Python numpy.issubclass_() Examples

The following are 13 code examples of numpy.issubclass_(). 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: fitpack2.py    From lambda-packs with MIT License 6 votes vote down vote up 
def __init__(self, theta, phi, r, tt, tp, w=None, eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, np_ = 8 + len(tt), 8 + len(tp)
        tt_, tp_ = zeros((nt_,), float), zeros((np_,), float)
        tt_[4:-4], tp_[4:-4] = tt, tp
        tt_[-4:], tp_[-4:] = np.pi, 2. * np.pi
        tt_, tp_, c, fp, ier = dfitpack.spherfit_lsq(theta, phi, r, tt_, tp_,
                                                     w=w, eps=eps)
        if ier < -2:
            deficiency = 6 + (nt_ - 8) * (np_ - 7) + ier
            message = _spherefit_messages.get(-3) % (deficiency, -ier)
            warnings.warn(message)
        elif ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_, tp_, c
        self.degrees = (3, 3)
Example #2
Source File: fitpack2.py    From Computable with MIT License 6 votes vote down vote up 
def __init__(self, theta, phi, r, tt, tp, w=None, eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, np_ = 8 + len(tt), 8 + len(tp)
        tt_, tp_ = zeros((nt_,), float), zeros((np_,), float)
        tt_[4:-4], tp_[4:-4] = tt, tp
        tt_[-4:], tp_[-4:] = np.pi, 2. * np.pi
        tt_, tp_, c, fp, ier = dfitpack.spherfit_lsq(theta, phi, r, tt_, tp_,
                                                     w=w, eps=eps)
        if ier < -2:
            deficiency = 6 + (nt_ - 8) * (np_ - 7) + ier
            message = _spherefit_messages.get(-3) % (deficiency, -ier)
            warnings.warn(message)
        elif not ier in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)
        self.fp = fp
        self.tck = tt_, tp_, c
        self.degrees = (3, 3)
Example #3
Source File: attrs.py    From nata with MIT License 6 votes vote down vote up 
def __call__(self, instance, attribute, value):
        if isinstance(value, np.ndarray):
            value_type = value.dtype
        else:
            value_type = type(value)

        if self.dtype is not None and not np.issubdtype(value_type, self.dtype):
            # TODO: add better error message
            raise TypeError(
                f"Attribute '{attribute.name}' of {instance.__class__} "
                + f"must have dtype {self.dtype}"
            )

        if self.subclass is not None and not np.issubclass_(
            type(value), self.subclass
        ):
            # TODO: add better error message
            raise TypeError(
                f"Attribute '{attribute.name}' of {instance.__class__} "
                + f"must be of subclass {self.subclass}"
            )
Example #4
Source File: fitpack2.py    From GraphicDesignPatternByPython with MIT License 6 votes vote down vote up 
def __init__(self, theta, phi, r, tt, tp, w=None, eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, np_ = 8 + len(tt), 8 + len(tp)
        tt_, tp_ = zeros((nt_,), float), zeros((np_,), float)
        tt_[4:-4], tp_[4:-4] = tt, tp
        tt_[-4:], tp_[-4:] = np.pi, 2. * np.pi
        tt_, tp_, c, fp, ier = dfitpack.spherfit_lsq(theta, phi, r, tt_, tp_,
                                                     w=w, eps=eps)
        if ier < -2:
            deficiency = 6 + (nt_ - 8) * (np_ - 7) + ier
            message = _spherefit_messages.get(-3) % (deficiency, -ier)
            warnings.warn(message)
        elif ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_, tp_, c
        self.degrees = (3, 3)
Example #5
Source File: type_mapping.py    From coremltools with BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up 
def type_to_builtin_type(type):
    # Infer from numpy type if it is one
    if type.__module__ == np.__name__:
        return numpy_type_to_builtin_type(type)

    # Otherwise, try to infer from a few generic python types
    if np.issubclass_(type, bool):
        return types_bool
    elif np.issubclass_(type, six.integer_types):
        return types_int32
    elif np.issubclass_(type, six.string_types):
        return types_str
    elif np.issubclass_(type, float):
        return types_fp32
    else:
        raise TypeError("Could not determine builtin type for " + str(type))
Example #6
Source File: fitpack2.py    From Splunking-Crime with GNU Affero General Public License v3.0 6 votes vote down vote up 
def __init__(self, theta, phi, r, tt, tp, w=None, eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, np_ = 8 + len(tt), 8 + len(tp)
        tt_, tp_ = zeros((nt_,), float), zeros((np_,), float)
        tt_[4:-4], tp_[4:-4] = tt, tp
        tt_[-4:], tp_[-4:] = np.pi, 2. * np.pi
        tt_, tp_, c, fp, ier = dfitpack.spherfit_lsq(theta, phi, r, tt_, tp_,
                                                     w=w, eps=eps)
        if ier < -2:
            deficiency = 6 + (nt_ - 8) * (np_ - 7) + ier
            message = _spherefit_messages.get(-3) % (deficiency, -ier)
            warnings.warn(message)
        elif ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_, tp_, c
        self.degrees = (3, 3)
Example #7
Source File: fitpack2.py    From lambda-packs with MIT License 5 votes vote down vote up 
def __init__(self, theta, phi, r, w=None, s=0., eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, tt_, np_, tp_, c, fp, ier = dfitpack.spherfit_smth(theta, phi,
                                                                r, w=w, s=s,
                                                                eps=eps)
        if ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_[:nt_], tp_[:np_], c[:(nt_ - 4) * (np_ - 4)]
        self.degrees = (3, 3)
Example #8
Source File: fitpack2.py    From Computable with MIT License 5 votes vote down vote up 
def __init__(self, theta, phi, r, w=None, s=0., eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, tt_, np_, tp_, c, fp, ier = dfitpack.spherfit_smth(theta, phi,
                                                                r, w=w, s=s,
                                                                eps=eps)
        if not ier in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)
        self.fp = fp
        self.tck = tt_[:nt_], tp_[:np_], c[:(nt_ - 4) * (np_ - 4)]
        self.degrees = (3, 3)
Example #9
Source File: fitpack2.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def __init__(self, theta, phi, r, w=None, s=0., eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, tt_, np_, tp_, c, fp, ier = dfitpack.spherfit_smth(theta, phi,
                                                                r, w=w, s=s,
                                                                eps=eps)
        if ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_[:nt_], tp_[:np_], c[:(nt_ - 4) * (np_ - 4)]
        self.degrees = (3, 3)
Example #10
Source File: estimator.py    From IDTxl with GNU General Public License v3.0 5 votes vote down vote up 
def find_estimator(est):
    """Return estimator class.

