@@ -80,7 +80,7 @@ class PerArrayDict(SliceableDataDict):
8080
8181 In addition, it makes sure the amount of data contained in those ndarrays
8282 matches the number of streamlines given at the instantiation of this
83- dictionary .
83+ instance .
8484 """
8585 def __init__ (self , nb_elements , * args , ** kwargs ):
8686 self .nb_elements = nb_elements
@@ -114,7 +114,7 @@ class PerArraySequenceDict(SliceableDataDict):
114114
115115 In addition, it makes sure the amount of data contained in those array
116116 sequences matches the number of elements given at the instantiation
117- of this dictionary .
117+ of the instance .
118118 """
119119 def __init__ (self , nb_elements , * args , ** kwargs ):
120120 self .nb_elements = nb_elements
@@ -136,9 +136,9 @@ def __setitem__(self, key, value):
136136class LazyDict (collections .MutableMapping ):
137137 """ Dictionary of generator functions.
138138
139- This container behaves like an dictionary but it makes sure its elements
140- are callable objects and assumed to be generator function yielding values.
141- When getting the element associated to a given key, the element (i.e. a
139+ This container behaves like a dictionary but it makes sure its elements are
140+ callable objects that it assumes are generator functions yielding values.
141+ When getting the element associated with a given key, the element (i.e. a
142142 generator function) is first called before being returned.
143143 """
144144 def __init__ (self , * args , ** kwargs ):
@@ -178,7 +178,7 @@ def __len__(self):
178178class TractogramItem (object ):
179179 """ Class containing information about one streamline.
180180
181- :class:`TractogramItem` objects have three main properties : `streamline`,
181+ :class:`TractogramItem` objects have three public attributes : `streamline`,
182182 `data_for_streamline`, and `data_for_points`.
183183
184184 Parameters
@@ -187,14 +187,14 @@ class TractogramItem(object):
187187 Points of this streamline represented as an ndarray of shape (N, 3)
188188 where N is the number of points.
189189 data_for_streamline : dict
190- Dictionary containing some data associated to this particular
191- streamline. Each key `k ` is mapped to a ndarray of shape (Pt,), where
192- `Pt` is the dimension of the data associated with key `k `.
190+ Dictionary containing some data associated with this particular
191+ streamline. Each key ``k` ` is mapped to a ndarray of shape (Pt,), where
192+ `` Pt`` is the dimension of the data associated with key ``k` `.
193193 data_for_points : dict
194194 Dictionary containing some data associated to each point of this
195- particular streamline. Each key `k` is mapped to a ndarray of
196- shape (Nt, Mk), where `Nt` is the number of points of this streamline
197- and ` Mk` is the dimension of the data associated with key `k `.
195+ particular streamline. Each key ``k`` is mapped to a ndarray of shape
196+ (Nt, Mk), where `` Nt`` is the number of points of this streamline and
197+ `` Mk`` is the dimension of the data associated with key ``k` `.
198198 """
199199 def __init__ (self , streamline , data_for_streamline , data_for_points ):
200200 self .streamline = np .asarray (streamline )
@@ -215,7 +215,7 @@ class Tractogram(object):
215215 choice as long as you provide the correct `affine_to_rasmm` matrix, at
216216 construction time, that brings the streamlines back to *RAS+*, *mm* space,
217217 where the coordinates (0,0,0) corresponds to the center of the voxel
218- (opposed to a corner).
218+ (as opposed to the corner of the voxel ).
219219
220220 Attributes
221221 ----------
@@ -224,18 +224,18 @@ class Tractogram(object):
224224 shape ($N_t$, 3) where $N_t$ is the number of points of
225225 streamline $t$.
226226 data_per_streamline : :class:`PerArrayDict` object
227- Dictionary where the items are (str, 2D array).
228- Each key represents an information $i$ to be kept alongside every
229- streamline, and its associated value is a 2D array of shape
230- ($T$, $P_i$) where $T $ is the number of streamlines and $P_i$ is
231- the number of values to store for that particular information $i$.
227+ Dictionary where the items are (str, 2D array). Each key represents a
228+ piece of information $i$ to be kept alongside every streamline, and its
229+ associated value is a 2D array of shape ($T$, $P_i$) where $T$ is the
230+ number of streamlines and $P_i $ is the number of values to store for
231+ that particular piece of information $i$.
232232 data_per_point : :class:`PerArraySequenceDict` object
233- Dictionary where the items are (str, :class:`ArraySequence`).
234- Each key represents an information $i$ to be kept alongside every
235- point of every streamline, and its associated value is an iterable
236- of ndarrays of shape ($N_t$, $M_i$) where $N_t$ is the number of
237- points for a particular streamline $t$ and $M_i$ is the number
238- values to store for that particular information $i$.
233+ Dictionary where the items are (str, :class:`ArraySequence`). Each key
234+ represents a piece of information $i$ to be kept alongside every point
235+ of every streamline, and its associated value is an iterable of
236+ ndarrays of shape ($N_t$, $M_i$) where $N_t$ is the number of points
237+ for a particular streamline $t$ and $M_i$ is the number values to store
238+ for that particular piece of information $i$.
239239 """
240240 def __init__ (self , streamlines = None ,
241241 data_per_streamline = None ,
@@ -424,29 +424,29 @@ class LazyTractogram(Tractogram):
424424 choice as long as you provide the correct `affine_to_rasmm` matrix, at
425425 construction time, that brings the streamlines back to *RAS+*, *mm* space,
426426 where the coordinates (0,0,0) corresponds to the center of the voxel
427- (opposed to a corner).
427+ (as opposed to the corner of the voxel ).
428428
429429 Attributes
430430 ----------
431431 streamlines : generator function
432432 Generator function yielding streamlines. Each streamline is an
433433 ndarray of shape ($N_t$, 3) where $N_t$ is the number of points of
434434 streamline $t$.
435- data_per_streamline : :class:`LazyDict` object
435+ data_per_streamline : instance of :class:`LazyDict`
436436 Dictionary where the items are (str, instantiated generator).
437- Each key represents an information $i$ to be kept alongside every
438- streamline, and its associated value is a generator function
439- yielding that information via ndarrays of shape ($P_i$,) where
440- $P_i$ is the number of values to store for that particular
441- information $i$.
437+ Each key represents a piece of information $i$ to be kept alongside
438+ every streamline, and its associated value is a generator function
439+ yielding that information via ndarrays of shape ($P_i$,) where $P_i$ is
440+ the number of values to store for that particular piece of information
441+ $i$.
442442 data_per_point : :class:`LazyDict` object
443- Dictionary where the items are (str, instantiated generator).
444- Each key represents an information $i$ to be kept alongside every
445- point of every streamline, and its associated value is a generator
446- function yielding that information via ndarrays of shape
447- ( $N_t$, $M_i$) where $N_t$ is the number of points for a particular
448- streamline $t$ and $M_i$ is the number of values to store for
449- that particular information $i$.
443+ Dictionary where the items are (str, instantiated generator). Each key
444+ represents a piece of information $i$ to be kept alongside every point
445+ of every streamline, and its associated value is a generator function
446+ yielding that information via ndarrays of shape ($N_t$, $M_i$) where
447+ $N_t$ is the number of points for a particular streamline $t$ and $M_i$
448+ is the number of values to store for that particular piece of
449+ information $i$.
450450
451451 Notes
452452 -----
@@ -599,7 +599,6 @@ def _apply_affine():
599599 def _set_streamlines (self , value ):
600600 if value is not None and not callable (value ):
601601 raise TypeError ("`streamlines` must be a generator function." )
602-
603602 self ._streamlines = value
604603
605604 @property
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