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stressfield.py
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stressfield.py
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'''
A class that deals with StressField data.
Written by R. Jolivet, Feb 2014.
'''
# Externals
import sys
import numpy as np
import pyproj as pp
import matplotlib.pyplot as plt
# Personals
from .SourceInv import SourceInv
from . import okadafull as okada
from . import csiutils as utils
from . import triangularDisp as triDisp
class stressfield(SourceInv):
'''
A class that handles a stress field. Not used in a long time, untested, could be incorrect.
Args:
* name : Name of the StressField dataset.
Kwargs:
* utmzone : UTM zone. Default is 10 (Western US).
* lon0 : Longitude of the custom utmzone
* lat0 : Latitude of the custom utmzone
* ellps : ellipsoid
* verbose : talk to me
'''
def __init__(self, name, utmzone=None, lon0=None, lat0=None, ellps='WGS84', verbose=True):
# Base class init
super(stressfield, self).__init__(name,
utmzone=utmzone,
lon0=lon0, lat0=lat0,
ellps=ellps)
# Initialize the data set
self.name = name
self.dtype = 'strainfield'
if verbose:
print ("---------------------------------")
print ("---------------------------------")
print ("Initialize StressField data set {}".format(self.name))
self.verbose=verbose
# Initialize some things
self.lon = None
self.lat = None
self.x = None
self.y = None
self.depth = None
self.Stress = None
self.trace = None
# All done
return
def setXYZ(self, x, y, z):
'''
Sets the values of x, y and z.
Args:
* x : array of floats (km)
* y : array of floats (km)
* z : array of floats (km)
Returns:
* None
'''
# Set
self.x = x
self.y = y
self.depth = z
# Set lon lat
lon, lat = self.xy2ll(x, y)
self.lon = lon
self.lat = lat
# All done
return
def setLonLatZ(self, lon, lat , z):
'''
Sets longitude, latitude and depth.
Args:
* lon : array of floats (km)
* lat : array of floats (km)
* z : array of floats (km)
Returns:
* None
'''
# Set
self.lon = lon
self.lat = lat
self.depth = z
# XY
x, y = self.ll2xy(lon, lat)
self.x = x
self.y = y
# All done
return
def fault2Stress_finitediff(self, fault, s2m=1., p2m=1e3, la=30e9, mu=30e9, nu=0.25, slipdirection='sd', force_dip=None, verbose=False, dx=1., mp=True):
'''
Takes a fault, or a list of faults, and computes the stress change associated with the slip on the fault.
The calculation is done with finite differences
Args:
* fault : Fault object (RectangularFault).
Kwargs:
* s2m : Conversion factor for the slip units. Factor is to put everything in meters.
* p2m : Conversion factor for the distance units. Factor is to put everything in meters.
* slipdirection : any combination of s, d, and t.
* la : Lamé parameter (default is 30GPa)
* mu : Shear Modulus (default is 30GPa).
* nu : Poisson's ratio (default is 0.25).
* force_dip : Specify the dip angle of the patches
* verbos : talk to me
* dx : finite difference step (default is 1m)
Returns:
* None
'''
# Verbose?
if verbose: print('Computing stress changes from fault {}'.format(fault.name))
# Check if fault type corresponds
assert fault.patchType in ('rectangle', 'triangle'), 'FD Stress calculation not implemented for the triangular tent case yet...'
