''' Constants and classes for matlab 5 read and write

See also mio5_utils.pyx where these same constants arise as c enums.

If you make changes in this file, don't forget to change mio5_utils.pyx
'''
from __future__ import division, print_function, absolute_import

import numpy as np

from .miobase import convert_dtypes

miINT8 = 1
miUINT8 = 2
miINT16 = 3
miUINT16 = 4
miINT32 = 5
miUINT32 = 6
miSINGLE = 7
miDOUBLE = 9
miINT64 = 12
miUINT64 = 13
miMATRIX = 14
miCOMPRESSED = 15
miUTF8 = 16
miUTF16 = 17
miUTF32 = 18

mxCELL_CLASS = 1
mxSTRUCT_CLASS = 2
# The March 2008 edition of "Matlab 7 MAT-File Format" says that
# mxOBJECT_CLASS = 3, whereas matrix.h says that mxLOGICAL = 3.
# Matlab 2008a appears to save logicals as type 9, so we assume that
# the document is correct.  See type 18, below.
mxOBJECT_CLASS = 3
mxCHAR_CLASS = 4
mxSPARSE_CLASS = 5
mxDOUBLE_CLASS = 6
mxSINGLE_CLASS = 7
mxINT8_CLASS = 8
mxUINT8_CLASS = 9
mxINT16_CLASS = 10
mxUINT16_CLASS = 11
mxINT32_CLASS = 12
mxUINT32_CLASS = 13
# The following are not in the March 2008 edition of "Matlab 7
# MAT-File Format," but were guessed from matrix.h.
mxINT64_CLASS = 14
mxUINT64_CLASS = 15
mxFUNCTION_CLASS = 16
# Not doing anything with these at the moment.
mxOPAQUE_CLASS = 17  # This appears to be a function workspace
# https://www-old.cae.wisc.edu/pipermail/octave-maintainers/2007-May/002824.html
mxOBJECT_CLASS_FROM_MATRIX_H = 18

mdtypes_template = {
    miINT8: 'i1',
    miUINT8: 'u1',
    miINT16: 'i2',
    miUINT16: 'u2',
    miINT32: 'i4',
    miUINT32: 'u4',
    miSINGLE: 'f4',
    miDOUBLE: 'f8',
    miINT64: 'i8',
    miUINT64: 'u8',
    miUTF8: 'u1',
    miUTF16: 'u2',
    miUTF32: 'u4',
    'file_header': [('description', 'S116'),
                    ('subsystem_offset', 'i8'),
                    ('version', 'u2'),
                    ('endian_test', 'S2')],
    'tag_full': [('mdtype', 'u4'), ('byte_count', 'u4')],
    'tag_smalldata':[('byte_count_mdtype', 'u4'), ('data', 'S4')],
    'array_flags': [('data_type', 'u4'),
                    ('byte_count', 'u4'),
                    ('flags_class','u4'),
                    ('nzmax', 'u4')],
    'U1': 'U1',
    }

mclass_dtypes_template = {
    mxINT8_CLASS: 'i1',
    mxUINT8_CLASS: 'u1',
    mxINT16_CLASS: 'i2',
    mxUINT16_CLASS: 'u2',
    mxINT32_CLASS: 'i4',
    mxUINT32_CLASS: 'u4',
    mxINT64_CLASS: 'i8',
    mxUINT64_CLASS: 'u8',
    mxSINGLE_CLASS: 'f4',
    mxDOUBLE_CLASS: 'f8',
    }

mclass_info = {
    mxINT8_CLASS: 'int8',
    mxUINT8_CLASS: 'uint8',
    mxINT16_CLASS: 'int16',
    mxUINT16_CLASS: 'uint16',
    mxINT32_CLASS: 'int32',
    mxUINT32_CLASS: 'uint32',
    mxINT64_CLASS: 'int64',
    mxUINT64_CLASS: 'uint64',
    mxSINGLE_CLASS: 'single',
    mxDOUBLE_CLASS: 'double',
    mxCELL_CLASS: 'cell',
    mxSTRUCT_CLASS: 'struct',
    mxOBJECT_CLASS: 'object',
    mxCHAR_CLASS: 'char',
    mxSPARSE_CLASS: 'sparse',
    mxFUNCTION_CLASS: 'function',
    mxOPAQUE_CLASS: 'opaque',
    }

