.uniform(1,3,size=(30,30))  # example of bad plot
fgsize=(12,4)
numrecs = np.size(data,axis=0)
cbar_min = np.min(data)
cbar_max = np.max(data)
cbarlabels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), num=5, endpoint=True)


for tt in range(0, numrecs):
    plt.figure(figsize=fgsize, dpi=80)
    plt.title('this is a title')
    plt.contourf(data[tt, :, :], 35, vmin=cbar_min, vmax=cbar_max, cmap='coolwarm')
    cbar =plt.colorbar()
    cbar.set_ticks(cbarlabels)
    cbar.set_ticklabels(cbarlabels)
    cbar.set_label('my data has units')
    plt.show()
    plt.close()

这是 bad plot 的示例。颜色似乎有限,但颜色条改变了它的 color/label 限制。我该如何解决?

这是一个 good plot 的例子。

事实证明,contourf 在设置颜色图的级别时有点棘手,请参阅 this answer。您可以通过对轮廓进行归一化来获得适当的限制和颜色,如下所示:

import numpy as np
import matplotlib.pyplot as plt

data = np.random.uniform(0, 5, size=(24,30,30))
data[3,:,:]=np.random.uniform(1,3,size=(30,30))  # example of bad plot
fgsize=(12,4)
numrecs = np.size(data,axis=0)
cbar_min = np.min(data)
cbar_max = np.max(data)
cbarlabels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), num=5, endpoint=True)

# Set the normalisation for 35 levels (as in your example)
import matplotlib.colors as mc
levels = np.linspace(np.floor(cbar_min), np.ceil(cbar_max), 35) # to draw 35 levels
norm = mc.BoundaryNorm(levels, 256)

for tt in range(0, numrecs):
    print cbar_min, cbar_max
    plt.figure(figsize=fgsize, dpi=80)
    plt.title('this is a title')

    # Draw those levels, with proper normalisation, here:
    plt.contourf(data[tt, :, :], levels, vmin=cbar_min, vmax=cbar_max, cmap='coolwarm', levels=levels, norm=norm)

    cbar = plt.colorbar()
    cbar.set_ticks(cbarlabels)
    cbar.set_ticklabels(cbarlabels)
    cbar.set_label('my data has units')
    plt.show()