skbio.stats.gradient.TrajectoryGradientANOVA#

class skbio.stats.gradient.TrajectoryGradientANOVA(coords, prop_expl, metadata_map, trajectory_categories=None, sort_category=None, axes=3, weighted=False)[source]#

Perform trajectory analysis using the RMS trajectory algorithm.

For each group in a category, each component of the result trajectory is computed as taking the sorted list of samples in the group and taking the norm of the coordinates of the 2nd sample minus 1st sample, 3rd sample minus 2nd sample and so on.

See also

GradientANOVA

Built-ins

__eq__(value, /)

Return self==value.

__ge__(value, /)

Return self>=value.

__getstate__(/)

Helper for pickle.

__gt__(value, /)

Return self>value.

__hash__(/)

Return hash(self).

__le__(value, /)

Return self<=value.

__lt__(value, /)

Return self<value.

__ne__(value, /)

Return self!=value.

__str__(/)

Return str(self).

Methods

get_trajectories()

Compute the trajectories for each group and category and run ANOVA.