    Return an estimator class. If input is a class, check if it implements
    methods 'estimate' and 'is_parallel' necessary for network analysis
    (see abstract class 'Estimator' for documentation). If input is a string,
    search for class with that name in IDTxl and return it.

    Args:
        est : str | Class
            name of an estimator class implemented in IDTxl or custom estimator
            class

    Returns
        Class
            Estimator class
    """
    if inspect.isclass(est):
        # Test if provided class implements the Estimator class. This
        # constraint may be relaxed in the future.
        if not np.issubclass_(est, Estimator):
            raise RuntimeError('Provided class should implement abstract class'
                               ' Estimator.')
        return est
    elif type(est) is str:
        module_list = _package_contents()
        estimator = None
        for m in module_list:
            try:
                module = importlib.import_module('.' + m, __package__)
                return getattr(module, est)
            except AttributeError:
                pass
        if not estimator:
            raise RuntimeError('Estimator {0} not found.'.format(est))
    else:
        raise TypeError('Please provide an estimator class or the name of an '
                        'estimator as string.')
Example #11
Source File: util.py    From holoviews with BSD 3-Clause "New" or "Revised" License 5 votes vote down vote up 
def numpy_scalar_to_python(scalar):
    """
    Converts a NumPy scalar to a regular python type.
    """
    scalar_type = type(scalar)
    if np.issubclass_(scalar_type, np.float_):
        return float(scalar)
    elif np.issubclass_(scalar_type, np.int_):
        return int(scalar)
    return scalar
Example #12
Source File: fitpack2.py    From Splunking-Crime with GNU Affero General Public License v3.0 5 votes vote down vote up 
def __init__(self, theta, phi, r, w=None, s=0., eps=1E-16):
        if np.issubclass_(w, float):
            w = ones(len(theta)) * w
        nt_, tt_, np_, tp_, c, fp, ier = dfitpack.spherfit_smth(theta, phi,
                                                                r, w=w, s=s,
                                                                eps=eps)
        if ier not in [0, -1, -2]:
            message = _spherefit_messages.get(ier, 'ier=%s' % (ier))
            raise ValueError(message)

        self.fp = fp
        self.tck = tt_[:nt_], tp_[:np_], c[:(nt_ - 4) * (np_ - 4)]
        self.degrees = (3, 3)
Example #13
Source File: type_mapping.py    From coremltools with BSD 3-Clause "New" or "Revised" License 4 votes vote down vote up 
def numpy_type_to_builtin_type(nptype):
    if type(nptype) == np.dtype:
        nptype = nptype.type

    if np.issubclass_(nptype, np.bool) or np.issubclass_(nptype, np.bool_):
        # numpy as 2 bool types it looks like. what is the difference?
        return types_bool
    elif np.issubclass_(nptype, np.int8):
        return types_int8
    elif np.issubclass_(nptype, np.int16):
        return types_int16
    elif np.issubclass_(nptype, np.int32):
        return types_int32
    elif np.issubclass_(nptype, np.int64):
        return types_int64
    elif np.issubclass_(nptype, np.uint8):
        return types_int8
    elif np.issubclass_(nptype, np.uint16):
        return types_int16
    elif np.issubclass_(nptype, np.uint32):
        return types_int32
    elif np.issubclass_(nptype, np.uint64):
        return types_int64
    elif np.issubclass_(nptype, np.int):
        # Catch all int
        return types_int32
    elif np.issubclass_(nptype, np.object_):
        # symbolic shape is considered int32
        return types_int32
    elif np.issubclass_(nptype, np.float16):
        return types_fp16
    elif np.issubclass_(nptype, np.float32) or np.issubclass_(nptype, np.single):
        return types_fp32
    elif np.issubclass_(nptype, np.float64) or np.issubclass_(nptype, np.double):
        return types_fp64
    elif (
        np.issubclass_(nptype, six.string_types)
        or np.issubclass_(nptype, np.string_)
        or np.issubclass_(nptype, np.str_)
    ):
        return types_str
    else:
        raise TypeError("Unsupported numpy type: %s" % (nptype))


# Tries to get the equivalent builtin type of a
# numpy or python type.