skbio.math.gradient.WindowDifferenceGradientANOVA

class skbio.math.gradient.WindowDifferenceGradientANOVA(coords, prop_expl, metadata_map, window_size, **kwargs)[source]

Perform trajectory analysis using the modified first difference algorithm

It calculates the norm for all the time-points and subtracts the mean of the next number of elements specified in window_size and the current element.

Parameters:

coords : pandas.DataFrame

The coordinates for each sample id

prop_expl : array like

The numpy 1-D array with the proportion explained by each axis in coords

metadata_map : pandas.DataFrame

The metadata map, indexed by sample ids and columns are metadata categories

window_size : int or long

The window size to use while computing the differences

Raises:

ValueError

If the window_size is not a positive integer

See also

GradientANOVA

Methods

get_trajectories() Compute the trajectories for each group in each category and run ANOVA over the results to test group independence.