halotools.utils.resample_x_to_match_y(x, y, bins, seed=None)[source] [edit on github]

Return the indices that resample x (with replacement) so that the resampled distribution matches the histogram of y. The returned indexing array will be sorted so that the i^th element of x[idx] is as close as possible to the i^th value of x, subject to the the constraint that x[idx] matches y.

x : ndarray

Numpy array of shape (nx, )

y : ndarray

Numpy array of shape (ny, )

bins : ndarray

Numpy array of shape (nbins, ) defining how the distribution y will be binned to evaluate its PDF.

seed : int, optional

Random number seed used to generate indices. Default is None for stochastic results.

indices : ndarray

Numpy array of shape (nx, )


>>> nx, ny = int(1e5), int(1e4)
>>> x = np.random.normal(loc=0, size=nx, scale=1)
>>> y = np.random.normal(loc=1, size=ny, scale=0.5)
>>> bins = np.linspace(-5, 5, 100)
>>> indices = resample_x_to_match_y(x, y, bins)
>>> rescaled_x = x[indices]