er from moltiple curves the represent the area of floor plans,
but the problem is, I cant fine a way to intelligently divide the curves - responsively to the radiation analysis color (for example - that yelow area on of the building will have more division on each floor plan)
do you have any ideas on how to do that?
i tried to use attractors be failed miserably..
THANKS,
Limor.…
write a definition that represents the following surface that I have created out of paper.
This is essentially a squared surface subdivided into triangular segments. For that reason I was hoping I could use Zubin's example about triangles in chapter 3 of his book.
I'm sure, you guys know these kind of folding technique, but to clarify the pattern of the surface, here's a quick diagram:
My approach was to use the point cloud out of Zubani's example and select points with the Cull Nth component according to the pattern shown in the diagram. These points I would then offset with a z-vector component while keeping the distance between the points fixed.
However, after spending now several days trying to figure this out, I definitely ran into a wall..
As I see it, the example generates multiple points for the same coordinates, meaning there are occasions where there 6 points on top of each other.
Further, the Cull Nth component doesn't work exactly as I've hoped, the problem lies in the transition from one row to another..
I was also thinking instead of creating a series of points and then trying to filter specific points out to create (a) the surfaces and (b) the offset, maybe I should start creating these separate lists from the beginning?
Or, instead of point cloud series, using a surface and the sDivide component?
As you see, I am pretty confused/lost in the problem... any help would be greatly appreciated!
Thanks!
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aching my skill set here, but bare with me.
I want to create an animated facade of squares which rotate depending on a sequence of grey-scale images. I've got pretty far thanks to many discussions here, but have hit a blank with exporting my animated model to 3ds max.
Here's my GH script - it's a botch of 3 or 4 various things incorporating centipede at the start and end to get the animation.
All good and it works! It produces animations which I can sequence for presentations too thanks to it's bmp export, which is sort of a side-product.
What I have a problem is that the OBJs it produces error wildly when imported to max. eg in rhino it looks like
But when I've imported them to max it looks like
and as it animates it just gets longer and smaller.
NOW I reckon it might be because my model in grasshopper is 100 separate geometries and it'd like it to be a single one - but I've not achieved that.
Does anyone have any ideas how to solve this? My end result I would like to look like this rendered still from max, but animated.
Thankyou all! This also uses Firefly, so you might need that installed to see how my file works.
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Added by chris parrott at 10:34am on September 11, 2015
and Grasshopper. Recently I tried doing some test project just to see what can I do. My target is to design a small house for an atom family. Though as you might think - it'll be a parametric one. And I encountered exactly what's in the title. So here it goes: 1. Something is wrong with the measuring units in the complex profiles. I met this problem while making I-beam. In ArchiCAD it had 127/76 mm while in Grasshopper i had 127000/76200mm so a little bigger. 2. I'm unable to turn off the preview. I mean when I delete something in Grasshopper/Rhino it still exists in ArchiCAD. I have to unlock it and then delete it. 3. Coordinates for points seem broken. They have to be multiplied 1000 times to match. 