def plot_interface(self, x, y, z, scale='km'):
"""
take xyz data, create a grid and make a contour plot
"""
import pek1dplotting as p1dp
z = p1dp.update_scale(z, scale)
xi = np.array(
np.meshgrid(
np.linspace(
min(x), max(x), 20), np.linspace(
min(y), max(y), 50))).T
zi = si.griddata(np.vstack([x, y]).T,
z,
xi,
method=self.imethod)
cmap = plt.get_cmap(self.cmap)
if self.levels is None:
plt1 = plt.contourf(xi[:, :, 0], xi[:, :, 1], zi, cmap=cmap)
self.levels = plt1.levels
else:
plt1 = plt.contourf(xi[:, :, 0], xi[:, :, 1], zi,
levels=self.levels, cmap=cmap)
ax = plt.gca()
ax.set_aspect('equal')
if self.plot_cbar:
self.add_cbar()
if self.xlim is not None:
plt.xlim(self.xlim)
if self.ylim is not None:
plt.ylim(self.ylim)
def plot_interface(self,x,y,z,scale='km'):
"""
take xyz data, create a grid and make a contour plot
"""
import pek1dplotting as p1dp
z = p1dp.update_scale(z,scale)
xi = np.array(np.meshgrid(np.linspace(min(x),max(x),20),np.linspace(min(y),max(y),50))).T
zi = si.griddata(np.vstack([x,y]).T,
z,
xi,
method=self.imethod)
cmap = plt.get_cmap(self.cmap)
if self.levels is None:
plt1 = plt.contourf(xi[:,:,0],xi[:,:,1],zi,cmap=cmap)
self.levels = plt1.levels
else:
plt1 = plt.contourf(xi[:,:,0],xi[:,:,1],zi,
levels=self.levels,cmap=cmap)
ax = plt.gca()
ax.set_aspect('equal')
if self.plot_cbar:
self.add_cbar()
if self.xlim is not None:
plt.xlim(self.xlim)
if self.ylim is not None:
plt.ylim(self.ylim)
def plot_aniso_and_interfaces(self,plot_aniso=True):
"""
plot a set of models and up to three interfaces for comparison.
"""
import pek1dplotting as p1dp
if type(self.xyzfiles) == str:
self.xyzfiles = [self.xyzfiles]
if self.subplot_layout == 'vertical':
s1,s2 = len(self.xyzfiles)+1,1
sp_labels = ['y']*(len(self.xyzfiles)-1)+['xy']
ad_labels = 'y'
if not plot_aniso:
s1 -= 1
elif self.subplot_layout == 'horizontal':
s2,s1 = len(self.xyzfiles)+1,1
sp_labels = ['x']*(len(self.xyzfiles))
ad_labels = 'xy'
if not plot_aniso:
s2 -= 1
sp_labels[0] += 'y'
# elif self.subplot_layout == 'grid':
# s1 = int(np.ceil((len(self.xyzfiles)+1)**0.5))
# s2 = s1
# sp_labels = ['','xy','x']
# ad_labels = 'y'
# set self.cmap false for the time being, until all individual plots are done
cbar = self.plot_cbar
self.plot_cbar = False
header_rows,scale = [[d[at] for d in [self.aniso_depth_file_dict,
self.xyzfiles_dict]] for at in ['header_rows','scale']]
self.depth = p1dp.update_scale(self.depth,scale[0])
zmin,zmax = np.amin(self.depth),np.amax(self.depth)
for f in self.xyzfiles:
z = p1dp.update_scale(np.loadtxt(f,skiprows=header_rows[1])[:,2],
scale[1])
if np.amin(z) < zmin:
zmin = np.amin(z)
if np.amax(z) > zmax:
zmax = np.amax(z)
self.levels = np.linspace(zmin,zmax,self.n_levels)
x,y = self.x,self.y
# if self.figsize is None:
# ar = ((float(s1)/float(s2))*((np.amax(y) - np.amin(y))/(np.amax(x) - np.amin(x))))**0.9
# self.figsize=(10,10*ar)
plt.figure(figsize=self.figsize)
plt.subplot(s1,s2,1)
if plot_aniso:
sp = range(2,len(self.xyzfiles)+2)
self.plot_aniso_depth_map()
title = "Magnitude and depth of anisotropy\nfrom 1D anisotropic inversions"
self._update_axis_params(title,ad_labels)
else:
sp = range(1,len(self.xyzfiles)+1)
# plt.gca().set_xticklabels([])
for s,ss in enumerate(sp):
ax = plt.subplot(s1,s2,ss)
# print self.xyzfiles[s]
xyz = np.loadtxt(self.xyzfiles[s],skiprows=header_rows[1])
