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Merge branch 'Dom'

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Conflicts:
	simpegPF/Dev/model.png
	simpegPF/Dev/obspred.png
This commit is contained in:
D Fournier
2016-04-29 11:05:45 -07:00
parent 241dc83354 4c1a893109
commit c40b9a9add
59 changed files with 383327 additions and 71217 deletions
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simpegPF/BaseGrav.py
+52
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@@ -0,0 +1,52 @@
from SimPEG import Maps, Survey, Utils, np, sp
from scipy.constants import mu_0
import re
class LinearSurvey(Survey.BaseSurvey):
"""Base Magnetics Survey"""
rxLoc = None #: receiver locations
rxType = None #: receiver type
def __init__(self, srcField, **kwargs):
self.srcField = srcField
Survey.BaseSurvey.__init__(self, **kwargs)
def eval(self, u):
return u
@property
def nD(self):
return self.prob.G.shape[0]
@property
def nRx(self):
return self.srcField.rxList[0].locs.shape[0]
# def setBackgroundField(self, SrcField):
# if getattr(self, 'B0', None) is None:
# self._B0 = SrcField.param[0] * dipazm_2_xyz(SrcField.param[1],SrcField.param[2])
# return self._B0
class SrcField(Survey.BaseSrc):
""" Define the inducing field """
param = None #: Inducing field param (Amp, Incl, Decl)
def __init__(self, rxList, **kwargs):
super(SrcField, self).__init__(rxList, **kwargs)
class RxObs(Survey.BaseRx):
"""A station location must have be located in 3-D"""
def __init__(self, locsXYZ, **kwargs):
locs = locsXYZ
assert locsXYZ.shape[1] == 3, 'locs must in 3-D (x,y,z).'
super(RxObs, self).__init__(locs, 'tmi', storeProjections=False, **kwargs)
@property
def nD(self):
"""Number of data in the receiver."""
return self.locs[0].shape[0]
simpegPF/BaseMag.py
+48 -349
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@@ -105,6 +105,54 @@ class BaseMagSurvey(Survey.BaseSurvey):
return np.r_[bfx, bfy, bfz]
class LinearSurvey(Survey.BaseSurvey):
"""Base Magnetics Survey"""
rxLoc = None #: receiver locations
rxType = None #: receiver type
def __init__(self, srcField, **kwargs):
self.srcField = srcField
Survey.BaseSurvey.__init__(self, **kwargs)
def eval(self, u):
return u
@property
def nD(self):
return self.prob.G.shape[0]
@property
def nRx(self):
return self.srcField.rxList[0].locs.shape[0]
# def setBackgroundField(self, SrcField):
# if getattr(self, 'B0', None) is None:
# self._B0 = SrcField.param[0] * dipazm_2_xyz(SrcField.param[1],SrcField.param[2])
# return self._B0
class SrcField(Survey.BaseSrc):
""" Define the inducing field """
param = None #: Inducing field param (Amp, Incl, Decl)
def __init__(self, rxList, param = None, **kwargs):
self.param = param
super(SrcField, self).__init__(rxList, **kwargs)
class RxObs(Survey.BaseRx):
"""A station location must have be located in 3-D"""
def __init__(self, locsXYZ, **kwargs):
locs = locsXYZ
assert locsXYZ.shape[1] == 3, 'locs must in 3-D (x,y,z).'
super(RxObs, self).__init__(locs, 'tmi', storeProjections=False, **kwargs)
@property
def nD(self):
"""Number of data in the receiver."""
return self.locs[0].shape[0]
class MagSurveyBx(object):
"""docstring for MagSurveyBx"""
def __init__(self, **kwargs):
@@ -144,352 +192,3 @@ class WeightMap(Maps.IdentityMap):
return Utils.sdiag(self.weight)
def readUBCmagObs(obs_file):
"""
Read and write UBC mag file format
INPUT:
:param fileName, path to the UBC obs mag file
OUTPUT:
:param dobs, observation in (x y z [data] [wd])
:param B, primary field information (BI, BD, B0)
:param M, magnetization orentiaton (MI, MD)
"""
fid = open(obs_file,'r')
# First line has the inclination,declination and amplitude of B0
line = fid.readline()
B = np.array(line.split(),dtype=float)
# Second line has the magnetization orientation and a flag
line = fid.readline()
M = np.array(line.split(),dtype=float)
# Third line has the number of rows
line = fid.readline()
ndat = np.array(line.split(),dtype=int)
# Pre-allocate space for obsx, obsy, obsz, data, uncert
line = fid.readline()
temp = np.array(line.split(),dtype=float)
dobs = np.zeros((ndat,len(temp)), dtype=float)
for ii in range(ndat):
dobs[ii,:] = np.array(line.split(),dtype=float)
line = fid.readline()
return B, M, dobs
def read_MAGfwr_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
modfile
magfile
topofile
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Jul 17, 2013
@author: dominiquef
"""
fid = open(input_file,'r')
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
modfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
magfile = []
else:
magfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
return mshfile, obsfile, modfile, magfile, topofile
def read_MAGinv_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
topofile
start model
ref model
mag model
weightfile
chi_target
as, ax ,ay, az
upper, lower bounds
lp, lqx, lqy, lqz
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Dec 21th, 2015
@author: dominiquef
"""
fid = open(input_file,'r')
# Line 1
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
# Line 2
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
# Line 3
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
# Line 4
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mstart = float(l_input[1])
else:
mstart = l_input[0].rstrip()
# Line 5
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mref = float(l_input[1])
else:
mref = l_input[0].rstrip()
# Line 6
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='DEFAULT':
magfile = []
else:
magfile = l_input[0].rstrip()
# Line 7
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='DEFAULT':
wgtfile = []
else:
wgtfile = l_input[0].rstrip()
# Line 8
line = fid.readline()
l_input = re.split('[!\s]',line)
chi = float(l_input[0])
# Line 9
line = fid.readline()
l_input = re.split('[!\s]',line)
val = np.array(l_input[0:4])
alphas = val.astype(np.float)
# Line 10
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:3])
bounds = val.astype(np.float)
else:
bounds = l_input[0].rstrip()
# Line 11
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:6])
lpnorms = val.astype(np.float)
else:
lpnorms = l_input[0].rstrip()
return mshfile, obsfile, topofile, mstart, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms
def read_GOCAD_ts(tsfile):
"""Read GOCAD triangulated surface (*.ts) file
INPUT:
tsfile: Triangulated surface
OUTPUT:
vrts : Array of vertices in XYZ coordinates [n x 3]
trgl : Array of index for triangles [m x 3]. The order of the vertices
is important and describes the normal
n = cross( (P2 - P1 ) , (P3 - P1) )
Created on Jan 13th, 2016
Author: @fourndo
"""
fid = open(tsfile,'r')
line = fid.readline()
# Skip all the lines until the vertices
while re.match('TFACE',line)==None:
line = fid.readline()
line = fid.readline()
vrtx = []
# Run down all the vertices and save in array
while re.match('VRTX',line):
l_input = re.split('[\s*]',line)
temp = np.array(l_input[2:5])
vrtx.append(temp.astype(np.float))
# Read next line
line = fid.readline()
vrtx = np.asarray(vrtx)
# Skip lines to the triangles
while re.match('TRGL',line)==None:
line = fid.readline()
# Run down the list of triangles
trgl = []
# Run down all the vertices and save in array
while re.match('TRGL',line):
l_input = re.split('[\s*]',line)
temp = np.array(l_input[1:4])
trgl.append(temp.astype(np.int))
# Read next line
line = fid.readline()
trgl = np.asarray(trgl)
return vrtx, trgl
def gocad2vtk(gcFile,mesh,bcflag,inflag):
""""
Function to read gocad polystructure file and output indexes of mesh with in the structure.
"""
import vtk, vtk.util.numpy_support as npsup
print "Reading GOCAD ts file..."
vrtx, trgl = read_GOCAD_ts(gcFile)
# Adjust the index
trgl = trgl - 1
# Make vtk pts
ptsvtk = vtk.vtkPoints()
ptsvtk.SetData(npsup.numpy_to_vtk(vrtx,deep=1))
# Make the polygon connection
polys = vtk.vtkCellArray()
for face in trgl:
poly = vtk.vtkPolygon()
poly.GetPointIds().SetNumberOfIds(len(face))
for nrv, vert in enumerate(face):
poly.GetPointIds().SetId(nrv,vert)
polys.InsertNextCell(poly)
# Make the polydata, structure of connections and vrtx
polyData = vtk.vtkPolyData()
polyData.SetPoints(ptsvtk)
polyData.SetPolys(polys)
# Make implicit func
ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
ImpDistFunc.SetInput(polyData)
# Convert the mesh
vtkMesh = vtk.vtkRectilinearGrid()
vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx,deep=1))
vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy,deep=1))
vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz,deep=1))
# Add indexes
vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC),deep=1)
vtkInd.SetName('Index')
vtkMesh.GetCellData().AddArray(vtkInd)
extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
extractImpDistRectGridFilt.SetInputData(vtkMesh)
if bcflag is True:
extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
else:
extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
if inflag is True:
extractImpDistRectGridFilt.ExtractInsideOn()
else:
extractImpDistRectGridFilt.ExtractInsideOff()
print "Extracting indices from grid..."
# Executing the pipe
extractImpDistRectGridFilt.Update()
# Get index inside
insideGrid = extractImpDistRectGridFilt.GetOutput()
insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
# Return the indexes inside
return insideGrid
simpegPF/Dev/Archives/fwr_MAG_data.py
-95
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@@ -1,95 +0,0 @@
def fwr_MAG_data(mesh,B,M,rxLoc,model,flag):
"""
Forward model magnetic data using integral equation
INPUT:
xn, yn, zn = Mesh nodes location
B = Inducing field parameter [Binc, Bdecl, B0]
M = Magnetization matrix [Minc, Mdecl]
rxLox = Observation location informat [obsx, obsy, obsz]
model = Model associated with mesh
OUTPUT:
dobs =Observation array in format [obsx, obsy, obsz, data]
Created on Oct 7, 2015
@author: dominiquef
"""
#%%
from SimPEG import np, Utils, sp, mkvc
from get_T_mat import get_T_mat
xn = mesh.vectorNx;
yn = mesh.vectorNy;
zn = mesh.vectorNz;
mcell = (len(xn)-1) * (len(yn)-1) * (len(zn)-1)
ndata = rxLoc.shape[0]
# Convert declination from north to cartesian
Md = (450.-float(M[1]))%360.
# Create magnetization matrix
mx = np.cos(np.deg2rad(M[0])) * np.cos(np.deg2rad(Md))
my = np.cos(np.deg2rad(M[0])) * np.sin(np.deg2rad(Md))
mz = np.sin(np.deg2rad(M[0]))
Mx = Utils.sdiag(np.ones([mcell])*mx*B[2])
My = Utils.sdiag(np.ones([mcell])*my*B[2])
Mz = Utils.sdiag(np.ones([mcell])*mz*B[2])
#matplotlib.pyplot.spy(scipy.sparse.csr_matrix(Mx))
#plt.show()
Mxyz = sp.vstack((Mx,My,Mz));
#%% Create TMI projector
# Convert Bdecination from north to cartesian
D = (450.-float(B[1]))%360.
Ptmi = mkvc(np.r_[np.cos(np.deg2rad(B[0]))*np.cos(np.deg2rad(D)),np.cos(np.deg2rad(B[0]))*np.sin(np.deg2rad(D)),np.sin(np.deg2rad(B[0]))],2).T;
if flag=='tmi':
d = np.zeros(ndata)
elif flag=='xyz':
d = np.zeros(int(3*ndata))
# Loop through all observations and create forward operator (ndata-by-mcell)
print "Begin forward modeling " +str(int(ndata)) + " data points..."
# Add counter to dsiplay progress. Good for large problems
progress = -1;
for ii in range(ndata):
tx, ty, tz = get_T_mat(xn,yn,zn,rxLoc[ii,:])
Gxyz = np.vstack((tx,ty,tz))*Mxyz
if flag=='xyz':
d[ii:ndata:] = mkvc(Gxyz.dot(model))
elif flag=='tmi':
d[ii] = Ptmi.dot(Gxyz.dot(model))
#%%
# Forward operator
d_iter = np.floor(float(ii)/float(ndata)*10.);
if d_iter > progress:
arg = "Done " + str(d_iter*10) + " %"
print arg
progress = d_iter;
print "Done 100% ...forward modeling completed!!\n"
return d
simpegPF/Dev/Archives/get_MAG_F.py
-132
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@@ -1,132 +0,0 @@
def fwr_MAG_F(mesh,B,M,rxLoc,flag):
"""
Forward model magnetic data using integral equation
INPUT:
mesh = Mesh in SimPEG format
B = Inducing field parameter [Binc, Bdecl, B0]
M = Magnetization information
[OPTIONS]
1- [Minc, Mdecl] : Assumes uniform magnetization orientation
2- [mx1,mx2,..., my1,...,mz1] : cell-based defined magnetization direction
3- diag(M): Block diagonal matrix with [Mx, My, Mz] along the diagonal
rxLox = Observation location informat [obsx, obsy, obsz]
flag = 'tmi' | 'xyz' | 'full'
[OPTIONS]
1- tmi : Magnetization direction used and data are projected onto the
inducing field direction F.shape([ndata, nc])
2- xyz : Magnetization direction used and data are given in 3-components
F.shape([3*ndata, nc])
3- full: Full tensor matrix stored with shape([3*ndata, 3*nc])
OUTPUT:
F = Linear forward modeling operation
Created on Dec, 20th 2015
@author: dominiquef
"""
#%%
from SimPEG import np, Utils, sp, mkvc
from get_T_mat import get_T_mat
xn = mesh.vectorNx;
yn = mesh.vectorNy;
zn = mesh.vectorNz;
mcell = (len(xn)-1) * (len(yn)-1) * (len(zn)-1)
ndata = rxLoc.shape[0]
#%% Create TMI projector
# Convert Bdecination from north to cartesian
D = (450.-float(B[1]))%360.
Ptmi = mkvc(np.r_[np.cos(np.deg2rad(B[0]))*np.cos(np.deg2rad(D)),
np.cos(np.deg2rad(B[0]))*np.sin(np.deg2rad(D)),
np.sin(np.deg2rad(B[0]))],2).T;
# Pre-allocate space
if flag=='tmi' | flag == 'xyz':
# If assumes uniform magnetization direction
if len(M) == 2:
# Convert declination from north to cartesian
Md = (450.-float(M[1]))%360.
# Create magnetization matrix
mx = np.cos(np.deg2rad(M[0])) * np.cos(np.deg2rad(Md))
my = np.cos(np.deg2rad(M[0])) * np.sin(np.deg2rad(Md))
mz = np.sin(np.deg2rad(M[0]))
Mx = Utils.sdiag(np.ones([mcell])*mx*B[2])
My = Utils.sdiag(np.ones([mcell])*my*B[2])
Mz = Utils.sdiag(np.ones([mcell])*mz*B[2])
Mxyz = sp.vstack((Mx,My,Mz));
# Otherwise if given a vector 3*ncells
elif len(M) == mesh.nC * 3:
Mxyz = sp.spdiags(M,0,mesh.nC * 3,mesh.nC * 3)
if flag == 'tmi':
F = np.zeros((ndata, mesh.nC))
elif flag == 'xyz':
F = np.zeros((int(3*ndata), mesh.nC))
elif flag == 'full':
F = np.zeros((int(3*ndata), int(3*mesh.nC)))
else:
print """Flag must be either 'tmi' | 'xyz' | 'full', please revised"""
return
# Loop through all observations and create forward operator (ndata-by-mcell)
print "Begin calculation of forward operator: " + flag
# Add counter to dsiplay progress. Good for large problems
progress = -1;
for ii in range(ndata):
tx, ty, tz = get_T_mat(xn,yn,zn,rxLoc[ii,:])
if flag=='tmi':
F[ii,:] = Ptmi.dot(np.vstack((tx,ty,tz)))*Mxyz
elif flag == 'xyz':
F[ii,:] = tx*Mxyz
F[ii+ndata,:] = ty*Mxyz
F[ii+2*ndata,:] = tz*Mxyz
elif flag == 'full':
F[ii,:] = tx
F[ii+ndata,:] = ty
F[ii+2*ndata,:] = tz
# Display progress
counter = np.floor(float(ii)/float(ndata)*10.);
if counter > progress:
arg = "Done " + str(counter*10) + " %"
print arg
progress = counter;
print "Done 100% ...forward modeling completed!!\n"
return F
simpegPF/Dev/Archives/get_T_mat.py
-133
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@@ -1,133 +0,0 @@
'''
Created on Sep 27, 2015
@author: dominiquef
'''
def get_T_mat(xn,yn,zn,rxLoc):
"""
Load in the nodes of a tensor mesh and computes the magnetic tensor
for a given observation location [obsx, obsy, obsz]
OUTPUT:
Tx = [Txx Txy Txz]
Ty = [Tyx Tyy Tyz]
Tz = [Tzx Tzy Tzz]
where each elements have dimension 1-by-mcell.
