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.