should follow the instruction which mostapha has wrote in https://github.com/mostaphaRoudsari/ladybug/blob/master/resources/I...
Instructions for Installing Ladybug + Honeybee: (Follow steps 1-6 for basic functionality and 1-11 for full functionality) 0. If you have an old version of LB+HB, download the file here (https://app.box.com/s/ds96em9l6stxpcw8kgtf) and open it in Grasshopper to remove your old Ladybug and Honeybee version. 1. Make sure that you have a working copy of both Rhino and Grasshopper installed. 2. Open Rhino and type "Grasshopper" into the command line (without quotations). Wait for grasshopper to load. 3. Install GHPython by downloading the file at this link (http://www.food4rhino.com/project/ghpython?ufh) and drag the .gha file onto the Grasshopper canvas. 4. Select and drag all of the files in the "userObjects" folder (downloaded with this instructions file) onto your Grasshopper canvas. You should see Ladybug and Honeybee appear as tabs on the grasshopper tool bar. (If you are reading this instruction on github you can download them from http://www.food4rhino.com/project/ladybug-honeybee) 5. Download the files at this link (https://app.box.com/s/bh9sbpgajdtmmystv3n4), unzip them and copy the contents to both C:\ladybug and C:\Users\[yourUsername]\AppData\Roaming\Ladybug. 6. Restart Rhino and Grasshopper. You now have a fully-functioning Ladybug. For Honeybee, continue to the following: 7. Install Radiance to C:\Radiance by downloading it from this link (https://github.com/NREL/Radiance/releases/download/4.2.2/radiance-4...) and running the exe. 6. Install Daysim to C:\DAYSIM by downloading it at this link (http://daysim.ning.com/page/download) and running the exe. 8. Install Energy Plus 8.1 to C:\EnergyPlusV8-1-0 by going to the DOE website (http://apps1.eere.energy.gov/buildings/energyplus/energyplus_downlo...), making an account, going to "download older versions of EnergyPlus, selecting 8.1 and running the exe. 9. Copy falsecolor2.exe (http://pyrat.googlecode.com/files/falsecolor2.exe) and evalglare.exe (http://www.ise.fraunhofer.de/en/downloads-englisch/software/evalgla...) to C:\Radiance\bin 10. Download the OpenStudio Libraries (https://app.box.com/s/y2sx16k98g1lfd3r47zi) and unzip them to C:\ladybug\OpenStudio. 11. You now have a fully-working version of Ladybug + Honeybee. Get started visualizing weather data with these video tutorials (https://www.youtube.com/playlist?list=PLruLh1AdY-Sj_XGz3kzHUoWmpWDX...).
It works for me..
Agus…
decided to concentrate my effort today on this problem and manage to come up with a solution !
I will explain it if somebody else is looking for a similar solution.
Finally my only problem was to create an alternating true/false list that inverse at certain index, this what I came up with: I have a list of points and random index , the box and sphere represent true and false, and the blue sphere is the node(index) where I want to see an inversion.
In reality, it was pretty simple, I just didn't know the right modules. (In yellow, it's the most important part of the patch)(Sorry for the spelling mistake)
Here is a diagram of what I did: I created a list going to 1 to [number of lines], here it's 1 to 10, I had node at 3-4 and 7-8. For each node I created a list of 1 repeated [(number of lines)-index] times. Here, 7 (10-3) and 3 (10-7) times.
After grafting everything, I add everything in mass addition module. I had my final list which I checked if it was divisible by two.
It was more of a logic problem than a grasshopper problem.
Here it is the initial shape with what I wanted !
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three categories, each one corresponding to different shapeType_ input:- polygons (shapeType_ = 0): anything consisted of closed polygons: buildings, grass areas, forests, lakes, etc
- polylines (shapeType_ = 1): non closed polylines as: streets, roads, highways, rivers, canals, train tracks ...- points (shapeType_ = 2): any point features, like: Trees, building entrances, benches, junctions between roads... Store locations: restaurants, bars, pharmacies, post offices...
