Pairwise

API reference for sovai.extensions.pairwise

Module: sovai.extensions.pairwise

Functions

estimate_rank()

def estimate_rank(tensor_data, explained_var_threshold = 0.95)

Estimate rank for each mode based on explained variance.

Parameters

Parameter	Type	Description
tensor_data	—	—
explained_var_threshold	—	Default: 0.95

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relative_distance_calc()

def relative_distance_calc(
    df_factors,
    orient = 'cross-sectional',
    on = 'date',
    distance = 'cosine',
    metric = 'pearson',
    calculations = ['mean'],
)

Calculates the relative distance matrix based on the initial distance calculation and then computes the bar S matrix.

Parameters

Parameter	Type	Description
df_factors	—	DataFrame containing the data.
orient	—	Orientation for the initial distance calculation.
on	—	The level to group on ('ticker' or 'date').
distance	—	The distance metric to use ('cosine', 'euclidean', etc.).
metric	—	The metric to use for time-series distance calculation.
calculations	—	List of calculations to perform in distance_cross.

Returns

: DataFrame representing the normalized bar S matrix.

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