FM / core

/usr/local/lib64/python3.6/site-packages/numpy/core/

/usr/local/lib64/python3.6/site-packages/numpy/core

Name	Size	Mode	Actions
include/	-	0755	rm
lib/	-	0755	rm
tests/	-	0755	rm
__pycache__/	-	0755	rm
arrayprint.py	59114	0644	edit dl rm
cversions.py	347	0644	edit dl rm
defchararray.py	70041	0644	edit dl rm
einsumfunc.py	50689	0644	edit dl rm
fromnumeric.py	119216	0644	edit dl rm
function_base.py	18034	0644	edit dl rm
generate_numpy_api.py	7022	0644	edit dl rm
getlimits.py	19076	0644	edit dl rm
machar.py	10786	0644	edit dl rm
memmap.py	11562	0644	edit dl rm
multiarray.py	54410	0644	edit dl rm
numeric.py	74615	0644	edit dl rm
numerictypes.py	16563	0644	edit dl rm
overrides.py	7481	0644	edit dl rm
records.py	35083	0644	edit dl rm
setup.py	42409	0644	edit dl rm
setup_common.py	18410	0644	edit dl rm
shape_base.py	29014	0644	edit dl rm
umath.py	2040	0644	edit dl rm
umath_tests.py	389	0644	edit dl rm
_add_newdocs.py	202741	0644	edit dl rm
_asarray.py	9874	0644	edit dl rm
_dtype.py	9820	0644	edit dl rm
_dtype_ctypes.py	3673	0644	edit dl rm
_exceptions.py	6145	0644	edit dl rm
_internal.py	26293	0644	edit dl rm
_methods.py	9148	0644	edit dl rm
_multiarray_tests.cpython-36m-x86_64-linux-gnu.so	167112	0755	edit dl rm
_multiarray_umath.cpython-36m-x86_64-linux-gnu.so	4169248	0755	edit dl rm
_operand_flag_tests.cpython-36m-x86_64-linux-gnu.so	13168	0755	edit dl rm
_rational_tests.cpython-36m-x86_64-linux-gnu.so	59856	0755	edit dl rm
_string_helpers.py	2855	0644	edit dl rm
_struct_ufunc_tests.cpython-36m-x86_64-linux-gnu.so	13272	0755	edit dl rm
_type_aliases.py	8846	0644	edit dl rm
_ufunc_config.py	13821	0644	edit dl rm
_umath_tests.cpython-36m-x86_64-linux-gnu.so	27768	0755	edit dl rm
__init__.py	4335	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/numpy/core/_exceptions.py (6145B)

"""
Various richly-typed exceptions, that also help us deal with string formatting
in python where it's easier.

By putting the formatting in `__str__`, we also avoid paying the cost for
users who silence the exceptions.
"""
from numpy.core.overrides import set_module

def _unpack_tuple(tup):
    if len(tup) == 1:
        return tup[0]
    else:
        return tup

def _display_as_base(cls):
    """
    A decorator that makes an exception class look like its base.

We use this to hide subclasses that are implementation details - the user
    should catch the base type, which is what the traceback will show them.

Classes decorated with this decorator are subject to removal without a
    deprecation warning.
    """
    assert issubclass(cls, Exception)
    cls.__name__ = cls.__base__.__name__
    return cls

class UFuncTypeError(TypeError):
    """ Base class for all ufunc exceptions """
    def __init__(self, ufunc):
        self.ufunc = ufunc

@_display_as_base
class _UFuncBinaryResolutionError(UFuncTypeError):
    """ Thrown when a binary resolution fails """
    def __init__(self, ufunc, dtypes):
        super().__init__(ufunc)
        self.dtypes = tuple(dtypes)
        assert len(self.dtypes) == 2

def __str__(self):
        return (
            "ufunc {!r} cannot use operands with types {!r} and {!r}"
        ).format(
            self.ufunc.__name__, *self.dtypes
        )

@_display_as_base
class _UFuncNoLoopError(UFuncTypeError):
    """ Thrown when a ufunc loop cannot be found """
    def __init__(self, ufunc, dtypes):
        super().__init__(ufunc)
        self.dtypes = tuple(dtypes)

def __str__(self):
        return (
            "ufunc {!r} did not contain a loop with signature matching types "
            "{!r} -> {!r}"
        ).format(
            self.ufunc.__name__,
            _unpack_tuple(self.dtypes[:self.ufunc.nin]),
            _unpack_tuple(self.dtypes[self.ufunc.nin:])
        )

