or GH with: 1. Animation Timeline 2. Rendering 3. API
Summary:
Animation Timeline: Smooth animation system that plays at the real-world speed; so you know the robot will run just right when you upload the code.
Rendering: Extensive options and outputs; so you can generate amazing videos.
API: Access our functions through Python and C# scripting; so you can manage parameters and actions for complex processes for each target.
More info:
Animation Timeline:
Build an animation from a list of Planes, it's that easy! Get these from points, curves or surfaces. Download the example files with the trial and test it yourself.
The unique Timeline component displays all the important robot warnings and the digital Input/Ouput:
RED – clash detection BLUE - singularities YELLOW – over rotation ORANGE – out of reach Digital Inut/Output: red=off, green=on
Rendering:
IO smoothly interpolates between all the Planes you set. This means you can generate keyframes for positions between Planes too e.g. you have two planes defining a tool path, IO can generate 2000 keyframes. Smooooth!
Rendered in full colour as standard, not GH red :-)
LiveBaking - let's you use Rhino render settings in real-time (can be a bit slow!)
Slider animation - use the native 'Animate' option to export hi-res images and create videos easily. Just set the number of frames you need (hint: divide total time in seconds by the frames-per-second rate)
Bake unlimited meshes as keyframes for export to render-pipelines in 3DS etc.
API
Accessing the IO functions through Python and C# let's you build more powerful definitions. You can assign data to every position the robot reaches, allowing you to control speed, acceleration, wait-times, actions and more. Examples comparing C# with Python are included in the examples files.
You can also use teh API build your own plugins that use the IO timeline to do all the hard work like IK and creating valid code, while you enjoy developing your new process...
Check out the website for more features and videos of the example definitions: www.robots.io
Download the PDF guide: 150314_IO_Primer_v1.pdf.
See www.robots.io for more info and pricing.
Developed by RoboFold Ltd. Used by leading academics, researchers and professionals.
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Added by Gregory Epps at 10:15am on November 7, 2014
3. receiver gets data from sender via input (0) < the data here may be changed in the meantime, for instance if its a double then I would like to add 1 to it.
4. receiver sends data to sender's input(2)
5. go to 1.
VS 2013 studio project folder
SENDER
Public Class loopStart Inherits GH_Component
Dim cnt As Integer
Friend Property counter() As Integer Get Return cnt End Get Set(value As Integer) cnt = value End Set End Property
Dim iData As New GH_Structure(Of IGH_Goo)
Friend Property startData() As GH_Structure(Of IGH_Goo) Get Return iData End Get Set(value As GH_Structure(Of IGH_Goo)) iData = value End Set End Property
Public Sub New() MyBase.New("loopStart", "loopStart", "Start the loop with this one.", "Extra", "Extra") End Sub
Public Overrides ReadOnly Property ComponentGuid() As System.Guid Get Return New Guid("bdf1b60d-6757-422b-9d2d-08257996a88c") End Get End Property
Protected Overrides Sub RegisterInputParams(ByVal pManager As Grasshopper.Kernel.GH_Component.GH_InputParamManager) pManager.AddGenericParameter("Data", "dIn", "Data to loop", GH_ParamAccess.tree) pManager.AddIntegerParameter("Steps", "S", "Number of loops", GH_ParamAccess.item) pManager.AddGenericParameter("<X>", "<X>", "Please leave this one alone, don't input anything.", GH_ParamAccess.tree) pManager.Param(2).Optional = True End Sub
Protected Overrides Sub RegisterOutputParams(ByVal pManager As Grasshopper.Kernel.GH_Component.GH_OutputParamManager) pManager.AddGenericParameter("Data", "dOut", "Data to loop", GH_ParamAccess.tree) End Sub
Public Overrides Sub CreateAttributes() m_attributes = New loopStartAttributes(Me) End Sub
Protected Overrides Sub SolveInstance(ByVal DA As Grasshopper.Kernel.IGH_DataAccess)
