Components¶
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import matplotlib.pyplot as plt
import numpy as np
from easydynamics.sample_model import DampedHarmonicOscillator
from easydynamics.sample_model import DeltaFunction
from easydynamics.sample_model import Gaussian
from easydynamics.sample_model import Lorentzian
from easydynamics.sample_model import Polynomial
%matplotlib widget
import matplotlib.pyplot as plt
import numpy as np
from easydynamics.sample_model import DampedHarmonicOscillator
from easydynamics.sample_model import DeltaFunction
from easydynamics.sample_model import Gaussian
from easydynamics.sample_model import Lorentzian
from easydynamics.sample_model import Polynomial
%matplotlib widget
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# Creating a component
gaussian = Gaussian(display_name='Gaussian', width=0.5, area=1)
dho = DampedHarmonicOscillator(display_name='DHO', center=1.0, width=0.3, area=2.0)
lorentzian = Lorentzian(display_name='Lorentzian', center=-1.0, width=0.2, area=1.0)
polynomial = Polynomial(display_name='Polynomial', coefficients=[0.1, 0, 0.5]) # y=0.1+0.5*x^2
x = np.linspace(-2, 2, 100)
plt.figure()
y = gaussian.evaluate(x)
plt.plot(x, y, label='Gaussian')
y = dho.evaluate(x)
plt.plot(x, y, label='DHO')
y = lorentzian.evaluate(x)
plt.plot(x, y, label='Lorentzian')
y = polynomial.evaluate(x)
plt.plot(x, y, label='Polynomial')
plt.legend()
plt.show()
# Creating a component
gaussian = Gaussian(display_name='Gaussian', width=0.5, area=1)
dho = DampedHarmonicOscillator(display_name='DHO', center=1.0, width=0.3, area=2.0)
lorentzian = Lorentzian(display_name='Lorentzian', center=-1.0, width=0.2, area=1.0)
polynomial = Polynomial(display_name='Polynomial', coefficients=[0.1, 0, 0.5]) # y=0.1+0.5*x^2
x = np.linspace(-2, 2, 100)
plt.figure()
y = gaussian.evaluate(x)
plt.plot(x, y, label='Gaussian')
y = dho.evaluate(x)
plt.plot(x, y, label='DHO')
y = lorentzian.evaluate(x)
plt.plot(x, y, label='Lorentzian')
y = polynomial.evaluate(x)
plt.plot(x, y, label='Polynomial')
plt.legend()
plt.show()
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# The area under the DHO curve is indeed equal to the area parameter.
xx = np.linspace(-15, 15, 10000)
yy = dho.evaluate(xx)
area = np.trapezoid(yy, xx)
print(f'Area under DHO curve: {area:.4f}')
# The area under the DHO curve is indeed equal to the area parameter.
xx = np.linspace(-15, 15, 10000)
yy = dho.evaluate(xx)
area = np.trapezoid(yy, xx)
print(f'Area under DHO curve: {area:.4f}')
Area under DHO curve: 1.9999
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delta = DeltaFunction(display_name='Delta', center=0.0, area=1.0)
x1 = np.linspace(-2, 2, 100)
y = delta.evaluate(x1)
x2 = np.linspace(-2, 2, 51)
y2 = delta.evaluate(x2)
plt.figure()
plt.plot(x1, y, label='Delta Function')
plt.plot(x2, y2, label='Delta Function (coarser)')
plt.legend()
plt.show()
# The area under the Delta function is indeed equal to
# the area parameter.
xx = np.linspace(-2, 2, 10000)
yy = delta.evaluate(xx)
area = np.trapezoid(y, x1)
print(area)
delta = DeltaFunction(display_name='Delta', center=0.0, area=1.0)
x1 = np.linspace(-2, 2, 100)
y = delta.evaluate(x1)
x2 = np.linspace(-2, 2, 51)
y2 = delta.evaluate(x2)
plt.figure()
plt.plot(x1, y, label='Delta Function')
plt.plot(x2, y2, label='Delta Function (coarser)')
plt.legend()
plt.show()
# The area under the Delta function is indeed equal to
# the area parameter.
xx = np.linspace(-2, 2, 10000)
yy = delta.evaluate(xx)
area = np.trapezoid(y, x1)
print(area)
0.9999999999999999
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import scipp as sc
x1 = sc.linspace(dim='x', start=-2.0, stop=2.0, num=100, unit='meV')
x2 = sc.linspace(dim='x', start=-2.0 * 1e3, stop=2.0 * 1e3, num=101, unit='microeV')
polynomial = Polynomial(display_name='Polynomial', coefficients=[0.1, 0, 0.5]) # y=0.1+0.5*x^2
y1 = polynomial.evaluate(x1)
y2 = polynomial.evaluate(x2)
plt.figure()
plt.plot(x1.values, y1, label='Polynomial meV', color='blue')
plt.plot(x2.values / 1000, y2, label='Polynomial microeV', linestyle='dashed', color='orange')
plt.legend()
plt.show()
import scipp as sc
x1 = sc.linspace(dim='x', start=-2.0, stop=2.0, num=100, unit='meV')
x2 = sc.linspace(dim='x', start=-2.0 * 1e3, stop=2.0 * 1e3, num=101, unit='microeV')
polynomial = Polynomial(display_name='Polynomial', coefficients=[0.1, 0, 0.5]) # y=0.1+0.5*x^2
y1 = polynomial.evaluate(x1)
y2 = polynomial.evaluate(x2)
plt.figure()
plt.plot(x1.values, y1, label='Polynomial meV', color='blue')
plt.plot(x2.values / 1000, y2, label='Polynomial microeV', linestyle='dashed', color='orange')
plt.legend()
plt.show()
/home/runner/work/dynamics-lib/dynamics-lib/src/easydynamics/sample_model/components/model_component.py:99: UserWarning: Input x has unit µeV, but Polynomial component has unit meV. Converting Polynomial to µeV. warnings.warn(