Response

class ompy.Response(path)[source]

Bases: object

Interpolates response read from file for current setup

Implementaion of following method Guttormsen et al., NIM A 374 (1996) 371–376. DOI:10.1016/0168-9002(96)00197-0

Throughout the class, be aware that “compton” mat refer to all non-discrete structures (instead of the real Compton effect only).

Variables

  • resp (pd.DataFrame) – Information of the response table

  • compton_matrix (np.ndarray) – array with compton counts. Shape is (N_incident, N_cmp).

  • Ecmp_array (np.ndarray) – energy array for the compton counts

  • smooth_compton (bool) – If True, the compoton array is smoothed before further processing. defaults to False

  • truncate (float) – After how many sigma to truncate gaussian smoothing. Defaults to 6.

The resonse object is initialized with the path to the source files required to perform the interpolation. The path varaiable can either be a folder (assuming “old” format) or a zip file containing the files otherwise found in the folder in the “old” format.

Parameters

path (str or Path) – Path to the required file(s)

Todo

  • adapt rutines for the possibility that not all cmp spectra have the same binning

Methods Summary

E_compton(Eg, theta)

Calculates the energy of an electron that is scattered an angle theta by a gamma-ray of energy Eg.

LoadDir(path[, resp_name, spec_prefix])

Method for loading response file and compton spectra from a folder.

LoadZip(path[, resp_name, spec_prefix])

Method for loading response file and compton spectra from zipfile.

dE_dtheta(Eg, theta)

Function to correct number of counts due to delta(theta) Adapted from MAMA in the file kelvin.f It is dE/dtheta of the E(theta) in Eq.

discrete_peaks(i_response, fwhm_abs_array)

Add discrete peaks for a given channel and smooth them

fan_method(E, compton, i_start, i_stop)

Fan method

get_closest_compton(E)

Find and rebin closest energies from available response functions

get_probabilities()

Interpolate full-energy peak probabilities (…)

interpolate([Eout, fwhm_abs, return_table])

Interpolated the response matrix

iterpolate_checks()

Check on the inputs to interpolate

linear_backscatter(E, compton)

Interpolate one-to-one up to the backscatter peak

linear_cmp_interpolation(E, compton[, …])

Linear interpolation between the compton spectra

linear_to_end(E, compton, i_start, i_stop)

Interpolate one-to-one from the last fan energy to the Emax

two_channel_split(E_centroid, E_array)

When E_centroid is between two bins in E_array, this function returns the indices of the two nearest bins and the distance to the lower bin.

Methods Documentation

static E_compton(Eg, theta)[source]

Calculates the energy of an electron that is scattered an angle theta by a gamma-ray of energy Eg. Adapted from MAMA, file “folding.f”, which references Canberra catalog ed.7, p.2.

Note

For Eg <= 0.1 it returns Eg. (workaround)

Parameters

  • Eg – Energy of gamma-ray in keV

  • theta – Angle of scatter in radians

Returns

Energy Ee of scattered electron

LoadDir(path, resp_name='resp.dat', spec_prefix='cmp')[source]

Method for loading response file and compton spectra from a folder.

Parameters

  • path (Union[str, Path]) – path to folder

  • resp_name (Optional[str], optional) – name of file with response table

  • spec_prefix (Optional[str], optional) – Prefix for all spectra

Returns

(tuple) containing

  • resp (DataFrame): Information of the response table.

  • compton_matrix (ndarray): matrix with compton counts.

    Shape is (N_incident, N_cmp)

  • last.E (ndarray): energy array

LoadZip(path, resp_name='resp.csv', spec_prefix='cmp')[source]

Method for loading response file and compton spectra from zipfile.

Is assumes that path is a zip file that constains at least XX files. At least one has to be a special summary table to be named resp_name.

Parameters

  • path (Union[str, Path]) – path to folder

  • resp_name (Optional[str], optional) – name of file with response table

  • spec_prefix (Optional[str], optional) – Prefix for all spectra

Returns

(tuple) containing

  • resp (DataFrame): Information of the response table.

  • compton_matrix (ndarray): matrix with compton counts.

    Shape is (N_incident, N_cmp)

  • last.E (ndarray): energy array

static dE_dtheta(Eg, theta)[source]

Function to correct number of counts due to delta(theta) Adapted from MAMA in the file kelvin.f It is dE/dtheta of the E(theta) in Eq. (2) in Guttormsen 1996.

