e matching with a dedicated component which creates combinations of items. You can find the [Cross Reference] component in the Sets.List panel.
When Grasshopper iterates over lists of items, it will match the first item in list A with the first item in list B. Then the second item in list A with the second item in list B and so on and so forth. Sometimes however you want all items in list A to combine with all items in list B, the [Cross Reference] component allows you to do this.
Here we have two input lists {A,B,C} and {X,Y,Z}. Normally Grasshopper would iterate over these lists and only consider the combinations {A,X}, {B,Y} and {C,Z}. There are however six more combinations that are not typically considered, to wit: {A,Y}, {A,Z}, {B,X}, {B,Z}, {C,X} and {C,Y}. As you can see the output of the [Cross Reference] component is such that all nine permutations are indeed present.
We can denote the behaviour of data cross referencing using a table. The rows represent the first list of items, the columns the second. If we create all possible permutations, the table will have a dot in every single cell, as every cell represents a unique combination of two source list indices:
Sometimes however you don't want all possible permutations. Sometimes you wish to exclude certain areas because they would result in meaningless or invalid computations. A common exclusion principle is to ignore all cells that are on the diagonal of the table. The image above shows a 'holistic' matching, whereas the 'diagonal' option (available from the [Cross Reference] component menu) has gaps for {0,0}, {1,1}, {2,2} and {3,3}:
If we apply this to our {A,B,C}, {X,Y,Z} example, we should expect to not see the combinations for {A,X}, {B,Y} and {C,Z}:
The rule that is applied to 'diagonal' matching is: "Skip all permutations where all items have the same list index". 'Coincident' matching is the same as 'diagonal' matching in the case of two input lists which is why I won't show an example of it here (since we are only dealing with 2-list examples), but the rule is subtly different: "Skip all permutations where any two items have the same list index".
The four remaining matching algorithms are all variations on the same theme. 'Lower triangle' matching applies the rule: "Skip all permutations where the index of an item is less than the index of the item in the next list", resulting in an empty triangle but with items on the diagonal.
'Lower triangle (strict)' matching goes one step further and also eliminates the items on the diagonal:
'Upper Triangle' and 'Upper Triangle (strict)' are mirror images of the previous two algorithms, resulting in empty triangles on the other side of the diagonal line:
…
lts.
In the visualization, points is an interesting option. It's a matter of aesthetics I guess, I go with surfaces :) Also what you can try is selecting Filters -> Slice (you can also find it in the icons above the pipeline viewer), in the Slice options below the pipeline press Z normal and on the Z coordinate press some height relevant to the buildings (e.g. 1.75m a typical human scale). That would show you the flow around the buildings on that height. Experiment with selecting other normals and values. Keep playing with the filters there's some cool things in there. Also you can check out the mailing list and extensive paraview documentation.
Concerning the errors I apologize because I just downloaded your case.
It appears that the decomposeParDict is not included in the system folder. I am not sure if this is due to BF not going through the whole workflow yet or an ommission on our side. Please feel free to add it in Github. I will also note it down and pass it to Mostaph to check. In the meantime please find attached a VERY detailed decomposeParDict file. I took the liberty to set it at 4 processors (the numberOfSubDomains value) and also selected (that is uncommented) the scotch decomposition method. It's the easiest method to use since it is automatic and doesn't require any more inputs on how the domain is decomposed on the x,y,z directions (which would require you to change values in the attached file).
Now, the different folders created are simply snapshots of the current solution at the specific timestep. To control how often the solver is saving change the writeInterval number in the controlDict file. You can also change almost all these values on the fly, while OF is running.
Finally, concerning the other errors of parafoam it seems somehow parafoam is reading the intial condition names instead of actual results from the solution files and it doesn't like it.
Does this happen only when you open the case (i.e. at 0 time) or does it also happen when you move to an other timestep?
Also, are you using paraFoam, paraview or the paraFoam -builtin method?
The extension of the paraFoam file seems to be .foam which means you are probably using the built in viewer. That might be the issue but I'm not sure.
Can you try running paraview, navigate to your case folder, open the .foam file and see if there is still an error?
Also, if it isn't much trouble can you zip one of the time folders and attach it here? I'd like to take a look at what's inside to check against what the error report says.
Once again thanks for testing!
