Python numpy.unsignedinteger() Examples

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_gcd_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.gcd(a, b), [4, 40])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.gcd(a, b), [4]*4)

        # reduce
        a = np.array([15, 25, 35], dtype=dtype)
        assert_equal(np.gcd.reduce(a), 5)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.gcd(a, b), [20,  1,  2,  1,  4,  5]) 

def _test_lcm_inner(self, dtype):
        # basic use
        a = np.array([12, 120], dtype=dtype)
        b = np.array([20, 200], dtype=dtype)
        assert_equal(np.lcm(a, b), [60, 600])

        if not issubclass(dtype, np.unsignedinteger):
            # negatives are ignored
            a = np.array([12, -12,  12, -12], dtype=dtype)
            b = np.array([20,  20, -20, -20], dtype=dtype)
            assert_equal(np.lcm(a, b), [60]*4)

        # reduce
        a = np.array([3, 12, 20], dtype=dtype)
        assert_equal(np.lcm.reduce([3, 12, 20]), 60)

        # broadcasting, and a test including 0
        a = np.arange(6).astype(dtype)
        b = 20
        assert_equal(np.lcm(a, b), [0, 20, 20, 60, 20, 20]) 

def _checksum(fname, buffer_size=512 * 1024, dtype='uint64'):
    # https://github.com/airware/buzzard/pull/39/#discussion_r239071556
    dtype = np.dtype(dtype)
    dtypesize = dtype.itemsize
    assert buffer_size % dtypesize == 0
    assert np.issubdtype(dtype, np.unsignedinteger)

    acc = dtype.type(0)
    with open(fname, "rb") as f:
        with np.warnings.catch_warnings():
            np.warnings.filterwarnings('ignore', r'overflow encountered')

            for chunk in iter(lambda: f.read(buffer_size), b""):
                head = np.frombuffer(chunk, dtype, count=len(chunk) // dtypesize)
                head = np.add.reduce(head, dtype=dtype, initial=acc)
                acc += head

                tailsize = len(chunk) % dtypesize
                if tailsize > 0:
                    # This should only be needed for file's tail
                    tail = chunk[-tailsize:] + b'\0' * (dtypesize - tailsize)
                    tail = np.frombuffer(tail, dtype)
                    acc += tail
        return '{:016x}'.format(acc.item()) 

def _checksum(fname, buffer_size=512 * 1024, dtype='uint64'):
    # https://github.com/airware/buzzard/pull/39/#discussion_r239071556
    dtype = np.dtype(dtype)
    dtypesize = dtype.itemsize
    assert buffer_size % dtypesize == 0
    assert np.issubdtype(dtype, np.unsignedinteger)

    acc = dtype.type(0)
    with open(fname, "rb") as f:
        with np.warnings.catch_warnings():
            np.warnings.filterwarnings('ignore', r'overflow encountered')

            for chunk in iter(lambda: f.read(buffer_size), b""):
                head = np.frombuffer(chunk, dtype, count=len(chunk) // dtypesize)
                head = np.add.reduce(head, dtype=dtype, initial=acc)
                acc += head

                tailsize = len(chunk) % dtypesize
                if tailsize > 0:
                    # This should only be needed for file's tail
                    tail = chunk[-tailsize:] + b'\0' * (dtypesize - tailsize)
                    tail = np.frombuffer(tail, dtype)
                    acc += tail
        return '{:016x}'.format(acc.item()) 

def test_abstract(self):
        assert_(issubclass(np.number, numbers.Number))

        assert_(issubclass(np.inexact, numbers.Complex))
        assert_(issubclass(np.complexfloating, numbers.Complex))
        assert_(issubclass(np.floating, numbers.Real))

        assert_(issubclass(np.integer, numbers.Integral))
        assert_(issubclass(np.signedinteger, numbers.Integral))
        assert_(issubclass(np.unsignedinteger, numbers.Integral)) 

