Sample Model¶

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In [1]:

import matplotlib.pyplot as plt
import numpy as np

from easydynamics.sample_model import BrownianTranslationalDiffusion
from easydynamics.sample_model import ComponentCollection
from easydynamics.sample_model import DampedHarmonicOscillator
from easydynamics.sample_model import Gaussian
from easydynamics.sample_model import Polynomial
from easydynamics.sample_model.background_model import BackgroundModel
from easydynamics.sample_model.resolution_model import ResolutionModel
from easydynamics.sample_model.sample_model import SampleModel

%matplotlib widget

import matplotlib.pyplot as plt import numpy as np from easydynamics.sample_model import BrownianTranslationalDiffusion from easydynamics.sample_model import ComponentCollection from easydynamics.sample_model import DampedHarmonicOscillator from easydynamics.sample_model import Gaussian from easydynamics.sample_model import Polynomial from easydynamics.sample_model.background_model import BackgroundModel from easydynamics.sample_model.resolution_model import ResolutionModel from easydynamics.sample_model.sample_model import SampleModel %matplotlib widget

In [2]:

# Create a diffusion_model and components for the SampleModel
Q = np.linspace(0.5, 2, 7)
energy = np.linspace(-2, 2, 501)

scale = 1.0
diffusion_coefficient = 2.4e-9  # m^2/s
diffusion_unit = 'm**2/s'
diffusion_model = BrownianTranslationalDiffusion(
    display_name='DiffusionModel',
    scale=scale,
    diffusion_coefficient=diffusion_coefficient,
    diffusion_unit=diffusion_unit,
)


# Creating components
component_collection = ComponentCollection()
gaussian = Gaussian(display_name='Gaussian', width=0.2, area=1, center=1.5)
dho = DampedHarmonicOscillator(display_name='DHO', center=1.0, width=0.3, area=2.0)

# Adding components to the component collection
component_collection.append_component(gaussian)
component_collection.append_component(dho)

sample_model = SampleModel(
    diffusion_models=diffusion_model,
    components=component_collection,
    Q=Q,
    unit='meV',
    display_name='MySampleModel',
    temperature=10,
)

# Calculate the model intensity at the specified Q and energy values
# y_list will be a list of intensity arrays, one for each Q value
sample_intensity = sample_model.evaluate(energy)

plt.figure()
for i, Q_value in enumerate(Q):
    plt.plot(energy, sample_intensity[i], label=f'Q={Q_value:.2f} Å⁻¹')
plt.xlabel('Energy (meV)')
plt.ylabel('Intensity (a.u.)')
plt.title('Sample Model Evaluation at 10 K')
plt.legend()
plt.show()

# Create a diffusion_model and components for the SampleModel Q = np.linspace(0.5, 2, 7) energy = np.linspace(-2, 2, 501) scale = 1.0 diffusion_coefficient = 2.4e-9 # m^2/s diffusion_unit = 'm**2/s' diffusion_model = BrownianTranslationalDiffusion( display_name='DiffusionModel', scale=scale, diffusion_coefficient=diffusion_coefficient, diffusion_unit=diffusion_unit, ) # Creating components component_collection = ComponentCollection() gaussian = Gaussian(display_name='Gaussian', width=0.2, area=1, center=1.5) dho = DampedHarmonicOscillator(display_name='DHO', center=1.0, width=0.3, area=2.0) # Adding components to the component collection component_collection.append_component(gaussian) component_collection.append_component(dho) sample_model = SampleModel( diffusion_models=diffusion_model, components=component_collection, Q=Q, unit='meV', display_name='MySampleModel', temperature=10, ) # Calculate the model intensity at the specified Q and energy values # y_list will be a list of intensity arrays, one for each Q value sample_intensity = sample_model.evaluate(energy) plt.figure() for i, Q_value in enumerate(Q): plt.plot(energy, sample_intensity[i], label=f'Q={Q_value:.2f} Å⁻¹') plt.xlabel('Energy (meV)') plt.ylabel('Intensity (a.u.)') plt.title('Sample Model Evaluation at 10 K') plt.legend() plt.show()

In [3]:

# Create a BackgroundModel and show other ways to set Q and components

background_model = BackgroundModel()
background_model.Q = Q

background_model.components = Polynomial(coefficients=[1, 0.1, 0.01])
background = background_model.evaluate(energy)

# Also create a ResolutionModel.
# It doesn't do anything here, but shows how to set it up.
resolution_model = ResolutionModel()
resolution_model.Q = Q
resolution_model.append_component(Gaussian(width=0.05))
resolution = resolution_model.evaluate(energy)

# Create a BackgroundModel and show other ways to set Q and components background_model = BackgroundModel() background_model.Q = Q background_model.components = Polynomial(coefficients=[1, 0.1, 0.01]) background = background_model.evaluate(energy) # Also create a ResolutionModel. # It doesn't do anything here, but shows how to set it up. resolution_model = ResolutionModel() resolution_model.Q = Q resolution_model.append_component(Gaussian(width=0.05)) resolution = resolution_model.evaluate(energy)

/home/runner/work/dynamics-lib/dynamics-lib/src/easydynamics/sample_model/model_base.py:206: UserWarning: Q is not set. No component collections generated
  warnings.warn('Q is not set. No component collections generated', UserWarning)

In [4]:

# Plot the three models together
for i, Q_value in enumerate(Q):
    plt.figure()
    plt.plot(energy, sample_intensity[i], label='Sample model')
    plt.plot(energy, background[i], label='Background model')
    plt.plot(energy, resolution[i], label='Resolution model')
    plt.legend()
    plt.xlabel('Energy (meV)')
    plt.ylabel('Intensity (a.u.)')
    plt.title(f'Sample Model Evaluation at 10 K and Q ={Q_value:.2f} Å⁻¹')
    plt.legend()
    plt.show()

# Plot the three models together for i, Q_value in enumerate(Q): plt.figure() plt.plot(energy, sample_intensity[i], label='Sample model') plt.plot(energy, background[i], label='Background model') plt.plot(energy, resolution[i], label='Resolution model') plt.legend() plt.xlabel('Energy (meV)') plt.ylabel('Intensity (a.u.)') plt.title(f'Sample Model Evaluation at 10 K and Q ={Q_value:.2f} Å⁻¹') plt.legend() plt.show()