The EasyLEED API

The EasyLEED package is divided into several subpackages:

• base: Core functionality (fitting procedures, Tracker class, etc.)
• kalman: Implementation of Kalman filter classes
• io: Input/Output functionality (reading FITS, PIL, and IMG files)
• gui: Graphical User Interface

easyleed.base

Base class providing common functionality for analyzing Leed patterns.

class easyleed.base.SpotModel

Data model for a Spot that stores all the information in various lists.

class easyleed.base.Tracker(x_in, y_in, radius, energy, x_c=None, y_c=None, input_precision=1, window_scaling=False)

Tracks spots through intensity information and velocity prediction.

easyleed.base.adjust_slice(image, x_sl_min, x_sl_max, y_sl_min, y_sl_max)

Adjusts slice if it is trying to get pieces outside the image.

>>> image = np.ones((2, 2))
>>> adjust_slice(image, 0, 1.5, 0, 2)
(0, 1, 0, 2)
>>> adjust_slice(image, -5.5, 2, -0.5, 10)
(0, 2, 0, 2)

easyleed.base.calc_distances(shape, x, y, squared=True)

Helper function that returns an array of distances to x, y. This array can be useful for fancy indexing of numpy arrays.

squared: return the squared distance (default: True)

easyleed.base.calc_intensity(npimage, x, y, radius, background_substraction=True)

Calculates the intensity of a spot.

npimage: numpy array of intensity values x, y: position of the spot radius: radius of the spot background_substraction: boolean to turn substraction on/off

easyleed.base.gaussian2d(height, center_x, center_y, width_x, width_y=None, offset=0)

Returns a two dimensional gaussian function with the given parameters

easyleed.base.guess_from_Gaussian(image, *args, **kwargs)

Guess position of spot from a Gaussian fit.

easyleed.base.moments(data)

Calculates the moments of 2d data. Returns [height, x, y, width_x, width_y] the gaussian parameters of a 2D distribution by calculating its moments.

easyleed.kalman

Kalman filters for tracking the spots

class easyleed.kalman.AbstractKalmanFilter(x, P, H)

Abstract implementation of a Kalman filter.

Matrices and Vectors can be given in any input format np.matrix() understands. Vectors are internally transposed and should therefore be given as column vectors.

measurement_distance(z, R=None)

Returns the squared Mahalanobis distance of the given measurement.

z: measurement vector

predict(F, Q=array([[ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.], [ 0., 0., 0., 0.]]))

Predict next state.

F: state transition matrix Q: process covariance matrix

predict_measurement()

Returns the predicted measurement.

predict_measurement_covariance(R=None)

Returns the covariance matrix of a predicted measurement.

update(z, R)

Update state estimate.

z: measurement vector R: measurement covariance matrix

class easyleed.kalman.AbstractPVKalmanFilter(x_in, y_in, P, time, vx_in=0, vy_in=0)

Kalman filter for 2d-tracking using position and velocity as state variables.

easyleed.io

Import routines for different LEED file formats

class easyleed.io.FitsImageLoader(image_paths, regex)

Load .fits image files.

class easyleed.io.ImageFormat(abbrev, loader)

Class describing an image format.

class easyleed.io.ImageLoader(image_paths, regex)

Abstract base class for a class loading LEED images.

Subclasses need to provide

• get_image(image_path)

Subclasses may override (default: from filename with regex)

• get_energy(image_path)

current_energy()

Get current energy.

custom_iter(energies)

Returns an iterator to iter over the given energies.

goto(energy)

Get image at given beam energy.

next()

Get image at next higher beam energy.

previous()

Get image at next lower beam energy.

restart()

Start at lowest energy again.

class easyleed.io.ImgImageLoader(image_paths, regex)

Load .img image files (HotLeed format).

class easyleed.io.PILImageLoader(image_paths, regex)

Load image files supported by Python Imaging Library (PIL).

easyleed.io.normalize255(array)

Returns a normalized array of uint8.

easyleed.io.npimage2qimage(npimage)

Converts numpy grayscale image to qimage.

easyleed.gui

Various classes for providing a graphical user interface.

