it seems that was this. Now all is working fine !
Glad that it worked! But I am still a bit worried. Gismo components only modify the gdal-data/osmconf.ini file and no other MapWinGIS file. So your MapWinGIS installation files should not be compromised. The fact that you did not get the "COM CLSID" error message when running the "Gismo Gismo" component suggests that MapWinGIS has been properly installed. So I wonder if the cause for the permanent "invalid shapes" warning has again something with the fact that your system is again not allowing the MapWinGIS to properly edit the osmconf.ini. Maybe this problem will appear again, and again, and reinstallation of MapWinGIS every time can be somewhat bothersome.
- About the terrain generation, is it possible to have the texture from google or other provider mapped onto the terrain surface from gismo component ? (Same as using the ladybug terrain generator in fact). I try to used the image extracted by ladybug component and then applied it to the gismo terrain but the texture is rotated by 90°.
The issue with the rotation can be solved by swapping/reversing the U,V directions of the terrain surface. A slightly more important issue is that terrain surface generated with Gismo "Terrain Generator" component might have a bit smaller radius than what the radius_ input required. This stems from the fact that the terrain data first needs to be downloaded in geographic coordinate system, and then projected. Some projecting issues may occur at the very edges of the projected terrain, so I had to slightly cut out the very edges of the terrain which results in the actual terrain diameters being slightly shorted in both directions. This means that if you apply the same satellite image from Ladybug "Terrain Generator" component to Gismo "Terrain Generator" component the results may not be the same.I attached below a python component which tries to solve this issue by extending the edges of Gismo "Terrain Generator" terrain, and then cutting them with the cuboid of the exact dimensions as the radius_ input. Have in mind that this extension of the original terrain at its edges is not a correct representation of the actual terrain in that location. But rather just an extension of the isoparameteric curve of the terrain surface. So basically: some 0 to 10% (0 to 10 percent of the width and length) of the terrain around all four edges is not the actual terrain for that location, but rather just its extension.The python component is located at the very right of the definition attached below.
Also, if you would like to use the satellite images from Ladybug "Terrain Generator" component along with "OSM shapes", sometimes you may find slight differences in position of the shapes. This is due to openstreetmap data not being based on Google Maps (that's what Ladybug "Terrain Generator" component is using), but rather on Bing, MapQuest and a few others.
- About the requiredKeys_ input of OSM shapes, I understand what you mean and your advice, but in most cases I use it, the component was working fine even without input. I think it's better to extract all tags, values and keys of the selected area, instead of searching for specific ones as I try to find all data related to what I want after, isn't it ? To check what keys are present on the area also.
Ineed, you are correct.I though you were trying to only create a terrain, 3d buildings and maybe find some school or similar 3d building, for these two locations. The recommendation I mentioned previously is due to shapefiles having a limit (2044) to how many keys it can contain. This requires further testing of some big cities locations with maybe larger radii, which I haven't performed due to my poor PC configuration. But in theory, I imagine that it may happen that a downloaded .osm file may have more than 2044 keys. In that case shapefile will only record 2044 of them, and disregard the others. That was my point.But again 2044 is a lot of keys, and I haven't been checking much this in practice. For example, when I set the radius_ to 1000 meters, and use your "3 Rue de Bretonvilliers Paris" location I get around 350 something keys, which is way below the 2044.Another reason why one should use the requiredKeys_ input is to make the Gismo OSM components run quicker: for example, the upper mentioned 350 something keys will result in 350 values for each branch of the "OSM shapes" component's "values" output.Which means if you have 10 000 shapes, the "OSM shapes" component will have 10 000 branches with 350 items on each branch (values). This can make all Gismo OSM components very heavy, and significantly elongate the calculation process.With requiredKeys_ input you may end up with only a couple of tens of items per each branch.Sorry for the long reply.…
Added by djordje to Gismo at 8:57am on June 11, 2017
ting at multiple geometries in the same location. I simply sorted the list of values and used the Delete Consecutive component. This potentially rearranges the order of values but I don't think that matters in your case. I also threw in an Int component which actually seems to make a difference (try sidestepping it and you will see!).
2-I flattened the output of the mesh component before sending it to union. This ensures that the original mesh is booleaned once with all the components rather than individually with each of the 86 components.
Is this what the result should look like?
One suggestion for future postings: when referencing geometry in rhino, it often helps if you attach your rhino file as well so people don't have to guess where you are starting from.
