mvpa2.clfs.stats.FixedNullDist

Inheritance diagram of FixedNullDist
class mvpa2.clfs.stats.FixedNullDist(dist, **kwargs)

Proxy/Adaptor class for SciPy distributions.

All distributions from SciPy’s ‘stats’ module can be used with this class.

Examples

>>> import numpy as np
>>> from scipy import stats
>>> from mvpa2.clfs.stats import FixedNullDist
>>>
>>> dist = FixedNullDist(stats.norm(loc=2, scale=4), tail='left')
>>> dist.p(2)
0.5
>>>
>>> dist.cdf(np.arange(5))
array([ 0.30853754,  0.40129367,  0.5       ,  0.59870633,  0.69146246])
>>>
>>> dist = FixedNullDist(stats.norm(loc=2, scale=4), tail='right')
>>> dist.p(np.arange(5))
array([ 0.69146246,  0.59870633,  0.5       ,  0.40129367,  0.30853754])

Attributes

descr Description of the object if any
tail

Methods

cdf(x) Return value of the cumulative distribution function at x.
dists() Implementations returns a sequence of the dist_class instances that were used to fit the distribution.
fit(measure, ds) Does nothing since the distribution is already fixed.
p(x[, return_tails]) Returns the p-value for values of x.
rcdf(x) Implementations return the value of the reverse cumulative distribution function.
reset()
Parameters:

dist : distribution object

This can be any object the has a cdf() method to report the cumulative distribition function values.

enable_ca : None or list of str

Names of the conditional attributes which should be enabled in addition to the default ones

disable_ca : None or list of str

Names of the conditional attributes which should be disabled

tail : {‘left’, ‘right’, ‘any’, ‘both’}

Which tail of the distribution to report. For ‘any’ and ‘both’ it chooses the tail it belongs to based on the comparison to p=0.5. In the case of ‘any’ significance is taken like in a one-tailed test.

descr : str

Description of the instance

Attributes

descr Description of the object if any
tail

Methods

cdf(x) Return value of the cumulative distribution function at x.
dists() Implementations returns a sequence of the dist_class instances that were used to fit the distribution.
fit(measure, ds) Does nothing since the distribution is already fixed.
p(x[, return_tails]) Returns the p-value for values of x.
rcdf(x) Implementations return the value of the reverse cumulative distribution function.
reset()
cdf(x)

Return value of the cumulative distribution function at x.

fit(measure, ds)

Does nothing since the distribution is already fixed.