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This may be a corrupt mesh error

Abby123455r opened this issue · comments

commented

Problem description

i made a 3d geometry on freecad. and then mesh it on gmsh..after that i import it in pygimli for simulation. but when i try to invert the simulated data it gives me following error:
GIMLI::Cell* GIMLI::Mesh::findCell(const GIMLI::RVector3&, size_t&, bool) const no cells or boundaries for this node. This may be a corrupt mesh

Your environment

OS : Windows
CPU(s) : 32
Environment : Jupyter

Operating system: Windows,
Python version: 3.10,
pyGIMLi version: 1.5.0
Way of installation: Conda package

Steps to reproduce

import pygimli.meshtools as mt
import pygimli as pg
import pybert as pb
import gmsh
from pygimli.physics import ert
gmsh.initialize()
msh_nm = 'cone.msh'
gmsh.open(msh_nm)
mesh_mod = mt.readGmsh(msh_nm, verbose=True)

Reading bucket cone.msh...

Nodes: 3295
Entries: 18299
Points: 32
Lines: 0
Triangles: 2385
Quads: 0
Tetrahedra: 15882

Creating mesh object...

Dimension: 3-D
Boundary types: 2 (-2, -1)
Regions: 1 (1,)
Marked nodes: 32 (99,)

Done.

Mesh: Nodes: 3295 Cells: 15882 Boundaries: 33154

pg.show(mesh_mod, markers=True, showMesh=True)
bert_file = '01_1.udf'
BERT = pg.load(bert_file)

mgr = ert.ERTManager('01_1.udf')
# Define resistivity mapping (rhomap)
rhomap = [
    [1, 300.0]]
data_mod = ert.simulate(mesh_mod , res=rhomap  scheme=BERT, noiseLevel=1,
                    noiseAbs=1e-6, seed=1337 )
data_mod.save('practice.dat' )
mgr = ert.ERTManager('practice.dat')
inv = mgr.invert(lam=5, verbose=True)
np.testing.assert_approx_equal(mgr.inv.chi2(), 0.7, significant=1)

Paste your script output here.

15/05/24 - 12:12:42 - pyGIMLi - INFO - Found 3 regions.
15/05/24 - 12:12:42 - pyGIMLi - INFO - (ERTModelling) Region with smallest marker (0) set to background.
15/05/24 - 12:12:42 - pyGIMLi - INFO - Found 3 regions.
15/05/24 - 12:12:42 - pyGIMLi - INFO - (ERTModelling) Region with smallest marker (0) set to background.
15/05/24 - 12:12:42 - pyGIMLi - INFO - Creating forward mesh from region infos.
15/05/24 - 12:12:42 - pyGIMLi - INFO - Creating refined mesh (H2) to solve forward task.
15/05/24 - 12:12:42 - pyGIMLi - INFO - Mesh for forward task: Mesh: Nodes: 2093 Cells: 3824 Boundaries: 3042
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
Cell In[112], line 1
----> 1 inv = mgr.invert(lam=5, verbose=True)
      2 np.testing.assert_approx_equal(mgr.inv.chi2(), 0.7, significant=1)

File C:\WINDOWS\system32\D\pg\Lib\site-packages\pygimli\frameworks\methodManager.py:825, in MeshMethodManager.invert(self, data, mesh, startModel, **kwargs)
    822 dataVals = self._ensureData(self.fop.data)
    823 errorVals = self._ensureError(self.fop.data, dataVals)
--> 825 if self.fop.mesh() is None:
    826     pg.critical('Please provide a mesh')
    828 kwargs['startModel'] = startModel

File C:\WINDOWS\system32\D\pg\Lib\site-packages\pygimli\frameworks\modelling.py:709, in MeshModelling.mesh(self)
    706 self._applyRegionProperties()
    708 if self._regionManagerInUse and self._regionChanged is True:
--> 709     self.createFwdMesh_()
    711 return super().mesh()

File C:\WINDOWS\system32\D\pg\Lib\site-packages\pygimli\frameworks\modelling.py:695, in MeshModelling.createFwdMesh_(self)
    685     pg.verbose("\tRegion: {0}, Parameter: {1}, PD: {2},"
    686                " Single: {3}, Background: {4}, Fixed: {5}".format(
    687                    iId,
   (...)
    691                    self.regionManager().region(iId).isBackground(),
    692                    self.regionManager().region(iId).fixValue()))
    694 m = self.createRefinedFwdMesh(m)
--> 695 self.setMeshPost(m)
    697 self._regionChanged = False
    698 super().setMesh(m, ignoreRegionManager=True)

File C:\WINDOWS\system32\D\pg\Lib\site-packages\pygimli\physics\ert\ertModelling.py:211, in ERTModelling.setMeshPost(self, mesh)
    209 def setMeshPost(self, mesh):
    210     """Set mesh (at a later stage)."""
--> 211     self._core.setMesh(mesh, ignoreRegionManager=True)

RuntimeError: ./core/src/mesh.cpp:928		GIMLI::Cell* GIMLI::Mesh::findCell(const GIMLI::RVector3&, size_t&, bool) const  no cells or boundaries for this node. This may be a corrupt mesh

If possible, please add one or more labels to your issue, e.g. if you expect that your issue is rather a question than a problem with the code, please add the label "question".

commented

It doesn't look like you are passing a mesh to the inversion from your code so it does one for you. I haven't properly understood if you would like to use mesh_mod for your inversion. It seems you have to create another mesh for the inversion.

commented

i want to use same mesh for both modeling and inversion.is it not possible to use same mesh?

