Python numpy.can_cast() 使用实例

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Example 1

def set_data(self, A):
        """
        Set the image array

        ACCEPTS: numpy/PIL Image A
        """

        self._full_res = A
        self._A = A

        if (self._A.dtype != np.uint8 and
                not np.can_cast(self._A.dtype, np.float)):
            raise TypeError("Image data can not convert to float")

        if (self._A.ndim not in (2, 3) or
                (self._A.ndim == 3 and self._A.shape[-1] not in (3, 4))):
            raise TypeError("Invalid dimensions for image data")

        self._imcache = None
        self._rgbacache = None
        self._oldxslice = None
        self._oldyslice = None
        self._sx, self._sy = None, None 

Example 2

def fillna(self, value):
        if not np.can_cast(value, self.dtype):
            raise TypeError("fill value must match dtype of series")
        return self.map_partitions(M.fillna, value, meta=self) 

Example 3

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 4

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= filled(domain(da, db), True)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 5

def _get_reduce_op(ops, dtype):
    for i in ops._ops:
        if numpy.can_cast(dtype.type, i[0][0]):
            return i
    raise TypeError("Type is mismatched. %s(...), %s" % (ops.name, dtype.type)) 

Example 6

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 7

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= filled(domain(da, db), True)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 8

def copyto(dst, src, casting='same_kind', where=None):
    """Copies values from one array to another with broadcasting.

    This function can be called for arrays on different devices. In this case,
    casting, ``where``, and broadcasting is not supported, and an exception is
    raised if these are used.

    Args:
        dst (cupy.ndarray): Target array.
        src (cupy.ndarray): Source array.
        casting (str): Casting rule. See :func:`numpy.can_cast` for detail.
        where (cupy.ndarray of bool): If specified, this array acts as a mask,
            and an element is copied only if the corresponding element of
            ``where`` is True.

    .. seealso:: :func:`numpy.copyto`

    """
    if not numpy.can_cast(src.dtype, dst.dtype, casting):
        raise TypeError('Cannot cast %s to %s in %s casting mode' %
                        (src.dtype, dst.dtype, casting))
    if dst.size == 0:
        return

    if where is None:
        if _can_memcpy(dst, src):
            dst.data.copy_from(src.data, src.nbytes)
        else:
            core.elementwise_copy(src, dst)
    else:
        core.elementwise_copy_where(src, where, dst) 

Example 9

def __init__(self, name, *dimensions, data=None, kind=None):
        super(Field, self).__init__(name)
        self.__name = name
        self.dimensions = dimensions

        if kind is None:
            if data is None:
                self.kind = COMPLEX
            elif isinstance(data, (numpy.ndarray, numpy.number)):
                self.kind = DTYPE_KINDS[data.dtype.kind]
            elif isinstance(data, SCALAR_TYPES):
                self.kind = SCALAR_KINDS[type(data)]
        else:
            assert kind in (REAL, COMPLEX)
            self.kind = kind

        dtype = DEFAULT_DTYPES[self.kind]
        shape = tuple(d.grid.size for d in dimensions)

        if data is None:
            self.data = numpy.empty(shape, dtype)
        elif isinstance(data, SCALAR_TYPES):
            self.data = numpy.ones(shape, dtype) * numpy.array(data).astype(dtype)
        elif isinstance(data, numpy.ndarray):
            assert data.shape == shape
            assert numpy.can_cast(data.dtype, dtype)
            self.data = data.astype(dtype)
        else:
            raise ValueError 

Example 10

def replace(self, to_replace, value, inplace=False, filter=None,
                regex=False, mgr=None):
        to_replace_values = np.atleast_1d(to_replace)
        if not np.can_cast(to_replace_values, bool):
            return self
        return super(BoolBlock, self).replace(to_replace, value,
                                              inplace=inplace, filter=filter,
                                              regex=regex, mgr=mgr) 

Example 11

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 12

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 13

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= filled(domain(da, db), True)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        masked_result._update_from(result)
        return masked_result 

Example 14

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 15

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= filled(domain(da, db), True)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 16