Only the upper half 5 elements have to be computed since symetric.
Currently done as for-loops but will eventually be changed to vector
indexing, once the topography has been figured out.
"""
from SimPEG import np, mkvc
ncx = len(xn)-1
ncy = len(yn)-1
ncz = len(zn)-1
mcell = ncx*ncy*ncz
# Pre-allocate space for 1D array
Tx = np.zeros((1,3*mcell))
Ty = np.zeros((1,3*mcell))
Tz = np.zeros((1,3*mcell))
yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
yn1,xn1,zn1 = np.meshgrid(yn[0:ncy], xn[0:ncx], zn[0:ncz])
yn2 = mkvc(yn2)
yn1 = mkvc(yn1)
zn2 = mkvc(zn2)
zn1 = mkvc(zn1)
xn2 = mkvc(xn2)
xn1 = mkvc(xn1)
#%%
#==============================================================================
dz2 = rxLoc[2] - zn1;
dz1 = rxLoc[2] - zn2;
dy2 = yn2 - rxLoc[1];
dy1 = yn1 - rxLoc[1];
dx2 = xn2 - rxLoc[0];
dx1 = xn1 - rxLoc[0];
R1 = ( dy2**2 + dx2**2 );
R2 = ( dy2**2 + dx1**2 );
R3 = ( dy1**2 + dx2**2 );
R4 = ( dy1**2 + dx1**2 );
arg1 = np.sqrt( dz2**2 + R2 );
arg2 = np.sqrt( dz2**2 + R1 );
arg3 = np.sqrt( dz1**2 + R1 );
arg4 = np.sqrt( dz1**2 + R2 );
arg5 = np.sqrt( dz2**2 + R3 );
arg6 = np.sqrt( dz2**2 + R4 );
arg7 = np.sqrt( dz1**2 + R4 );
arg8 = np.sqrt( dz1**2 + R3 );
Tx[0,0:mcell] = np.arctan2( dy1 * dz2 , ( dx2 * arg5 ) ) +\
- np.arctan2( dy2 * dz2 , ( dx2 * arg2 ) ) +\
np.arctan2( dy2 * dz1 , ( dx2 * arg3 ) ) +\
- np.arctan2( dy1 * dz1 , ( dx2 * arg8 ) ) +\
np.arctan2( dy2 * dz2 , ( dx1 * arg1 ) ) +\
- np.arctan2( dy1 * dz2 , ( dx1 * arg6 ) ) +\
np.arctan2( dy1 * dz1 , ( dx1 * arg7 ) ) +\
- np.arctan2( dy2 * dz1 , ( dx1 * arg4 ) );
Ty[0,0:mcell] = np.log( ( dz2 + arg2 ) / (dz1 + arg3 ) ) +\
-np.log( ( dz2 + arg1 ) / (dz1 + arg4 ) ) +\
np.log( ( dz2 + arg6 ) / (dz1 + arg7 ) ) +\
-np.log( ( dz2 + arg5 ) / (dz1 + arg8 ) );
Ty[0,mcell:2*mcell] = np.arctan2( dx1 * dz2 , ( dy2 * arg1 ) ) +\
- np.arctan2( dx2 * dz2 , ( dy2 * arg2 ) ) +\
np.arctan2( dx2 * dz1 , ( dy2 * arg3 ) ) +\
- np.arctan2( dx1 * dz1 , ( dy2 * arg4 ) ) +\
np.arctan2( dx2 * dz2 , ( dy1 * arg5 ) ) +\
- np.arctan2( dx1 * dz2 , ( dy1 * arg6 ) ) +\
np.arctan2( dx1 * dz1 , ( dy1 * arg7 ) ) +\
- np.arctan2( dx2 * dz1 , ( dy1 * arg8 ) );
R1 = (dy2**2 + dz1**2);
R2 = (dy2**2 + dz2**2);
R3 = (dy1**2 + dz1**2);
R4 = (dy1**2 + dz2**2);
Ty[0,2*mcell:] = np.log( ( dx1 + np.sqrt( dx1**2 + R1 ) ) / (dx2 + np.sqrt( dx2**2 + R1 ) ) ) +\
-np.log( ( dx1 + np.sqrt( dx1**2 + R2 ) ) / (dx2 + np.sqrt( dx2**2 + R2 ) ) ) +\
np.log( ( dx1 + np.sqrt( dx1**2 + R4 ) ) / (dx2 + np.sqrt( dx2**2 + R4 ) ) ) +\
-np.log( ( dx1 + np.sqrt( dx1**2 + R3 ) ) / (dx2 + np.sqrt( dx2**2 + R3 ) ) );
R1 = (dx2**2 + dz1**2);
R2 = (dx2**2 + dz2**2);
R3 = (dx1**2 + dz1**2);
R4 = (dx1**2 + dz2**2);
Tx[0,2*mcell:] = np.log( ( dy1 + np.sqrt( dy1**2 + R1 ) ) / (dy2 + np.sqrt( dy2**2 + R1 ) ) ) +\
-np.log( ( dy1 + np.sqrt( dy1**2 + R2 ) ) / (dy2 + np.sqrt( dy2**2 + R2 ) ) ) +\
np.log( ( dy1 + np.sqrt( dy1**2 + R4 ) ) / (dy2 + np.sqrt( dy2**2 + R4 ) ) ) +\
-np.log( ( dy1 + np.sqrt( dy1**2 + R3 ) ) / (dy2 + np.sqrt( dy2**2 + R3 ) ) );
Tz[0,2*mcell:] = -( Ty[0,mcell:2*mcell] + Tx[0,0:mcell] );
Tz[0,mcell:2*mcell] = Ty[0,2*mcell:];
Tx[0,mcell:2*mcell] = Ty[0,0:mcell];
Tz[0,0:mcell] = Tx[0,2*mcell:];
Tx = Tx/(4*np.pi);
Ty = Ty/(4*np.pi);
Tz = Tz/(4*np.pi);
return Tx,Ty,Tz
simpegPF/Dev/Archives/get_UBC_mesh.py
-117
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@@ -1,117 +0,0 @@
'''
Created on Jul 17, 2013
@author: dominiquef
'''
def get_UBC_mesh(meshfile):
""" Read UBC mesh file and extract parameters
Works for the condenced version (20 * 3) --> [20 20 20] """
fid = open(meshfile,'r')
from numpy import zeros
# Go through the log file and extract data and the last achieved misfit
for ii in range (1, 6):
line = fid.readline()
line = line.split(' ')
# First line: number of cells in i, j, k
if ii == 1:
numcell=[]
for jj in range(len(line)):
t = int(line[jj])
numcell.append(t)
nX = numcell[0]
nY = numcell[1]
nZ = numcell[2]
# Second line: origin coordinate (X,Y,Z)
elif ii==2:
origin = []
for jj in range(len(line)):
t = float(line[jj])
origin.append(t)
# Other lines for the xn, yn, zn (nodes location)
elif ii==3:
xn=zeros((nX+1,1), dtype=float)
xn[0] = origin[0]
count_entry = 0;
count = 0;
while (count<nX):
if line[count_entry].find('*') != -1:
ndx = line[count_entry].split('*')
for kk in range(int(ndx[0])):
xn[count+1] = xn[count] + (ndx[1])
count = count+1
count_entry=count_entry+1
else:
t = float(line[count_entry])
xn[count+1]= xn[count] +t
count = count+1;
count_entry=count_entry+1
elif ii==4:
yn=zeros((nY+1,1), dtype=float)
yn[0] = origin[0]
count_entry = 0;
count = 0;
while (count<nY):
if line[count_entry].find('*') != -1:
ndx = line[count_entry].split('*')
for kk in range(int(ndx[0])):
yn[count+1] = yn[count] + (ndx[1])
count = count+1
count_entry=count_entry+1
else:
t = float(line[count_entry])
yn[count+1]= yn[count] +t
count = count+1;
count_entry=count_entry+1
elif ii==5:
zn=zeros((nZ+1,1), dtype=float)
zn[0] = origin[0]
count_entry = 0;
count = 0;
while (count<nZ):
if line[count_entry].find('*') != -1:
ndx = line[count_entry].split('*')
for kk in range(int(ndx[0])):
zn[count+1] = zn[count] + (ndx[1])
count = count+1
count_entry=count_entry+1
else:
t = float(line[count_entry])
zn[count+1]= zn[count] +t
count = count+1;
count_entry=count_entry+1
fid.close();
return xn,yn,zn
simpegPF/Dev/Archives/read_MAG_obs.py
-58
View File
@@ -1,58 +0,0 @@
'''
Created on Jul 17, 2013
@author: dominiquef
'''
def read_MAG_obs(obs_file):
"""Read input files for the lp_norm script"""
from numpy import zeros
fid = open(obs_file,'r')
# First line has the declination, inclination and amplitude of B0
line = fid.readline()
line = line.split()
Incl = float(line[0])
Decl = float(line[1])
B0 = float(line[2])
# Second line has the magnetization orientation and a flag
line = fid.readline()
line = line.split()
Minc = float(line[0])
Mdec = float(line[1])
FLAG = float(line[2])
# Third line has the number of rows
line = fid.readline()
line = line.split()
ndat = int(line[0])
# Pre-allocate space for obsx, obsy, obsz, data, uncert
obsx = zeros((ndat,1), dtype=float)
obsy = zeros((ndat,1), dtype=float)
obsz = zeros((ndat,1), dtype=float)
data = zeros((ndat,1), dtype=float)
unct = zeros((ndat,1), dtype=float)
for ii in range(ndat):
line = fid.readline()
line = line.split()
obsx[ii] = line[0]
obsy[ii] = line[1]
obsz[ii] = line[2]
if len(line)>3:
data[ii] = line[3]
if len(line)>4:
unct[ii] = line[4]
return Decl, Incl, B0, Mdec, Minc, obsx, obsy, obsz, data, unct
simpegPF/Dev/Archives/read_MAGfwr_inp.py
-52
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@@ -1,52 +0,0 @@
def read_MAGfwr_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
modfile
magfile
topofile
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Jul 17, 2013
@author: dominiquef
"""
fid = open(input_file,'r')
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
modfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
magfile = []
else:
magfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
return mshfile, obsfile, modfile, magfile, topofile
simpegPF/Dev/FWR_data.dat
-628
View File
@@ -1,628 +0,0 @@
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-45.00 135.00 1.00
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simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver.py
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#%%
from SimPEG import *
import simpegPF as PF
import pylab as plt
import os
home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\CraigModel\\GRAV\\checkerboard_tests'
inpfile = 'PYGRAV3D_inv.inp'
dsep = '\\'
os.chdir(home_dir)
plt.close('all')
#%% User input
# Initial beta
beta_in = 1e-2
# Treshold values for compact norm
eps_p = 1e-3 # Small model values
eps_q = 1e-3 # Small model gradient
# Plotting parameter
vmin = -0.3
vmax = 0.3
#%%
# Read input file
[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
# Load mesh file
mesh = Mesh.TensorMesh.readUBC(mshfile)
# Load in observation file
survey = PF.Gravity.readUBCgravObs(obsfile)
# Get obs location and data
rxLoc = survey.srcField.rxList[0].locs
d = survey.dobs
wd = survey.std
ndata = survey.srcField.rxList[0].locs.shape[0]
# Load in topofile or create flat surface
if topofile == 'null':
# All active
actv = np.asarray(range(mesh.nC))
else:
topo = np.genfromtxt(topofile,skip_header=1)
# Find the active cells
actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
nC = len(actv)
# Create active map to go from reduce set to full
actvMap = Maps.InjectActiveCells(mesh, actv, -100)
# Creat reduced identity map
idenMap = Maps.IdentityMap(nP = nC)
# Load starting model file
if isinstance(mstart, float):
mstart = np.ones(nC) * mstart
else:
mstart = Mesh.TensorMesh.readModelUBC(mesh,mstart)
mstart = mstart[actv]
# Load reference file
if isinstance(mref, float):
mref = np.ones(nC) * mref
else:
mref = Mesh.TensorMesh.readModelUBC(mesh,mref)
mref = mref[actv]
# Get index of the center for plotting
midx = int(mesh.nCx/2)
midy = int(mesh.nCy/2)
#%% Plot obs data
PF.Gravity.plot_obs_2D(survey,'Observed Data')
#%% Run inversion
prob = PF.Gravity.GravityIntegral(mesh, mapping = idenMap, actInd = actv)
prob.solverOpts['accuracyTol'] = 1e-4
survey.pair(prob)
# Write out the predicted file and generate the forward operator
pred = prob.fields(mstart)
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred0.dat',survey,pred)
#
# Make depth weighting
#wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
#wr = ( wr/np.max(wr) )
#wr_out = actvMap * wr
# Load weighting file
if wgtfile is None:
wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 3., np.min(mesh.hx)/4.)
wr = wr**2.
else:
wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)
wr = wr[actv]
wr = wr**2.
#%% Plot depth weighting
plt.figure()
ax = plt.subplot()
mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (0, wr.max()))
plt.title('Distance weighting')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
#%% Create inversion objects
# First start with an l2 regularization
reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap)
reg.mref = mref
reg.wght = wr
# Create pre-conditioner
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
# Data misfit function
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
opt = Optimization.ProjectedGNCG(maxIter=20,lower=bounds[0],upper=bounds[1], maxIterCG= 50, tolCG = 1e-4)
opt.approxHinv = PC
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
target = Directives.TargetMisfit()
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
m0 = mstart
# Run inversion
mrec = inv.run(m0)
m_out = actvMap*mrec
# Write result
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out)
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
# Plot predicted
pred = prob.fields(mrec)
#PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data')
#PF.Magnetics.plot_obs_2D(rxLoc,(d-pred),wd,'Residual Data')
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out sections of the smooth model
yslice = midx+1
m_out[m_out==-100] = np.nan
plt.figure()
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
plt.title('Cross Section')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
plt.figure()
ax = plt.subplot(121)
plt.hist(mrec,100)
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model values - Smooth')
ax = plt.subplot(122)
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model gradient values - Smooth')
#%% Run one more round for sparsity
phim = invProb.phi_m_last
phid = invProb.phi_d
reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
reg.recModel = mrec
reg.mref = mref
reg.wght = wr
reg.eps_p = eps_p
reg.eps_q = eps_q
reg.norms = lpnorms
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
#reg.alpha_s = 1.