Dim numLoop As Integer DA.GetData(1, numLoop)
Dim loopDt As New Grasshopper.Kernel.Data.GH_Structure(Of IGH_Goo)
If cnt = 0 Then Me.startData.Clear() DA.GetDataTree(0, Me.startData) loopDt = startData.Duplicate DA.SetDataTree(0, loopDt) End If
If cnt < numLoop - 1 And cnt > 0 Then DA.GetDataTree(2, loopDt) DA.SetDataTree(0, loopDt) Me.ExpireSolution(True) Else DA.GetDataTree(2, loopDt) DA.SetDataTree(0, loopDt) End If
cnt += 1
End Sub
End Class
RECEIVER
Public Class loopEnd Inherits GH_Component
Dim aData As New GH_Structure(Of IGH_Goo)
Friend Property anyData() As GH_Structure(Of IGH_Goo) Get Return aData End Get Set(value As GH_Structure(Of IGH_Goo)) aData = value End Set End Property
Public Sub New() MyBase.New("loopEnd", "loopEnd", "End the loop with this one.", "Extra", "Extra") End Sub
Public Overrides ReadOnly Property ComponentGuid() As System.Guid Get Return New Guid("3ffa3b66-8160-4ab3-87c9-356b2c17aadd") End Get End Property
Protected Overrides Sub RegisterInputParams(ByVal pManager As Grasshopper.Kernel.GH_Component.GH_InputParamManager) pManager.AddGenericParameter("Data", "dIn", "Data to loop", GH_ParamAccess.tree) End Sub
Protected Overrides Sub RegisterOutputParams(ByVal pManager As Grasshopper.Kernel.GH_Component.GH_OutputParamManager) pManager.AddGenericParameter("Data", "dOut", "Data after the loop", GH_ParamAccess.tree) End Sub
Protected Overrides Sub SolveInstance(ByVal DA As Grasshopper.Kernel.IGH_DataAccess) Me.aData.Clear() DA.GetDataTree(0, Me.aData) runner()
DA.SetDataTree(0, Me.aData) End Sub
Sub runner()
Dim doc As GH_document = Grasshopper.Instances.ActiveCanvas.Document Dim docl As list(Of iGH_DocumentObject) = (doc.Objects)
For i As Integer = 0 To docl.count - 1 Step 1 Dim comp As Object = docl(i) If comp.NickName = "loopStart" Then Dim compp As IGH_Param = comp.Params.input(2) compp.VolatileData.Clear() compp.AddVolatileDataTree(anyData) Exit For End If Next End Sub
End Class
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option, after downloading check if .ghuser files are blocked (right click -> "Properties" and select "Unblock"). Then paste them in File->Special Folders->User Object Folder. You can download the example files from here. They act in similar way, Ladybug Photovoltaics components do: we pick a surface, and get an answer to a question: "How much thermal energy, for a certain number of persons can my roof, building facade... generate if I would populate them with Solar Water Heating collectors"? This information can then be used to cover domestic hot water, space heating or space cooling loads:
Components enable setting specific details of the system, or using simplified ones. They cover analysis of domestic hot water load, final performance of the SWH system, its embodied energy, energy value, consumption, emissions... And finding optimal system and storage size. By Dr. Chengchu Yan and Djordje Spasic, with invaluable support of Dr. Willian Beckman, Dr. Jason M. Keith, Jeff Maguire, Nicolas DiOrio, Niraj Palsule, Sargon George Ishaya and Craig Christensen. Hope you will enjoy using the components! References: 1) Calculation of delivered energy: Solar Engineering of Thermal Processes, John Wiley and Sons, J. Duffie, W. Beckman, 4th ed., 2013. Technical Manual for the SAM Solar Water Heating Model, NREL, N. DiOrio, C. Christensen, J. Burch, A. Dobos, 2014. A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015
2) Domestic hot water load: Modeling patterns of hot water use in households, Ernest Orlando Lawrence Berkeley National Laboratory; Lutz, Liu, McMahon, Dunham, Shown, McGrue; Nov 1996. ASHRAE 2003 Applications Handbook (SI), Chapter 49, Service water heating
3) Mains water temperature Residential alternative calculation method reference manual, California energy commission, June 2013. Development of an Energy Savings Benchmark for All Residential End-Uses, NREL, August 2004. Solar water heating project analysis chapter, Minister of Natural Resources Canada, 2004.
