Python numpy.obj2sctype() Examples

The following are 30 code examples of numpy.obj2sctype(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function .
Example #1
Source File: print_coercion_tables.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #2
Source File: print_coercion_tables.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #3
Source File: print_coercion_tables.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #4
Source File: print_coercion_tables.py    From coffeegrindsize with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #5
Source File: print_coercion_tables.py    From ImageFusion with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes: print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #6
Source File: print_coercion_tables.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #7
Source File: print_coercion_tables.py    From recruit with Apache License 2.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #8
Source File: print_coercion_tables.py    From pySINDy with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #9
Source File: print_coercion_tables.py    From Fluid-Designer with GNU General Public License v3.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes: print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #10
Source File: print_coercion_tables.py    From Carnets with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #11
Source File: print_coercion_tables.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #12
Source File: print_coercion_tables.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #13
Source File: print_coercion_tables.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #14
Source File: print_coercion_tables.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #15
Source File: print_coercion_tables.py    From Computable with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes: print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #16
Source File: print_coercion_tables.py    From vnpy_crypto with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #17
Source File: print_coercion_tables.py    From keras-lambda with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #18
Source File: print_coercion_tables.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #19
Source File: print_coercion_tables.py    From lambda-packs with MIT License 5 votes vote down vote up
def print_coercion_table(ntypes, inputfirstvalue, inputsecondvalue, firstarray, use_promote_types=False):
    print('+', end=' ')
    for char in ntypes:
        print(char, end=' ')
    print()
    for row in ntypes:
        if row == 'O':
            rowtype = GenericObject
        else:
            rowtype = np.obj2sctype(row)

        print(row, end=' ')
        for col in ntypes:
            if col == 'O':
                coltype = GenericObject
            else:
                coltype = np.obj2sctype(col)
            try:
                if firstarray:
                    rowvalue = np.array([rowtype(inputfirstvalue)], dtype=rowtype)
                else:
                    rowvalue = rowtype(inputfirstvalue)
                colvalue = coltype(inputsecondvalue)
                if use_promote_types:
                    char = np.promote_types(rowvalue.dtype, colvalue.dtype).char
                else:
                    value = np.add(rowvalue, colvalue)
                    if isinstance(value, np.ndarray):
                        char = value.dtype.char
                    else:
                        char = np.dtype(type(value)).char
            except ValueError:
                char = '!'
            except OverflowError:
                char = '@'
            except TypeError:
                char = '#'
            print(char, end=' ')
        print() 
Example #20
Source File: test_numeric.py    From pySINDy with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #21
Source File: test_numeric.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #22
Source File: test_numeric.py    From twitter-stock-recommendation with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #23
Source File: test_numeric.py    From coffeegrindsize with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #24
Source File: test_numeric.py    From keras-lambda with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #25
Source File: test_numeric.py    From elasticintel with GNU General Public License v3.0 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #26
Source File: test_numeric.py    From ImageFusion with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                        lambda a, b:a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                        lambda a, b:a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                        lambda a, b:a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                        lambda a, b:a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                        lambda a, b:a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                        lambda a, b:a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                        np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                        lambda a, b:a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                        lambda a, b:a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                        lambda a, b:a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                        lambda a, b:a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                        lambda a, b:a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                        lambda a, b:a*b, ftype(0), ftype(np.inf)) 
Example #27
Source File: test_numeric.py    From mxnet-lambda with Apache License 2.0 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #28
Source File: test_numeric.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #29
Source File: test_numeric.py    From GraphicDesignPatternByPython with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf)) 
Example #30
Source File: test_numeric.py    From Mastering-Elasticsearch-7.0 with MIT License 4 votes vote down vote up
def test_floating_exceptions(self):
        # Test basic arithmetic function errors
        with np.errstate(all='raise'):
            # Test for all real and complex float types
            for typecode in np.typecodes['AllFloat']:
                ftype = np.obj2sctype(typecode)
                if np.dtype(ftype).kind == 'f':
                    # Get some extreme values for the type
                    fi = np.finfo(ftype)
                    ft_tiny = fi.tiny
                    ft_max = fi.max
                    ft_eps = fi.eps
                    underflow = 'underflow'
                    divbyzero = 'divide by zero'
                else:
                    # 'c', complex, corresponding real dtype
                    rtype = type(ftype(0).real)
                    fi = np.finfo(rtype)
                    ft_tiny = ftype(fi.tiny)
                    ft_max = ftype(fi.max)
                    ft_eps = ftype(fi.eps)
                    # The complex types raise different exceptions
                    underflow = ''
                    divbyzero = ''
                overflow = 'overflow'
                invalid = 'invalid'

                self.assert_raises_fpe(underflow,
                                       lambda a, b: a/b, ft_tiny, ft_max)
                self.assert_raises_fpe(underflow,
                                       lambda a, b: a*b, ft_tiny, ft_tiny)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a*b, ft_max, ftype(2))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a/b, ft_max, ftype(0.5))
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a+b, ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       lambda a, b: a-b, -ft_max, ft_max*ft_eps)
                self.assert_raises_fpe(overflow,
                                       np.power, ftype(2), ftype(2**fi.nexp))
                self.assert_raises_fpe(divbyzero,
                                       lambda a, b: a/b, ftype(1), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a/b, ftype(0), ftype(0))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a-b, ftype(np.inf), ftype(np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a+b, ftype(np.inf), ftype(-np.inf))
                self.assert_raises_fpe(invalid,
                                       lambda a, b: a*b, ftype(0), ftype(np.inf))