from __future__ import division, absolute_import, print_function

import os
import sys
import types
import re
import warnings

from numpy.core.numerictypes import issubclass_, issubsctype, issubdtype
from numpy.core.overrides import set_module
from numpy.core import ndarray, ufunc, asarray
import numpy as np

# getargspec and formatargspec were removed in Python 3.6
from numpy.compat import getargspec, formatargspec

__all__ = [
    'issubclass_', 'issubsctype', 'issubdtype', 'deprecate',
    'deprecate_with_doc', 'get_include', 'info', 'source', 'who',
    'lookfor', 'byte_bounds', 'safe_eval'
    ]

def get_include():
    """
    Return the directory that contains the NumPy \\*.h header files.

    Extension modules that need to compile against NumPy should use this
    function to locate the appropriate include directory.

    Notes
    -----
    When using ``distutils``, for example in ``setup.py``.
    ::

        import numpy as np
        ...
        Extension('extension_name', ...
                include_dirs=[np.get_include()])
        ...

    """
    import numpy
    if numpy.show_config is None:
        # running from numpy source directory
        d = os.path.join(os.path.dirname(numpy.__file__), 'core', 'include')
    else:
        # using installed numpy core headers
        import numpy.core as core
        d = os.path.join(os.path.dirname(core.__file__), 'include')
    return d


def _set_function_name(func, name):
    func.__name__ = name
    return func


class _Deprecate(object):
    """
    Decorator class to deprecate old functions.

    Refer to `deprecate` for details.

    See Also
    --------
    deprecate

    """

    def __init__(self, old_name=None, new_name=None, message=None):
        self.old_name = old_name
        self.new_name = new_name
        self.message = message

    def __call__(self, func, *args, **kwargs):
        """
        Decorator call.  Refer to ``decorate``.

        """
        old_name = self.old_name
        new_name = self.new_name
        message = self.message

        if old_name is None:
            try:
                old_name = func.__name__
            except AttributeError:
                old_name = func.__name__
        if new_name is None:
            depdoc = "`%s` is deprecated!" % old_name
        else:
            depdoc = "`%s` is deprecated, use `%s` instead!" % \
                     (old_name, new_name)

        if message is not None:
            depdoc += "\n" + message

        def newfunc(*args,**kwds):
            """`arrayrange` is deprecated, use `arange` instead!"""
            warnings.warn(depdoc, DeprecationWarning, stacklevel=2)
            return func(*args, **kwds)

        newfunc = _set_function_name(newfunc, old_name)
        doc = func.__doc__
        if doc is None:
            doc = depdoc
        else:
            doc = '\n\n'.join([depdoc, doc])
        newfunc.__doc__ = doc
        try:
            d = func.__dict__
        except AttributeError:
            pass
        else:
            newfunc.__dict__.update(d)
        return newfunc

def deprecate(*args, **kwargs):
    """
    Issues a DeprecationWarning, adds warning to `old_name`'s
    docstring, rebinds ``old_name.__name__`` and returns the new
    function object.

    This function may also be used as a decorator.

    Parameters
    ----------
    func : function
        The function to be deprecated.
    old_name : str, optional
        The name of the function to be deprecated. Default is None, in
        which case the name of `func` is used.
    new_name : str, optional
        The new name for the function. Default is None, in which case the
        deprecation message is that `old_name` is deprecated. If given, the
        deprecation message is that `old_name` is deprecated and `new_name`
        should be used instead.
    message : str, optional
        Additional explanation of the deprecation.  Displayed in the
        docstring after the warning.

    Returns
    -------
    old_func : function
        The deprecated function.

    Examples
    --------
    Note that ``olduint`` returns a value after printing Deprecation
    Warning:

    >>> olduint = np.deprecate(np.uint)
    >>> olduint(6)
    /usr/lib/python2.5/site-packages/numpy/lib/utils.py:114:
    DeprecationWarning: uint32 is deprecated
      warnings.warn(str1, DeprecationWarning, stacklevel=2)
    6

    """
    # Deprecate may be run as a function or as a decorator
    # If run as a function, we initialise the decorator class
    # and execute its __call__ method.

    if args:
        fn = args[0]
        args = args[1:]

        return _Deprecate(*args, **kwargs)(fn)
    else:
        return _Deprecate(*args, **kwargs)

deprecate_with_doc = lambda msg: _Deprecate(message=msg)


#--------------------------------------------
# Determine if two arrays can share memory
#--------------------------------------------

def byte_bounds(a):
    """
    Returns pointers to the end-points of an array.

    Parameters
    ----------
    a : ndarray
        Input array. It must conform to the Python-side of the array
        interface.

