# encoding: utf-8 # module dipy.segment.featurespeed # from C:\Users\xukai\Downloads\发票2\venv\Lib\site-packages\dipy\segment\featurespeed.cp311-win_amd64.pyd # by generator 1.147 # no doc # imports import builtins as __builtins__ # import numpy as np # C:\Users\xukai\Downloads\发票2\venv\Lib\site-packages\numpy\__init__.py # functions def extract(*args, **kwargs): # real signature unknown """ Extracts features from data. Parameters ---------- feature : `Feature` object Tells how to extract features from the data. datum : list of 2D arrays List of sequence of N-dimensional points. Returns ------- list of 2D arrays List of features extracted from `data`. """ pass def infer_shape(*args, **kwargs): # real signature unknown """ Infers shape of the features extracted from data. Parameters ---------- feature : `Feature` object Tells how to infer shape of the features. data : list of 2D arrays List of sequences of N-dimensional points. Returns ------- list of tuples Shapes of the features inferred from `data`. """ pass def __pyx_unpickle_ArcLengthFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_CenterOfMassFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_CythonFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_Enum(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_Feature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_IdentityFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_MidpointFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_ResampleFeature(*args, **kwargs): # real signature unknown pass def __pyx_unpickle_VectorOfEndpointsFeature(*args, **kwargs): # real signature unknown pass # classes class Feature(object): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). Parameters ---------- is_order_invariant : bool (optional) tells if this feature is invariant to the sequence's ordering. This means starting from either extremities produces the same features. (Default: True) Notes ----- When subclassing `Feature`, one only needs to override the `extract` and `infer_shape` methods. """ def extract(self, *args, **kwargs): # real signature unknown """ Extracts features from a sequential datum. Parameters ---------- datum : 2D array Sequence of N-dimensional points. Returns ------- 2D array Features extracted from `datum`. """ pass def infer_shape(self, *args, **kwargs): # real signature unknown """ Infers the shape of features extracted from a sequential datum. Parameters ---------- datum : 2D array Sequence of N-dimensional points. Returns ------- int, 1-tuple or 2-tuple Shape of the features. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass is_order_invariant = property(lambda self: object(), lambda self, v: None, lambda self: None) # default """ Is this feature invariant to the sequence's ordering """ __pyx_vtable__ = None # (!) real value is '' class CythonFeature(Feature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). Parameters ---------- is_order_invariant : bool, optional Tells if this feature is invariant to the sequence's ordering (Default: True). Notes ----- By default, when inheriting from `CythonFeature`, Python methods will call their C version (e.g. `CythonFeature.extract` -> `self.c_extract`). """ def extract(self, *args, **kwargs): # real signature unknown """ Extracts features from a sequential datum. Parameters ---------- datum : 2D array Sequence of N-dimensional points. Returns ------- 2D array Features extracted from `datum`. Notes ----- This method calls its Cython version `self.c_extract` accordingly. """ pass def infer_shape(self, *args, **kwargs): # real signature unknown """ Infers the shape of features extracted from a sequential datum. Parameters ---------- datum : 2D array Sequence of N-dimensional points. Returns ------- tuple Shape of the features. Notes ----- This method calls its Cython version `self.c_infer_shape` accordingly. """ pass def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class ArcLengthFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The feature being extracted consists of one scalar representing the arc length of the sequence (i.e. the sum of the length of all segments). """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class CenterOfMassFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The feature being extracted consists of one N-dimensional point representing the mean of the points, i.e. the center of mass. """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class IdentityFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The features being extracted are the actual sequence's points. This is useful for metric that does not require any pre-processing. """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class MidpointFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The feature being extracted consists of one N-dimensional point representing the middle point of the sequence (i.e. `nb_points//2`th point). """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class ResampleFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The features being extracted are the points of the sequence once resampled. This is useful for metrics requiring a constant number of points for all streamlines. """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' class VectorOfEndpointsFeature(CythonFeature): """ Extracts features from a sequential datum. A sequence of N-dimensional points is represented as a 2D array with shape (nb_points, nb_dimensions). The feature being extracted consists of one vector in the N-dimensional space pointing from one end-point of the sequence to the other (i.e. `S[-1]-S[0]`). """ def __init__(self, *args, **kwargs): # real signature unknown pass @staticmethod # known case of __new__ def __new__(*args, **kwargs): # real signature unknown """ Create and return a new object. See help(type) for accurate signature. """ pass def __reduce__(self, *args, **kwargs): # real signature unknown pass def __setstate__(self, *args, **kwargs): # real signature unknown pass __pyx_vtable__ = None # (!) real value is '' # variables with complex values __loader__ = None # (!) real value is '<_frozen_importlib_external.ExtensionFileLoader object at 0x000001DD6569F610>' __spec__ = None # (!) real value is "ModuleSpec(name='dipy.segment.featurespeed', loader=<_frozen_importlib_external.ExtensionFileLoader object at 0x000001DD6569F610>, origin='C:\\\\Users\\\\xukai\\\\Downloads\\\\??2\\\\venv\\\\Lib\\\\site-packages\\\\dipy\\\\segment\\\\featurespeed.cp311-win_amd64.pyd')" __test__ = {}