This blog post is a rough approximation of the lecture I gave at the AAG10 conference in Vienna on September 21st 2010. Naturally it will be quite a different experience as the medium is quite…
Added by David Rutten at 3:27pm on September 24, 2010
ocessed once Grasshopper is done with whatever it's doing now.
3) Grasshopper tells the Slider object that the mouse moved and the slider works out the new value as implied by the new cursor position.
4) The slider then expires itself and its dependencies ([VB Step 1] in this case, but there can be any number of dependent objects).
5) When [VB Step 1] is expired by the slider, it will in turn expire its dependencies (VB Step 2), and so on, recursively until all indirect dependencies of the slider have been expired.
6) When the expiration shockwave has subsided, runtime control is returned to the slider object, which tells the parent document that stuff has changed and that a new solution is much sought after.
7) The Document class then iterates over all its objects (they are stored in View order, not from left to right), solving each one in turn. (Assuming the object needs solving, but since in your example ALL objects will be expired by a slider change, I shall assume that here).
8) It's hard to tell which object will get triggered first. You'd have to superimpose them in order to see which one is visually the bottom-most object, but let's assume for purposes of completeness that it's the [VB Step 1] object which is solved first.
9) [VB Step 1] is triggered by the document, which causes it to collect all the input data.
10) The input parameter [x] is asked to collect all its data, which in turn will trigger the Slider to solve itself (it got expired in step 4 remember?). This is not a tricky operation, it merely copies the slider value into the slider data structure and shouts "DONE!".
11) [x] then collects the number, stores it into its own data structure and returns priority to the [VB Step 1] object.
12) [VB Step 1] now has sufficient data to get started, so it will trigger the script inside of it. When the script completes, the component is all ready and it will tell the parent document it can move on to the next object (the iteration loop from step 7).
13) Let us assume that the slider object is next on the list, but since it has already been solved (it was solved because [VB Step 1] needed the value) it can be skipped right away, which leaves us with the last object in the document which is still unsolved.
14) [VB Step 2] will be triggered by the document in very much the same way as [VB Step 1] was triggered in step 9. It will also start by collecting all input data.
15) Since all the input data for [VB Step 2] is either defined locally or provided by an object which has already been solved, this process is now swift and simple.
16) Upon collecting all data and running the user script, the component will surrender priority and the document becomes active again.
17) The document triggers a redraw of the Grasshopper Canvas and the Rhino viewports and then surrenders priority again and so on and so forth all the way up the hierarchy until Grasshopper becomes idle again.
[end boring]
Pretty involved for a small 3-component setup, but there you have it.
To answer somewhat more directly your questions:
- The order in which objects are solved is the same as the order in which they are drawn. This is only the case at present, this behaviour may change in the future.
- Adding a delay will not solve anything, since the execution of all components is serial, not parallel. Adding a delay simply means putting everything on hold for N milliseconds.
- [VB Step 1] MUST be solved prior to [VB Step 2] because otherwise there'd be no data to travel from [GO] to [Activate]. The only tricky part here is that sometimes [VB Step 1] will be solved as part of the process of [VB Step 2], while at other times it may be solved purely on its own merits. This should not make a difference to you as it does not affect the order in which your scripts are called.
--
The Man from Scene 24…
Added by David Rutten at 4:43pm on December 10, 2009
number of divisions on that curve as in the defintion (i.e. by 4). The offset in the def is slightly different and should cull two or three more curves as in the lists that show my aim below.
Basically I want to look into each branch of the groups of points from each closed curve . Marking in a list whether it contains a one or a zero (0= outside 1 = coincidents).
