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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
import pickle


    

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DH = 40.0;
NX = 250;
NY = 125;


    

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vpmin = 2500.0;
vpmax = 4500.0;


    

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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'] = 12.5, 11


    

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f = open("../start/inclusions_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("../model/modelTest_vp_stage_8.bin")
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])
    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)
    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()
    cbar=plt.colorbar(aspect=10,pad=0.03)
    cbar.set_label(r"Vp [m/s]" , fontdict=font, labelpad=10)
    plt.text(0.1, 0.5,an,fontdict=font,color='black')
    plt.tight_layout()


    

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plt.close('all')
plt.figure()
do_plot(1, mod_fwi, 'magma', '(a)', r"FWI result", vpmin, vpmax)
do_plot(2, mod_true, 'magma', '(b)', r"True 2 inclusion model", vpmin, vpmax)
#plt.savefig('test.png', format='png', dpi=100)
#plt.savefig('test.pdf', format='pdf')
plt.show()


    

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