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geodeticplot.py
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geodeticplot.py
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'''
Class that plots the class verticalfault, gps and insar in 3D.
Written by R. Jolivet and Z. Duputel, April 2013.
Edited by T. Shreve, May 2019. Commented out lines 386, 391, 460, 485, 1121, 1131 because plotting fault patches was incorrect...
Added plotting option for pressure sources
July 2019: R Jolivet replaced basemap by cartopy.
Sept 2024: JD Dianala, some cleanup...
'''
# Numerics
import numpy as np
import scipy.interpolate as sciint
import scipy.ndimage as sciim
# Geography
import pyproj as pp
# Os
import os, copy, sys
# Matplotlib
import matplotlib
import matplotlib.pyplot as plt
import matplotlib.colors as colors
import matplotlib.cm as cmx
import matplotlib.collections as colls
from matplotlib.patches import PathPatch
import matplotlib.patches as patches
import matplotlib.transforms as transforms
# Cartopy
import cartopy
import cartopy.crs as ccrs
import cartopy.feature as cfeature
from cartopy.io import PostprocessedRasterSource, LocatedImage
from cartopy.io.srtm import SRTM1Source, SRTM3Source
from cartopy.io import srtm
# mpl_toolkits
from mpl_toolkits.mplot3d import Axes3D
import mpl_toolkits.mplot3d.art3d as art3d
# CSI
from .SourceInv import SourceInv
from .gebco import GebcoSource
class geodeticplot(object):
'''
A class to create plots of geodetic data with faults. Geographic representation is based on cartopy.
Two figures are created. One with a map and the other with a 3D view of the fault.
Args:
* lonmin : left-boundary of the map
* lonmax : Right-boundary of the map
* latmin : Bottom-boundary of the map
* latmax : Top of the map
Kwargs:
* figure : Figure number
* pbaspect : ??
* resolution : Resolution of the mapped coastlines, lakes, rivers, etc. See cartopy for details
* figsize : tuple of the size of the 2 figures
Returns:
* None
'''
def __init__(self,lonmin, latmin, lonmax, latmax,
figure=None, pbaspect=None,resolution='auto',
figsize=[None,None], Map=True, Fault=True):
# Save
self.lonmin = lonmin
self.lonmax = lonmax
self.latmin = latmin
self.latmax = latmax
# Lon0 lat0
self.lon0 = lonmin + (lonmax-lonmin)/2.
self.lat0 = latmin + (latmax-latmin)/2.
# Projection
self.projection = ccrs.PlateCarree()
self.resolution = resolution
# Open a figure
if Fault:
figFaille = plt.figure(figure, figsize=figsize[0])
faille = figFaille.add_subplot(111, projection='3d')
# Chec figure number
if figure == None:
fignums = plt.get_fignums()
if len(fignums)>0:
nextFig = np.max(plt.get_fignums())+1
else:
nextFig = 1
else:
nextFig=figure+1
# Open another one
if Map:
figCarte = plt.figure(nextFig, figsize=figsize[1])
carte = figCarte.add_subplot(111, projection=self.projection)
carte.set_extent([self.lonmin, self.lonmax, self.latmin, self.latmax], crs=self.projection)
# Gridlines (there is something wrong with the gridlines class...)
gl = carte.gridlines(crs=self.projection, draw_labels=True, alpha=0.5, zorder=0)
gl.xlabel_style = {'size': 'large', 'color': 'k', 'weight': 'bold'}
gl.ylabel_style = {'size': 'large', 'color': 'k', 'weight': 'bold'}
self.cartegl = gl
#carte.set_xticks(carte.get_xticks())
#carte.set_yticks(carte.get_yticks())
#carte.tick_params(axis='both', which='major', labelsize='large')
# Set the axes
if Fault:
faille.set_xlabel('Longitude')
faille.set_ylabel('Latitude')
faille.set_zlabel('Depth (km)')
# store plots
if Fault:
self.faille = faille
self.figFaille = figFaille
else:
self.faille = None
self.figFaille = None
if Map:
self.carte = carte
self.figCarte = figCarte
else:
self.carte = None
self.figCarte = None
# All done
return
def drawScaleBar(self, scalebar, csiobj, lonlat=None, zorder=0, textoffset=10., linewidth=1, color='k', fontdict=None):
'''
Draw a {scalebar} km bar for scale at {lonlat}.
