def load_data():
top = geoprobe.horizon('data/seismic/Horizons/seafloor.hzn')
base = geoprobe.horizon('data/seismic/Horizons/channels.hzn')
vol = geoprobe.volume('data/seismic/Volumes/example.vol')
coh = geoprobe.volume('data/seismic/Volumes/coherence.vol')
vol.data = vol.load()
coh.data = coh.load()
base = smooth_horizon(base)
top = smooth_horizon(top)
return vol, coh, base, top
def test_isopach():
x, y = np.mgrid[50:100, 50:100]
z1 = np.hypot(x - x.mean(), y - y.mean())
z2 = 2 * z1
hor1 = geoprobe.horizon(x=x.ravel(), y=y.ravel(), z=z1.ravel())
hor2 = geoprobe.horizon(x=x.ravel(), y=y.ravel(), z=z2.ravel())
iso = geoprobe.utilities.create_isopach(hor2, hor1)
assert np.allclose(iso.x, x.ravel())
assert np.allclose(iso.y, y.ravel())
assert np.allclose(z2 - z1, iso.grid)
def test_isopach():
x, y = np.mgrid[50:100, 50:100]
z1 = np.hypot(x - x.mean(), y - y.mean())
z2 = 2 * z1
hor1 = geoprobe.horizon(x=x.ravel(), y=y.ravel(), z=z1.ravel())
hor2 = geoprobe.horizon(x=x.ravel(), y=y.ravel(), z=z2.ravel())
iso = geoprobe.utilities.create_isopach(hor2, hor1)
assert np.allclose(iso.x, x.ravel())
assert np.allclose(iso.y, y.ravel())
assert np.allclose(z2 - z1, iso.grid)
def smooth_horizon(hor):
z = hor.grid
z = scipy.ndimage.median_filter(z.astype(float), 4)
z = scipy.ndimage.gaussian_filter(z, 1.5)
xmin, xmax, ymin, ymax = hor.grid_extents
y, x = np.mgrid[ymin:ymax+1, xmin:xmax+1]
return geoprobe.horizon(x.flatten(), y.flatten(), z.flatten())
def load_data():
top = geoprobe.horizon('data/seismic/Horizons/channels.hzn')
vol = geoprobe.volume('data/seismic/Volumes/example.vol')
vol.data = vol.load()
top = smooth_horizon(top)
return vol, top
def seafloor_mute(self, seafloor, pad=0, color='white', value=None):
"""
"Mute" (i.e. plot a filled polygon over) the seismic data above the
seafloor.
Parameters:
-----------
seafloor: string filename or geoprobe.horizon instance
The seafloor horizon (or filename of one) to use.
pad: number
The vertical (above the seafloor) padding in z (time or depth)
units between the actual horizon values and the bottom of the
filled polygon.
color: matplotlib color specifier (e.g. string or tuple of floats)
The color of the filled polygon.
value: number (default=None)
If specified, the "color" kwarg is ignored, and self.colormap
is used to choose the color based on the input "value".
Returns:
--------
A matplotlib PolyCollection artist.
"""
if isinstance(seafloor, basestring):
seafloor = geoprobe.horizon(seafloor)
dist, z = self.slice_horizon(seafloor)
z -= pad
if value is not None:
color = self.im.cmap(self.im.norm(value))
collection = self.ax.fill_between(dist, self.zmin, z, facecolor=color,
edgecolor='none')
return collection
def plot_present_day(fig):
topax = fig.add_subplot(6, 1, 1, aspect=2, adjustable='box')
seafloor = geoprobe.horizon('/data/nankai/data/Horizons/jdk_seafloor.hzn')
plot_horizons(topax, data.horizons + [seafloor])
plt.setp(topax.get_xticklabels(), visible=True)
topax.set_ylabel('Depth (km bsl)')
topax.set_xlabel('Distance Along Section (km)')
return topax
def plot_present_day(fig):
topax = fig.add_subplot(6,1,1, aspect=2, adjustable='box')
seafloor = geoprobe.horizon('/data/nankai/data/Horizons/jdk_seafloor.hzn')
plot_horizons(topax, data.horizons + [seafloor])
plt.setp(topax.get_xticklabels(), visible=True)
topax.set_ylabel('Depth (km bsl)')
topax.set_xlabel('Distance Along Section (km)')
return topax
def main():