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
opt = Optimization.ProjectedGNCG(maxIter=20 , maxIterLS = 20,lower=bounds[0],upper=bounds[1], maxIterCG= 50, tolCG = 1e-4)
opt.approxHinv = PC
#opt.phim_last = reg.eval(mrec)
# opt = Optimization.InexactGaussNewton(maxIter=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
#betaest = Directives.BetaEstimate_ByEig()
target = Directives.TargetMisfit()
IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS])
m0 = mrec
# Run inversion
mrec = inv.run(m0)
m_out = actvMap*mrec
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.sus',m_out)
pred = prob.fields(mrec)
#%% Plot obs data
PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out a section of the model
yslice = midx
m_out[m_out==-100] = np.nan
plt.figure()
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-18, clim = (vmin,vmax) , pcolorOpts = {'cmap':'bwr'})
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-18]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-23, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-23]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax), pcolorOpts = {'cmap':'bwr'})
plt.title('Cross Section')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
plt.figure()
ax = plt.subplot(121)
plt.hist(mrec,100)
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model values - Sparse lp:'+str(lpnorms[0]))
ax = plt.subplot(122)
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model gradient values - Sparse lqx: ' + str(lpnorms[1]) + ' lqy:'+ str(lpnorms[2]) + ' lqz:' + str(lpnorms[3]))
simpegPF/Dev/GRAV/Intgrl_GRAV_Inv_Driver_LdM_Craig.py
+323
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#%%
from SimPEG import *
import simpegPF as PF
import pylab as plt
import os
import numpy as np
#home_dir = 'C:\Egnyte\Private\craigm\PHD\LdM\Gravity\Bouguer\SIMPEG\models'
home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev\GRAV'
#inpfile = 'PYGRAV3D_inv_LdM_Craig.inp'
inpfile = 'PYGRAV3D_inv_checkerboard.inp'
dsep = '\\'
os.chdir(home_dir)
plt.close('all')
#%% User input
# Initial beta
beta_in = 1e-2
# Treshold values for compact norm
eps_p = 0.01 # Compact model values
eps_q = 0.01 # ompact model gradient
# Plotting parameter
vmin = -0.1
vmax = 0.2
#%%
# Read input file
[mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms] = PF.Gravity.read_GRAVinv_inp(home_dir + dsep + inpfile)
# Load mesh file
mesh = Mesh.TensorMesh.readUBC(mshfile)
# Load in observation file
survey = PF.Gravity.readUBCgravObs(obsfile)
# Get obs location and data
rxLoc = survey.srcField.rxList[0].locs
d = survey.dobs
wd = survey.std
ndata = survey.srcField.rxList[0].locs.shape[0]
# Load in topofile or create flat surface
if topofile == 'null':
# All active
actv = np.asarray(range(mesh.nC))
else:
topo = np.genfromtxt(topofile,skip_header=1)
# Find the active cells
actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
nC = len(actv)
# Create active map to go from reduce set to full
actvMap = Maps.InjectActiveCells(mesh, actv, -100)
# Creat reduced identity map
idenMap = Maps.IdentityMap(nP = nC)
# Load starting model file
if isinstance(mstart, float):
mstart = np.ones(nC) * mstart
else:
mstart = Mesh.TensorMesh.readModelUBC(mesh,mstart)
mstart = mstart[actv]
# Load reference file
if isinstance(mref, float):
mref = np.ones(nC) * mref
else:
mref = Mesh.TensorMesh.readModelUBC(mesh,mref)
mref = mref[actv]
# Get index of the center for plotting
midx = int(mesh.nCx/2)
midy = int(mesh.nCy/2)
#%% Plot obs data
#PF.Gravity.plot_obs_2D(survey,'Observed Data')
#%% Run inversion
prob = PF.Gravity.GravityIntegral(mesh, mapping = idenMap, actInd = actv)
prob.solverOpts['accuracyTol'] = 1e-4
survey.pair(prob)
# Write out the predicted file and generate the forward operator
pred = prob.fields(mstart)
PF.Gravity.writeUBCobs(home_dir + dsep + 'Pred0.dat',survey,pred)
# Make depth weighting
#wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
#wr = ( wr/np.max(wr) )
#wr_out = actvMap * wr
#A different weighting function from Dominic
#wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 2., np.min(mesh.hx)/4.)
#wr = wr**2.
# Load weighting file
if wgtfile is None:
wr = PF.Magnetics.get_dist_wgt(mesh, rxLoc, actv, 2., np.min(mesh.hx)/4.)
wr = wr**2.
else:
wr = Mesh.TensorMesh.readModelUBC(mesh, home_dir + dsep + wgtfile)
wr = wr[actv]
wr = wr**2.
#%% Plot depth weighting
plt.figure()
ax = plt.subplot()
datwgt=mesh.plotSlice(actvMap*wr, ax = ax, normal = 'Y', ind=midx+1 ,clim = (-1e-1, wr.max()))
plt.title('Distance weighting')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(datwgt[0],orientation="vertical")
cb.set_label('Weighting')
plt.savefig(home_dir + dsep + 'Weighting.png', dpi=300)
#%% Create inversion objects
print '\nRun smooth inversion \n'
# First start with an l2 (smooth model) regularization
reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap)
reg.mref = mref
reg.wght = wr
# Create pre-conditioner
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
# Data misfit function
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
opt = Optimization.ProjectedGNCG(maxIter=20,lower=bounds[0],upper=bounds[1], maxIterCG= 20, tolCG = 1e-3)
opt.approxHinv = PC
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
target = Directives.TargetMisfit()
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
m0 = mstart
# Run inversion
mrec = inv.run(m0)
m_out = actvMap*mrec
# Write result
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.den',m_out)
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
# Plot predicted
pred = prob.fields(mrec)
#PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data')
#PF.Magnetics.plot_obs_2D(rxLoc,(d-pred),wd,'Residual Data')
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out sections of the smooth model
yslice = midx+1
plt.figure(figsize=(15,10))
plt.suptitle('Smooth Inversion')
ax = plt.subplot(221)
dat1=mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (vmin,vmax))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
ax = plt.subplot(222)
dat = mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax))
plt.title('Cross Section')
plt.xlabel('Easting(m)');plt.ylabel('Elevation')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
plt.savefig(home_dir + str('\Figure1.png'), dpi=300, bb_inches='tight')
#plot histograms
plt.figure(figsize=(15,10))
ax = plt.subplot(121)
plt.hist(mrec,100)
plt.yscale('log', nonposy='clip')
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
plt.title('Histogram of model values - Smooth')
ax = plt.subplot(122)
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
plt.yscale('log', nonposy='clip')
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
plt.title('Histogram of model gradient values - Smooth')
plt.savefig(home_dir + str('\Figure2.png'), dpi=300, bb_inches='tight')
#%% Run one more round for sparsity (Compact model)
print '\nRun compact inversion \n'
phim = invProb.phi_m_last
phid = invProb.phi_d
reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
reg.recModel = mrec
reg.mref = mref
reg.wght = wr
reg.eps_p = eps_p
reg.eps_q = eps_q
reg.norms = lpnorms
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
#reg.alpha_s = 1.
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./wd
opt = Optimization.ProjectedGNCG(maxIter=10 ,lower=bounds[0],upper=bounds[1], maxIterCG= 25, tolCG = 1e-4)
opt.approxHinv = PC
#opt.phim_last = reg.eval(mrec)
# opt = Optimization.InexactGaussNewton(maxIter=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
#betaest = Directives.BetaEstimate_ByEig()
target = Directives.TargetMisfit()
IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS])
m0 = mrec
# Run inversion
mrec = inv.run(m0)
m_out = actvMap*mrec
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.den',m_out)
pred = prob.fields(mrec)
#%% Plot obs data
PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data', vmin = np.min(d), vmax = np.max(d))
plt.savefig(home_dir + str('\Figure3.png'), dpi=300, bb_inches='tight')
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
plt.savefig(home_dir + str('\Figure4.png'), dpi=300, bb_inches='tight')
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out a section of the compact model
yslice = midx
plt.figure(figsize=(15,10))
plt.suptitle('Compact Inversion')
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (vmin,vmax))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (vmin,vmax))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.scatter(rxLoc[0:,0], rxLoc[0:,1], color='w',s=1)
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('Easting (m)');plt.ylabel('Northing (m)')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (vmin,vmax))
plt.title('Cross Section')
plt.xlabel('Easting (m)');plt.ylabel('Elevation (m)')
plt.gca().set_aspect('equal', adjustable='box')
cb = plt.colorbar(dat1[0],orientation="vertical", ticks=np.linspace(vmin, vmax, 4))
cb.set_label('Density (kg/m3)')
plt.savefig(home_dir + str('\Figure5.png'), dpi=300, bb_inches='tight')
plt.figure(figsize=(15,10))
ax = plt.subplot(121)
plt.hist(mrec,100)
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model values - Sparse lp:'+str(lpnorms[0]))
ax = plt.subplot(122)
plt.hist(reg.regmesh.cellDiffxStencil*mrec,100)
plt.xlim(mrec.mean() - 4.*(mrec.std()), mrec.mean() + 4.*(mrec.std()))
plt.yscale('log', nonposy='clip')
plt.title('Histogram of model gradient values - Sparse lqx: ' + str(lpnorms[1]) + ' lqy:'+ str(lpnorms[2]) + ' lqz:' + str(lpnorms[3]))
plt.savefig(home_dir + str('\Figure6.png'), dpi=300, bb_inches='tight')
simpegPF/Dev/GRAV/Mesh_10m.msh
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47 47 20
-60.00 -60.00 280.00
50.00 30.00 20.00 41*10.00 20.00 30.00 50.00
50.00 30.00 20.00 41*10.00 20.00 30.00 50.00
17*10.00 20.00 30.00 50
simpegPF/Dev/GRAV/PYGRAV3D_inv.inp
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Mesh_10m.msh ! Mesh file
Grav.dat ! Obsfile
Gaussian.topo ! Topofile | null
VALUE 1e-4 ! Starting model
VALUE 0.0 ! Reference model
DEFAULT ! Cell based weight file
1 ! target chi factor | DEFAULT=1
1 1 1 1 ! alpha s, x ,y ,z
VALUE -1 1 ! Lower and Upper Bounds for p-component
VALUE 0 1 1 1 1 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
simpegPF/Dev/GRAV/Pred0.dat
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191
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simpegPF/Dev/GRAV/SimPEGWr.dat
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simpegPF/Dev/Intgrl_MAG_Fwr_Driver.py
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import os
home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\ownCloud\Research\Modelling\Synthetic\Block_Gaussian_topo'
inpfile = 'PYMAG3C_fwr.inp'
dsep = '\\'
os.chdir(home_dir)
#%%
from SimPEG import np, sp, Utils, mkvc, Maps
import simpegPF as PF
import pylab as plt
## New scripts to be added to basecode
#from fwr_MAG_data import fwr_MAG_data
#from read_MAGfwr_inp import read_MAGfwr_inp
#%%
# Read input file
[mshfile, obsfile, modfile, magfile, topofile] = PF.BaseMag.read_MAGfwr_inp(inpfile)
# Load mesh file
mesh = Utils.meshutils.readUBCTensorMesh(mshfile)
# Load model file
model = Utils.meshutils.readUBCTensorModel(modfile,mesh)
# Load in topofile or create flat surface
if topofile == 'null':
actv = np.ones(mesh.nC)
else:
topo = np.genfromtxt(topofile,skip_header=1)
actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
Utils.writeUBCTensorModel('nullcell.dat',mesh,actv)
# Load in observation file
[B,M,dobs] = PF.BaseMag.readUBCmagObs(obsfile)
rxLoc = dobs[:,0:3]
#rxLoc[:,2] += 5 # Temporary change for test
ndata = rxLoc.shape[0]
# Load GOCAD surf
tsfile = 'SphereA.ts'
[vrtx, trgl] = PF.BaseMag.read_GOCAD_ts(tsfile)
#%% Run forward modeling
# Compute forward model using integral equation
d = PF.Magnetics.Intgrl_Fwr_Data(mesh,B,M,rxLoc,model,actv,'tmi')
# Form data object with coordinates and write to file
wd = np.zeros((ndata,1))
# Save forward data to file
PF.Magnetics.writeUBCobs(home_dir + dsep + 'FWR_data.dat',B,M,rxLoc,d,wd)
simpegPF/Dev/Intgrl_MAG_Fwr_DualSphereTopo_Test.py
-187
View File
@@ -1,187 +0,0 @@
import os
home_dir = 'C:\\LC\\Private\\dominiquef\\Projects\\4414_Minsim\\Modeling\\MAG'
os.chdir(home_dir)
#%%
from SimPEG import *
import matplotlib.pyplot as plt
import simpegPF as PF
import scipy.interpolate as interpolation
import time
#from fwr_MAG_data import fwr_MAG_data
plt.close('all')
topofile = 'Gaussian.topo'
zoffset = 2
#%% Create survey
# Load in topofile or create flat surface
if not topofile:
actv = np.ones(mesh.nC)
else:
topo = np.genfromtxt(topofile,skip_header=1)
B = np.array(([90.,0.,50000.]))
M = np.array(([90.,0.,315.]))
# Sphere radius
R = 25.
# # Or create juste a plane grid
xr = np.linspace(-99., 99., 40)
yr = np.linspace(-49., 49., 20)
X, Y = np.meshgrid(xr, yr)
sclx = 100.
dx = np.asarray([15., 10., 5., 2.5])
d_iter = len(dx)
l1_r = np.zeros(d_iter)
l2_r = np.zeros(d_iter)
linf_r = np.zeros(d_iter)
timer = np.zeros(d_iter)
mcell = np.zeros(d_iter)
#%% Loop through decreasing meshes and measure the residual
# Create mesh using simpeg and write out in GIF format
for ii in range(d_iter):
nc = int(sclx/dx[ii])
hxind = [(dx[ii], 2*nc)]
hyind = [(dx[ii], nc)]
hzind = [(dx[ii], nc)]
mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCN')
mcell[ii] = mesh.nC
actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
# Drape observations on topo + offset
if not topofile:
Z = np.ones((xr.size, yr.size)) * 2.5
else:
F = interpolation.NearestNDInterpolator(topo[:,0:2],topo[:,2])
Z = F(X,Y) + zoffset
rxLoc = np.c_[Utils.mkvc(X.T), Utils.mkvc(Y.T), Utils.mkvc(Z.T)]
ndata = rxLoc.shape[0]
xn = mesh.vectorNx
yn = mesh.vectorNy
zn = mesh.vectorNz
print 'Mesh size: ' + str(mcell[ii])
#%% Create model
chibkg = 0.
chiblk = 0.01
model = np.ones(mcell[ii])*chibkg
# Do a three sphere problem for more frequencies
sph_ind = PF.MagAnalytics.spheremodel(mesh, 0., 0., -sclx/3, R)
model[sph_ind] = 0.5*chiblk
sph_ind = PF.MagAnalytics.spheremodel(mesh, -sclx/2., 0., -sclx/3., R/3.)
model[sph_ind] = 4.*chiblk
sph_ind = PF.MagAnalytics.spheremodel(mesh, sclx/2., 0., -sclx/2.5, R/2.5)
model[sph_ind] = 2.5*chiblk
Utils.writeUBCTensorMesh('Mesh.msh',mesh)
Utils.writeUBCTensorModel('Model.sus',mesh,model)
#actv = np.ones(mesh.nC)
#%% Forward mode ldata
start_time = time.time()
d = PF.Magnetics.Intgrl_Fwr_Data(mesh,B,M,rxLoc,model,actv,'tmi')
timer[ii] = (time.time() - start_time)
#fwr_tmi = d[0:ndata]
#fwr_y = d[ndata:2*ndata]
#fwr_z = d[2*ndata:]
#%% Get the analystical answer and compute the residual
#bxa,bya,bza = PF.MagAnalytics.MagSphereAnaFunA(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R,0.,0.,0.,chiblk, np.array(([0.,0.,B[2]])),'secondary')
Bd = (450.-float(B[1]))%360.
Bi = B[0]; # Convert dip to horizontal to cartesian
Bx = np.cos(np.deg2rad(Bi)) * np.cos(np.deg2rad(Bd)) * B[2]
By = np.cos(np.deg2rad(Bi)) * np.sin(np.deg2rad(Bd)) * B[2]
Bz = np.sin(np.deg2rad(Bi)) * B[2]
Bo = np.c_[Bx, By, Bz]
Ptmi = mkvc(np.r_[np.cos(np.deg2rad(Bi))*np.cos(np.deg2rad(Bd)),np.cos(np.deg2rad(Bi))*np.sin(np.deg2rad(Bd)),np.sin(np.deg2rad(Bi))],2).T;
bxa,bya,bza = PF.MagAnalytics.MagSphereFreeSpace(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R,0., 0., -sclx/3, 0.5*chiblk, Bo)
bxb,byb,bzb = PF.MagAnalytics.MagSphereFreeSpace(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R/3., -sclx/2., 0., -sclx/3.,4.*chiblk, Bo)
bxc,byc,bzc = PF.MagAnalytics.MagSphereFreeSpace(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R/2.5, sclx/2., 0., -sclx/2.5,2.5*chiblk, Bo)
bx = bxa + bxb + bxc
by = bya + byb + byc
bz = bza + bzb + bzc
b_tmi = mkvc(Ptmi.dot(np.c_[bx,by,bz].T))
r_tmi = d - b_tmi
#r_By = fwr_y - bya
#r_Bz = fwr_z - bza
l2_r[ii] = np.sum( r_tmi**2 ) **0.5
l1_r[ii] = np.sum( np.abs( r_tmi ) )
linf_r[ii] = np.max( np.abs( r_tmi ) )
#%% Write predicted to file
PF.Magnetics.writeUBCobs('Obsloc.loc',B,M,rxLoc,d,np.ones(len(d)))
#%% Plot results
print 'Residual between analytical sphere and integral forward'
print "dx \t nc \t l1 \t l2 \t linf \t Runtime"
for ii in range(d_iter):
print str(dx[ii]) + "\t" + str(mcell[ii]) + "\t" + str(l1_r[ii]) + "\t" + str(l2_r[ii]) + "\t" + str(linf_r[ii]) + "\t" + str(timer[ii])
#%% Plot fields
plt.figure(1)
ax = plt.subplot()
plt.imshow(np.reshape(b_tmi,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.02)
plt.contour(X,Y, np.reshape(b_tmi,X.shape),10)
plt.scatter(X,Y, c=np.reshape(b_tmi,X.shape), s=20)
ax.set_title('Analytical')
#%% Plot the forward solution from integral
plt.figure(2)
ax = plt.subplot()
plt.imshow(np.reshape(d,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max() ], origin = 'lower')
plt.colorbar(fraction=0.02)
plt.contour(X,Y, np.reshape(d,X.shape),10)
plt.scatter(X,Y, c=np.reshape(d,X.shape), s=20)
ax.set_title('Numerical')
#%% Plot residual data
plt.figure(3)
ax = plt.subplot()
plt.imshow(np.reshape(r_tmi,X.shape), interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.02)
plt.contour(X,Y, np.reshape(r_tmi,X.shape),10)
plt.scatter(X,Y, c=np.reshape(r_tmi,X.shape), s=20)
ax.set_title('Sphere Ana Bx')
simpegPF/Dev/Intgrl_MAG_Fwr_SphereTest.py
-173
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@@ -1,173 +0,0 @@
import os
# home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev'
# os.chdir(home_dir)
#%%
from SimPEG import *
import matplotlib.pyplot as plt
import simpegPF as PF
#from fwr_MAG_data import fwr_MAG_data
plt.close('all')
#%% Create survey
B = np.array(([-45.,315.,50000.]))
