In [33]:

    

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


    

In [2]:

    

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


    

In [3]:

    

DH = 20.0;
NX = 500;
NY = 174;
vpmin=800.0


    

In [65]:

    

FSize = 20
font = {'color':  'black',
        'weight': 'normal',
        'size': FSize}
mpl.rc('xtick', labelsize=FSize) 
mpl.rc('ytick', labelsize=FSize) 
rcParams['figure.figsize'] = 12, 11


    

In [110]:

    

stage = 4;


    

In [121]:

    

#basename = "elastic_FWT/OBC_FWT/LBFGS/10_06_2016_vx_vy_1D_GRAD_FORM_1_2Hz/"
basename = "elastic_FWT/OBC_FWT/LBFGS/21_05_2015_vx_vy_1D/"


    

In [122]:

    

name_vp = basename + "modelTest_vp_stage_" + "%0.*f" %(0,np.fix(stage)) + ".bin"
f = open (name_vp)
data_type = np.dtype ('float32').newbyteorder ('<')
vp = np.fromfile (f, dtype=data_type)
vp = vp.reshape(NX,NY)
vp = np.transpose(vp)
vp = np.flipud(vp)


    

In [123]:

    

name_vs = basename + "modelTest_vs_stage_" + "%0.*f" %(0,np.fix(stage)) + ".bin"
f = open (name_vs)
data_type = np.dtype ('float32').newbyteorder ('<')
vs = np.fromfile (f, dtype=data_type)
vs = vs.reshape(NX,NY)
vs = np.transpose(vs)
vs = np.flipud(vs)


    

In [124]:

    

name_rho = basename + "modelTest_rho_stage_" + "%0.*f" %(0,np.fix(stage)) + ".bin"
f = open (name_rho)
data_type = np.dtype ('float32').newbyteorder ('<')
rho = np.fromfile (f, dtype=data_type)
rho = rho.reshape(NX,NY)
rho = np.transpose(rho)
rho = np.flipud(rho)


    

In [14]:

    

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);


    

In [166]:

    

def do_plot(n, model, cm, an, title, vpmin, vpmax):
    
    ax=plt.subplot(3, 1, n)
    ax.set_xticks([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
    ax.set_yticks([0.5, 1, 1.5, 2, 2.5, 3, 3.5])
    
    #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.ylabel('Depth [km]', fontdict=font)
    if n==3:
        plt.xlabel('Distance [km]', fontdict=font)
    plt.gca().invert_yaxis()
    cbar=plt.colorbar(aspect=8, pad=0.02)
    cbar.set_label(title, fontdict=font, labelpad=10)
    plt.text(0.1, 0.32,an,fontdict=font,color='white')
    plt.tight_layout()


    

In [167]:

    

plt.close('all')
plt.figure()
do_plot(1, vp, my_cmap_cm, '(a)', r"$\rm{V_p [m/s]}$", 950, 4600)
do_plot(2, vs, my_cmap_cm, '(b)', r"$\rm{V_s [m/s]}$", 550, 2700)
do_plot(3, rho, my_cmap_cm, '(c)', r"$\rm{\rho [kg/m^3]}$", 1200, 2800)
#plt.savefig('test.png', format='png', dpi=100)
plt.savefig('test.pdf', format='pdf')
plt.show()


    

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