# Path to the example data dir relative to the location of this script.
# This is just so that the script can be called from a different directory
datadir = os.path.dirname(__file__) + '/data/'
# Read an existing geoprobe horizon
hor = geoprobe.horizon(datadir + 'Horizons/channels.hzn')
print_info(hor)
plot(hor)
def main():
# Path to the example data dir relative to the location of this script.
# This is just so that the script can be called from a different directory
datadir = os.path.dirname(__file__) + '/data/'
# Read an existing geoprobe horizon
hor = geoprobe.horizon(datadir + 'Horizons/channels.hzn')
print_info(hor)
plot(hor)
def plot_horizon(self, hor, colormap=None):
if isinstance(hor, basestring):
hor = geoprobe.horizon(hor)
if colormap is None:
colormap = mpl.cm.jet
hor.grid_extents = self.extents
data = -hor.grid
ls = utilities.Shader(azdeg=315, altdeg=45)
rgb = ls.shade(data, cmap=colormap, mode='overlay')
im = self.ax.imshow(rgb, extent=self.extents, origin='lower')
return im
def plot_horizon(self, hor, colormap=None):
if isinstance(hor, basestring):
hor = geoprobe.horizon(hor)
if colormap is None:
colormap = mpl.cm.jet
hor.grid_extents = self.extents
data = -hor.grid
ls = utilities.Shader(azdeg=315, altdeg=45)
rgb = ls.shade(data, cmap=colormap, mode='overlay')
im = self.ax.imshow(rgb, extent=self.extents, origin='lower')
return im
def __init__(self, ax, vol, horizonname=None, extents=None, name=''):
if extents is None:
extents = [vol.xmin, vol.xmax, vol.ymin, vol.ymax]
self.name = name
self.extents = extents
self.vol = vol
self.ax = ax
if horizonname is not None:
self.base_hor = geoprobe.horizon(horizonname)
self.base_hor.grid_extents = extents
self.baseim = self.plot_horizon(self.base_hor)
self.ax.axis(extents)
self.ax.set_aspect(self.vol.dyW / self.vol.dxW)
self.ax.set_title(name)
self.bounds = utilities.extents_to_poly(*extents)
def __init__(self, ax, vol, horizonname=None, extents=None, name=''):
if extents is None:
extents = [vol.xmin, vol.xmax, vol.ymin, vol.ymax]
self.name = name
self.extents = extents
self.vol = vol
self.ax = ax
if horizonname is not None:
self.base_hor = geoprobe.horizon(horizonname)
self.base_hor.grid_extents = extents
self.baseim = self.plot_horizon(self.base_hor)
self.ax.axis(extents)
self.ax.set_aspect(self.vol.dyW / self.vol.dxW)
self.ax.set_title(name)
self.bounds = utilities.extents_to_poly(*extents)
def xyz2hor(xyz):
return geoprobe.horizon(*xyz.T)
# These are in stratigraphic order from oldest to youngest
horizon_names = [
'jdk_forearc_horizon_7.hzn',
'jdk_forearc_horizon_6.hzn',
'jdk_forearc_horizon_5.hzn',
'jdk_forearc_horizon_4.hzn',
'jdk_forearc_horizon_3.5.hzn',
'jdk_forearc_horizon_3.hzn',
'jdk_forearc_horizon_2.5.hzn',
'jdk_forearc_horizon_2.hzn',
'jdk_forearc_horizon_1.5.hzn',
'jdk_forearc_horizon_1.hzn',
]
horizon_names = [os.path.join(basedir, 'Horizons', item) for item in horizon_names]
horizons = [geoprobe.horizon(item) for item in horizon_names]
gulick_names = ['7', '6', '5', '4', '3.5', '3', '2.5', '2', '1.5', '1']
# Best fit shear angle for inclined shear
alpha = 70
def to_xyz(hor):
return np.vstack([hor.x, hor.y, hor.z]).T
def xyz2hor(xyz):
return geoprobe.horizon(*xyz.T)
def to_world(points):
points = np.atleast_2d(points)
import geoprobe
import data
import utilities
from fault_kinematics import homogeneous_simple_shear
from process_bootstrap_results import get_result, load
fault = data.to_world(data.to_xyz(data.fault))
alpha = data.alpha
f, group = load()
for hor in data.horizons:
print hor.name
xyz = data.to_world(data.to_xyz(hor))
slip = get_result(hor.name, group)
restored = homogeneous_simple_shear.inclined_shear(fault, xyz, slip, alpha)
print 'Resampling...'
