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Possibly deal with a good chunk of the old_divs

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This commit is contained in:
Brendan Smithyman
2016-07-17 16:02:43 -05:00
parent 7189ec5b2f
commit f7a70aa6a7
85 changed files with 369 additions and 454 deletions
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SimPEG/Examples/DC_Analytic_Dipole.py
+2 -3
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@@ -4,7 +4,6 @@ from __future__ import unicode_literals
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from past.utils import old_div
from SimPEG import *
import SimPEG.EM.Static.DC as DC
@@ -45,7 +44,7 @@ def run(plotIt=True):
rn = (srclocN.reshape([1,-1])).repeat(rxloc.shape[0], axis = 0)
rP = np.sqrt(((rxloc-rp)**2).sum(axis=1))
rN = np.sqrt(((rxloc-rn)**2).sum(axis=1))
return I/(sigma*2.*np.pi)*(old_div(1,rP)-old_div(1,rN))
return I/(sigma*2.*np.pi)*(1/rP-1/rN)
data_anaP = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxP, sighalf)
data_anaN = DChalf(np.r_[-200, 0, 0.],np.r_[+200, 0, 0.], xyz_rxN, sighalf)
@@ -68,7 +67,7 @@ def run(plotIt=True):
ax[0].set_title('Computed')
plt.show()
return old_div(np.linalg.norm(data-data_ana),np.linalg.norm(data_ana))
return np.linalg.norm(data-data_ana) / np.linalg.norm(data_ana)
if __name__ == '__main__':
SimPEG/Examples/DC_Forward_PseudoSection.py
+7 -8
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@@ -6,7 +6,6 @@ from builtins import int
from future import standard_library
standard_library.install_aliases()
from builtins import range
from past.utils import old_div
from SimPEG import Mesh, Utils, np, sp
import SimPEG.DCIP as DC
import time
@@ -66,7 +65,7 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
model[ind] = sig[2]
# Get index of the center
indy = int(old_div(mesh.nCy,2))
indy = int(mesh.nCy // 2)
# Plot the model for reference
# Define core mesh extent
@@ -87,8 +86,8 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
# Define some global geometry
dl_len = np.sqrt( np.sum((locs[0,:] - locs[1,:])**2) )
dl_x = old_div(( Tx[-1][0,1] - Tx[0][0,0] ), dl_len)
dl_y = old_div(( Tx[-1][1,1] - Tx[0][1,0] ), dl_len)
dl_x = ( Tx[-1][0,1] - Tx[0][0,0] ) / dl_len
dl_y = ( Tx[-1][1,1] - Tx[0][1,0] ) / dl_len
#azm = np.arctan(dl_y/dl_x)
#Set boundary conditions
@@ -98,7 +97,7 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
# line source for simplicity.
Div = mesh.faceDiv
Grad = mesh.cellGrad
Msig = Utils.sdiag(old_div(1.,(mesh.aveF2CC.T*(old_div(1.,model)))))
Msig = Utils.sdiag(1./(mesh.aveF2CC.T*(1./model)))
A = Div*Msig*Grad
@@ -109,7 +108,7 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
# We will solve the system iteratively, so a pre-conditioner is helpful
# This is simply a Jacobi preconditioner (inverse of the main diagonal)
dA = A.diagonal()
P = sp.spdiags(old_div(1,dA),0,A.shape[0],A.shape[0])
P = sp.spdiags(1/dA,0,A.shape[0],A.shape[0])
# Now we can solve the system for all the transmitters
# We want to store the data
@@ -133,10 +132,10 @@ def run(loc=None, sig=None, radi=None, param=None, surveyType='dipole-dipole', u
tx = np.squeeze(Tx[ii][:,0:1])
tinf = tx + np.array([dl_x,dl_y,0])*dl_len*2
inds = Utils.closestPoints(mesh, np.c_[tx,tinf].T)
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( old_div([-1], mesh.vol[inds]) )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*([-1] / mesh.vol[inds])
else:
inds = Utils.closestPoints(mesh, np.asarray(Tx[ii]).T )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*( old_div([-1,1], mesh.vol[inds]) )
RHS = mesh.getInterpolationMat(np.asarray(Tx[ii]).T, 'CC').T*([-1,1] / mesh.vol[inds])
# Iterative Solve
Ainvb = sp.linalg.bicgstab(P*A,P*RHS, tol=1e-5)
SimPEG/Examples/EM_Schenkel_Morrison_Casing.py
+15 -16
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@@ -5,7 +5,6 @@ from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from builtins import range
from past.utils import old_div
from SimPEG import *
from SimPEG.EM import FDEM, Analytics, mu_0
import time
@@ -75,8 +74,8 @@ def run(plotIt=True):
casing_l = 300 # length of the casing
casing_r = 0.1
casing_a = casing_r - old_div(casing_t,2.) # inner radius
casing_b = casing_r + old_div(casing_t,2.) # outer radius
casing_a = casing_r - casing_t / 2. # inner radius
casing_b = casing_r + casing_t / 2. # outer radius
casing_z = np.r_[-casing_l,0.]
