Glossary

Full list of arpespythontools modules/ routines in alphabetical order:

import arpespythontools as arp

crop_2d

data_crop, x_crop, y_crop = arp.crop_2d(data, x, y, x_min, x_max, y_min, y_max)

Returns cropped 2D array and corresponding axes scaling vectors defined by [x_min, x_max] and [y_min, y_max].

Inputs:

• data : 2D array (intensity matrix).
• x : 1D vector (e.g., angle).
• y : 1D vector (e.g., energy).
• x_min and x_max : lower and upper bound of x to crop.
• y_min and y_max : lower and upper bound of y to crop.

Outputs:

• data_crop : cropped 2D array.
• x_crop : corresponding x-scaling vector.
• y_crop : corresponding y-scaling vector.

cv2d

cv2d = arp.cv2d(data, x, y, bw=5, c1=0.001, c2=0.001, w=1)

Calculates two-dimensional curvature. The details about the curvature method can be found here: P. Zhang et. al., A precise method for visualizing dispersive features in image plots, Review of Scientific Instruments 82, 043712 (2011).

Inputs:

• data : 2D spectra.
• x : 1D array of energy.
• y : 1D array of theta values.
• bw : width for box-car smoothing, integer number of points (default value = 5).
• c1, c2 : free parameters as described in the above reference (optional).
• w : scaling weight (optional). Default weight is 1.

Outputs:

• cv2d : 2D array of curvature. Output array has the same shape as the input array.

export_itx

arp.export_itx(path, data, x=[], y=[], z =[], wave_name='wave', \
    x_label='x-label', y_label='y-label', z_label='z-label')

Exports 1D, 2D, or 3D array to Igor text (.itx) file.

Inputs:

• path : Output filename or path of the .itx file.
• data : Input data array to save. Could be 1D, 2D, or 3D array.
• x, y, z (optional) : axes scaling for the corresponding input data array. If a value is not provided, default DimOffset=0 and DimDelta=1 would be applied.
• wave_name (optional) : Igor wave name.
• x-, y-, z-label (optional) : labels for x, y and z, respectively.

import_itx

data, x, y, z = arp.import_itx(name)

Loads data and its axes scaling from Igor text (.itx) format.

Inputs:

• name (string) : Input Igor text filename.

Outputs:

• data : 1D, 2D, or 3D array.
• x, y, z : axes scales. Number of output returned depends on the input wave dimension.

k_conv

data_k, e_bin, k = arp.k_conv(data, energy, angle, fermi_energy)

Transforms the intensity fromm real space to k-space.

Inputs:

• data : 2D array of intensity values in real space. Dimension 1 is along energy and Dimension 2 is along angle.
• energy : 1D array of kinetic energy values in eV.
• angle : 1D array of theta values in degree.
• fermi_energy (number) : Fermi energy value in eV in terms of kinetic energy.

Outputs:

• data_k : 2D array of intensity values in k-space. Intensity values outside the interpolation range is set to NaN (not a number).
• e_bin : 1D array of Binding energy values in eV. Binding energy below Fermi energy is positive convention is used.
• k : 1D array of momentum (k) values in $\mathring{A}^{-1}$.

k_conv3d

data_k, e_bin, kx, ky = arp.k_conv3d(data, energy, theta, phi, fermi_energy)

Transforms the Fermi map data from real space to k-space.

Inputs:

• data : 3D matrix of intensity values in real space. Dimension 1 is along kinetic energy, Dimension 2 is along theta, and Dimension 3 along phi.
• energy : 1D array of kinetic energy values in eV.
• theta : 1D array of theta values in degree. This is the direction along the slit.
• phi : 1D array of phi values in degree. This is the direction perpendicular to the slit.
• fermi_energy (number) : Fermi energy value in eV in terms of kinetic energy.

Outputs:

• data_k : 3D matrix of intensity values in k-space. Intensity values outside the interpolation range is set to NaN (not a number).
• e_bin : 1D array of Binding energy values in eV. Binding energy below Fermi energy is positive convention is used.
• kx, ky : 1D array of momentum (k) values in $\mathring{A}^{-1}$ along the slit, and perpendicular to the slit directions, respectively.

k_conv3d_mp

data_k, e_bin, kx, ky = arp.k_conv3d_mp(data, energy, theta, phi, fermi_energy)

Multiprocessing implementation of k_conv3d. Should be up to as many times faster as many processor cores are available. Transforms the Fermi map data from real space to k-space.

Inputs:

• data : 3D matrix of intensity values in real space. Dimension 1 is along kinetic energy, Dimension 2 is along theta, and Dimension 3 along phi.
• energy : 1D array of kinetic energy values in eV.
• theta : 1D array of theta values in degree. This is the direction along the slit.
• phi : 1D array of phi values in degree. This is the direction perpendicular to the slit.
• fermi_energy (number) : Fermi energy value in eV in terms of kinetic energy.

