s is like flattening your data PARTIALLY - chopping an index off the end of the branch paths without obliterating the tree entirely. When working with one "set" of input data, a flatten works to get these lists to match up - but when working with multiple sets, we need to be careful to preserve the original branch indices that keep all four of your original regions separate. As a rule, whenever you're feeding two data trees into any component, they should have the same number of branches. (or one should have branches and the other should be a flat list, in other cases).
The rule of thumb I tend to teach is this:
In 90% of cases...
For lists, all your inputs should either have 1 item or N items. That is to say, if you're feeding 4 items into one input and 9 items into another, something is probably wrong.
For trees, all your inputs should have either 1 branch or M branches. That is to say, if you're feeding a tree w/ branches {0;0} to {0;3} into one input, and a tree w branches {0;0;0} to {0;3;8} into the other input, something is probably wrong.
Grasshopper essentially matches up branches first, then lists second. By "matching" I mean it processes them together. Simple example of the Line component - it will match the first branch of points in the A input to the first branch of points in the B input, creating lines between those points, then match the second branches, the third branches, etc. THEN, it applies the same logic to the level of the list (with a pair of matched branches {0;2}, match all the items in those branches to each other - first item in one branch to the first item in the other branch, etc.)
This is a tricky concept but it seems like you're already well on your way to understanding it from your definition - "PShift" is a critical tool in your path management arsenal. I hope this (overly long) response helps clear things up for you!
…
he TOF and TSRF indices. They show, how "distant" is your _PV_SWHsurface from the optimal _PV_SWHsurface surface in terms of tilt and azimuth angles.However, in your case we are not interested in TOF and TSRF indices. We would just like to know what are the _PV_SWHsurface optimal tilt and azimuth angles, regardless of the supplied _PV_SWHsurface.
So the circular surface supplied to the "TOF" component's _PV_SWHsurface input is irrelevant. It can be of any area, and any tilt/azimuth angle.The PV_SWHsurfacesArea output of the "PV SWH system size" component depends on a couple of factors:moduleActiveAreaPercent_ (leave it at 90%).
moduleEfficiency_,
systemSize_.Calculation of systemSize_ depends on your electricity demand, cost of the PV system, type of the object, country, local regulations etc. This is something that an engineer needs to determine.For example, in USA for a residential house in the Sunbelt, depending on finances, a household would try to cover 100% of its annual electricity needs with their PV system. Which means that the systemSize_ you chose needs to cover the annual electricity consumption. You can perform EnergyPlus simulation or use any other way to get the annual electricity consumption.
Ladybug "Photovoltaics Performance" component can calculate the optimal systemSize_ by given the annual electricity consumption.However the component is made to address fixed tilt and azimuth PV systems only.An approximate way to overcome this is to calculate the optimal systemSize_ for fixed tilt and azimuth PV system, and then multiply it with the "difference in %s" panel at the very right of the fixed_vs_tracker_PV2.gh file. Again, this is not what Ladybug "Photovoltaics Performance" component is made to do, but it will probably get you in a ball park.
Inputted 32 degrees for north_ direction is actually 328 degrees.This is due to Ladybug Photovoltaics being based on NREL model which uses clockwise angles convention. This convention is also most commonly used in solar radiation analysis.
Dubai weather data files are uploaded in here.
…
ARRAY with certain spatial order or mechanism under consideration of ecological design. The evaluation and definition of “ARRAY” are open to applicants’ imaginations. While the term “ecological” is subjected to many definitions: social, ecological, sustainable, its re-evaluations are open to students’ interpretations. Entrants are free to choose or make site, real or virtual.
ELIGIBILITY
Open to international students in the fields of architecture and design related disciplines from an accredited four-year or five-year architecture program. Graduates with certificate in 2011 are accepted. Teamed collaboration consisting of no more than 3 students in the above mentioned fields is permitted. Works submitted must be of applicants’ original works. Works done through school studios are accepted, but limited to 2011 term.
ENTRY FEE
Free
DEADLINES
Online Registration deadline: Oct 30th, 2011, 17:00 Taipei Time
(Upon completing registration, applicant will receive a registration number via email.)
