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import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
from matplotlib.colors import LightSource, Normalize
from matplotlib.pyplot import gca
from pylab import rcParams
from matplotlib import rc
from matplotlib.ticker import FormatStrFormatter
from mpl_toolkits.axes_grid1 import make_axes_locatable
import pickle


    

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fp = open('cmap_overthrust.pkl', 'rb')
my_cmap_cm = pickle.load(fp)
fp.close()


    

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DH = 25.0;
NX = 800;
NY = 186;


    

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vpmin = 2360.0;
vpmax = 6000.0;


    

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FSize = 20
font = {'color':  'black',
        'weight': 'normal',
        'size': FSize}
mpl.rc('xtick', labelsize=FSize) 
mpl.rc('ytick', labelsize=FSize) 
rcParams['figure.figsize'] = 16, 8


    

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f = open("../start/overthrust_true.vp")
data_type = np.dtype ('float32').newbyteorder ('<')
mod_true = np.fromfile (f, dtype=data_type)
mod_true = mod_true.reshape(NX,NY)
mod_true = np.transpose(mod_true)
mod_true = np.flipud(mod_true)


    

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f = open("29_09_2016_lbfgs_app_Hessian/modelTest_vp_stage_8.bin")
#f = open("../start/overthrust_start_smooth2.vp")
data_type = np.dtype ('float32').newbyteorder ('<')
mod_fwi = np.fromfile (f, dtype=data_type)
mod_fwi = mod_fwi.reshape(NX,NY)
mod_fwi = np.transpose(mod_fwi)
mod_fwi = np.flipud(mod_fwi)


    

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x = np.arange(0.0, DH*NX, DH)
y = np.arange(0.0, DH*NY, DH)
x = np.divide(x,1000.0);
y = np.divide(y,1000.0);


    

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def do_plot(n, model, cm, an, title, vpmin, vpmax):
    
    ax=plt.subplot(2, 1, n)
    ax.set_xticks([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20])
    ax.set_yticks([1, 2, 3, 4, 5])
    
    #plt.rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
    rc('font',**{'family':'sans-serif','sans-serif':['Helvetica']})
    ## for Palatino and other serif fonts use:
    #rc('font',**{'family':'serif','serif':['Palatino']})
    #plt.rc('text', usetex=True)
    rc('text', usetex=True)
    
    # plt.pcolor(x, y, vp, cmap=cm, vmin=vpmin)
    im1 = plt.imshow(model, cmap=cm, interpolation='none', extent=[0.0,NX*DH/1000.0,0.0,NY*DH/1000.0], vmin=vpmin, vmax=vpmax)
    a = gca()
    a.set_xticklabels(a.get_xticks(), font)
    a.set_yticklabels(a.get_yticks(), font)
    plt.axis('scaled')
    plt.title(title, fontdict=font)
    plt.ylabel('Depth [km]', fontdict=font)
    if n==2:
        plt.xlabel('Distance [km]', fontdict=font)
    plt.gca().invert_yaxis()
    
    # add annotation
    plt.text(0.1, 0.4,an,fontdict=font,color='white')
    
    # fit and label colorbar
    divider = make_axes_locatable(ax)
    cax = divider.append_axes("right", size="2.5%", pad=0.05)
    cbar = plt.colorbar(im1, cax=cax)
    cbar.set_label(r"Vp [m/s]", fontdict=font, labelpad=1)


    

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plt.close('all')
plt.figure()
do_plot(1, mod_fwi, 'gray_r', '(a)', r"FWI result (f = 20.6 Hz)", vpmin, vpmax)
#do_plot(1, mod_fwi, 'gray_r', '(a)', r"Initial model", vpmin, vpmax)
do_plot(2, mod_true, 'gray_r', '(b)', r"True Overthrust model", vpmin, vpmax)
#plt.savefig('test.png', format='png', dpi=100)
plt.savefig('test.pdf', bbox_inches='tight', format='pdf')
plt.tight_layout()
plt.show()


    

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