M = np.array(([-45.,315.]))
# Sphere radius
R = 0.25
# # Or create juste a plane grid
xr = np.linspace(-2., 2., 5)
yr = np.linspace(-2., 2., 5)
X, Y = np.meshgrid(xr, yr)
Z = np.ones((xr.size, yr.size)) * 2.5
rxLoc = np.c_[Utils.mkvc(X), Utils.mkvc(Y), Utils.mkvc(Z)]
ndata = rxLoc.shape[0]
d_iter = 4
lrl = np.zeros(d_iter)
#%% Loop through decreasing meshes and measure the residual
# Create mesh using simpeg and write out in GIF format
for ii in range(d_iter):
nc = 3**(ii+1)
hxind = [(1./nc, nc)]
hyind = [(1./nc, nc)]
hzind = [(1./nc, nc)]
mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCC')
xn = mesh.vectorNx
yn = mesh.vectorNy
zn = mesh.vectorNz
mcell = mesh.nC
print 'Mesh size: ' + str(mcell)
sph_ind = PF.MagAnalytics.spheremodel(mesh, 0, 0, 0, R)
chibkg = 0.
chiblk = 0.01
model = np.ones(mcell)*chibkg
model[sph_ind] = chiblk
actv = np.ones(mcell)
#%% Forward mode ldata
d = PF.Magnetics.Intgrl_Fwr_Data(mesh,B,M,rxLoc,model,actv,'xyz')
fwr_x = d[0:ndata]
fwr_y = d[ndata:2*ndata]
fwr_z = d[2*ndata:]
#%% Get the analystical answer and compute the residual
bxa,bya,bza = PF.MagAnalytics.MagSphereAnaFunA(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R,0.,0.,0.,chiblk, np.array(([0.,0.,B[2]])),'secondary')
Bd = (450.-float(B[1]))%360.
Bi = B[0]; # Convert dip to horizontal to cartesian
Bx = np.cos(np.deg2rad(Bi)) * np.cos(np.deg2rad(Bd)) * B[2]
By = np.cos(np.deg2rad(Bi)) * np.sin(np.deg2rad(Bd)) * B[2]
Bz = np.sin(np.deg2rad(Bi)) * B[2]
Bo = np.c_[Bx, By, Bz]
bxa,bya,bza = PF.MagAnalytics.MagSphereFreeSpace(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R,0.,0.,0.,chiblk, Bo)
#bxa,bya,bza = PF.MagAnalytics.MagSphereAnaFunA(rxLoc[:,0],rxLoc[:,1],rxLoc[:,2],R,0.,0.,0.,chiblk, np.array(([0.,0.,B[2]])),'secondary')
r_Bx = fwr_x - bxa
r_By = fwr_y - bya
r_Bz = fwr_z - bza
lrl[ii] = sum( r_Bx**2 + r_By**2 + r_Bz**2 ) **0.5
#%% Plot results
print 'Residual between analytical sphere and integral forward'
for ii in range(d_iter):
nc = 3**(ii+1)
print "||r||= " + str(lrl[ii]) + "\t dx= " + str(1./nc)
#%% Plot fields
plt.figure(1)
ax = plt.subplot(221)
plt.imshow(np.reshape(bxa,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(bxa,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(bxa,X.shape).T, s=20)
ax.set_title('Sphere Ana Bx')
ax = plt.subplot(222)
plt.imshow(np.reshape(bya,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(bya,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(bya,X.shape).T, s=20)
ax.set_title('Sphere Ana By')
ax = plt.subplot(212)
plt.imshow(np.reshape(bza,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(bza,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(bza,X.shape).T, s=20)
ax.set_title('Sphere Ana Bz')
#%% Plot the forward solution from integral
plt.figure(2)
ax = plt.subplot(221)
plt.imshow(np.reshape(fwr_x,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max() ], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(fwr_x,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(fwr_x,X.shape).T, s=20)
ax.set_title('Sphere Ana Bx')
ax = plt.subplot(222)
plt.imshow(np.reshape(fwr_y,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(fwr_y,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(fwr_y,X.shape).T, s=20)
ax.set_title('Sphere Ana By')
ax = plt.subplot(212)
plt.imshow(np.reshape(fwr_z,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(fwr_z,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(fwr_z,X.shape).T, s=20)
ax.set_title('Sphere Ana Bz')
#%% Plot foward data
plt.figure(3)
ax = plt.subplot(221)
plt.imshow(np.reshape(r_Bx,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(r_Bx,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(r_Bx,X.shape).T, s=20)
ax.set_title('Sphere Ana Bx')
ax = plt.subplot(222)
plt.imshow(np.reshape(r_By,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(r_By,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(r_By,X.shape).T, s=20)
ax.set_title('Sphere Ana By')
ax = plt.subplot(212)
plt.imshow(np.reshape(r_Bz,X.shape).T, interpolation="bicubic", extent=[xr.min(), xr.max(), yr.min(), yr.max()], origin = 'lower')
plt.colorbar(fraction=0.04)
plt.contour(X,Y, np.reshape(r_Bz,X.shape).T,10)
plt.scatter(X,Y, c=np.reshape(r_Bz,X.shape).T, s=20)
ax.set_title('Sphere Ana Bz')
plt.show()
simpegPF/Dev/MAG/Block_sphere_model.sus
+44180
View File
File diff suppressed because it is too large Load Diff
simpegPF/Dev/MAG/Gaussian.topo
+21610
View File
File diff suppressed because it is too large Load Diff
simpegPF/Dev/Intgrl_MAG_Inv_Driver.py → simpegPF/Dev/MAG/Intgrl_MAG_Inv_Driver.py
+91 -70
View File
@@ -6,8 +6,9 @@ import pylab as plt
import os
#home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev'
#home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Block_Gaussian_topo'
#home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Nut_Cracker\\Induced_MAG3C'
home_dir = '.\\'
#home_dir = '.\\'
inpfile = 'PYMAG3D_inv.inp'
@@ -16,31 +17,32 @@ os.chdir(home_dir)
## New scripts to be added to basecode
#from fwr_MAG_data import fwr_MAG_data
#from read_MAGfwr_inp import read_MAGfwr_inp
plt.close('all')
#%%
# Read input file
[mshfile, obsfile, topofile, mstart, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms] = PF.BaseMag.read_MAGinv_inp(home_dir + dsep + inpfile)
[mshfile, obsfile, topofile, mstart, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms] = PF.Magnetics.read_MAGinv_inp(home_dir + dsep + inpfile)
# Load mesh file
mesh = Mesh.TensorMesh.readUBC(mshfile)
#mesh = Utils.meshutils.readUBCTensorMesh(mshfile)
# Load in observation file
[B,M,dobs] = PF.BaseMag.readUBCmagObs(obsfile)
survey = PF.Magnetics.readUBCmagObs(obsfile)
rxLoc = dobs[:,0:3]
d = dobs[:,3]
wd = dobs[:,4]
rxLoc = survey.srcField.rxList[0].locs
d = survey.dobs
wd = survey.std
ndata = rxLoc.shape[0]
beta_in = 1e+2
ndata = survey.srcField.rxList[0].locs.shape[0]
beta_in = 1e+5
eps_p = 1e-4
eps_q = 1e-4
# Load in topofile or create flat surface
if topofile == 'null':
# All active
actv = np.ones(mesh.nC)
actv = np.asarray(range(mesh.nC))
else:
@@ -48,26 +50,33 @@ else:
# Find the active cells
actv = PF.Magnetics.getActiveTopo(mesh,topo,'N')
nC = int(sum(actv))
nC = len(actv)
# Create active map to go from reduce set to full
actvMap = Maps.ActiveCells(mesh, actv, -100)
# Creat reduced identity map
idenMap = Maps.IdentityMap(nP = nC)
# Load starting model file
if isinstance(mstart, float):
mstart = np.ones(nC) * mstart
else:
mstart = Utils.meshutils.readUBCTensorModel(mstart,mesh)
mstart = mstart[actv==1]
mstart = mstart[actv]
# Load reference file
if isinstance(mref, float):
mref = np.ones(nC) * mref
else:
mref = Utils.meshutils.readUBCTensorModel(mref,mesh)
mref = mref[actv==1]
mref = mref[actv]
# Get magnetization vector for MOF
if magfile=='DEFAULT':
M_xyz = PF.Magnetics.dipazm_2_xyz(np.ones(nC) * M[0], np.ones(nC) * M[1])
M_xyz = PF.Magnetics.dipazm_2_xyz(np.ones(nC) * survey.srcField.param[1], np.ones(nC) * survey.srcField.param[2])
else:
M_xyz = np.genfromtxt(magfile,delimiter=' \n',dtype=np.str,comments='!')
@@ -76,54 +85,52 @@ else:
midx = int(mesh.nCx/2)
midy = int(mesh.nCy/2)
# Create forward operator
F = PF.Magnetics.Intrgl_Fwr_Op(mesh,B,M_xyz,rxLoc,actv,'tmi')
# Get distance weighting function
wr = PF.Magnetics.get_dist_wgt(mesh,rxLoc,actv,3.,np.min(mesh.hx)/4)
wrMap = PF.BaseMag.WeightMap(mesh, wr)
#==============================================================================
# wr = PF.Magnetics.get_dist_wgt(mesh,rxLoc,actv,3.,np.min(mesh.hx)/4)
# #wrMap = PF.BaseMag.WeightMap(nC, wr)
#==============================================================================
wr_out = np.zeros(mesh.nC)
wr_out[actv==1] = wr
Mesh.TensorMesh.writeModelUBC(mesh,home_dir+dsep+'wr.dat',wr_out)
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
#%% Plot obs data
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
#%% Run inversion
prob = PF.Magnetics.MagneticIntegral(mesh, mapping = idenMap, actInd = actv)
prob.solverOpts['accuracyTol'] = 1e-4
#survey = Survey.LinearSurvey()
survey.pair(prob)
#survey.makeSyntheticData(data, std=0.01)
#survey.dobs=d
#survey.mtrue = model
# Write out the predicted
pred = F.dot(mstart)
PF.Magnetics.writeUBCobs(home_dir + dsep + 'Pred.dat',B,M,rxLoc,pred,wd)
pred = prob.fields(mstart)
PF.Magnetics.writeUBCobs(home_dir + dsep + 'Pred.dat',survey,pred)
wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
wr = ( wr/np.max(wr) )
wr_out = actvMap * wr
#%%
plt.figure()
ax = plt.subplot()
mesh.plotSlice(wr_out, ax = ax, normal = 'Y', ind=midx )
mesh.plotSlice(wr_out, ax = ax, normal = 'Y', ind=midx ,clim = (-1e-3, wr.max()))
plt.title('Distance weighting')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
#%% Plot obs data
PF.Magnetics.plot_obs_2D(rxLoc,d,wd,'Observed Data')
#%% Run inversion
prob = PF.Magnetics.MagneticIntegral(mesh, F)
prob.solverOpts['accuracyTol'] = 1e-4
survey = Survey.LinearSurvey()
survey.pair(prob)
#survey.makeSyntheticData(data, std=0.01)
survey.dobs=d
#survey.mtrue = model
reg = Regularization.Simple(mesh, mapping=wrMap)
reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap)
reg.mref = mref
reg.wght = wr
#reg.alpha_s = 1.
# Create pre-conditioner
diagA = np.sum(F**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()*(wr**2.0)
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = wd
opt = Optimization.ProjectedGNCG(maxIter=10,lower=0.,upper=1.)
dmis.Wd = 1/wd
opt = Optimization.ProjectedGNCG(maxIter=10,lower=0.,upper=1., maxIterCG= 20, tolCG = 1e-3)
opt.approxHinv = PC
# opt = Optimization.InexactGaussNewton(maxIter=6)
@@ -139,16 +146,14 @@ m0 = mstart
# Run inversion
mrec = inv.run(m0)
m_out = np.ones(mesh.nC)
m_out[actv==1] = mrec
m_out = actvMap*mrec
# Write result
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l2l2.sus',m_out)
#Utils.meshutils.writeUBCTensorModel(home_dir+dsep+'wr.dat',mesh,wr_out)
# Plot predicted
pred = F.dot(mrec)
pred = prob.fields(mrec)
#PF.Magnetics.plot_obs_2D(rxLoc,pred,wd,'Predicted Data')
#PF.Magnetics.plot_obs_2D(rxLoc,(d-pred),wd,'Residual Data')
@@ -156,87 +161,103 @@ print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out a section of the model
yslice = midx-7
yslice = midx
m_out[m_out==-100] = np.nan
plt.figure()
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z Section')
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-1, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Top')
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
plt.title('Cross Section')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
#%% Run one more round for sparsity
phim = invProb.phi_m_last
phid = invProb.phi_d
reg = Regularization.SparseRegularization(mesh, mapping=wrMap, eps=1e-4)
reg.m = mrec
reg = Regularization.Sparse(mesh, indActive = actv, mapping = idenMap)
reg.recModel = mrec
reg.mref = mref
reg.wght = wr
reg.eps_p = eps_p
reg.eps_q = eps_q
reg.norms = lpnorms
diagA = np.sum(F**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()*(wr**2.0)
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
#reg.alpha_s = 1.
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = wd
opt = Optimization.ProjectedGNCG(maxIter=8 ,maxIterLS=10, maxIterCG = 20,tolCG = 1e-4,lower=0.,upper=1.)
opt = Optimization.ProjectedGNCG(maxIter=20 ,lower=0.,upper=1., maxIterCG= 10, tolCG = 1e-4)
opt.approxHinv = PC
#opt.phim_last = reg.eval(mrec)
# opt = Optimization.InexactGaussNewton(maxIter=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = invProb.beta)
beta = Directives.BetaSchedule(coolingFactor=1, coolingRate=1)
update_beta = Directives.Scale_Beta(tol = 0.05)
#betaest = Directives.BetaEstimate_ByEig()
target = Directives.TargetMisfit()
IRLS =Directives.update_IRLS( eps_min=1e-3, phi_m_last = phim )
IRLS =Directives.Update_IRLS( phi_m_last = phim, phi_d_last = phid )
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS])
inv = Inversion.BaseInversion(invProb, directiveList=[beta,IRLS,update_beta])
m0 = mrec
# Run inversion
mrec = inv.run(m0)
m_out[actv==1] = mrec
m_out = actvMap*mrec
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_inv_l0l2.sus',m_out)
pred = prob.fields(mrec)
#%% Plot obs data
PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data')
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
print "Final misfit:" + str(np.sum( ((d-pred)/wd)**2. ) )
#%% Plot out a section of the model
yslice = midx-7
yslice = midx
m_out[m_out==-100] = np.nan
plt.figure()
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z Section')
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-1, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = (mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Top')
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (-mrec.min(), mrec.max()))
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = (mrec.min(), mrec.max()))
plt.title('Cross Section')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
simpegPF/Dev/MAG/Mag_Inv_Param.py
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# -*- coding: utf-8 -*-
"""
Created on Wed Feb 03 21:34:50 2016
@author: dominiquef
"""
from SimPEG import *
import simpegPF as PF
from simpegPF import BaseMag as MAG
from numpy.polynomial import polynomial
import pylab as plt
import os
#home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\Documents\GIT\SimPEG\simpegpf\simpegPF\Dev'
#home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\ownCloud\\Research\\Modelling\\Synthetic\\Parametric_plane'
#home_dir = 'C:\\LC\\Private\\dominiquef\\Projects\\4414_Minsim\\Modeling\\MAG\\Lalor'
#home_dir = 'C:\Users\dominiquef.MIRAGEOSCIENCE\ownCloud\Research\Nate\Modeling'
home_dir = 'C:\\Users\\dominiquef.MIRAGEOSCIENCE\\Google Drive\\DevDomNateDBE\\DomNate\\Fault_synthetic\\NE'
#home_dir = '.\\'
plt.close('all')
inpfile = 'PYMAG3D_inv.inp'
dsep = '\\'
os.chdir(home_dir)
## New scripts to be added to basecode
#from fwr_MAG_data import fwr_MAG_data
#from read_MAGfwr_inp import read_MAGfwr_inp
beta_in = 1e+0
ndv = -100
#%%
# Read input file
[mshfile, obsfile, topofile, m0_val, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms] = PF.Magnetics.read_MAGinv_inp(home_dir + dsep + inpfile)
#obsfile = 'Synthetic.obs'
#obsfile ='Lalor_rtp_2pc_10nT_RegRem.obs'
#obsfile = 'Obs_ALL.obs'
# Discretization for new mesh
dx = 50.
