Python numpy.iterable() Examples

The following are 30 code examples for showing how to use numpy.iterable(). These examples are extracted from open source projects. 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.

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Example 1
Project: lattice   Author: tensorflow   File: estimators.py    License: Apache License 2.0 6 votes vote down vote up
def _verify_config(model_config, feature_columns):
  """Verifies that the config is setup correctly and ready for model_fn."""
  if feature_columns:
    feature_configs = [
        model_config.feature_config_by_name(feature_column.name)
        for feature_column in feature_columns
    ]
  else:
    feature_configs = model_config.feature_configs or []

  for feature_config in feature_configs:
    if not feature_config.num_buckets:
      if (not np.iterable(feature_config.pwl_calibration_input_keypoints) or
          any(not isinstance(x, float)
              for x in feature_config.pwl_calibration_input_keypoints)):
        raise ValueError(
            'Input keypoints are invalid for feature {}: {}'.format(
                feature_config.name,
                feature_config.pwl_calibration_input_keypoints))

  if (not np.iterable(model_config.output_initialization) or any(
      not isinstance(x, float) for x in model_config.output_initialization)):
    raise ValueError('Output initilization is invalid: {}'.format(
        model_config.output_initialization)) 
Example 2
Project: recruit   Author: Frank-qlu   File: stride_tricks.py    License: Apache License 2.0 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    it = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C')
    with it:
        # never really has writebackifcopy semantics
        broadcast = it.itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 3
Project: plydata   Author: has2k1   File: tidy.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def spread(verb):
    key = verb.key
    value = verb.value

    if isinstance(key, str) or not np.iterable(key):
        key = [key]

    if isinstance(value, str) or not np.iterable(key):
        value = [value]

    key_value = pd.Index(list(chain(key, value))).drop_duplicates()
    index = verb.data.columns.difference(key_value).tolist()
    data = pd.pivot_table(
        verb.data,
        values=value,
        index=index,
        columns=key,
        aggfunc=identity,
    )

    clean_indices(data, verb.sep, inplace=True)
    data = data.infer_objects()
    return data 
Example 4
Project: lambda-packs   Author: ryfeus   File: stride_tricks.py    License: MIT License 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    it = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C')
    with it:
        # never really has writebackifcopy semantics
        broadcast = it.itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 5
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: stride_tricks.py    License: MIT License 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    broadcast = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C').itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 6
Project: vnpy_crypto   Author: birforce   File: stride_tricks.py    License: MIT License 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    broadcast = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C').itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 7
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: stride_tricks.py    License: MIT License 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    it = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C')
    with it:
        # never really has writebackifcopy semantics
        broadcast = it.itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 8
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: units.py    License: MIT License 6 votes vote down vote up
def get_converter(self, x):
        """Get the converter interface instance for *x*, or None."""
        if hasattr(x, "values"):
            x = x.values  # Unpack pandas Series and DataFrames.
        if isinstance(x, np.ndarray):
            # In case x in a masked array, access the underlying data (only its
            # type matters).  If x is a regular ndarray, getdata() just returns
            # the array itself.
            x = np.ma.getdata(x).ravel()
            # If there are no elements in x, infer the units from its dtype
            if not x.size:
                return self.get_converter(np.array([0], dtype=x.dtype))
        try:  # Look up in the cache.
            return self[type(x)]
        except KeyError:
            try:  # If cache lookup fails, look up based on first element...
                first = cbook.safe_first_element(x)
            except (TypeError, StopIteration):
                pass
            else:
                # ... and avoid infinite recursion for pathological iterables
                # where indexing returns instances of the same iterable class.
                if type(first) is not type(x):
                    return self.get_converter(first)
        return None 
Example 9
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: colorbar.py    License: MIT License 6 votes vote down vote up
def set_ticks(self, ticks, update_ticks=True):
        """
        Set tick locations.

        Parameters
        ----------
        ticks : {None, sequence, :class:`~matplotlib.ticker.Locator` instance}
            If None, a default Locator will be used.

        update_ticks : {True, False}, optional
            If True, tick locations are updated immediately.  If False,
            use :meth:`update_ticks` to manually update the ticks.

