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Python crashing when checking intersection between meshes with vedo

I'm having a really weird behaviour when using vedo's intersectWith() function to check intersection between meshes. I'm checking intersections between thousands of simple planar meshes (basically squares, of the same size, made by 2 triangles, rotated in different angles in both z and x axis) and sometimes, when checking some of those pairs, python crashes. No error, it just crashes in that function.
I found out that when the center point of both meshes is exactly the same, the problem happens. I corrected that by adding noise, but still, some other combinations throw the same problem.
I was able to isolate one of the cases and make a small testing example that produces the crash:
m1v = np.array([[17903.93947473, 11418.12995419, 2572.68075251],[17889.43531656, 11423.09300945, 2546.89320749],[17913.65204344, 11446.51421055, 2572.68075251],[17899.14788527, 11451.47726581, 2546.89320749]])
m2v = np.array([[17897.68174692, 11454.30365475, 2573.22453367],[17917.8546173 , 11442.45883457, 2554.44274633],[17882.4917027 , 11428.43354543, 2573.22453367],[17902.66457308, 11416.58872525, 2554.44274633]])
m1f = [[0,1,2],[1,2,3]]
m1 = vd.Mesh([m1v,m1f])
m2 = vd.Mesh([m2v,m1f])
m1.intersectWith(m2,tol=1e-06)
I suspect that if (i don't know really..) maybe some coordinates of the vertices are the same, for some reason it crashes (maybe some division by 0 or something in the intersect check).
Has anybody working with vedo (or vtk, vedo is a wraapper of vtk) had the same issue or has any idea why it's happening?

Problems re-implementing the fipy mesh20x20 example from my own IDE

I am currently using fipy but am still relatively new to the nuiances associated with the package. While I have been able to regenerate the desired heatmap from the examples folder in for the mesh20x20 diffusion example using the command line, I have struggled to replicate it within a Spyder IDE. I am using python version 3.8 . It is simple enough to generate it using the "examples" folder from the command line the command line image generated, however, when I attempt to "re-program" it I end up with iterations of the following. the following result. I am hoping to be able to regenerate the smooth color transition from the examples folder, as opposed to the discrete dichromatic option that I have been limited to at present. I believe there is some issues with the viewer in some capacity I believe some related issues may have cropped up in the past for others, potentially as it relates to colorbar reformatting, though I have not yet been capable of effectively implementing these workarounds to generate the desired imagery. datamin and datamax in Viewer() did not work
I would be greatly indebted for any assitance the community could provide.
from fipy.terms.transientTerm import TransientTerm
from fipy.terms.implicitDiffusionTerm import ImplicitDiffusionTerm
from fipy.terms.explicitDiffusionTerm import ExplicitDiffusionTerm
from fipy.meshes.nonUniformGrid2D import NonUniformGrid2D
from fipy.variables.cellVariable import CellVariable
from fipy.viewers.matplotlibViewer.matplotlib2DViewer import Matplotlib2DViewer
####
#Global Inputs
D=1
steps=10
#Dimensional Inputs
nx=20
dx=1
ny=20
dy=1
L=dx*nx
#Temporal Inputs
#nt=20
#dt=1
#cell variable initial values
value=0
#construct mesh from dimensional pts
mesh=NonUniformGrid2D(nx=nx, dx=dx, ny=ny, dy=dy)
#construct term variables phi with name, mesh design
phi=CellVariable(name="solutionvariable", mesh=mesh, value=0)
#construct boundary conditions
#dirichlet ---> we can an automatic application of neumann to top right and bottom left
valueTopLeft=0
valueBottomRight=1
#assign boundary conditions to a face or cell
X, Y=mesh.faceCenters
facesTopLeft=((mesh.facesLeft & (Y > L/2 )) | (mesh.facesTop &( X < L/2)))
facesBottomRight=((mesh.facesRight & (Y < L/2)) | (mesh.facesBottom & (X > L/2)))
#constrain variables
phi.constrain(valueTopLeft, facesTopLeft)
phi.constrain(valueBottomRight, facesBottomRight)
#equation construction
eq=TransientTerm()==ExplicitDiffusionTerm(coeff=D)
#equation solving and either viewing and/or extraction
timestepduration=0.9 *(dx**2)/(2*D)
for step in range(steps):
eq.solve(var=phi, dt=timestepduration)
print(phi[step])
viewer=Matplotlib2DViewer(vars=phi, datamin=0, datamax=1)
viewer.axes.set_title("Solutionvbl(Step %d)" % (step+1,))

Figured it out I think. I was using ExplicitDiffusion and the example utilizes ImplicitDiffusion. When I tried this all I got back was a blank monochromatic image (and returned zeros for my phi[step] at the end. I am happy to report that once a "kickstart" value is provided in the value section for cellVariable (I used 0.001), and utilized in conjunction with ImplicitDiffusion, and the timestepduration is increased from its limit of 0.9x**2/2D to the utilized 9x**2/2D used in the example documentation it more or less adheres to the image generated when run from the command line. Grateful to have this sorted. Hope this provides assistance to anyone else who might run into a similar problem.

