11.11.3. astroML.lumfunc.bootstrap_Cminus¶
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astroML.lumfunc.bootstrap_Cminus(x, y, xmax, ymax, xbins, ybins, Nbootstraps=10, normalize=False)[source]¶ Compute the binned distributions using the Cminus method, with bootstrapped estimates of the errors
- Parameters
- xarray_like
array of x values
- yarray_like
array of y values
- xmaxarray_like
array of maximum x values for each y value
- ymaxarray_like
array of maximum y values for each x value
- xbinsarray_like
array of bin edges for the x function: size=Nbins_x + 1
- ybinsarray_like
array of bin edges for the y function: size=Nbins_y + 1
- Nbootstrapsint
number of bootstrap resamplings to perform
- normalizeboolean
if true, then returned distributions are normalized. Default is False.
- Returns
- dist_x, err_x, dist_y, err_yndarrays
distributions of size Nbins_x and Nbins_y