        """
        if np.iterable(ticks):
            self.locator = ticker.FixedLocator(ticks, nbins=len(ticks))
        else:
            self.locator = ticks

        if update_ticks:
            self.update_ticks()
        self.stale = True 
Example 10
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: patches.py    License: MIT License 6 votes vote down vote up
def draw(self, renderer):
        if not self.get_visible():
            return

        # FancyArrowPatch has traditionally forced the capstyle and joinstyle.
        with cbook._setattr_cm(self, _capstyle='round', _joinstyle='round'), \
                self._bind_draw_path_function(renderer) as draw_path:

            # FIXME : dpi_cor is for the dpi-dependency of the linewidth. There
            # could be room for improvement.
            self.set_dpi_cor(renderer.points_to_pixels(1.))
            path, fillable = self.get_path_in_displaycoord()

            if not np.iterable(fillable):
                path = [path]
                fillable = [fillable]

            affine = transforms.IdentityTransform()

            for p, f in zip(path, fillable):
                draw_path(
                    p, affine,
                    self._facecolor if f and self._facecolor[3] else None) 
Example 11
Project: GraphicDesignPatternByPython   Author: Relph1119   File: stride_tricks.py    License: MIT License 6 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    it = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C')
    with it:
        # never really has writebackifcopy semantics
        broadcast = it.itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 12
Project: GraphicDesignPatternByPython   Author: Relph1119   File: ticker.py    License: MIT License 6 votes vote down vote up
def _validate_steps(steps):
        if not np.iterable(steps):
            raise ValueError('steps argument must be a sequence of numbers '
                             'from 1 to 10')
        steps = np.asarray(steps)
        if np.any(np.diff(steps) <= 0):
            raise ValueError('steps argument must be uniformly increasing')
        if steps[-1] > 10 or steps[0] < 1:
            warnings.warn('Steps argument should be a sequence of numbers\n'
                          'increasing from 1 to 10, inclusive. Behavior with\n'
                          'values outside this range is undefined, and will\n'
                          'raise a ValueError in future versions of mpl.')
        if steps[0] != 1:
            steps = np.hstack((1, steps))
        if steps[-1] != 10:
            steps = np.hstack((steps, 10))
        return steps 
Example 13
Project: python3_ios   Author: holzschu   File: ticker.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def _validate_steps(steps):
        if not np.iterable(steps):
            raise ValueError('steps argument must be a sequence of numbers '
                             'from 1 to 10')
        steps = np.asarray(steps)
        if np.any(np.diff(steps) <= 0):
            raise ValueError('steps argument must be uniformly increasing')
        if steps[-1] > 10 or steps[0] < 1:
            warnings.warn('Steps argument should be a sequence of numbers\n'
                          'increasing from 1 to 10, inclusive. Behavior with\n'
                          'values outside this range is undefined, and will\n'
                          'raise a ValueError in future versions of mpl.')
        if steps[0] != 1:
            steps = np.hstack((1, steps))
        if steps[-1] != 10:
            steps = np.hstack((steps, 10))
        return steps 
Example 14
Project: python3_ios   Author: holzschu   File: dates.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def julian2num(j):
    """
    Convert a Julian date (or sequence) to a Matplotlib date (or sequence).

    Parameters
    ----------
    j : float or sequence of floats
        Julian date(s)

    Returns
    -------
    float or sequence of floats
        Matplotlib date(s)
    """
    if cbook.iterable(j):
        j = np.asarray(j)
    return j - JULIAN_OFFSET 
Example 15
Project: python3_ios   Author: holzschu   File: dates.py    License: BSD 3-Clause "New" or "Revised" License 6 votes vote down vote up
def num2timedelta(x):
    """
    Convert number of days to a `~datetime.timedelta` object.

    If *x* is a sequence, a sequence of `~datetime.timedelta` objects will
    be returned.