def dtype_to_schema(typ):
    result = None
    if typ is bool or np.issubdtype(typ, np.bool_):
        result = {'type': 'boolean'}
    elif np.issubdtype(typ, np.unsignedinteger):
        result = {'type': 'integer', 'minimum': 0}
    elif np.issubdtype(typ, np.integer):
        result = {'type': 'integer'}
    elif np.issubdtype(typ, np.number):
        result = {'type': 'number'}
    elif np.issubdtype(typ, np.string_) or np.issubdtype(typ, np.unicode_):
        result = {'type': 'string'}
    elif isinstance(typ, np.dtype):
        if typ.fields:
            props = {k: dtype_to_schema(t) for k, t in typ.fields.items()}
            result = {'type': 'object', 'properties': props}
        elif typ.shape:
            result = shape_and_dtype_to_schema(typ.shape, typ.subdtype)
        elif np.issubdtype(typ, np.object_):
            result = {'type': 'string'}
        else:
            assert False, f'unexpected dtype {typ}'
    else:
        assert False, f'unexpected non-dtype {typ}'
    lale.type_checking.validate_is_schema(result)
    return result 

def _assert_safe_casting(cls, data, subarr):
        """
        Ensure incoming data can be represented as uints.
        """
        if not issubclass(data.dtype.type, np.unsignedinteger):
            if not np.array_equal(data, subarr):
                raise TypeError('Unsafe NumPy casting, you must '
                                'explicitly cast') 

def _safely_castable_to_int(dt):
    """Test whether the numpy data type `dt` can be safely cast to an int."""
    int_size = np.dtype(int).itemsize
    safe = ((np.issubdtype(dt, int) and dt.itemsize <= int_size) or
            (np.issubdtype(dt, np.unsignedinteger) and dt.itemsize < int_size))
    return safe 

def _validate_array(a):
    if a.ndim != 2:
        if a.ndim != 3 or a.shape[2] > 4 or a.shape[2] == 0:
            raise ValueError("array must be 2D, or 3D with shape "
                             "(m, n, d) with 1 <= d <= 4.")
    itemsize = a.dtype.itemsize
    if not _np.issubdtype(a.dtype, _np.unsignedinteger) or itemsize > 2:
        raise ValueError("array must be an array of 8- or 16-bit "
                         "unsigned integers")


# Notes on color_type:
#
#  color_type   meaning                    tRNS chunk contents (optional)
#  ----------   ------------------------   --------------------------------
#      0        grayscale                  Single gray level value, 2 bytes
#      2        RGB                        Single RGB, 2 bytes per channel
#      3        8 bit indexed RGB or RGBA  Series of 1 byte alpha values
#      4        Grayscale and alpha
#      6        RGBA
#
#
# from http://www.w3.org/TR/PNG/:
# Table 11.1 - Allowed combinations of colour type and bit depth
#
#                      Color  Allowed
# PNG image type       type  bit depths      Interpretation
# Greyscale              0   1, 2, 4, 8, 16  Each pixel is a greyscale
#                                            sample
# Truecolour             2   8, 16           Each pixel is an RGB triple
# Indexed-colour         3   1, 2, 4, 8      Each pixel is a palette index;
#                                            a PLTE chunk shall appear.
# Greyscale with alpha   4   8, 16           Each pixel is a greyscale
#                                            sample followed by an alpha
#                                            sample.
# Truecolour with alpha  6   8, 16           Each pixel is an RGB triple
#                                            followed by an alpha sample. 

def _assert_safe_casting(cls, data, subarr):
        """
        Ensure incoming data can be represented as uints.
        """
        if not issubclass(data.dtype.type, np.unsignedinteger):
            if not np.array_equal(data, subarr):
                raise TypeError('Unsafe NumPy casting, you must '
                                'explicitly cast') 

def is_unsigned_integer_dtype(arr_or_dtype):
    """
    Check whether the provided array or dtype is of an unsigned integer dtype.

    Parameters
    ----------
    arr_or_dtype : array-like
        The array or dtype to check.

    Returns
    -------
    boolean : Whether or not the array or dtype is of an
              unsigned integer dtype.

    Examples
    --------
    >>> is_unsigned_integer_dtype(str)
    False
    >>> is_unsigned_integer_dtype(int)  # signed
    False
    >>> is_unsigned_integer_dtype(float)
    False
    >>> is_unsigned_integer_dtype(np.uint64)
    True
    >>> is_unsigned_integer_dtype(np.array(['a', 'b']))
    False
    >>> is_unsigned_integer_dtype(pd.Series([1, 2]))  # signed
    False
    >>> is_unsigned_integer_dtype(pd.Index([1, 2.]))  # float
    False
    >>> is_unsigned_integer_dtype(np.array([1, 2], dtype=np.uint32))
    True
    """

    if arr_or_dtype is None:
        return False
    tipo = _get_dtype_type(arr_or_dtype)
    return (issubclass(tipo, np.unsignedinteger) and
            not issubclass(tipo, (np.datetime64, np.timedelta64))) 