# Load mesh file
mesh = Mesh.TensorMesh.readUBC(mshfile)
z0 = mesh.x0[2] + np.sum(mesh.hz)
#mesh = Utils.meshutils.readUBCTensorMesh(mshfile)
#V2D = polynomial.polyvander2d(mesh.vectorCCx,mesh.vectorCCy,[1,1])
# Load in observation file
survey = PF.Magnetics.readUBCmagObs(obsfile)
rxLoc_full = survey.srcField.rxList[0].locs
data = survey.dobs
wd = survey.std
npad = 10
#%% Pick points from dats and generate local mesh
PF.Magnetics.plot_obs_2D(rxLoc_full,data, levels = [0.])
#PF.Magnetics.plot_obs_2D(dobs[:,:3],dobs[:,3],dobs[:,4],'Observed Data')
gin = np.asarray(plt.ginput(100, timeout = 0))
#gin = np.asarray([[ -81.82517326, -167.83403552],
# [ -21.0157401 , 133.78075295]])
for ii in range(gin.shape[0]-1):
dl_len = np.sqrt( np.sum((gin[ii,:] - gin[ii+1,:])**2) )
dl_x = ( gin[ii,0] - gin[ii+1,0] ) / dl_len
dl_y = ( gin[ii+1,1] - gin[ii,1] ) / dl_len
azm = -np.arctan(dl_x/dl_y)
# Create rotation matrix
Rz = np.array([[np.cos(azm), -np.sin(azm)],
[np.sin(azm), np.cos(azm)]])
# Re-center the experiment
midx = np.median([gin[ii,0],gin[ii+1,0]])
midy = np.median([gin[ii+1,1],gin[ii,1]])
temp = np.vstack([rxLoc_full[:,0].T- midx, rxLoc_full[:,1].T- midy])
# Rotate
ROTxy = Rz.dot(temp)
# Grab data points within a box
indx = (np.abs(ROTxy[0,:]) < dl_len) & (np.abs(ROTxy[1,:]) < dl_len/2)
subrx = MAG.RxObs(np.c_[ROTxy[0,indx].T, ROTxy[1,indx].T, rxLoc_full[indx,2]])
d = data[indx]
uncert = wd[indx]
srcParam = np.asarray(survey.srcField.param)
srcParam[2] = srcParam[2] - np.rad2deg(azm)
srcField = MAG.SrcField([subrx],srcParam)
survey = MAG.LinearSurvey(srcField)
survey.dobs = d
survey.std = uncert
PF.Magnetics.writeUBCobs(home_dir+'\\Obsloc_local.dat',survey,survey.dobs)
rxLoc = survey.srcField.rxList[0].locs
PF.Magnetics.plot_obs_2D(rxLoc,d,'Observed Data')
ndata = rxLoc.shape[0]
# Get extent limits
xlim = np.max(np.abs(rxLoc[:,0]))
ylim = np.max(np.abs(rxLoc[:,1]))
ncx = int(4*xlim/dx)
ncy = int(2*ylim/dx)
ncz = int(np.min([ncx,ncy]))
hxind = [(dx,npad,-1.3),(dx, ncx),(dx,npad,1.3)]
hyind = [(dx,npad,-1.3),(dx, ncy),(dx,npad,1.3)]
hzind = [(dx,npad,-1.3),(dx, ncz)]
mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCN')
mesh.x0[2] = np.max(rxLoc[:,2]) - np.sum(mesh.hz) # Keep top of mesh at same location as before
Mesh.TensorMesh.writeUBC(mesh,home_dir+dsep+'Mesh_local.msh')
# Load in topofile or create flat surface
if topofile == 'null':
# All active
actv = np.asarray(range(mesh.nC))
else:
topo = np.genfromtxt(topofile,skip_header=1)
temp = np.vstack([topo[:,0].T- midx, topo[:,1].T- midy])
# Rotate
ROTxy = Rz.dot(temp)
ROT_topo = np.c_[ROTxy[0,:].T, ROTxy[1,:].T, topo[:,2]]
# Find the active cells
actv = PF.Magnetics.getActiveTopo(mesh,ROT_topo,'N')
nC = len(actv)
idenMap = Maps.IdentityMap(nP = nC)
# Create active map to go from reduce set to full
actvMap = Maps.InjectActiveCells(mesh, actv, ndv)
# Load starting model file
# if isinstance(mstart, float):
mstart = np.ones(nC) * m0_val
# else:
# mstart = Utils.meshutils.readUBCTensorModel(mstart,mesh)
# mstart = mstart[actv]
# Get magnetization vector for MOF
if magfile=='DEFAULT':
M_xyz = PF.Magnetics.dipazm_2_xyz(np.ones(nC) * survey.srcField.param[1], np.ones(nC) * survey.srcField.param[2])
else:
M_xyz = np.genfromtxt(magfile,delimiter=' \n',dtype=np.str,comments='!')
# Get index of the center
#==============================================================================
# midx = int(mesh.nCx/2)
# midy = int(mesh.nCy/2)
#==============================================================================
# Create forward operator
#F = PF.Magnetics.Intrgl_Fwr_Op(mesh,B,M_xyz,rxLoc,actv,'tmi')
#%% Run inversion
# First start with regular inversion for regional removal
prob = PF.Magnetics.MagneticIntegral(mesh, mapping = idenMap, actInd = actv)
prob.solverOpts['accuracyTol'] = 1e-4
survey.pair(prob)
#%%
pred = prob.fields(mstart)
wr = np.sum(prob.G**2.,axis=0)**0.5 / mesh.vol[actv]
wr = ( wr/np.max(wr) )
#IWr = Utils.sdiag(1/wr)
#wrMap = PF.BaseMag.WeightMap(mesh, wr)
#prob.mapping = wrMap
#prob._G = prob._G * IWr
reg = Regularization.Simple(mesh, indActive = actv, mapping = idenMap)
reg.mref = 0.
reg.wght = wr
#reg.alpha_s = 1.
# Create pre-conditioner
diagA = np.sum(prob.G**2.,axis=0) + beta_in*(reg.W.T*reg.W).diagonal()
PC = Utils.sdiag(diagA**-1.)
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./survey.std
opt = Optimization.ProjectedGNCG(maxIter=10,lower=0.,upper=1., maxIterCG= 20, tolCG = 1e-3)
opt.approxHinv = PC
# opt = Optimization.InexactGaussNewton(maxIter=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
#betaest = Directives.BetaEstimate_ByEig()
target = Directives.TargetMisfit()
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target])
m0 = mstart
# Run inversion
mrec = inv.run(m0)
m_out = actvMap*mrec
#%% Temporary plotting scipts
yslice = 14
plt.figure()
ax = plt.subplot(221)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-5, clim = (mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-5]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(222)
mesh.plotSlice(m_out, ax = ax, normal = 'Z', ind=-8, clim = ( mrec.min(), mrec.max()))
plt.plot(np.array([mesh.vectorCCx[0],mesh.vectorCCx[-1]]), np.array([mesh.vectorCCy[yslice],mesh.vectorCCy[yslice]]),c='w',linestyle = '--')
plt.title('Z: ' + str(mesh.vectorCCz[-8]) + ' m')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
ax = plt.subplot(212)
mesh.plotSlice(m_out, ax = ax, normal = 'Y', ind=yslice, clim = ( mrec.min(), mrec.max()))
plt.title('Cross Section')
plt.xlabel('x');plt.ylabel('z')
plt.gca().set_aspect('equal', adjustable='box')
#%% Remove core cells and forward model
m_out = np.reshape(m_out,(mesh.nCx,mesh.nCy,mesh.nCz), order = 'F')
m_out[npad:-npad,npad:-npad,npad:] = m_out[npad:-npad,npad:-npad,npad:]*0.
m_out = mkvc(m_out)
m_pad = m_out[actv]
Mesh.TensorMesh.writeModelUBC(mesh,home_dir+'\\SimPEG_Inv_l2l2.sus',actvMap*mrec)
Mesh.TensorMesh.writeModelUBC(mesh,home_dir+'\\SimPEG_Scooped.sus',actvMap*m_pad)
# Forward model the fields and substract from data
fwr = prob.fields(m_pad)
d_res = survey.dobs - fwr
PF.Magnetics.plot_obs_2D(rxLoc,fwr,'Forward Scoop Data', levels = [0.])
PF.Magnetics.plot_obs_2D(rxLoc,d_res,'RegRem Data', levels = [0.])
survey.dobs = d_res
#%% Reduce the space to only the core region
# Create new mesh for local inversion
hxind = [(dx, ncx)]
hyind = [(dx, ncy)]
hzind = [(dx, ncz)]
x0 = mesh.x0
z0 = x0[2] + np.sum(mesh.hz)
mesh = Mesh.TensorMesh([hxind, hyind, hzind], 'CCN')
mesh.x0[2] = z0 - np.sum(mesh.hz)
core = m_out==0
grnd = core[actv]
inds = np.asarray([inds for inds, elem in enumerate(grnd, 1) if elem], dtype = int) - 1
#%% Re-run with poly map
# Load in topofile or create flat surface
if topofile == 'null':
# All active
actv = np.asarray(range(mesh.nC))
else:
topo = np.genfromtxt(topofile,skip_header=1)
temp = np.vstack([topo[:,0].T- midx, topo[:,1].T- midy])
# Rotate
ROTxy = Rz.dot(temp)
ROT_topo = np.c_[ROTxy[0,:].T, ROTxy[1,:].T, topo[:,2]]
# Find the active cells
actv = PF.Magnetics.getActiveTopo(mesh,ROT_topo,'N')
nC = len(actv)
idenMap = Maps.IdentityMap(nP = nC)
# Create active map to go from reduce set to full
actvMap = Maps.InjectActiveCells(mesh, actv, ndv)
# Load starting model file
mstart = np.ones(nC) * m0_val
#%% Invert with polymap for plane
#
#
# Create active map to go from reduce set to full
#actvMap = Maps.ActiveCells(mesh, actv, -100)
#
## Creat reduced identity map
#idenMap = Maps.IdentityMap(nP = nC)
#
XYZ = mesh.gridCC
order = [1,1]
YZ = Utils.ndgrid(mesh.vectorCCy, mesh.vectorCCz)
V = polynomial.polyvander2d(YZ[:,0], YZ[:,1], order)
#f = polynomial.polyval2d(XYZ[:,1], XYZ[:,2], c.reshape((order[0]+1,order[1]+1))) - XYZ[:,0]
polymap = Maps.PolyMap(mesh, order, normal='X', logSigma=False, actInd = actv)
polymap.slope = 1.0
#polymap.actInd = actv
#m0 = np.r_[1e-2, 0., 0.0, -0.5, 0.2, 0.]
m0 = np.r_[1e-4, 0, 1., 0., 0., 0.]
#Mesh.TensorMesh.writeModelUBC(mesh,home_dir+dsep+'True_m.sus',polymap*m0)
#Mesh.TensorMesh.writeModelUBC(mesh,home_dir+dsep+'Starting_m.sus',actvMap*polymap*m0)
m1D = Mesh.TensorMesh([(order[0]+1)*(order[1]+1)+2])
weight = ((V**2).sum(axis=0))**0.5
weight = weight / weight.max()
prob_core = PF.Magnetics.MagneticIntegral(mesh, mapping = idenMap*polymap, actInd = actv)
prob_core.solverOpts['accuracyTol'] = 1e-4
survey.pair(prob_core)
#prob_core._G = prob.G[:,inds]
#%%
pred = prob_core.fields(m0)
wr = np.sum(prob_core.G**2.,axis=0)**0.5 / mesh.vol[actv]
wr = ( wr/np.max(wr) )
IWr = Utils.sdiag(1/wr)
wrMap = PF.BaseMag.WeightMap(mesh, wr)
prob_core.mapping = wrMap * polymap
prob_core._G = prob_core.G * IWr
reg = Regularization.Simple(m1D)
reg.alpha_x = 0.
reg.alpha_y = 0.
reg.alpha_z = 0.
reg.norms = [2., 2., 2., 2.]
#reg.mref = np.r_[0., 1., 421500., 1000., 10., 0.5]
reg.mref = np.zeros(6)
#==============================================================================
# reg.wght = np.asarray([ 1.00000000e+00 ,6.50176844e-01 ,4.20328370e-06 ,1.52004209e-03,
# 4.82475226e-05 ,1.37620903e-02])**2.
#==============================================================================
lower = np.r_[0.,0.,-1e+8,-1e+8,-1e+8,-1e+8]
upper = np.r_[1.,1.,1e+8,1e+8,1e+8,1e+8]
#reg.mref = mref
#reg.alpha_s = 1.