Parameters

  • Eg – Energy of gamma-ray in keV

  • theta – Angle of scatter in radians

Returns

dE_dtheta

Return type

TYPE

discrete_peaks(i_response, fwhm_abs_array)[source]

Add discrete peaks for a given channel and smooth them

Parameters

  • i_response (int) – Channel in response matrix

  • fwhm_abs_array (np.ndarray) – Array with fwhms for each channel

Return type

ndarray

Returns

Array with smoothed discrete peaks

fan_method(E, compton, i_start, i_stop)[source]

Fan method

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • i_start (int) – Index where to start (usually end of backscatter)

  • i_stop (int) – Index where to stop (usually E+n*resolution). Note that it can be stopped earlier, which will be reported through i_last

Returns

R is Response for E, and i_last last

index of fan-method

Return type

Tuple[np.ndarray, int]

get_closest_compton(E)[source]

Find and rebin closest energies from available response functions

If E < self.resp[‘Eg’].min() the compton matrix will be replaced by an array of zeros.

Parameters

E (float) – Description

Returns

ilow and ihigh are indices of closest energies

Return type

Tuple[int, int]

get_probabilities()[source]

Interpolate full-energy peak probabilities (…)

interpolate(Eout=None, fwhm_abs=None, return_table=False)[source]

Interpolated the response matrix

Perform the interpolation for the energy range specified in Eout with FWHM at 1332 keV given by FWHM_abs (in keV).

The interpolation is split into energy regions. Below the back-scattering energy Ebsc we interpolate linearly, then we apply the “fan method” (Guttormsen 1996) in the region from Ebsc up to the Compton edge, then linear extrapolation again the rest of the way.

Parameters

  • folderpath – The path to the folder containing Compton spectra and

  • resp.dat –

  • Eout_array – The desired energies of the output response matrix.

  • fwhm_abs (Optional[float]) – The experimental absolute full-width-half-max at 1.33 MeV. Note: In the article it is recommended to use 1/10 of the real FWHM for unfolding.

  • return_table (optional) – Returns “all” output, see below

Returns

  • response (Matrix): Response matrix with incident energy on the “Ex” axis and the spectral response on the “Eg” axis

  • response_table (DataFrame, optional): Table with efficiencies, FE, SE (…) probabilities, and so on

Return type

Matrix or Tuple[Matrix, pd.DataFrame]

iterpolate_checks()[source]

Check on the inputs to interpolate

linear_backscatter(E, compton)[source]

Interpolate one-to-one up to the backscatter peak

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

Returns

R is Response for E, and

i_bc is index of backscatter peak

Return type

Tuple[np.ndarray, int]

linear_cmp_interpolation(E, compton, fill_value='extrapolate')[source]

Linear interpolation between the compton spectra

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • fill_value (str, optional) – Fill value beyond boundaries

Returns

Interpolated values

Return type

f_cmp (nd.array)

linear_to_end(E, compton, i_start, i_stop)[source]

Interpolate one-to-one from the last fan energy to the Emax

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • i_start (int) – Index where to start (usually end of fan method)

  • i_stop (int) – Index where to stop (usually E+n*resolution)

Returns

Response for E

Return type

np.ndarray

static two_channel_split(E_centroid, E_array)[source]

When E_centroid is between two bins in E_array, this function returns the indices of the two nearest bins and the distance to the lower bin. The distance to the higher bin is 1-floor_distance

Parameters

  • E_centroid (double) – The energy of the centroid (mid-bin)

  • E_array (np.array, double) – The energy grid to distribute

static E_compton(Eg, theta)[source]

Calculates the energy of an electron that is scattered an angle theta by a gamma-ray of energy Eg. Adapted from MAMA, file “folding.f”, which references Canberra catalog ed.7, p.2.

Note

For Eg <= 0.1 it returns Eg. (workaround)

Parameters

  • Eg – Energy of gamma-ray in keV

  • theta – Angle of scatter in radians

Returns

Energy Ee of scattered electron

LoadDir(path, resp_name='resp.dat', spec_prefix='cmp')[source]

Method for loading response file and compton spectra from a folder.

Parameters

  • path (Union[str, Path]) – path to folder

  • resp_name (Optional[str], optional) – name of file with response table

  • spec_prefix (Optional[str], optional) – Prefix for all spectra

Returns

(tuple) containing

  • resp (DataFrame): Information of the response table.

  • compton_matrix (ndarray): matrix with compton counts.

    Shape is (N_incident, N_cmp)

  • last.E (ndarray): energy array

LoadZip(path, resp_name='resp.csv', spec_prefix='cmp')[source]

Method for loading response file and compton spectra from zipfile.