Kind regards,
Theodore.…
radiance parameters to get rid of blotching. To add another level of complexity to my problem, I am running simulations with a translucent material with the following properties: void trans testTrans
0
0
7 0.478 0.478 0.478 0.000 0.010 0.178 0.635
I have had no issues with the renderings when I use clear glazing, as seen on this image:
However the blotching-issue becomes very noticeable when I introduce translucent glazing into the scene:
For the two above cases I used the following parameters:
_av_ is set to 0
xScale is set to 2
_ab_ is set to 6
_dc_ is set to 0.5
_aa_ is set to 0.2
_ad_ is set to 2048
_st_ is set to 0.5
yScale is set to 2
_ps_ is set to 4
_ar_ is set to 64
_as_ is set to 2048
_ds_ is set to 0.25
_pt_ is set to 0.1
_dr_ is set to 1
_pj_ is set to 0.9
_dp_ is set to 256
_dt_ is set to 0.25
_lr_ is set to 6
_dj_ is set to 0.5
_lw_ is set to 0.01
I ran another test with increased Radiance parameters and got the following output:
with the following parameters:
_av_ is set to 0
xScale is set to 6
_ab_ is set to 6
_dc_ is set to 0.75
_aa_ is set to 0.1
_ad_ is set to 4096
_st_ is set to 0.15
yScale is set to 6
_ps_ is set to 2
_ar_ is set to 128
_as_ is set to 4096
_ds_ is set to 0.05
_pt_ is set to 0.05
_dr_ is set to 3
_pj_ is set to 0.9
_dp_ is set to 512
_dt_ is set to 0.15
_lr_ is set to 8
_dj_ is set to 0.7
_lw_ is set to 0.005
Although the second blotching case is much better than the first, it is still very bad for hours when the sun is lower in the sky. The above images are rendered for a clear sky at 18:00 in Germany in a West-facing room.
Sorry for the long post! Can someone help? Kind regards, Örn
…
the space that you are designing and your design intent. Just think about an atrium vs a museum. And now think of the atrium in two different climate zones. As a [lighting] designer you make the decision on how do you want the space to be, how the climate is and then try to take advantage of skylight and/or direct sunlight to achieve your design goals.
2. Yes. There is a watchTheSky component next to sky types which let you visualize the sky. There is also an example file that you can check.
3. This one again depends on your model. For your model I would suggest a minimum number of 4 for your final analysis. -ab is only one of the parameters. Check this slides by John Mardaljevic if you want to have a better understanding of radiance parameters and their effect on the results.
I also added the link to "Tutorial on the Use of Daysim Simulations for Sustainable Design" by Christoph Reinhart to teaching materials. I encourage you to at least read chapters 1 and 2 of the tutorial. Check pages 25 and 27 have two examples about selecting the parameters.
Great questions. Keep them coming.
Mostapha…
the space that you are designing and your design intent. Just think about an atrium vs a museum. And now think of the atrium in two different climate zones. As a [lighting] designer you make the decision on how do you want the space to be, how the climate is and then try to take advantage of skylight and/or direct sunlight to achieve your design goals.
2. Yes. There is a watchTheSky component next to sky types which let you visualize the sky. There is also an example file that you can check.
3. This one again depends on your model. For your model I would suggest a minimum number of 4 for your final analysis. -ab is only one of the parameters. Check this slides by John Mardaljevic if you want to have a better understanding of radiance parameters and their effect on the results.
I also added the link to "Tutorial on the Use of Daysim Simulations for Sustainable Design" by Christoph Reinhart to teaching materials. I encourage you to at least read chapters 1 and 2 of the tutorial. Check pages 25 and 27 have two examples about selecting the parameters.
Great questions. Keep them coming.
Mostapha…
evel in which each final branch contains a list of one number from each list in all its variations with the other two lists.
12
AB
xy
Becomes eight possible combinations:
1Ax
1Ay
1Bx
1By
2Ax
2Ay
2Bx
2By
Either I could immediately break into 8 branches or branch twice from 2 items to 4 items then from those 4 items to 8 final items. I keep trying grafting with all manner of tree components and *never* obtain a simple dual branching fractal tree structure. I barely even need a tree actually, but I'd prefer each final branch to contain a list I can pull each final value individual value out of rather than dealing with string extraction. This is all to eventually plug all these variations into a parametric mesh model that now uses three sliders, and Python script also to bake them all as OBJ files.
Crucially I also need to obtain the numbers to use as part of my multiply exported OBJ files. I can so far only get a single range to export as a series of OBJ files automatically but not the whole three list array of them.