'''
# Check
assert type(scalebar) == float, 'scalebar should be float: {}'.format(type(scalebar))
# Chose where to put the bar
if lonlat is not None:
lonc, latc = lonlat
else:
lonc = self.lonmin + (self.lonmax-self.lonmin)/10.
latc = self.latmin + (self.latmax-self.latmin)/10.
# Convert to xy and build the end points
xc,yc = csiobj.ll2xy(lonc,latc)
# End points
x1 = xc-scalebar/2.
x2 = xc+scalebar/2.
# Convert
lon1,lat1 = csiobj.xy2ll(x1,yc)
lon2,lat2 = csiobj.xy2ll(x2,yc)
lonc,latc = csiobj.xy2ll(xc,yc+textoffset)
# Show me
self.carte.plot([lon1, lon2], [lat1,lat2], '-', color=color,
linewidth=linewidth, zorder=zorder)
self.carte.text(lonc,latc,'{} km'.format(scalebar), fontdict=fontdict,
horizontalalignment='center',zorder=zorder)
# All done
return
def close(self, fig2close=['map', 'fault']):
'''
Closes all the figures
Kwargs:
* fig2close : a list of 'map' and 'fault'. By default, closes both figures
Returns:
* None
'''
# Check
if type(fig2close) is not list:
fig2close = [fig2close]
# Figure 1
if 'fault' in fig2close:
plt.close(self.figFaille)
if 'map' in fig2close:
plt.close(self.figCarte)
# All done
return
def show(self, mapaxis=None, triDaxis=None, showFig=['fault', 'map'], fitOnBox=False):
'''
Show to screen
Kwargs:
* mapaxis : Specify the axis type for the map (see matplotlib)
* triDaxis : Specify the axis type for the 3D projection (see mpl_toolkits)
* showFig : List of plots to show on screen ('fault' and/or 'map')
* fitOnBox : If True, fits the horizontal axis to the one asked at initialization
Returns:
* None
'''
# Change axis of the map
if mapaxis != None and self.carte is not None:
self.carte.axis(mapaxis)
# Change the axis of the 3d projection
if triDaxis != None and self.faille is not None:
self.faille.axis(triDaxis)
# Fits the horizontal axis to the asked values
if fitOnBox:
if self.lonmin>180.:
self.lonmin -= 360.
if self.lonmax>180.:
self.lonmax -= 360.
if self.carte is not None: self.carte.set_extent([self.lonmin, self.lonmax, self.latmin, self.latmax])
if self.faille is not None:
self.faille.set_xlim(self.carte.get_xlim())
self.faille.set_ylim(self.carte.get_ylim())
# Delete figures
if 'map' not in showFig:
plt.close(self.figCarte)
if 'fault' not in showFig:
plt.close(self.figFaille)
# Show
plt.show()
# All done
return
def savefig(self, prefix, mapaxis='equal', ftype='pdf', dpi=None, bbox_inches=None,
triDaxis='auto', saveFig=['fault', 'map']):
'''
Save to file.