# Get the slip distribution
nPatch = len(fault.patch)
strikeslip = np.zeros((nPatch,))
dipslip = np.zeros((nPatch,))
tensileslip = np.zeros((nPatch,))
if 's' in slipdirection: strikeslip = fault.slip[:,0]*s2m
if 'd' in slipdirection: dipslip = fault.slip[:,1]*s2m
if 't' in slipdirection: tensileslip = fault.slip[:,2]*s2m
# Compute the unit displacements along the three dimensions at each earthquake location
if fault.patchType=='triangle':
# Create holders
plusdx = []
minusdx = []
plusdy = []
minusdy = []
plusdz = []
minusdz = []
if mp:
# Imports
import multiprocessing as mp
from functools import partial
# Create a pool of workers
pool = mp.Pool(mp.cpu_count())
# Create a partial function with fixed arguments
func = partial(_calcDisp, self.x, self.y, self.depth, dx, p2m, nu)
# Iterate over the patches in parallel
results = pool.starmap(func, zip(fault.patch, strikeslip, dipslip, tensileslip))
# Close the pool and wait for the work to finish
pool.close()
pool.join()
# Clean up and sort
plusdx = [r[0] for r in results]
minusdx = [r[1] for r in results]
plusdy = [r[2] for r in results]
minusdy = [r[3] for r in results]
plusdz = [r[4] for r in results]
minusdz = [r[5] for r in results]
else:
# Iterate over the patches
for ii, (patch, ss, ds, ts) in enumerate(zip(fault.patch, strikeslip, dipslip, tensileslip)):
# Show me
if verbose:
sys.stdout.write('\r Patch {} / {}'.format(ii, len(fault.patch)))
sys.stdout.flush()
# X-axis
plusdx.append(triDisp.displacement(self.x*p2m+dx, self.y*p2m, self.depth*p2m, list(patch*p2m),
ss, ds, ts, nu=nu))
minusdx.append(triDisp.displacement(self.x*p2m-dx, self.y*p2m, self.depth*p2m, list(patch*p2m),
ss, ds, ts, nu=nu))
# Y-axis
plusdy.append(triDisp.displacement(self.x*p2m, self.y*p2m+dx, self.depth*p2m, list(patch*p2m),
ss, ds, ts, nu=nu))
minusdy.append(triDisp.displacement(self.x*p2m, self.y*p2m-dx, self.depth*p2m, list(patch*p2m),
ss, ds, ts, nu=nu))
# Z-axis
plusdz.append(triDisp.displacement(self.x*p2m, self.y*p2m, self.depth*p2m-dx, list(patch*p2m),
ss, ds, ts, nu=nu))
minusdz.append(triDisp.displacement(self.x*p2m, self.y*p2m, self.depth*p2m+dx, list(patch*p2m),
ss, ds, ts, nu=nu))
sys.stdout.write('\n')
sys.stdout.flush()
# Sum the contributions
plusdx = np.array(plusdx).sum(axis=0)
minusdx = np.array(minusdx).sum(axis=0)
plusdy = np.array(plusdy).sum(axis=0)
minusdy = np.array(minusdy).sum(axis=0)
plusdz = np.array(plusdz).sum(axis=0)
minusdz = np.array(minusdz).sum(axis=0)
elif fault.patchType=='rectangle':
# Build Arrays
xc = np.zeros((nPatch,))
yc = np.zeros((nPatch,))
zc = np.zeros((nPatch,))
width = np.zeros((nPatch,))
length = np.zeros((nPatch,))
strike = np.zeros((nPatch,))
dip = np.zeros((nPatch,))
# Build the arrays for okada
for ii in range(len(fault.patch)):
if verbose:
sys.stdout.write('\r Patch {} / {}'.format(ii, len(fault.patch)))
sys.stdout.flush()
xc[ii], yc[ii], zc[ii], width[ii], length[ii], strike[ii], dip[ii] = fault.getpatchgeometry(fault.patch[ii], center=True)
sys.stdout.write('\n')
sys.stdout.flush()
# Don't invert zc (for the patches, we give depths, so it has to be positive)
xc *= p2m
yc *= p2m
zc *= p2m
width *= p2m
length *= p2m
# If force dip
if force_dip is not None: dip[:] = force_dip
# X-axis
plusdx = okada.displacement(self.x*p2m+dx, self.y*p2m, -1.0*self.depth*p2m,
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
minusdx = okada.displacement(self.x*p2m-dx, self.y*p2m, -1.0*self.depth*p2m,
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
# Y-axis
plusdy = okada.displacement(self.x*p2m, self.y*p2m+dx, -1.0*self.depth*p2m,