    Parameters
    ----------
    x : float, sequence of floats
        Number of days. The fraction part represents hours, minutes, seconds.

    Returns
    -------
    `datetime.timedelta` or list[`datetime.timedelta`]

    """
    if not cbook.iterable(x):
        return _ordinalf_to_timedelta(x)
    else:
        x = np.asarray(x)
        if not x.size:
            return x
        return _ordinalf_to_timedelta_np_vectorized(x).tolist() 
Example 16
def _broadcast_to(array, shape, subok, readonly):
    shape = tuple(shape) if np.iterable(shape) else (shape,)
    array = np.array(array, copy=False, subok=subok)
    if not shape and array.shape:
        raise ValueError('cannot broadcast a non-scalar to a scalar array')
    if any(size < 0 for size in shape):
        raise ValueError('all elements of broadcast shape must be non-'
                         'negative')
    needs_writeable = not readonly and array.flags.writeable
    extras = ['reduce_ok'] if needs_writeable else []
    op_flag = 'readwrite' if needs_writeable else 'readonly'
    it = np.nditer(
        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'] + extras,
        op_flags=[op_flag], itershape=shape, order='C')
    with it:
        # never really has writebackifcopy semantics
        broadcast = it.itviews[0]
    result = _maybe_view_as_subclass(array, broadcast)
    if needs_writeable and not result.flags.writeable:
        result.flags.writeable = True
    return result 
Example 17
Project: recruit   Author: Frank-qlu   File: function_base.py    License: Apache License 2.0 5 votes vote down vote up
def iterable(y):
    """
    Check whether or not an object can be iterated over.

    Parameters
    ----------
    y : object
      Input object.

    Returns
    -------
    b : bool
      Return ``True`` if the object has an iterator method or is a
      sequence and ``False`` otherwise.


    Examples
    --------
    >>> np.iterable([1, 2, 3])
    True
    >>> np.iterable(2)
    False

    """
    try:
        iter(y)
    except TypeError:
        return False
    return True 
Example 18
Project: recruit   Author: Frank-qlu   File: function_base.py    License: Apache License 2.0 5 votes vote down vote up
def _piecewise_dispatcher(x, condlist, funclist, *args, **kw):
    yield x
    # support the undocumented behavior of allowing scalars
    if np.iterable(condlist):
        for c in condlist:
            yield c 
Example 19
Project: recruit   Author: Frank-qlu   File: function_base.py    License: Apache License 2.0 5 votes vote down vote up
def __init__(self, pyfunc, otypes=None, doc=None, excluded=None,
                 cache=False, signature=None):
        self.pyfunc = pyfunc
        self.cache = cache
        self.signature = signature
        self._ufunc = None    # Caching to improve default performance

        if doc is None:
            self.__doc__ = pyfunc.__doc__
        else:
            self.__doc__ = doc

        if isinstance(otypes, str):
            for char in otypes:
                if char not in typecodes['All']:
                    raise ValueError("Invalid otype specified: %s" % (char,))
        elif iterable(otypes):
            otypes = ''.join([_nx.dtype(x).char for x in otypes])
        elif otypes is not None:
            raise ValueError("Invalid otype specification")
        self.otypes = otypes

        # Excluded variable support
        if excluded is None:
            excluded = set()
        self.excluded = set(excluded)

        if signature is not None:
            self._in_and_out_core_dims = _parse_gufunc_signature(signature)
        else:
            self._in_and_out_core_dims = None 
Example 20
Project: lambda-packs   Author: ryfeus   File: function_base.py    License: MIT License 5 votes vote down vote up
def iterable(y):
    """
    Check whether or not an object can be iterated over.

    Parameters
    ----------
    y : object
      Input object.

    Returns
    -------
    b : bool
      Return ``True`` if the object has an iterator method or is a
      sequence and ``False`` otherwise.