Args:
* prefix : Prefix used for filenames
Kwargs:
* mapaxis : 'equal' or 'auto'
* ftype : 'eps', 'pdf', 'png'
* dpi : whatever dot-per-inche you'd like
* bbox_inches : pdf details
* triDaxis : 3D axis scaling
* saveFig : Which figures to save
Returns:
* None
'''
# Change axis of the map
if mapaxis is not None and self.carte is not None:
self.carte.axis(mapaxis)
# Change the axis of the 3d proj
if triDaxis is not None and self.faille is not None:
self.faille.axis(triDaxis)
# Save
if (ftype == 'png') and (dpi is not None) and (bbox_inches is not None):
if 'fault' in saveFig and self.faille is not None:
self.figFaille.savefig('%s_fault.png' % (prefix),
dpi=dpi, bbox_inches=bbox_inches)
if 'map' in saveFig and self.carte is not None:
self.figCarte.savefig('%s_map.png' % (prefix),
dpi=dpi, bbox_inches=bbox_inches)
else:
if 'fault' in saveFig and self.faille is not None:
self.figFaille.savefig('{}_fault.{}'.format(prefix, ftype))
if 'map' in saveFig and self.carte is not None:
self.figCarte.savefig('{}_map.{}'.format(prefix, ftype))
# All done
return
def addColorbar(self, values, scalarMap, cbaxis, cborientation, figure, cblabel=''):
'''
Adds a colorbar for a given {scalarMap} to the chosen {figure}
Args:
* values : Values used fr the plot
* scalaMap : Scalar Mappable from matplotlib
* cbaxis : [Left, Bottom, Width, Height] shape of the axis in which the colorbar is plot
* cborientation : 'horizontal' or 'vertical'
* figure : Figure object
Kwargs:
* cblabel : Label the colorbar
'''
scalarMap.set_array(values)
cax = figure.add_axes(cbaxis)
cb = plt.colorbar(scalarMap, cax=cax, orientation=cborientation)
cb.set_label(label=cblabel, weight='bold')
# Save this axis
self.cbax = cb
# All done
return
def clf(self):
'''
Clears the figures
Returns:
* None
'''
self.figFaille.clf()
self.figCarte.clf()
return
def titlemap(self, titre, y=1.1):
'''
Sets the title of the map.
Args:
* titre : title of the map
Returns:
* None
'''
self.carte.set_title(titre, y=y)
# All done
return
def titlefault(self, titre):
'''
Sets the title of the fault model.
Args:
* titre : title of the fault
Returns:
* None
'''
self.faille.set_title(titre, title=1.08)
# All done
return
def setzaxis(self, depth, zticklabels=None):
'''
Set the z-axis.
Args:
* depth : Maximum depth.
Kwargs:
* ztickslabel : which labels to use
Returns:
* None
'''
if self.faille is None:
print('No fault figure work on')
return
self.faille.set_zlim3d([-1.0*(depth+5), 0])
if zticklabels is None:
zticks = []
zticklabels = []
for z in np.linspace(0,depth,5):
zticks.append(-1.0*z)
zticklabels.append(z)
else:
zticks = []
for z in zticklabels:
zticks.append(-1.0*z)
self.faille.set_zticks(zticks)
self.faille.set_zticklabels(zticklabels)
# All done
return
def set_view(self, elevation, azimuth, shape=(1., 1., 1.)):
'''
Sets azimuth and elevation angle for the 3D plot.
Args:
* elevation : Point of view elevation angle
* azimuth : Point of view azimuth angle
Kwargs:
* shape : [scale_x, scale_y, scale_z] (0-1 each)
Returns:
* None
'''
# Check
if self.faille is None:
print('No Fault figure to work on')
return
# Set angles
self.faille.view_init(elevation,azimuth)
# Thank you stackoverflow
self.faille.get_proj = lambda: np.dot(Axes3D.get_proj(self.faille),
np.diag([shape[0], shape[1], shape[2], 1]))
#all done
return
def equalize3dAspect(self):
"""
Make the 3D axes have equal aspect. Not working yet (maybe never).