4) Pipe diameters and pump power: Planning & Installing Solar Thermal Systems, Earthscan, 2nd edition
5) Sun postion and POA irradiance, the same as for Ladybug Photovoltaics (Michalsky (1988), diffuse irradiance by Perez (1990), ground reflected irradiance by Liu, Jordan (1963))
6) Optimal system and storage tank size: A simplified method for optimal design of solar water heating systems based on life-cycle energy analysis, Renewable Energy journal, Yan, Wang, Ma, Shi, Vol 74, Feb 2015.…
via MIDI controllers.
my idea is to link PureData to GH via UDP. why pure data? cause' i can relate data like GH to generate numeric relations (and link it to audio generation)
so far i got PD and Processing to talk, but i can't get to grasshopper.
i use this definitions to make pd and processing to talk http://ubaa.net/shared/processing/udp/ and this GHX to get the data to GH http://www.grasshopper3d.com/forum/attachment/download?id=2985220%3...
i got this data from this post but the GH definition doesn't work for me. i have tried LAN definitions and "the engine" as well but they both freeze, even if i send data thru processing or PD.
i have a lot of questions at this time
1.- why processing tells me that i am getting the data from diferent ports, while i'm using 6000?
2.- why in the UDP definition i get no data out, even if it should say something like "waiting fordata/port/etc.." that's defined in the C# capsule
3.- is there a direct way to get midi data (key and CC) to GH
i also tried to use firefly to get the data via COM port. i know you can do this trick in processing but i just don't know how.
well. if anyone could help me i would share the results here (since it's a magister, results shoud be very interesting)
UDP has allways been a unsolved issue on other posts. maybe we could work it out ;)
Thanks…
Added by jota aldunce at 8:43am on September 28, 2010
arq, que se celebrará entre el 28 de Enero y el 1 de Febrero de 2013 en el Colegio de Arquitectos de Granada.
El taller está destinado a arquitectos, artistas y diseñadores, tanto como profesionales, como estudiantes de grado y posgrado, que, sin necesidad de haber tenido ningún contacto previo con entornos de programación o herramientas informáticas de dibujo paramétrico o generativo, están interesados en probar y experimentar con las opciones que nos pueden ofrecer a los diseñadores.
El taller está dividido en tres bloques:
Curso intensivo: del 28 de Enero al 30 de Febrero, en horario de mañana, de 10 a 14. Taller de proyectos: del 28 de Enero al 30 de Febrero, por la tarde, de 16 a 20; y el 31 de Febrero, durante todo el día.
Presentaciones: viernes 1 de Febrero, mañana y tarde.
Utilizaremos Grasshopper, el editor algorítmico asociado al software de modelado tridimensional y dibujo Rhinoceros, por su facilidad de aprendizaje, al tratarse de un entorno gráfico, facilidad de adquisición, al ser gratuito y haber disponible una versión de prueba de Rhinoceros también gratuita, y amplia difusión en los últimos años. Y lo emplearemos tanto como modelador, como conector entre otros softwares y varias disciplinas. Por este motivo, también utilizaremos algunos de sus plug-ins, como Geco, para análisis ambiental, Elk, para enlazarlo con OpenStreetMap o Kangaroo, para simulación de sistemas físicos.
Lo único que necesitas es un ordenador portátil (si no pudieras conseguir), hacer el ingreso con el importe correspondiente y mandarnos tus datos y el recibo bancario del ingreso a smartlabgranada@gmail.com. Puedes ver los detalles en el apartado de Inscripción. El resto del material, tanto software como hardware, lo ponemos nosotros.
Nuestro acercamiento a estas herramientas es entusiasta acerca del potencial creativo que pueden ofrecer a diseñadores y artistas, pero también crítico y especulativo. Nos alejamos tanto de una posición puramente formalista, como del estricto funcionalismo, a los que desde los últimos años frecuentemente se ha asociado a esta disciplina.…
Added by Miguel Vidal at 8:42am on January 19, 2013
the results myself and I am open to changing the name/description of the input based on what you have found here. modulateFlowOrTemp is not the best name for what seems to be going on and we should change it to reflect more what is happening in the IDF.
Here is how I am understanding the results of the different cases:
1) When the variable flow option is selected (and the outdoor air set to "None"), the heating and cooling of the space seems to happen only through re-circulation of the indoor air. My comparison to a VAV system was not appropriate and perhaps it would be better to compare it to a window air conditioner or a warm air furnace, which, as far as I understand, only re-circulate indoor air and do not bring in outside air.
2) My reasoning for the name modulateFlowOrTemp came mostly from my realization that the supply air temperature remained within the defined limits when the variable flow option is selected (and the outdoor air set to "None"). When the outdoor air was set to Maximum or Sum, the supply air temperature went way out of the temperature limits that I initially set. I realize now that the flows are varying in both cases and the name of the input really must change.