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
minusdy = okada.displacement(self.x*p2m, self.y*p2m-dx, -1.0*self.depth*p2m,
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
# Z-axis
plusdz = okada.displacement(self.x*p2m, self.y*p2m, -1.0*(self.depth*p2m-dx),
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
minusdz = okada.displacement(self.x*p2m, self.y*p2m, -1.0*(self.depth*p2m+dx),
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
nu=nu).T
# Now that we have the displacement in many places, just compute the finite difference
# First line of Δu
Δuxx = (plusdx[0]-minusdx[0])/(2*dx)
Δuxy = (plusdy[0]-minusdy[0])/(2*dx)
Δuxz = (plusdz[0]-minusdz[0])/(2*dx)
# Second line of Δu
Δuyx = (plusdx[1]-minusdx[1])/(2*dx)
Δuyy = (plusdy[1]-minusdy[1])/(2*dx)
Δuyz = (plusdz[1]-minusdz[1])/(2*dx)
# Third line of Δu
Δuzx = (plusdx[2]-minusdx[2])/(2*dx)
Δuzy = (plusdy[2]-minusdy[2])/(2*dx)
Δuzz = (plusdz[2]-minusdz[2])/(2*dx)
# Build up the matrix
Δu = np.zeros((3,3,self.x.shape[0]))
Δu[0,:,:] = np.vstack((Δuxx, Δuxy, Δuxz))
Δu[1,:,:] = np.vstack((Δuyx, Δuyy, Δuyz))
Δu[2,:,:] = np.vstack((Δuzx, Δuzy, Δuzz))
self.Δu = Δu
# Make a strain tensor
self.Strain = 0.5*(Δu + Δu.transpose((1,0,2)))
# Compute the stress tensor assuming μ=30 GPa and λ=30 GPa
μ = la
λ = la
self.Stress = 2*μ*self.Strain + (λ*np.trace(self.Strain, axis1=0, axis2=1)[:,np.newaxis, np.newaxis]*np.eye(3)).transpose((1, 2, 0))
self.stresstype = 'total'
# All done
return
def fault2Stress(self, fault, s2m=1., p2m=1e3, la=30e9, mu=30e9, nu=0.25, slipdirection='sd', force_dip=None, verbose=False):
'''
Takes a fault, or a list of faults, and computes the stress change associated with the slip on the fault.
Args:
* fault : Fault object (RectangularFault).
Kwargs:
* s2m : Conversion factor for the slip units. Factor is to put everything in meters.
* p2m : Conversion factor for the distance units. Factor is to put everything in meters.
* slipdirection : any combination of s, d, and t.
* la : Lamé parameter (default is 30GPa)
* mu : Shear Modulus (default is 30GPa).
* nu : Poisson's ratio (default is 0.25).
* force_dip : Specify the dip angle of the patches
* verbos : talk to me
Returns:
* None
'''
# Verbose?
if verbose: print('Computing stress changes from fault {}'.format(fault.name))
# Check if fault type corresponds
if fault.patchType=='rectangle':
# Get a number
nPatch = len(fault.patch)
# Build Arrays
xc = np.zeros((nPatch,))
yc = np.zeros((nPatch,))
zc = np.zeros((nPatch,))
width = np.zeros((nPatch,))
length = np.zeros((nPatch,))
strike = np.zeros((nPatch,))
dip = np.zeros((nPatch,))
# Build the arrays for okada
for ii in range(len(fault.patch)):
if verbose:
sys.stdout.write('\r Patch {} / {}'.format(ii, len(fault.patch)))
sys.stdout.flush()
xc[ii], yc[ii], zc[ii], width[ii], length[ii], strike[ii], dip[ii] = fault.getpatchgeometry(fault.patch[ii], center=True)
# Don't invert zc (for the patches, we give depths, so it has to be positive)
xc *= p2m
yc *= p2m
zc *= p2m
width *= p2m
length *= p2m
# Get the slip distribution
strikeslip = np.zeros((nPatch,))
dipslip = np.zeros((nPatch,))
tensileslip = np.zeros((nPatch,))
if 's' in slipdirection: strikeslip = fault.slip[:,0]*s2m
if 'd' in slipdirection: dipslip = fault.slip[:,1]*s2m
if 't' in slipdirection: tensileslip = fault.slip[:,2]*s2m
# If force dip
if force_dip is not None: dip[:] = force_dip
# Get the Stress
self.stresstype = 'total'
self.Stress, flag, flag2 = okada.stress(self.x*p2m, self.y*p2m, -1.0*self.depth*p2m,