Returns:
* None
"""
# Check
if self.faille is None:
print('No Fault figure to work on')
return
xlim = self.faille.get_xlim3d()
ylim = self.faille.get_ylim3d()
zlim = self.faille.get_zlim3d()
x_range = xlim[1] - xlim[0]
y_range = ylim[1] - ylim[0]
z_range = zlim[1] - zlim[0]
x0 = 0.5 * (xlim[1] + xlim[0])
y0 = 0.5 * (ylim[1] + ylim[0])
z0 = 0.5 * (zlim[1] + zlim[0])
max_range = 0.5 * np.array([x_range, y_range, z_range]).max()
self.faille.set_xlim3d([x0-max_range, x0+max_range])
self.faille.set_ylim3d([y0-max_range, y0+max_range])
self.faille.set_zlim3d(zlim)
self.figFaille.set_size_inches((14,6))
return
def set_xymap(self, xlim, ylim):
'''
Sets the xlim and ylim on the map.
Args:
* xlim : tuple of the ongitude limits
* ylim : tuple of the latitude limits
Returns:
* None
'''
# check
if self.carte is None: return
self.carte.set_extent([xlim[0], xlim[1], ylim[0], ylim[1]])
# All done
return
def shadedTopography(self, source='gebco', smooth=3, azimuth=140, altitude=45,
alpha=1., zorder=1, cmap='Greys', norm=None,
gebcotype='sub_ice_topo', gebcoyear=2022,
srtmversion=1):
'''
if source == 'gebco':
Plots the shaded topography Gebco.
Needs user to download Gebco data and store that in ~/.local/share/cartopy/GEBCO
if source == 'srtm':
Plots the shaded topography from SRTM. Thanks to Thomas Lecocq.
Needs user to download the SRTM tiles and unzip them beforehand (until the day cartopy guru's
manage to input a login and password to access directly SRTM data).
Tiles must be stored at ~/.local/share/cartopy/SRTM/SRTMGL1 or in the directory given
by the environment variable CARTOPY_DATA_DIR (which must be set before importing cartopy)
Args:
* smooth : Smoothing factor in pixels of SRTM data (3 is nice)
* azimuth : Azimuth of the sun
* elevation : Sun elevation
* alpha : Alpha
* srtmversion : 1 or 3
* gebcotype : 'sub_ice_topo'
* gebcoyear : 2022
Returns:
* None
'''
# check
if self.carte is None: return
# Define toposhading (thanks Thomas Lecocq and the Cartopy website)
def shade(located_elevations):
"""
Given an array of elevations in a LocatedImage, add a relief (shadows) to
give a realistic 3d appearance.
"""
new_img = srtm.add_shading(sciim.gaussian_filter(located_elevations.image, smooth),
azimuth=azimuth, altitude=altitude)
return LocatedImage(new_img, located_elevations.extent)
if source == 'srtm':
# Version
if srtmversion == 1:
source = SRTM1Source(max_nx=8, max_ny=8)
elif srtmversion == 3:
source = SRTM3Source(max_nx=8, max_ny=8)
elif source == 'gebco':
# Get it
source = GebcoSource(dtype=gebcotype, year=gebcoyear)
# Build the raster
if smooth>0.:
shaded_topo = PostprocessedRasterSource(source, shade)
else:
shaded_topo = source
# Add the raster
self.carte.add_raster(shaded_topo, cmap=cmap, alpha=alpha, zorder=zorder, clim=norm)
# All done
return
def drawCoastlines(self, color='k', linewidth=1.0, linestyle='solid',
resolution='10m', landcolor='lightgrey', seacolor=None, drawMapScale=None,
parallels=None, meridians=None, drawOnFault=False,
alpha=0.5, zorder=1):
'''
Draws the coast lines in the desired area.
