from fatiando.seismic import profile
from fatiando.inversion import linear
from fatiando import vis, utils, ui
import cPickle as pickle
params = __import__('exercicio2_entrada')
with open(params.dados) as f:
zp, tts, thickness, velocity = pickle.load(f)
mu = params.norma_minima
area = (0, 10000, 0, 600)
vmin, vmax, zmin, zmax = area
thick = float(sum(thickness))/float(params.camadas)
model = params.camadas*[thick]
solver = linear.overdet(len(model))
p, residuals = profile.invert_vertical(tts, zp, model, solver, damping=mu)
pyplot.figure(figsize=(12,5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")
from fatiando.seismic import profile
from fatiando.inversion import linear
from fatiando import vis, utils, ui
import cPickle as pickle
params = __import__('exercicio3_entrada')
with open(params.dados) as f:
zp, tts, thickness, velocity = pickle.load(f)
mu = params.suavidade
area = (0, 10000, 0, 600)
vmin, vmax, zmin, zmax = area
thick = float(sum(thickness)) / float(params.camadas)
model = params.camadas * [thick]
solver = linear.overdet(len(model))
p, residuals = profile.invert_vertical(tts, zp, model, solver, smooth=mu)
pyplot.figure(figsize=(12, 5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")
from fatiando.seismic import profile
from fatiando.inversion import linear
from fatiando import vis, utils, ui
import cPickle as pickle
params = __import__('exercicio3_entrada')
with open(params.dados) as f:
zp, tts, thickness, velocity = pickle.load(f)
mu = params.suavidade
area = (0, 10000, 0, 600)
vmin, vmax, zmin, zmax = area
thick = float(sum(thickness))/float(params.camadas)
model = params.camadas*[thick]
solver = linear.overdet(len(model))
p, residuals = profile.invert_vertical(tts, zp, model, solver, smooth=mu)
pyplot.figure(figsize=(12,5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")
import cPickle as pickle
params = __import__('exercicio4_entrada')
with open(params.dados) as f:
zp, tts, thickness, velocity = pickle.load(f)
mu = params.variacao_total
beta = params.beta
area = (0, 10000, 0, 600)
vmin, vmax, zmin, zmax = area
thick = float(sum(thickness)) / float(params.camadas)
model = params.camadas * [thick]
solver = gradient.levmarq(initial=0.000001 * numpy.ones(len(model)))
p, residuals = profile.invert_vertical(tts,
zp,
model,
solver,
sharp=mu,
beta=beta)
pyplot.figure(figsize=(12, 5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
from fatiando.inversion import gradient
from fatiando import vis, utils, ui
import cPickle as pickle
params = __import__('exercicio4_entrada')
with open(params.dados) as f:
zp, tts, thickness, velocity = pickle.load(f)
mu = params.variacao_total
beta = params.beta
area = (0, 10000, 0, 600)
vmin, vmax, zmin, zmax = area
thick = float(sum(thickness))/float(params.camadas)
model = params.camadas*[thick]
solver = gradient.levmarq(initial=0.000001*numpy.ones(len(model)))
p, residuals = profile.invert_vertical(tts, zp, model, solver, sharp=mu, beta=beta)
pyplot.figure(figsize=(12,5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")
thickness, velocity = ui.picker.draw_layers(area, figure.gca())
zp = numpy.arange(zmin + 1, zmax, 1)
tts, error = utils.contaminate(profile.vertical(thickness, velocity, zp),
params.ruido, percent=True, return_stddev=True)
pyplot.figure(figsize=(6, 5))
pyplot.title("Dados observados")
pyplot.plot(tts, zp, '.k')
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.show()
solver = linear.overdet(len(thickness))
p, residuals = profile.invert_vertical(tts, zp, thickness, solver)
pyplot.figure(figsize=(12,5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")
zp = numpy.arange(zmin + 1, zmax, 1)
tts, error = utils.contaminate(profile.vertical(thickness, velocity, zp),
params.ruido,
percent=True,
return_stddev=True)
pyplot.figure(figsize=(6, 5))
pyplot.title("Dados observados")
pyplot.plot(tts, zp, '.k')
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.show()
solver = linear.overdet(len(thickness))
p, residuals = profile.invert_vertical(tts, zp, thickness, solver)
pyplot.figure(figsize=(12, 5))
pyplot.subplot(1, 2, 1)
pyplot.grid()
pyplot.title("Perfilagem sismica vertical")
pyplot.plot(tts, zp, 'ok', label='Observado')
pyplot.plot(tts - residuals, zp, '-r', label='Predito')
leg = pyplot.legend(loc='lower left', numpoints=1)
leg.get_frame().set_alpha(0.5)
pyplot.xlabel("Tempo de chegada (s)")
pyplot.ylabel("Profundidade (m)")
pyplot.ylim(sum(thickness), 0)
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title("Perfil de velocidades")