{0;0}0. 21. 22. 23. 2 {0;1} 0. 01. 22. 03. 2 {0;2}0. 01. 02. 03. 0 {0;3}0. 21. 22. 23. 2 {0;4}0. 21. 22. 23. 2 {0;5}0. 21. 22. 23. 2 {0;6}0. 01. 22. 23. 1 {0;7}0. 21. 22. 03. 0 {0;8}0. 21. 22. 23. 2 {0;9}0. 21. 22. 23. 2 {0;10}0. 21. 22. 23. 2 {0;11}0. 21. 22. 23. 2 {0;12}0. 21. 22. 23. 2 {0;13}0. 01. 22. 23. 0 {0;14}0. 21. 22. 23. 2
I want to create a list from these points. That marks each curve that pokes out, in a cull pattern as such:
20022210222202
Using a 1 where there are co-incidents in the curve points and the boundary. A 2 for true (outside points) and a 0 for containment. So I might be able to use the 1 in future developments - however if a true false list is easiest I can live with that.
So could I use F(x) function? - to look for 0 or 1's in each bunch of points and thus list as such for a cull pattern? or will Path mapper help me here? Or can I rely on simply grafting and splitting??
I am usure of the neatest solution and would love to learn. Hope you can direct me.rgrds
J.…
. 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
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A repository of generic or complex examples.
Example 01: Attractor Values
ND_001_AttractorValues.gh
Example 02: Curve Values
ND_002_CurveValues.gh
Example 03: Point Attractor
ND_003_PointAttract
ssibili e facili da usare. Il corso parte dalle basi della programmazione di arduino fino ad arrivare all’interazione tra un oggetto fisico ed un imput informativo. tutor: Gianpiero Picerno Ceraso
Programma: I giorno Introduzione al Phisical Computing, input digitali e analogici, le basi del linguaggio di programmazione, esempi applicativi; led, pulsanti, fotorestistenze, servo motore, sensore di temperatura, di flessione, sensori di movimento, potenziometri.
II giorno Arduino ethernet, uso di un relè per carichi elevati, accelerometro, introduzione a Processing, interazione di Arduino e Processing, Introduzione a Grassoppher e Firefly e interazione con Arduino.
orario corso: 10:00 – 13:00 e 14:00 – 17:00 (pausa pranzo 13:00 – 14:00) costo: 150€ + IVA deadline: 13 marzo numero minimo di partecipanti: 3
Per iscrizioni scrivi a info@medaarch.com specificando nome, cognome, mail, recapito telefonico e il nome del corso al quali sei interessato. In seguito all’invio del modulo di pre-iscrizione, i partecipanti riceveranno una mail contenente tutte le specifiche di pagamento.
Per seguire il cluster su Arduino è necessario installare il software Arduino 1.0.5 al seguente linkhttp://arduino.cc/en/Main/Software#.Ux3hQj95MYE facendo attenzione a scaricare quello relativo al proprio sistema operativo, Windows 32 o 64 e Mac OS.
Software necessari solo per una parte del corso: Processing 2.1.1 https://processing.org/download/?processing
Rhino 5 http://www.rhino3d.com/it/download Grasshopper for Rhino5http://www.grasshopper3d.com/page/download-1Firefly http://fireflyexperiments.com/
Il cluster rientra in un fitto calendario di attività formative organizzate dalla Medaarch per lanno 2013-2014.…
Series“, è il corso più seguito in Italia sulla modellazione parametrica, giunto al nono anno consecutivo di attivazione. Plug it fornirà ai partecipanti un’effettiva padronanza delle più avanzate tecniche di modellazione digitale, approfondendo le metodologie della modellazione algoritmica e parametrica nel campo dell’architettura e del design del prodotto. Il corso è rivolto a studenti e professionisti dei settori della progettazione architettonica, design, moda e gioielleria, con esperienza minima nel disegno CAD bidimensionale (acquisita su qualsiasi piattaforma software) e si articolerà in lezioni teoriche frontali ed esercitazioni guidate.
