def plot(self,
depth_range=(0, 60000.),
ddepth=100.,
ddbin=2000.,
vel_range=None,
dvbin=100.,
percent=False,
plot_mode=True,
plot_median=True,
plot_mean=False,
show_cbar=True,
aspect=.02,
phase='p',
axes=None):
''' Plot a two 2D Histogram of seismic velocities
:param depth_range: Depth range, ``(dmin, dmax)``,
defaults to ``(0, 60)``
:type depth_range: tuple
:param vel_range: Velocity range, ``(vmin, vmax)``
:type vel_range: tuple
:param ddepth: Stepping in [m], defaults to ``.1``
:type ddepth: float
:param dvbin: Bin size in velocity dimension [m/s], defaults to .1
:type dvbin: float
:param dvbin: Bin size in depth dimension [m], defaults to 2000.
:type dvbin: float
:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p``
:type phase: str
:param plot_mode: Plot the Mode
:type plot_mode: bool
:param plot_mean: Plot the Mean
:type plot_mean: bool
:param plot_median: Plot the Median
:type plot_median: bool
:param axes: Axes to plot into, defaults to None
:type axes: :class:`matplotlib.Axes`
'''
import matplotlib.pyplot as plt
fig, ax = _getCanvas(axes)
ax = fig.gca()
if vel_range is not None:
vmin, vmax = vel_range
dmin, dmax = depth_range
vfield, vedg, dedg = self.histogram2d(vel_range=vel_range,
depth_range=depth_range,
ddepth=ddepth,
dvbin=dvbin,
ddbin=ddbin,
phase=phase)
vfield /= (ddbin / ddepth)
if percent:
vfield /= vfield.sum(axis=1)[num.newaxis, :]
grid_ext = [vedg[0], vedg[-1], dedg[-1], dedg[0]]
histogram = ax.imshow(vfield.swapaxes(0, 1),
interpolation='nearest',
extent=grid_ext,
aspect=aspect)
if show_cbar:
cticks = num.unique(
num.arange(0, vfield.max(),
vfield.max() // 10).round())
cbar = fig.colorbar(histogram,
ticks=cticks,
format='%1i',
orientation='horizontal')
if percent:
cbar.set_label('Percent')
else:
cbar.set_label('Number of Profiles')
if plot_mode:
sdepth, vel_mode, _ = self.modeVelocity(depth_range=depth_range,
ddepth=ddepth)
ax.plot(vel_mode[sdepth < dmax] + ddepth / 2,
sdepth[sdepth < dmax],
alpha=.8,
color='w',
label='Mode')
if plot_mean:
sdepth, vel_mean, _ = self.meanVelocity(depth_range=depth_range,
ddepth=ddepth)
ax.plot(vel_mean[sdepth < dmax] + ddepth / 2,
sdepth[sdepth < dmax],
alpha=.8,
color='w',
linestyle='--',
label='Mean')
if plot_median:
sdepth, vel_median, _ = self.medianVelocity(
depth_range=depth_range, ddepth=ddepth)
ax.plot(vel_median[sdepth < dmax] + ddepth / 2,
sdepth[sdepth < dmax],
alpha=.8,
color='w',
linestyle=':',
label='Median')
ax.grid(True, which="both", color="w", linewidth=.8, alpha=.4)
ax.text(.025,
.025,
'%d Profiles' % self.nprofiles,
color='w',
alpha=.7,
transform=ax.transAxes,
fontsize=9,
va='bottom',
ha='left')
ax.set_title('Crustal Velocity Distribution')
ax.set_xlabel('%s [km/s]' % vel_labels[phase])
ax.set_ylabel('Depth [km]')
yscaled(1. / km, ax)
xoffset_scale(dvbin / 2, 1. / km, ax)
ax.set_xlim(vel_range)
if self.name is not None:
ax.set_title('%s for %s' % (ax.get_title(), self.name))
if plot_mode or plot_mean or plot_median:
leg = ax.legend(loc=1, fancybox=True, prop={'size': 10.})
leg.get_frame().set_alpha(.6)
if axes is None:
plt.show()
def command_tttview(args):
import numpy as num
import matplotlib.pyplot as plt
from pyrocko.plot.cake_plot import mpl_init, labelspace, xscaled, yscaled
mpl_init()
def setup(parser):
parser.add_option('--source-depth',
dest='depth',
type=float,
help='Source depth in km')
parser, options, args = cl_parse(
'tttview',
args,
setup=setup,
details="Comma seperated <phase-ids>, eg. 'fomosto tttview Pdiff,S'.")
