skbio.stats.gradient.WindowDifferenceGradientANOVA#

class skbio.stats.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:

coordspandas.DataFrame: The coordinates for each sample id
prop_explarray like: The numpy 1-D array with the proportion explained by each axis in coords
metadata_mappandas.DataFrame: The metadata map, indexed by sample ids and columns are metadata categories
window_sizeint 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 (inherited)

get_trajectories

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

Special methods (inherited)

`__eq__`	Return self==value.
`__ge__`	Return self>=value.
`__getstate__`	Helper for pickle.
`__gt__`	Return self>value.
`__hash__`	Return hash(self).
`__le__`	Return self<=value.
`__lt__`	Return self<value.
`__ne__`	Return self!=value.
`__str__`	Return str(self).

Details