If you have further questions, just ask ;-)
cbass…
oftware connections built from the initial seed of the project. As always you can download the new release from Food4Rhino. Make sure to remove the older version of Ladybug and Honeybee and update your scripts.
This release is also special since today it is just about 3 years (3 years and 2 weeks) from the first release of Ladybug. As with any release, there have been a number of bug fixes and improvements but we also have some major news this time. In no specific order and to ensure that the biggest developments do not get lost in the extensive list of updates, here are the major ones:
Mostapha is re-writing Ladybug!
Ladybug for DynamoBIM is finally available.
Chris made bakeIt really useful by incorporating an export pathway to PDFs and vector-based programs.
Honeybee is now connected to THERM and the LBNL suite thanks to Chris Mackey.
Sarith has addressed a much-desired wish for Honeybee (Hi Theodore!) by adding components to model electric lighting with Radiance.
Djordje is on his way to making renewable energy deeply integrated with Ladybug by releasing components for modeling solar hot water.
There is new bug. Check the bottom of the post for Dragonfly!
Last but definitely not least (in case you’re not still convinced that this release is a major one) Miguel has started a new project that brings some of Ladybug’s features directly to Rhino. We mean Rhino Rhino - A Rhino plugin! Say hi to Icarus! #surprise
Before we forget! Ladybug and Honeybee now have official stickers. Yes! We know about T-Shirts and mugs and they will be next. For now, you can deck-out your laptops and powerhouse simulation machines with the symbology of our collaborative software ecosystem.
Now go grab a cup of tea/coffee and read the details below:
Rewriting Ladybug!
Perhaps the most far-reaching development of the last 4 months is an effort on the part of Mostapha to initiate a well structured, well documented, flexible, and extendable version of the Ladybug libraries. While such code is something that few community members will interact with directly, a well-documented library is critical for maintaining the project, adding new features, and for porting Ladybug to other software platforms.
The new Ladybug libraries are still under development across a number of new repositories and they separate a ladybug-core, which includes epw parsing and all non-geometric functions, from interface-specific geometry libraries. This allows us to easily extend Ladybug to other platforms with a different geometry library for each platform (ie. ladybug-grasshopper, ladybug-dynamo, ladybug-web, etc) all of which are developed on top of the ladybug-core.
Without getting too technical, here is an example of a useful outcome of this development. If you want to know the number of hours that relative humidity is more than 90% for a given epw, all that you have to code (in any python interface) is the following:
import ladybug as lb
_epwFile = r"C:\EnergyPlusV7-2-0\WeatherData\USA_CO_Golden-NREL.724666_TMY3.epw"
epwfile = lb.epw.EPW(_epwFile)
filteredData = epwfile.relativeHumidity.filterByConditionalStatement('x>90')
print "Number of hours with Humidity more than 90 is %d "%len(filteredData.timeStamps)
Compare that to the 500 + lines that you would have had to write previously for this operation, which were usually tied to a single interface! Now let’s see what will happen if you want to use the geometry-specific libraries. Let’s draw a sunpath in Grasshopper:
import ladybuggrasshopper.epw as epw
import ladybuggrasshopper.sunpath as sunpath
# get location data form epw file
location = epw.EPW(_epwFile).location
# initiate sunpath based on location
sp = sunpath.Sunpath.fromLocation(location, northAngle = 0, daylightSavingPeriod = None, basePoint =cenPt, scale = scale, sunScale = sunScale)
# draw sunpath geometry
sp.drawAnnualSunpath()
# assign geometries to outputs
...
Finally we ask, how would this code will look if we wanted to make a sunpath for dynamo? Well, it will be exactly the same! Just change ladybuggrasshopper in the second line to ladybugdynamo! Here is the code which is creating the sunpath below.
With this ease of scripting, we hope to involve more of our community members in our development and make it easy for others to use ladybug in their various preferred applications. By the next release, we will produce an API documentation (documentation of all the ladybug classes, methods and properties that you can script with) and begin making tutorials for those interested in getting deeper into Ladybug development.
LADYBUG
1 - Initial Release of Ladybug for Dynamo:
As is evident from the post above, we are happy to announce the first release of Ladybug for Dynamo! You can download the ladybug package from Dynamo package manager. Make sure to download version 0.0.6 which is actually 0.0.1! It took a number of trial and errors to get it up there. Once you have the file downloaded you can watch these videos to get started:
The source code can be find under ladybug-dynamo repository and (as you can already guess) it is using the new code base. It includes a very small toolkit of essential Ladybug components/nodes but it has enough to get you started. You can import weather files, draw sunpaths and run sunlighthours or radiation analyses.