try:
phase_ids = args.pop().split(',')
except Exception:
parser.error('cannot get <phase-ids> argument')
np = 1
store_dir = get_store_dir(args)
for phase_id in phase_ids:
try:
store = gf.Store(store_dir)
phase = store.get_stored_phase(phase_id)
axes = plt.subplot(2, len(phase_ids), np)
labelspace(axes)
xscaled(1. / km, axes)
yscaled(1. / km, axes)
phase.plot_2d(axes)
axes.set_title(phase_id)
np += 1
except gf.StoreError as e:
die(e)
axes = plt.subplot(2, 1, 2)
num_d = 100
distances = num.linspace(store.config.distance_min,
store.config.distance_max, num_d)
if options.depth:
depth = options.depth
depth *= 1000
else:
depth = store.config.source_depth_min + (
store.config.source_depth_max - store.config.source_depth_min) / 2.
if isinstance(store.config, gf.ConfigTypeA):
arrivals = num.empty(num_d)
for phase_id in phase_ids:
arrivals[:] = num.NAN
for i, d in enumerate(distances):
arrivals[i] = store.t(phase_id, (depth, d))
axes.plot(distances / 1000, arrivals, label=phase_id)
axes.set_title('source depth %s km' % (depth / 1000))
axes.set_xlabel('distance [km]')
axes.set_ylabel('TT [s]')
axes.legend()
plt.tight_layout()
plt.show()
def command_modelview(args):
import matplotlib.pyplot as plt
import numpy as num
from pyrocko.plot.cake_plot import mpl_init, labelspace, xscaled, yscaled
mpl_init()
neat_labels = {
'vp': '$v_p$',
'vs': '$v_s$',
'qp': '$Q_p$',
'qs': '$Q_s$',
'rho': '$\\rho$'
}
def setup(parser):
parser.add_option(
'--parameters',
dest='parameters',
default='vp,vs',
metavar='vp,vs,....',
help='select one or several of vp, vs, rho, qp, qs, vp/vs, qp/qs')
units = {'vp': '[km/s]', 'vs': '[km/s]', 'rho': '[g/cm^3]'}
parser, options, args = cl_parse('modelview', args, setup=setup)
store_dirs = get_store_dirs(args)
parameters = options.parameters.split(',')
fig, axes = plt.subplots(1,
len(parameters),
sharey=True,
figsize=(len(parameters) * 3, 5))
if not isinstance(axes, num.ndarray):
axes = [axes]
axes = dict(zip(parameters, axes))
for store_id in store_dirs:
try:
store = gf.Store(store_id)
mod = store.config.earthmodel_1d
z = mod.profile('z')
for p in parameters:
ax = axes[p]
labelspace(ax)
if '/' in p:
p1, p2 = p.split('/')
profile = mod.profile(p1) / mod.profile(p2)
else:
profile = mod.profile(p)
ax.plot(profile, -z, label=store_id.split('/')[-1])
if p in ['vs', 'vp', 'rho']:
xscaled(1. / 1000., ax)
yscaled(1. / km, ax)
except gf.StoreError as e:
die(e)
for p, ax in axes.items():
ax.grid()
if p in neat_labels:
lab = neat_labels[p]
elif all(x in neat_labels for x in p.split('/')):
lab = '/'.join(neat_labels[x] for x in p.split('/'))
else:
lab = p
ax.set_title(lab, y=1.02)
if p in units:
lab += ' ' + units[p]
ax.autoscale()
ax.set_xlabel(lab)
axes[parameters[0]].set_ylabel('Depth [km]')
handles, labels = ax.get_legend_handles_labels()
if len(store_dirs) > 1:
ax.legend(handles,
labels,
bbox_to_anchor=(0.5, 0.12),
bbox_transform=fig.transFigure,
ncol=3,
loc='upper center',
fancybox=True)
plt.subplots_adjust(bottom=0.22, wspace=0.05)
plt.show()
def command_tttview(args):
import numpy as num
import matplotlib.pyplot as plt
from pyrocko.plot.cake_plot import mpl_init, labelspace, xscaled, yscaled
mpl_init()
def setup(parser):
parser.add_option(
'--source-depth', dest='depth', type=float,
help='Source depth in km')
parser, options, args = cl_parse(
'tttview', args, setup=setup,
details="Comma seperated <phase-ids>, eg. 'fomosto tttview Pdiff,S'.")
