Glossary

calc_area

area = suv.calc_area(y, x, x_start=None, x_end=None)

Calculates area under the curve for given x and y values. x_start and x_end can be specified to set the limit of integration region, if not provided whole range is integrated.

$$A = \int_{x\_start}^{x\_end} y dx$$

Inputs:

• x and y : 1D vectors of same length.
• x_start and x_end : number (float or int), lower and upper limits of the integration. Optional inputs.

Outputs:

• area : number (float). Area under the curve. Could take negative values (e.g., $y$ is negative and $x$ is positive).

fit_gauss

x_fit, y_fit = suv.fit_gauss(x, y, a=None, x0=None, sigma=None, xmin=None, xmax=None, num=1000)

returns x, Gaussian fitted y values, and prints out relevant parameters. xmin and xmax determines the range to fit. If xmin and xmax are not provided, whole range is used. num determines the number of points returned in x_fit and y_fit.

Inputs:

• x and y : 1D vectors of same length.
• a : optional input, number, peak height in the units of $y$.
• x0 : optional input, number, peak position in $x$.
• sigma : optional input, number, width of peak.
• xmin and xmax : number (float or int), lower and upper bounds of fitting. Optional inputs.
• num : length of returned vectors (x_fit and y_fit). Optional input, default is 1000.

Outputs:

• x_fit and y_fit : 1D vectors of length num (default is 1000).

It will also print out the relevant fitting parameters to the standard output.

fit_lorentz

x_fit, y_fit = suv.fit_lorentz(x, y, a=None, x0=None, gamma=None, xmin=None, xmax=None, num=1000)

returns x, Lorentzian fitted y values, and prints out relevant parameters. xmin and xmax determines the range to fit. If xmin and xmax are not provided, whole range is used. num determines the number of points returned in x_fit and y_fit.

Inputs:

• x and y : 1D vectors of same length.
• a : optional input, number, peak height in the units of $y$.
• x0 : optional input, number, peak position in $x$.
• gamma : optional input, number, width of peak.
• xmin and xmax : number (float or int), lower and upper bounds of fitting. Optional inputs.
• num : length of returned vectors (x_fit and y_fit). Optional input, default is 1000.

Outputs:

• x_fit and y_fit : 1D vectors of length num (default is 1000).

It will also print out the relevant fitting parameters to the standard output.

load

data = suv.load(filename, scan=None)
data = suv.load("datafile.txt", 2)

It will return a two dimensional array with columns for various parameters. If the second argument, i.e., the scan number is not specified, the code will read the last scan from the file.

Inputs:

• filename : string, local or https file path.
• scan : optional, integer, if no scan argument is provided it loads the last scan.

Outputs:

• data : 2D array. Rows represent different data points, while the columns are different parameters (energy, intensity etc.).

lock_peak

data_corr = suv.lock_peak(data, refdata, x1=None, x2=None, E_col=0, I_col=9, I0_col=4)

Locks peak position with respect to the reference data. It locks the maximum of intensity to the same energy; the range of peak search can be specified by input x1 and x2. If no bounds are given, it will find the maximum in the whole data range.

norm_bg

int_corr = suv.norm_bg(energy, intensity, x1, x2, x_norm_loc=None)

Removes linear background, and normalizes the data. x1, x2 are energy values that determines the slope of the background. By default the normalization done at the tail point of the spectra. It can be changed to other point, enter the corresponding energy value as x_norm_loc. The intention is to normalize at an energy value away from the peaks/features of interest.

save_csv

suv.save_csv("datafile.txt", csvname=None, scan=None)

saves scan to a csv file. The file will be saved in the save directory as datafile with name datafile.csv unless csvname is specified. Like the load module, if the scan number is not specified, it will read the last scan from the file.