Data manipulation

Pingwyn has the following functions for data manipulation.

pingwyn.affine_correct(image, vectors_from, ...)	Perform an affine transformation on an image.
pingwyn.align_rows(image[, mask, method])	Perform Gwyddion-like median row alignment of images.
pingwyn.bin(obj[, bins, keep_dims, method])	Bin an object by combining datapoints.
pingwyn.clip(obj[, min, max, relative])	Clip data to cut off extreme values.
pingwyn.copy(obj)	Create an in-memory copy of a pingwyn object.
pingwyn.curve_fix_zero(curve[, strat])	Shift a curve such that the points at x = 0 or y = 0 are set to zero.
pingwyn.curves_to_profiles(curves)	Convert individual curves to line profiles.
pingwyn.differentiate(obj[, method, absolute])	Differentiate the closest thing to dy/dx for the given object.
pingwyn.fix_zero(obj, *args, **kwargs)	Wrapper for pingwyn.image_fix_zero, pingwyn.curve_fix_zero and pingwyn.profile_fix_zero.
pingwyn.image_fix_zero(image[, mask])	Set minimum value of an image to zero.
pingwyn.normalise(obj[, strat])	Normalise an object.
pingwyn.profile_fix_zero(profile[, strat])	Shift a profile such that for each curve in the profile, the points at x = 0 or y = 0 are set to zero.
pingwyn.remove_artefacts(image_trace, ...[, ...])	Remove a variety of scanning artefacts using FFT based feature detection.
pingwyn.remove_plane(image[, order, mask])	Remove an n-th order polynomial background from an image
pingwyn.smooth(obj, n_points[, strat])	Smooth data points.
pingwyn.square_pixels(image)	Resize an image such that the width and height of a pixel are equal (i.e. square).
pingwyn.to_float(obj)	Convert object values to floats.
pingwyn.to_float64(obj)	Convert object values to numpy 64-bit floats.
pingwyn.to_int(obj)	Convert object values to integers between 0 to 255
pingwyn.to_uint8(obj)	Convert object values to numpy unsigned 8-bit integers.