@@ -86,25 +85,25 @@ def run(plotIt=True):
src_loc = np.r_[0.,0.,dsz]
inf_loc = np.r_[0.,0.,1e4]
print('Skin Depth: ', [(old_div(500.,np.sqrt(sigmaback*_))) for _ in freqs])
print('Skin Depth: ', [(500. / np.sqrt(sigmaback*_)) for _ in freqs])
# ------------------ MESH ------------------
# fine cells near well bore
csx1, csx2 = 2e-3, 60.
pfx1, pfx2 = 1.3, 1.3
ncx1 = np.ceil(old_div(casing_b,csx1)+2)
ncx1 = np.ceil(casing_b/csx1)+2
# pad nicely to second cell size
npadx1 = np.floor(old_div(np.log(old_div(csx2,csx1)), np.log(pfx1)))
npadx1 = np.log(csx2/csx1) // np.log(pfx1)
hx1a,hx1b = Utils.meshTensor([(csx1,ncx1)]),Utils.meshTensor([(csx1,npadx1,pfx1)])
dx1 = sum(hx1a)+sum(hx1b)
dx1 = np.floor(old_div(dx1,csx2))
hx1b *= old_div((dx1*csx2 - sum(hx1a)),sum(hx1b))
dx1 = dx1 // csx2
hx1b *= (dx1*csx2 - sum(hx1a)) / sum(hx1b)
# second chunk of mesh
dx2 = 300. # uniform mesh out to here
ncx2 = np.ceil(old_div((dx2 - dx1),csx2))
ncx2 = np.ceil((dx2 - dx1) / csx2)
npadx2 = 45
hx2a, hx2b = Utils.meshTensor([(csx2,ncx2)]), Utils.meshTensor([(csx2,npadx2,pfx2)])
hx = np.hstack([hx1a,hx1b,hx2a,hx2b])
@@ -112,7 +111,7 @@ def run(plotIt=True):
# z-direction
csz = 0.05
nza = 10
ncz, npadzu, npadzd = np.int(np.ceil(old_div(np.diff(casing_z)[0],csz)))+10, 68, 68 # cell size, number of core cells, number of padding cells in the x- direction
ncz, npadzu, npadzd = np.int(np.ceil(np.diff(casing_z)[0]/csz))+10, 68, 68 # cell size, number of core cells, number of padding cells in the x- direction
hz = Utils.meshTensor([(csz,npadzd,-1.3), (csz,ncz), (csz,npadzu,1.3)]) # vector of cell widths in the z-direction
# Mesh
@@ -190,7 +189,7 @@ def run(plotIt=True):
# assemble the source
sg = np.hstack([sg_x,sg_y,sg_z])
sg_p = [FDEM.Src.RawVec_e([],_,old_div(sg,mesh.area)) for _ in freqs]
sg_p = [FDEM.Src.RawVec_e([],_,sg/mesh.area) for _ in freqs]
# downhole source
dg_x = np.zeros(mesh.vnF[0],dtype=complex)
@@ -199,7 +198,7 @@ def run(plotIt=True):
# vertically directed wire
dgv_indx = (mesh.gridFz[:,0] < csx1) # go through the center of the well
dgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] > dsz + old_div(csz,2.))
dgv_indz = (mesh.gridFz[:,2] <= +csz*nza) & (mesh.gridFz[:,2] > dsz + csz/2.)
dgv_ind = dgv_indx & dgv_indz
dg_z[dgv_ind] = -1.
