firecrown.generators.two_point
==============================

.. py:module:: firecrown.generators.two_point

.. autoapi-nested-parse::

   Generator support for TwoPoint statistics.



Attributes
----------

.. autoapisummary::

   firecrown.generators.two_point.ELL_FOR_XI_DEFAULTS


Classes
-------

.. autoapisummary::

   firecrown.generators.two_point.LogLinearElls
   firecrown.generators.two_point.EllOrThetaConfig


Functions
---------

.. autoapisummary::

   firecrown.generators.two_point.log_linear_ells
   firecrown.generators.two_point.generate_bin_centers
   firecrown.generators.two_point.calculate_ells_for_interpolation
   firecrown.generators.two_point.generate_ells_cells
   firecrown.generators.two_point.generate_reals
   firecrown.generators.two_point.apply_ells_min_max
   firecrown.generators.two_point.apply_theta_min_max


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

.. py:data:: ELL_FOR_XI_DEFAULTS

.. py:class:: LogLinearElls(/, **data)

   Bases: :py:obj:`pydantic.BaseModel`

   .. autoapi-inheritance-diagram:: firecrown.generators.two_point.LogLinearElls
      :parts: 1


   Generator for log-linear integral ell values.

   Not all ell values will be generated. The result will contain each integral
   value from min to mid. Starting from mid, and going up to max, there will be
   n_log logarithmically spaced values.

   Note that midpoint must be strictly greater than minimum, and strictly less
   than maximum. n_log must be positive.


   .. py:attribute:: minimum
      :type:  Annotated[int, Field(ge=0)]


   .. py:attribute:: midpoint
      :type:  Annotated[int, Field(ge=0)]


   .. py:attribute:: maximum
      :type:  Annotated[int, Field(ge=0)]


   .. py:attribute:: n_log
      :type:  Annotated[int, Field(ge=1)]


   .. py:method:: require_increasing()

      Validate the ell values.



   .. py:method:: generate()

      Generate the log-linear ell values.

      The result will contain each integral value from min to mid. Starting
      from mid, and going up to max, there will be n_log logarithmically
      spaced values.

      :param minimum: The low edge of the first bin.
      :param midpoint: The high edge of the last in the linear range.
      :param maximum: The high edge of the last bin.
      :param n_log: The number of bins in the log section of the range.



.. py:function:: log_linear_ells(*, minimum, midpoint, maximum, n_log)

   Create an array of ells to sample the power spectrum.

   This is used for for real-space predictions. The result will contain
   each integral value from min to mid. Starting from mid, and going up
   to max, there will be n_log logarithmically spaced values.

   All values are rounded to the nearest integer.

   :param minimum: The low edge of the first bin.
   :param midpoint: The high edge of the last in the linear range.
   :param maximum: The high edge of the last bin.
   :param n_log: The number of bins in the log section of the range.


.. py:function:: generate_bin_centers(*, minimum, maximum, n, binning = 'log')

   Return the centers of bins that span the range from minimum to maximum.

   If binning is 'log', this will generate logarithmically spaced bins; if
   binning is 'lin', this will generate linearly spaced bins.

   :param minimum: The low edge of the first bin.
   :param maximum: The high edge of the last bin.
   :param n: The number of bins.
   :param binning: Either 'log' or 'lin'.
   :return: The centers of the bins.


.. py:function:: calculate_ells_for_interpolation(min_ell, max_ell)

   See log_linear_ells.

   This method mixes together:
       1. the default parameters in ELL_FOR_XI_DEFAULTS
       2. the first and last values in w.

   and then calls log_linear_ells with those arguments, returning whatever it
   returns.


.. py:class:: EllOrThetaConfig

   Bases: :py:obj:`TypedDict`

   .. autoapi-inheritance-diagram:: firecrown.generators.two_point.EllOrThetaConfig
      :parts: 1


   A dictionary of options for generating the ell or theta.

   This dictionary contains the minimum, maximum and number of
   bins to generate the ell or theta values at which to compute the statistics.

   :param minimum: The start of the binning.
   :param maximum: The end of the binning.
   :param n: The number of bins.
   :param binning: Pass 'log' to get logarithmic spaced bins and 'lin' to get linearly
       spaced bins. Default is 'log'.



   .. py:attribute:: minimum
      :type:  float


   .. py:attribute:: maximum
      :type:  float


   .. py:attribute:: n
      :type:  int


   .. py:attribute:: binning
      :type:  str


.. py:function:: generate_ells_cells(ell_config)

   Generate ells or theta values from the configuration dictionary.

   :param ell_config: the configuration parameters.
   :return: ells and Cells


.. py:function:: generate_reals(theta_config)

   Generate theta and xi values from the configuration dictionary.

   :param ell_config: the configuration parameters.
   :return: ells and Cells


.. py:function:: apply_ells_min_max(ells, Cells, indices, ell_min, ell_max)

   Apply the minimum and maximum ell values to the ells and Cells.


.. py:function:: apply_theta_min_max(thetas, xis, indices, theta_min, theta_max)

   Apply the minimum and maximum theta values to the thetas and xis.