dabench.observer
================

.. py:module:: dabench.observer

.. autoapi-nested-parse::

   Observer module



Classes
-------

.. autoapisummary::

   dabench.observer.Observer


Package Contents
----------------

.. py:class:: Observer(state_vec, random_time_density = 1.0, random_location_density = 1.0, random_time_count = None, random_location_count = None, times = None, locations = None, stationary_observers = True, error_bias = 0.0, error_sd = 0.0, error_positive_only = False, random_seed = 99, store_as_jax = False)

   Flexibly samples observations from generated data

   :param state_vec: Data generator/loader object from which
                     to gather observations.
   :param random_location_density: Fraction of locations in
                                   system_dim to randomly select for observing, must be value
                                   between 0 and 1. Default is 1.
   :param random_time_density: Fraction of times to randomly select
                               for observing must be value between 0 and 1. Default is 1.
   :param random_location_count: Number of locations in data_obj's
                                 system_dim to randomly select for observing. Default is None.
                                 User should specify one of: random_location_count,
                                 random_location_density, or location_indices.
                                 If random_location_count is specified, it takes precedent over
                                 random_location_density.
   :param random_time_count: Number of times to randomly select for
                             observing. Default is None. User should specify one of:
                             random_time_count, random_time_density, or time_indices.
                             If random_time_count is specified, it takes precedent over
                             random_time_density.
   :param locations: Manually specified indices for observing.
                     If 1D array provided, assumed to be for flattened system_dim.
                     If >1D, must have same dimensionality as data generator's
                     original_dim (e.g. (x, y, z)). If stationary_observers=False,
                     expects leading time dimension. If not specified, will be randomly
                     generated according to random_location_density OR
                     random_location_count. Default is None.
   :param times: Indices of times to gather observations from.
                 If not specified, randomly generate according to
                 random_time_density OR random_time_count. Default is None.
   :param stationary_observers: If True, samples from same indices at
                                each time step. If False, randomly generates/expects new
                                observation indices at each timestep. Default is True.
                                If False:
                                    If using random_location_count, the same number of indices
                                        will be randomly generated.
                                    If using random_location_density, indices are randomly
                                        generated, with the possibility of a different number
                                        of locations at each times step..
                                    If using location_indices, expects indices to either be 2D
                                        (time_dim, system_dim) or >2D (time_dim, original_dim).
   :param error_bias: Mean of normal distribution of
                      observation errors. If provided as an array, it is taken to be
                      variable-specific and the length must be equal to
                      data_obj.system_dim. Default is 0.
   :param error_sd: Standard deviation of observation errors.
                    observation errors. If provided as an array, it is taken to be
                    variable-specific and the length be equal to data_obj.system_dim.
                    Default is 0.
   :param error_positive_only: Clip errors to be positive only. Default is
                               False.
   :param random_seed: Random seed for sampling times and locations.
                       Default is 99.
   :param store_as_jax: Store values as jax array instead of numpy array.
                        Default is False (store as numpy).

   .. attribute:: locations

      Location indices for making
      observations. In system_dim (1D) or original dim
      (>1D) of self.state_vec.

      :type: ArrayLike

   .. attribute:: location_dim

      Number of locations sampled from (max
      in a single time step, if non-stationary observers).

      :type: int

   .. attribute:: times

      Time indices to gather observations
      from.

      :type: ArrayLike

   .. attribute:: time_dim

      Number of times sampled from.

      :type: int


   .. py:method:: observe()

      Generate observations.

      :returns: ObsVector containing observation values, times, locations, and
                errors