snsim.io_utils
==============

.. py:module:: snsim.io_utils

.. autoapi-nested-parse::

   This module contains io stuff.



Attributes
----------

.. autoapisummary::

   snsim.io_utils.imp_json
   snsim.io_utils.imp_pyarrow
   snsim.io_utils.imp_fq


Classes
-------

.. autoapisummary::

   snsim.io_utils.NpEncoder


Functions
---------

.. autoapisummary::

   snsim.io_utils.write_sim
   snsim.io_utils.read_sim_file
   snsim.io_utils.write_fit
   snsim.io_utils.open_fit


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

.. py:data:: imp_json
   :value: True


.. py:data:: imp_pyarrow
   :value: True


.. py:data:: imp_fq
   :value: True


.. py:class:: NpEncoder(*, skipkeys=False, ensure_ascii=True, check_circular=True, allow_nan=True, sort_keys=False, indent=None, separators=None, default=None)

   Bases: :py:obj:`json.JSONEncoder`


   Extensible JSON <https://json.org> encoder for Python data structures.

   Supports the following objects and types by default:

   +-------------------+---------------+
   | Python            | JSON          |
   +===================+===============+
   | dict              | object        |
   +-------------------+---------------+
   | list, tuple       | array         |
   +-------------------+---------------+
   | str               | string        |
   +-------------------+---------------+
   | int, float        | number        |
   +-------------------+---------------+
   | True              | true          |
   +-------------------+---------------+
   | False             | false         |
   +-------------------+---------------+
   | None              | null          |
   +-------------------+---------------+

   To extend this to recognize other objects, subclass and implement a
   ``.default()`` method with another method that returns a serializable
   object for ``o`` if possible, otherwise it should call the superclass
   implementation (to raise ``TypeError``).


   Constructor for JSONEncoder, with sensible defaults.

   If skipkeys is false, then it is a TypeError to attempt
   encoding of keys that are not str, int, float or None.  If
   skipkeys is True, such items are simply skipped.

   If ensure_ascii is true, the output is guaranteed to be str
   objects with all incoming non-ASCII characters escaped.  If
   ensure_ascii is false, the output can contain non-ASCII characters.

   If check_circular is true, then lists, dicts, and custom encoded
   objects will be checked for circular references during encoding to
   prevent an infinite recursion (which would cause an RecursionError).
   Otherwise, no such check takes place.

   If allow_nan is true, then NaN, Infinity, and -Infinity will be
   encoded as such.  This behavior is not JSON specification compliant,
   but is consistent with most JavaScript based encoders and decoders.
   Otherwise, it will be a ValueError to encode such floats.

   If sort_keys is true, then the output of dictionaries will be
   sorted by key; this is useful for regression tests to ensure
   that JSON serializations can be compared on a day-to-day basis.

   If indent is a non-negative integer, then JSON array
   elements and object members will be pretty-printed with that
   indent level.  An indent level of 0 will only insert newlines.
   None is the most compact representation.

   If specified, separators should be an (item_separator, key_separator)
   tuple.  The default is (', ', ': ') if *indent* is ``None`` and
   (',', ': ') otherwise.  To get the most compact JSON representation,
   you should specify (',', ':') to eliminate whitespace.

   If specified, default is a function that gets called for objects
   that can't otherwise be serialized.  It should return a JSON encodable
   version of the object or raise a ``TypeError``.



   .. py:method:: default(obj)

      Implement this method in a subclass such that it returns
      a serializable object for ``o``, or calls the base implementation
      (to raise a ``TypeError``).

      For example, to support arbitrary iterators, you could
      implement default like this::

          def default(self, o):
              try:
                  iterable = iter(o)
              except TypeError:
                  pass
              else:
                  return list(iterable)
              # Let the base class default method raise the TypeError
              return super().default(o)




.. py:function:: write_sim(wpath, name, formats, header, data)

   Write simulated lcs.

   :param wpath: The path where to write file.
   :type wpath: str
   :param name: Simulation name.
   :type name: str
   :param formats: List of files fopprmats to write.
   :type formats: np.array(str)
   :param header: The simulation header.
   :type header: dict
   :param data: Dataframe containing lcs.
   :type data: pandas.DataFrame

   :returns: Just write files.
   :rtype: None


.. py:function:: read_sim_file(file_path, engine='pyarrow')

   Read a sim file.

   :param file_path: Path of the file.
   :type file_path: str

   :returns: The name, the header and the lcs of the simulation.
   :rtype: str, dict, pandas.DataFrame


.. py:function:: write_fit(sim_lcs_meta, fit_res, fit_model_name, sim_header, directory)

   Write fit into a fits file.

   :param sim_lcs_meta: Meta data of all lightcurves.
   :type sim_lcs_meta: dict{list}
   :param fit_res: List of sncosmo fit results for each lightcurve.
   :type fit_res: list(sncosmo.utils.Result)
   :param directory: Destination of write file.
   :type directory: str
   :param sim_meta: General simulation meta data.
   :type sim_meta: dict

   :returns: Just write a file.
   :rtype: None


.. py:function:: open_fit(file)

   USe to open fit file.

   :param file: Fit results parquet file
   :type file: str

   :returns: The fit results.
   :rtype: pandas.DataFrame