    Examples
    --------
    >>> np.iterable([1, 2, 3])
    True
    >>> np.iterable(2)
    False

    """
    try:
        iter(y)
    except TypeError:
        return False
    return True 
Example 21
Project: lambda-packs   Author: ryfeus   File: function_base.py    License: MIT License 5 votes vote down vote up
def __init__(self, pyfunc, otypes=None, doc=None, excluded=None,
                 cache=False, signature=None):
        self.pyfunc = pyfunc
        self.cache = cache
        self.signature = signature
        self._ufunc = None    # Caching to improve default performance

        if doc is None:
            self.__doc__ = pyfunc.__doc__
        else:
            self.__doc__ = doc

        if isinstance(otypes, str):
            for char in otypes:
                if char not in typecodes['All']:
                    raise ValueError("Invalid otype specified: %s" % (char,))
        elif iterable(otypes):
            otypes = ''.join([_nx.dtype(x).char for x in otypes])
        elif otypes is not None:
            raise ValueError("Invalid otype specification")
        self.otypes = otypes

        # Excluded variable support
        if excluded is None:
            excluded = set()
        self.excluded = set(excluded)

        if signature is not None:
            self._in_and_out_core_dims = _parse_gufunc_signature(signature)
        else:
            self._in_and_out_core_dims = None 
Example 22
Project: lambda-packs   Author: ryfeus   File: _numpy_compat.py    License: MIT License 5 votes vote down vote up
def _broadcast_to(array, shape, subok, readonly):
        shape = tuple(shape) if np.iterable(shape) else (shape,)
        array = np.array(array, copy=False, subok=subok)
        if not shape and array.shape:
            raise ValueError('cannot broadcast a non-scalar to a scalar array')
        if any(size < 0 for size in shape):
            raise ValueError('all elements of broadcast shape must be non-'
                             'negative')
        broadcast = np.nditer(
            (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'],
            op_flags=['readonly'], itershape=shape, order='C').itviews[0]
        result = _maybe_view_as_subclass(array, broadcast)
        if not readonly and array.flags.writeable:
            result.flags.writeable = True
        return result 
Example 23
Project: lambda-packs   Author: ryfeus   File: function_base.py    License: MIT License 5 votes vote down vote up
def iterable(y):
    """
    Check whether or not an object can be iterated over.

    Parameters
    ----------
    y : object
      Input object.

    Returns
    -------
    b : bool
      Return ``True`` if the object has an iterator method or is a
      sequence and ``False`` otherwise.


    Examples
    --------
    >>> np.iterable([1, 2, 3])
    True
    >>> np.iterable(2)
    False

    """
    try:
        iter(y)
    except TypeError:
        return False
    return True 
Example 24
Project: lambda-packs   Author: ryfeus   File: function_base.py    License: MIT License 5 votes vote down vote up
def __init__(self, pyfunc, otypes=None, doc=None, excluded=None,
                 cache=False, signature=None):
        self.pyfunc = pyfunc
        self.cache = cache
        self.signature = signature
        self._ufunc = None    # Caching to improve default performance

        if doc is None:
            self.__doc__ = pyfunc.__doc__
        else:
            self.__doc__ = doc

        if isinstance(otypes, str):
            for char in otypes:
                if char not in typecodes['All']:
                    raise ValueError("Invalid otype specified: %s" % (char,))
        elif iterable(otypes):
            otypes = ''.join([_nx.dtype(x).char for x in otypes])
        elif otypes is not None:
            raise ValueError("Invalid otype specification")
        self.otypes = otypes

        # Excluded variable support
        if excluded is None:
            excluded = set()
        self.excluded = set(excluded)

        if signature is not None:
            self._in_and_out_core_dims = _parse_gufunc_signature(signature)
        else:
            self._in_and_out_core_dims = None 
Example 25
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: function_base.py    License: MIT License 5 votes vote down vote up
def iterable(y):
    """
    Check whether or not an object can be iterated over.

    Parameters
    ----------
    y : object
      Input object.

    Returns
    -------
    b : {0, 1}
      Return 1 if the object has an iterator method or is a sequence,
      and 0 otherwise.