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 17

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= domain(da, db)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 18

def perform(self, node, inp, out_):
        x, i = inp
        out, = out_
        # Copy always implied by numpy advanced indexing semantic.
        if out[0] is not None and out[0].shape == (len(i),) + x.shape[1:]:
            o = out[0]
        else:
            o = None

        # If i.dtype is more precise than numpy.intp (int32 on 32-bit machines,
        # int64 on 64-bit machines), numpy may raise the following error:
        # TypeError: array cannot be safely cast to required type.
        # We need to check if values in i can fit in numpy.intp, because
        # if they don't, that should be an error (no array can have that
        # many elements on a 32-bit arch).
        if i.dtype != numpy.intp:
            i_ = theano._asarray(i, dtype=numpy.intp)
            if not numpy.can_cast(i.dtype, numpy.intp):
                # Check if there was actually an incorrect conversion
                if numpy.any(i != i_):
                    raise IndexError(
                        'index contains values that are bigger '
                        'than the maximum array size on this system.', i)
            i = i_

        out[0] = x.take(i, axis=0, out=o) 

Example 19

def print_cancast_table(ntypes):
    print('X', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        print(row, end=' ')
        for col in ntypes:
            print(int(np.can_cast(row, col)), end=' ')
        print() 

Example 20

def __call__(self, a, b, *args, **kwargs):
        "Execute the call behavior."
        # Get the data
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate(divide='ignore', invalid='ignore'):
            result = self.f(da, db, *args, **kwargs)
        # Get the mask as a combination of the source masks and invalid
        m = ~umath.isfinite(result)
        m |= getmask(a)
        m |= getmask(b)
        # Apply the domain
        domain = ufunc_domain.get(self.f, None)
        if domain is not None:
            m |= filled(domain(da, db), True)
        # Take care of the scalar case first
        if (not m.ndim):
            if m:
                return masked
            else:
                return result
        # When the mask is True, put back da if possible
        # any errors, just abort; impossible to guarantee masked values
        try:
            np.copyto(result, 0, casting='unsafe', where=m)
            # avoid using "*" since this may be overlaid
            masked_da = umath.multiply(m, da)
            # only add back if it can be cast safely
            if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                result += masked_da
        except:
            pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 21

def require_dataset(self, name, shape, dtype, exact=False, **kwds):
        """ Open a dataset, creating it if it doesn't exist.

        If keyword "exact" is False (default), an existing dataset must have
        the same shape and a conversion-compatible dtype to be returned.  If
        True, the shape and dtype must match exactly.

        Other dataset keywords (see create_dataset) may be provided, but are
        only used if a new dataset is to be created.

        Raises TypeError if an incompatible object already exists, or if the
        shape or dtype don't match according to the above rules.
        """

        with phil:
            if not name in self:
                return self.create_dataset(name, *(shape, dtype), **kwds)

            dset = self[name]
            if not isinstance(dset, Dataset):
                raise TypeError("Incompatible object (%s) already exists" % dset.__class__.__name__)

            if not shape == dset.shape:
                raise TypeError("Shapes do not match (existing %s vs new %s)" % (dset.shape, shape))

            if exact:
                if not dtype == dset.dtype:
                    raise TypeError("Datatypes do not exactly match (existing %s vs new %s)" % (dset.dtype, dtype))
            elif not numpy.can_cast(dtype, dset.dtype):
                raise TypeError("Datatypes cannot be safely cast (existing %s vs new %s)" % (dset.dtype, dtype))

            return dset 

Example 22

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 23

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 24

def copyto(dst, src, casting='same_kind', where=None):
    """Copies values from one array to another with broadcasting.

    This function can be called for arrays on different devices. In this case,
    casting, ``where``, and broadcasting is not supported, and an exception is
    raised if these are used.

    Args:
        dst (cupy.ndarray): Target array.
        src (cupy.ndarray): Source array.
        casting (str): Casting rule. See :func:`numpy.can_cast` for detail.
        where (cupy.ndarray of bool): If specified, this array acts as a mask,
            and an element is copied only if the corresponding element of
            ``where`` is True.

