`NuclearReflectivity`

class nexus.NuclearReflectivity(experiment, sample, angles, time_start, time_stop, time_step, max_detuning=400.0, intensity_data=[], scaling='auto', background=0.0, offset=0.0, resolution=0.001, fit_weight=1.0, bunch_spacing=inf, residual=<nexus.clib.cnexus.Sqrt; proxy of <Swig Object of type 'Residual *'> >, coherence=False, print_progress=False, id='')

Bases: FitMeasurement

Constructor for the NuclearReflectivityEnergy class. Class to calculate the angular dependent and time-integrated resonant scattering intensity of the experiment while for one sample the gracing-incidence angle is changed.

Parameters:

id (string) – User identifier.
experiment (Experiment) – Experiment.
sample (GrazingSample) –
Sample of the Experiment for the calculation.

Changed in version 2.0.0: changed from old Sample class to GrazingSample.
angles (list) – List of the angles.
time_start (float) – Start time for the integration (ns).
time_stop (float) – Stop time for the integration (ns).
time_step (float) – Step size for the time axis (ns).
max_detuning (float) – Maximum value of the energy detuning in units of the resonant linewidth. Set this value to speed up the calculation. If zero no maximum is applied. The FFT window is always auto.
intensity_data (list or ndarray) – Intensity data for fitting.
scaling (float or Var or string) – Intensity scaling factor for fitting. Default is auto.
background (float or Var or string) – Background for fitting. Default is 0.
offset (float or Var) –
Angular offset of the model. Defualt is 0.

Added in version 1.1.0.
resolution (float or Var) – Resolution value for convolution.
fit_weight (float) – Relative weight for the cost function in multi measurement fitting.
bunch_spacing (float) – Spacing of subsequent X-ray bunches in time (nanoseconds).
residual (Residual) – Implementation of the residual calculation used for fitting.
coherence (bool) –
Determines if the summation over the thickness and divergence distributions is performed coherently (True) or incoherently (False). Default is False.

Added in version 1.0.3.
print_progrees (bool) –
Determines if the progress bar is printed. Default is False.

Added in version 1.2.0.

id

User identifier.

Type:: string

experiment

Experiment.

Type:: Experiment

sample

Sample of the Experiment for the calculation.

Changed in version 2.0.0: changed from old Sample class to GrazingSample.

Type:: GrazingSample

angles

List of the angles.

Type:: list

time_start

Start time for the integration (ns).

Type:: float

time_stop

Stop time for the integration (ns).

Type:: float

time_step

Step size for the time axis (ns).

Type:: float

max_detuning

Maximum value of the energy detuning in units of the resonant linewidth. Set this value to speed up the calculation. If zero no maximum is applied. The FFT window is always auto.

Type:: float

result

List of angle-dependent time-integrated intensity values in units of (\(\Gamma\)).

Type:: list

intensity_data

Intensity data for fitting.

Type:: list

data_size

Number of data points of experimental data.

Type:: int

scaling

Intensity scaling factor for fitting.

Type:: Var

background

Background for fitting.

Type:: Var

offset

Angular offset of the model. Defualt is 0.

Added in version 1.1.0.

Type:: float or Var

resolution

Resolution value for convolution. Default is 0.001 deg.

Type:: Var

resolution_kernel

weight of the Gaussian resolution same step size as detuning.

Type:: list

fit_weight

Relative weight for the cost function in multi measurement fitting.

Type:: float

bunch_spacing

Spacing of subsequent X-ray bunches in time (nanoseconds).

Type:: float

residual

Implementation of the residual calculation used for fitting.

Type:: Residual

coherence

Determines if the summation over the thickness and divergence distributions is performed coherently (True) or incoherently (False). Default is False.

Added in version 1.0.3.

Type:: bool

print_progrees

Determines if the progress bar is printed. Default is False.

Added in version 1.2.0.

Type:: bool

Calculate()

Calculates the class method. Also callable via operator ().

Returns:: Array of intensity values.
Return type:: ndarray

Cost()

Get the cost function of the measurement

\[cost = \frac{1}{n} \sum_i r(y_i, \hat{y}_i)\]

Added in version 2.0.0.

Returns:: cost function value.
Return type:: float

MeanSquaredError()

Get the mean squared error (MSE) of the measurement

\[cost = \frac{1}{n} \sum_i (y_i - \hat{y}_i)^2\]

Added in version 2.0.0.

Returns:: MSE value.
Return type:: float

Plot(data=True, residuals=True, datacolor='black', theorycolor='r', theorywidth=2, datalinestyle='none', datamarker='+', datamarkersize=2, datafillstyle='full', legend=True, errors=False, errorcap=2, name=None)

Plot the NuclearReflectivity.

Added in version 1.0.3.

Changed in version 1.2.0.

Parameters:

data (bool) – Select if intensity_data should be plot.
residuals (bool) – Select if residuals from fit should be plot.
datacolor (string) – See matplotlib documentation.
theorycolor (string) – See matplotlib documentation.
theorywidth (float) – See matplotlib documentation.
datalinestyle (string) – See matplotlib documentation.
datamarker (string) – See matplotlib documentation.
datamarkersize (float) – See matplotlib documentation.
datafillstyle (string) – See matplotlib documentation.
legend (bool) – Select if legend should be plot when model and data are plot.
errors (bool) – Select if error bars should be plot.
errorcap (float) – See matplotlib documentation (capsize).
name (string) –
If given, the plot is saved under this name.

Added in version 1.1.0.

Velocity()

Returns the velocity detuning of the measurement in units of mm/s.

Returns:: Velocity detuning (mm/s).
Return type:: ndarray

NuclearReflectivity

`NuclearReflectivity`