pygram11.var1dmw¶

pygram11.
var1dmw
(x, weights, bins, flow=False)[source]¶ Histogram data with multiple weight variations and variable width bins.
 Parameters
x (array_like) – data to histogram
bins (array_like) – bin edges
weights (array_like) – weight variations for the elements of
x
, first dimension is the shape ofx
, second dimension is the number of weights.density (bool) – normalize histogram bins as value of PDF such that the integral over the range is 1.
flow (bool) – if
True
the under and overflow bin contents are added to the first and last bins, respectively
 Returns
numpy.ndarray
– The bin counts.numpy.ndarray
– The standard error of each bin count, \(\sqrt{\sum_i w_i^2}\).
Examples
Using three different weight variations:
>>> x = np.random.randn(10000) >>> weights = np.abs(np.random.randn(x.shape[0], 3)) >>> bin_edges = [3.0, 2.5, 1.5, 0.25, 0.25, 2.0, 3.0] >>> h, err = var1dmw(x, weights, bin_edges) >>> h.shape (6, 3) >>> err.shape (6, 3)