    .. seealso:: :func:`numpy.copyto`

    """

    src_type = type(src)
    src_is_python_scalar = (src_type in six.integer_types or
                            src_type in (bool, float, complex))
    if src_is_python_scalar:
        src_dtype = numpy.dtype(type(src))
        can_cast = numpy.can_cast(src, dst.dtype, casting)
    else:
        src_dtype = src.dtype
        can_cast = numpy.can_cast(src_dtype, dst.dtype, casting)

    if not can_cast:
        raise TypeError('Cannot cast %s to %s in %s casting mode' %
                        (src_dtype, dst.dtype, casting))
    if dst.size == 0:
        return

    if src_is_python_scalar:
        dst.fill(src)
        return

    if where is None:
        if _can_memcpy(dst, src):
            dst.data.copy_from(src.data, src.nbytes)
        else:
            device = dst.device
            with device:
                if src.device != device:
                    src = src.copy()
                core.elementwise_copy(src, dst)
    else:
        core.elementwise_copy_where(src, where, dst) 

Example 25

def set_dtype(self, value, check=True):
        """Change data type of the bin contents.

        Allowed conversions:
        - from integral to float types
        - between the same category of type (float/integer)
        - from float types to integer if weights are trivial

        Parameters
        ----------
        value: np.dtype or something convertible to it.
        check: bool
            If True (default), all values are checked against the limits
        """

        # TODO: Refactor out?
        # TODO? Deal with unsigned types
        value = np.dtype(value)

        if value == self.dtype:
            return    # No change

        if value.kind in "iu":
            type_info = np.iinfo(value)
        elif value.kind == "f":
            type_info = np.finfo(value)
        else:
            raise RuntimeError("Unsupported dtype. Only integer/floating-point types are supported.")

        if np.can_cast(self.dtype, value):
            pass    # Ok
        elif check:
            if np.issubdtype(value, np.integer):
                if self.dtype.kind == "f":
                    for array in (self._frequencies, self._errors2):
                        if np.any(array % 1.0):
                            raise RuntimeError("Data contain non-integer values.")
            for array in (self._frequencies, self._errors2):
                if np.any((array > type_info.max) | (array < type_info.min)):
                    raise RuntimeError("Data contain values outside the specified range.")

        self._dtype = value
        self._frequencies = self._frequencies.astype(value)
        self._errors2 = self._errors2.astype(value)
        self._missed = self._missed.astype(value) 

Example 26

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 27

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 28

def __init__(self, value, shape=None, dtype=None):
        """
        Create a new lazy array.

        `value` : may be an int, long, float, bool, NumPy array, iterator,
                  generator or a function, `f(i)` or `f(i,j)`, depending on the
                  dimensions of the array.

        `f(i,j)` should return a single number when `i` and `j` are integers,
        and a 1D array when either `i` or `j` or both is a NumPy array (in the
        latter case the two arrays must have equal lengths).
        """

        self.dtype = dtype
        self.operations = []
        if isinstance(value, basestring):
            raise TypeError("An larray cannot be created from a string")
        elif isinstance(value, larray):
            if shape is not None and value.shape is not None:
                assert shape == value.shape
            self._shape = shape or value.shape
            self.base_value = value.base_value
            self.dtype = dtype or value.dtype
            self.operations = value.operations  # should deepcopy?
      
        elif isinstance(value, collections.Sized):  # False for numbers, generators, functions, iterators
            if have_scipy and sparse.issparse(value):  # For sparse matrices
                self.dtype = dtype or value.dtype                           
            elif not isinstance(value, numpy.ndarray):  
                value = numpy.array(value, dtype=dtype)
            elif dtype is not None:
               assert numpy.can_cast(value.dtype, dtype, casting='safe')  # or could convert value to the provided dtype
            if shape and value.shape != shape:
                raise ValueError("Array has shape %s, value has shape %s" % (shape, value.shape))
            self._shape = value.shape
            self.base_value = value
    
        else:
            assert numpy.isreal(value)  # also True for callables, generators, iterators
            self._shape = shape
            if dtype is None or isinstance(value, dtype):
                self.base_value = value
            else:
                try:
                    self.base_value = dtype(value)
                except TypeError:
                    self.base_value = value 

Example 29

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 30

def test_datetime_casting_rules(self):
        # Cannot cast safely/same_kind between timedelta and datetime
        assert_(not np.can_cast('m8', 'M8', casting='same_kind'))
        assert_(not np.can_cast('M8', 'm8', casting='same_kind'))
        assert_(not np.can_cast('m8', 'M8', casting='safe'))
        assert_(not np.can_cast('M8', 'm8', casting='safe'))

