diff --git a/src/eddymotion/data/pet.py b/src/eddymotion/data/pet.py index 415b477c..44a97b89 100644 --- a/src/eddymotion/data/pet.py +++ b/src/eddymotion/data/pet.py @@ -51,7 +51,7 @@ class PET: frame_time = attr.ib(default=None, repr=_data_repr) """A 1D numpy array with the midpoint timing of each sample.""" total_duration = attr.ib(default=None, repr=_data_repr) - """A float number represaenting the total duration of acquisition.""" + """A float number representing the total duration of acquisition.""" em_affines = attr.ib(default=None) """ diff --git a/src/eddymotion/estimator.py b/src/eddymotion/estimator.py index 148c769d..7efff9d0 100644 --- a/src/eddymotion/estimator.py +++ b/src/eddymotion/estimator.py @@ -64,11 +64,15 @@ def fit( Number of iterations this particular model is going to be repeated. align_kwargs : :obj:`dict` Parameters to configure the image registration process. - model : :obj:`str` + models : :obj:`list` Selects the diffusion model that will generate the registration target corresponding to each gradient map. See :obj:`~eddymotion.model.ModelFactory` for allowed models (and corresponding keywords). + omp_nthreads : :obj:`int` + Maximum number of threads an individual process may use. + n_jobs : :obj:`int` + Number of parallel jobs. seed : :obj:`int` or :obj:`bool` Seed the random number generator (necessary when we want deterministic estimation). diff --git a/src/eddymotion/model/base.py b/src/eddymotion/model/base.py index 59b7a863..e0e8d2e9 100644 --- a/src/eddymotion/model/base.py +++ b/src/eddymotion/model/base.py @@ -47,8 +47,6 @@ def init(model="DTI", **kwargs): Parameters ---------- - gtab : :obj:`numpy.ndarray` - An array representing the gradient table in RAS+B format. model : :obj:`str` Diffusion model. Options: ``"DTI"``, ``"DKI"``, ``"S0"``, ``"AverageDW"`` diff --git a/src/eddymotion/viz.py b/src/eddymotion/viz.py index a298d092..38d112b0 100644 --- a/src/eddymotion/viz.py +++ b/src/eddymotion/viz.py @@ -115,7 +115,7 @@ def draw_circles(positions, radius, n_samples=20): r""" Draw circular patches (lying on a sphere) at given positions. - Adapted from from `Emmanuel Caruyer's code + Adapted from `Emmanuel Caruyer's code `__, which is distributed under the revised BSD License: @@ -164,7 +164,7 @@ def draw_points(gradients, ax, rad_min=0.3, rad_max=0.7, cmap="viridis"): """ Draw the vectors on a shell. - Adapted from from `Emmanuel Caruyer's code + Adapted from `Emmanuel Caruyer's code `__, which is distributed under the revised BSD License: @@ -184,7 +184,7 @@ def draw_points(gradients, ax, rad_min=0.3, rad_max=0.7, cmap="viridis"): gradients : array-like shape (N, 4) A 2D numpy array of the gradient table in RAS+B format. ax : :obj:`matplotlib.axes.Axis` - The matplolib axes instance to plot in. + The matplotlib axes instance to plot in. rad_min : :obj:`float` between 0 and 1 Minimum radius of the circle that renders a gradient direction rad_max : :obj:`float` between 0 and 1