58 lines
2.1 KiB
Python
58 lines
2.1 KiB
Python
"""
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Plots l* for varying input parameters for both Mie and Rayleigh scattering.
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"""
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from scattering import *
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import numpy as np
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import matplotlib.pyplot as plt
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# Default Scattering Parameters
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n_p = 1.8 # particle refractive index
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n_s = 1.332 # medium refractive index (water)
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a_p = 250e-9 # particle radii [meters]
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lambda_vac = 685e-9 # wavelength of light in vacuum [meters]
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phi = 0.03 # particle volume fraction
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# Generate Parameter Ranges
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n_range = 100 # number of data points between values
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phi_range = np.linspace(0.01, 0.15, n_range)
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a_p_range = np.linspace(150e-9/2, 1000e-9/2, n_range)
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n_p_range = np.linspace(1.6, 2, n_range)
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# Initialize Result Array
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l_star = np.empty(shape=(n_range, 3, 2))
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# Collect Scattering Data
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for i in range(n_range):
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_, _, _, l_star[i, 0, 0], _ \
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= mie_scattering(n_p, n_s, a_p, lambda_vac, phi_range[i])
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_, _, _, l_star[i, 1, 0], _ \
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= mie_scattering(n_p, n_s, a_p_range[i], lambda_vac, phi)
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_, _, _, l_star[i, 2, 0], _ \
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= mie_scattering(n_p_range[i], n_s, a_p, lambda_vac, phi)
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_, _, _, l_star[i, 0, 1], _ \
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= rayleigh_scattering(n_p, n_s, a_p, lambda_vac, phi_range[i])
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_, _, _, l_star[i, 1, 1], _ \
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= rayleigh_scattering(n_p, n_s, a_p_range[i], lambda_vac, phi)
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_, _, _, l_star[i, 2, 1], _ \
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= rayleigh_scattering(n_p_range[i], n_s, a_p, lambda_vac, phi)
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# Plot Data
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fig, (ax1, ax2, ax3) = plt.subplots(1, 3)
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ax1.plot(phi_range, l_star[:, 0, 0]*1e6, 'k', label='Mie', linewidth=2)
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ax1.plot(phi_range, l_star[:, 0, 1]*1e6, 'k--', label='Rayleigh', linewidth=2)
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ax1.legend()
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ax1.set(xlabel=r'$\phi$', ylabel='l* [µm]')
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ax2.plot(a_p_range*1e9, l_star[:, 1, 0]*1e6, 'k', label='Mie', linewidth=2)
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ax2.plot(a_p_range*1e9, l_star[:, 1, 1]*1e6, 'k--', label='Rayleigh', linewidth=2)
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ax2.set(xlabel=r'$a_p$ [nm]')
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ax3.plot(n_p_range, l_star[:, 2, 0]*1e6, 'k', label='Mie', linewidth=2)
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ax3.plot(n_p_range, l_star[:, 2, 1]*1e6, 'k--', label='Rayleigh', linewidth=2)
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ax3.set(xlabel=r'$n_p$')
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# title with default parameters listed
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plt.suptitle(r'$n_p$ = %.3f, $n_s$ = %.3f, $a_p$ = %i nm, $\lambda$ = %i nm, $\phi$ = %.2f' % (n_p, n_s, a_p*1e9, lambda_vac*1e9, phi))
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plt.show()
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