Kwargs:
* color : Color of lines
* linewidth : Width of lines
* linestyle : Style of lines
* resolution : Resolution of the coastline. Can be 10m, 50m or 110m
* drawLand : Fill the continents (True/False)
* drawMapScale : Draw a map scale (None or length in km)
* parallels : If int, number of parallels. If float, spacing in degrees between parallels. If np.array, array of parallels
* meridians : Number of meridians to draw or array of meridians
* drawOnFault : Draw on 3D fault as well
* zorder : matplotlib order of plotting
Returns:
* None
'''
# check
if self.carte is None: return
# Scale bar
if drawMapScale is not None:
self.drawScaleBar(drawMapScale, lonlat=None)
# Ocean color (not really nice since this colors everything in the background)
if seacolor=='image':
self.carte.stock_img()
else:
if seacolor is not None:
self.carte.add_feature(cfeature.NaturalEarthFeature('physical',
'ocean',
scale=resolution,
edgecolor=color,
facecolor=seacolor,
zorder=np.max([zorder-1,0])))
# coastlines in cartopy are multipolygon objects. Polygon has exterior, which has xy
self.coastlines = cfeature.NaturalEarthFeature('physical', 'land', scale=resolution,
edgecolor=color,
facecolor=landcolor,
linewidth=linewidth,
linestyle=linestyle,
zorder=zorder, alpha=alpha)
# Draw and get the line object
self.carte.add_feature(self.coastlines)
## MapScale
if drawMapScale is not None:
assert False, 'Cannot draw a map scale yet. To be implemented...'
# Parallels
if parallels is not None:
lmin,lmax = self.latmin, self.latmax
if type(parallels) is int:
parallels = np.linspace(lmin, lmax, parallels+1)
elif type(parallels) is float:
parallels = np.arange(lmin, lmax+parallels, parallels)
parallels = np.round(parallels, decimals=2)
# Meridians
if meridians is not None:
lmin,lmax = self.lonmin, self.lonmax
if type(meridians) is int:
meridians = np.linspace(lmin, lmax, meridians+1)
elif type(meridians) is float:
meridians = np.arange(lmin, lmax+meridians, meridians)
meridians = np.round(meridians, decimals=2)
# Draw them
if meridians is not None and parallels is not None:
gl = self.carte.gridlines(color='gray', xlocs=meridians, ylocs=parallels, linestyle=(0, (1, 1)))
# All done
return
def drawCountries(self, resolution='10m', linewidth=1., edgecolor='gray', facecolor='lightgray', alpha=1., zorder=0):
'''
See the cartopy manual for options
'''
# Check
if self.carte is not None:
self.countries = cfeature.NaturalEarthFeature(scale=resolution, category='cultural', name='admin_0_countries',
linewidth=linewidth, edgecolor=edgecolor, facecolor=facecolor,
alpha=alpha, zorder=zorder)
self.carte.add_feature(self.countries)
# All done
return
def faulttrace(self, fault, color='r', add=False, discretized=False, linewidth=1, zorder=1):
'''
Plots a fault trace.
Args:
* fault : Fault instance
Kwargs:
* color : Color of the fault.
* add : plot the faults in fault.addfaults
* discretized : Plot the discretized fault
* zorder : matplotlib order of plotting
Returns:
* None
'''
# discretized?
if discretized:
lon = fault.loni
lat = fault.lati
else:
lon = fault.lon
lat = fault.lat
# Plot the added faults before
if add:
for f in fault.addfaults:
#f[0][f[0]<0.] += 360.
self.carte.plot(f[0], f[1], '-k', zorder=zorder, linewidth=linewidth)
for f in fault.addfaults:
if self.faille_flag:
self.faille.plot(f[0], f[1], '-k', linewidth=linewidth)
# Plot the surface trace
#lon[lon<0] += 360.
