`Transmission`

class nexus.Transmission(experiment, sample, energy, angles, intensity_data=[], scaling='auto', background=0.0, offset=0.0, resolution=0.001, fit_weight=1.0, residual=<nexus.clib.cnexus.Log10; proxy of <Swig Object of type 'Residual *'> >, id='')

Bases: FitMeasurement

Constructor for the Transmission class. Calculates the intensity of the experiment for one sample whose incidence angle is changed in grazing-incidence transmission geometry.

Parameters:

id (string) – User identifier.
experiment (Experiment) – Experiment.
sample (GrazingSample) –
Sample of the Experiment whose angle is changed.

Changed in version 2.0.0: changed from old Sample class to GrazingSample.
energy (float) – X-ray energy in eV.
angles (list) – List of the angles.
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. Default 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.
residual (Residual) – Implementation of the residual calculation used for fitting.

id

User identifier.

Type:: string

experiment

Experiment.

Type:: Experiment

sample

Sample of the Experiment whose angle is changed.

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

Type:: GrazingSample

energy

X-ray energy in eV.

Type:: float

angles

List of the angles.

Type:: list

result

List of intensity values.

Type:: list

intensity_data

Intensity data for fitting.

Type:: list or ndarray

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.

Added in version 1.1.0.

Type:: float or Var

resolution

Resolution value for convolution.

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

residual

Implementation of the residual calculation used for fitting.

Type:: Residual

Calculate()

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

Returns:: Array of float 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 Transmission.

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

Transmission

`Transmission`