4. Now one of the most important. Is it possible to somehow SHOW Grasshopper where are already made in ArchiCAD objects. Even if they'll remain still. For example I want to make a parametrical roof. Do I have to model whole building from scratch in Grasshopper or is there some fast way to "import" existing scene so I can limit my work with Grasshopper only to parametrical one. 5. Is it possible to make "points" as controlling points in AC? Like, if I'd like to make a beam in a desired place which I will mark by that point and then I will "show" Grasshopper that point and tell it to make an object in there so I can control it within grasshopper. I tried ti do this using AC Control Point but when I click "Send changes" button, Grasshopper and Rhino crush immediately. It only happens then, with control points. 6. It seems that "move" component won't work with "2D curve" component connected directly. It is possible that some of those problems are outdated. I was playing around in Grasshopper a few months ago, before summer break, but now I plan to try something new and it would be nice to know what to do. I appreciate any answer to any of those questions. Please help, you guys, are my only hope. Thanks in advance! Karol…
t file** - ply file with just x,y,z locations. I got it from a 3d scanner. Here is how first few lines of file looks like - ply format ascii 1.0 comment VCGLIB generated element vertex 6183 property float x property float y property float z end_header -32.3271 -43.9859 11.5124 -32.0631 -43.983 11.4945 12.9266 -44.4913 28.2031 13.1701 -44.4918 28.2568 13.4138 -44.4892 28.2531 13.6581 -44.4834 28.1941 13.9012 -44.4851 28.2684 ... ... ... In case you need the data - please email me on **nisha.m234@gmail.com**. **Algorithm:** I am trying to find principal curvatures for extracting the ridges and valleys. The steps I am following is: 1. Take a point x 2. Find its k nearest neighbors. I used k from 3 to 20. 3. average the k nearest neighbors => gives (_x, _y, _z) 4. compute covariance matrix 5. Now I take eigen values and eigen vectors of this covariance matrix 6. I get u, v and n here from eigen vectors. u is a vector corresponding to largest eigen value v corresponding to 2nd largest n is 3rd smallest vector corresponding to smallest eigen value 7. Then for transforming the point(x,y,z) I compute matrix T T = [ui ] [u ] [x - _x] [vi ] = [v ] x [y - _y] [ni ] [n ] [z - _z] 8. for each i of the k nearest neighbors:<br> [ n1 ] [u1*u1 u1*v1 v1*v1] [ a ]<br> [ n2 ] = [u2*u2 u2*v2 v2*v2] [ b ] <br> [... ] [ ... ... ... ] [ c ] <br> [ nk ] [uk*uk uk*vk vk*vk]<br> Solve this for a, b and c with least squares 9. this equations will give me a,b,c 10. now I compute eigen values of matrix [a b b a ] 11. This will give me 2 eigen values. one is Kmin and another Kmax. **My Problem:** The output is no where close to finding the correct Ridges and Valleys. I am totally Stuck and frustrated. I am not sure where exactly I am getting it wrong. I think the normal's are not computed correctly. But I am not sure. I am very new to graphics programming and so this maths, normals, shaders go way above my head. Any help will be appreciated. **PLEASE PLEASE HELP!!** **Resources:** I am using Visual Studio 2010 + Eigen Library + ANN Library. **Other Options used** I tried using MeshLab. I used ball pivoting triangles remeshing in MeshLab and then applied the polkadot3d shader. If correctly identifies the ridges and valleys. But I am not able to code it. **My Function:** //the function outputs to ply file void getEigen() { int nPts; // actual number of data points ANNpointArray dataPts; // data points ANNpoint queryPt; // query point ANNidxArray nnIdx;// near neighbor indices ANNdistArray dists; // near neighbor distances ANNkd_tree* kdTree; // search structure //for k = 25 and esp = 2, seems to got few ridges queryPt = annAllocPt(dim); // allocate query point dataPts = annAllocPts(maxPts, dim); // allocate data points nnIdx = new ANNidx[k]; // allocate near neigh indices dists = new ANNdist[k]; // allocate near neighbor dists nPts = 0; // read data points ifstream dataStream; dataStream.open(inputFile, ios::in);// open data file dataIn = &dataStream; ifstream queryStream; queryStream.open("input/query.