Submission deadline: email sent by Nov 3rd, 2011, 17:00 Taipei Time
SUBMISSION REQUIREMENTS
This is a digital competition and no hardcopies are necessary. Entrants must submit their proposal via email no later than Nov 3rd, 2011 17:00 (Taipei Time) to the following email address:
hojenhwang@mail.ntut.edu.tw
The project submission must contain the following files:
1. Two A1 boards in portrait format (594mm x 841mm), with identification number at the upper right corner. Names and other identifying information are not allowed on front side of the boards. The resolution of the boards must be 300dpi, RGB mode and saved as JPG files.. The files must be named after the registration number followed by the board number. For example: 03956-board1.jpg and 03956-board2.jpg.
2. A DOC file containing the project discription (600 words max). This file must be named after the registration number followed by the word "discription". For example: 03956-discription.doc.
3. A scan of statement form. This file must be named after the registration number followed by the word "statement_scan". For example: 03956-statement_scan.jpg.
4. All the files must be placed in a ZIP folder named after your registration number. For example: 03956.zip. Size of the ZIP folder is suggested to be less than 15mb, while size more than 25mb will not be accepted
AWARDS
(1) Gold Prize winner will be awarded TWD 60,000 and a trophy.
(2) Silver Prize winner will be awarded TWD 30,000 and a trophy
(3) Bronze Prize winner will be awarded TWD 15,000 and a trophy
(4) Honorable Mention winners will be awarded TWD 5,000 and a merit certificate
Winners will be announced and notified by mid of Nov, 2011.
JURY
Two stages of open jury. Details to be announced
PUBLIC EXHIBITION
Nov 13, 2011~ Nov 18, 2011 at NTUT, Taipei
…
Added by Yu-Min Su at 2:03am on September 23, 2011
ve Intermediate Insight of Computational Design Strategies While Exploring Rangoli Art form in 2 Dimension and 3Dimesion in which Participants will not only be trained to Digitally Design using Parametric software's but they will also be trained to Fabricate them in reality.
This Course will be explored in manner where Participants will understand inter-dependency of Rhinoceros3D & Grasshoper3D through a unique Hybrid Teaching Method While Exploring Rangoli Geometry .
The course will also take participants through Topics such as - Computational Thinking, - Computational / Parametric Design, - Computational Rangoli Exploration, - Digital Fabrication, - 3D Visualization ( Rhino3D 6), - Making Info-graphics & Design Diagrams ( Rhino3d 6 ).
Participants will also be doing a Project at the last Leg of Workshop in which they will implement the skill they gained in first Few Weeks.
{ Tutor } Nitant Pixelkar (Computational Artist / Designer, Mumbai)
Nitant Hirlekar A.k.a. Pixelkar, is a Computational Artist. He graduated from Rachana Sansad school of Interior Design 2011, Mumbai. In Academics He Bagged Two Gold and One Silver Medal on National Level.
In his post academic days, he came across the Emerging Computational Techniques in Design industry in which Algorithm serves as a main Functional part. He uses Algorithms to Deconstruct the Captured images in Pixelated form using the Grid of the Desired Indian Art Forms.
He Heads Collective Group Named "Mutation Lab” which is a multidisciplinary Design & Art Cell. Where they Explore Computational Approach while Designing Various Scales Spatial Installation, Digital Fabrication, Interactive Installations and Computational Consultancy for Various Architects.
He has exhibited his first artwork in Kalaghoda Arts Festival for in 2014 And further in 2016 and 2017.In 2015 he exhibited in Dharavi Biennale” organized by Wellcome Trust,London & Sneha Organisation, Mumbai Which was internationally acclaimed. In 2016 he got Featured on a TV show - The Creative Indian's as an Absolut Creative Indian of the Week.
Academically he is been involved in Many Computational Design Workshops / Elective Studios for School of Interior Design (Rachna Sansad), LS Raheja College of Architecture & Rat-Lab (Delhi).
{ Participants } The Course is aimed at Architecture, Interior Design, Product Design,Furniture Design & Fashion Design Students and Professionals. However we would be thrilled to have any Interdisciplinary Artist / Creator/ Maker to join the Course as well.
{ Level }
Intermediate
{ Timing } Monday To Friday - 6:00 PM to 9:00 PM (15 Hours/ Week = 5 Week X 15 Hours = 75 Hours )
{ Dates } Registration Ends - 24th April 2020 **Subejct to Availablity
{ Workshop Dates } 4th May 2020 To 5th June 2020
{ Venue } Lower Parel,Mumbai ( Details To Be Announced )
{ Schedule }
{Registration Form}…
; GH, this one came out and rhinoceros is disappear...like this
it said " Rhinoceros5's working is stopped. because some problems occured so Rhinoceros5 can't work correctly no longer " then I have no choice but terminate Rhinoceros.