xc, yc, zc,
width, length,
strike, dip,
strikeslip, dipslip, tensileslip,
mu, nu,
full=True)
# Flags
self.flag = flag
self.flag2 = flag2
elif fault.patchType=='triangle':
# Get the slip distribution
strikeslip = np.zeros_like(fault.slip[:,0])
dipslip = np.zeros_like(fault.slip[:,1])
tensileslip = np.zeros_like(fault.slip[:,2])
if 's' in slipdirection: strikeslip = fault.slip[:,0]*s2m
if 'd' in slipdirection: dipslip = fault.slip[:,1]*s2m
if 't' in slipdirection: tensileslip = fault.slip[:,2]*s2m
# Create holder
Strain = np.zeros((3,3,self.x.shape[0]))
# Iterate
for ii, (patch, ss, ds, ts) in enumerate(zip(fault.patch, strikeslip, dipslip, tensileslip)):
if verbose:
sys.stdout.write('\r Patch {} / {}'.format(ii, len(fault.patch)))
sys.stdout.flush()
Strain[:,:,:] += triDisp.strain(self.x*p2m, self.y*p2m, self.depth*p2m, list(patch*p2m),
ss, ds, ts, nu=nu)
# Clean up
sys.stdout.write('\n')
sys.stdout.flush()
# Save the strain
self.Strain = Strain
# Compute the stress tensor assuming μ=30 GPa and λ=30 GPa
μ = la
λ = la
self.Stress = 2*μ*self.Strain + (λ*np.trace(self.Strain, axis1=0, axis2=1)[:,np.newaxis, np.newaxis]*np.eye(3)).transpose((1, 2, 0))
self.stresstype = 'total'
# Else
else:
# Nothing to do
print('Stress calculation not implemented for the triangular tent case yet...')
# All done
return
def computeTrace(self):
'''
Computes the Trace of the stress tensor.
'''
# Assert there is something to do
assert (self.Stress is not None), 'There is no stress tensor...'
# Check something
if self.stresstype in ('deviatoric'):
print('You should not compute the trace of the deviatoric tensor...')
print(' Previous Trace value erased...')
# Get it
self.trace = np.trace(self.Stress, axis1=0, axis2=1)
# All done
return
def total2deviatoric(self):
'''
Computes the deviatoric stress tensor dS = S - Tr(S)I
'''
# Check
if self.stresstype in ('deviatoric'):
print('Stress tensor is already a deviatoric tensor...')
return
# Remove Trace
self.Stress -= (np.trace(self.Stress, axis1=0, axis2=1)[..., np.newaxis, np.newaxis]*np.eye(3)).transpose(1,2,0)
# Change
self.stresstype = 'deviatoric'
# All done
return
def computeTractions(self, strike, dip):
'''
Computes the tractions given a plane with a given strike and dip.
Args:
* strike : Strike (radians).
* dip : Dip (radians).
If these are floats, all the tensors will be projected on that plane. Otherwise, they need to be the size ofthe number of tensors.
Positive Normal Traction means extension. Positive Shear Traction means left-lateral.
'''
# Get number of data points
Np = self.Stress.shape[2]
# Check the sizes
strike = np.ones((Np,))*strike
dip = np.ones((Np,))*dip
# Create the normal vectors
n1, n2, n3 = self.strikedip2normal(strike, dip)
# Compute the stress vectors
T = [ np.dot(n1[:,i], self.Stress[:,:,i]) for i in range(Np)]
# Compute the Shear Stress and Normal Stress
Sigma = np.array([ np.dot(T[i],n1[:,i]) for i in range(Np) ])
TauStrike = np.array([ np.dot(T[i],n2[:,i]) for i in range(Np) ])
TauDip = np.array([ np.dot(T[i],n3[:,i]) for i in range(Np) ])
# All done
return n1, n2, n3, T, Sigma, TauStrike, TauDip
def computeSecInv(self):
''' Computes the second invariant of the stress tensor and returns it'''
# Calculate the second invariant of the stress tensor
eigenvals = np.linalg.eigvals(self.Stress.transpose(2,0,1))
# There it is
J2 = 0.5*(eigenvals[:,0]**2 + eigenvals[:,1]**2 + eigenvals[:,2]**2)
return J2
def getTractions(self, strike, dip):
'''
Just a wrapper around computeTractions to store the result, if necessary.
