axis limits for scatter plot not holding in matplotlib

Question

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'$y$')

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?

Can you print the values of xLimHist and yLimHist and show how / where they are calculated? When I make my own contour plot and then overlay scatter points, your code works correctly. If I define xLimHist and yLimHist in such a way that it should exclude some of the scatter points, then the plot does indeed exclude those and it does not fit itself to contain all scatter points. So my guess is that you're defining xLimHist and yLimHist incorrectly. — ely
– ely, Commented Apr 24, 2012 at 3:27

sbraden · Accepted Answer · 2012-04-24 03:45:13Z

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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