flip.data_vector.galaxypv_vectors
=================================

.. py:module:: flip.data_vector.galaxypv_vectors


Attributes
----------

.. autoapisummary::

   flip.data_vector.galaxypv_vectors.jax_installed


Classes
-------

.. autoapisummary::

   flip.data_vector.galaxypv_vectors.VelFromLogDist
   flip.data_vector.galaxypv_vectors.VelFromTullyFisher
   flip.data_vector.galaxypv_vectors.VelFromFundamentalPlane


Module Contents
---------------

.. py:data:: jax_installed
   :value: True


.. py:class:: VelFromLogDist(data, covariance_observation=None, velocity_estimator='full')

   Bases: :py:obj:`flip.data_vector.basic.DataVector`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: _kind
      :value: 'velocity'



   .. py:attribute:: _needed_keys
      :value: ['eta']



   .. py:property:: conditional_needed_keys

      Returns a list of keys needed for the data vector calculation,
      including any additional keys that are conditionally required.

      :returns: A list of keys needed for the data vector calculation.
      :rtype: list


   .. py:method:: give_data_and_variance(parameter_values_dict, *args)

      Returns the data and variance for the velocity.

      If the covariance observation is available, it returns the velocity data and the covariance observation.
      Otherwise, it returns the velocity data and the squared velocity error.

      :param \*args: Additional arguments (not used in this method).

      :returns: A tuple containing the velocity data and the variance.
      :rtype: tuple



   .. py:attribute:: velocity_estimator
      :value: 'full'



.. py:class:: VelFromTullyFisher(data, h, covariance_observation=None, velocity_estimator='full')

   Bases: :py:obj:`flip.data_vector.basic.DataVector`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: _kind
      :value: 'velocity'



   .. py:attribute:: _needed_keys
      :value: ['zobs', 'logW', 'm_mean', 'rcom_zobs']



   .. py:attribute:: _free_par
      :value: ['a', 'b']



   .. py:property:: conditional_needed_keys

      Returns a list of conditional keys based on the availability of covariance observation.

      If the covariance observation is None, the method adds "e_logW" and "e_m_mean" to the list of conditional keys.

      :returns: A list of conditional keys.
      :rtype: list


   .. py:method:: compute_observed_distance_modulus(parameter_values_dict)

      Compute the observed distance modulus based on the given parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: The observed distance modulus.
      :rtype: float



   .. py:method:: compute_distance_modulus_difference(parameter_values_dict)

      Compute the difference in distance modulus.

      This method calculates the difference in distance modulus based on the provided parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: The difference in distance modulus.
      :rtype: float



   .. py:method:: compute_observed_distance_modulus_variance(parameter_values_dict)

      Compute the variance of the observed distance modulus.

      :param parameter_values_dict: A dictionary containing parameter values.
      :type parameter_values_dict: dict

      :returns: The variance of the observed distance modulus.
      :rtype: float or ndarray



   .. py:method:: give_data_and_variance(parameter_values_dict)

      Compute the velocities and velocity variances based on the given parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: A tuple containing the velocities and velocity variances.
      :rtype: tuple



   .. py:method:: _init_A()

      Initializes the matrix A for the galaxypv_vectors class.

      :returns: The initialized matrix A.
      :rtype: A (ndarray)



   .. py:attribute:: velocity_estimator
      :value: 'full'



   .. py:attribute:: h


   .. py:attribute:: _A
      :value: None



   .. py:attribute:: _host_matrix
      :value: None



.. py:class:: VelFromFundamentalPlane(data, h, covariance_observation=None, velocity_estimator='full')

   Bases: :py:obj:`flip.data_vector.basic.DataVector`


   Helper class that provides a standard way to create an ABC using
   inheritance.


   .. py:attribute:: _kind
      :value: 'velocity'



   .. py:attribute:: _needed_keys
      :value: ['zobs', 'logRe', 'logsig', 'logI', 'rcom_zobs']



   .. py:attribute:: _free_par
      :value: ['a', 'b', 'c']



   .. py:property:: conditional_needed_keys

      Returns a list of conditional keys based on the availability of covariance observation.

      If the covariance observation is None, the method adds "e_logW" and "e_m_mean" to the list of conditional keys.

      :returns: A list of conditional keys.
      :rtype: list


   .. py:method:: compute_observed_distance_modulus(parameter_values_dict)

      Compute the observed distance modulus based on the given parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: The observed distance modulus.
      :rtype: float



   .. py:method:: compute_distance_modulus_difference(parameter_values_dict)

      Compute the difference in distance modulus.

      This method calculates the difference in distance modulus based on the provided parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: The difference in distance modulus.
      :rtype: float



   .. py:method:: compute_observed_distance_modulus_variance(parameter_values_dict)

      Compute the variance of the observed distance modulus.

      :param parameter_values_dict: A dictionary containing parameter values.
      :type parameter_values_dict: dict

      :returns: The variance of the observed distance modulus.
      :rtype: float or ndarray



   .. py:method:: give_data_and_variance(parameter_values_dict)

      Compute the velocities and velocity variances based on the given parameter values.

      :param parameter_values_dict: A dictionary containing the parameter values.
      :type parameter_values_dict: dict

      :returns: A tuple containing the velocities and velocity variances.
      :rtype: tuple



   .. py:method:: _init_A()

      Initializes the matrix A for the galaxypv_vectors class.

      :returns: The initialized matrix A.
      :rtype: A (ndarray)



   .. py:attribute:: velocity_estimator
      :value: 'full'



   .. py:attribute:: h


   .. py:attribute:: _A
      :value: None



   .. py:attribute:: _host_matrix
      :value: None