try:
phase_ids = args.pop().split(',')
except Exception:
parser.error('cannot get <phase-ids> argument')
np = 1
store_dir = get_store_dir(args)
for phase_id in phase_ids:
try:
store = gf.Store(store_dir)
phase = store.get_stored_phase(phase_id)
axes = plt.subplot(2, len(phase_ids), np)
labelspace(axes)
xscaled(1./km, axes)
yscaled(1./km, axes)
phase.plot_2d(axes)
axes.set_title(phase_id)
np += 1
except gf.StoreError as e:
die(e)
axes = plt.subplot(2, 1, 2)
num_d = 100
distances = num.linspace(store.config.distance_min,
store.config.distance_max,
num_d)
if options.depth:
depth = options.depth
depth *= 1000
else:
depth = store.config.source_depth_min + (
store.config.source_depth_max - store.config.source_depth_min)/2.
if isinstance(store.config, gf.ConfigTypeA):
arrivals = num.empty(num_d)
for phase_id in phase_ids:
arrivals[:] = num.NAN
for i, d in enumerate(distances):
arrivals[i] = store.t(phase_id, (depth, d))
axes.plot(distances/1000, arrivals, label=phase_id)
axes.set_title('source depth %s km' % (depth/1000))
axes.set_xlabel('distance [km]')
axes.set_ylabel('TT [s]')
axes.legend()
plt.tight_layout()
plt.show()
def command_modelview(args):
import matplotlib.pyplot as plt
import numpy as num
from pyrocko.plot.cake_plot import mpl_init, labelspace, xscaled, yscaled
mpl_init()
neat_labels = {
'vp': '$v_p$',
'vs': '$v_s$',
'qp': '$Q_p$',
'qs': '$Q_s$',
'rho': '$\\rho$'}
def setup(parser):
parser.add_option(
'--parameters', dest='parameters',
default='vp,vs', metavar='vp,vs,....',
help='select one or several of vp, vs, rho, qp, qs, vp/vs, qp/qs')
units = {'vp': '[km/s]', 'vs': '[km/s]', 'rho': '[g/cm^3]'}
parser, options, args = cl_parse('modelview', args, setup=setup)
store_dirs = get_store_dirs(args)
parameters = options.parameters.split(',')
fig, axes = plt.subplots(1,
len(parameters),
sharey=True,
figsize=(len(parameters)*3, 5))
if not isinstance(axes, num.ndarray):
axes = [axes]
axes = dict(zip(parameters, axes))
for store_id in store_dirs:
try:
store = gf.Store(store_id)
mod = store.config.earthmodel_1d
z = mod.profile('z')
for p in parameters:
ax = axes[p]
labelspace(ax)
if '/' in p:
p1, p2 = p.split('/')
profile = mod.profile(p1)/mod.profile(p2)
else:
profile = mod.profile(p)
ax.plot(profile, -z, label=store_id.split('/')[-1])
if p in ['vs', 'vp', 'rho']:
xscaled(1./1000., ax)
yscaled(1./km, ax)
except gf.StoreError as e:
die(e)
for p, ax in axes.items():
ax.grid()
if p in neat_labels:
lab = neat_labels[p]
elif all(x in neat_labels for x in p.split('/')):
lab = '/'.join(neat_labels[x] for x in p.split('/'))
else:
lab = p
ax.set_title(lab, y=1.02)
if p in units:
lab += ' ' + units[p]
ax.autoscale()
ax.set_xlabel(lab)
axes[parameters[0]].set_ylabel('Depth [km]')
handles, labels = ax.get_legend_handles_labels()
if len(store_dirs) > 1:
ax.legend(
handles,
labels,
bbox_to_anchor=(0.5, 0.12),
bbox_transform=fig.transFigure,
ncol=3,
loc='upper center',
fancybox=True)
plt.subplots_adjust(bottom=0.22,
wspace=0.05)
plt.show()
def plot(self, depth_range=(0, 60000.), ddepth=100., ddbin=2000.,
vel_range=None, dvbin=100.,
percent=False,
plot_mode=True, plot_median=True, plot_mean=False,
show_cbar=True,
aspect=.02,
phase='p',
axes=None):
''' Plot a two 2D Histogram of seismic velocities
:param depth_range: Depth range, ``(dmin, dmax)``,
defaults to ``(0, 60)``
:type depth_range: tuple
:param vel_range: Velocity range, ``(vmin, vmax)``
:type vel_range: tuple
:param ddepth: Stepping in [m], defaults to ``.1``
:type ddepth: float
:param dvbin: Bin size in velocity dimension [m/s], defaults to .1
:type dvbin: float
:param dvbin: Bin size in depth dimension [m], defaults to 2000.