class easyleed.gui.AboutWidget

PyQt widget for About Box Panel

class easyleed.gui.GraphicsScene(parent=None)

Custom GraphicScene having all the main content.

drawBackground(painter, rect)

Draws image in background if it exists.

keyPressEvent(event)

Processes key events through either

• deleting the focus item

or

• propagating the event

mousePressEvent(event)

Processes mouse events through either

• propagating the event

or

• instantiating a new Circle (on left-click)
• instantiating a new Center (on right-click)

removeAll()

Remove all spots from the scene (leaves background unchanged).

removeCenter()

Remove center from the scene (leaves background unchanged).

setBackground(image, labeltext)

Sets the background image.

class easyleed.gui.GraphicsView(parent=None)

Custom GraphicsView to display the scene.

class easyleed.gui.MainWindow(parent=None)

EasyLEED’s main window.

addActions(target, actions)

Convenience function that adds the actions to the target. If an action is None a separator will be added.

createAction(text, slot=None, shortcut=None, icon=None, tip=None, checkable=False, signal='triggered()')

Convenience function that creates an action with the specified attributes.

custEnBtnClicked()

Action when custom energy button is clicked

fileOpen()

Prompts the user to select input image files.

fileQuit()

Special quit-function as the normal window closing might leave something on the background

liveSmoothParameters()

Real time setting smoothing parameters from Parameter Settings panel into actual smoothed curve

loadCenter()

Load Center location from csv file

loadSpots()

Load Spots location from csv file

restart()

Delete stored plot information and start fresh

saveCenter()

Saves the center locations to a file, uses workers saveCenter-method

saveScreenShot()

Save Screenshot

saveSpots()

Saves the spot locations to a file, uses workers saveLoc-method

setCustEnergy()

Take energy from custom energy text and move the corresponding frame

slider_moved(sliderNewPos)

This function tracks what to do with a slider movement.

class easyleed.gui.ParameterSettingWidget

PyQt widget for setting tracking parameters

applyParameters()

Parameter setting control

collectParameters()

Parameter setting control

loadValues()

Load a file of set parameter values that has been saved with the widget

saveValues()

Basic saving of the set parameter values to a file

class easyleed.gui.PlotWidget

Custom PyQt widget canvas for plotting

create_main_frame()

Create the mpl Figure and FigCanvas objects.

save()

Saving the plot

updatePlot()

Basic Matplotlib plotting I(E)-curve

class easyleed.gui.QGraphicsCenterItem(point, size, parent=None)

Provides an QGraphicsItem to display the center position on a QGraphicsScene.

class easyleed.gui.QGraphicsMovableItem(parent=None)

Provides an QGraphicsItem that can be moved with the arrow keys.

Pressing Shift at the same time allows fine adjustments.

keyPressEvent(event)

Handles keyPressEvents.

The item can be moved using the arrow keys. Applying Shift at the same time allows fine adjustments.

moveDown(distance)

Moves the circle distance down.

moveLeft(distance)

Moves the circle distance to the left.

moveRight(distance)

Moves the circle distance to the right.

moveUp(distance)

Moves the circle distance up.

onPositionChange(point)

Handles incoming position change request.

class easyleed.gui.QGraphicsSpotItem(point, radius, parent=None)

Provides an QGraphicsItem to display a Spot on a QGraphicsScene.

changeSize(inc)

Change radius by inc.

inc > 0: increase inc < 0: decrease

keyPressEvent(event)

Handles keyPressEvents.

The circles radius can be changed using the plus and minus keys.

onRadiusChange(radius)

Handles incoming radius change request.

class easyleed.gui.QSpotModel(parent=None)

Wraps a SpotModel to offer signals.

Provides the following signals: - intensityChanged - positionChanged - radiusChanged

class easyleed.gui.Worker(spots, center, energy, parent=None)

Worker that manages the spots.

spots_map: - key: spot - value: SpotModel, Tracker

createDataframe()

Create internal dataframe with intensities, spot locations, and center

numProcessed()

Return the number of processed images.

saveCenter(filename)

save center location

saveIntensity(filename)

save intensities

saveLoc(filename)

save spots location