x,y,z = [xyz[:,i] for i in range(3)]
self.plot_interface(x,y,z,
scale=scale[1])
self.add_xy_data(ss)
self.add_ax_text(ss)
self._update_axis_params(title=self.xyzfile_titles[s],
labels=sp_labels[s])
if 'x' not in sp_labels[s]:
ax.set_xticklabels([])
plt.xlabel('')
if 'y' not in sp_labels[s]:
ax.set_yticklabels([])
plt.ylabel('')
self.plot_cbar = cbar
bottom = self.cbar_ax[1]+self.cbar_ax[3]+0.05
plt.subplots_adjust(wspace=self.wspace,
hspace=self.hspace,
bottom=bottom)
if self.plot_cbar:
self.add_cbar()
def plot_parameter(self,parameter,
ylim=[6,0],
horizon_list = None,
horizon_zscale = 'km',
new_figure = True,
plot_inmodel=True,
additional_data = None):
"""
parameter = 'anisotropy', 'minmax', or 'strike' or list containing
several of these
additional_data - additional data (e.g. resistivity logs)
to plot on the figure. Provide as a list of 2D numpy arrays [depth, param]
"""
import pek1dplotting as p1dp
# self.get_station_distance()
#
# # define some initial locations to put the plots corresponding to distance along profile
# profile_x = (self.station_distances - np.amin(self.station_distances))
#
# # normalise so max distance is at 1
# profile_x /= (np.amax(self.station_distances)-np.amin(self.station_distances))
#
# # make an empty array to put buffered distances
# profile_x_buf = np.zeros_like(profile_x)
#
modelno = self.Model_suite.modelno
#
## print profile_x
px = self.ax_width
dx = self.plot_spacing
nx = len(self.Model_suite.model_list)
profile_x = np.linspace(0.,px*nx+dx*(nx-1),nx) + px/2.
profile_x = np.linspace(0.,1.-2.5*px-dx,nx) + px + dx
# print profile_x,px,dx,nx
#
#
#
# # shift each station along the profile so that they don't overlap each other
# for i in range(len(profile_x)):
# if i == 0:
# profile_x_buf[i] = profile_x[i]
# else:
# profile_x_buf[i] = max(profile_x[i],profile_x_buf[i-1]+px+self.plot_spacing)
# # renormalise so that end station is still within the plot bounds
# profile_x_buf /= np.amax(profile_x_buf)/(self.fig_width-2.*px)
# profile_x_buf += px/2
#
# if new_figure:
# plt.figure(figsize=(len(profile_x),5*self.ax_height))
for i in range(len(self.Model_suite.model_list)):
data_list = []
try:
Model = self.Model_suite.model_list[i]
data_list.append(Model.models[modelno-1])
if plot_inmodel:
if len(self.Model_suite.inmodel_list) > 0:
Inmodel = self.Model_suite.inmodel_list[i]
data_list.append(Inmodel.inmodel)
# ax = plt.subplot(1,len(self.Model_suite.model_list),i+1)
ax = plt.axes([profile_x[i],self.ax_bottom,px,self.ax_height])
axes = []
twin = False
if 'minmax' in parameter:
ls,lw = '-',1
twin = True
for modelvals in data_list:
plt.plot(modelvals[:,3],modelvals[:,1],'0.5',ls=ls,lw=lw)
p, = plt.plot(modelvals[:,2],modelvals[:,1],'k',ls=ls,lw=lw)
plt.xscale('log')
lw*=0.5
ax = self._set_axis_params(ax,'minmax')
axes.append([ax,p])
if 'aniso' in parameter:
ls,lw = '-',1
color = 'k'
if twin:
ax = make_twiny()
color = 'b'
twin = True
for modelvals in data_list:
p, = plt.plot(modelvals[:,3]/modelvals[:,2],modelvals[:,1],
'k-',ls=ls,lw=lw)
plt.xscale('log')
lw *= 0.5
ax = self._set_axis_params(ax,'aniso')
axes.append([ax,p])
if 'strike' in parameter:
color,lw = 'k',1
ls = '-'
if twin:
ax=make_twiny()
color,lw = 'b',0.5
twin = True
for modelvals in data_list:
p, = plt.plot(modelvals[:,4]%180,modelvals[:,1],color,ls=ls,lw=lw)