restored = data.to_model(restored)
restored = utilities.grid_xyz(restored)
new_hor = geoprobe.horizon(*restored.T)
new_hor.write('restored_horizons/' + hor.name + '.hzn')
f.close()
from mayavi import mlab
import numpy as np
import geoprobe
import scipy.ndimage
hor = geoprobe.horizon('data/seismic/Horizons/channels.hzn')
vol = geoprobe.volume('data/seismic/Volumes/example.vol')
data = vol.load()
# Because we're not working in inline/crossline, convert to "pixel" coords.
z = hor.grid
z = vol.model2index(z, axis='z', int_conversion=False)
# Clip out some spikes and smooth the surface a bit...
z = scipy.ndimage.median_filter(z, 4)
z = scipy.ndimage.gaussian_filter(z, 1)
# Quirks due to the way hor.grid is defined...
mlab.surf(np.arange(z.shape[0]), np.arange(z.shape[1]), -z.T,
colormap='gist_earth')
source = mlab.pipeline.scalar_field(data)
source.spacing = [1, 1, -1]
for axis in ['x', 'y']:
plane = mlab.pipeline.image_plane_widget(source,
plane_orientation='{}_axes'.format(axis),
slice_index=100, colormap='gray')
plane.module_manager.scalar_lut_manager.reverse_lut = True
mlab.show()
def xyz2hor(xyz):
return geoprobe.horizon(*xyz.T)
'jdk_forearc_horizon_7.hzn',
'jdk_forearc_horizon_6.hzn',
'jdk_forearc_horizon_5.hzn',
'jdk_forearc_horizon_4.hzn',
'jdk_forearc_horizon_3.5.hzn',
'jdk_forearc_horizon_3.hzn',
'jdk_forearc_horizon_2.5.hzn',
'jdk_forearc_horizon_2.hzn',
'jdk_forearc_horizon_1.5.hzn',
'jdk_forearc_horizon_1.hzn',
]
horizon_names = [
os.path.join(basedir, 'Horizons', item) for item in horizon_names
]
horizons = [geoprobe.horizon(item) for item in horizon_names]
gulick_names = ['7', '6', '5', '4', '3.5', '3', '2.5', '2', '1.5', '1']
# Best fit shear angle for inclined shear
alpha = 70
def to_xyz(hor):
return np.vstack([hor.x, hor.y, hor.z]).T
def xyz2hor(xyz):
return geoprobe.horizon(*xyz.T)
def __init__(self, horizons, styles=None):
self.horizons = [geoprobe.horizon(hor) for hor in horizons]
if styles is None:
styles = [dict() for _ in horizons]
self.styles = styles
def top_texture(hor, vol):
"""Coherence extracted 50 meters below top horizon."""
hor = geoprobe.horizon(hor.x, hor.y, hor.z + 50)
hor.grid_extents = vol.xmin, vol.xmax, vol.ymin, vol.ymax
return geoprobe.utilities.extractWindow(hor, vol, 0, 0)