#lon[np.logical_or(lon<self.lonmin, lon>self.lonmax)] += 360.
if hasattr(fault, 'color'): color = fault.color
if hasattr(fault, 'linewidth'): linewidth = fault.linewidth
if self.faille is not None: self.faille.plot(lon, lat, '-{}'.format(color), linewidth=linewidth)
if self.carte is not None: self.carte.plot(lon, lat, '-{}'.format(color), zorder=zorder,
linewidth=linewidth)
# All done
return
def faultpatches(self, fault, slip='strikeslip', norm=None, colorbar=True,
cbaxis=[0.1, 0.2, 0.1, 0.02], cborientation='horizontal', cblabel='',
plot_on_2d=False, revmap=False, linewidth=1.0, cmap='jet', offset=None,
alpha=1.0, factor=1.0, zorder=3, edgecolor='slip', colorscale='normal'):
'''
Plot the fualt patches
Args:
* fault : Fault instance
Kwargs:
* slip : Can be 'strikeslip', 'dipslip', 'tensile', 'total' or 'coupling'
* norm : Limits for the colorbar.
* colorbar : if True, plots a colorbar.
* cbaxis : [Left, Bottom, Width, Height] of the colorbar axis
* cborientation : 'horizontal' (default)
* cblabel : Write something next to the colorbar.
* plot_on_2d : if True, adds the patches on the map.
* revmap : Revert the colormap
* linewidth : Width of the edges of the patches
* cmap : Colormap (any of the matplotlib ones)
* factor : scale factor for fault slip values
* zorder : matplotlib order of plotting
* edgecolor : either a color or 'slip'
* colorscale : 'normal' or 'log'
Returns:
* None
'''
# Get slip
if slip in ('strikeslip'):
slip = fault.slip[:,0].copy()
elif slip in ('dipslip'):
slip = fault.slip[:,1].copy()
elif slip in ('tensile'):
slip = fault.slip[:,2].copy()
elif slip in ('total'):
slip = np.sqrt(fault.slip[:,0]**2 + fault.slip[:,1]**2 + fault.slip[:,2]**2)
elif slip in ('coupling'):
slip = fault.coupling.copy()
else:
print ("Unknown slip direction")
return
slip *= factor
# norm
if norm == None:
vmin=slip.min()
vmax=slip.max()
else:
vmin=norm[0]
vmax=norm[1]
# Potential offset of the fault wrt. its true position
if offset is None:
offset = [0., 0., 0.]
# set z axis
try:
self.setzaxis(fault.depth+5., zticklabels=fault.z_patches)
except:
print('Warning: Depth cannot be determined automatically. Please set z-axis limit manually')
# set color business
if revmap:
cmap = plt.get_cmap(cmap)
else:
cmap = plt.get_cmap(cmap)
if colorscale in ('normal', 'n'):
cNorm = colors.Normalize(vmin=vmin, vmax=vmax)
elif colorscale in ('log', 'l', 'lognormal'):
cNorm = colors.LogNorm(vmin=vmin, vmax=vmax)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
# fault figure
if self.faille is not None:
Xs = np.array([])
Ys = np.array([])
for p in range(len(fault.patch)):
ncorners = len(fault.patchll[0])
x = []
y = []
z = []
for i in range(ncorners):
x.append(fault.patchll[p][i][0]+offset[0])
y.append(fault.patchll[p][i][1]+offset[1])
z.append(-1.0*fault.patchll[p][i][2]+offset[2])
verts = []
for xi,yi,zi in zip(x,y,z):
#if xi<0.: xi += 360.
verts.append((xi,yi,zi))
rect = art3d.Poly3DCollection([verts])
rect.set_facecolor(scalarMap.to_rgba(slip[p]))
if edgecolor=='slip':
rect.set_edgecolors(scalarMap.to_rgba(slip[p]))
else:
rect.set_edgecolors(edgecolor)
if alpha<1.0:
rect.set_alpha(alpha)
rect.set_linewidth(linewidth)
self.faille.add_collection3d(rect)
# Reset x- and y-lims
self.faille.set_xlim([self.lonmin,self.lonmax])
self.faille.set_ylim([self.latmin,self.latmax])
# If 2d.
if plot_on_2d and self.carte is not None:
for p, patch in zip(range(len(fault.patchll)), fault.patchll):
x = []
y = []
for i in range(ncorners):
x.append(patch[i][0]+offset[0])
y.append(patch[i][1]+offset[1])
verts = []
for xi,yi in zip(x,y):
#if xi<0.: xi += 360.