lw *= 0.5
ax = self._set_axis_params(ax,'strike')
axes.append([ax,p])
if horizon_list is not None:
for h in horizon_list:
elev = ed.get_elevation(Model.x,Model.y,h)
elev = p1dp.update_scale(elev,horizon_zscale)
plt.plot(plt.xlim(),[elev]*2)
if additional_data is not None:
print "plotting additional data"
plt.plot(additional_data[i][:,0],additional_data[i][:,1],lw=0.1)
if i != 0:
ax.set_yticklabels([])
for ax,p in axes:
ax.xaxis.label.set_color(p.get_color())
ax.tick_params(axis='x', colors=p.get_color())
ax.spines['bottom'].set_color(p.get_color())
if i == 0:
for label in ax.get_yticklabels():
label.set_fontproperties(self.font)
label.set_fontsize(self.label_fontsize)
ylab = plt.ylabel('Depth, km')
ylab.set_fontproperties(self.font)
if self.title_type == 'single':
if i == 0:
if type(parameter) == list:
titlestring = ' and '.join([self.titles[p] for p in parameter])
else: titlestring = self.titles[parameter]
title = plt.title(titlestring,ha='left')
title.set_fontproperties(self.font)
title.set_fontsize(self.title_fontsize)
elif self.title_type == 'multiple':
title = plt.title(self.titles[i])
elif self.title_type == 'station':
title = plt.title(self.Model_suite.model_list[i].station)
title.set_fontproperties(self.font)
title.set_fontsize(self.title_fontsize)
except IndexError:
print "station omitted"
def plot_aniso_and_interfaces(self):
"""
plot a set of models and up to three interfaces for comparison.
"""
import pek1dplotting as p1dp
if type(self.xyzfiles) == str:
self.xyzfiles = [self.xyzfiles]
if len(self.xyzfiles) == 1:
s1,s2 = 2,1
sp = [2]
sp_labels = ['y']
ad_labels = 'xy'
elif len(self.xyzfiles) == 2:
s1,s2 = 3,1
sp = [2,3]
sp_labels = ['y','xy']
ad_labels = 'y'
# if more than 3 interfaces provided, plot the first 3
elif len(self.xyzfiles) >= 3:
s1,s2 = 2,2
sp = [2,3,4]
sp_labels = ['','xy','x']
ad_labels = 'y'
# set self.cmap false for the time being, until all individual plots are done
cbar = self.cbar
self.cbar = False
header_rows,scale = [[d[at] for d in [self.aniso_depth_file_dict,
self.xyzfiles_dict]] for at in ['header_rows','scale']]
self.z = p1dp.update_scale(self.z,scale[0])
zmin,zmax = np.amin(self.z),np.amax(self.z)
for f in self.xyzfiles:
z = p1dp.update_scale(np.loadtxt(f,skiprows=header_rows[1])[:,2],
scale[1])
if np.amin(z) < zmin:
zmin = np.amin(z)
if np.amax(z) > zmax:
zmax = np.amax(z)
self.levels = np.linspace(zmin,zmax,self.n_levels)
x,y = self.x,self.y
ar = ((float(s1)/float(s2))*((np.amax(y) - np.amin(y))/(np.amax(x) - np.amin(x))))**0.9
plt.figure(figsize=(self.figsize,self.figsize*ar))
plt.subplot(s1,s2,1)
self.plot_aniso_depth_map()
title = "Magnitude and depth of anisotropy\nfrom 1D anisotropic inversions"
self._update_axis_params(title,ad_labels)
plt.gca().set_xticklabels([])
for s,ss in enumerate(sp):
ax = plt.subplot(s1,s2,ss)
print self.xyzfiles[s]
xyz = np.loadtxt(self.xyzfiles[s],skiprows=header_rows[1])
x,y,z = [xyz[:,i] for i in range(3)]
self.plot_interface(x,y,z,
scale=scale[1])
self._update_axis_params(title=self.xyzfile_titles[s],
labels=sp_labels[s])
if 'x' not in sp_labels[s]:
ax.set_xticklabels([])
plt.xlabel('')
if 'y' not in sp_labels[s]:
ax.set_yticklabels([])
plt.ylabel('')
self.cbar = cbar
plt.subplots_adjust(wspace=0.0)
ax = plt.axes([0.88,0.1,0.08,0.8])
ax.set_visible(False)
if self.cbar:
