pyengnet package

Submodules

pyengnet.Dataset module

class pyengnet.Dataset.Dataset(filePath=None, data=None, gene=None, nmi_th=0.7, spearman_th=0.7, kendall_th=0.7, readded_th=0.7, hub_th=2, cores=1)

Bases: object

This class represents a Dataset model

property column_size

Number of columns of the dataset

property data

The dataset stored in memory.

property filePath

The path where the dataset file is stored.

property gene

Gene names list of the dataset stored in a numpy.array

property hub_threshold

Threshold to determine if the node studie is a hub. Set this threshold to -1 to run the algorithm with standard selection.

property kendall_threshold

Threshold for the Kendall classifier (Used in phase 1 of the EnGNet algorithm).

property ncores

Number of CPU cores used for parallelisation.

property nmi_threshold

Threshold for the NMI classifier (Used in phase 1 of the EnGNet algorithm).

property readded_edges_threshold

Threshold to determine if the edge would be return into the network after the pruning step

property row_size

Number of rows of the dataset

property spearman_threshold

Threshold for the Spearman classifier (Used in phase 1 of the EnGNet algorithm).

pyengnet.Engnet module

pyengnet.File module

pyengnet.Kendall module

pyengnet.NMI module

class pyengnet.NMI.NMI

Bases: object

NMI measurement class coded in a parallel ecosystem with CPUs.

static process(dataset, arr1, arr2)

Function that performs NMI’s measure for two genes.

Parameters

arr1: numpy.array

Array storing all the values of the dataset for a gene X.

arr2: numpy.array

Array storing all the values of the dataset for a gene Y.

Return : int, double

ans: int

This value indicates whether the calculated NMI’s coefficient is valid according to the threshold offered by the user. If this variable stores the value 1, it is valid, whereas it is invalid if the stored value is 0.

corr: double

NMI’s coefficient calculated.

pyengnet.Normalization module

class pyengnet.Normalization.Normalization

Bases: object

normalizedArray(genNormalized, size)

Function used by the NMI measure to normalise the values of a gene stored in a dataset.

Parameters

gen: array

Array representing the non-normalised values for a gene.

genNormalized: array

Array storing the normalised values

size: int

Number of values involved in normalisation.

pyengnet.Spearman module

pyengnet.version module

File to store the software version.

Module contents