verts.append((xi,yi))
rect = colls.PolyCollection([verts])
rect.set_facecolor(scalarMap.to_rgba(slip[p]))
rect.set_edgecolors('gray')
rect.set_linewidth(linewidth)
if alpha<1.0:
rect.set_alpha(alpha)
rect.set_zorder(zorder)
self.carte.add_collection(rect)
# put up a colorbar
if colorbar:
if self.faille is not None: self.addColorbar(slip, scalarMap, cbaxis, cborientation, self.figFaille, cblabel=cblabel)
if plot_on_2d and self.carte is not None:
self.addColorbar(slip, scalarMap, cbaxis, cborientation,self.figCarte, cblabel=cblabel)
# All done
return
def pressuresource(self, fault, delta='pressure', norm=None, colorbar=True,
cbaxis=[0.1, 0.2, 0.1, 0.02], cborientation='horizontal', cblabel='',
revmap=False, linewidth=1.0, cmap='jet',
alpha=1.0, factor=1.0, zorder=3, plot_on_2d=False):
'''
Plots a pressure source.
Args:
* fault : Pressure source instance
Kwargs:
* delta : Can be 'pressure' or 'volume'
* norm : Limits for the colorbar.
* colorbar : if True, plots a colorbar.
* revmap : Reverts the colormap
* linewidth : width of the edhe of the source
* cmap : matplotlib colormap
* plot_on_2d : if True, adds the patches on the map.
* factor : scale factor for pressure values
* zorder : matplotlib plotting order
Returns:
* None
'''
# Get slip
if delta == 'pressure':
delta = fault.deltapressure
elif delta == 'volume':
delta = fault.deltavolume
else:
print ("Unknown slip direction")
return
delta *= factor
# norm
if norm == None:
vmin=0
vmax=delta
else:
vmin=norm[0]
vmax=norm[1]
# set z axis
self.setzaxis(fault.ellipshape['z0']+5., zticklabels=None)
# set color business
if revmap:
cmap = plt.get_cmap(cmap)
else:
cmap = plt.get_cmap(cmap)
cNorm = colors.Normalize(vmin=vmin, vmax=vmax)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
Xs = np.array([])
Ys = np.array([])
#plot 3-d spheroid here
#Radii -- assuming prolate spheroid (z-axis is the semi-major axis when dip = 90, y-axis is semi-major axis when strike = 0), in km
rx, ry, rz = fault.ellipshape['a']*fault.ellipshape['A']/1000.,fault.ellipshape['a']/1000.,fault.ellipshape['a']*fault.ellipshape['A']/1000.
#All spherical angles
u = np.linspace(0, 2 * np.pi, 100)
v = np.linspace(0, np.pi, 100 )
#xyz coordinates for spherical angles
ex = rx * np.outer(np.cos(u), np.sin(v))
ey = ry * np.outer(np.sin(u), np.sin(v))
ez = rz * np.outer(np.ones_like(u), np.cos(v))
#strike and dip in radians, multiplied by -1 because we want clockwise rotations
strike = -1*fault.ellipshape['strike']* np.pi / 180.
dip = -1*fault.ellipshape['dip']* np.pi / 180.
#??? NEEDS TO BE CONFIRMED ---(could use scipy.spatial.transformations, but would require an additional package installation)
#This conforms to the dMODELS formulation of Yang
#All of this should probably be double, triple-checked to make sure we are plotting the source correctly
rotex = np.asarray([[1,0,0],[0,np.cos(dip),-np.sin(dip)],[0,np.sin(dip),np.cos(dip)]])
#rotey = np.asarray([[np.cos(dip), 0., np.sin(dip)],[0., 1.,0.],[-np.sin(dip), 0, np.cos(dip)]])
rotez = np.asarray([[np.cos(strike), -np.sin(strike), 0.],[np.sin(strike), np.cos(strike),0.],[0.,0.,1.]])
