Esempio n. 1
0
import numpy as np
import matplotlib.pyplot as plt
import atomic

from ensemble_average import time_dependent_power


if __name__ == '__main__':
    times = np.logspace(-7, 0, 50)
    temperature = np.logspace(0, 3, 50)
    density = 1e19

    from atomic.pec import TransitionPool
    ad = atomic.element('argon')
    tp = TransitionPool.from_adf15('adas_data/pec/transport_llu#ar*.dat')
    ad = tp.filter_energy(2e3, 20e3, 'eV').create_atomic_data(ad)

    rt = atomic.RateEquations(ad)
    y = rt.solve(times, temperature, density)

    taus = np.array([ 1e14, 1e15, 1e16, 1e17, 1e18])/density

    plt.figure(2); plt.clf()
    time_dependent_power(y, taus)
    plt.ylim(ymin=1e-35)
    plt.draw()

    plt.figure(3); plt.clf()
    time_dependent_power(y, taus, ensemble_average=True)
    plt.ylim(ymin=1e-35)
    plt.draw()
Esempio n. 2
0
    for i, key in enumerate(['line_power', 'continuum_power', 'cx_power']):
        if label:
            label_str = key
        else:
            label_str = None
        c= ad.coeffs[key](charge, te, ne)
        ax.loglog(te, c, colors[i], label=label_str, **kwargs)

    ax.set_ylabel('$P/n_\mathrm{e} n_\mathrm{I}\ [\mathrm{W m^3}]$')


if __name__ == '__main__':
    ad = atomic.element('carbon')

    tp = TransitionPool.from_adf15('adas_data/pec/pec96#c_pju*.dat')
    #tp = tp.filter_energy(2e3, 20e3, 'eV')
    ad_filtered = tp.create_atomic_data(ad)

    te = np.logspace(0, 3)

    f = plt.figure(1); f.clf()

    for i, charge in enumerate([1, 2, 5]):
        ax = f.add_subplot(3, 1, i+1)
        plot_coeffs(ad, te, charge)
        plot_coeffs(ad_filtered, te, charge, marker='x', ls='', label=None)
        ax.set_ylim(1e-35, 1e-30)
        label = '$\mathrm{%s}^{%d+}$' % (ad.element, charge)
        ax.text(0.02, 0.95, label, transform=ax.transAxes, va='top')
Esempio n. 3
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def parabolic_profile(y0):
    x = np.linspace(1., 0, 50)
    y = 1 - x**2
    y *= y0
    return x, y

r, temperature = parabolic_profile(3e3)
r, density = parabolic_profile(1e19)

try:
    ad
except NameError:
    from atomic.pec import TransitionPool
    ad = atomic.element('argon')
    tp = TransitionPool.from_adf15('adas_data/pec/transport_llu#ar*.dat')
    ad = tp.filter_energy(2e3, 20e3, 'eV').create_atomic_data(ad)

eq = atomic.CoronalEquilibrium(ad)
y = eq.ionisation_stage_distribution(temperature, density)

ne_tau = np.array([1e-1, 1e-2, 1e-3])
impurity_fraction = 0.05


texts = ['$10^{%d}$' % i for i in np.log10(ne_tau)]

try:
    tau_ss
except NameError:
    t_normalized = np.logspace(-4, 0, 500)
Esempio n. 4
0
    for i, key in enumerate(['line_power', 'continuum_power', 'cx_power']):
        if label:
            label_str = key
        else:
            label_str = None
        c = ad.coeffs[key](charge, te, ne)
        ax.loglog(te, c, colors[i], label=label_str, **kwargs)

    ax.set_ylabel('$P/n_\mathrm{e} n_\mathrm{I}\ [\mathrm{W m^3}]$')


if __name__ == '__main__':
    ad = atomic.element('carbon')

    tp = TransitionPool.from_adf15('../adas_data/pec96#c_pju*.dat')
    #tp = tp.filter_energy(2e1, 20e3, 'eV')
    ad_filtered = tp.create_atomic_data(ad)

    te = np.logspace(0, 3)

    f = plt.figure(1)
    f.clf()

    for i, charge in enumerate([1, 2, 5]):
        ax = f.add_subplot(3, 1, i + 1)
        plot_coeffs(ad, te, charge)
        plot_coeffs(ad_filtered, te, charge, marker='x', ls='', label=None)
        ax.set_ylim(1e-35, 1e-30)
        label = '$\mathrm{%s}^{%d+}$' % (ad.element, charge)
        ax.text(0.02, 0.95, label, transform=ax.transAxes, va='top')