So basically when you ran the "OSM shapes" component with the shapeType_ = 2, you will get a lot of points. If you would like to get only 3d trees, you run the "OSM 3D" component and it will create 3d trees from only those points which are in fact trees. You can also check which points are trees by looking at the exact location on openstreetmap.org. For example:
Or use the "OSM Search" component which will identify all trees among the points, regardless of whether 3d trees can be created or not.However, when it comes to 3d trees there is a catch:
Sometimes the geometry which Gismo streams from OpenStreetMap.org does not contain a "height" key. Or it does contain it but the value for that key is missing.OpenStreetMap is free editable map database, so anyone with internet access and free registered account on openstreetmap.org can add features (like trees) to the map database. However, regular people sometimes do not have height measuring devices which are needed for specific objects as trees.So "OSM 3D" component will generate 3d trees from only those tree points which contain a valid "height" key.However, a small workaround is to input a domain(range) into the randomHeightRange_ input of "OSM 3D" component (for example the following one: "5 to 10"):
This will result in creation of other 3d trees which do not have defined height, by randomizing their height. randomHeightRange_ input can also be applied to 3d buildings, and it is definitively something I need to write a separate article on.
In the end it may be that nobody mapped the trees in the area you are looking for.
After you map a tree to openstreetmap.org then it will instantly be available to you or any other user of Gismo. I will be adding some tutorials in the future on how this can be done. But probably not in the next couple of weeks.
Let me know if any of this helps, or if I completely misunderstood your issue.…
Added by djordje to Gismo at 3:52am on February 8, 2017
Ladybug + Honeybee:
(Follow steps 0-4 for basic functionality and 0-9 for full functionality)
0. If you have an old version of LB+HB, download the file here (https://app.box.com/s/ds96em9l6stxpcw8kgtf)
and open it in Grasshopper to remove your old Ladybug and Honeybee version.
1. Make sure that you have a working copy of both Rhino and Grasshopper installed.
2. Open Rhino and type "Grasshopper" into the command line (without quotations). Wait for grasshopper to load.
3. Install GHPython 0.6.0.3 by downloading the file at this link (http://www.food4rhino.com/project/ghpython?ufh) and
drag the .gha file onto the Grasshopper canvas.
4. Select and drag all of the userObject files (downloaded with this instructions file) onto your Grasshopper canvas.
You should see Ladybug and Honeybee appear as tabs on the grasshopper tool bar.
(If you are reading this instruction on github you can download them from http://www.food4rhino.com/project/ladybug-honeybee)
5. Restart Rhino and Grasshopper. You now have a fully-functioning Ladybug. For Honeybee, continue to the following:
6. Install Radiance to C:\Radiance by downloading it from this link (https://github.com/NREL/Radiance/releases/download/4.2.2/radiance-4.2.2-win32.exe) and running the exe.
7. Install Daysim 4.0 for Windows to C:\DAYSIM by downloading it at this link (http://daysim.ning.com/page/download) and running the exe.
8. Install EnergyPlus 8.1 to C:\EnergyPlusV8-1-0 by going to the DOE website (http://apps1.eere.energy.gov/buildings/energyplus/energyplus_download.cfm), making an account, going to "download older
versions of EnergyPlus, selecting 8.1 and running the exe.
9. Copy falsecolor2.exe (http://pyrat.googlecode.com/files/falsecolor2.exe) and evalglare.exe (http://www.ise.fraunhofer.de/en/downloads-englisch/software/evalglare_windows.zip/at_download/file) to C:\Radiance\bin
10. You now have a fully-working version of Ladybug + Honeybee. Get started visualizing weather data with these video tutorials (https://www.youtube.com/playlist?list=PLruLh1AdY-Sj_XGz3kzHUoWmpWDXNep1O).
After I've done all the above I followed this video
https://vimeo.com/96155674
And everything works well.
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nted" in space (at instance definition creation phase): indicates the obvious fact that if garbage in > garbage out (try it).
2. Load the GH thing. Task for you: Using Named Views locate the points of interest as described further and make a suitable view. That way you can navigate rather easily around (hope dies last).
3. Your attractors are controlled from here:
The slider in blue picks some attractor to play with. You can use this while the K2 is running.