There are some discussion about RhinoIronPython installing numpy though, no one has same problem like me. so Please somebody tell me!!
and one more question...just in case, I tried to install numpy into ironPython2.7
C:\Program Files (x86)\IronPython 2.7>ipy "C:\Program Files (x86)\IronPython 2.7\ironpkg-1.0.0..py" --installBootstrapping: c:\users\owner\appdata\local\temp\tmp2nand1\ironpkg-1.0.0-1.egg 118 KB [.................................................................]
C:\Program Files (x86)\IronPython 2.7>ironpkg -hUsage: ironpkg-script.py [options] [name] [version]
.
.
.
C:\Program Files (x86)\IronPython 2.7>ironpkg scipyWrote configuration file: C:\Users\owner\.ironpkg=============================================================================Traceback (most recent call last): File "C:\Program Files (x86)\IronPython 2.7\ironpkg-script.py", line 10, in <module> File "C:\Program Files (x86)\IronPython 2.7\lib\site-packages\enstaller\main.py", line 364, in main File "C:\Program Files (x86)\IronPython 2.7\lib\site-packages\enstaller\indexed_repo\chain.py", line 27, in __init__ File "C:\Program Files (x86)\IronPython 2.7\lib\site-packages\enstaller\indexed_repo\chain.py", line 67, in add_repo File "C:\Program Files (x86)\IronPython 2.7\lib\site-packages\enstaller\utils.py", line 92, in write_data_from_url File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 435, in open File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 407, in _call_chain File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 654, in http_error_302 File "C:\Program Files (x86)\IronPython 2.7\Lib\httplib.py", line 1261, in __init__ File "C:\Program Files (x86)\IronPython 2.7\lib\site-packages\enstaller\utils.py", line 73, in open_url File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 154, in urlopen File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 547, in http_response File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 467, in error File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 429, in open File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 446, in _open File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 407, in _call_chain File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 1240, in https_open File "C:\Program Files (x86)\IronPython 2.7\Lib\urllib2.py", line 1167, in do_openAttributeError: 'module' object has no attribute '_create_default_https_context'
C:\Program Files (x86)\IronPython 2.7>
how can I deal with this error?…
lly it should not make much of a difference - random number generation is not affected, mutation also is not. crossover is a bit more tricky, I use Simulated Binary Crossover (SBX-20) which was introduced already in 1194:
Deb K., Agrawal R. B.: Simulated Binary Crossover for Continuous Search Space, inIITK/ME/SMD-94027, Convenor, Technical Reports, Indian Institue of Technology, Kanpur, India,November 1994
Abst ract. The success of binary-coded gene t ic algorithms (GA s) inproblems having discrete sear ch sp ace largely depends on the codingused to represent the prob lem variables and on the crossover ope ratorthat propagates buildin g blocks from pare nt strings to childrenst rings . In solving optimization problems having continuous searchspace, binary-co ded GAs discr et ize the search space by using a codingof the problem var iables in binary st rings. However , t he coding of realvaluedvari ables in finit e-length st rings causes a number of difficulties:inability to achieve arbit rary pr ecision in the obtained solution , fixedmapping of problem var iab les, inh eren t Hamming cliff problem associatedwit h binary coding, and processing of Holland 's schemata incont inuous search space. Although a number of real-coded GAs aredevelop ed to solve optimization problems having a cont inuous searchspace, the search powers of these crossover operators are not adequate .In t his paper , t he search power of a crossover operator is defined int erms of the probability of creating an arbitrary child solut ion froma given pair of parent solutions . Motivated by t he success of binarycodedGAs in discret e search space problems , we develop a real-codedcrossover (which we call the simulated binar y crossover , or SBX) operatorwhose search power is similar to that of the single-point crossoverused in binary-coded GAs . Simulation results on a number of realvaluedt est problems of varying difficulty and dimensionality suggestt hat the real-cod ed GAs with t he SBX operator ar e ab le to perform asgood or bet t er than binary-cod ed GAs wit h t he single-po int crossover.SBX is found to be particularly useful in problems having mult ip le optimalsolutions with a narrow global basin an d in prob lems where thelower and upper bo unds of the global optimum are not known a priori.Further , a simulation on a two-var iable blocked function showsthat the real-coded GA with SBX work s as suggested by Goldberg
and in most cases t he performance of real-coded GA with SBX is similarto that of binary GAs with a single-point crossover. Based onth ese encouraging results, this paper suggests a number of extensionsto the present study.