    Examples
    --------
    >>> np.iterable([1, 2, 3])
    1
    >>> np.iterable(2)
    0

    """
    try:
        iter(y)
    except:
        return 0
    return 1 
Example 26
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: function_base.py    License: MIT License 5 votes vote down vote up
def __init__(self, pyfunc, otypes='', doc=None, excluded=None,
                 cache=False):
        self.pyfunc = pyfunc
        self.cache = cache
        self._ufunc = None    # Caching to improve default performance

        if doc is None:
            self.__doc__ = pyfunc.__doc__
        else:
            self.__doc__ = doc

        if isinstance(otypes, str):
            self.otypes = otypes
            for char in self.otypes:
                if char not in typecodes['All']:
                    raise ValueError(
                        "Invalid otype specified: %s" % (char,))
        elif iterable(otypes):
            self.otypes = ''.join([_nx.dtype(x).char for x in otypes])
        else:
            raise ValueError(
                "Invalid otype specification")

        # Excluded variable support
        if excluded is None:
            excluded = set()
        self.excluded = set(excluded) 
Example 27
Project: vnpy_crypto   Author: birforce   File: function_base.py    License: MIT License 5 votes vote down vote up
def iterable(y):
    """
    Check whether or not an object can be iterated over.

    Parameters
    ----------
    y : object
      Input object.

    Returns
    -------
    b : bool
      Return ``True`` if the object has an iterator method or is a
      sequence and ``False`` otherwise.


    Examples
    --------
    >>> np.iterable([1, 2, 3])
    True
    >>> np.iterable(2)
    False

    """
    try:
        iter(y)
    except TypeError:
        return False
    return True 
Example 28
Project: vnpy_crypto   Author: birforce   File: function_base.py    License: MIT License 5 votes vote down vote up
def __init__(self, pyfunc, otypes=None, doc=None, excluded=None,
                 cache=False, signature=None):
        self.pyfunc = pyfunc
        self.cache = cache
        self.signature = signature
        self._ufunc = None    # Caching to improve default performance

        if doc is None:
            self.__doc__ = pyfunc.__doc__
        else:
            self.__doc__ = doc

        if isinstance(otypes, str):
            for char in otypes:
                if char not in typecodes['All']:
                    raise ValueError("Invalid otype specified: %s" % (char,))
        elif iterable(otypes):
            otypes = ''.join([_nx.dtype(x).char for x in otypes])
        elif otypes is not None:
            raise ValueError("Invalid otype specification")
        self.otypes = otypes

        # Excluded variable support
        if excluded is None:
            excluded = set()
        self.excluded = set(excluded)

        if signature is not None:
            self._in_and_out_core_dims = _parse_gufunc_signature(signature)
        else:
            self._in_and_out_core_dims = None 
Example 29
Project: vnpy_crypto   Author: birforce   File: mosaicplot.py    License: MIT License 5 votes vote down vote up
def _normalize_split(proportion):
    """
    return a list of proportions of the available space given the division
    if only a number is given, it will assume a split in two pieces
    """
    if not iterable(proportion):
        if proportion == 0:
            proportion = array([0.0, 1.0])
        elif proportion >= 1:
            proportion = array([1.0, 0.0])
        elif proportion < 0:
            raise ValueError("proportions should be positive,"
                              "given value: {}".format(proportion))
        else:
            proportion = array([proportion, 1.0 - proportion])
    proportion = np.asarray(proportion, dtype=float)
    if np.any(proportion < 0):
        raise ValueError("proportions should be positive,"
                          "given value: {}".format(proportion))
    if np.allclose(proportion, 0):
        raise ValueError("at least one proportion should be "
                          "greater than zero".format(proportion))
    # ok, data are meaningful, so go on
    if len(proportion) < 2:
        return array([0.0, 1.0])
    left = r_[0, cumsum(proportion)]
    left /= left[-1] * 1.0
    return left 
Example 30
Project: vnpy_crypto   Author: birforce   File: indexing.py    License: MIT License 5 votes vote down vote up
def __iter__(self):
        raise NotImplementedError('ix is not iterable')