Python numpy.iterable() Examples
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Example #1
Source File: stride_tricks.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 6 votes |
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 #2
Source File: stride_tricks.py From recruit with Apache License 2.0 | 6 votes |
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
Source File: stride_tricks.py From lambda-packs with MIT License | 6 votes |
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 #4
Source File: tidy.py From plydata with BSD 3-Clause "New" or "Revised" License | 6 votes |
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 #5
Source File: estimators.py From lattice with Apache License 2.0 | 6 votes |
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 #6
Source File: stride_tricks.py From auto-alt-text-lambda-api with MIT License | 6 votes |
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
Source File: stride_tricks.py From vnpy_crypto with MIT License | 6 votes |
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 #8
Source File: stride_tricks.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
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 #9
Source File: units.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
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 #10
Source File: colorbar.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
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 #11
Source File: patches.py From Mastering-Elasticsearch-7.0 with MIT License | 6 votes |
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 #12
Source File: stride_tricks.py From GraphicDesignPatternByPython with MIT License | 6 votes |
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 #13
Source File: ticker.py From GraphicDesignPatternByPython with MIT License | 6 votes |
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
Source File: ticker.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
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 #15
Source File: dates.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
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 #16
Source File: dates.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 6 votes |
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 #17
Source File: function_base.py From recruit with Apache License 2.0 | 5 votes |
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
Source File: envi.py From spectral with MIT License | 5 votes |
def _has_frame_offset(params): ''' Returns True if header params indicate non-zero frame offsets. Arguments: `params` (dict): Dictionary of header parameters assocaited with hdr file. Returns: bool This function returns True when either "major frame offsets" or "minor frame offsets" is specified and contains a non-zero value. ''' for param in ['major frame offsets', 'minor frame offsets']: if param in params: val = params[param] if np.iterable(val): offsets = [int(x) for x in val] else: offsets = [int(val)] * 2 if not np.all(np.equal(offsets, 0)): return True return False
Example #19
Source File: _broadcast.py From sdeint with GNU General Public License v3.0 | 5 votes |
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 #20
Source File: function_base.py From Fluid-Designer with GNU General Public License v3.0 | 5 votes |
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 #21
Source File: function_base.py From recruit with Apache License 2.0 | 5 votes |
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 #22
Source File: function_base.py From GraphicDesignPatternByPython with MIT License | 5 votes |
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 #23
Source File: function_base.py From GraphicDesignPatternByPython with MIT License | 5 votes |
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
Source File: function_base.py From recruit with Apache License 2.0 | 5 votes |
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
Source File: _base.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def set_ybound(self, lower=None, upper=None): """ Set the lower and upper numerical bounds of the y-axis. This method will honor axes inversion regardless of parameter order. It will not change the autoscaling setting (``Axes._autoscaleYon``). Parameters ---------- lower, upper : float or None The lower and upper bounds. If *None*, the respective axis bound is not modified. See Also -------- get_ybound get_ylim, set_ylim invert_yaxis, yaxis_inverted """ if upper is None and np.iterable(lower): lower, upper = lower old_lower, old_upper = self.get_ybound() if lower is None: lower = old_lower if upper is None: upper = old_upper if self.yaxis_inverted(): if lower < upper: self.set_ylim(upper, lower, auto=None) else: self.set_ylim(lower, upper, auto=None) else: if lower < upper: self.set_ylim(lower, upper, auto=None) else: self.set_ylim(upper, lower, auto=None)
Example #26
Source File: _base.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def set_xbound(self, lower=None, upper=None): """ Set the lower and upper numerical bounds of the x-axis. This method will honor axes inversion regardless of parameter order. It will not change the autoscaling setting (``Axes._autoscaleXon``). Parameters ---------- lower, upper : float or None The lower and upper bounds. If *None*, the respective axis bound is not modified. See Also -------- get_xbound get_xlim, set_xlim invert_xaxis, xaxis_inverted """ if upper is None and np.iterable(lower): lower, upper = lower old_lower, old_upper = self.get_xbound() if lower is None: lower = old_lower if upper is None: upper = old_upper if self.xaxis_inverted(): if lower < upper: self.set_xlim(upper, lower, auto=None) else: self.set_xlim(lower, upper, auto=None) else: if lower < upper: self.set_xlim(lower, upper, auto=None) else: self.set_xlim(upper, lower, auto=None)
Example #27
Source File: __init__.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def is_scalar_or_string(val): """Return whether the given object is a scalar or string like.""" return isinstance(val, str) or not np.iterable(val)
Example #28
Source File: ticker.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def _validate_steps(steps): if not np.iterable(steps): raise ValueError('steps argument must be an increasing sequence ' 'of numbers between 1 and 10 inclusive') steps = np.asarray(steps) if np.any(np.diff(steps) <= 0) or steps[-1] > 10 or steps[0] < 1: raise ValueError('steps argument must be an increasing sequence ' 'of numbers between 1 and 10 inclusive') if steps[0] != 1: steps = np.hstack((1, steps)) if steps[-1] != 10: steps = np.hstack((steps, 10)) return steps
Example #29
Source File: patches.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def get_path(self): """ Return the path of the arrow in the data coordinates. Use get_path_in_displaycoord() method to retrieve the arrow path in display coordinates. """ _path, fillable = self.get_path_in_displaycoord() if np.iterable(fillable): _path = concatenate_paths(_path) return self.get_transform().inverted().transform_path(_path)
Example #30
Source File: test_units.py From python3_ios with BSD 3-Clause "New" or "Revised" License | 5 votes |
def __getitem__(self, item): if iterable(self.magnitude): return Quantity(self.magnitude[item], self.units) else: return Quantity(self.magnitude, self.units)