4. Don't change anything here (think of it as a black box: who cares how it works? nobody actually):
5. Enable the other "black box": job done your real-life stuff is placed:
6. Enable the solver: your "real-life" things start to bounce around:
7. Go there are play with the slider. A different attractor yields an other solution:
8. With real-life things in place if you disable the C# ... they are instantly deleted and you are back in lines/points and the likes:
9. Either with instance definitions or Lines/points change ... er ... hmm ... these "simple" parameters and discover the truth out there:
10. Since these are a "few" and they affect the simulation with a variety of ways ... we need a "self calibrating" system: some mini big Brother that does the job for us. Kinda like applying safely the brakes when it rains (I hate ABS mind).
NOTE: the rod with springs requires some additional code ,more (that deals with NESTED instance definitions) in order to (b) bounce as a whole and at the same time (b) elongates or shrinks a bit.
More soon.
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ng/702/30
EDIT: DK2 works, not with positional tracking yet (14/09/15)
Source is here:
https://github.com/provolot/RhinoRift
Steps:
1) Download these files (also attached below):
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper_v0.4.ghx
https://github.com/provolot/oculus-grasshopper/raw/master/OpenTrackRiftGrasshopperUDP.ini
https://github.com/provolot/oculus-grasshopper/raw/master/oculus-grasshopper-test_v0.1.3dm
2) Download OpenTrack - http://ananke.laggy.pk/opentrack/, and setup/install. Once installed, double-click to open.
3) In OpenTrack, load the 'OpenTrackRiftGrasshopperUDP.ini' profile. Click the 'Start' button and move your Rift around - make sure that it looks like the Yaw/Pitch/Roll data is being sent. TX/TY/TZ will all be 0, as Oculus doesn't have absolute positioning data.
4) In Rhino, open the test 3dm. You'll notice that there are two viewports - called 'LeftEye' and 'RightEye'. These have been placed to mimic where the screens should be for the Oculus Rift --- but only when Rhino is in fullscreen mode, with the command 'Fullscreen'. The placement needs to be tweaked, but should work.
If you want to use your own model, you can load your own .3dm file in Rhino, then you can right-click on the viewport name, and go to Viewport Layout > Read from File. If you then load my test file, Rhino should open my two viewports, sized correctly, onto your model.
The placement of these viewports need to be tweaked; if you find a better viewport layout, upload an empty Rhino file with your viewports, and we can share eye-layout 'templates'!
5) In Grasshopper, open the .ghx definition. Everything that is multiple-grouped is a value that can be changed. Two things here:
- IPD: Set this and convert it to the proper units for your model.
- Left/right viewport names. In this case, leave this as-is, since you're using my example file.
6) Turn on the Grasshopper Timer, if it isn't on already.
7) In the GH definition, toggle 'SyncEyes' to be True. Then, in the left viewport, try orbiting around with the mouse. The 'RightEye' viewport should move around as well, pretty much simultaneously.
8) In OpenTrack, click 'Start', then toggle 'ReadUDP' to be True. You should see the 'OpenTrackInfo' panel fill with data that's constantly changing.
9) Move around the landscape with your camera, and when you set on a starting view that's ideal, click the triangle of the Data Dam component to 'store' the data.
10) Finally, toggle 'OculusMove' to be true. If all works correctly, both viewports should move based on the Rift's movement.
Let me know if you have any problems!
Cheers,
Dan…
Added by Dan Taeyoung at 11:47pm on December 10, 2013
. From the Thermal Comfort Indices component, Comfort Index 11 (TCI-11):MRT = f(Ta, Tground, Rprim, e)
with:- Ta = DryBulbTemperature coming from ImportEPW component- Tground = f(Ta, N) where N comes from totalSkyCover input. Tground influences the long-wave radiation emitted by the ground in the MRT calculation.- Rprim defined as solar radiation absorbed by nude man = f(Kglob, hS1, ac)- ac is the clothingAlbedo in % (bodyCharacteristics input)- I can't find any definition in the code of Kglob and hS1. Could you tell me please what are those values referencered to? --> probably the globalHorizontalRadiation but how?- e = vapour pressure calculated from Ta and Relative Humidity input
Do you agree that in this case the MRT does not depend on these inputs: location, meanRadiantTemperature, dewPointTemperature and wind speed?It does not depend neither on the other bodyCharacteristics like bodyPosture, age, sex, met, activityDuration...?