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FORM FINDING STRATEGIES | Livello Intermedio | Analisi ambientale ed ottimizzazione della forma
Form Finding Strategies è il secondo step del percorso formativo in tre fasi “AAD Workshop Series“. Il workshop intende esplorare le possibilità di generazione di forme efficienti in relazione ad influenze esterne ed alle caratteristiche intrinseche della materia stessa. Analisi ambientale (input solari, termici ed acustici) ed analisi/ottimizzazione strutturale FEM saranno le principali metodologie utilizzate per raggiungere gli obiettivi di ricerca della forma. Saranno introdotti numerosi plug-ins tra cui: Weaverbird, Kangaroo, Geco/Ecotect, Ladybug, Millipede. Il corso si rivolge a studenti e professionisti con conoscenza base di Rhino e Grasshopper.
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PERSPECTIVES | Livello Avanzato | Python coding e modellazione algoritmica avanzata
Il nuovo corso Perspectives proposto per la prima volta nel 2019 (ed ultimo step del percorso formativo in tre fasi “AAD Workshop Series) introdurrà gli studenti alla programmazione Python ed alla sua integrazione con Grasshopper. Verranno inoltre esplorate tecniche avanzate di generazione formale basate su iterazioni. Tra i principali plugins utilizzati: GhPython, Anemone, Hoopsnake, Plankton, MeshMachine, Pufferfish. Pensato come workshop innovativo sulle prospettive e sfide future del design computazionale, è rivolto a studenti e professionisti con esperienza in modellazione algoritmica con Grasshopper.
INFO ED ISCRIZIONI
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use I don't agree with the practice of using site EUI as a metric to evaluate the thermodynamic performance, environmental impact, or monetary value of a building. I disagree with this practice for the same reason that there are no "totalThermalLoad" and "thermalLoadBalance" for simulations run with full HVAC. I can summarize these reasons in the following way:
When we run a simulation with ideal air loads, the heating/cooling values we get are THERMAL ENERGY that is directly added to or removed from the zone. In this way, we can draw a rough parallel between these two types of energy since they are are generally of a similar type and quality. As such, I am ok with adding them together to get total thermal load or subtracting them to get a sense of thermal load balance.
However, when we run a simulation will full HVAC, the heating/cooling values that we get are usually HEATING FUEL ENERGY and ELECTRICITY respectively. Fuel energy and electricity are fundamentally two different types and qualities of energy. To cite the second law of thermodynamics, the exergy (or the capacity to do work) of electricity is much greater than that of fuel. This is evident in the fact that, to produce a given unit of electricity, I often have to burn at least 3 units of fuel energy (though this can be much more for inefficient plants). With each step in a power plant - making steam, turning a turbine, turning a generator - there are significant energy losses. This difference in exergy is also evident in the fact that there are so many more things that I can do directly with a unit of electricity than I can do with the same unit of fuel energy. I can use electricity to directly refrigerate, produce light energy or power a motor just as easily as I can use to to cook, produce hot water, or heat a space. While I can cook, make hot water, or heat a space directly with fuel energy, refrigeration and lighting are much more difficult. For this reason, I do not feel comfortable adding electricity and fuel together either in the totalThermalLoad output or in a site EUI metric.
Still, the use of site EUI has become so ingrained in the industry that I have to acknowledge it and at least show users how it's calculated. In my view, it's an ad-hoc metric that was invented to deal with previously limited amount of information on energy sources.
Instead of using site EUI, I would recommend using the following metrics depending on what you are trying to evaluate:
Utility Cost / Square Meter - to measure the monetary value of a building to an owner or user
Kg CO2 / Square Meter - to measure the environmental and climatic impact of a building
Emergy / Square Meter - to measure the overall thermodynamic performance of a building
The first two are actually fairly easy to calculate these days just by researching your site's utility rates or grid energy mixture and multiplying the building electricity or fuel by their respective rates. I will add in some capabilities to Honeybee soon to make it even easier for you to get these values from your EPW file and databases of utility rates/grid mixture. Emergy is much harder to calculate as you have to trace all your energy sources all of the way back to the sun but there are a number of experts at work to make this calculation possible (probably in the next few years, we may have much easier ways to calculate it).
Hope this helps explain the current setup.
-Chris…
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…