Outputs:

• data_k : 3D matrix of intensity values in k-space. Intensity values outside the interpolation range is set to NaN (not a number).
• e_bin : 1D array of Binding energy values in eV. Binding energy below Fermi energy is positive convention is used.
• kx, ky : 1D array of momentum (k) values in $\mathring{A}^{-1}$ along the slit, and perpendicular to the slit directions, respectively.

laplacian

diff2 = arp.laplacian(data, x, y, bw=5, w=1)

Laplacian (second order partial derivatives with respect to both energy and angle) of the spectra.

Inputs:

• data : 2D spectra.
• x : 1D array of energy.
• y : 1D array of theta values.
• bw : width for box-car smoothing, integer number of points (default value = 5).
• w : scaling weight (optional). Default weight is 1.

Outputs:

• diff2 : 2D array of spectra after taking second order partial derivative w.r.t. both energy and angle. This array has the same shape as input array.

line_profile

edc = arp.line_profile(data, y, y_min, y_max)

Returns the 1D vector of integrated line profile. The integration is done along the second dimension of data.

Inputs:

• data : 2D array.
• y : 1D vector of axis scaling along the second dimension of data.
• y_min, y_max : integration bounds.

Outputs:

• edc : 1D vector of integrated values defined by the width [y_min, y_max] along the first dimension.

load_ses_map

data, energy, theta, phi = arp.load_map_data(name)

Loads Fermi map data from output .zip file of Scienta-Omicron SES program.

Inputs:

• name (string) : name or file path of .zip map data file. It could be a local path or URL path.

Outputs:

• data: 3D array of intensity values. Dimension 1 → energy, Dimension 2 → angle theta (along the slit direction), and Dimension 3 → angle phi (azimuth/ perpendicular to the slit direction).
• energy: 1D vector of kinetic energy points in eV.
• theta: 1D vector of theta values in degree.
• phi : 1D vector of phi values in degree.

load_ses_spectra

data, angle, energy = arp.load_ses_spectra(name)

Loads data from a text file produced by Scienta-Omicron SES program.

Inputs:

• name (string) : name or file path of SES .txt file. It could be a local path or a URL address.

Outputs:

• data : 2D array (numpy ndarry) of intensity values.
• angle : 1D vector (numpy ndarry) of angle values in degree.
• energy : 1D vector (numpy ndarry) of kinetic energy values in eV.

plane_slice

surf = arp.plane_slice(data, x, x_min, x_max)

Returns the 2D slice along the first dimension of data and integrated in the width [x_min, x_max].

Inputs:

• data : 3D matrix.
• x : axes scaling along the first dimension.
• x_min, x_max : integration bounds.

Outputs:

• surf : 2D array.

rotate_2d

data_r, theta_r, phi_r = arp.rotate_2d(data, angle, theta, phi)

Rotates 2D array with rotation axis perpendicular to the plane. Center of rotation is at theta=0, phi=0.

Inputs:

• data : 2D array. The data will be rotated perpendicular to the plane.
• angle : amount of rotation in degree. Positive value rotates clockwise.
• theta : 1D array of axis scaling along the second dimension of data.
• phi : 1D array of axis scaling along the third dimension of data.

Outputs:

• data_r : rotated 2D matrix. Data points outside of interpolation range is set to NaN (not a number).
• theta_r : 1D array of axis scaling along the second dimension of data_r.
• phi_r : 1D array of axis scaling along the third dimension of data_r.

rotate_3d

data_r, theta_r, phi_r = arp.rotate_3d(data, angle, theta, phi)

Rotates the volume data (3D matrix) with respect to the first dimension. Center of rotation is at theta=0, phi=0.

Inputs:

• data : 3D array. First, second, and third dimensions are along energy, theta, and phi, respectively. The data will be rotated perpendicular to energy, i.e., in the theta-phi plane.
• angle : amount of rotation in degree. Positive value rotates clockwise.
• theta : 1D array of axis scaling along the second dimension of data.
• phi : 1D array of axis scaling along the third dimension of data.

Outputs:

• data_r : rotated 3D matrix. Data points outside of interpolation range is set to NaN (not a number).
• theta_r : 1D array of axis scaling along the second dimension of data_r.
• phi_r : 1D array of axis scaling along the third dimension of data_r.

save_xps

arp.save_xps(energy, intensity, "xps_data.x_y")

Save XPS energy and intensity in two column plaintext file.

Inputs:

• energy : one dimensional vector
• intensity : one dimensional vector
• filename : Optional output filename.

Two column data is saved in file.