oasislmf.pytools.common.input_files
===================================

.. py:module:: oasislmf.pytools.common.input_files


Attributes
----------

.. autoapisummary::

   oasislmf.pytools.common.input_files.logger
   oasislmf.pytools.common.input_files.EVENTRATES_FILE
   oasislmf.pytools.common.input_files.OCCURRENCE_FILE
   oasislmf.pytools.common.input_files.PERIODS_FILE
   oasislmf.pytools.common.input_files.QUANTILE_FILE
   oasislmf.pytools.common.input_files.RETURNPERIODS_FILE


Functions
---------

.. autoapisummary::

   oasislmf.pytools.common.input_files.read_event_rates
   oasislmf.pytools.common.input_files.read_quantile
   oasislmf.pytools.common.input_files.read_occurrence
   oasislmf.pytools.common.input_files.read_periods
   oasislmf.pytools.common.input_files.read_return_periods


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

.. py:data:: logger

.. py:data:: EVENTRATES_FILE
   :value: 'event_rates.csv'


.. py:data:: OCCURRENCE_FILE
   :value: 'occurrence.bin'


.. py:data:: PERIODS_FILE
   :value: 'periods.bin'


.. py:data:: QUANTILE_FILE
   :value: 'quantile.bin'


.. py:data:: RETURNPERIODS_FILE
   :value: 'returnperiods.bin'


.. py:function:: read_event_rates(run_dir, filename=EVENTRATES_FILE)

   Reads event rates from a CSV file
   Args:
       run_dir (str | os.PathLike): Path to input files dir
       filename (str | os.PathLike): event rates csv file name
   Returns:
       unique_event_ids (ndarray[oasis_int]): unique event ids
       event_rates (ndarray[oasis_float]): event rates


.. py:function:: read_quantile(sample_size, run_dir, filename=QUANTILE_FILE, return_empty=False)

   Generate a quantile interval Dictionary based on sample size and quantile binary file
   Args:
       sample_size (int): Sample size
       run_dir (str | os.PathLike): Path to input files dir
       filename (str | os.PathLike): quantile binary file name
       return_empty (bool): return an empty intervals array regardless of the existence of the quantile binary
   Returns:
       intervals (quantile_interval_dtype): Numpy array emulating a dictionary for numba


.. py:function:: read_occurrence(run_dir, filename=OCCURRENCE_FILE)

   Read the occurrence binary file and returns an occurrence map
   Args:
       run_dir (str | os.PathLike): Path to input files dir
       filename (str | os.PathLike): occurrence binary file name
   Returns:
       occ_map (ndarray[occ_map_dtype]): numpy map of event_id, period_no, occ_date_id from the occurrence file


.. py:function:: read_periods(no_of_periods, run_dir, filename=PERIODS_FILE)

   Returns an array of period weights for each period between 1 and no_of_periods inclusive (with no gaps).
   Args:
       no_of_periods (int): Number of periods
       run_dir (str | os.PathLike): Path to input files dir
       filename (str | os.PathLike): periods binary file name
   Returns:
       period_weights (ndarray[period_weights_dtype]): Period weights


.. py:function:: read_return_periods(use_return_period_file, run_dir, filename=RETURNPERIODS_FILE)

   Returns an array of return periods decreasing order with no duplicates.
   Args:
       use_return_period_file (bool): Bool to use Return Period File
       run_dir (str | os.PathLike): Path to input files dir
       filename (str | os.PathLike): return periods binary file name
   Returns:
       return_periods (ndarray[np.int32]): Return Periods
       use_return_period_file (bool): Bool to use Return Period File