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = 1./survey.std
opt = Optimization.ProjectedGNCG(maxIter=15,maxIterLS=50, maxIterCG = 10,tolCG = 1e-3, lower = lower,upper=upper)
#opt.approxHinv = sp.eye(6)
beta_in = 1e+2
# opt = Optimization.InexactGaussNewton(maxIter=6)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt, beta = beta_in)
beta = Directives.BetaSchedule(coolingFactor=2, coolingRate=1)
#betaest = Directives.BetaEstimate_ByEig()
target = Directives.TargetMisfit()
up_Wj = Directives.Update_Wj()
up_Wj.itr = 2
inv = Inversion.BaseInversion(invProb, directiveList=[beta,target,up_Wj])
#m0 = mstart
#Utils.diagEst(prob.Jtvec,2)
# Run inversion
mrec = inv.run(m0)
sus = polymap*mrec
m_out = actvMap * sus
# Write result
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_Param.sus',m_out)
Mesh.TensorMesh.writeUBC(mesh,'Working_mesh.msh')
m_out = actvMap *polymap*m0
Mesh.TensorMesh.writeModelUBC(mesh,'SimPEG_Param_m0.sus',m_out)
# Plot predicted
pred = prob_core.fields(mrec)
PF.Magnetics.plot_obs_2D(rxLoc,pred,'Predicted Data', vmin = np.min(survey.dobs), vmax = np.max(survey.dobs))
PF.Magnetics.plot_obs_2D(rxLoc,survey.dobs-pred,'Residual Data')
#PF.Magnetics.writeUBCobs(home_dir + dsep + 'Pred_Final.pre',B,M,rxLoc,pred,np.ones(len(d)))
print "Final misfit:" + str(np.sum( ((d-pred)/uncert)**2. ) )
#%% Write parametric surface
yz = Utils.ndgrid(np.r_[-ncy/2*dx,0,ncy/2*dx],np.r_[mesh.vectorCCz[-1],mesh.vectorCCz[0]])
xout = polynomial.polyval2d(yz[:,0],yz[:,1],np.reshape(mrec[2:],(2,2)))
xyz = np.c_[xout,yz]
# Rotate back to global coordinates
# Create rotation matrix
Rz = np.array([[np.cos(-azm), -np.sin(-azm)],
[np.sin(-azm), np.cos(-azm)]])
temp = Rz.dot( np.vstack([xyz[:,0].T, xyz[:,1].T]) )
if ii == 0:
# Rotate
ROTxyz = np.c_[temp[0,:].T + midx, temp[1,:].T + midy, xyz[:,2]]
else:
ROTxyz = np.vstack([ROTxyz,np.c_[temp[0,:].T + midx, temp[1,:].T + midy, xyz[:,2]]])
#Write out the surface
with file(home_dir + dsep + 'Surf.dat','w') as fid:
np.savetxt(fid, ROTxyz, fmt='%e',delimiter=' ',newline='\n')
#%% Right GOCAD ts file
with file(home_dir + dsep + 'Surf.ts','w') as fid:
fid.write('GOCAD TSurf 1\n')
fid.write('HEADER {name:Mag_Param}\n')
fid.write('TFACE\n')
for ii in range(ROTxyz.shape[0]):
fid.write('VRTX %i %6.2f %6.2f %6.2f\n' %(ii+1, ROTxyz[ii,0],ROTxyz[ii,1],ROTxyz[ii,2]) )
for ii in range(ROTxyz.shape[0]/3):
fid.write('TRGL %i %i %i\n' %(ii+1, ii+2, np.mod(ii+3,6)+1 ))
fid.write('TRGL %i %i %i\n' %(ii+2, np.mod(ii+3,6)+1, np.mod(ii+4,6)+1 ))
fid.write('END\n')
simpegPF/Dev/MAG/Mesh_10m.msh
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47 47 20
-60.00 -60.00 280.00
50.00 30.00 20.00 41*10.00 20.00 30.00 50.00
50.00 30.00 20.00 41*10.00 20.00 30.00 50.00
17*10.00 20.00 30.00 50
simpegPF/Dev/MAG/Obs_loc_TMI.obs
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90 0 50000
90 0 1
616
105 155 240.831177 -0.7588417 1
115 155 244.046936 -0.7915504 1
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simpegPF/Dev/PYMAG3D_inv.inp → simpegPF/Dev/MAG/PYMAG3D_inv.inp
+4 -4
View File
@@ -1,6 +1,6 @@
Mesh_40m.msh ! Mesh file
Obs_IND_GRID_TMI.obs ! Obsfile
null ! Topofile | null
Mesh_10m.msh ! Mesh file
Obs_loc_TMI.obs ! Obsfile
Gaussian.topo ! Topofile | null
VALUE 1e-4 ! Starting model
VALUE 0 ! Reference model
DEFAULT !..\AzmDip.dat ! Magnetization vector model
@@ -8,4 +8,4 @@ DEFAULT ! Cell based weight file
1 ! target chi factor | DEFAULT=1
1 1 1 1 ! alpha s, x ,y ,z
VALUE 0 1 ! Lower and Upper Bounds for p-component
VALUE 0 2 2 2 1 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
VALUE 0 1 1 1 1 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
simpegPF/Dev/MAG/Pred.dat
+619
View File
@@ -0,0 +1,619 @@
0.00 90.00 50000.00
0.00 90.00 1.00
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simpegPF/Dev/MAG/SimPEG_inv_l0l2.sus
+44180
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simpegPF/Dev/MAG/SimPEG_inv_l2l2.sus
+44180
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simpegPF/Dev/MAG3Cfwr.inp
-5
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@@ -1,5 +0,0 @@
Mesh.msh ! Mesh file
Obs_loc.dat ! Obsfile
Model.dat ! Susceptibility model
null ! M_azm_dip.dat ! Magnetization model | null
null ! Topography file | null
simpegPF/Dev/MAG3Csen.inp
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Mesh.msh ! Mesh file
Obs_loc.dat ! Obsfile
null ! Topofile | null
DISTANCE ! weighting flag DISTANCE | DEPTH
G ! Define output TxTyTz | G
simpegPF/Dev/MAG3Csen.log
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MAG3Csen
Generates sparse matrices for magnetostatic forward modeling: Tx, Ty, Tz
Topographic model: nullcell.dat
DISTANCE | DEPTH weighting: wr.dat
Written by: Dominique Fournier
Last update: July 14th, 2014
INPUT FILES:
Mesh: Mesh.msh
Obsfile: Obs_loc.dat
Topography:
Weighting: DISTANCE
Computed 0 pct of data in 0.04128 sec
Computed 5 pct of data in 0.04634 sec
Computed 10 pct of data in 0.05386 sec
Computed 15 pct of data in 0.06035 sec
Computed 20 pct of data in 0.06507 sec
Computed 25 pct of data in 0.07160 sec
Computed 30 pct of data in 0.08211 sec
Computed 35 pct of data in 0.08901 sec
Computed 40 pct of data in 0.09365 sec
Computed 45 pct of data in 0.10179 sec
Computed 50 pct of data in 0.10963 sec
Computed 55 pct of data in 0.11704 sec
Computed 60 pct of data in 0.12449 sec
Computed 65 pct of data in 0.13205 sec
Computed 70 pct of data in 0.13838 sec
Computed 75 pct of data in 0.14311 sec
Computed 80 pct of data in 0.14761 sec
Computed 85 pct of data in 0.15447 sec
Computed 90 pct of data in 0.15941 sec
Computed 95 pct of data in 0.16424 sec
Computed 100 pct of data in 0.17136 sec
Sensitivity calculation completed in: 0.002860 min
simpegPF/Dev/MAG3D_inv.inp
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Mesh.msh ! Mesh file
FWR_data.dat ! Obsfile
null ! Topofile
Model.dat ! Starting model
VALUE 0.0 ! Reference model
DEFAULT !..\AzmDip.dat ! Magnetization vector model
DEFAULT ! Cell based weight file
1 ! target chi factor | DEFAULT=1
1 1 1 1 ! alpha s, x ,y ,z
VALUE 0 1 ! Lower and Upper Bounds for p-component
VALUE 0 2 2 2 1 ! lp-norm for amplitude inversion FILE pqxqyqzr.dat ! Norms VALUE p, qx, qy, qz, r | FILE m-by-5 matrix
simpegPF/Dev/MagForward_Intergral.ipynb
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simpegPF/Dev/Mesh.msh
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20 20 20
-0.50 -0.50 0.50
0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05
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simpegPF/Dev/Mesh_40m.msh
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38 31 12
421780.00 544950.00 1600.00
151.00 108.00 77.00 55.00 30*40.00 55.00 77.00 108.00 151.00
151.00 108.00 77.00 55.00 23*40.00 55.00 77.00 108.00 151.00
12*40.00
simpegPF/Dev/Model.dat
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simpegPF/Dev/Obs_IND_GRID_TMI.obs
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90.00 0.00 50000.00
90.00 0.00 1.00
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simpegPF/Dev/SimPEG_inv.sus
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simpegPF/Dev/SimPEG_inv_l0l2.sus
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simpegPF/Dev/SimPEG_inv_l2l2.sus
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simpegPF/Dev/Tile1.msh
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66 52 24
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simpegPF/Dev/magfor3d.log
-31
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@@ -1,31 +0,0 @@
Parallelized with OpenMP. # of threads: 4
MAG3D - Version 5.0 : MAGFOR3D
Developed by University of British Columbia
Geophysical Inversion Facility (UBC-GIF)
(C) Copyright 1992 - 2013, UBC-GIF,
Department of Earth and Ocean Sciences, UBC
http://gif.eos.ubc.ca/
This program is licensed to:
For internal use within UBC-GIF.
MAGFOR3D started on: 12/21/2015 08:35:38
magfor3d Mesh.msh Obs_loc.dat Model.dat
# of surface data: 625
# of borehole data: 0
model was read from file: Model.dat
TOTAL cpu time: 0:00:00.16
MAGFOR3D ended on: 12/21/2015 08:35:39
simpegPF/Dev/magfor3d.mag
-628
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45.00 315.00 50000.00 !! incl, decl, geomag
-45.00 135.00 1 !! aincl, adecl, idir
625 !! # of data
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4.166670000E-01 5.000000000E-01 5.500000000E-01 2.226649E+02
4.583330000E-01 -5.000000000E-01 5.500000000E-01 -8.099267E+02
4.583330000E-01 -4.583330000E-01 5.500000000E-01 -8.848866E+02
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4.583330000E-01 -3.750000000E-01 5.500000000E-01 -1.029956E+03
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4.583330000E-01 -1.666670000E-01 5.500000000E-01 -1.196510E+03
4.583330000E-01 -1.250000000E-01 5.500000000E-01 -1.165985E+03
4.583330000E-01 -8.333330000E-02 5.500000000E-01 -1.109314E+03
4.583330000E-01 -4.166670000E-02 5.500000000E-01 -1.027700E+03
4.583330000E-01 0.000000000E+00 5.500000000E-01 -9.243473E+02
4.583330000E-01 4.166670000E-02 5.500000000E-01 -8.041995E+02
4.583330000E-01 8.333330000E-02 5.500000000E-01 -6.734053E+02
4.583330000E-01 1.250000000E-01 5.500000000E-01 -5.386001E+02
4.583330000E-01 1.666670000E-01 5.500000000E-01 -4.061587E+02
4.583330000E-01 2.083330000E-01 5.500000000E-01 -2.815633E+02
4.583330000E-01 2.500000000E-01 5.500000000E-01 -1.689640E+02
4.583330000E-01 2.916670000E-01 5.500000000E-01 -7.102407E+01
4.583330000E-01 3.333330000E-01 5.500000000E-01 1.103644E+01
4.583330000E-01 3.750000000E-01 5.500000000E-01 7.722713E+01
4.583330000E-01 4.166670000E-01 5.500000000E-01 1.284713E+02
4.583330000E-01 4.583330000E-01 5.500000000E-01 1.662941E+02
4.583330000E-01 5.000000000E-01 5.500000000E-01 1.925379E+02
5.000000000E-01 -5.000000000E-01 5.500000000E-01 -7.461582E+02
5.000000000E-01 -4.583330000E-01 5.500000000E-01 -8.099267E+02
5.000000000E-01 -4.166670000E-01 5.500000000E-01 -8.722184E+02
5.000000000E-01 -3.750000000E-01 5.500000000E-01 -9.305613E+02
5.000000000E-01 -3.333330000E-01 5.500000000E-01 -9.820190E+02
5.000000000E-01 -2.916670000E-01 5.500000000E-01 -1.023319E+03
5.000000000E-01 -2.500000000E-01 5.500000000E-01 -1.051072E+03
5.000000000E-01 -2.083330000E-01 5.500000000E-01 -1.062073E+03
5.000000000E-01 -1.666670000E-01 5.500000000E-01 -1.053680E+03
5.000000000E-01 -1.250000000E-01 5.500000000E-01 -1.024210E+03
5.000000000E-01 -8.333330000E-02 5.500000000E-01 -9.732772E+02
5.000000000E-01 -4.166670000E-02 5.500000000E-01 -9.020055E+02
5.000000000E-01 0.000000000E+00 5.500000000E-01 -8.130400E+02
5.000000000E-01 4.166670000E-02 5.500000000E-01 -7.103443E+02
5.000000000E-01 8.333330000E-02 5.500000000E-01 -5.987970E+02
5.000000000E-01 1.250000000E-01 5.500000000E-01 -4.836628E+02
5.000000000E-01 1.666670000E-01 5.500000000E-01 -3.700392E+02
5.000000000E-01 2.083330000E-01 5.500000000E-01 -2.623794E+02
5.000000000E-01 2.500000000E-01 5.500000000E-01 -1.641466E+02
5.000000000E-01 2.916670000E-01 5.500000000E-01 -7.767438E+01
5.000000000E-01 3.333330000E-01 5.500000000E-01 -4.169920E+00
5.000000000E-01 3.750000000E-01 5.500000000E-01 5.615031E+01
5.000000000E-01 4.166670000E-01 5.500000000E-01 1.038361E+02
5.000000000E-01 4.583330000E-01 5.500000000E-01 1.399730E+02
5.000000000E-01 5.000000000E-01 5.500000000E-01 1.659610E+02
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0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 4.000000000000000000e+00
0.000000000000000000e+00 1.000000000000000000e+00 2.000000000000000000e+00 3.000000000000000000e+00 4.000000000000000000e+00
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simpegPF/Dev/wr.dat
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simpegPF/Gravity.py
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from SimPEG import *
import BaseGrav as GRAV
import re
class GravityIntegral(Problem.BaseProblem):
#surveyPair = Survey.LinearSurvey
storeG = True #: Store the forward matrix by default, otherwise just compute d
actInd = None #: Active cell indices provided
def __init__(self, mesh, mapping=None, **kwargs):
Problem.BaseProblem.__init__(self, mesh, mapping=mapping, **kwargs)
def fwr_op(self):
# Add forward function
# kappa = self.curModel.kappa TODO
sus = self.mapping*self.curModel
return self.G.dot(sus)
def fields(self, m):
self.curModel = m
total = np.zeros(self.survey.nRx)
induced = self.fwr_op()
# rem = self.rem
if induced is not None:
total += induced
return total
# return self.G.dot(self.mapping*(m))
def Jvec(self, m, v, f=None):
dmudm = self.mapping.deriv(m)
return self.G.dot(dmudm*v)
def Jtvec(self, m, v, f=None):
dmudm = self.mapping.deriv(m)
return dmudm.T * (self.G.T.dot(v))
@property
def G(self):
if not self.ispaired:
raise Exception('Need to pair!')
if getattr(self,'_G', None) is None:
self._G = self.Intrgl_Fwr_Op( 'z' )
return self._G
def Intrgl_Fwr_Op(self, flag):
"""
Gravity forward operator in integral form
flag = 'z' | 'xyz'
Return
_G = Linear forward modeling operation
Created on March, 15th 2016
@author: dominiquef
"""
# Find non-zero cells
#inds = np.nonzero(actv)[0]
if getattr(self, 'actInd', None) is not None:
if self.actInd.dtype=='bool':
inds = np.asarray([inds for inds, elem in enumerate(self.actInd, 1) if elem], dtype = int) - 1
else:
inds = self.actInd
else:
inds = np.asarray(range(self.mesh.nC))
nC = len(inds)
# Create active cell projector
P = sp.csr_matrix((np.ones(nC),(inds, range(nC))),
shape=(self.mesh.nC, nC))
# Create vectors of nodal location (lower and upper coners for each cell)
xn = self.mesh.vectorNx;
yn = self.mesh.vectorNy;
zn = self.mesh.vectorNz;
yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
yn1,xn1,zn1 = np.meshgrid(yn[0:-1], xn[0:-1], zn[0:-1])
Yn = P.T*np.c_[mkvc(yn1), mkvc(yn2)]
Xn = P.T*np.c_[mkvc(xn1), mkvc(xn2)]
Zn = P.T*np.c_[mkvc(zn1), mkvc(zn2)]
rxLoc = self.survey.srcField.rxList[0].locs
ndata = rxLoc.shape[0]
# Pre-allocate space and create magnetization matrix if required
# Pre-allocate space
if flag == 'z':
G = np.zeros((ndata, nC))
elif flag == 'xyz':
G = np.zeros((int(3*ndata), nC))
else:
print """Flag must be either 'z' | 'xyz', please revised"""
return
# Loop through all observations and create forward operator (ndata-by-nC)
print "Begin calculation of forward operator: " + flag
# Add counter to dsiplay progress. Good for large problems
count = -1;
for ii in range(ndata):
if flag=='z':
tt = get_T_mat(Xn,Yn,Zn,rxLoc[ii,:])
G[ii,:] = tt
elif flag == 'xyz':
print "Sorry 3-component not implemented yet"
# Display progress
count = progress(ii,count,ndata)
print "Done 100% ...forward operator completed!!\n"
return G
def get_T_mat(Xn,Yn,Zn,rxLoc):
"""
Load in the active nodes of a tensor mesh and computes the gravity tensor
for a given observation location rxLoc[obsx, obsy, obsz]
INPUT:
Xn, Yn, Zn: Node location matrix for the lower and upper most corners of
all cells in the mesh shape[nC,2]
M
OUTPUT:
Tx = [Txx Txy Txz]
Ty = [Tyx Tyy Tyz]
Tz = [Tzx Tzy Tzz]
where each elements have dimension 1-by-nC.
Only the upper half 5 elements have to be computed since symetric.
Currently done as for-loops but will eventually be changed to vector
indexing, once the topography has been figured out.
Created on Oct, 20th 2015
@author: dominiquef
"""
NewtG=6.6738e-3
eps = 1e-10 # add a small value to the locations to avoid /0
nC = Xn.shape[0]
# Pre-allocate space for 1D array
T = np.zeros((1,nC))
dz = rxLoc[2] - Zn + eps
dy = Yn - rxLoc[1] + eps
dx = Xn - rxLoc[0] + eps
# Compute contribution from each corners
for aa in range(2):
for bb in range(2):
for cc in range(2):
r = (dx[:,aa] ** 2 + dy[:,bb] ** 2 + dz[:,cc] ** 2) ** (0.50)
T = T - NewtG * (-1) ** aa * (-1) ** bb * (-1) ** cc * (dx[:,aa] * np.log ( dy[:,bb] + r ) + dy[:,bb] * np.log ( dx[:,aa] + r ) - dz[:,cc] * np.arctan ( dx[:,aa] * dy[:,bb] / ( dz[:,cc] * r )))
return T
def progress(iter,prog,final):
"""
progress(iter,prog,final)
Function measuring the progress of a process and print to screen the %.
Useful to estimate the remaining runtime of a large problem.
Created on Dec, 20th 2015
@author: dominiquef
"""
arg = np.floor(float(iter)/float(final)*10.);
if arg > prog:
strg = "Done " + str(arg*10) + " %"
print strg
prog = arg;
return prog
def writeUBCobs(filename,survey,d):
"""
writeUBCobs(filename,survey,d)
Function writing an observation file in UBC-GRAV3D format.
