xarray_sci

File Purpose: high-level xarray functions. May be especially useful for science.

E.g., gaussian filter, polynomial fit.

Functions

xarray_assign_polyfit_stddev(dataset, *[, ...])	assign polyfit stddev to dataset['polyfit_stddev'], treating dataset like a result of polyfit.
xarray_coarsened_polyfit(array, coord, ...)	returns result of coarsening array, then polyfitting along the fine dimension, in each window.
xarray_curve_eval(params, f, xdata, *[, stddev])	evaluate a curve fit result (params) for this function at these xdata.
xarray_curve_fit(array, f, dim, *[, stddev, ...])	scipy.optimize.curve_fit(f, xdata=array[dim], ydata=array).
xarray_gaussian_filter(array[, dim, sigma, ...])	returns array after applying scipy.ndimage.gaussian_filter to it.
xarray_interp_inverse(array[, interpto, ...])	interpolate a DataArray but using the array values as one of the interpolation variables;
xarray_line_fit(array, dim, *[, pnames, pbounds])	returns result of xarray_curve_fit with f a line:
xarray_polyfit(array, coord, degree, *[, ...])	returns array.polyfit(coord, degree, **kw_polyfit), after swapping coord to be a dimension, if needed.
xarray_polyfit_eval(dataset[, at, to_dataset])	evaluate the polyfit in dataset at these coordinates.

Classes

XarrayCurveFitter(array, dim, *[, ...])	class for helping with curve fitting.
XarrayLineFitter(array, dim, *[, ...])	XarrayCurveFitter with f a line: f(x, slope, intercept) = slope * x + intercept.