import parametro import auxfunctionsmodule as aux import fortransubroutines as fortran start_time = time.time() StackImage = np.zeros( (parametro.Nz, parametro.Nx)) # variable responsible for storing the migrated images # Loads the source position Fx, Fz = np.loadtxt('posicoes_fonte.dat', dtype='int', unpack=True) N_shot = np.size(Fx) # Generate binary with final image fortran.savefinalimage(parametro.Nz,\ parametro.Nx,\ parametro.N_shot,\ parametro.caminho_migracao,\ parametro.nome_prin) # plot Stack image generated in fortran filename_imagem = "../Imagem/" '%s' % (parametro.nome_prin) + "_FinalImage.bin" StackImage = aux.readbinaryfile(parametro.Nz, parametro.Nx, filename_imagem) aux.plotmodel(StackImage, 'gray') pl.show() elapsed_time_python = time.time() - start_time print("Tempo de processamento python = ", elapsed_time_python, "s")
import time import matplotlib.pyplot as pl import numpy as np import multiprocessing as mp # Modules created import parametro import auxfunctionsmodule as aux import fortransubroutines as fortran start_time = time.time() # plot Stack image generated in fortran filename_imagem = parametro.caminho_migracao + parametro.nome_prin + "_FinalImage.bin" StackImage = aux.readbinaryfile(parametro.Nz, parametro.Nx, filename_imagem) aux.plotmodel(StackImage, 'gray') #pl.show() fortran.laplacian(parametro.Nz,\ parametro.Nx,\ parametro.h,\ parametro.caminho_migracao,\ parametro.nome_prin+"_FinalImage") # plot Stack image generated in fortran filename_imagem = parametro.caminho_migracao + parametro.nome_prin + "_FinalImage_Laplacian.bin" Laplacian = aux.readbinaryfile(parametro.Nz, parametro.Nx, filename_imagem) aux.plotmodel(Laplacian, 'gray') pl.show()
import multiprocessing as mp # Modules created import parametro import auxfunctionsmodule as aux import fortransubroutines as fortran # This variable will tell fortran that # we want to do the modelling of the seismograms regTTM = 0 start_time = time.time() # Velocity Model used C = aux.readbinaryfile(parametro.Nz,parametro.Nx,parametro.modeloreal) aux.plotmodel(C,'jet') # Creates the seismic source fortran.wavelet(1,parametro.dt,1,parametro.f_corte) # Shows the seismic pulse aux.plotgraphics(2,'wavelet_ricker.dat', 'k') #pl.show() # Define the source's samples lixo, fonte = np.loadtxt('wavelet_ricker.dat', unpack = True) # Creates the damping layer function func_amort = aux.amort(parametro.fat,parametro.nat) aux.plotgraphics(1,'f_amort.dat','k') #pl.show()
# Modules from Python import time import matplotlib.pyplot as pl import numpy as np import multiprocessing as mp # Modules created import parametro import auxfunctionsmodule as aux import fortransubroutines as fortran filename_imagem = "../imagens_artigo/MarmousiRTMTT_Seismogram020.bin" Image = aux.readbinaryfile(parametro.Nt,parametro.Nx,filename_imagem) #Image[0:36,:] = 0.0 #Image = Image/np.max(np.abs(Image)) aux.plotmodel(Image,'gray') pl.show()