153 lines
4.5 KiB
Python
153 lines
4.5 KiB
Python
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"""
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Various richly-typed exceptions, that also help us deal with string formatting
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in python where it's easier.
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By putting the formatting in `__str__`, we also avoid paying the cost for
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users who silence the exceptions.
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"""
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from numpy.core.overrides import set_module
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def _unpack_tuple(tup):
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if len(tup) == 1:
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return tup[0]
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else:
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return tup
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def _display_as_base(cls):
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"""
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A decorator that makes an exception class look like its base.
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We use this to hide subclasses that are implementation details - the user
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should catch the base type, which is what the traceback will show them.
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Classes decorated with this decorator are subject to removal without a
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deprecation warning.
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"""
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assert issubclass(cls, Exception)
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cls.__name__ = cls.__base__.__name__
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cls.__qualname__ = cls.__base__.__qualname__
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set_module(cls.__base__.__module__)(cls)
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return cls
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class UFuncTypeError(TypeError):
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""" Base class for all ufunc exceptions """
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def __init__(self, ufunc):
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self.ufunc = ufunc
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@_display_as_base
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class _UFuncBinaryResolutionError(UFuncTypeError):
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""" Thrown when a binary resolution fails """
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def __init__(self, ufunc, dtypes):
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super().__init__(ufunc)
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self.dtypes = tuple(dtypes)
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assert len(self.dtypes) == 2
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def __str__(self):
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return (
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"ufunc {!r} cannot use operands with types {!r} and {!r}"
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).format(
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self.ufunc.__name__, *self.dtypes
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)
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@_display_as_base
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class _UFuncNoLoopError(UFuncTypeError):
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""" Thrown when a ufunc loop cannot be found """
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def __init__(self, ufunc, dtypes):
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super().__init__(ufunc)
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self.dtypes = tuple(dtypes)
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def __str__(self):
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return (
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"ufunc {!r} did not contain a loop with signature matching types "
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"{!r} -> {!r}"
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).format(
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self.ufunc.__name__,
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_unpack_tuple(self.dtypes[:self.ufunc.nin]),
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_unpack_tuple(self.dtypes[self.ufunc.nin:])
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)
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@_display_as_base
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class _UFuncCastingError(UFuncTypeError):
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def __init__(self, ufunc, casting, from_, to):
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super().__init__(ufunc)
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self.casting = casting
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self.from_ = from_
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self.to = to
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@_display_as_base
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class _UFuncInputCastingError(_UFuncCastingError):
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""" Thrown when a ufunc input cannot be casted """
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def __init__(self, ufunc, casting, from_, to, i):
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super().__init__(ufunc, casting, from_, to)
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self.in_i = i
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def __str__(self):
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# only show the number if more than one input exists
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i_str = "{} ".format(self.in_i) if self.ufunc.nin != 1 else ""
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return (
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"Cannot cast ufunc {!r} input {}from {!r} to {!r} with casting "
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"rule {!r}"
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).format(
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self.ufunc.__name__, i_str, self.from_, self.to, self.casting
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)
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@_display_as_base
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class _UFuncOutputCastingError(_UFuncCastingError):
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""" Thrown when a ufunc output cannot be casted """
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def __init__(self, ufunc, casting, from_, to, i):
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super().__init__(ufunc, casting, from_, to)
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self.out_i = i
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def __str__(self):
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# only show the number if more than one output exists
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i_str = "{} ".format(self.out_i) if self.ufunc.nout != 1 else ""
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return (
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"Cannot cast ufunc {!r} output {}from {!r} to {!r} with casting "
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"rule {!r}"
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).format(
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self.ufunc.__name__, i_str, self.from_, self.to, self.casting
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)
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# Exception used in shares_memory()
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@set_module('numpy')
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class TooHardError(RuntimeError):
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pass
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@set_module('numpy')
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class AxisError(ValueError, IndexError):
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""" Axis supplied was invalid. """
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def __init__(self, axis, ndim=None, msg_prefix=None):
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# single-argument form just delegates to base class
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if ndim is None and msg_prefix is None:
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msg = axis
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# do the string formatting here, to save work in the C code
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else:
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msg = ("axis {} is out of bounds for array of dimension {}"
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.format(axis, ndim))
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if msg_prefix is not None:
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msg = "{}: {}".format(msg_prefix, msg)
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super(AxisError, self).__init__(msg)
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@_display_as_base
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class _ArrayMemoryError(MemoryError):
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""" Thrown when an array cannot be allocated"""
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def __init__(self, shape, dtype):
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self.shape = shape
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self.dtype = dtype
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def __str__(self):
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return "Unable to allocate array with shape {} and data type {}".format(self.shape, self.dtype)
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