Args:
* strike : Strike (radians).
* dip : Dip (radians).
If these are floats, all the tensors will be projected on that plane. Otherwise, they need to be the size ofthe number of tensors.
Positive Normal Traction means extension. Positive Shear Traction means left-lateral.
'''
# Compute tractions
n1, n2, n3, T, Sigma, TauStrike, TauDip = self.computeTractions(strike, dip)
# Store everything
self.n1 = n1
self.n2 = n2
self.n3 = n3
self.T = T
self.Sigma = Sigma
self.TauStrike = TauStrike
self.TauDip = TauDip
# All done
return
def strikedip2normal(self, strike, dip):
'''
Returns a vector normal to a plane with a given strike and dip (radians).
Args:
* strike : strike angle in radians
* dip : dip angle in radians
Returns:
* tuple of unit vectors
'''
# Compute normal
n1 = np.array([np.sin(dip)*np.cos(strike), -1.0*np.sin(dip)*np.sin(strike), np.cos(dip)])
# Along Strike
n2 = np.array([np.sin(strike), np.cos(strike), np.zeros(strike.shape)])
# Along Dip
n3 = np.cross(n1, n2, axisa=0, axisb=0).T
# All done
if len(n1.shape)==1:
return n1.reshape((3,1)), n2.reshape((3,1)), n3.reshape((3,1))
else:
return n1, n2, n3
def getprofile(self, name, loncenter, latcenter, length, azimuth, width, data='trace'):
'''
Project the wanted quantity onto a profile. Works on the lat/lon coordinates system.
Args:
* name : Name of the profile.
* loncenter : Profile origin along longitude.
* latcenter : Profile origin along latitude.
* length : Length of profile.
* azimuth : Azimuth in degrees.
* width : Width of the profile.
Kwargs:
* data : name of the data to use ('trace')
Returns:
* None
'''
print('Get the profile called {}'.format(name))
# the profiles are in a dictionary
if not hasattr(self, 'profiles'):
self.profiles = {}
# Which value are we going to use
try:
val = self.__getattribute__(data)
except:
print('Keyword unknown. Please implement it...')
return
# Mask the data
if hasattr(self, 'mask'):
i = np.where(self.mask.value.flatten()==1)
val[i] = np.nan
# Convert the lat/lon of the center into UTM.
xc, yc = self.ll2xy(loncenter, latcenter)
# Get the profile
Dalong, Dacros, Bol, boxll, box, xe1, ye1, xe2, ye2, lon, lat = utils.coord2prof(self, xc, yc, length, azimuth, width)
# Store it in the profile list
self.profiles[name] = {}
dic = self.profiles[name]
dic['Center'] = [loncenter, latcenter]
dic['Length'] = length
dic['Width'] = width
dic['Box'] = np.array(boxll)
dic['data'] = val[Bol]
dic['Depth'] = self.depth[Bol]
dic['Distance'] = np.array(Dalong)
dic['Normal Distance'] = np.array(Dacros)
dic['EndPoints'] = [[xe1, ye1], [xe2, ye2]]
# All done
return
def writeProfile2File(self, name, filename, fault=None):
'''
Writes the profile named 'name' to the ascii file filename.
