Python run 예제들

예제 #1

from fatiando.mesher.dd import SquareMesh
from fatiando.seismic import traveltime, srtomo
from fatiando import vis, logger, utils, inversion
import cPickle as pickle

params = __import__('exercicio4_entrada')
mu = params.suavidade
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.linear.overdet(mesh.size)
results = srtomo.run(tts, srcs, recs, mesh, solver, smooth=mu)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia (Suavidade)')
vis.map.squaremesh(mesh, estimate, vmin=1./vmax, vmax=1./vmin,
    cmap=pyplot.cm.seismic_r)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title('Residuos (erro %g s)' % (error))
pyplot.hist(residuals, color='gray', bins=10)
pyplot.xlabel("Segundos")

예제 #2

파일: exercicio5.py 프로젝트: marlonchg/inverse-problems

from fatiando import vis, logger, utils, inversion
import cPickle as pickle

log = logger.get()
params = __import__('exercicio5_entrada')
mu = params.variacao_total
beta = params.beta
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.gradient.steepest(numpy.zeros(mesh.size))
results = srtomo.run(tts, srcs, recs, mesh, solver, sharp=mu, beta=beta)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia (Variacao Total)')
vis.map.squaremesh(mesh, estimate, vmin=1./vmax, vmax=1./vmin,
    cmap=pyplot.cm.seismic_r)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title('Residuos (erro %g s)' % (error))
pyplot.hist(residuals, color='gray', bins=10)
pyplot.xlabel("Segundos")

예제 #3

파일: exercicio6.py 프로젝트: pinga-lab/inversao-iag-2012

smooth = params.suavidade
sharp = params.variacao_total
beta = params.beta
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.gradient.steepest(numpy.zeros(mesh.size))
results = srtomo.run(tts,
                     srcs,
                     recs,
                     mesh,
                     solver,
                     damping=damping,
                     smooth=smooth,
                     sharp=sharp,
                     beta=beta)
estimate, residuals = results

with open('exercicio6-modelo.pickle', 'w') as f:
    data = estimate
    pickle.dump(data, f)

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia')
vis.map.squaremesh(mesh,

예제 #4

파일: exercicio5.py 프로젝트: pinga-lab/inversao-iag-2012

from fatiando import vis, logger, utils, inversion
import cPickle as pickle

log = logger.get()
params = __import__('exercicio5_entrada')
mu = params.variacao_total
beta = params.beta
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.gradient.steepest(numpy.zeros(mesh.size))
results = srtomo.run(tts, srcs, recs, mesh, solver, sharp=mu, beta=beta)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia (Variacao Total)')
vis.map.squaremesh(mesh,
                   estimate,
                   vmin=1. / vmax,
                   vmax=1. / vmin,
                   cmap=pyplot.cm.seismic_r)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()

예제 #5

파일: exercicio6.py 프로젝트: marlonchg/inverse-problems

import cPickle as pickle

params = __import__('exercicio6_entrada')
damping = params.norma_minima
smooth = params.suavidade
sharp = params.variacao_total
beta = params.beta
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.gradient.steepest(numpy.zeros(mesh.size))
results = srtomo.run(tts, srcs, recs, mesh, solver, damping=damping,
    smooth=smooth, sharp=sharp, beta=beta)
estimate, residuals = results

with open('exercicio6-modelo.pickle', 'w') as f:
    data = estimate
    pickle.dump(data, f)

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia')
vis.map.squaremesh(mesh, estimate, vmin=1./vmax, vmax=1./vmin,
    cmap=pyplot.cm.seismic_r)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)

예제 #6

파일: exercicio2.py 프로젝트: marlonchg/inverse-problems

import numpy
from fatiando.mesher.dd import SquareMesh
from fatiando.seismic import traveltime, srtomo
from fatiando import vis, logger, utils, inversion
import cPickle as pickle

params = __import__('exercicio2_entrada')
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.linear.overdet(mesh.size)
results = srtomo.run(tts, srcs, recs, mesh, solver)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia')
vis.map.squaremesh(mesh, estimate, vmin=1./vmax, vmax=1./vmin,
    cmap=pyplot.cm.gist_gray)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title('Residuos (erro %g s)' % (error))
pyplot.hist(residuals, color='gray', bins=10)
pyplot.xlabel("Segundos")

예제 #7

파일: exercicio2.py 프로젝트: pinga-lab/inversao-iag-2012

import numpy
from fatiando.mesher.dd import SquareMesh
from fatiando.seismic import traveltime, srtomo
from fatiando import vis, logger, utils, inversion
import cPickle as pickle

params = __import__('exercicio2_entrada')
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.linear.overdet(mesh.size)
results = srtomo.run(tts, srcs, recs, mesh, solver)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia')
vis.map.squaremesh(mesh,
                   estimate,
                   vmin=1. / vmax,
                   vmax=1. / vmin,
                   cmap=pyplot.cm.gist_gray)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()

예제 #8

from fatiando.mesher.dd import SquareMesh
from fatiando.seismic import traveltime, srtomo
from fatiando import vis, logger, utils, inversion
import cPickle as pickle

params = __import__('exercicio3_entrada')
mu = params.norma_minima
area = (0, 5, 0, 5)
with open(params.dados) as f:
    model, src_loc, rec_loc, tts, error = pickle.load(f)
shape = model.shape
vmin, vmax = model.props['vp'].min(), model.props['vp'].max()
srcs, recs = utils.connect_points(src_loc, rec_loc)
mesh = SquareMesh(area, shape)
solver = inversion.linear.overdet(mesh.size)
results = srtomo.run(tts, srcs, recs, mesh, solver, damping=mu)
estimate, residuals = results

pyplot.figure(figsize=(14, 5))
pyplot.subplot(1, 2, 1)
pyplot.axis('scaled')
pyplot.title('Tomografia (Norma Minima)')
vis.map.squaremesh(mesh, estimate, vmin=1./vmax, vmax=1./vmin,
    cmap=pyplot.cm.seismic_r)
cb = pyplot.colorbar()
cb.set_label('Vagarosidade')
pyplot.subplot(1, 2, 2)
pyplot.grid()
pyplot.title('Residuos (erro %g s)' % (error))
pyplot.hist(residuals, color='gray', bins=10)
pyplot.xlabel("Segundos")