cbar = plt.colorbar(fraction=0.8)
cbar.set_label("Depth, km")
cticks = range(int(self.levels[0]),int(self.levels[-1]+1))
cbar.set_ticks(cticks)
def plot_parameter(self,
parameter,
ylim=[6, 0],
horizon_list=None,
horizon_zscale='km',
new_figure=True,
plot_inmodel=True,
additional_data=None):
"""
parameter = 'anisotropy', 'minmax', or 'strike' or list containing
several of these
additional_data - additional data (e.g. resistivity logs)
to plot on the figure. Provide as a list of 2D numpy arrays [depth, param]
"""
import pek1dplotting as p1dp
# self.get_station_distance()
#
# # define some initial locations to put the plots corresponding to distance along profile
# profile_x = (self.station_distances - np.amin(self.station_distances))
#
# # normalise so max distance is at 1
# profile_x /= (np.amax(self.station_distances)-np.amin(self.station_distances))
#
# # make an empty array to put buffered distances
# profile_x_buf = np.zeros_like(profile_x)
#
modelno = self.Model_suite.modelno
#
## print profile_x
px = self.ax_width
dx = self.plot_spacing
nx = len(self.Model_suite.model_list)
profile_x = np.linspace(0., px * nx + dx * (nx - 1), nx) + px / 2.
profile_x = np.linspace(0., 1. - 2.5 * px - dx, nx) + px + dx
# print profile_x,px,dx,nx
#
#
#
# # shift each station along the profile so that they don't overlap each other
# for i in range(len(profile_x)):
# if i == 0:
# profile_x_buf[i] = profile_x[i]
# else:
# profile_x_buf[i] = max(profile_x[i],profile_x_buf[i-1]+px+self.plot_spacing)
# # renormalise so that end station is still within the plot bounds
# profile_x_buf /= np.amax(profile_x_buf)/(self.fig_width-2.*px)
# profile_x_buf += px/2
#
# if new_figure:
# plt.figure(figsize=(len(profile_x),5*self.ax_height))
for i in range(len(self.Model_suite.model_list)):
data_list = []
try:
Model = self.Model_suite.model_list[i]
data_list.append(Model.models[modelno - 1])
if plot_inmodel:
if len(self.Model_suite.inmodel_list) > 0:
Inmodel = self.Model_suite.inmodel_list[i]
data_list.append(Inmodel.inmodel)
# ax = plt.subplot(1,len(self.Model_suite.model_list),i+1)
ax = plt.axes(
[profile_x[i], self.ax_bottom, px, self.ax_height])
axes = []
twin = False
if 'minmax' in parameter:
ls, lw = '-', 1
twin = True
for modelvals in data_list:
plt.plot(modelvals[:, 3],
modelvals[:, 1],
'0.5',
ls=ls,
lw=lw)
p, = plt.plot(modelvals[:, 2],
modelvals[:, 1],
'k',
ls=ls,
lw=lw)
plt.xscale('log')
lw *= 0.5
ax = self._set_axis_params(ax, 'minmax')
axes.append([ax, p])
if 'aniso' in parameter:
ls, lw = '-', 1
color = 'k'
if twin:
ax = make_twiny()
color = 'b'
twin = True
for modelvals in data_list:
p, = plt.plot(modelvals[:, 3] / modelvals[:, 2],
modelvals[:, 1],
'k-',
ls=ls,
lw=lw)
plt.xscale('log')
lw *= 0.5
ax = self._set_axis_params(ax, 'aniso')
axes.append([ax, p])
if 'strike' in parameter:
color, lw = 'k', 1
ls = '-'
if twin:
ax = make_twiny()
color, lw = 'b', 0.5
twin = True
for modelvals in data_list:
p, = plt.plot(modelvals[:, 4] % 180,
modelvals[:, 1],
color,
ls=ls,
lw=lw)
lw *= 0.5
ax = self._set_axis_params(ax, 'strike')
axes.append([ax, p])
if horizon_list is not None:
for h in horizon_list:
elev = ed.get_elevation(Model.x, Model.y, h)
elev = p1dp.update_scale(elev, horizon_zscale)
plt.plot(plt.xlim(), [elev] * 2)
if additional_data is not None:
print "plotting additional data"
