TransmissionModel

The TransmissionModel class in the nres package is used to define and fit transmission models for nuclear resonance data. It combines cross-section calculations with response functions and background models to provide a comprehensive tool for analyzing transmission spectra.

Basic Usage

To use the TransmissionModel, you first need to import the necessary modules and create a cross-section object:

import numpy as np
from nres.cross_section import CrossSection
from nres.models import TransmissionModel

# Create a cross-section object (example)
xs = CrossSection("Ta181", T=300)

# Create a TransmissionModel
model = TransmissionModel(xs, response="expo_gauss", background="polynomial3")

Changing Parameters

You can modify the model parameters using the model.params attribute:

# Change the thickness parameter
model.params['thickness'].value = 0.1
model.params['thickness'].min = 0.01
model.params['thickness'].max = 1.0

# Adjust response function parameters
model.params['sigma'].value = 1e-5
model.params['tau'].value = 1e-6

# Modify background parameters
model.params['b0'].value = 0.01
model.params['b1'].value = 1e-6

Conducting a Fit

To fit the model to experimental data, you can use the fit method:

import pandas as pd

# Load your experimental data (example)
data = pd.read_csv("experimental_data.csv")

# Perform the fit
result = model.fit(data, emin=0.5e6, emax=20e6)

# Print fit report
print(result.fit_report())

Showing Results and Plotting

After fitting, you can visualize the results using the built-in plotting method:

# Plot the fit results
fig, axes = result.plot(plot_bg=True)

# Customize the plot (optional)
axes[0].set_ylim(0, 1)
axes[0].set_xscale('log')

# Display the plot
import matplotlib.pyplot as plt
plt.show()

The plot shows the experimental data points, the best-fit curve, and the residuals. If plot_bg=True, it also displays the background function.

Advanced Usage

Varying Weights and Time-of-Flight Parameters

You can allow certain parameters to vary during fitting:

model = TransmissionModel(xs,
                          vary_weights=True,
                          vary_tof=True,
                          vary_background=True,
                          vary_response=True)

# Fit with varying parameters
result = model.fit(data, emin=0.5e6, emax=20e6)

Updating Cross-Section

You can update the cross-section of an existing model:

new_xs = CrossSection("W182", T=300)
updated_model = model.set_cross_section(new_xs, inplace=False)

Varying All Parameters

To quickly vary or fix all parameters:

# Vary all parameters except 'thickness'
model.vary_all(vary=True, except_for=['thickness'])

# Fix all parameters
model.vary_all(vary=False)

This documentation provides an overview of the TransmissionModel class and its key functionalities. Users can refer to this guide to understand how to create models, adjust parameters, perform fits, and visualize results using your nres package.