Args:
* name : name of the profile to work with
* filename : output file name
Kwargs:
* fault : fualt object
Returns:
* None
'''
# open a file
fout = open(filename, 'w')
# Get the dictionary
dic = self.profiles[name]
# Write the header
fout.write('#---------------------------------------------------\n')
fout.write('# Profile Generated with StaticInv\n')
fout.write('# Center: {} {} \n'.format(dic['Center'][0], dic['Center'][1]))
fout.write('# Endpoints: \n')
fout.write('# {} {} \n'.format(dic['EndPoints'][0][0], dic['EndPoints'][0][1]))
fout.write('# {} {} \n'.format(dic['EndPoints'][1][0], dic['EndPoints'][1][1]))
fout.write('# Box Points: \n')
fout.write('# {} {} \n'.format(dic['Box'][0][0],dic['Box'][0][1]))
fout.write('# {} {} \n'.format(dic['Box'][1][0],dic['Box'][1][1]))
fout.write('# {} {} \n'.format(dic['Box'][2][0],dic['Box'][2][1]))
fout.write('# {} {} \n'.format(dic['Box'][3][0],dic['Box'][3][1]))
# Place faults in the header
if fault is not None:
if fault.__class__ is not list:
fault = [fault]
fout.write('# Fault Positions: \n')
for f in fault:
d = self.intersectProfileFault(name, f)
fout.write('# {} {} \n'.format(f.name, d))
fout.write('#---------------------------------------------------\n')
# Write the values
for i in range(len(dic['Distance'])):
d = dic['Distance'][i]
Dp = dic['data'][i]
if np.isfinite(Dp):
fout.write('{} {} \n'.format(d, Dp))
# Close the file
fout.close()
# all done
return
def plotprofile(self, name, data='veast', fault=None, comp=None):
'''
Plot profile.
Args:
* name : Name of the profile.
Kwargs:
* data : which data to plot
* fault : fault object
* comp : ??
Returns:
* None
'''
# open a figure
fig = plt.figure()
carte = fig.add_subplot(121)
prof = fig.add_subplot(122)
# Get the data we want to plot
if data=='trace':
dplot = self.trace
else:
print('Keyword Unknown, please implement it....')
return
# Mask the data
i = np.where(self.mask.value.flatten()==0)
dplot = dplot[i]
x = self.x.flatten()[i]
y = self.y.flatten()[i]
# Get min and max
MM = np.abs(dplot).max()
# Prepare a color map for insar
import matplotlib.colors as colors
import matplotlib.cm as cmx
cmap = plt.get_cmap('seismic')
cNorm = colors.Normalize(vmin=-1.0*MM, vmax=MM)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
# plot the StressField Points on the Map
carte.scatter(x, y, s=20, c=dplot, cmap=cmap, vmin=-1.0*MM, vmax=MM, linewidths=0.0)
scalarMap.set_array(dplot)
plt.colorbar(scalarMap)
# plot the box on the map
b = self.profiles[name]['Box']
bb = np.zeros((5, 2))
for i in range(4):
x, y = self.ll2xy(b[i,0], b[i,1])
bb[i,0] = x
bb[i,1] = y
bb[4,0] = bb[0,0]
bb[4,1] = bb[0,1]
carte.plot(bb[:,0], bb[:,1], '.k')
carte.plot(bb[:,0], bb[:,1], '-k')
# plot the profile
x = self.profiles[name]['Distance']
y = self.profiles[name]['data']
p = prof.plot(x, y, label=data, marker='.', linestyle='')
# If a fault is here, plot it
if fault is not None:
# If there is only one fault
if fault.__class__ is not list:
fault = [fault]
# Loop on the faults
for f in fault:
carte.plot(f.xf, f.yf, '-')
# Get the distance
d = self.intersectProfileFault(name, f)
if d is not None:
ymin, ymax = prof.get_ylim()
prof.plot([d, d], [ymin, ymax], '--', label=f.name)
# plot the legend
prof.legend()
# axis of the map
carte.axis('equal')
# Show to screen
plt.show()
# All done
return
def plot(self, data='trace', faults=None, gps=None, figure=123, ref='utm', legend=False, comp=None):
'''
Plot one component of the strain field.
Kwargs:
* data : Type of data to plot. Can be 'trace'
* faults : list of faults to plot.
* gps : list of gps networks to plot.
* figure : figure number
* ref : utm or lonlat
* legend : add a legend
* comp : ??
Returns:
* None
'''
# Get the data we want to plot
if data=='trace':
dplot = self.trace
else:
print('Keyword Unknown, please implement...')