MRT calculated by the TCI-11 method is the mean radiant temperature of a vector pointing vertically with a sky view factor of 100%?For ParisOrly epw,
2. From the SolarAdjustedTemperature component (that seems to be more used for the UTCI calculation examples on Hydra compared to TCI-11).
In contrast to the TCI-11, this component distinguishes diffuse and direct radiation and contextualizes the calculation thanks to _ContextShading input, right? It can also be applied to a mannequin thanks to the CumSkyMatrix and thus evaluate the dishomogeneity of radiation exposure.This component seems not to consider the influence of vapour pressure on the result --> is it then more precise to put the MRT output (from the TCI) as an input of meanRadTemperature for SolarAdjustedTemperature?The default groundReflectivity is set to 0.25 --> is GroundReflectivity taken into account in the Tground or MRT calculation in the TCI component? If yes, what is the hypothesised groundReflectivity?The default clothing albedo of 37% (TCI-11 bodyCharacteristics) corresponds to Clothing Absorptivity of 63%?
If the CumSkyMatrix input is not supplied, I get 9 results for the mannequin --> where are those points/results coming from?
If the CumSkyMatrix input is supplied,I suppose the calculation of the 482 results correspond to a calculation method similar to the radiation analysis component that is averaged over the analysis period. Right?But I don't understand why the mannequin is composed of 481 faces and meshFaceResult gives 482 results.
Finally, what is the link between the MESH results, the solarAdjustedMRT and the Effective Radiant field ? Is there a paper to have a detailed explanation of the method?
3. Here are some results for the ParisOrly energyplus weather data. You can find here attached the grasshopper definition.There is no shading in this simulation and the result coming from the ThermalComfort indices for MRT is very different compared to the solar adjusted MRT.Why such a big difference and which of the result should be plugged into the UTCI calculation component?
Results for ParisOrly.epwM,D,H:1,1,12
Ta : 6.5°Crh: 100%globalHorizontalRadiation: 54 Wh/m2totalSkyCover: 10MRT (TCI-11): 1.2°C
_CumSkyMtxOrDirNormRad = directNormalRadiation : 0 Wh/m2diffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.64°CMRTDelta: 4.14°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = TasolarAdjustedMRT: 10.47°CMRTDelta: 3.97°C
_CumSkyMtxOrDirNormRad = CumulativeSkyMtxdiffuseHorizontalRad: 54 Wh/m2_meanRadTemp = MRT (TCI-11)solarAdjustedMRT: 5.17°CMRTDelta: 3.97°C
Thanks a lot for your helpRegards,
Aymeric
…
and ran into a little speed bump.
My questions begin by describing what I have so far, and that as the screenshot describes, I have a list of centroids that I have derived out of 40 boxes (generated through a loop and hoopsnake). I have split the 40 centroids into 4 lists using the sift pattern component (1,0,0,0) & (0,1,0,0) & (0,0,1,0) & (0,0,0,1). That ended up with 4 lists each made of 40 items (lots of NULLS in the place of each 0). I then used the clean tree to remove the nulls, and that successfully gave me 4 lists of 10 items each. When feeding the four lists simultaneously to the clean tree component I got a flat list combining the 4 sublists.
Finally my questions:
1- I want to recombine those 4 lists into a single tree structure (1 list with 4 branches, 1 for each of those lists, instead of 1 flat list). I tried the unflatten component but can't seem to get it done the way I want. Please note that I want the number of branches to be variable.
2- Is there a way to automate the sift pattern component generation instead of manually entering the above mentioned patterns? Because I want the pattern generation to be parametric and responsive to the number of loops used earlier to generate the boxes.
Your help is very appreciated, thank you all.
…
stributes structural supports for a uniformly loaded domain using e.g. the internal energy of the loaded domain as fitness. Here the uniformly loaded domain is represented by the trimmed surface. My genomes are the support positions (green crosses), which are restricted to a set of predefined grid points. I’m currently using an (i,j)-coordinate indexing for these grid points (illustrated in the viewport just below) as opposed to a sequential , “one-dimensional” numbering (illustrated in the viewport further down).
