"""Compatibility functions for numpy versions in lib

np_new_unique
-------------
Optionally provides the count of the number of occurences of each
unique element.

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"""

from __future__ import absolute_import
from distutils.version import LooseVersion

import numpy as np

from .python import PY3

NP_LT_114 = LooseVersion(np.__version__) < LooseVersion('1.14')
NP_LT_113 = LooseVersion(np.__version__) < '1.13.0'

np_matrix_rank = np.linalg.matrix_rank
np_new_unique = np.unique


def recarray_select(recarray, fields):
    """"
    Work-around for changes in NumPy 1.13 that return views for recarray
    multiple column selection
    """
    from pandas import DataFrame
    fields = [fields] if not isinstance(fields, (tuple, list)) else fields
    if len(fields) == len(recarray.dtype):
        selection = recarray
    else:
        recarray = DataFrame.from_records(recarray)
        selection = recarray[fields].to_records(index=False)

    _bytelike_dtype_names(selection)
    return selection


def _bytelike_dtype_names(arr):
    # See # 3658
    if not PY3:
        dtype = arr.dtype
        names = dtype.names
        names = [bytes(name) if isinstance(name, unicode)  # noqa:F821
                 else name for name in names]
        dtype.names = names


def lstsq(a, b, rcond=None):
    """
    Shim that allows modern rcond setting with backward compat for NumPY
    earlier than 1.14
    """
    if NP_LT_114 and rcond is None:
        rcond = -1
    return np.linalg.lstsq(a, b, rcond=rcond)
