pyplot.suptitle("Escolha o epicentro")
ax = pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
vis.map.points(recs, '^r', label="Stations")
ax2 = pyplot.subplot(1, 2, 2)
pyplot.title('Tempos de chegada')
s = numpy.arange(len(ttr)) + 1
width = 0.2
pyplot.bar(s - width, ttr, width, color='r')
ax2.set_xticks(s)
pyplot.xlabel("Estacao")
pyplot.ylabel("Tempo de chegada")
src_model = ui.picker.points(area, ax, marker='*', color='y')
srcs, recs = utils.connect_points(src_model, recs)
ptime = traveltime.straight_ray_2d(model, 'vp', srcs, recs)
stime = traveltime.straight_ray_2d(model, 'vs', srcs, recs)
ttr_model = stime - ptime
with open('exercicio2-modelo.pickle', 'w') as f:
data = {'ttr': ttr_model, 'recs': recs, 'src': src_model}
pickle.dump(data, f)
pyplot.figure(figsize=(14, 6))
pyplot.subplot(1, 2, 1)
pyplot.title('Epicentros')
pyplot.axis('scaled')
vis.map.points(recs, '^r', label="Estacao")
vis.map.points(src_model, '*y', label="Epicentro")
vis.map.set_area(area)
pyplot.legend(loc='upper left', shadow=True, numpoints=1, prop={'size': 10})
ax = pyplot.subplot(1, 1, 1)
pyplot.axis('scaled')
pyplot.suptitle("Escolha o evento")
vis.map.points(rec_points, '^r')
src = ui.picker.points(area, ax, marker='*', color='y')
pyplot.figure()
ax = pyplot.subplot(1, 1, 1)
pyplot.axis('scaled')
pyplot.suptitle("Escolha a estimativa inicial")
vis.map.points(rec_points, '^r')
vis.map.points(src, '*y')
inicial = ui.picker.points(area, ax, marker='*', color='k')[0]
srcs, recs = utils.connect_points(src, rec_points)
ptime = traveltime.straight_ray_2d(model, 'vp', srcs, recs)
stime = traveltime.straight_ray_2d(model, 'vs', srcs, recs)
error_level = params.ruido
ttr_true = stime - ptime
ttr, error = utils.contaminate(ttr_true, error_level, percent=True,
return_stddev=True)
solver = inversion.gradient.newton(initial=inicial)
result = epicenter.flat_earth(ttr, recs, vp, vs, solver)
estimate, residuals = result
predicted = ttr - residuals
pyplot.figure(figsize=(14,6))
pyplot.subplot(1, 2, 1)
pyplot.title('Epicentro + estacoes')
pyplot.axis('scaled')
vis.map.points(recs, '^r', label="Estacaoes")
from fatiando.seismic import traveltime
from fatiando import vis, logger, utils, inversion
import cPickle as pickle
params = __import__('exercicio1_entrada')
imgfile = params.imagem
area = (0, 5, 0, 5)
shape = params.tamanho
model = SquareMesh(area, shape)
model.img2prop(imgfile, params.vmin, params.vmax, 'vp')
src_loc = utils.random_points(area, params.epicentros)
rec_loc = utils.circular_points(area, params.sismometros, random=True)
srcs, recs = utils.connect_points(src_loc, rec_loc)
tts, error = utils.contaminate(traveltime.straight_ray_2d(
model, 'vp', srcs, recs),
params.ruido,
percent=True,
return_stddev=True)
with open(params.dados, 'w') as f:
data = [model, src_loc, rec_loc, tts, error]
pickle.dump(data, f)
pyplot.figure(figsize=(7, 5))
pyplot.axis('scaled')
pyplot.title('Modelo de velocidades')
vis.map.squaremesh(model, model.props['vp'], cmap=pyplot.cm.seismic)
cb = pyplot.colorbar()
cb.set_label('Velocidade')
vis.map.points(src_loc, '*y', label="Epicentros")
pyplot.suptitle("Escolha o epicentro")
ax = pyplot.subplot(1, 2, 1)
pyplot.axis("scaled")
vis.map.points(recs, "^r", label="Stations")
ax2 = pyplot.subplot(1, 2, 2)
pyplot.title("Tempos de chegada")
s = numpy.arange(len(ttr)) + 1
width = 0.2
pyplot.bar(s - width, ttr, width, color="r", yerr=error)
ax2.set_xticks(s)
pyplot.xlabel("Estacao")
pyplot.ylabel("Tempo de chegada")
src_model = ui.picker.points(area, ax, marker="*", color="y")
srcs, recs = utils.connect_points(src_model, recs)
ptime = traveltime.straight_ray_2d(model, "vp", srcs, recs)
stime = traveltime.straight_ray_2d(model, "vs", srcs, recs)
ttr_model = stime - ptime
with open("exercicio3-modelo.pickle", "w") as f:
data = {"ttr": ttr_model, "recs": recs, "src": src_model}
pickle.dump(data, f)
pyplot.figure(figsize=(14, 6))
pyplot.subplot(1, 2, 1)
pyplot.title("Epicentros")
pyplot.axis("scaled")
vis.map.points(recs, "^r", label="Estacao")
vis.map.points(src_model, "*y", label="Epicentro")
vis.map.set_area(area)
pyplot.legend(loc="upper left", shadow=True, numpoints=1, prop={"size": 10})
from fatiando import vis, logger, utils, inversion
import cPickle as pickle
params = __import__('exercicio1_entrada')
imgfile = params.imagem
area = (0, 5, 0, 5)
shape = params.tamanho
model = SquareMesh(area, shape)
model.img2prop(imgfile, params.vmin, params.vmax, 'vp')
src_loc = utils.random_points(area, params.epicentros)
rec_loc = utils.circular_points(area, params.sismometros, random=True)
srcs, recs = utils.connect_points(src_loc, rec_loc)
tts, error = utils.contaminate(
traveltime.straight_ray_2d(model, 'vp', srcs, recs), params.ruido, percent=True,
return_stddev=True)
with open(params.dados, 'w') as f:
data = [model, src_loc, rec_loc, tts, error]
pickle.dump(data, f)
pyplot.figure(figsize=(7, 5))
pyplot.axis('scaled')
pyplot.title('Modelo de velocidades')
vis.map.squaremesh(model, model.props['vp'], cmap=pyplot.cm.seismic)
cb = pyplot.colorbar()
cb.set_label('Velocidade')
vis.map.points(src_loc, '*y', label="Epicentros")
vis.map.points(rec_loc, '^r', label="Sismometros")
leg = pyplot.legend(loc='lower left', shadow=True, numpoints=1)
