Some extra scripts for movie generation

from __future__ import division, absolute_import, print_function
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import numpy as np
from dmft.twosite import dmft_loop, TwoSite_Matsubara
from slaveparticles.quantum import dos

def movie_feature(res, name):
    """Outputs an animate movie of the evolution of an specific feature"""
    figi, ax = plt.subplots()
    line, = ax.plot([], [], '*-')
    ax.set_ylim(-1e-8, 0)
    beta = res[0, 2].beta
    sim = TwoSite_Matsubara(beta, res[0, 2].t, 30*beta)

    iwn = np.arange(1, 30*beta, 2) / beta
    ax.set_xlim(0, iwn.max())
    ax.set_xlabel('$i\\omega_n$')
    ax.set_ylabel(r'$Im \Sigma$')
    ax.set_title('Evolution of the Self Energy at $\\beta=${}'.format(beta))


    def run(i):
        # update the data
        u_int = res[i, 0]
        sim.mu = u_int / 2.
        sim.solve(u_int/2., u_int, res[i, 2].hyb_V())
        s = sim.GF[r'$\Sigma$'].imag
        ymin, ymax = ax.get_ylim()

        if s.min() <= ymin and s.min() >= -12:
            ax.set_ylim(np.max([2*s.min(), -12]), 0)
            ax.figure.canvas.draw()
        line.set_data(iwn, s)
        plt.legend([line], ['U={:.2f}'.format(u_int)])
        return line,

    ani = anim.FuncAnimation(figi, run, blit=True, interval=150,
                             frames=res.shape[0])
    ani.save(name+'.mp4')
    plt.close(figi)


def movie_feature_real(res, name):
    """Outputs an animate movie of the evolution of an specific feature"""
    f, (ax1, ax2, ax3) = plt.subplots(3, sharex=True)

    line, = ax1.plot([], [], '--')
    ax1.set_xlim([-6, 6])
    ax1.set_ylim([0, 0.66])

    line2, = ax2.plot([], [], '-')
    ax2.set_ylim([-6, 6])

    line3, = ax3.plot([], [], '-')
    ax3.set_ylim([-6, 6])

    beta = res[0, 2].beta
    ax1.set_xlabel('$\\omega / t$')
    ax1.set_ylabel(r'$A(\omega)$')
    ax2.set_ylabel(r'$\Sigma(\omega)$')
    ax3.set_ylabel(r'$G_{imp}(\omega)$')
    f.subplots_adjust(hspace=0)

    def init():
        line.set_data([], [])
        line2.set_data([], [])
        line3.set_data([], [])
        return line, line2, line3,

    def run(i):
        u_int = res[i, 0]
        w = res[i, 2].omega
        s = res[i, 2].GF[r'$\Sigma$']
        g = res[i, 2].GF['Imp G']
        ra = w+u_int/2.-s
        rho = dos.bethe_lattice(ra, res[i, 2].t)

        line.set_data(w, rho)
        line2.set_data(w, s)
        line3.set_data(w, g)
        ax1.set_title('Transition to Mott Insulator at '
                      '$\\beta=${} and U/D={}'.format(beta, u_int))

        return line, line2, line3

    ani = anim.FuncAnimation(f, run, blit=True, interval=150, init_func=init,
                             frames=res.shape[0])
    ani.save(name+'.mp4')
    plt.close(f)


def run_halffill(axis='matsubara', du=0.05):
    fig = plt.figure()
    u_int = np.arange(0, 6.2, du)
    for beta in [6, 10, 20, 30, 50, 100, 1e3]:
        out_file = axis+'_halffill_b{}_dU{}'.format(beta, du)
        try:
            res = np.load(out_file+'.npy')
        except IOError:
            res = dmft_loop(u_int, axis, beta=beta, hop=1)
            np.save(out_file, res)

        plt.plot(res[:, 0]/2, res[:, 1], '+-', label='$\\beta = {}$'.format(beta))

    plt.legend(loc=0)
    plt.title('Quasiparticle weigth, estimated in {} frequencies'.format(axis))
    plt.ylabel('Z')
    plt.xlabel('U/D')
    fig.savefig(out_file+'_Z.png', format='png',
                transparent=False, bbox_inches='tight', pad_inches=0.05)
    plt.close(fig)

if __name__ == "__main__":
    run_halffill('real')
    run_halffill('matsubara')

Total running time of the script: ( 0 minutes 0.000 seconds)