(i,j)-indexing systemAltenative, sequential indexing system
The support positions are computed by two gene pools; one governing the i-index, Gene List {i}, and one governing the j-index, Gene List {j}, of each support. The value of slider 0 in Gene List {i} is paired with the value of slider 0 in Gene List {j} etc. and the amount of sliders corresponds to the amount of supports. The screen shot below depicts the slider constellation corresponding to the support distribution depicted above. Unfortunately the j-index represented in the sliders needs remapping as the number of j-indices vary for each i-index (horizontal row of grid points). With the current setup I have 12^6 x 9^6 = 1,6 x 10^12 different genomes. If I were to use the sequential, “one-dimensional” numbering, I would only use one gene pool with sliders ranging from 0 to 76 meaning that remapping could be avoided and thereby having only 76^6 = 1,9 x 10^11 different genomes.
So, my current genome setup causes a bunch of issues related to the Evolutionary Solver: Remapping Changing one of the j-index sliders, will not necessarily change the related support position but it will still facilitate another genome to be calculated by the solver. (This problem could be eliminated by using the sequential, “one-dimensional” numbering)
Switching slider values around If the values of e.g. slider 0 were to be switched around with the values of slider 5, this again would yield a new genome but an identical solution. (This problem cannot be eliminated by using the sequential, “one-dimensional” numbering)
Coincident support positions Two or more supports may be located in the same position. (This problem cannot be eliminated by using the sequential, “one-dimensional” numbering)
I find it impossible to imagine the fictive “fitness landscape” of this problem and not only because of the multidimensional genome characteristic but just as much because of these listed, intertwined peculiarities. I’ve tried running the Simulated Annealing Solver as well, but my experience is that the Evolutionary Solver yields better results. To my awareness, the solver uses some kind of topographical proximity searcher. This is why, I think that the solving process itself benefits more from analysing the (i,j)-index system, in which neighbouring grid points hold more uniform topographical information than the sequential, “one-dimensional” numbering, which might have big ID-numbering gaps between neighbours. Have I understood this correctly?
Cheers…
ow the steps of the successful run when step 1.2 is bypassed (note that the and OpenFOAM session is open in the background while running the Butterfly demo file):
1. create wind tunnel, and use different parameters of (4,4) for _globalRefLevel_ as suggested by Theodoro in this post
2. run blockMesh:
3. run snappyHexMesh:
4. run checkMesh:
5. connect the case from checkMesh to simpleFOAM and run the simulation:
6. the simulation converged at 1865 iteration, but the results visualization part has some problem:
7. so I revised this part according to suggestions from Hagit:
8. and the results can be visualized for P and U values:
The GH file used for the successful run shown above is attached here.
Now, the following is the error I got when the case from the update fvScheme component is used for simpleFOAM simulation:
the warning message on the simpleFOAM component is:
1. Solution exception: --> OpenFOAM command Failed!#0 Foam::error::printStack(Foam::Ostream&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #1 Foam::sigFpe::sigHandler(int) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #2 ? in "/lib64/libc.so.6" #3 double Foam::sumProd<double>(Foam::UList<double> const&, Foam::UList<double> const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #4 Foam::PCG::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #5 Foam::GAMGSolver::solveCoarsestLevel(Foam::Field<double>&, Foam::Field<double> const&) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #6 Foam::GAMGSolver::Vcycle(Foam::PtrList<Foam::lduMatrix::smoother> const&, Foam::Field<double>&, Foam::Field<double> const&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::Field<double>&, Foam::PtrList<Foam::Field<double> >&, Foam::PtrList<Foam::Field<double> >&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #7 Foam::GAMGSolver::solve(Foam::Field<double>&, Foam::Field<double> const&, unsigned char) const in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libOpenFOAM.so" #8 Foam::fvMatrix<double>::solveSegregated(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/lib/libfiniteVolume.so" #9 Foam::fvMatrix<double>::solve(Foam::dictionary const&) in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #10 Foam::fvMatrix<double>::solve() in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #11 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam" #12 __libc_start_main in "/lib64/libc.so.6" #13 ? in "/opt/OpenFOAM/OpenFOAM-v1606+/platforms/linux64GccDPInt32Opt/bin/simpleFoam"
The error message from the readMe! output node is attached below as a text file.
Hope you can kindly advise what the important steps or parameters I might have missed here. I assume it might be related to OpenFOAM rather than with the Butterfly workflow...
Thank you very much!
- Ji
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