        # Can cast safely/same_kind from integer to timedelta
        assert_(np.can_cast('i8', 'm8', casting='same_kind'))
        assert_(np.can_cast('i8', 'm8', casting='safe'))

        # Cannot cast safely/same_kind from float to timedelta
        assert_(not np.can_cast('f4', 'm8', casting='same_kind'))
        assert_(not np.can_cast('f4', 'm8', casting='safe'))

        # Cannot cast safely/same_kind from integer to datetime
        assert_(not np.can_cast('i8', 'M8', casting='same_kind'))
        assert_(not np.can_cast('i8', 'M8', casting='safe'))

        # Cannot cast safely/same_kind from bool to datetime
        assert_(not np.can_cast('b1', 'M8', casting='same_kind'))
        assert_(not np.can_cast('b1', 'M8', casting='safe'))
        # Can cast safely/same_kind from bool to timedelta
        assert_(np.can_cast('b1', 'm8', casting='same_kind'))
        assert_(np.can_cast('b1', 'm8', casting='safe'))

        # Can cast datetime safely from months/years to days
        assert_(np.can_cast('M8[M]', 'M8[D]', casting='safe'))
        assert_(np.can_cast('M8[Y]', 'M8[D]', casting='safe'))
        # Cannot cast timedelta safely from months/years to days
        assert_(not np.can_cast('m8[M]', 'm8[D]', casting='safe'))
        assert_(not np.can_cast('m8[Y]', 'm8[D]', casting='safe'))
        # Can cast datetime same_kind from months/years to days
        assert_(np.can_cast('M8[M]', 'M8[D]', casting='same_kind'))
        assert_(np.can_cast('M8[Y]', 'M8[D]', casting='same_kind'))
        # Can't cast timedelta same_kind from months/years to days
        assert_(not np.can_cast('m8[M]', 'm8[D]', casting='same_kind'))
        assert_(not np.can_cast('m8[Y]', 'm8[D]', casting='same_kind'))
        # Can't cast datetime same_kind across the date/time boundary
        assert_(not np.can_cast('M8[D]', 'M8[h]', casting='same_kind'))
        assert_(not np.can_cast('M8[h]', 'M8[D]', casting='same_kind'))
        # Can cast timedelta same_kind across the date/time boundary
        assert_(np.can_cast('m8[D]', 'm8[h]', casting='same_kind'))
        assert_(np.can_cast('m8[h]', 'm8[D]', casting='same_kind'))

        # Cannot cast safely if the integer multiplier doesn't divide
        assert_(not np.can_cast('M8[7h]', 'M8[3h]', casting='safe'))
        assert_(not np.can_cast('M8[3h]', 'M8[6h]', casting='safe'))
        # But can cast same_kind
        assert_(np.can_cast('M8[7h]', 'M8[3h]', casting='same_kind'))
        # Can cast safely if the integer multiplier does divide
        assert_(np.can_cast('M8[6h]', 'M8[3h]', casting='safe')) 

Example 31

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        masked_result._update_from(result)
        return masked_result 

Example 32

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 33

def test_datetime_casting_rules(self):
        # Cannot cast safely/same_kind between timedelta and datetime
        assert_(not np.can_cast('m8', 'M8', casting='same_kind'))
        assert_(not np.can_cast('M8', 'm8', casting='same_kind'))
        assert_(not np.can_cast('m8', 'M8', casting='safe'))
        assert_(not np.can_cast('M8', 'm8', casting='safe'))

        # Can cast safely/same_kind from integer to timedelta
        assert_(np.can_cast('i8', 'm8', casting='same_kind'))
        assert_(np.can_cast('i8', 'm8', casting='safe'))

        # Cannot cast safely/same_kind from float to timedelta
        assert_(not np.can_cast('f4', 'm8', casting='same_kind'))
        assert_(not np.can_cast('f4', 'm8', casting='safe'))

        # Cannot cast safely/same_kind from integer to datetime
        assert_(not np.can_cast('i8', 'M8', casting='same_kind'))
        assert_(not np.can_cast('i8', 'M8', casting='safe'))