Corner Refine Method, CORNER_REFINE_SUBPIX, from AcUro with Python and OpenCV

Hi There
I want to increase the accuracy of the marker detection from aruco.detectMarkers. So, I want to use Corner Refine Method with CORNER_REFINE_SUBPIX, but I do not understand how it is implemented in python.
Sample code:
frame = cv.imread("test.png")
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
para = aruco.DetectorParameters_create()
det_corners, ids, rejected = aruco.detectMarkers(gray,dictionary,parameters=para)
aruco.drawDetectedMarkers(frame,det_corners,ids)
Things I have tried:
para.cornerRefinementMethod()
para.cornerRefinementMethod(aruco.CORNER_REFINE_SUBPIX)
para.cornerRefinementMethod.CORNER_REFINE_SUBPIX
para = aruco.DetectorParameters_create(aruco.CORNER_REFINE_SUBPIX)
para = aruco.DetectorParameters_create(para.cornerRefinementMethod(aruco.CORNER_REFINE_SUBPIX))
They did not work, I’m pretty new to python ArUco so I hope that there is a simple and obvious solution.
I would also Like to implement enclosed markers like in the Documentation(Page 4). Do you happen to know if there is a way to generate these enclosed markers in python?

Concerning the first part of your question, you were pretty close: I assume your trouble is in switching and tweaking the "para" options. If so, you only need to set the corresponding values in the parameters object like
para.cornerRefinementMethod = aruco.CORNER_REFINE_SUBPIX
Note that "aruco.CORNER_REFINE_SUBPIX" is simply an integer. You can verify this by typing type(aruco.CORNER_REFINE_SUBPIX) in the console. Thus assigning values to the "para" object works like mentioned above.
You might also want to tweak the para.cornerRefinementWinSize which seems to be implemented in units of code pixels, not actual image pixel units.
Concerning the second part, you might have to write a function, that adds the boxes at the corner points, which you can get using the detectMarker function. Note that the corner points are always ordered clockwise, thus you can easily assign the correct offset values (like "up & left", "up & right" etc.).

para.cornerRefinementMethod = 1
may work.

Abaqus Python getByBoundingBox command

I have a 2D part in Abaqus with many partitions and I therefore want to select many edges with the getByBoundingBox command to create a surface set. This is the bit of code I have:
p = mdb.models['Model-1'].parts['Plate']
s = p.edges
edges = s.getByBoundingBox((0,0.02,0,0.003,0.04,0))
p.Surface(side1Edges=edges, name='r1')
But it gives me the following error: "edges = s.getByBoundingBox((0,0.02,0,0.003,0.04,0)) TypeError: arg1; found tuple, expecting float".
Any advice much appreciated.

The corners of the bounding box should be provided as 6 separate numbers and not as a single tuple. The solution is very simple, just change the leading "((" and trailing "))" to single "(" and ")". So the call looks like this s.getByBoundingBox(0,0.02,0,0.003,0.04,0).

this comes quite late but in case anyone enters and has the same doubt:
When telling to Abaqus which edge/face/element you are actually selecting, sometimes you need to specify the "ID" of that object, that's why it's asking for a float instead of a tuple in the error message. This can be solved as:
You select the edge/face/node/element you want:
edge = s.getByBoundingBox((0,0.02,0,0.003,0.04,0))
Create a intermediate variable to know the "ID" of the element:
edge_id = edge.id
You now can refenciate it in the dialog for creating surfaces:
p.Surface(side1Edges=p.edges[edge_id], name='r1')
In this case, you're telling Abaqus to select the edge with the id "edge_id" from all the edges that your part "p" has.
This happens many times and you've to be aware what Abaqus is expecting from the code. Sometimes can be the object itselft, a tuple of elements or simply a float expressed as a tupple e.g: edge = (number, )
Regards

I tried the modified code on a 2D plate with the following code
p = mdb.models['Model-1'].parts['Plate']
s = p.edges
edges=s.getByBoundingBox(0,0,0,25,25,1)
And it does not crash. But its not really clear how you can create a surface using this. You need to use a different strategy to achieve what you want. You can find create a surface using the 'pointOn' method.

Python, generating a ten Point polygon

I am attempting to generate a polygon with Points.
I am using Python 3.4 on Windows 7.
I would like to know where my error is in this line of code.
leftEar = Polygon(Point(158,218), Point(160,208), Point(166,197), Point(174,186), Point(183,180), Point(190,179), Point(195,184), Point(197,191), Point(193,199), Point(184,210))
leftEar.setFill("blue")
leftEar.setOutline("black")
LeftEar.draw(win)
These points were all gathered from within a graphic window using another line of code provided to me by another person. Posting that into this window is nearly impossible, even when I hand type it in using only the space bar to obtain the indentations.

You have capitalised the 'L' of LeftEar in the final line.