7. ConclusionsIn this paper, a real-coded crossover operator has been develop ed bas ed ont he search characte rist ics of a single-point crossover used in binary -codedGAs. In ord er to define the search power of a crossover operator, a spreadfactor has been introduced as the ratio of the absolute differences of thechildren points to that of the parent points. Thereaft er , the probabilityof creat ing a child point for two given parent points has been derived forthe single-point crossover. Motivat ed by the success of binary-coded GAsin problems wit h discrete sear ch space, a simul ated bin ary crossover (SBX)operator has been develop ed to solve problems having cont inuous searchspace. The SBX operator has search power similar to that of the single-po intcrossover.On a number of t est fun ctions, including De Jong's five te st fun ct ions, ithas been found that real-coded GAs with the SBX operator can overcome anumb er of difficult ies inherent with binary-coded GAs in solving cont inuoussearch space problems-Hamming cliff problem, arbitrary pr ecision problem,and fixed mapped coding problem. In the comparison of real-coded GAs wit ha SBX operator and binary-coded GAs with a single-point crossover ope rat or ,it has been observed that the performance of the former is better than thelatt er on continuous functions and the performance of the former is similarto the lat ter in solving discret e and difficult functions. In comparison withanother real-coded crossover operator (i.e. , BLX-0 .5) suggested elsewhere ,SBX performs better in difficult test functions. It has also been observedthat SBX is particularly useful in problems where the bounds of the optimum
point is not known a priori and wher e there are multi ple optima, of whichone is global.Real-coded GAs wit h t he SBX op erator have also been tried in solvinga two-variab le blocked function (the concept of blocked fun ctions was introducedin [10]). Blocked fun ct ions are difficult for real-coded GAs , becauselocal optimal points block t he progress of search to continue towards t heglobal optimal point . The simulat ion results on t he two-var iable blockedfunction have shown that in most occasions , the sea rch proceeds the way aspr edicted in [10]. Most importantly, it has been observed that the real-codedGAs wit h SBX work similar to that of t he binary-coded GAs wit h single-pointcrossover in overcoming t he barrier of the local peaks and converging to t heglobal bas in. However , it is premature to conclude whether real-coded GAswit h SBX op erator can overcome t he local barriers in higher-dimensionalblocked fun ct ions.These results are encour aging and suggest avenues for further research.Because the SBX ope rat or uses a probability distribut ion for choosing a childpo int , the real-coded GAs wit h SBX are one st ep ahead of the binary-codedGAs in te rms of ach ieving a convergence proof for GAs. With a direct probabilist ic relationship between children and parent points used in t his paper,cues from t he clas sical stochast ic optimization methods can be borrowed toachieve a convergence proof of GAs , or a much closer tie between the classicaloptimization methods and GAs is on t he horizon.
In short, according to the authors my SBX operator using real gene values is as good as older ones specially designed for discrete searches, and better in continuous searches. SBX as far as i know meanwhile is a standard general crossover operator.
But:
- there might be better ones out there i just havent seen yet. please tell me.
- besides tournament selection and mutation, crossover is just one part of the breeding pipeline. also there is the elite management for MOEA which is AT LEAST as important as the breeding itself.
- depending on the problem, there are almost always better specific ways of how to code the mutation and the crossover operators. but octopus is meant to keep it general for the moment - maybe there's a way for an interface to code those things yourself..!?
2) elite size = SPEA-2 archive size, yes. the rate depends on your convergence behaviour i would say. i usually start off with at least half the size of the population, but mostly the same size (as it is hard-coded in the new version, i just realize) is big enough.
4) the non-dominated front is always put into the archive first. if the archive size is exceeded, the least important individual (the significant strategy in SPEA-2) are truncated one by one until the size is reached. if it is smaller, the fittest dominated individuals are put into the elite. the latter happens in the beginning of the run, when the front wasn't discovered well yet.
3) yes it is. this is a custom implementation i figured out myself. however i'm close to have the HypE algorithm working in the new version, which natively has got the possibility to articulate perference relations on sets of solutions.
