Modified lumfunc to include cumulative distributions #75
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astroML/lumfunc.py
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| @@ -98,7 +98,7 @@ def Cminus(x, y, xmax, ymax): | |||
| return Nx, Ny, cuml_x, cuml_y | |||
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| def binned_Cminus(x, y, xmax, ymax, xbins, ybins, normalize=False): | |||
| def binned_Cminus(x, y, xmax, ymax, xbins, ybins, normalize=False, get_cumulative=False): | |||
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Let's change get_cumulative to return_cumulative
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Looks good! Last thing we need is unit tests for the new functionality. |
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I didn't test the binned and bootstrapped functions separately since one builds on the other. I also didn't test the bootstrapped function with and without the "return_cumulative" param set to True, as whether it's true or false the output uses the same lines of code right up until the very last bit |
| # Find the interpolated midpoints for those same | ||
| # stated bin boundaries | ||
| Icumx_mid = _sorted_interpolate(x_sort, cuml_x, 0.5*(xbins[1:] + xbins[:-1])) | ||
| Icumy_mid = _sorted_interpolate(y_sort, cuml_y, 0.5*(xbins[1:] + ybins[:-1])) |
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should be ybins[1:] + ybins[:-1], yes?
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The cumulative distribution can be accessed by setting the parameter get_cumulative to True. It defaults to False so that it doesn't break any existing code that generates functions from the old lumfunc.py