:py:mod:`respy.config`
======================

.. py:module:: respy.config

.. autoapi-nested-parse::

   General configuration for respy.

   ..
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Module Contents
---------------

.. py:data:: CHAOSPY_INSTALLED
   :annotation: = False

   

.. py:data:: ROOT_DIR
   

   

.. py:data:: TEST_DIR
   

   

.. py:data:: TEST_RESOURCES_DIR
   

   

.. py:data:: MAX_FLOAT
   :annotation: = 1e+200

   

.. py:data:: MIN_FLOAT
   

   

.. py:data:: MAX_LOG_FLOAT
   :annotation: = 460

   

.. py:data:: MIN_LOG_FLOAT
   

   

.. py:data:: COVARIATES_DOT_PRODUCT_DTYPE
   

   
   numpy.dtype : Dtype of covariates before being used in a dot product.

   If you convert a DataFrame with boolean variables and others to an NumPy array, the
   resulting array will have an 'object' dtype. Having an 'object' dtype array causes a lot
   of problems as functions like :func:`numpy.exp` will fail raising an uninformative error
   message.















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.. py:data:: DTYPE_STATES
   

   

.. py:data:: INDEXER_DTYPE
   

   
   numpy.dtype : Data type for the entries in the state space indexer.
















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.. py:data:: INDEXER_INVALID_INDEX
   

   
   int : Identifier for invalid states.

   Every valid state has a unique number which is stored in the state space indexer at the
   correct position. Invalid entries in the indexer are filled with
   :data:`INDEXER_INVALID_INDEX` which is the most negative value for
   :data:`INDEXER_DTYPE`. Using the invalid value as an index likely raises an
   :class:`IndexError` as negative indices cannot exceed the length of the indexed array
   dimension.















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.. py:data:: TOL_REGRESSION_TESTS
   :annotation: = 1e-10

   

.. py:data:: SEED_STARTUP_ITERATION_GAP
   :annotation: = 1000000

   

.. py:data:: DEFAULT_OPTIONS
   

   

.. py:data:: KEANE_WOLPIN_1994_MODELS
   

   

.. py:data:: KEANE_WOLPIN_1997_MODELS
   :annotation: = ['kw_97_basic', 'kw_97_basic_respy', 'kw_97_extended', 'kw_97_extended_respy']

   

.. py:data:: KEANE_WOLPIN_2000_MODELS
   :annotation: = ['kw_2000']

   

.. py:data:: ROBINSON_CRUSOE_MODELS
   :annotation: = ['robinson_crusoe_basic', 'robinson_crusoe_extended', 'robinson_crusoe_with_observed_characteristics']

   

.. py:data:: EXAMPLE_MODELS