pts", ios::in);// open data file queryIn = &queryStream; while (nPts < maxPts && readPt(*dataIn, dataPts[nPts])) nPts++; kdTree = new ANNkd_tree( // build search structure dataPts, // the data points nPts, // number of points dim); // dimension of space while (readPt(*queryIn, queryPt)) // read query points { kdTree->annkSearch( // search queryPt, // query point k, // number of near neighbors nnIdx, // nearest neighbors (returned) dists, // distance (returned) eps); // error bound double x = queryPt[0]; double y = queryPt[1]; double z = queryPt[2]; double _x = 0.0; double _y = 0.0; double _z = 0.0; #pragma region Compute covariance matrix for (int i = 0; i < k; i++) { _x += dataPts[nnIdx[i]][0]; _y += dataPts[nnIdx[i]][1]; _z += dataPts[nnIdx[i]][2]; } _x = _x/k; _y = _y/k; _z = _z/k; double A[3][3] = {0,0,0,0,0,0,0,0,0}; for (int i = 0; i < k; i++) { double X = dataPts[nnIdx[i]][0]; double Y = dataPts[nnIdx[i]][1]; double Z = dataPts[nnIdx[i]][2]; A[0][0] += (X-_x) * (X-_x); A[0][1] += (X-_x) * (Y-_y); A[0][2] += (X-_x) * (Z-_z); A[1][0] += (Y-_y) * (X-_x); A[1][1] += (Y-_y) * (Y-_y); A[1][2] += (Y-_y) * (Z-_z); A[2][0] += (Z-_z) * (X-_x); A[2][1] += (Z-_z) * (Y-_y); A[2][2] += (Z-_z) * (Z-_z); } MatrixXd C(3,3); C <<A[0][0]/k, A[0][1]/k, A[0][2]/k, A[1][0]/k, A[1][1]/k, A[1][2]/k, A[2][0]/k, A[2][1]/k, A[2][2]/k; #pragma endregion EigenSolver<MatrixXd> es(C); MatrixXd Eval = es.eigenvalues().real().asDiagonal(); MatrixXd Evec = es.eigenvectors().real(); MatrixXd u,v,n; double a = Eval.row(0).col(0).value(); double b = Eval.row(1).col(1).value(); double c = Eval.row(2).col(2).value(); #pragma region SET U V N if(a>b && a>c) { u = Evec.row(0); if(b>c) { v = Eval.row(1); n = Eval.row(2);} else { v = Eval.row(2); n = Eval.row(1);} } else if(b>a && b>c) { u = Evec.row(1); if(a>c) { v = Eval.row(0); n = Eval.row(2);} else { v = Eval.row(2); n = Eval.row(0);} } else { u = Eval.row(2); if(a>b) { v = Eval.row(0); n = Eval.row(1);} else { v = Eval.row(1); n = Eval.row(0);} } #pragma endregion MatrixXd O(3,3); O <<u, v, n; MatrixXd UV(k,3); VectorXd N(k,1); for( int i=0; i<k; i++) { double x = dataPts[nnIdx[i]][0];; double y = dataPts[nnIdx[i]][1];; double z = dataPts[nnIdx[i]][2];; MatrixXd X(3,1); X << x-_x, y-_y, z-_z; MatrixXd T = O * X; double ui = T.row(0).col(0).value(); double vi = T.row(1).col(0).value(); double ni = T.row(2).col(0).value(); UV.row(i) << ui * ui, ui * vi, vi * vi; N.row(i) << ni; } Vector3d S = UV.colPivHouseholderQr().solve(N); MatrixXd II(2,2); II << S.row(0).value(), S.row(1).value(), S.row(1).value(), S.row(2).value(); EigenSolver<MatrixXd> es2(II); MatrixXd Eval2 = es2.eigenvalues().real().asDiagonal(); MatrixXd Evec2 = es2.eigenvectors().real(); double kmin, kmax; if(Eval2.row(0).col(0).value() < Eval2.row(1).col(1).value()) { kmin = Eval2.row(0).col(0).value(); kmax = Eval2.row(1).col(1).value(); } else { kmax = Eval2.row(0).col(0).value(); kmin = Eval2.row(1).col(1).value(); } double thresh = 0.0020078; if (kmin < thresh && kmax > thresh ) cout << x << " " << y << " " << z << " " << 255 << " " << 0 << " " << 0 << endl; else cout << x << " " << y << " " << z << " " << 255 << " " << 255 << " " << 255 << endl; } delete [] nnIdx; delete [] dists; delete kdTree; annClose(); } Thanks, NISHA…
R_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh Butterfly is running blockMesh. PID: 1837 SET DOCKER_TLS_VERIFY=1&SET DOCKER_HOST=tcp://192.168.99.100:2376&SET DOCKER_CERT_PATH=C:\Users\akiwya\.docker\machine\machines\default&SET DOCKER_MACHINE_NAME=default&docker exec -i 4c9bb2f7444b pgrep snappyHexMesh
/*---------------------------------------------------------------------------*\ | ========= | | | \\ / F ield | OpenFOAM: The Open Source CFD Toolbox | | \\ / O peration | Version: v1612+ | | \\ / A nd | Web: www.OpenFOAM.com | | \\/ M anipulation | | \*---------------------------------------------------------------------------*/ Build : v1612+ Exec : blockMesh Date : May 22 2017 Time : 08:51:50 Host : "default" PID : 1837 Case : /home/ofuser/workingDir/butterfly/outdoor_airflow nProcs : 1 sigFpe : Enabling floating point exception trapping (FOAM_SIGFPE). fileModificationChecking : Monitoring run-time modified files using timeStampMaster (fileModificationSkew 10) allowSystemOperations : Allowing user-supplied system call operations
// * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * // Create time
Creating block mesh from "/home/ofuser/workingDir/butterfly/outdoor_airflow/system/blockMeshDict" Creating block edges No non-planar block faces defined Creating topology blocks Creating topology patches
Creating block mesh topology
Check topology
Basic statistics Number of internal faces : 0 Number of boundary faces : 6 Number of defined boundary faces : 6 Number of undefined boundary faces : 0 Checking patch -> block consistency
Creating block offsets Creating merge list .