There are two known issues in this release but neither of them is critical. You need to have Dynamo 0.9.1 or higher installed which you can download from here (http://dynamobuilds.com/). It is recommended that you run the scripts with ‘Manual’ run (as opposed to ‘Automatic’) since the more intense calculations can make Dynamo crash in automatic mode.
To put things in perspective, here is how we would map Ladybug for Dynamo vs Ladybug and Honeybee for Grasshopper on the classic ‘Hype graph’. The good news is that what we learned a lot from the last three years, making development of the Dynamo version easier and getting us to the plateau of productivity faster.
We should also note that the current development of the Dynamo interface is behind that of the Ladybug-Core, which means there are a number of features that are developed in the code but haven’t made their way to the nodes yet. They will be added gradually over the next month or two.
If you’re interested to get involved in the development process or have ideas for the development, follow ladybug on Facebook, Twitter and Github. We will only post major release news here. Facebook, github and twitter will be the main channels for posting the development process. There will also be a release of a new ladybug for Grasshopper soon that will use the came Ladybug-Core libraries as the Dynamo interface [Trying hard not to name it as Ladybug 2].
2 - New Project “Icarus” Provides Ladybug Capabilities Directly in Rhino
Speaking of expanded cross-platform capabilities, the talented Miguel Rus has produced a standalone Rhino Plugin off of the original Ladybug code that has been included in this release. After writing his own core C# libraries, Miguel’s plugin enables users to produce sunpath and run sunlight hours analyses in the Rhino scene without need of opening Grasshopper or engaging the (sometimes daunting) act of visual scripting.
This release includes his initial RHP plugin file. It is hoped that Miguel’s efforts will extend some of the capabilities of environmental design to individuals who are unfamiliar with visual scripting, casting the network of our community into new territory. We need your help spreading the word about Icarus since the people who will benefit the most from it have probably not read this far into the release notes. Also, as the project is in the early stages, your feedback can make a great difference. You can download the current release from this link.
Once you download the zip file. Right click and unblock it. Then extract the files under C:\Program Files\Rhinoceros 5 (64-bit)\Plug-ins\ folder. Drag and drop the RHP file into Rhino and you should be ready to go. You can either type Icarus in the command line or open it via the panels. Here is a short video that shows how to run a sunlighhours analysis study in Rhino.
3 - BakeIt Input Now Supports a Pathway to PDF +Vector Programs
As promised in the previous release, the BakeIt_ option available on Ladybug’s visual components has been enhanced to provide a full pathway to vector-based programs (like Illustrator and Inkscape) and eases the export to vector formats like PDFs.
This means that the BakeIt_ operation now places all text in the Rhino scene as actual editable text (not meshes) and any colored meshes are output as groups of colored hatches (so that they appear as color-filled polygons in vector-based programs). There is still an option to bake the colored geometries as light meshes (which requires smaller amounts of memory and computation time) but the new hatched capability should make it easier to incorporate Ladybug graphics in architectural drawings and documents like this vector psychrometric chart.
4 - Physiological Equivalent Temperature (PET) Now Available
Thanks to the efforts of Djordje Spasic, it is now possible to compute the common outdoor comfort metric ‘Physiological Equivalent Temperature’ (PET) with Ladybug. The capability has been included with this release of “Thermal Comfort Indices” component and is supported by a “Body Characteristics” component in the Extra tab. PET is particularly helpful for evaluating outdoor comfort at a high spatial resolution and so the next Honeybee release will include an option for PET with the microclimate map workflow.
5 - Solar Hot Water Components Available in WIP
Chengchu Yan and Djordje Spasic have built a set of components that perform detailed estimates of solar hot water. The components are currently undergoing final stages of testing and are available in the WIP tab of this release. You can read the full release notes for the components here.
6 - New Ladybug Graphic Standards
With the parallel efforts or so many developers, we have made an effort in this release to standardize the means by which you interact with the components. This includes warnings for missing inputs and the ability to make either icons or text appear on the components as you wish (Hi Andres!). A full list of all graphic standards can be found here. If you have any thoughts or comments on the new standards, feel free to voice them here.
