"""
Module for reading and writing matlab (TM) .mat files
"""
# Authors: Travis Oliphant, Matthew Brett

from __future__ import division, print_function, absolute_import

import numpy as np

from scipy.lib.six import string_types

from .miobase import get_matfile_version, docfiller
from .mio4 import MatFile4Reader, MatFile4Writer
from .mio5 import MatFile5Reader, MatFile5Writer

__all__ = ['find_mat_file', 'mat_reader_factory', 'loadmat', 'savemat',
           'whosmat']

def _open_file(file_like, appendmat):
    ''' Open `file_like` and return as file-like object '''
    if isinstance(file_like, string_types):
        try:
            return open(file_like, 'rb')
        except IOError as e:
            if appendmat and not file_like.endswith('.mat'):
                file_like += '.mat'
                return open(file_like, 'rb')
            raise IOError(e)
    # not a string - maybe file-like object
    try:
        file_like.read(0)
    except AttributeError:
        raise IOError('Reader needs file name or open file-like object')
    return file_like


@docfiller
def mat_reader_factory(file_name, appendmat=True, **kwargs):
    """Create reader for matlab .mat format files

    Parameters
    ----------
    %(file_arg)s
    %(append_arg)s
    %(load_args)s
    %(struct_arg)s

    Returns
    -------
    matreader : MatFileReader object
       Initialized instance of MatFileReader class matching the mat file
       type detected in `filename`.
    """
    byte_stream = _open_file(file_name, appendmat)
    mjv, mnv = get_matfile_version(byte_stream)
    if mjv == 0:
        return MatFile4Reader(byte_stream, **kwargs)
    elif mjv == 1:
        return MatFile5Reader(byte_stream, **kwargs)
    elif mjv == 2:
        raise NotImplementedError('Please use HDF reader for matlab v7.3 files')
    else:
        raise TypeError('Did not recognize version %s' % mjv)


@docfiller
def loadmat(file_name, mdict=None, appendmat=True, **kwargs):
    """
    Load MATLAB file

    Parameters
    ----------
    file_name : str
       Name of the mat file (do not need .mat extension if
       appendmat==True) Can also pass open file-like object.
    m_dict : dict, optional
        Dictionary in which to insert matfile variables.
    appendmat : bool, optional
       True to append the .mat extension to the end of the given
       filename, if not already present.
    byte_order : str or None, optional
       None by default, implying byte order guessed from mat
       file. Otherwise can be one of ('native', '=', 'little', '<',
       'BIG', '>').
    mat_dtype : bool, optional
       If True, return arrays in same dtype as would be loaded into
       MATLAB (instead of the dtype with which they are saved).
    squeeze_me : bool, optional
       Whether to squeeze unit matrix dimensions or not.
    chars_as_strings : bool, optional
       Whether to convert char arrays to string arrays.
    matlab_compatible : bool, optional
       Returns matrices as would be loaded by MATLAB (implies
       squeeze_me=False, chars_as_strings=False, mat_dtype=True,
       struct_as_record=True).
    struct_as_record : bool, optional
       Whether to load MATLAB structs as numpy record arrays, or as
       old-style numpy arrays with dtype=object.  Setting this flag to
       False replicates the behavior of scipy version 0.7.x (returning
       numpy object arrays).  The default setting is True, because it
       allows easier round-trip load and save of MATLAB files.
    variable_names : None or sequence
        If None (the default) - read all variables in file. Otherwise
        `variable_names` should be a sequence of strings, giving names of the
        matlab variables to read from the file.  The reader will skip any
        variable with a name not in this sequence, possibly saving some read
        processing.

    Returns
    -------
    mat_dict : dict
       dictionary with variable names as keys, and loaded matrices as
       values

    Notes
    -----
    v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported.

    You will need an HDF5 python library to read matlab 7.3 format mat
    files.  Because scipy does not supply one, we do not implement the
    HDF5 / 7.3 interface here.

    """
    variable_names = kwargs.pop('variable_names', None)
    MR = mat_reader_factory(file_name, appendmat, **kwargs)
    matfile_dict = MR.get_variables(variable_names)
    if mdict is not None:
        mdict.update(matfile_dict)
    else:
        mdict = matfile_dict
    if isinstance(file_name, string_types):
        MR.mat_stream.close()
    return mdict


@docfiller
def savemat(file_name, mdict,
            appendmat=True,
            format='5',
            long_field_names=False,
            do_compression=False,
            oned_as='row'):
    """
    Save a dictionary of names and arrays into a MATLAB-style .mat file.

    This saves the array objects in the given dictionary to a MATLAB-
    style .mat file.

    Parameters
    ----------
    file_name : str or file-like object
        Name of the .mat file (.mat extension not needed if ``appendmat ==
        True``).
        Can also pass open file_like object.
    mdict : dict
        Dictionary from which to save matfile variables.
    appendmat : bool, optional
        True (the default) to append the .mat extension to the end of the
        given filename, if not already present.
    format : {'5', '4'}, string, optional
        '5' (the default) for MATLAB 5 and up (to 7.2),
        '4' for MATLAB 4 .mat files
    long_field_names : bool, optional
        False (the default) - maximum field name length in a structure is
        31 characters which is the documented maximum length.
        True - maximum field name length in a structure is 63 characters
        which works for MATLAB 7.6+
    do_compression : bool, optional
        Whether or not to compress matrices on write.  Default is False.
    oned_as : {'row', 'column'}, optional
        If 'column', write 1-D numpy arrays as column vectors.
        If 'row', write 1-D numpy arrays as row vectors.

    See also
    --------
    mio4.MatFile4Writer
    mio5.MatFile5Writer
    """
    file_is_string = isinstance(file_name, string_types)
    if file_is_string:
        if appendmat and file_name[-4:] != ".mat":
            file_name = file_name + ".mat"
        file_stream = open(file_name, 'wb')
    else:
        try:
            file_name.write(b'')
        except AttributeError:
            raise IOError('Writer needs file name or writeable '
                           'file-like object')
        file_stream = file_name

    if format == '4':
        if long_field_names:
            raise ValueError("Long field names are not available for version 4 files")
        MW = MatFile4Writer(file_stream, oned_as)
    elif format == '5':
        MW = MatFile5Writer(file_stream,
                            do_compression=do_compression,
                            unicode_strings=True,
                            long_field_names=long_field_names,
                            oned_as=oned_as)
    else:
        raise ValueError("Format should be '4' or '5'")
    MW.put_variables(mdict)
    if file_is_string:
        file_stream.close()


@docfiller
def whosmat(file_name, appendmat=True, **kwargs):
    """
    List variables inside a MATLAB file

    .. versionadded:: 0.12.0

    Parameters
    ----------
    %(file_arg)s
    %(append_arg)s
    %(load_args)s
    %(struct_arg)s

    Returns
    -------
    variables : list of tuples
        A list of tuples, where each tuple holds the matrix name (a string),
        its shape (tuple of ints), and its data class (a string).
        Possible data classes are: int8, uint8, int16, uint16, int32, uint32,
        int64, uint64, single, double, cell, struct, object, char, sparse,
        function, opaque, logical, unknown.

    Notes
    -----
    v4 (Level 1.0), v6 and v7 to 7.2 matfiles are supported.

    You will need an HDF5 python library to read matlab 7.3 format mat
    files.  Because scipy does not supply one, we do not implement the
    HDF5 / 7.3 interface here.

    """
    ML = mat_reader_factory(file_name, **kwargs)
    variables = ML.list_variables()
    if isinstance(file_name, string_types):
        ML.mat_stream.close()
    return variables