3) I think that the reason why we don't see any effect from the air side economizer is because the heating/cooling energy results that you get from an ideal air system are just the sum of the sensible and the latent heat added/removed from the zone by the system. This value of heat added or removed from the zone does not change whether the added/removed heat comes from outside air or from a cooling/heating coil. Since there is no cooling coil or boiler or chiller in an ideal air system, there is no way to request an output of the energy added/removed by such a coil or chiller as opposed to that removed/added by outside air. In other words, the air side economizer option on the ideal air system is practically useless because it does not help us differentiate the cooling that comes from the outside air vs. that which comes from a coil. All that it does is change the outdoor air fraction while keeping the reported cooling/heating values the same.
Please let me know if you think that this explanation makes sense, Burin and, in light of all this, I am very interested in your suggestions.
From my own perspective, I am now convinced that the default should definitely have the outside air requirements set to "None" since, otherwise, we cannot distinguish cooling/heating that happens from addition of outside air and that which must be supplied by a coil. At least when we get rid of the outside air requirement, we can be sure that the ideal air system values are only showing heating/cooling from a coil or HVAC system.
I have decided to remove the airsideEconomizer input since it seems to give misleading expectations. I am going to recommend here on out that, if you want to estimate the effect of increasing outside air on cooling, you should use the "Set EP Airflow" component, use fan-driven natural ventilation, and you should connect a custom CSV schedule of airflow. You will have to create such a schedule with native GH components using the outside air temperature, your zone setpoints, and the times that you are cooling in your initial run of E+. Either you do this or you set up a full-blown system with OpenStudio.
I have also decided to get rid of the heatRecovery input since it seems like this will also produce misleading expectations by the same logic.
Lastly, I am going to change the name of the modulateFlowOrTemp_ input to outdoorAirReq_. The default will be to have no indoor air requirement as stated above but you can input either "maximum" or "sum" to have the IDF run accordingly.
Let me know if this sounds good or if you have suggestions. Updated GH file attached. The github has the new Ideal Air Loads component. Make sure that you have sync correctly and restart GH after updating your components.
-Chris…
e current data should be turned to be original data, is that right?there are 3 cases.
what do this components effect the performance after if i turn the component to be flatten and graft and to connect to other component?
{, is that0}
{0;0}
{0;0;0}
{0;0;0;0}
{0;0;0;0;0}
{0;0;0;0;0;0}…
ly this is a Rhino.Python problem and not a Grasshopper issue, but it could apply to both!
I was trying to take a simple example of moving a ball around and see how it could be animated through Rhino.Python. The code works great in wire frame with now memory issues at all. However, when I switch the view to Shaded or Rendered, things go south pretty quickly. The RAM usage of Rhino which was steady around 350mb (ish) now grows every frame after a minute or so, it is in the GB's and never drops even after the script has stopped.What gives? Clearly this must be possible because Bongo does something similar when it does animations. Check out my code below and I would love to hear your thoughts.
import time
import rhinoscriptsyntax as rs
import Rhino
height = 100
width = 100
x = 0
y = 0
xspeed = .1
yspeed = .3
start_time = time.time()
end_time = 60
run_time = 0
sphere = rs.AddSphere((x,y,0), 5)
while run_time < end_time:
x = x + xspeed
y = y + yspeed
if x > width/2 or x < -width/2:
xspeed = xspeed * -1
if y > height/2 or y < -height/2:
yspeed = yspeed * -1
rs.MoveObject(sphere, (xspeed, yspeed, 0))
Rhino.RhinoApp.Wait()
run_time = time.time() - start_time…
peuvent se diviser une surface avec ne importe quel motif imaginable. 3. Ici, je fournir un moyen de le faire via Lunchbox ... cela fonctionne mais il est fixe et donc nous avons besoin de jouer avec des arbres de données afin de créer le motif approprié par cas. 4. L'autre composante est un joint C # qui fait beaucoup de choses autres que de diviser ne importe quelle collection de points avec de nombreux modèles (voir le modèle ANDRE que je ai fait pour vous). 5. Vous devez décomposer une polysurface en morceaux afin de travailler sur les subdivisions. 6. Je donne une autre définition ainsi que pourrait agir comme un tutoriel sur la façon de traiter des ensembles de points via des composants de GH standards et des méthodes classiques.