        # Cannot cast safely/same_kind from bool to datetime
        assert_(not np.can_cast('b1', 'M8', casting='same_kind'))
        assert_(not np.can_cast('b1', 'M8', casting='safe'))
        # Can cast safely/same_kind from bool to timedelta
        assert_(np.can_cast('b1', 'm8', casting='same_kind'))
        assert_(np.can_cast('b1', 'm8', casting='safe'))

        # Can cast datetime safely from months/years to days
        assert_(np.can_cast('M8[M]', 'M8[D]', casting='safe'))
        assert_(np.can_cast('M8[Y]', 'M8[D]', casting='safe'))
        # Cannot cast timedelta safely from months/years to days
        assert_(not np.can_cast('m8[M]', 'm8[D]', casting='safe'))
        assert_(not np.can_cast('m8[Y]', 'm8[D]', casting='safe'))
        # Can cast datetime same_kind from months/years to days
        assert_(np.can_cast('M8[M]', 'M8[D]', casting='same_kind'))
        assert_(np.can_cast('M8[Y]', 'M8[D]', casting='same_kind'))
        # Can't cast timedelta same_kind from months/years to days
        assert_(not np.can_cast('m8[M]', 'm8[D]', casting='same_kind'))
        assert_(not np.can_cast('m8[Y]', 'm8[D]', casting='same_kind'))
        # Can't cast datetime same_kind across the date/time boundary
        assert_(not np.can_cast('M8[D]', 'M8[h]', casting='same_kind'))
        assert_(not np.can_cast('M8[h]', 'M8[D]', casting='same_kind'))
        # Can cast timedelta same_kind across the date/time boundary
        assert_(np.can_cast('m8[D]', 'm8[h]', casting='same_kind'))
        assert_(np.can_cast('m8[h]', 'm8[D]', casting='same_kind'))

        # Cannot cast safely if the integer multiplier doesn't divide
        assert_(not np.can_cast('M8[7h]', 'M8[3h]', casting='safe'))
        assert_(not np.can_cast('M8[3h]', 'M8[6h]', casting='safe'))
        # But can cast same_kind
        assert_(np.can_cast('M8[7h]', 'M8[3h]', casting='same_kind'))
        # Can cast safely if the integer multiplier does divide
        assert_(np.can_cast('M8[6h]', 'M8[3h]', casting='safe')) 

Example 34

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        masked_result._update_from(result)
        return masked_result 

Example 35

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 36

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 

Example 37

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        # New in 1.12: This behavior changes in 1.13, test for dep warning
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        with assert_warns(FutureWarning):
            c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 38

def require_dataset(self, name, shape=None, dtype=None, exact=False,
                        data=None, fillvalue=None):
        if name not in self:
            return self.create_dataset(
                name,
                shape=shape,
                dtype=dtype,
                data=data,
                fillvalue=fillvalue
            )

        current_object = self[name]

        if not isinstance(current_object, ds.Dataset):
            raise TypeError(
                "Incompatible object already exists: {}".format(
                    current_object.__class__.__name__
                )
            )

        data, attrs, meta = ds._prepare_write(data, self.plugin_manager.dataset_plugins.write_order)

        # TODO verify proper attributes

        _assert_data_shape_dtype_match(data, shape, dtype)
        shape, dtype = _data_to_shape_and_dtype(data, shape, dtype)

        if not np.array_equal(shape, current_object.shape):
            raise TypeError(
                "Shapes do not match (existing {} vs "
                "new {})".format(current_object.shape, shape)
            )

        if dtype != current_object.dtype:
            if exact:
                raise TypeError(
                    "Datatypes do not exactly match "
                    "existing {} vs new {})".format(current_object.dtype, dtype)
                )

            if not np.can_cast(dtype, current_object.dtype):
                raise TypeError(
                    "Cannot safely cast from {} to {}".format(
                        dtype,
                        current_object.dtype
                    )
                )

        return current_object 

Example 39

def test_casting(self):
        # Check that casting a structured array to change its byte order
        # works
        a = np.array([(1,)], dtype=[('a', '<i4')])
        assert_(np.can_cast(a.dtype, [('a', '>i4')], casting='unsafe'))
        b = a.astype([('a', '>i4')])
        assert_equal(b, a.byteswap().newbyteorder())
        assert_equal(a['a'][0], b['a'][0])