:type dvbin: float
:param phase: Phase to calculate ``p`` or ``s``, defaults to ``p``
:type phase: str
:param plot_mode: Plot the Mode
:type plot_mode: bool
:param plot_mean: Plot the Mean
:type plot_mean: bool
:param plot_median: Plot the Median
:type plot_median: bool
:param axes: Axes to plot into, defaults to None
:type axes: :class:`matplotlib.Axes`
'''
import matplotlib.pyplot as plt
fig, ax = _getCanvas(axes)
ax = fig.gca()
if vel_range is not None:
vmin, vmax = vel_range
dmin, dmax = depth_range
vfield, vedg, dedg = self.histogram2d(vel_range=vel_range,
depth_range=depth_range,
ddepth=ddepth, dvbin=dvbin,
ddbin=ddbin, phase=phase)
vfield /= (ddbin / ddepth)
if percent:
vfield /= vfield.sum(axis=1)[num.newaxis, :]
grid_ext = [vedg[0], vedg[-1], dedg[-1], dedg[0]]
histogram = ax.imshow(vfield.swapaxes(0, 1),
interpolation='nearest',
extent=grid_ext, aspect=aspect)
if show_cbar:
cticks = num.unique(
num.arange(0, vfield.max(), vfield.max() // 10).round())
cbar = fig.colorbar(histogram, ticks=cticks, format='%1i',
orientation='horizontal')
if percent:
cbar.set_label('Percent')
else:
cbar.set_label('Number of Profiles')
if plot_mode:
sdepth, vel_mode, _ = self.modeVelocity(depth_range=depth_range,
ddepth=ddepth)
ax.plot(vel_mode[sdepth < dmax] + ddepth/2,
sdepth[sdepth < dmax],
alpha=.8, color='w', label='Mode')
if plot_mean:
sdepth, vel_mean, _ = self.meanVelocity(depth_range=depth_range,
ddepth=ddepth)
ax.plot(vel_mean[sdepth < dmax] + ddepth/2,
sdepth[sdepth < dmax],
alpha=.8, color='w', linestyle='--', label='Mean')
if plot_median:
sdepth, vel_median, _ = self.medianVelocity(
depth_range=depth_range,
ddepth=ddepth)
ax.plot(vel_median[sdepth < dmax] + ddepth/2,
sdepth[sdepth < dmax],
alpha=.8, color='w', linestyle=':', label='Median')
ax.grid(True, which="both", color="w", linewidth=.8, alpha=.4)
ax.text(.025, .025, '%d Profiles' % self.nprofiles,
color='w', alpha=.7,
transform=ax.transAxes, fontsize=9, va='bottom', ha='left')
ax.set_title('Crustal Velocity Distribution')
ax.set_xlabel('%s [km/s]' % vel_labels[phase])
ax.set_ylabel('Depth [km]')
yscaled(1./km, ax)
xoffset_scale(dvbin/2, 1./km, ax)
ax.set_xlim(vel_range)
if self.name is not None:
ax.set_title('%s for %s' % (ax.get_title(), self.name))
if plot_mode or plot_mean or plot_median:
leg = ax.legend(loc=1, fancybox=True, prop={'size': 10.})
leg.get_frame().set_alpha(.6)
if axes is None:
plt.show()