…
ace when I start running Galapagos/Octopus (below is "room orientation optimization" shared at http://hydrashare.github.io/hydra/viewer?owner=mostaphaRoudsari&fork=hydra_1&id=Room_Orientation_Optimization&slide=0&scale=1&offset=0,0) It may take quite some time to see some results. That's fine for the above simulation. But my real challenge is, when I am going to optimize room dimension with respect to ASE and sDA calculations, either Galapagos or Octopus goes wildly and never come up with a solution. I believe the time-consuming calculation, especially sDA with higher -ab numbers, trigger the lag a lot? Any suggestion/trick to improve it?
Most importantly, based on your experience, for example to optimize window/exterior shades sizes and achieve ASE<10% and sDA>55% (LEED v.4 requirements), Octopus (due to its capacity of multiple objectives) is the only choice? Any other approaches within grasshopper?
Many thank!
Cheney
…
up structural systems in the parametric environment of Grasshopper. Participants will be guided through the basics of analysing and interpreting structural models, to optimisation processes and how to integrate Karamba3d into C# scripts.
This workshop is aimed towards beginner to intermediate users of Karamba however advanced users are also encouraged to apply. It is open to both professional and academic users.
Course Fee:
Professional EUR 750 (+VAT)
Educational EUR 375 (+VAT)
Course Outline
Introduction & Presentation of project examples
Optimization of cross sections of line based and surface based elements
Geometric Optimization
Topological Optimization
Structural Performance Informed Form Finding
Understanding analysis algorithms embedded in Karamba and visualising results
Complex Workflow processes in Rhino3d, Grasshopper3d and Karamba3d
Places are limited to a maximum of 10 participants with limited educational places. A minimum of 4 places are required for the workshop to take place.
The workshop will be cancelled should this quota not be filled by May 31st.
The workshop will be taught in English. Basic Rhino and Grasshopper knowledge is recommended. No knowledge of Karamba is needed.
Participants should bring their own laptops with either Rhino5/Rhino6 and Grasshopper3d installed. A 90 day trial version of Rhino can be downloaded from Rhino3d.
Karamba ½ year licenses for non-commercial use will be provided to all participants.
…
up structural systems in the parametric environment of Grasshopper. Participants will be guided through the basics of analysing and interpreting structural models, to optimisation processes and how to integrate Karamba3d into C# scripts.
This workshop is aimed towards beginner to intermediate users of Karamba however advanced users are also encouraged to apply. It is open to both professional and academic users.
Course Fee:
Professional EUR 750 (+VAT)
Student EUR 375 (+VAT)
Course Outline
Introduction & Presentation of project examples
Optimization of cross sections of line based and surface based elements
Geometric Optimization
Topological Optimization
Structural Performance Informed Form Finding
Understanding analysis algorithms embedded in Karamba and visualising results
Complex Workflow processes in Rhino3d, Grasshopper3d and Karamba3d
Places are limited to a maximum of 10 participants with limited educational places. A minimum of 4 places are required for the workshop to take place.
The workshop will be cancelled should this quota not be filled by October 15th.
The workshop will be taught in English. Basic Rhino and Grasshopper knowledge is recommended. No knowledge of Karamba is needed.
Participants should bring their own laptops with either Rhino5/Rhino6 and Grasshopper3d installed. A 90 day trial version of Rhino can be downloaded from Rhino3d.
Karamba ½ year licenses for non-commercial use will be provided to all participants.
…
ive 'correct' normal.
Non-normalized cross products is effectively weighting face normals by area, and is fast and simple, so we put that one as the default.
In some cases normalizing the cross-products improves the result, but not always.
Another option is to weight by angles, though this is computationally slightly more expensive, so might not be ideal for real-time updates on large meshes.
As an example, here is a mesh with a 90° corner, and uneven meshing on the 2 sides.
The arrows show:
0- Area weighted (non-normalized cross products)
1- Angle weighted
2- Normalized cross-products
Here the angle-weighted normal is the one at 45°, which is intuitively the 'best' one in this case.
These 3 seem to be the most commonly used, but there are many other possible definitions of normals - such as inverse-area weighted, mean curvature, etc...
I think really what would be best would be to put a few of these into Plankton, and include an optional argument in GetNormal for selecting which one you need for a particular application.
Pull requests welcome if you feel inspired to add this!
http://meshlabstuff.blogspot.co.uk/2009/04/on-computation-of-vertex-normals.html
http://steve.hollasch.net/cgindex/geometry/surfnorm.html…