@_display_as_base
class _UFuncCastingError(UFuncTypeError):
    def __init__(self, ufunc, casting, from_, to):
        super().__init__(ufunc)
        self.casting = casting
        self.from_ = from_
        self.to = to

@_display_as_base
class _UFuncInputCastingError(_UFuncCastingError):
    """ Thrown when a ufunc input cannot be casted """
    def __init__(self, ufunc, casting, from_, to, i):
        super().__init__(ufunc, casting, from_, to)
        self.in_i = i

def __str__(self):
        # only show the number if more than one input exists
        i_str = "{} ".format(self.in_i) if self.ufunc.nin != 1 else ""
        return (
            "Cannot cast ufunc {!r} input {}from {!r} to {!r} with casting "
            "rule {!r}"
        ).format(
            self.ufunc.__name__, i_str, self.from_, self.to, self.casting
        )

@_display_as_base
class _UFuncOutputCastingError(_UFuncCastingError):
    """ Thrown when a ufunc output cannot be casted """
    def __init__(self, ufunc, casting, from_, to, i):
        super().__init__(ufunc, casting, from_, to)
        self.out_i = i

def __str__(self):
        # only show the number if more than one output exists
        i_str = "{} ".format(self.out_i) if self.ufunc.nout != 1 else ""
        return (
            "Cannot cast ufunc {!r} output {}from {!r} to {!r} with casting "
            "rule {!r}"
        ).format(
            self.ufunc.__name__, i_str, self.from_, self.to, self.casting
        )

# Exception used in shares_memory()
@set_module('numpy')
class TooHardError(RuntimeError):
    pass

@set_module('numpy')
class AxisError(ValueError, IndexError):
    """ Axis supplied was invalid. """
    def __init__(self, axis, ndim=None, msg_prefix=None):
        # single-argument form just delegates to base class
        if ndim is None and msg_prefix is None:
            msg = axis

# do the string formatting here, to save work in the C code
        else:
            msg = ("axis {} is out of bounds for array of dimension {}"
                   .format(axis, ndim))
            if msg_prefix is not None:
                msg = "{}: {}".format(msg_prefix, msg)

super(AxisError, self).__init__(msg)

@_display_as_base
class _ArrayMemoryError(MemoryError):
    """ Thrown when an array cannot be allocated"""
    def __init__(self, shape, dtype):
        self.shape = shape
        self.dtype = dtype

@property
    def _total_size(self):
        num_bytes = self.dtype.itemsize
        for dim in self.shape:
            num_bytes *= dim
        return num_bytes

@staticmethod
    def _size_to_string(num_bytes):
        """ Convert a number of bytes into a binary size string """

# https://en.wikipedia.org/wiki/Binary_prefix
        LOG2_STEP = 10
        STEP = 1024
        units = ['bytes', 'KiB', 'MiB', 'GiB', 'TiB', 'PiB', 'EiB']

unit_i = max(num_bytes.bit_length() - 1, 1) // LOG2_STEP
        unit_val = 1 << (unit_i * LOG2_STEP)
        n_units = num_bytes / unit_val
        del unit_val

# ensure we pick a unit that is correct after rounding
        if round(n_units) == STEP:
            unit_i += 1
            n_units /= STEP

# deal with sizes so large that we don't have units for them
        if unit_i >= len(units):
            new_unit_i = len(units) - 1
            n_units *= 1 << ((unit_i - new_unit_i) * LOG2_STEP)
            unit_i = new_unit_i

unit_name = units[unit_i]
        # format with a sensible number of digits
        if unit_i == 0:
            # no decimal point on bytes
            return '{:.0f} {}'.format(n_units, unit_name)
        elif round(n_units) < 1000:
            # 3 significant figures, if none are dropped to the left of the .
            return '{:#.3g} {}'.format(n_units, unit_name)
        else:
            # just give all the digits otherwise
            return '{:#.0f} {}'.format(n_units, unit_name)

def __str__(self):
        size_str = self._size_to_string(self._total_size)
        return (
            "Unable to allocate {} for an array with shape {} and data type {}"
            .format(size_str, self.shape, self.dtype)
        )

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