plt.plot(additional_data[i][:, 0],
additional_data[i][:, 1],
lw=0.1)
if i != 0:
ax.set_yticklabels([])
for ax, p in axes:
ax.xaxis.label.set_color(p.get_color())
ax.tick_params(axis='x', colors=p.get_color())
ax.spines['bottom'].set_color(p.get_color())
if i == 0:
for label in ax.get_yticklabels():
label.set_fontproperties(self.font)
label.set_fontsize(self.label_fontsize)
ylab = plt.ylabel('Depth, km')
ylab.set_fontproperties(self.font)
if self.title_type == 'single':
if i == 0:
if type(parameter) == list:
titlestring = ' and '.join(
[self.titles[p] for p in parameter])
else:
titlestring = self.titles[parameter]
title = plt.title(titlestring, ha='left')
title.set_fontproperties(self.font)
title.set_fontsize(self.title_fontsize)
elif self.title_type == 'multiple':
title = plt.title(self.titles[i])
elif self.title_type == 'station':
title = plt.title(
self.Model_suite.model_list[i].station)
title.set_fontproperties(self.font)
title.set_fontsize(self.title_fontsize)
except IndexError:
print "station omitted"
def plot_aniso_and_interfaces(self):
"""
plot a set of models and up to three interfaces for comparison.
"""
import pek1dplotting as p1dp
if type(self.xyzfiles) == str:
self.xyzfiles = [self.xyzfiles]
if len(self.xyzfiles) == 1:
s1, s2 = 2, 1
sp = [2]
sp_labels = ['y']
ad_labels = 'xy'
elif len(self.xyzfiles) == 2:
s1, s2 = 3, 1
sp = [2, 3]
sp_labels = ['y', 'xy']
ad_labels = 'y'
# if more than 3 interfaces provided, plot the first 3
elif len(self.xyzfiles) >= 3:
s1, s2 = 2, 2
sp = [2, 3, 4]
sp_labels = ['', 'xy', 'x']
ad_labels = 'y'
# set self.cmap false for the time being, until all individual plots are done
cbar = self.cbar
self.cbar = False
header_rows, scale = [[
d[at] for d in [self.aniso_depth_file_dict, self.xyzfiles_dict]
] for at in ['header_rows', 'scale']]
self.z = p1dp.update_scale(self.z, scale[0])
zmin, zmax = np.amin(self.z), np.amax(self.z)
for f in self.xyzfiles:
z = p1dp.update_scale(
np.loadtxt(f, skiprows=header_rows[1])[:, 2], scale[1])
if np.amin(z) < zmin:
zmin = np.amin(z)
if np.amax(z) > zmax:
zmax = np.amax(z)
self.levels = np.linspace(zmin, zmax, self.n_levels)
x, y = self.x, self.y
ar = ((float(s1) / float(s2)) * ((np.amax(y) - np.amin(y)) /
(np.amax(x) - np.amin(x))))**0.9
plt.figure(figsize=(self.figsize, self.figsize * ar))
plt.subplot(s1, s2, 1)
self.plot_aniso_depth_map()
title = "Magnitude and depth of anisotropy\nfrom 1D anisotropic inversions"
self._update_axis_params(title, ad_labels)
plt.gca().set_xticklabels([])
for s, ss in enumerate(sp):
ax = plt.subplot(s1, s2, ss)
print self.xyzfiles[s]
xyz = np.loadtxt(self.xyzfiles[s], skiprows=header_rows[1])
x, y, z = [xyz[:, i] for i in range(3)]
self.plot_interface(x, y, z, scale=scale[1])
self._update_axis_params(title=self.xyzfile_titles[s],
labels=sp_labels[s])
if 'x' not in sp_labels[s]:
ax.set_xticklabels([])
plt.xlabel('')
if 'y' not in sp_labels[s]:
ax.set_yticklabels([])
plt.ylabel('')
self.cbar = cbar
plt.subplots_adjust(wspace=0.0)
ax = plt.axes([0.88, 0.1, 0.08, 0.8])
ax.set_visible(False)
if self.cbar:
cbar = plt.colorbar(fraction=0.8)
cbar.set_label("Depth, km")
cticks = range(int(self.levels[0]), int(self.levels[-1] + 1))
cbar.set_ticks(cticks)
def plot_aniso_and_interfaces(self, plot_aniso=True):
"""
plot a set of models and up to three interfaces for comparison.
