algorithms.statistics.models.utils

Module: algorithms.statistics.models.utils

Inheritance diagram for nipy.algorithms.statistics.models.utils:

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General matrix and other utilities for statistics

Class

StepFunction

class nipy.algorithms.statistics.models.utils.StepFunction(x, y, ival=0.0, sorted=False)

Bases: object

A basic step function

Values at the ends are handled in the simplest way possible: everything to the left of x[0] is set to ival; everything to the right of x[-1] is set to y[-1].

Examples

>>> x = np.arange(20)
>>> y = np.arange(20)
>>> f = StepFunction(x, y)
>>>
>>> f(3.2)
3.0
>>> res = f([[3.2, 4.5],[24, -3.1]])
>>> np.all(res == [[ 3, 4],
...                [19, 0]])
True

__init__(x, y, ival=0.0, sorted=False)

Initialize self. See help(type(self)) for accurate signature.

Functions

nipy.algorithms.statistics.models.utils.ECDF(values)

Return the ECDF of an array as a step function.

nipy.algorithms.statistics.models.utils.mad(a, c=0.6745, axis=0)

Median Absolute Deviation:

median(abs(a - median(a))) / c

nipy.algorithms.statistics.models.utils.monotone_fn_inverter(fn, x, vectorized=True, **keywords)

Given a monotone function x (no checking is done to verify monotonicity) and a set of x values, return an linearly interpolated approximation to its inverse from its values on x.