Creating polyMesh from blockMesh Creating patches Creating cells new cannot satisfy memory request. This does not necessarily mean you have run out of virtual memory. It could be due to a stack violation caused by e.g. bad use of pointers or an out of date shared library Runtime error (PythonException):
Butterfly failed to run OpenFOAM command! new cannot satisfy memory request. This does not necessarily mean you have run out of virtual memory. It could be due to a stack violation caused by e.g. bad use of pointers or an out of date shared library Traceback: line 51, in script
I don't really have any knowledge in CFD simulation and only watched the tutorials and managed to get the sample files to work. So this time, I replaced the starting geometry my building which is a curve building, I wonder if that is the issue that caused this problem. Can anyone enlighten me on the issue?
Warm regards,
Annie…
st variety of papers (mostly related with LIDAR airborne sampled clouds) ... but ... hmm ... no code (other than some "abstract" algos that may (or may not) work). Reason? A very hot cake that one these days: from reverse engineering to DARPA founded future defense systems and up to cruse missiles pattern recognition algos.
The solution (obviously doable only via code) is the so called flat hard clustering ... were points are sampled into clusters based on the coPlanarity "rule". For large amounts recursive octTrees (an oriented box divided in 8 "partitions") subdivisions are used and then pts are processed in parallel (and then clusters are re-evaluated in order to "absorb" other clusters with same plane A,B,C,D vars etc etc).
See what's happening in a very carefully made test point collection:
3.7 ms and the "ideal" clustering (7 search loops VS the max 42M theoretical threshold):
Depending on the pts "preparation" ... a considerable more time/search loops is required ... and ... well ... also "valid" clusters (4 points and up) made:
So "ideally" speaking in your case:
1. Mesh faces center points (or alternatively: mesh vertices) are sampled into a pts collection .
2. Hard flat coPlanarity clustering is attempted yielding pts/planes in equivalent DataTrees.
3. Planar Breps are made with respect the planes (like the black things captured above) and sampled, say, into a breps List.
4. The method Brep[] solids = Brep.CreateSolid(breps); is used for attempting to create your desired "engulfing" brep. This method is very slow mind (other waaaay faster approaches also available).
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to run at full screen. I've gone as far as using an iPad to use as the second monitor via AirDisplay (which actually works really well) but have never been satisfied with any setup that required you to look back and forth as if at a tennis match all day long.
Not long after first using Grasshopper 3+ years ago I've had the desire for a "Live Viewport" component that would allow a live image of the 3d geometry being generated directly in the canvas. Every once in a while I search the forums with the hope of finding a solution, but always come up empty handed. Someday this might exist although for now I have found what might be the next best thing to a native "Live Viewport" component and its enabled with a small app named Sticky Previews. This app uses the task bar preview feature within Windows 7's aero interface to create custom, floating preview windows from any open window currently running. I've only just discovered the app, but it seems to do the trick and has been stable and problem free so far. -- I will post an update if I find out that I might have spoken too soon. The install allows for a 30 day trial and is $15 bucks to purchase. I just found the app and don't know anything about this group that created the app. If you happen to know of them, Id be curious to find out more.
divided windows, cramped and slow;
unified window with floating rhino model preview;
link to the apps webpage;
http://www.ntwind.com/software/sticky-previews.html
Also works with other apps;
and the about me page screen shot;
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Added by Tyler Selby at 11:25pm on November 26, 2012