def _parse_sklearn_classifier(scope, model, inputs, custom_parsers=None):
    probability_tensor = _parse_sklearn_simple_model(
            scope, model, inputs, custom_parsers=custom_parsers)
    if model.__class__ in [NuSVC, SVC] and not model.probability:
        return probability_tensor
    options = scope.get_options(model, dict(zipmap=True))
    if not options['zipmap']:
        return probability_tensor
    this_operator = scope.declare_local_operator('SklearnZipMap')
    this_operator.inputs = probability_tensor
    label_type = Int64TensorType([None])
    classes = get_label_classes(scope, model)

    if (isinstance(model.classes_, list) and
            isinstance(model.classes_[0], np.ndarray)):
        # multi-label problem
        pass
    elif np.issubdtype(classes.dtype, np.floating):
        classes = np.array(list(map(lambda x: int(x), classes)))
        if set(map(lambda x: float(x), classes)) != set(model.classes_):
            raise RuntimeError("skl2onnx implicitly converts float class "
                               "labels into integers but at least one label "
                               "is not an integer. Class labels should "
                               "be integers or strings.")
        this_operator.classlabels_int64s = classes
    elif np.issubdtype(classes.dtype, np.signedinteger):
        this_operator.classlabels_int64s = classes
    elif np.issubdtype(classes.dtype, np.unsignedinteger):
        this_operator.classlabels_int64s = classes
    else:
        classes = np.array([s.encode('utf-8') for s in classes])
        this_operator.classlabels_strings = classes
        label_type = StringTensorType([None])

    output_label = scope.declare_local_variable('output_label', label_type)
    output_probability = scope.declare_local_variable(
        'output_probability',
        SequenceType(DictionaryType(label_type, scope.tensor_type())))
    this_operator.outputs.append(output_label)
    this_operator.outputs.append(output_probability)
    return this_operator.outputs 

def is_unsigned_integer_dtype(arr_or_dtype):
    """
    Check whether the provided array or dtype is of an unsigned integer dtype.

    Parameters
    ----------
    arr_or_dtype : array-like
        The array or dtype to check.

    Returns
    -------
    boolean : Whether or not the array or dtype is of an
              unsigned integer dtype.

    Examples
    --------
    >>> is_unsigned_integer_dtype(str)
    False
    >>> is_unsigned_integer_dtype(int)  # signed
    False
    >>> is_unsigned_integer_dtype(float)
    False
    >>> is_unsigned_integer_dtype(np.uint64)
    True
    >>> is_unsigned_integer_dtype(np.array(['a', 'b']))
    False
    >>> is_unsigned_integer_dtype(pd.Series([1, 2]))  # signed
    False
    >>> is_unsigned_integer_dtype(pd.Index([1, 2.]))  # float
    False
    >>> is_unsigned_integer_dtype(np.array([1, 2], dtype=np.uint32))
    True
    """

    if arr_or_dtype is None:
        return False
    tipo = _get_dtype_type(arr_or_dtype)
    return (issubclass(tipo, np.unsignedinteger) and
            not issubclass(tipo, (np.datetime64, np.timedelta64))) 

def test_abstract(self):
        assert_(issubclass(np.number, numbers.Number))

        assert_(issubclass(np.inexact, numbers.Complex))
        assert_(issubclass(np.complexfloating, numbers.Complex))
        assert_(issubclass(np.floating, numbers.Real))

        assert_(issubclass(np.integer, numbers.Integral))
        assert_(issubclass(np.signedinteger, numbers.Integral))
        assert_(issubclass(np.unsignedinteger, numbers.Integral)) 

def _assert_safe_casting(cls, data, subarr):
        """
        Ensure incoming data can be represented as uints.
        """
        if not issubclass(data.dtype.type, np.unsignedinteger):
            if not np.array_equal(data, subarr):
                raise TypeError('Unsafe NumPy casting, you must '
                                'explicitly cast') 

def test_abstract(self):
        assert_(issubclass(np.number, numbers.Number))

        assert_(issubclass(np.inexact, numbers.Complex))
        assert_(issubclass(np.complexfloating, numbers.Complex))
        assert_(issubclass(np.floating, numbers.Real))

        assert_(issubclass(np.integer, numbers.Integral))
        assert_(issubclass(np.signedinteger, numbers.Integral))
        assert_(issubclass(np.unsignedinteger, numbers.Integral))