散点图的轴限制未保存在matplotlib中 [英] axis limits for scatter plot not holding in matplotlib

问题描述

我正在尝试使用 matplotlib 将散点图叠加到等高线图上，其中包含

I am trying to overlay a scatter plot onto a contour plot using matplotlib, which contains

    plt.contourf(X, Y, XYprof.T, self.nLevels, extent=extentYPY, \
                 origin = 'lower')
    if self.doScatter == True and len(xyScatter['y']) != 0:
        plt.scatter(xyScatter['x'], xyScatter['y'], \
                    s=dSize, c=myColor, marker='.', edgecolor='none')
    plt.xlim(-xLimHist,  xLimHist)
    plt.ylim(-yLimHist, yLimHist)
    plt.xlabel(r'$x$')
    plt.ylabel(r'$y$')

最终发生的是，结果图扩展到包括所有散点，这些散点可能超过轮廓图的限制.有什么办法可以解决这个问题?

What ends up happening is the resulting plots extend to include all of the scatter points, which can exceed the limits for the contour plot. Is there any way to get around this?

推荐答案

我使用以下示例来尝试重现您的问题.如果保留默认值，x 和 y 的范围是 -3 到 3.我输入了 xlim 和 ylim，因此两者的范围都是 -2 到 2.它起作用了.

I used the following example to try and replicate your problem. If left to default, the range for x and y was -3 to 3. I input the xlim and ylim so the range for both was -2 to 2. It worked.

   import numpy as np
   import matplotlib.pyplot as plt
   from pylab import *

   # the random data
   x = np.random.randn(1000)
   y = np.random.randn(1000)

   fig = plt.figure(1, figsize=(5.5,5.5))

   X, Y = meshgrid(x, y)
   Z1 = bivariate_normal(X, Y, 1.0, 1.0, 0.0, 0.0)
   Z2 = bivariate_normal(X, Y, 1.5, 0.5, 1, 1)
   Z = 10 * (Z1 - Z2)

   origin = 'lower'
   CS = contourf(x, y, Z, 10, # [-1, -0.1, 0, 0.1],
                 cmap=cm.bone,
                 origin=origin)

   title('Nonsense')
   xlabel('x-stuff')
   ylabel('y-stuff')

   # the scatter plot:
   axScatter = plt.subplot(111)
   axScatter.scatter(x, y)

   # set axes range
   plt.xlim(-2, 2)
   plt.ylim(-2, 2)

   show()

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