adaptive_bins

adaptive split data into bins.

class AdaptiveBound(base_data, bins, base_bound=None)

Bases: object

adaptive bound cut for data value

static base_bound(data)

base bound for the data

get_bool_mask(data)

bool mask for splitting data

get_bound_patch(**kwargs)

get_bounds()

get split data bounds

get_bounds_data()

get split data bounds, and the data after splitting

static loop_split_bound(datas, n, base_bound=None)

loop for multi_split_bound, so n is list of list of int

static multi_split_bound(datas, n, base_bound=None)

multi data for single_split_bound, so n is list of int

>>> data = np.array([[1.0, 2.0, 1.4, 3.1], [2.0, 1.0, 3.0, 1.0]])
>>> bound, _ = AdaptiveBound.multi_split_bound(data, [2, 1])
>>> [(i[0][0]+1e-6, i[1][0]+1e-6) for i in bound]
[(1.0..., 1.7...), (1.7..., 3.1...)]

plot_bound(ax, **kwargs)

static single_split_bound(data, n=2, base_bound=None)

split data in the order of data value

>>> data = np.array([1.0, 2.0, 1.4, 3.1])
>>> AdaptiveBound.single_split_bound(data)
[(1.0, 1.7...), (1.7..., 3.1...)]

split_data(data)

split data, the shape is same as base_data

split_full_data(data, base_index=None)

split structure data, (TODO because large IO, the method is slow.)

adaptive_shape(m, bins, xmin, xmax)

binning_shape_function(m, bins)

cal_chi2(numbers, n_fp)