Avertissez si tous ceux-ci apparaissent floue pour vous: Si oui, je pourrais écrire une définition utilisant des composants de GH classiques - mais vous perdrez les variations de motifs de division.
mieux, Peter
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ing the maps to the broader community.
At the moment, there are just a few known issues left that I have to fix for complex geometric cases but they should run smoothly for most energy models that you generate with Honeybee. Within the next month, I will be clearing up these last issues and, by the end of the month, there will be an updated youtube tutorial playlist on the comfort tools and how to use them.
In the meantime, there's an updated example file (http://hydrashare.github.io/hydra/viewer?owner=chriswmackey&fork=hydra_2&id=Indoor_Microclimate_Map) and I wanted to get you all excited with some images and animations coming out of the design part of my thesis. I also wanted to post some documentation of all of the previous research that has made these climate maps possible and give out some much deserved thanks. To begin, this image gives you a sense of how the thermal maps are made by integrating several streams of data for EnergyPlus:
(https://drive.google.com/file/d/0Bz2PwDvkjovJaTMtWDRHMExvLUk/view?usp=sharing)
To get you excited, this youtube playlist has a whole bunch of time-lapse thermal animations that a lot of you should enjoy:
https://www.youtube.com/playlist?list=PLruLh1AdY-Sj3ehUTSfKa1IHPSiuJU52A
To give a brief summary of what you are looking at in the playlist, there are two proposed designs for completely passive co-habitation spaces in New York and Los Angeles.
These diagrams explain the Los Angeles design:
(https://drive.google.com/file/d/0Bz2PwDvkjovJM0JkM0tLZ1kxUmc/view?usp=sharing)
And this video gives you and idea of how it thermally performs:
These diagrams explain the New York design:
(https://drive.google.com/file/d/0Bz2PwDvkjovJS1BZVVZiTWF4MXM/view?usp=sharing)
And this video shows you the thermal performance:
Now to credit all of the awesome people that have made the creation of these thermal maps possible:
1) As any HB user knows, the open source engines and libraries under the hood of HB are EnergyPlus and OpenStudio and the incredible thermal richness of these maps would not have been possible without these DoE teams creating such a robust modeler so a big credit is definitely due to them.
2) Many of the initial ideas for these thermal maps come from an MIT Masters thesis that was completed a few years ago by Amanda Webb called "cMap". Even though these cMaps were only taking into account surface temperature from E+, it was the viewing of her radiant temperature maps that initially touched-off the series of events that led to my thesis so a great credit is due to her. You can find her thesis here (http://dspace.mit.edu/handle/1721.1/72870).
3) Since the thesis of A. Webb, there were two key developments that made the high resolution of the current maps believable as a good approximation of the actual thermal environment of a building. The first is a PhD thesis by Alejandra Menchaca (also conducted here at MIT) that developed a computationally fast way of estimating sub-zone air temperature stratification. The method, which works simply by weighing the heat gain in a room against the incoming airflow was validated by many CFD simulations over the course of Alejandra's thesis. You can find here final thesis document here (http://dspace.mit.edu/handle/1721.1/74907).
4) The other main development since the A. Webb thesis that made the radiant map much more accurate is a fast means of estimating the radiant temperature increase felt by an occupant sitting in the sun. This method was developed by some awesome scientists at the UC Berkeley Center for the Built Environment (CBE) Including Tyler Hoyt, who has been particularly helpful to me by supporting the CBE's Github page. The original paper on this fast means of estimating the solar temperature delta can be found here (http://escholarship.org/uc/item/89m1h2dg) although they should have an official publication in a journal soon.
5) The ASHRAE comfort models under the hood of LB+HB all are derived from the javascript of the CBE comfort tool (http://smap.cbe.berkeley.edu/comforttool). A huge chunk of credit definitely goes to this group and I encourage any other researchers who are getting deep into comfort to check the code resources on their github page (https://github.com/CenterForTheBuiltEnvironment/comfort_tool).
6) And, last but not least, a huge share of credit is due to Mostapha and all members of the LB+HB community. It is because of resources and help that Mostapha initially gave me that I learned how to code in the first place and the knowledge of a community that would use the things that I developed was, by fa,r the biggest motivation throughout this thesis and all of my LB efforts.
Thank you all and stay awesome,
-Chris…