@@ -221,7 +220,7 @@ def run(plotIt=True):
# assemble the source
dg = np.hstack([dg_x,dg_y,dg_z])
dg_p = [FDEM.Src.RawVec_e([],_,old_div(dg,mesh.area)) for _ in freqs]
dg_p = [FDEM.Src.RawVec_e([],_,dg/mesh.area) for _ in freqs]
# ------------ Problem and Survey ---------------
survey = FDEM.Survey(sg_p + dg_p)
@@ -259,9 +258,9 @@ def run(plotIt=True):
in1_in = in1[np.r_[inds]]
z_in = mesh.gridFz[inds_fz,2]
in0_in = in0_in.reshape([old_div(in0_in.shape[0],3),3])
in1_in = in1_in.reshape([old_div(in1_in.shape[0],3),3])
z_in = z_in.reshape([old_div(z_in.shape[0],3),3])
in0_in = in0_in.reshape([in0_in.shape[0]//3,3])
in1_in = in1_in.reshape([in1_in.shape[0]//3,3])
z_in = z_in.reshape([z_in.shape[0]//3,3])
I0 = in0_in.sum(1).real
I1 = in1_in.sum(1).real
SimPEG/Examples/FLOW_Richards_1D_Celia1990.py
+1 -2
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@@ -4,7 +4,6 @@ from __future__ import print_function
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from past.utils import old_div
from SimPEG import *
from SimPEG.FLOW import Richards
@@ -53,7 +52,7 @@ def run(plotIt=True):
def getFields(timeStep,method):
timeSteps = np.ones(old_div(360,timeStep))*timeStep
timeSteps = np.ones(360/timeStep)*timeStep
prob = Richards.RichardsProblem(M, mapping=E, timeSteps=timeSteps,
boundaryConditions=bc, initialConditions=h,
doNewton=False, method=method)
SimPEG/Examples/Inversion_IRLS.py
+5 -6
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@@ -6,7 +6,6 @@ from future import standard_library
standard_library.install_aliases()
from builtins import str
from builtins import range
from past.utils import old_div
from SimPEG import *
@@ -56,10 +55,10 @@ def run(N=100, plotIt=True):
# Distance weighting
wr = np.sum(prob.G**2.,axis=0)**0.5
wr = ( old_div(wr,np.max(wr)) )
wr = ( wr/np.max(wr))
dmis = DataMisfit.l2_DataMisfit(survey)
dmis.Wd = old_div(1.,wd)
dmis.Wd = 1./wd
betaest = Directives.BetaEstimate_ByEig()
@@ -68,15 +67,15 @@ def run(N=100, plotIt=True):
reg.cell_weights = wr
reg.mref = np.zeros(mesh.nC)
opt = Optimization.ProjectedGNCG(maxIter=100 ,lower=-2.,upper=2., maxIterLS = 20, maxIterCG= 10, tolCG = 1e-3)
invProb = InvProblem.BaseInvProblem(dmis, reg, opt)
update_Jacobi = Directives.Update_lin_PreCond()
# Set the IRLS directive, penalize the lowest 25 percentile of model values
# Start with an l2-l2, then switch to lp-norms
norms = [0., 0., 2., 2.]
norms = [0., 0., 2., 2.]
IRLS = Directives.Update_IRLS( norms=norms, prctile = 25, maxIRLSiter = 15, minGNiter=3)
inv = Inversion.BaseInversion(invProb, directiveList=[IRLS,betaest,update_Jacobi])
SimPEG/Examples/MT_1D_ForwardAndInversion.py
+1 -2
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@@ -4,7 +4,6 @@ from __future__ import print_function
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from past.utils import old_div
import SimPEG as simpeg
import numpy as np
import SimPEG.MT as MT
@@ -91,7 +90,7 @@ def run(plotIt=True):
std = 0.05 # 5% std
survey.std = np.abs(survey.dobs*std)
# Assign the data weight
Wd = old_div(1.,survey.std)
Wd = 1./survey.std
## Setup the inversion proceedure
# Define a counter
SimPEG/Examples/Maps_Mesh2Mesh.py
+1 -2
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@@ -4,7 +4,6 @@ from __future__ import print_function
from __future__ import absolute_import
from future import standard_library
standard_library.install_aliases()
from past.utils import old_div
from SimPEG import Mesh, Maps, Utils
def run(plotIt=True):
@@ -19,7 +18,7 @@ def run(plotIt=True):
M = Mesh.TensorMesh([100,100])
h1 = Utils.meshTensor([(6,7,-1.5),(6,10),(6,7,1.5)])
h1 = old_div(h1,h1.sum())
h1 = h1/h1.sum()
M2 = Mesh.TensorMesh([h1,h1])
V = Utils.ModelBuilder.randomModel(M.vnC, seed=79, its=50)
v = Utils.mkvc(V)