flip.covariance.contraction¶
Attributes¶
Classes¶
Functions¶
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Module Contents¶
- flip.covariance.contraction.log¶
- class flip.covariance.contraction.Contraction(model_name=None, model_type=None, contraction_dict=None, coordinates_dict=None, basis_definition=None, endpoint_los_definition=None, variant=None)¶
- classmethod init_from_flip(model_name, model_type, power_spectrum_dict, coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type='rprt', additional_parameters_values=None, basis_definition='bisector', endpoint_los_definition='bisector', variant=None, **kwargs)¶
- property type¶
- The type function is used to determine the type of covariance model that will be computed.
- The options are:
- - velocity: The covariance model is computed for velocity only.
- - density: The covariance model is computed for density only.
- - density_velocity: The covariance model is computed for both velocity and density, without cross-term (i.e., the covariances between velocities and densities are zero). This option should be used when computing a full 3D tomography in which we want to compute a separate 1D tomography along each axis (x, y, z
- Parameters:
self – Represent the instance of the class
- Returns:
The type of the model
- compute_contraction_sum(parameter_values_dict)¶
- The compute_contraction_sum function computes the sum of all the contractions
for a given model type and parameter values.
- Parameters:
self – Make the function a method of the class
parameter_values_dict – Get the coefficients for each of the covariances
:param : Get the coefficients of the model
- Returns:
A dictionary of contraction_covariance_sum
- flip.covariance.contraction.compute_contraction_coordinates(coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type, basis_definition, endpoint_los_definition)¶
- flip.covariance.contraction.contract_covariance(model_name, model_type, power_spectrum_dict, coord_1, coord_2, coord_1_reference, coord_2_reference, coordinate_type='rprt', additional_parameters_values=None, basis_definition='bisector', endpoint_los_definition='bisector', number_worker=8, hankel=True)¶