from results import loadG, loadGBenchmark, getSfun, getGfun, GlargeNfApp

import pylab as pl

import numpy as np

import matplotlib.pyplot as plt

from fig import fig, saveFig, fill_between, grid_selfmade

N=35000

wm=.021234;

colors=['red', 'green', 'blue', 'violet','yellow']

f=fig(0,size=10)

Nf=1.

kx=1

xs=np.linspace(kx-wm, kx+wm, N)

pl.plot(xs, -2*np.imag(GlargeNfApp(Nf,-1j*xs+0.000001,kx)),label='',color='black')

pl.plot(np.linspace(kx-.0005,kx+.0005,1000),500*[-120000,120000],color='black')

#pl.plot(xs, -np.imag(GlargeNfApp(Nf,-1j*xs+0.00001,kx)),label='',color='blue')

#pl.yscale('log')

pl.xlim([xs[0],xs[-1]])

#pl.legend(loc=4)

pl.ylim([-100000,100000])

grid_selfmade(f.get_axes()[0])

pl.xlabel(r'$\omega/\lambda^2$')

pl.ylabel(r'$A(\omega, k_x=\lambda^2)/\lambda^2$')

saveFig('inconsistency')

plt.show()