    Returns
    -------
    (low, high) : tuple of 2 integers
        The first integer is the first byte of the array, the second
        integer is just past the last byte of the array.  If `a` is not
        contiguous it will not use every byte between the (`low`, `high`)
        values.

    Examples
    --------
    >>> I = np.eye(2, dtype='f'); I.dtype
    dtype('float32')
    >>> low, high = np.byte_bounds(I)
    >>> high - low == I.size*I.itemsize
    True
    >>> I = np.eye(2, dtype='G'); I.dtype
    dtype('complex192')
    >>> low, high = np.byte_bounds(I)
    >>> high - low == I.size*I.itemsize
    True

    """
    ai = a.__array_interface__
    a_data = ai['data'][0]
    astrides = ai['strides']
    ashape = ai['shape']
    bytes_a = asarray(a).dtype.itemsize

    a_low = a_high = a_data
    if astrides is None:
        # contiguous case
        a_high += a.size * bytes_a
    else:
        for shape, stride in zip(ashape, astrides):
            if stride < 0:
                a_low += (shape-1)*stride
            else:
                a_high += (shape-1)*stride
        a_high += bytes_a
    return a_low, a_high


#-----------------------------------------------------------------------------
# Function for output and information on the variables used.
#-----------------------------------------------------------------------------


def who(vardict=None):
    """
    Print the NumPy arrays in the given dictionary.

    If there is no dictionary passed in or `vardict` is None then returns
    NumPy arrays in the globals() dictionary (all NumPy arrays in the
    namespace).

    Parameters
    ----------
    vardict : dict, optional
        A dictionary possibly containing ndarrays.  Default is globals().

    Returns
    -------
    out : None
        Returns 'None'.

    Notes
    -----
    Prints out the name, shape, bytes and type of all of the ndarrays
    present in `vardict`.

    Examples
    --------
    >>> a = np.arange(10)
    >>> b = np.ones(20)
    >>> np.who()
    Name            Shape            Bytes            Type
    ===========================================================
    a               10               40               int32
    b               20               160              float64
    Upper bound on total bytes  =       200

    >>> d = {'x': np.arange(2.0), 'y': np.arange(3.0), 'txt': 'Some str',
    ... 'idx':5}
    >>> np.who(d)
    Name            Shape            Bytes            Type
    ===========================================================
    y               3                24               float64
    x               2                16               float64
    Upper bound on total bytes  =       40

    """
    if vardict is None:
        frame = sys._getframe().f_back
        vardict = frame.f_globals
    sta = []
    cache = {}
    for name in vardict.keys():
        if isinstance(vardict[name], ndarray):
            var = vardict[name]
            idv = id(var)
            if idv in cache.keys():
                namestr = name + " (%s)" % cache[idv]
                original = 0
            else:
                cache[idv] = name
                namestr = name
                original = 1
            shapestr = " x ".join(map(str, var.shape))
            bytestr = str(var.nbytes)
            sta.append([namestr, shapestr, bytestr, var.dtype.name,
                        original])

    maxname = 0
    maxshape = 0
    maxbyte = 0
    totalbytes = 0
    for k in range(len(sta)):
        val = sta[k]
        if maxname < len(val[0]):
            maxname = len(val[0])
        if maxshape < len(val[1]):
            maxshape = len(val[1])
        if maxbyte < len(val[2]):
            maxbyte = len(val[2])
        if val[4]:
            totalbytes += int(val[2])

    if len(sta) > 0:
        sp1 = max(10, maxname)
        sp2 = max(10, maxshape)
        sp3 = max(10, maxbyte)
        prval = "Name %s Shape %s Bytes %s Type" % (sp1*' ', sp2*' ', sp3*' ')
        print(prval + "\n" + "="*(len(prval)+5) + "\n")

    for k in range(len(sta)):
        val = sta[k]
        print("%s %s %s %s %s %s %s" % (val[0], ' '*(sp1-len(val[0])+4),
                                        val[1], ' '*(sp2-len(val[1])+5),
                                        val[2], ' '*(sp3-len(val[2])+5),
                                        val[3]))
    print("\nUpper bound on total bytes  =       %d" % totalbytes)
    return

#-----------------------------------------------------------------------------


# NOTE:  pydoc defines a help function which works similarly to this
#  except it uses a pager to take over the screen.

# combine name and arguments and split to multiple lines of width
# characters.  End lines on a comma and begin argument list indented with
# the rest of the arguments.
def _split_line(name, arguments, width):
    firstwidth = len(name)
    k = firstwidth
    newstr = name
    sepstr = ", "