7 - Wet Bulb Temperature Now Available
Thanks to Antonello Di Nunzio - the newest member of the Ladybug development team, it is now possible to calculate wet bulb temperature with Ladybug. Antonello’s component can be found under the WIP tab and takes inputs of dry bulb temperature, relative humidity, and barometric pressure.
8 - New View Analysis Types
The view analysis component now allows for several different view studies in addition to the previous ‘view to test points.’ These include, skyview (which is helpful for studies of outdoor micro-climate), as well as spherical view and ‘cone of vision’ view, which are helpful for indoor studies evaluating the overall visual connection to the outdoors.
HONEYBEE
1 - Connection to THERM and LBNL Programs
With this release, many of you will notice that a new tab has been added to Honeybee. The tab “11 | THERM” includes 7 new components that enable you to export ready-to-simulate Lawrence Berkeley National Lab (LBNL) THERM files from Rhino/Grasshopper. THERM is a 2D finite element heat flow engine that is used to evaluate the performance of wall/window construction details by simulating thermal bridging behavior. The new Honeybee tab represents the first ever CAD plugin interface for THERM, which has been in demand since the first release of LBNL THERM several years ago. The export workflow involves the drawing of window/wall construction details in Rhino and the assigning of materials and boundary conditions in Grasshopper to produce ready-to-simulate THERM files that allow you to bypass the limited drawing interface of THERM completely. Additional components in the “11 | THERM” tab allow you to import the results of THERM simulations back into Grasshopper and assist with incorporating THERM results into Honeybee EnergyPlus simulations. Finally, two components assist with a connection to LBNL WINDOW for advanced modeling of Glazing constructions. Example files illustrating many of the capabilities of the new components can be found in there links.
THERM_Export_Workflow, THERM_Comparison_of_Stud_Wall_Constructions
Analyze_THERM_Results, Thermal_Bridging_with_THERM_and_EnergyPlus
Import_Glazing_System_from_LBNL_WINDOW, Import_LBNL_WINDOW_Glazing_Assembly_for_EnergyPlus
It is recommended that those who are using these THERM components for the first time begin by exploring this example file.
Tutorial videos on how to use the components will be posted soon. A great deal of thanks is due to the LBNL team that was responsive to questions at the start of the development and special thanks goes to Payette Architects, which allowed Chris Mackey (the author of the components) a significant amount of paid time to develop them.
2 - Electrical Lighting Components with Enhanced Capabilities for Importing and Manipulating IES Files
Thanks to the efforts of Sarith Subramaniam, it is now much easier and more flexible to include electric lighting in Honeybee Radiance simulations. A series of very exciting images and videos can be found in his release post.
You can find the components under WIP tab. Sarith is looking for feedback and wishes. Please give them a try and let him know your thoughts. Several example files showing how to use the components can be found here. 1, 2, 3.
3- Expanded Dynamic Shade Capabilities
After great demand, it is now possible to assign several different types of control strategies for interior blinds and shades for EnergyPlus simulations. Control thresholds range from zone temperature, to zone cooling load, to radiation on windows, to many combinations of these variables. The new component also features the ability to run EnergyPlus simulations with electrochromic glazing. An example file showing many of the new capabilities can be found here.
Dragonfly Beta
In order to link the capabilities of Ladybug + Honeybee to a wider range of climatic data sets and analytical tools, a new insect has been initiated under the name of Dragonfly. While the Dragonfly components are not included with the download of this release, the most recent version can be downloaded here. An example file showing how to use Dragonfly to warp EPW data to account for urban heat island effect can also be found here. By the next release, the capabilities of Dragonfly should be robust enough for it to fly on its own. Additional features that will be implemented in the next few months include importing thermal satellite image data to Rhino/GH as well as the ability to warp EPW files to account for climate change projections. Anyone interested in testing out the new insect should feel free to contact Chris Mackey.
And finally, it is with great pleasure that we welcome Sarith and Antonello to the team. As mentioned in the above release notes, Sarith has added a robust implementation for electric light modeling with Honeybee and Antonello has added a component to calculate wet bulb temperature while providing stellar support to a number of people here on the GH forum.
As always let us know your comments and suggestions.
Enjoy!
Ladybug+Honeybee development team
PS: Special thanks to Chris for writing most of the release notes!…
Crystallon is an open source project for creating lattice structures using Rhino and Grasshopper3D. The goal is to generate lattice structures within Rhino’s design environment without exporting t
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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