#Rotate around y-axis (or x-axis???) first, then z-axis
xyz = np.dot(np.array([ex,ey,ez]).T,np.dot(rotex,rotez))
ex_ll,ey_ll = np.array(fault.xy2ll(xyz[:,:,0]+fault.xf,xyz[:,:,1]+fault.yf))
ez_ll = xyz[:,:,2]-(fault.ellipshape['z0']/1000.)
if self.faille is not None:
#x0 and y0 are in lat/lon, depth is negative and in km
self.faille.plot_surface(ex_ll,ey_ll,ez_ll,color=scalarMap.to_rgba(delta))
# Reset x- and y-lims
self.faille.set_xlim([self.lonmin,self.lonmax])
self.faille.set_ylim([self.latmin,self.latmax])
# # If 2d. Just plots center for now, should plot ellipse projection onto surface
if plot_on_2d and self.carte is not None:
self.carte.scatter(fault.ellipshape['x0'],fault.ellipshape['y0'])
# put up a colorbar
if colorbar:
if self.faille is not None: self.addColorbar(delta, scalaMap, cbaxis, cborientation, self.figFaille, cblabel=cblabel)
if plot_on_2d and self.carte is not None:
self.addColorbar(delta, scalaMap, cbaxis, cborientation, self.figCarte, cblabel=cblabel)
# All done
return
def faultTents(self, fault,
slip='strikeslip', norm=None, colorbar=True, alpha=1.0,
cbaxis=[0.1, 0.2, 0.1, 0.02], cborientation='horizontal', cblabel='',
method='scatter', cmap='jet', plot_on_2d=False,
revmap=False, factor=1.0, npoints=10,
xystrides=[100, 100], zorder=0,
vertIndex=False):
'''
Plot a fault with tents.
Args:
* fault : TriangularTent fault instance
Kwargs:
* slip : Can be 'strikeslip', 'dipslip', 'tensile', 'total' or 'coupling'
* norm : Limits for the colorbar.
* colorbar : if True, plots a colorbar.
* method : Can be 'scatter' (plots all the sub points as a colored dot) or 'surface' (interpolates a 3D surface which can be ugly...)
* cmap : matplotlib colormap
* plot_on_2d : if True, adds the patches on the map.
* revmap : Reverse the default colormap
* factor : Scale factor for fault slip values
* npoints : Number of subpoints per patch. This number is only indicative of the actual number of points that is picked out by the dropSourcesInPatch function of EDKS.py. It only matters to make the interpolation finer. Default value is generally alright.
* xystrides : If method is 'surface', then xystrides is going to be the number of points along x and along y used to interpolate the surface in 3D and its color.
* vertIndex : Writes the index of the vertices
Returns:
* None
'''
# Get slip
if slip in ('strikeslip'):
slip = fault.slip[:,0].copy()
elif slip in ('dipslip'):
slip = fault.slip[:,1].copy()
elif slip in ('tensile'):
slip = fault.slip[:,2].copy()
elif slip in ('total'):
slip = np.sqrt(fault.slip[:,0]**2 + fault.slip[:,1]**2 + fault.slip[:,2]**2)
elif slip in ('coupling'):
slip = fault.coupling.copy()
elif slip in ('sensitivity'):
slip = fault.sensitivity.copy()
else:
print ("Unknown slip direction")
return
slip *= factor
# norm
if norm == None:
vmin=slip.min()
vmax=slip.max()
else:
vmin=norm[0]
vmax=norm[1]
# set z axis
self.setzaxis(fault.depth+5., zticklabels=fault.z_patches)
# set color business
if revmap:
cmap = plt.get_cmap('{}_r'.format(cmap))