NP_TO_MTYPES = {
    'f8': miDOUBLE,
    'c32': miDOUBLE,
    'c24': miDOUBLE,
    'c16': miDOUBLE,
    'f4': miSINGLE,
    'c8': miSINGLE,
    'i8': miINT64,
    'i4': miINT32,
    'i2': miINT16,
    'i1': miINT8,
    'u8': miUINT64,
    'u4': miUINT32,
    'u2': miUINT16,
    'u1': miUINT8,
    'S1': miUINT8,
    'U1': miUTF16,
    'b1': miUINT8,  # not standard but seems MATLAB uses this (gh-4022)
    }


NP_TO_MXTYPES = {
    'f8': mxDOUBLE_CLASS,
    'c32': mxDOUBLE_CLASS,
    'c24': mxDOUBLE_CLASS,
    'c16': mxDOUBLE_CLASS,
    'f4': mxSINGLE_CLASS,
    'c8': mxSINGLE_CLASS,
    'i8': mxINT64_CLASS,
    'i4': mxINT32_CLASS,
    'i2': mxINT16_CLASS,
    'i1': mxINT8_CLASS,
    'u8': mxUINT64_CLASS,
    'u4': mxUINT32_CLASS,
    'u2': mxUINT16_CLASS,
    'u1': mxUINT8_CLASS,
    'S1': mxUINT8_CLASS,
    'b1': mxUINT8_CLASS,  # not standard but seems MATLAB uses this
    }

''' Before release v7.1 (release 14) matlab (TM) used the system
default character encoding scheme padded out to 16-bits. Release 14
and later use Unicode. When saving character data, R14 checks if it
can be encoded in 7-bit ascii, and saves in that format if so.'''

codecs_template = {
    miUTF8: {'codec': 'utf_8', 'width': 1},
    miUTF16: {'codec': 'utf_16', 'width': 2},
    miUTF32: {'codec': 'utf_32','width': 4},
    }


def _convert_codecs(template, byte_order):
    ''' Convert codec template mapping to byte order

    Set codecs not on this system to None

    Parameters
    ----------
    template : mapping
       key, value are respectively codec name, and root name for codec
       (without byte order suffix)
    byte_order : {'<', '>'}
       code for little or big endian

    Returns
    -------
    codecs : dict
       key, value are name, codec (as in .encode(codec))
    '''
    codecs = {}
    postfix = byte_order == '<' and '_le' or '_be'
    for k, v in template.items():
        codec = v['codec']
        try:
            " ".encode(codec)
        except LookupError:
            codecs[k] = None
            continue
        if v['width'] > 1:
            codec += postfix
        codecs[k] = codec
    return codecs.copy()


MDTYPES = {}
for _bytecode in '<>':
    _def = {'dtypes': convert_dtypes(mdtypes_template, _bytecode),
            'classes': convert_dtypes(mclass_dtypes_template, _bytecode),
            'codecs': _convert_codecs(codecs_template, _bytecode)}
    MDTYPES[_bytecode] = _def


class mat_struct(object):
    ''' Placeholder for holding read data from structs

    We deprecate this method of holding struct information, and will
    soon remove it, in favor of the recarray method (see loadmat
    docstring)
    '''
    pass


class MatlabObject(np.ndarray):
    ''' ndarray Subclass to contain matlab object '''
    def __new__(cls, input_array, classname=None):
        # Input array is an already formed ndarray instance
        # We first cast to be our class type
        obj = np.asarray(input_array).view(cls)
        # add the new attribute to the created instance
        obj.classname = classname
        # Finally, we must return the newly created object:
        return obj

    def __array_finalize__(self,obj):
        # reset the attribute from passed original object
        self.classname = getattr(obj, 'classname', None)
        # We do not need to return anything


class MatlabFunction(np.ndarray):
    ''' Subclass to signal this is a matlab function '''
    def __new__(cls, input_array):
        obj = np.asarray(input_array).view(cls)
        return obj


class MatlabOpaque(np.ndarray):
    ''' Subclass to signal this is a matlab opaque matrix '''
    def __new__(cls, input_array):
        obj = np.asarray(input_array).view(cls)
        return obj


OPAQUE_DTYPE = np.dtype(
    [('s0', 'O'), ('s1', 'O'), ('s2', 'O'), ('arr', 'O')])