"""
import pek1dplotting as p1dp
if type(self.xyzfiles) == str:
self.xyzfiles = [self.xyzfiles]
if self.subplot_layout == 'vertical':
s1, s2 = len(self.xyzfiles) + 1, 1
sp_labels = ['y'] * (len(self.xyzfiles) - 1) + ['xy']
ad_labels = 'y'
if not plot_aniso:
s1 -= 1
elif self.subplot_layout == 'horizontal':
s2, s1 = len(self.xyzfiles) + 1, 1
sp_labels = ['x'] * (len(self.xyzfiles))
ad_labels = 'xy'
if not plot_aniso:
s2 -= 1
sp_labels[0] += 'y'
# elif self.subplot_layout == 'grid':
# s1 = int(np.ceil((len(self.xyzfiles)+1)**0.5))
# s2 = s1
# sp_labels = ['','xy','x']
# ad_labels = 'y'
# set self.cmap false for the time being, until all individual plots are done
cbar = self.plot_cbar
self.plot_cbar = False
header_rows, scale = [[
d[at] for d in [self.aniso_depth_file_dict, self.xyzfiles_dict]
] for at in ['header_rows', 'scale']]
self.depth = p1dp.update_scale(self.depth, scale[0])
zmin, zmax = np.amin(self.depth), np.amax(self.depth)
for f in self.xyzfiles:
z = p1dp.update_scale(
np.loadtxt(f, skiprows=header_rows[1])[:, 2], scale[1])
if np.amin(z) < zmin:
zmin = np.amin(z)
if np.amax(z) > zmax:
zmax = np.amax(z)
self.levels = np.linspace(zmin, zmax, self.n_levels)
x, y = self.x, self.y
# if self.figsize is None:
# ar = ((float(s1)/float(s2))*((np.amax(y) - np.amin(y))/(np.amax(x) - np.amin(x))))**0.9
# self.figsize=(10,10*ar)
plt.figure(figsize=self.figsize)
plt.subplot(s1, s2, 1)
if plot_aniso:
sp = range(2, len(self.xyzfiles) + 2)
self.plot_aniso_depth_map()
title = "Magnitude and depth of anisotropy\nfrom 1D anisotropic inversions"
self._update_axis_params(title, ad_labels)
else:
sp = range(1, len(self.xyzfiles) + 1)
# plt.gca().set_xticklabels([])
for s, ss in enumerate(sp):
ax = plt.subplot(s1, s2, ss)
# print self.xyzfiles[s]
xyz = np.loadtxt(self.xyzfiles[s], skiprows=header_rows[1])
x, y, z = [xyz[:, i] for i in range(3)]
self.plot_interface(x, y, z, scale=scale[1])
self.add_xy_data(ss)
self.add_ax_text(ss)
self._update_axis_params(title=self.xyzfile_titles[s],
labels=sp_labels[s])
if 'x' not in sp_labels[s]:
ax.set_xticklabels([])
plt.xlabel('')
if 'y' not in sp_labels[s]:
ax.set_yticklabels([])
plt.ylabel('')
self.plot_cbar = cbar
bottom = self.cbar_ax[1] + self.cbar_ax[3] + 0.05
plt.subplots_adjust(wspace=self.wspace,
hspace=self.hspace,
bottom=bottom)
if self.plot_cbar:
self.add_cbar()