commented

Of couse you can, but using the same mesh for synthetic and inverse modelling is considered a so-called inverse crime as you already provide information that you normally don't have. At least you should reset all cell markers by mesh['marker']=0.

commented

thank you it is working.but it is showing large chi2 and negitive dphi:
inv.iter 0 ... chi² = 12550.59

inv.iter 1 ... chi² = 3388.10 (dPhi = 72.10%) lam: 20.0

inv.iter 2 ... chi² = 2880.36 (dPhi = 15.17%) lam: 20.0

inv.iter 3 ... chi² = 2713.54 (dPhi = 6.22%) lam: 20.0

inv.iter 4 ... chi² = 3033.46 (dPhi = -11.19%) lam: 20.0
################################################################################

Abort criterion reached: dPhi = -11.19 (< 2.0%)

commented

Hard to give any recommendations without knowing details. I guess the mesh is just inappropriate with this low node number, maybe not even containing the electrodes.

commented 
import pygimli.meshtools as mt
import pygimli as pg
import pybert as pb
import gmsh
from pygimli.physics import ert
gmsh.initialize()
msh_nm = 'bucket cone.msh'
mesh_mod = mt.readGmsh(msh_nm, verbose=True)

output:Reading bucket cone.msh...
Nodes: 8455
Entries: 49328
Points: 32
Lines: 0
Triangles: 5586
Quads: 0
Tetrahedra: 43710

Creating mesh object...

Dimension: 3-D
Boundary types: 2 (-2, -1)
Regions: 1 (1,)
Marked nodes: 32 (99,)

Done.
Mesh: Nodes: 8455 Cells: 43710 Boundaries: 90213.

pg.show(mesh_mod, markers=True, showMesh=True)
bert_file = '01_1.udf'

# Import data using PyGimli
BERT = pg.load(bert_file)

# Display information about the imported data
print(BERT)
Data: Sensors: 32 data: 675, nonzero entries: ['a', 'b', 'm', 'n', 'valid']
mgr = ert.ERTManager('01_1.udf')
# Define resistivity mapping (rhomap)
rhomap = [
    [1, 300.0]]
data_mod = ert . simulate (mesh_mod , res=rhomap , scheme=BERT, noiseLevel=1,
                    noiseAbs=1e-6, seed=1337 )
data_mod . save ( 'practice.dat' )
data = pg.load("practice.dat")
print(data)
mgr = ert.ERTManager('practice.dat')
 mesh_mod['marker']=0
mgr.invert(verbose=True,mesh=mesh_mod,lam=10)

#out put of inversion:

23/05/24 - 12:20:52 - pyGIMLi - INFO - Found 1 regions.
23/05/24 - 12:20:52 - pyGIMLi - INFO - Creating forward mesh from region infos.
23/05/24 - 12:20:56 - pyGIMLi - INFO - Creating refined mesh (H2) to solve forward task.
23/05/24 - 12:21:07 - pyGIMLi - INFO - Mesh for forward task: Mesh: Nodes: 63412 Cells: 349680 Boundaries: 360852
23/05/24 - 12:21:15 - pyGIMLi - INFO - Use median(data values)=255.563433298874
23/05/24 - 12:21:15 - pyGIMLi - INFO - Created startmodel from forward operator: 43710, min/max=255.563433/255.563433
23/05/24 - 12:21:15 - pyGIMLi - INFO - Starting inversion.
fop: <pygimli.physics.ert.ertModelling.ERTModelling object at 0x00000193DFA5D2C0>
Data transformation: <pgcore._pygimli_.RTransLogLU object at 0x00000193FAFE8F40>
Model transformation: <pgcore._pygimli_.RTransLog object at 0x00000193DFA5D310>
min/max (data): 148/572
min/max (error): 1%/1%
min/max (start model): 256/256
--------------------------------------------------------------------------------
inv.iter 0 ... chi² =  256.64
--------------------------------------------------------------------------------
inv.iter 1 ... chi² =  243.72 (dPhi = 5.04%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 2 ... chi² =  236.36 (dPhi = 3.02%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 3 ... chi² =  230.17 (dPhi = 2.62%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 4 ... chi² =  223.60 (dPhi = 2.85%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 5 ... chi² =  212.04 (dPhi = 5.17%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 6 ... chi² =  206.51 (dPhi = 2.61%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 7 ... chi² =  201.27 (dPhi = 2.53%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 8 ... chi² =  196.75 (dPhi = 2.25%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 9 ... chi² =  192.43 (dPhi = 2.20%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 10 ... chi² =  188.30 (dPhi = 2.15%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 11 ... chi² =  183.95 (dPhi = 2.31%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 12 ... chi² =  180.17 (dPhi = 2.05%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 13 ... chi² =  176.55 (dPhi = 2.01%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 14 ... chi² =  172.73 (dPhi = 2.16%) lam: 10.0
--------------------------------------------------------------------------------
inv.iter 15 ... chi² =  169.40 (dPhi = 1.93%) lam: 10.0
################################################################################
#                Abort criterion reached: dPhi = 1.93 (< 2.0%)                 #
################################################################################
43710 [255.56343329887392,...,255.69008917555843]

The value of chi2 is too high

commented

Nobody can really help without seeing the mesh (maybe include a figure) and without seeing the data.

First point for high chi-square is having a look at the data. So please compute geometric factors numerically and show the apparent resistivity.

If the data look good, I suggest using total field computation with quadratic shape functions to ensure the quality of the forward operator by something like:

mgr = ERTManager(data, sr=False)
mgr.setMesh(mesh)
mgr.fop._core.createRefinedForwardMesh(True, True)

At any rate, we clearly need an example of ERT on a closed 3D geometry and probably some options to the ERT manager controlling the refinement.