INPUT
filename : Name of out file including directory
survey
flag : dobs | dpred
OUTPUT
Obsfile
Created on Dec, 27th 2015
@author: dominiquef
"""
rxLoc = survey.srcField.rxList[0].locs
wd = survey.std
data = np.c_[rxLoc , d , wd]
with file(filename,'w') as fid:
fid.write('%i\n' %len(d) )
np.savetxt(fid, data, fmt='%e',delimiter=' ',newline='\n')
print "Observation file saved to: " + filename
def getActiveTopo(mesh,topo,flag):
"""
getActiveTopo(mesh,topo)
Function creates an active cell model from topography
INPUT
mesh : Mesh in SimPEG format
topo : Scatter points defining topography [x,y,z]
OUTPUT
actv : Active cell model
Created on Dec, 27th 2015
@founrdo
"""
import scipy.interpolate as interpolation
if (flag=='N'):
Zn = np.zeros((mesh.nNx,mesh.nNy))
# wght = np.zeros((mesh.nNx,mesh.nNy))
cx = mesh.vectorNx
cy = mesh.vectorNy
F = interpolation.NearestNDInterpolator(topo[:,0:2],topo[:,2])
[Y,X] = np.meshgrid(cy,cx)
Zn = F(X,Y)
actv = np.zeros((mesh.nCx, mesh.nCy, mesh.nCz))
if (flag=='N'):
Nz = mesh.vectorNz[1:]
for jj in range(mesh.nCy):
for ii in range(mesh.nCx):
temp = [kk for kk in range(len(Nz)) if np.all(Zn[ii:(ii+2),jj:(jj+2)] > Nz[kk]) ]
actv[ii,jj,temp] = 1
actv = mkvc(actv==1)
inds = np.asarray([inds for inds, elem in enumerate(actv, 1) if elem], dtype = int) - 1
return inds
def plot_obs_2D(survey,varstr):
""" Function plot_obs(rxLoc,d,wd)
Generate a 2d interpolated plot from scatter points of data
INPUT
rxLoc : Observation locations [x,y,z]
d : Data vector
wd : Uncertainty vector
OUTPUT
figure()
Created on Dec, 27th 2015
@author: dominiquef
"""
from scipy.interpolate import griddata
import pylab as plt
rxLoc = survey.srcField.rxList[0].locs
d = survey.dobs
wd = survey.std
# Create grid of points
x = np.linspace(rxLoc[:,0].min(), rxLoc[:,0].max(), 100)
y = np.linspace(rxLoc[:,1].min(), rxLoc[:,1].max(), 100)
X, Y = np.meshgrid(x,y)
# Interpolate
d_grid = griddata(rxLoc[:,0:2],d,(X,Y), method ='linear')
# Plot result
plt.figure()
plt.subplot()
plt.imshow(d_grid, extent=[x.min(), x.max(), y.min(), y.max()],origin = 'lower')
plt.colorbar(fraction=0.02)
plt.contour(X,Y, d_grid,10)
plt.scatter(rxLoc[:,0],rxLoc[:,1], c=d, s=20)
plt.title(varstr)
plt.gca().set_aspect('equal', adjustable='box')
def readUBCgravObs(obs_file):
"""
Read UBC grav file format
INPUT:
:param fileName, path to the UBC obs grav file
OUTPUT:
:param survey
"""
fid = open(obs_file,'r')
# First line has the number of rows
line = fid.readline()
ndat = np.array(line.split(),dtype=int)
# Pre-allocate space for obsx, obsy, obsz, data, uncert
line = fid.readline()
temp = np.array(line.split(),dtype=float)
d = np.zeros(ndat, dtype=float)
wd = np.zeros(ndat, dtype=float)
locXYZ = np.zeros( (ndat,3), dtype=float)
for ii in range(ndat):
temp = np.array(line.split(),dtype=float)
locXYZ[ii,:] = temp[:3]
d[ii] = temp[3]
wd[ii] = temp[4]
line = fid.readline()
rxLoc = GRAV.RxObs(locXYZ)
srcField = GRAV.SrcField([rxLoc])
survey = GRAV.LinearSurvey(srcField)
survey.dobs = d
survey.std = wd
return survey
def read_GRAVinv_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
topofile
start model
ref model
weightfile
chi_target
as, ax ,ay, az
upper, lower bounds
lp, lqx, lqy, lqz
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Dec 21th, 2015
@author: dominiquef
"""
fid = open(input_file,'r')
# Line 1
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
# Line 2
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
# Line 3
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
# Line 4
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mstart = float(l_input[1])
else:
mstart = l_input[0].rstrip()
# Line 5
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mref = float(l_input[1])
else:
mref = l_input[0].rstrip()
# Line 7
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='DEFAULT':
wgtfile = None
else:
wgtfile = l_input[0].rstrip()
# Line 8
line = fid.readline()
l_input = re.split('[!\s]',line)
chi = float(l_input[0])
# Line 9
line = fid.readline()
l_input = re.split('[!\s]',line)
val = np.array(l_input[0:4])
alphas = val.astype(np.float)
# Line 10
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:3])
bounds = val.astype(np.float)
else:
bounds = l_input[0].rstrip()
# Line 11
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:6])
lpnorms = val.astype(np.float)
else:
lpnorms = l_input[0].rstrip()
return mshfile, obsfile, topofile, mstart, mref, wgtfile, chi, alphas, bounds, lpnorms
simpegPF/Magnetics.py
+728 -170
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@@ -1,36 +1,217 @@
from SimPEG import *
import BaseMag
import BaseMag as MAG
from scipy.constants import mu_0
from MagAnalytics import spheremodel, CongruousMagBC
import re
class MagneticIntegral(Problem.BaseProblem):
surveyPair = Survey.LinearSurvey
#surveyPair = Survey.LinearSurvey
def __init__(self, mesh, G, mapping=None, **kwargs):
storeG = True #: Store the forward matrix by default, otherwise just compute d
actInd = None #: Active cell indices provided
M = None #: Magnetization matrix provided, otherwise all induced
def __init__(self, mesh, mapping=None, **kwargs):
Problem.BaseProblem.__init__(self, mesh, mapping=mapping, **kwargs)
self.G = G
def fwr_ind(self):
# Add forward function
# kappa = self.curModel.kappa TODO
kappa = self.mapping*self.curModel
return self.G.dot(kappa)
def fwr_rem(self):
#TODO check if we are inverting for M
return self.G.dot(self.mapping(m))
def fields(self, m):
return self.G.dot(self.mapping*(m))
self.curModel = m
total = np.zeros(self.survey.nRx)
induced = self.fwr_ind()
# rem = self.rem
if induced is not None:
total += induced
return total
# return self.G.dot(self.mapping*(m))
def Jvec(self, m, v, u=None):
def Jvec(self, m, v, f=None):
dmudm = self.mapping.deriv(m)
return self.G.dot(dmudm*v)
def Jtvec(self, m, v, u=None):
def Jtvec(self, m, v, f=None):
dmudm = self.mapping.deriv(m)
return dmudm.T * (self.G.T.dot(v))
@property
def G(self):
if not self.ispaired:
raise Exception('Need to pair!')
if getattr(self,'_G', None) is None:
self._G = self.Intrgl_Fwr_Op( 'ind' )
return self._G
# @property
# def Grem(self):
# if not self.ispaired:
# raise Exception('Need to pair!')
# if getattr(self,'_Grem', None) is None:
# self._Grem = Intrgl_Fwr_Op('full')
# return self._Grem
def Intrgl_Fwr_Op(self, flag):
"""
Magnetic forward operator in integral form
flag = 'ind' | 'full'
1- ind : Magnetization fixed by user
3- full: Full tensor matrix stored with shape([3*ndata, 3*nc])
Return
_G = Linear forward modeling operation
Created on March, 13th 2016
@author: dominiquef
"""
# Find non-zero cells
#inds = np.nonzero(actv)[0]
if getattr(self, 'actInd', None) is not None:
if self.actInd.dtype=='bool':
inds = np.asarray([inds for inds, elem in enumerate(self.actInd, 1) if elem], dtype = int) - 1
else:
inds = self.actInd
else:
inds = np.asarray(range(self.mesh.nC))
nC = len(inds)
# Create active cell projector
P = sp.csr_matrix((np.ones(nC),(inds, range(nC))),
shape=(self.mesh.nC, nC))
# Create vectors of nodal location (lower and upper coners for each cell)
xn = self.mesh.vectorNx;
yn = self.mesh.vectorNy;
zn = self.mesh.vectorNz;
yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
yn1,xn1,zn1 = np.meshgrid(yn[0:-1], xn[0:-1], zn[0:-1])
Yn = P.T*np.c_[mkvc(yn1), mkvc(yn2)]
Xn = P.T*np.c_[mkvc(xn1), mkvc(xn2)]
Zn = P.T*np.c_[mkvc(zn1), mkvc(zn2)]
rxLoc = self.survey.srcField.rxList[0].locs
ndata = rxLoc.shape[0]
survey = self.survey
# Pre-allocate space and create magnetization matrix if required
if (flag=='ind'):
# # If assumes uniform magnetization direction
# if M.shape != (nC,3):
# print 'Magnetization vector must be Nc x 3'
# return
if getattr(self, 'M', None) is None:
M = dipazm_2_xyz(np.ones(nC) * survey.srcField.param[1],np.ones(nC) * survey.srcField.param[2])
Mx = Utils.sdiag(M[:,0]*survey.srcField.param[0])
My = Utils.sdiag(M[:,1]*survey.srcField.param[0])
Mz = Utils.sdiag(M[:,2]*survey.srcField.param[0])
Mxyz = sp.vstack((Mx,My,Mz))
if survey.srcField.rxList[0].rxType == 'tmi':
G = np.zeros((ndata, nC))
# Convert Bdecination from north to cartesian
D = (450.-float(survey.srcField.param[2]))%360.
I = survey.srcField.param[1]
# Projection matrix
Ptmi = mkvc(np.r_[np.cos(np.deg2rad(I))*np.cos(np.deg2rad(D)),
np.cos(np.deg2rad(I))*np.sin(np.deg2rad(D)),
np.sin(np.deg2rad(I))],2).T;
elif survey.srcField.rxList[0].rxType == 'xyz':
G = np.zeros((int(3*ndata), nC))
elif flag == 'full':
G = np.zeros((int(3*ndata), int(3*nC)))
else:
print """Flag must be either 'ind' | 'full', please revised"""
return
# Loop through all observations and create forward operator (ndata-by-nC)
print "Begin calculation of forward operator: " + flag
# Add counter to dsiplay progress. Good for large problems
count = -1;
for ii in range(ndata):
tx, ty, tz = get_T_mat(Xn,Yn,Zn,rxLoc[ii,:])
if flag == 'ind':
if survey.srcField.rxList[0].rxType =='tmi':
G[ii,:] = Ptmi.dot(np.vstack((tx,ty,tz)))*Mxyz
elif survey.srcField.rxList[0].rxType =='xyz':
G[ii,:] = tx*Mxyz
G[ii+ndata,:] = ty*Mxyz
G[ii+2*ndata,:] = tz*Mxyz
elif flag == 'full':
G[ii,:] = tx
G[ii+ndata,:] = ty
G[ii+2*ndata,:] = tz
# Display progress
count = progress(ii,count,ndata)
print "Done 100% ...forward operator completed!!\n"
return G
class MagneticsDiffSecondary(Problem.BaseProblem):
"""
Secondary field approach using differential equations!
"""
surveyPair = BaseMag.BaseMagSurvey
modelPair = BaseMag.BaseMagMap
surveyPair = MAG.BaseMagSurvey
modelPair = MAG.BaseMagMap
def __init__(self, model, mapping=None, **kwargs):
Problem.BaseProblem.__init__(self, model, mapping=mapping, **kwargs)
@@ -525,139 +706,139 @@ def Intgrl_Fwr_Data(mesh,B,M,rxLoc,model,actv,flag):
return d
def Intrgl_Fwr_Op(mesh,B,M,rxLoc,actv,flag):
"""
Magnetic forward operator in integral form
INPUT:
mesh = Mesh in SimPEG format
B = Inducing field parameter [Binc, Bdecl, B0]
M = Magnetization information
[OPTIONS]
1- [Minc, Mdecl] : Assumes uniform magnetization orientation
2- [mx1,mx2,..., my1,...,mz1] : cell-based defined magnetization direction
3- diag(M): Block diagonal matrix with [Mx, My, Mz] along the diagonal
rxLox = Observation location informat [obsx, obsy, obsz]
flag = 'tmi' | 'xyz' | 'full'
[OPTIONS]
1- tmi : Magnetization direction used and data are projected onto the
inducing field direction F.shape([ndata, nc])
2- xyz : Magnetization direction used and data are given in 3-components
F.shape([3*ndata, nc])
3- full: Full tensor matrix stored with shape([3*ndata, 3*nc])
OUTPUT:
F = Linear forward modeling operation
Created on Dec, 20th 2015
@author: dominiquef
"""
# Find non-zero cells
#inds = np.nonzero(actv)[0]
if actv.dtype=='bool':
inds = np.asarray([inds for inds, elem in enumerate(actv, 1) if elem], dtype = int) - 1
else:
inds = actv
nC = len(inds)
# Create active cell projector
P = sp.csr_matrix((np.ones(nC),(inds, range(nC))),
shape=(mesh.nC, nC))
# Create vectors of nodal location (lower and upper coners for each cell)
xn = mesh.vectorNx;
yn = mesh.vectorNy;
zn = mesh.vectorNz;
yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
yn1,xn1,zn1 = np.meshgrid(yn[0:-1], xn[0:-1], zn[0:-1])
Yn = P.T*np.c_[mkvc(yn1), mkvc(yn2)]
Xn = P.T*np.c_[mkvc(xn1), mkvc(xn2)]
Zn = P.T*np.c_[mkvc(zn1), mkvc(zn2)]
ndata = rxLoc.shape[0]
# Convert Bdecination from north to cartesian
D = (450.-float(B[1]))%360.
# Pre-allocate space and create magnetization matrix if required
if (flag=='tmi') | (flag == 'xyz'):
# If assumes uniform magnetization direction
if M.shape != (nC,3):
print 'Magnetization vector must be Nc x 3'
return
Mx = Utils.sdiag(M[:,0]*B[2])
My = Utils.sdiag(M[:,1]*B[2])
Mz = Utils.sdiag(M[:,2]*B[2])
Mxyz = sp.vstack((Mx,My,Mz))
if flag == 'tmi':
F = np.zeros((ndata, nC))
# Projection matrix
Ptmi = mkvc(np.r_[np.cos(np.deg2rad(B[0]))*np.cos(np.deg2rad(D)),
np.cos(np.deg2rad(B[0]))*np.sin(np.deg2rad(D)),
np.sin(np.deg2rad(B[0]))],2).T;
elif flag == 'xyz':
F = np.zeros((int(3*ndata), nC))
elif flag == 'full':
F = np.zeros((int(3*ndata), int(3*nC)))
else:
print """Flag must be either 'tmi' | 'xyz' | 'full', please revised"""
return
# Loop through all observations and create forward operator (ndata-by-nC)
print "Begin calculation of forward operator: " + flag
# Add counter to dsiplay progress. Good for large problems
count = -1;
for ii in range(ndata):
tx, ty, tz = get_T_mat(Xn,Yn,Zn,rxLoc[ii,:])
if flag=='tmi':
F[ii,:] = Ptmi.dot(np.vstack((tx,ty,tz)))*Mxyz
elif flag == 'xyz':
F[ii,:] = tx*Mxyz
F[ii+ndata,:] = ty*Mxyz
F[ii+2*ndata,:] = tz*Mxyz
elif flag == 'full':
F[ii,:] = tx
F[ii+ndata,:] = ty
F[ii+2*ndata,:] = tz
# Display progress
count = progress(ii,count,ndata)
print "Done 100% ...forward operator completed!!\n"
return F
#def Intrgl_Fwr_Op(mesh,B,M,rxLoc,actv,flag):
