lib5c.operators.modeling module

class lib5c.operators.modeling.EmpiricalPvalueOperator

Bases: lib5c.operators.base.InteractionMatrixOperator

Operator for assigning empirical right-tail p-values to all interactions in an InteractionMatrix.

apply_inplace(target, **kwargs)

Transform the target InteractionMatrix, setting its interactions to their emprical right-tail p-values.

Parameters

• target (InteractionMatrix) – The InteractionMatrix object to transform.

• kwargs (other keyword arguments) – To be utilized by subclasses.

Returns

The transformed InteractionMatrix.

Return type

InteractionMatrix

Notes

This transformation uses the kind='strict' kwarg of scipy.stats.percentileofscore(), which means the resulting values represent the fraction of all the values that are greater than or equal to the value at that position.

Examples

>>> import numpy as np
>>> from lib5c.core.interactions import InteractionMatrix
>>> from lib5c.operators.modeling import EmpiricalPvalueOperator
>>> X = np.arange(16, dtype=float).reshape((4, 4))
>>> im = InteractionMatrix(X + X.T)
>>> print(im)
InteractionMatrix of size 4
[[ 0.  5. 10. 15.]
 [ 5. 10. 15. 20.]
 [10. 15. 20. 25.]
 [15. 20. 25. 30.]]
>>> epo = EmpiricalPvalueOperator()
>>> result = epo.apply(im)
>>> print(result)
InteractionMatrix of size 4
[[1.  0.9 0.8 0.6]
 [0.9 0.8 0.6 0.4]
 [0.8 0.6 0.4 0.2]
 [0.6 0.4 0.2 0.1]]
>>> result.print_log()
InteractionMatrix created
transformed to empirical p-values