toolbox_scs.detectors.viking

Module Contents

Classes

Viking

The Viking analysis (spectrometer used in combination with Andor Newton

class toolbox_scs.detectors.viking.Viking(proposalNB)

The Viking analysis (spectrometer used in combination with Andor Newton camera)

The objects of this class contain the meta-information about the settings of the spectrometer, not the actual data, except possibly a dark image for background subtraction.

The actual data is loaded into xarray`s via the method `from_run(), and stays there.

PROPOSAL

the number of the proposal

Type:

int

X_RANGE

the slice to take in the non-dispersive direction, in pixels. Defaults to the entire width.

Type:

slice

Y_RANGE

the slice to take in the energy dispersive direction

Type:

slice

USE_DARK

whether to do dark subtraction. Is initially False, magically switches to True if a dark has been loaded, but may be reset.

Type:

bool

ENERGY_CALIB

The 2nd degree polynomial coefficients for calibration from pixel to energy. Defaults to [0, 1, 0] (no calibration applied).

Type:

1D array (len=3)

BL_POLY_DEG

the dgree of the polynomial used for baseline subtraction. Defaults to 1.

Type:

int

BL_SIGNAL_RANGE

the dispersive-axis range, defined by an interval [min, max], to avoid when fitting a polynomial for baseline subtraction. Multiple ranges can be provided in the form [[min1, max1], [min2, max2], …].

Type:

list

FIELDS

the fields to be loaded from the data. Add additional fields if so desired.

Type:

list of str

Example

proposal = 2953 v = Viking(proposal) v.X_RANGE = slice(0, 1900) v.Y_RANGE = slice(38, 80) v.ENERGY_CALIB = [1.47802667e-06, 2.30600328e-02, 5.15884589e+02] v.BL_SIGNAL_RANGE = [500, 545]

set_params(**params)

get_params(*params)

from_run(runNB, add_attrs=True)

load a run

Load the run runNB. A thin wrapper around toolbox_scs.load.

Parameters:

• runNB (int) – the run number

• add_attrs (bool) – if True, adds the camera parameters as attributes to the dataset (see get_camera_params())

• Output –

• ------ –

• ds (xarray Dataset) – the dataset containing the camera images

Example

data = v.from_run(145) # load run 145

data1 = v.from_run(145) # load run 145 data2 = v.from_run(155) # load run 155 data = xarray.concat([data1, data2], ‘trainId’) # combine both

load_dark(runNB=None)

integrate(data)

This function calculates the mean over the non-dispersive dimension to create a spectrum. If the camera parameters are known, the spectrum is multiplied by the number of photoelectrons per ADC count. A new variable “spectrum” is added to the data.

get_camera_gain(run)

Get the preamp gain of the camera in the Viking spectrometer for a specified run.

Parameters:

• run (extra_data DataCollection) – information on the run

• Output –

• ------ –

• gain (int) –

e_per_counts(run, gain=None)

Conversion factor from camera digital counts to photoelectrons per count. The values can be found in the camera datasheet (Andor Newton) but they have been slightly corrected for High Sensitivity mode after analysis of runs 1204, 1207 and 1208, proposal 2937.

Parameters:

• run (extra_data DataCollection) – information on the run

• gain (int) – the camera preamp gain

• Output –

• ------ –

• ret (float) – photoelectrons per count

get_camera_params(run)

removePolyBaseline(data)

Removes a polynomial baseline to a spectrum, assuming a fixed position for the signal.

Parameters:

• data (xarray Dataset) – The Viking data containing the variable “spectrum”

• Output –

• ------ –

• data – the original dataset with the added variable “spectrum_nobl” containing the baseline subtracted spectra.

xas(data, data_ref, thickness=1, plot=False, plot_errors=True, xas_ylim=(-1, 3))

Given two independent datasets (one with sample and one reference), this calculates the average XAS spectrum (absorption coefficient), associated standard deviation and standard error. The absorption coefficient is defined as -log(It/I0)/thickness.

Parameters:

• data (xarray Dataset) – the dataset containing the spectra with sample

• data_ref (xarray Dataset) – the dataset containing the spectra without sample

• thickness (float) – the thickness used for the calculation of the absorption coefficient

• plot (bool) – If True, plot the resulting average spectra.

• plot_errors (bool) – If True, adds the 95% confidence interval on the spectra.

• xas_ylim (tuple or list of float) – the y limits for the XAS plot.

• Output –

• ------ –

• xas (xarray Dataset) – the dataset containing the computed XAS quantities: I0, It, absorptionCoef and their associated errors.

calibrate(runList, plot=True)

This routine determines the calibration coefficients to translate the camera pixels into energy in eV. The Viking spectrometer is calibrated using the beamline monochromator: runs with various monochromatized photon energy are recorded and their peak position on the detector are determined by Gaussian fitting. The energy vs. position data is then fitted to a second degree polynomial.

Parameters:

• runList (list of int) – the list of runs containing the monochromatized spectra

• plot (bool) – if True, the spectra, their Gaussian fits and the calibration curve are plotted.

• Output –

• ------ –

• energy_calib (np.array) – the calibration coefficients (2nd degree polynomial)