Diffraction2D#

class pyxem.signals.Diffraction2D(*args, **kwargs)[source]#

Bases: CommonDiffraction, Signal2D

Signal class for two-dimensional diffraction data in Cartesian coordinates.

Parameters:

*args – See Signal2D.
**kwargs – See Signal2D

Attributes

Diffraction2D.ai

Methods

`Diffraction2D.add_ellipse_array_as_markers`(...)	Add a ellipse parameters array to a signal as HyperSpy markers.
`Diffraction2D.add_peak_array_as_markers`(...)	[Deprecated] Add a peak array to the signal as HyperSpy markers.
`Diffraction2D.angular_mask`(angle0, angle1[, ...])	Get a bool array with True values between angle0 and angle1.
`Diffraction2D.angular_slice_radial_average`([...])	[Deprecated] Do radial average of different angular slices.
`Diffraction2D.apply_affine_transformation`(D)	Correct geometric distortion by applying an affine transformation.
`Diffraction2D.apply_gain_normalisation`(...)	Apply gain normalization to experimentally acquired electron diffraction patterns.
`Diffraction2D.center_direct_beam`([method, ...])	Estimate the direct beam position in each experimentally acquired electron diffraction pattern and translate it to the center of the image square.
`Diffraction2D.center_of_mass`([threshold, mask])	Get the centre of the STEM diffraction pattern using center of mass.
`Diffraction2D.correct_bad_pixels`(...)	Correct bad (dead/hot) pixels by replacing their values with the mean value of neighbors.
`Diffraction2D.filter`(func[, inplace])	Filters the entire dataset given some function applied to the data.
`Diffraction2D.find_dead_pixels`([...])	Find dead pixels in the diffraction images.
`Diffraction2D.find_hot_pixels`([...])	Find hot pixels in the diffraction images.
`Diffraction2D.flip_diffraction_x`()	Flip the dataset along the diffraction x-axis.
`Diffraction2D.flip_diffraction_y`()	Flip the dataset along the diffraction y-axis.
`Diffraction2D.get_azimuthal_integral1d`(npt)	Creates a polar reprojection using pyFAI's azimuthal integrate 2d.
`Diffraction2D.get_azimuthal_integral2d`(npt)	Creates a polar reprojection using pyFAI's azimuthal integrate 2d.
`Diffraction2D.get_diffraction_vectors`([...])	Find vectors from the diffraction pattern.
`Diffraction2D.get_direct_beam_mask`(radius)	Generate a signal mask for the direct beam.
`Diffraction2D.get_direct_beam_position`(method)	Estimate the direct beam position in each experimentally acquired electron diffraction pattern.
`Diffraction2D.get_medfilt1d`([npt_rad, ...])	Calculate the radial integrated profile curve as I = f(chi)
`Diffraction2D.get_radial_integral`(npt, npt_rad)	Calculate the radial integrated profile curve as I = f(chi)
`Diffraction2D.get_variance`(npt[, method, ...])	Calculates the variance using one of the methods described in [1]. A shot noise correction
`Diffraction2D.intensity_peaks`(peak_array[, ...])	Get intensity of a peak in the diffraction data.
`Diffraction2D.make_probe_navigation`([method])
`Diffraction2D.peak_position_refinement_com`(...)	Refines the peak position using the center of mass.
`Diffraction2D.plot`(args, *kwargs)	Plot the signal at the current coordinates.
`Diffraction2D.rotate_diffraction`(angle[, ...])	Rotate the diffraction dimensions.
`Diffraction2D.set_ai`([center, wavelength, ...])	[Deprecated] This function sets the .ai parameter which stores an ~pyfai.AzimuthalIntegrator object based on the current calibration applied to the diffraction pattern.
`Diffraction2D.shift_diffraction`(shift_x, shift_y)	Shift the diffraction patterns in a pixelated STEM signal.
`Diffraction2D.sigma_clip`([npt_rad, ...])	Perform the 2D integration and perform a sigm-clipping iterative filter along each row.
`Diffraction2D.subtract_diffraction_background`([...])	Background subtraction of the diffraction data.
`Diffraction2D.template_match`(template[, inplace])	Template match the signal dimensions with a binary image.
`Diffraction2D.template_match_disk`([disk_r, ...])	Template match the signal dimensions with a disk.
`Diffraction2D.template_match_ring`([r_inner, ...])	Template match the signal dimensions with a ring.
`Diffraction2D.template_match_with_binary_image`(...)	[Deprecated] Template match the signal dimensions with a binary image.
`Diffraction2D.threshold_and_mask`([...])	Get a thresholded and masked of the signal.