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(1) I have been exporting small sections of a larger model into Maya from Rhino as FBX. In Maya I rotate and scale the models (-90 in X, Scale XYZ 0.001). The Named Views are being saved, but do not have a successful import into the Maya model. They do not appear as in Rhino, and the problem is not solved by scaling or rotating the cameras.
(2) If I try going the other direction, the cameras exported from Maya as FBX are also not aligning with the model in Rhino as they are in Maya.. I will do my best to post some images of the problem and hope you can help.
error !!
This is what the named views look like
here I am trying to the other way with a good view from Maya
strange placement..
This is the best result I can achieve, after I scale the camera by 1000
Any Advice???
Thanks, Robert.
…
ysim.ning.com/
When you run the simualtion you will notice on the batch terminal that Daysim is also being called, so you may want to consider how Daysim uses Radiance files & data.
Regarding your current problem, I think you stumbled onto something weird and interesting.
Interior and exterior readings appear to differ by 40 in the best case scenarios. Even setting the transmittance to 1 yields similar results. I tried changing from cummulative sky to climate sky and got similar values. Changing the test points did nothing either.
I think, (yet I'm too lazy to prove this) that the difference in values stems from diffuse radiation over the sky dome.
If you delete everything except the glass you'll notice that interior values are like 80-90% of the exterior values (this seems like the expected behaviour with a transmittance of 1). So, if we consider that a vertical window, part of an opaque box, is receiving radiation from 25% of a sphere, as you start to inset the interior test points the radiation they receive will be a fraction of the 25%.
Let me try to explain this better...The exterior surface receives radiation from a section of a sphere calculated by 180degrees on the xy plane (let’s call this angle theta) and by 90degrees (let’s call this angle phi) in azimuthal elevation. If you integrate this over spherical coordinates (theta from 0 to pi; phi from 0 to pi/2) you will find that it comes to a quarter of a sphere. By comparison, the interior surface will not integrate theta from 0 to 180degrees,nor phi from 0 to 90degrees, instead it will be the subtended angle from the exterior surface as a function of their separation; the farther in you go the smaller the view of the outside.
If my hypothesis is correct there shouldn't be that much difference since the separation is only 10cms...the subtended angle would be like 170 instead of 180 for theta and 85 instead of 90 for phi...overall if you integrate both spherical areas there should only by a difference of 10%.
In conclusion, I believe the unexpected behaviour stems from the previous subtended angle thing. If direct radiation was the only factor the difference would be the aforementioned 10%, which suggests that an additional source of energy is also affected by this. Perhaps indirect and diffuse radiation from other areas of the sky dome.
I’m definitely intrigued on why this is happening. Please post if you figure it out.
Regards,
Mauricio
…
azione parametrica e generativa attraverso Grasshopper, plug-in di programmazione visuale per Rhinoceros 3D (uno dei più diffusi modellatori NURBS per l‘architettura e il design). Il workshop mira a gestire e sviluppare il rapporto tra informazione e geometria lavorando sui sistemi ad involucro in condizioni specifiche.La discretizzazione di superfici (pannellizazione Nurbs o Mesh), la modellazione delle geometrie attraverso informazioni (siano esse provenienti da analisi ambientali, mappe o database) e l’estrazione e la gestione di queste informazioni, richiede la comprensione di strutture di dati al fine di gestire completamente processo che va dalla progettazione alla costruzione.I partecipanti impareranno come costruire e sviluppare strutture di dati parametrici per informare geometrie ‘data-driven’ e come estrarre le informazioni rilevanti da tali modelli per il processo di costruzione.
Modulo 2 – Il workshop, volto a promuovere le nuove tecnologie digitali di supporto alla progettazione e alla fabbricazione, esplorerà l’integrazione tra design e prototipazione tramite processi di stampa 3d di materiale ceramico al fine di comprenderne allo stesso tempo sia il comportamento del materiale che i vincoli e le opportunità offerte dall’utilizzo di tali tecnologie.Infatti utilizzando grasshopper ed una macchina a controllo numerico i partecipanti apprenderanno le modalità per la generazione parametrica dei modelli e la creazione del codice per la loro prototipazione (Gcode creato direttamente in Grasshopper). Il workshop darà quindi ai partecipanti la possibilità di testare direttamente i loro elaborati digitali stampandoli in modo da comprendere come le informazioni articolate tramite tali strumenti di design producano specifici effetti sia morfologici che estetici.…