        # Check that equality comparison works on structured arrays if
        # they are 'equiv'-castable
        a = np.array([(5, 42), (10, 1)], dtype=[('a', '>i4'), ('b', '<f8')])
        b = np.array([(42, 5), (1, 10)], dtype=[('b', '>f8'), ('a', '<i4')])
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        assert_equal(a == b, [True, True])

        # Check that 'equiv' casting can reorder fields and change byte
        # order
        assert_(np.can_cast(a.dtype, b.dtype, casting='equiv'))
        c = a.astype(b.dtype, casting='equiv')
        assert_equal(a == c, [True, True])

        # Check that 'safe' casting can change byte order and up-cast
        # fields
        t = [('a', '<i8'), ('b', '>f8')]
        assert_(np.can_cast(a.dtype, t, casting='safe'))
        c = a.astype(t, casting='safe')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that 'same_kind' casting can change byte order and
        # change field widths within a "kind"
        t = [('a', '<i4'), ('b', '>f4')]
        assert_(np.can_cast(a.dtype, t, casting='same_kind'))
        c = a.astype(t, casting='same_kind')
        assert_equal((c == np.array([(5, 42), (10, 1)], dtype=t)),
                     [True, True])

        # Check that casting fails if the casting rule should fail on
        # any of the fields
        t = [('a', '>i8'), ('b', '<f4')]
        assert_(not np.can_cast(a.dtype, t, casting='safe'))
        assert_raises(TypeError, a.astype, t, casting='safe')
        t = [('a', '>i2'), ('b', '<f8')]
        assert_(not np.can_cast(a.dtype, t, casting='equiv'))
        assert_raises(TypeError, a.astype, t, casting='equiv')
        t = [('a', '>i8'), ('b', '<i2')]
        assert_(not np.can_cast(a.dtype, t, casting='same_kind'))
        assert_raises(TypeError, a.astype, t, casting='same_kind')
        assert_(not np.can_cast(a.dtype, b.dtype, casting='no'))
        assert_raises(TypeError, a.astype, b.dtype, casting='no')

        # Check that non-'unsafe' casting can't change the set of field names
        for casting in ['no', 'safe', 'equiv', 'same_kind']:
            t = [('a', '>i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting))
            t = [('a', '>i4'), ('b', '<f8'), ('c', 'i4')]
            assert_(not np.can_cast(a.dtype, t, casting=casting)) 

Example 40

def __call__(self, a, b, *args, **kwargs):
        """
        Execute the call behavior.

        """
        # Get the data, as ndarray
        (da, db) = (getdata(a), getdata(b))
        # Get the result
        with np.errstate():
            np.seterr(divide='ignore', invalid='ignore')
            result = self.f(da, db, *args, **kwargs)
        # Get the mask for the result
        (ma, mb) = (getmask(a), getmask(b))
        if ma is nomask:
            if mb is nomask:
                m = nomask
            else:
                m = umath.logical_or(getmaskarray(a), mb)
        elif mb is nomask:
            m = umath.logical_or(ma, getmaskarray(b))
        else:
            m = umath.logical_or(ma, mb)

        # Case 1. : scalar
        if not result.ndim:
            if m:
                return masked
            return result

        # Case 2. : array
        # Revert result to da where masked
        if m is not nomask and m.any():
            # any errors, just abort; impossible to guarantee masked values
            try:
                np.copyto(result, 0, casting='unsafe', where=m)
                # avoid using "*" since this may be overlaid
                masked_da = umath.multiply(m, da)
                # only add back if it can be cast safely
                if np.can_cast(masked_da.dtype, result.dtype, casting='safe'):
                    result += masked_da
            except:
                pass

        # Transforms to a (subclass of) MaskedArray
        masked_result = result.view(get_masked_subclass(a, b))
        masked_result._mask = m
        if isinstance(a, MaskedArray):
            masked_result._update_from(a)
        elif isinstance(b, MaskedArray):
            masked_result._update_from(b)
        return masked_result 
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