# """
#
# Magnetic forward operator in integral form
#
# INPUT:
# mesh = Mesh in SimPEG format
# B = Inducing field parameter [Binc, Bdecl, B0]
# M = Magnetization information
# [OPTIONS]
# 1- [Minc, Mdecl] : Assumes uniform magnetization orientation
# 2- [mx1,mx2,..., my1,...,mz1] : cell-based defined magnetization direction
# 3- diag(M): Block diagonal matrix with [Mx, My, Mz] along the diagonal
#
# rxLox = Observation location informat [obsx, obsy, obsz]
#
# flag = 'tmi' | 'xyz' | 'full'
# [OPTIONS]
# 1- tmi : Magnetization direction used and data are projected onto the
# inducing field direction F.shape([ndata, nc])
#
# 2- xyz : Magnetization direction used and data are given in 3-components
# F.shape([3*ndata, nc])
#
# 3- full: Full tensor matrix stored with shape([3*ndata, 3*nc])
#
# OUTPUT:
# F = Linear forward modeling operation
#
# Created on Dec, 20th 2015
#
# @author: dominiquef
#
# """
# # Find non-zero cells
# #inds = np.nonzero(actv)[0]
# if actv.dtype=='bool':
# inds = np.asarray([inds for inds, elem in enumerate(actv, 1) if elem], dtype = int) - 1
# else:
# inds = actv
#
# nC = len(inds)
#
# # Create active cell projector
# P = sp.csr_matrix((np.ones(nC),(inds, range(nC))),
# shape=(mesh.nC, nC))
#
# # Create vectors of nodal location (lower and upper coners for each cell)
# xn = mesh.vectorNx;
# yn = mesh.vectorNy;
# zn = mesh.vectorNz;
#
# yn2,xn2,zn2 = np.meshgrid(yn[1:], xn[1:], zn[1:])
# yn1,xn1,zn1 = np.meshgrid(yn[0:-1], xn[0:-1], zn[0:-1])
#
# Yn = P.T*np.c_[mkvc(yn1), mkvc(yn2)]
# Xn = P.T*np.c_[mkvc(xn1), mkvc(xn2)]
# Zn = P.T*np.c_[mkvc(zn1), mkvc(zn2)]
#
# ndata = rxLoc.shape[0]
#
# # Convert Bdecination from north to cartesian
# D = (450.-float(B[1]))%360.
#
#
# # Pre-allocate space and create magnetization matrix if required
# if (flag=='tmi') | (flag == 'xyz'):
# # If assumes uniform magnetization direction
# if M.shape != (nC,3):
#
# print 'Magnetization vector must be Nc x 3'
# return
#
#
# Mx = Utils.sdiag(M[:,0]*B[2])
# My = Utils.sdiag(M[:,1]*B[2])
# Mz = Utils.sdiag(M[:,2]*B[2])
#
# Mxyz = sp.vstack((Mx,My,Mz))
#
#
#
# if flag == 'tmi':
# F = np.zeros((ndata, nC))
#
# # Projection matrix
# Ptmi = mkvc(np.r_[np.cos(np.deg2rad(B[0]))*np.cos(np.deg2rad(D)),
# np.cos(np.deg2rad(B[0]))*np.sin(np.deg2rad(D)),
# np.sin(np.deg2rad(B[0]))],2).T;
#
# elif flag == 'xyz':
#
# F = np.zeros((int(3*ndata), nC))
#
# elif flag == 'full':
# F = np.zeros((int(3*ndata), int(3*nC)))
#
#
# else:
# print """Flag must be either 'tmi' | 'xyz' | 'full', please revised"""
# return
#
#
# # Loop through all observations and create forward operator (ndata-by-nC)
# print "Begin calculation of forward operator: " + flag
#
# # Add counter to dsiplay progress. Good for large problems
# count = -1;
# for ii in range(ndata):
#
#
# tx, ty, tz = get_T_mat(Xn,Yn,Zn,rxLoc[ii,:])
#
# if flag=='tmi':
# F[ii,:] = Ptmi.dot(np.vstack((tx,ty,tz)))*Mxyz
#
# elif flag == 'xyz':
# F[ii,:] = tx*Mxyz
# F[ii+ndata,:] = ty*Mxyz
# F[ii+2*ndata,:] = tz*Mxyz
#
# elif flag == 'full':
# F[ii,:] = tx
# F[ii+ndata,:] = ty
# F[ii+2*ndata,:] = tz
#
#
# # Display progress
# count = progress(ii,count,ndata)
#
# print "Done 100% ...forward operator completed!!\n"
#
# return F
def get_T_mat(Xn,Yn,Zn,rxLoc):
"""
@@ -823,9 +1004,9 @@ def dipazm_2_xyz(dip,azm_N):
M = np.zeros((nC,3))
# Modify azimuth from North to Cartesian-X
azm_X = (450.- azm_N) % 360.
azm_X = (450.- np.asarray(azm_N)) % 360.
D = np.deg2rad(dip)
D = np.deg2rad(np.asarray(dip))
I = np.deg2rad(azm_X)
M[:,0] = np.cos(D) * np.cos(I) ;
@@ -913,7 +1094,7 @@ def get_dist_wgt(mesh,rxLoc,actv,R,R0):
temp = (R1 + R0)**-R + (R2 + R0)**-R + (R3 + R0)**-R + (R4 + R0)**-R + (R5 + R0)**-R + (R6 + R0)**-R + (R7 + R0)**-R + (R8 + R0)**-R
wr = wr + (V*temp/8.)**2
wr = wr + (V*temp/8.)**2.
count = progress(dd,count,ndata)
@@ -926,7 +1107,7 @@ def get_dist_wgt(mesh,rxLoc,actv,R,R0):
return wr
def writeUBCobs(filename,B,M,rxLoc,d,wd):
def writeUBCobs(filename,survey,d):
"""
writeUBCobs(filename,B,M,rxLoc,d,wd)
@@ -934,11 +1115,8 @@ def writeUBCobs(filename,B,M,rxLoc,d,wd):
INPUT
filename : Name of out file including directory
B : Inducing field parameters [Inc, Decl, Intensity]
M : Magnetization orientation [Inc, Decl, dtype]
rxLoc : Observation locations [obsx, obsy, obsz]
d : Data vector
wd : Uncertainty vector
survey
flag : dobs | dpred
OUTPUT
Obsfile
@@ -948,11 +1126,17 @@ def writeUBCobs(filename,B,M,rxLoc,d,wd):
@author: dominiquef
"""
B = survey.srcField.param
rxLoc = survey.srcField.rxList[0].locs
wd = survey.std
data = np.c_[rxLoc , d , wd]
with file(filename,'w') as fid:
fid.write('%6.2f %6.2f %6.2f\n' %(B[0], B[1], B[2]) )
fid.write('%6.2f %6.2f %6.2f\n' %(M[0], M[1], 1) )
fid.write('%6.2f %6.2f %6.2f\n' %(B[2], B[1], B[0]) )
fid.write('%6.2f %6.2f %6.2f\n' %(B[2], B[1], 1) )
fid.write('%i\n' %len(d) )
np.savetxt(fid, data, fmt='%e',delimiter=' ',newline='\n')
@@ -1009,8 +1193,8 @@ def getActiveTopo(mesh,topo,flag):
return inds
def plot_obs_2D(rxLoc,d,wd,varstr):
""" Function plot_obs(rxLoc,d,wd)
def plot_obs_2D(rxLoc,d = None ,varstr = 'Mag Obs', vmin = None, vmax = None, levels = None):
""" Function plot_obs(rxLoc,d)
Generate a 2d interpolated plot from scatter points of data
INPUT
@@ -1030,22 +1214,396 @@ def plot_obs_2D(rxLoc,d,wd,varstr):
from scipy.interpolate import griddata
import pylab as plt
# Create grid of points
x = np.linspace(rxLoc[:,0].min(), rxLoc[:,0].max(), 100)
y = np.linspace(rxLoc[:,1].min(), rxLoc[:,1].max(), 100)
X, Y = np.meshgrid(x,y)
# Interpolate
d_grid = griddata(rxLoc[:,0:2],d,(X,Y), method ='linear')
# Plot result
plt.figure()
plt.subplot()
plt.imshow(d_grid, extent=[x.min(), x.max(), y.min(), y.max()],origin = 'lower')
plt.colorbar(fraction=0.02)
plt.contour(X,Y, d_grid,10)
plt.scatter(rxLoc[:,0],rxLoc[:,1], c=d, s=20)
plt.scatter(rxLoc[:,0],rxLoc[:,1], c='k', s=10)
if d is not None:
if (vmin is None):
vmin = d.min()
if (vmax is None):
vmax = d.max()
# Create grid of points
x = np.linspace(rxLoc[:,0].min(), rxLoc[:,0].max(), 100)
y = np.linspace(rxLoc[:,1].min(), rxLoc[:,1].max(), 100)
X, Y = np.meshgrid(x,y)
# Interpolate
d_grid = griddata(rxLoc[:,0:2],d,(X,Y), method ='linear')
plt.imshow(d_grid, extent=[x.min(), x.max(), y.min(), y.max()],origin = 'lower', vmin = vmin, vmax = vmax)
plt.colorbar(fraction=0.02)
if levels is None:
plt.contour(X,Y, d_grid,10,vmin = vmin, vmax = vmax)
else:
plt.contour(X,Y, d_grid,levels = levels,colors = 'r', vmin = vmin, vmax = vmax)
plt.title(varstr)
plt.gca().set_aspect('equal', adjustable='box')
def readUBCmagObs(obs_file):
"""
Read and write UBC mag file format
INPUT:
:param fileName, path to the UBC obs mag file
OUTPUT:
:param survey
:param M, magnetization orentiaton (MI, MD)
"""
fid = open(obs_file,'r')
# First line has the inclination,declination and amplitude of B0
line = fid.readline()
B = np.array(line.split(),dtype=float)
# Second line has the magnetization orientation and a flag
line = fid.readline()
M = np.array(line.split(),dtype=float)
# Third line has the number of rows
line = fid.readline()
ndat = np.array(line.split(),dtype=int)
# Pre-allocate space for obsx, obsy, obsz, data, uncert
line = fid.readline()
temp = np.array(line.split(),dtype=float)
d = np.zeros(ndat, dtype=float)
wd = np.zeros(ndat, dtype=float)
locXYZ = np.zeros( (ndat,3), dtype=float)
for ii in range(ndat):
temp = np.array(line.split(),dtype=float)
locXYZ[ii,:] = temp[:3]
if len(temp) > 3:
d[ii] = temp[3]
if len(temp)==5:
wd[ii] = temp[4]
line = fid.readline()
rxLoc = MAG.RxObs(locXYZ)
srcField = MAG.SrcField([rxLoc],(B[2],B[0],B[1]))
survey = MAG.LinearSurvey(srcField)
survey.dobs = d
survey.std = wd
return survey
def read_MAGfwr_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
modfile
magfile
topofile
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Jul 17, 2013
@author: dominiquef
"""
fid = open(input_file,'r')
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
modfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
magfile = []
else:
magfile = l_input[0].rstrip()
line = fid.readline()
l_input = line.split('!')
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
return mshfile, obsfile, modfile, magfile, topofile
def read_MAGinv_inp(input_file):
"""Read input files for forward modeling MAG data with integral form
INPUT:
input_file: File name containing the forward parameter
OUTPUT:
mshfile
obsfile
topofile
start model
ref model
mag model
weightfile
chi_target
as, ax ,ay, az
upper, lower bounds
lp, lqx, lqy, lqz
# All files should be in the working directory, otherwise the path must
# be specified.
Created on Dec 21th, 2015
@author: dominiquef
"""
fid = open(input_file,'r')
# Line 1
line = fid.readline()
l_input = line.split('!')
mshfile = l_input[0].rstrip()
# Line 2
line = fid.readline()
l_input = line.split('!')
obsfile = l_input[0].rstrip()
# Line 3
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='null':
topofile = []
else:
topofile = l_input[0].rstrip()
# Line 4
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mstart = float(l_input[1])
else:
mstart = l_input[0].rstrip()
# Line 5
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
mref = float(l_input[1])
else:
mref = l_input[0].rstrip()
# Line 6
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='DEFAULT':
magfile = []
else:
magfile = l_input[0].rstrip()
# Line 7
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input=='DEFAULT':
wgtfile = []
else:
wgtfile = l_input[0].rstrip()
# Line 8
line = fid.readline()
l_input = re.split('[!\s]',line)
chi = float(l_input[0])
# Line 9
line = fid.readline()
l_input = re.split('[!\s]',line)
val = np.array(l_input[0:4])
alphas = val.astype(np.float)
# Line 10
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:3])
bounds = val.astype(np.float)
else:
bounds = l_input[0].rstrip()
# Line 11
line = fid.readline()
l_input = re.split('[!\s]',line)
if l_input[0]=='VALUE':
val = np.array(l_input[1:6])
lpnorms = val.astype(np.float)
else:
lpnorms = l_input[0].rstrip()
return mshfile, obsfile, topofile, mstart, mref, magfile, wgtfile, chi, alphas, bounds, lpnorms
def read_GOCAD_ts(tsfile):
"""Read GOCAD triangulated surface (*.ts) file
INPUT:
tsfile: Triangulated surface
OUTPUT:
vrts : Array of vertices in XYZ coordinates [n x 3]
trgl : Array of index for triangles [m x 3]. The order of the vertices
is important and describes the normal
n = cross( (P2 - P1 ) , (P3 - P1) )
Created on Jan 13th, 2016
Author: @fourndo
"""
fid = open(tsfile,'r')
line = fid.readline()
# Skip all the lines until the vertices
while re.match('TFACE',line)==None:
line = fid.readline()
line = fid.readline()
vrtx = []
# Run down all the vertices and save in array
while re.match('VRTX',line):
l_input = re.split('[\s*]',line)
temp = np.array(l_input[2:5])
vrtx.append(temp.astype(np.float))
# Read next line
line = fid.readline()
vrtx = np.asarray(vrtx)
# Skip lines to the triangles
while re.match('TRGL',line)==None:
line = fid.readline()
# Run down the list of triangles
trgl = []
# Run down all the vertices and save in array
while re.match('TRGL',line):
l_input = re.split('[\s*]',line)
temp = np.array(l_input[1:4])
trgl.append(temp.astype(np.int))
# Read next line
line = fid.readline()
trgl = np.asarray(trgl)
return vrtx, trgl
def gocad2vtk(gcFile,mesh,bcflag,inflag):
""""
Function to read gocad polystructure file and output indexes of mesh with in the structure.
"""
import vtk, vtk.util.numpy_support as npsup
print "Reading GOCAD ts file..."
vrtx, trgl = read_GOCAD_ts(gcFile)
# Adjust the index
trgl = trgl - 1
# Make vtk pts
ptsvtk = vtk.vtkPoints()
ptsvtk.SetData(npsup.numpy_to_vtk(vrtx,deep=1))
# Make the polygon connection
polys = vtk.vtkCellArray()
for face in trgl:
poly = vtk.vtkPolygon()
poly.GetPointIds().SetNumberOfIds(len(face))
for nrv, vert in enumerate(face):
poly.GetPointIds().SetId(nrv,vert)
polys.InsertNextCell(poly)
# Make the polydata, structure of connections and vrtx
polyData = vtk.vtkPolyData()
polyData.SetPoints(ptsvtk)
polyData.SetPolys(polys)
# Make implicit func
ImpDistFunc = vtk.vtkImplicitPolyDataDistance()
ImpDistFunc.SetInput(polyData)
# Convert the mesh
vtkMesh = vtk.vtkRectilinearGrid()
vtkMesh.SetDimensions(mesh.nNx,mesh.nNy,mesh.nNz)
vtkMesh.SetXCoordinates(npsup.numpy_to_vtk(mesh.vectorNx,deep=1))
vtkMesh.SetYCoordinates(npsup.numpy_to_vtk(mesh.vectorNy,deep=1))
vtkMesh.SetZCoordinates(npsup.numpy_to_vtk(mesh.vectorNz,deep=1))
# Add indexes
vtkInd = npsup.numpy_to_vtk(np.arange(mesh.nC),deep=1)
vtkInd.SetName('Index')
vtkMesh.GetCellData().AddArray(vtkInd)
extractImpDistRectGridFilt = vtk.vtkExtractGeometry() # Object constructor
extractImpDistRectGridFilt.SetImplicitFunction(ImpDistFunc) #
extractImpDistRectGridFilt.SetInputData(vtkMesh)
if bcflag is True:
extractImpDistRectGridFilt.ExtractBoundaryCellsOn()
else:
extractImpDistRectGridFilt.ExtractBoundaryCellsOff()
if inflag is True:
extractImpDistRectGridFilt.ExtractInsideOn()
else:
extractImpDistRectGridFilt.ExtractInsideOff()
print "Extracting indices from grid..."
# Executing the pipe
extractImpDistRectGridFilt.Update()
# Get index inside
insideGrid = extractImpDistRectGridFilt.GetOutput()
insideGrid = npsup.vtk_to_numpy(insideGrid.GetCellData().GetArray('Index'))
# Return the indexes inside
return insideGrid
simpegPF/__init__.py
+2
View File
@@ -1,3 +1,5 @@
import MagAnalytics
import BaseMag
import Magnetics
import BaseGrav
import Gravity
simpegPF/notebooks/SimPEG Tutorial - MAG Linear Problem.ipynb
+1719 -1725
View File
File diff suppressed because one or more lines are too long