return
# Creates the figure
fig = plt.figure(figure)
ax = fig.add_subplot(111)
# Set the axes
if ref=='utm':
ax.set_xlabel('Easting (km)')
ax.set_ylabel('Northing (km)')
else:
ax.set_xlabel('Longitude')
ax.set_ylabel('Latitude')
# Mask the data
if hasattr(self, 'mask'):
i = np.where(self.mask.value.flatten()==0)
dplot = dplot[i]
x = self.x.flatten()[i]
y = self.y.flatten()[i]
lon = self.lon.flatten()[i]
lat = self.lat.flatten()[i]
else:
x = self.x.flatten()
y = self.y.flatten()
lon = self.lon.flatten()
lat = self.lat.flatten()
# Get min and max
MM = np.abs(dplot).max()
# prepare a color map for the strain
import matplotlib.colors as colors
import matplotlib.cm as cmx
cmap = plt.get_cmap('seismic')
cNorm = colors.Normalize(vmin=-1.0*MM, vmax=MM)
scalarMap = cmx.ScalarMappable(norm=cNorm, cmap=cmap)
# plot the wanted data
if ref=='utm':
ax.scatter(x, y, s=20, c=dplot.flatten(), cmap=cmap, vmin=-1.0*MM, vmax=MM, linewidths=0.)
else:
ax.scatter(lon, lat, s=20, c=dplot.flatten(), cmap=cmap, vmin=-1.0*MM, vmax=MM, linewidths=0.)
# Plot the surface fault trace if asked
if faults is not None:
if faults.__class__ is not list:
faults = [faults]
for fault in faults:
if ref=='utm':
ax.plot(fault.xf, fault.yf, '-b', label=fault.name)
else:
ax.plot(fault.lon, fault.lat, '-b', label=fault.name)
# Plot the gps if asked
if gps is not None:
if gps.__class__ is not list:
gps = [gps]
for g in gps:
if ref=='utm':
ax.quiver(g.x, g.y, g.vel_enu[:,0], g.vel_enu[:,1], label=g.name)
else:
ax.quiver(g.lon, g.lat, g.vel_enu[:,0], g.vel_enu[:,1], label=g.name)
# Legend
if legend:
ax.legend()
# axis equal
ax.axis('equal')
# Colorbar
scalarMap.set_array(dplot.flatten())
plt.colorbar(scalarMap)
# Show
plt.show()
# all done
return
def intersectProfileFault(self, name, fault):
'''
Gets the distance between the fault/profile intersection and the profile center.
Args:
* name : name of the profile.
* fault : fault object.
Returns:
* None
'''
# Import shapely
import shapely.geometry as geom
# Grab the fault trace
xf = fault.xf
yf = fault.yf
# Grab the profile
prof = self.profiles[name]
# import shapely
import shapely.geometry as geom
# Build a linestring with the profile center
Lp = geom.LineString(prof['EndPoints'])
# Build a linestring with the fault
ff = []
for i in range(len(xf)):
ff.append([xf[i], yf[i]])
Lf = geom.LineString(ff)
# Get the intersection
if Lp.crosses(Lf):
Pi = Lp.intersection(Lf)
p = Pi.coords[0]
else:
return None
# Get the center
lonc, latc = prof['Center']
xc, yc = self.ll2xy(lonc, latc)
# Get the sign
xa,ya = prof['EndPoints'][0]
vec1 = [xa-xc, ya-yc]
vec2 = [p[0]-xc, p[1]-yc]
sign = np.sign(np.dot(vec1, vec2))
# Compute the distance to the center
d = np.sqrt( (xc-p[0])**2 + (yc-p[1])**2)*sign
# All done
return d
def output2GRD(self, outfile, data='dilatation', comp=None):
'''
Output the desired field to a grd file.
Args:
* outfile : Name of the outputgrd file.
Kwargs:
* data : Type of data to output. Can be 'veast', 'vnorth', 'dilatation', 'projection', 'strainrateprojection'
* comp : if data is projection or 'strainrateprojection', give the name of the projection you want.
Returns:
* None
'''
# Get the data we want to plot
if data=='veast':
dplot = self.vel_east.value
units = 'mm/yr'
elif data=='vnorth':
dplot = self.vel_north.value
units = 'mm/yr'
elif data=='dilatation':
if not hasattr(self, 'dilatation'):
self.computeDilatationRate()
dplot = self.dilatation.reshape((self.length, self.width))
units = ' '
elif data=='projection':
dplot = self.velproj[comp]['Projected Velocity']
units = ' '
elif data=='strainrateprojection':
dplot = self.Dproj[comp]['Projected Strain Rate'].reshape((self.length, self.width))