moments¶
- sofia_redux.toolkit.stats.stats.moments(data, threshold=None, mask=None, axis=None, get_mask=False)[source]¶
Computes statistics on a data set avoiding deviant points if requested
Moments are calculated for a given set of data. If a value is passed to threshold, then the dataset is searched for outliers. A data point is identified as an outlier if abs(x_i - x_med)/MAD > threshold, where x_med is the median, MAD is the median absolute deviation defined as 1.482 * median(abs(x_i - x_med)).
- Parameters:
- dataarray_like of float
(shape1) Data on which to calculate moments
- maskarray_like of bool
(shape1) Mask to apply to data
- thresholdfloat, optional
Sigma threshold over which values are identified as outliers
- axisint, optional
Axis over which to calculate statistics
- get_maskbool, optional
If True, only return the output mask
- Returns:
- dict or numpy.ndarray
If
get_maskis False, returns a dictionary containing the following statistics: mean, var, stddev, skew, kurt, stderr, mask. Otherwise, returns the output mask.