esat package#
Subpackages#
- esat.cli package
- esat.data package
- esat.error package
- esat.model package
- esat.rotational package
Submodules#
esat.configs module#
esat.metrics module#
Collection of metric functions which are used throughout the code base.
- esat.metrics.calculate_Q(residuals, uncertainty)#
- esat.metrics.q_factor(V, U, W, H)#
- esat.metrics.q_loss(V, U, W, H, uncertainty: bool = True)#
- esat.metrics.qr_loss(V, U, W, H, alpha=4.0)#
esat.utils module#
Collection of utility functions used throughout the code base.
- esat.utils.calculate_factor_correlation(factor1, factor2)#
- esat.utils.compare_all_factors(matrix1, matrix2)#
- esat.utils.memory_estimate(n_features, n_samples, factors, cores: int = None)#
Estimate the memory usage of the algorithm.
- Parameters:
n_features – Number of features.
n_samples – Number of samples.
factors – Number of factors.
- Returns:
Estimated memory usage in bytes.
- Return type:
int
- esat.utils.min_timestep(data: DataFrame)#
Find the minimum timestep in a dataframe.
- Parameters:
data – Dataframe to be searched.
- Returns:
Minimum timestep.
- Return type:
int
- esat.utils.np_encoder(object)#
Convert any numpy type to a generic type for json serialization.
- Parameters:
object – Object to be converted.
- Returns:
Generic object or an unchanged object if not a numpy type
- Return type:
object