Is assumes that path is a zip file that constains at least XX files. At least one has to be a special summary table to be named resp_name.

Parameters

  • path (Union[str, Path]) – path to folder

  • resp_name (Optional[str], optional) – name of file with response table

  • spec_prefix (Optional[str], optional) – Prefix for all spectra

Returns

(tuple) containing

  • resp (DataFrame): Information of the response table.

  • compton_matrix (ndarray): matrix with compton counts.

    Shape is (N_incident, N_cmp)

  • last.E (ndarray): energy array

static dE_dtheta(Eg, theta)[source]

Function to correct number of counts due to delta(theta) Adapted from MAMA in the file kelvin.f It is dE/dtheta of the E(theta) in Eq. (2) in Guttormsen 1996.

Parameters

  • Eg – Energy of gamma-ray in keV

  • theta – Angle of scatter in radians

Returns

dE_dtheta

Return type

TYPE

discrete_peaks(i_response, fwhm_abs_array)[source]

Add discrete peaks for a given channel and smooth them

Parameters

  • i_response (int) – Channel in response matrix

  • fwhm_abs_array (np.ndarray) – Array with fwhms for each channel

Return type

ndarray

Returns

Array with smoothed discrete peaks

fan_method(E, compton, i_start, i_stop)[source]

Fan method

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • i_start (int) – Index where to start (usually end of backscatter)

  • i_stop (int) – Index where to stop (usually E+n*resolution). Note that it can be stopped earlier, which will be reported through i_last

Returns

R is Response for E, and i_last last

index of fan-method

Return type

Tuple[np.ndarray, int]

get_closest_compton(E)[source]

Find and rebin closest energies from available response functions

If E < self.resp[‘Eg’].min() the compton matrix will be replaced by an array of zeros.

Parameters

E (float) – Description

Returns

ilow and ihigh are indices of closest energies

Return type

Tuple[int, int]

get_probabilities()[source]

Interpolate full-energy peak probabilities (…)

interpolate(Eout=None, fwhm_abs=None, return_table=False)[source]

Interpolated the response matrix

Perform the interpolation for the energy range specified in Eout with FWHM at 1332 keV given by FWHM_abs (in keV).

The interpolation is split into energy regions. Below the back-scattering energy Ebsc we interpolate linearly, then we apply the “fan method” (Guttormsen 1996) in the region from Ebsc up to the Compton edge, then linear extrapolation again the rest of the way.

Parameters

  • folderpath – The path to the folder containing Compton spectra and

  • resp.dat –

  • Eout_array – The desired energies of the output response matrix.

  • fwhm_abs (Optional[float]) – The experimental absolute full-width-half-max at 1.33 MeV. Note: In the article it is recommended to use 1/10 of the real FWHM for unfolding.

  • return_table (optional) – Returns “all” output, see below

Returns

  • response (Matrix): Response matrix with incident energy on the “Ex” axis and the spectral response on the “Eg” axis

  • response_table (DataFrame, optional): Table with efficiencies, FE, SE (…) probabilities, and so on

Return type

Matrix or Tuple[Matrix, pd.DataFrame]

iterpolate_checks()[source]

Check on the inputs to interpolate

linear_backscatter(E, compton)[source]

Interpolate one-to-one up to the backscatter peak

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

Returns

R is Response for E, and

i_bc is index of backscatter peak

Return type

Tuple[np.ndarray, int]

linear_cmp_interpolation(E, compton, fill_value='extrapolate')[source]

Linear interpolation between the compton spectra

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • fill_value (str, optional) – Fill value beyond boundaries

Returns

Interpolated values

Return type

f_cmp (nd.array)

linear_to_end(E, compton, i_start, i_stop)[source]

Interpolate one-to-one from the last fan energy to the Emax

Parameters

  • E (float) – Incident energy

  • compton (dict) – Dict. with information about the compton spectra to interpolate between

  • i_start (int) – Index where to start (usually end of fan method)

  • i_stop (int) – Index where to stop (usually E+n*resolution)

Returns

Response for E

Return type

np.ndarray

static two_channel_split(E_centroid, E_array)[source]

When E_centroid is between two bins in E_array, this function returns the indices of the two nearest bins and the distance to the lower bin. The distance to the higher bin is 1-floor_distance

Parameters

  • E_centroid (double) – The energy of the centroid (mid-bin)

  • E_array (np.array, double) – The energy grid to distribute