what is in your opinion the best way to get data (measure date for example) into modelica (dymola)? Is it possible, to import data from python to modelica (for example into a combi-time-table)?
My idea would be as follows:
pre processing of measured data in python
load the data from python into modelica (comi-time-table)
rund simulation studies (scripted in python)
I would appreciate any suggestions.
That's probably a matter of opinion. But since you have to do much of your data post- and preprocessing in Python I would definitely export my (plant) model from Dymola as a co-simulation FMU and run it in Python.
In Dymola you can export FMU's and 'execute' them on the same pc that holds the Dymola license file. If you need to run the FMU on another pc you'll have to buy a special binary export license.
There is a free Python package called PyFMI (www.pyfmi.org) which makes it easy to run an FMU in Python. See the examples at http://www.jmodelica.org/page/4924.
PyFMI can be a bit tricky to get up and running (with the right Python package dependencies and so on). So if you are not an experienced Python user I would suggest that you download the installer for JModelica.org which will do much the setting up for you.
Best regards,
Rene Just Nielsen
As Rene Just Nielsen pointed out, this is primarily opinion based.
To give another way of accomplishing your goal, try the DymolaInterface. You could either set the table-parameter via the Interface in python, our use a .txt-file which you create and alter in python, and Modelica just knows the path to the file. The interface comes with your Dymola installation under Modelica\Library\python_interface\dymola.egg where you will also find documentation for the functions.
Another python-package for using FMU's is FMPy. I image both FMPy and PyFMI have their pros and cons.
The last option which does not require any external python package would be to use mos-files to execute simulations and use the .txt-files to read in the data. If the task you described is the only thing you want to accomplish, mos-scripts are quite sufficient.
Related
Short version:
Is it possible to create a standalone program that can be distributed to computers that don't have python installed, which writes a python script during runtime and executes it during or shortly after?
Long version:
A project I've been wanting to do for a while is to create a visual programming interface, that lets people use Machine Learning without needing to know python/keras/numpy syntax. Programs like lobe or rapidminer already do this, but they are all bound to their own interfaces and servers. What i would like to do is create a program that:
anyone can use without needing python/anaconda installed
allow the user to create visual scripts like in scratch or google-blocs
generates python code behind the scenes containing keras or tf code
is able to execute the script
is able to show the code to the user for:
educational purposes
allowing the user to use it as a base for a more complex program
Since the generation part would just need to create a text file almost any interface and language like python/java using Qt or C# / javascript using Unity, would qualify. I think that should definitely be doable, probably just very long, but that is not my largest concern.
The problem:
I have tried to search everywhere on the internet about things like standalone python programs which led me to for instance py2exe. Those kind of python-to-exe's work great, but they all require the script to be compiled on a machine containing a python environment. In my case i want to be able to generate a python script on the user's PC, and run it directly after from there.
The alternative
If this isn't possible i might just create the whole AI part myself, not using python nor libraries like keras or tensorflow, but in a unity game for instance. The downside to this would be that it exists already(like rapidminer), it would be less optimized/versatile/customizable and doesn't show what the "real" machine learning script would look.
If there are any other alternatives i would be happy to hear them
PS.
I have mostly Python & Keras, moderate Java and little Unity3D or web JS experience
I'm using Windows with anaconda
Distributing to linux/mac would be nice, but not required
maybe you should check the Orange Data Mining software, it's written in python and it has the same purpose as your project (https://orange.biolab.si/). On the other hand, some time ago I tried to compile my app that contains machine learning libraries but to date, I have not been able to achieve it. Instead, what I use is the WINPYTHON project, this is a portable Anaconda software that allows you to run projects on any PC without the need to install anything (https://winpython.github.io/).
Yes, it is possible!
I had the same requirement, so I wrote my visual programming language and IDE...
...that could generate an almost python-like script, and which is compiled natively inside the app, without the use of any external compilers or libraries.
My target architecture was mobile devices, but it also works on browsers via the unity plugin.
...and yes, that's correct, it runs natively on your phone or tablet in a simulated sandbox, with its own built-in IDE.
It's written in C#, and implemented in Unity3d
You can check it out at https://aiBoard.blog
..and see the videos at https://youtu.be/DIDgu9jrdLc
I'm helping my wife try and navigate IBM SPSS and python. She knows SPSS, and I kinda know python -- We might be able to work together. As it stands, I understand that I can call small snippets of python from within an SPSS syntax. While this is useful for looping and conditional branching based on data, it seems a little fuzzy to me. It almost feels like Inversion of Control, but not really.
I was wondering is it possible to have a python script, external to an spss syntax, that can still use the SPSS libraries in any meaningful way, or do I have to keep my scripts confined to the SPSS syntax and runtime?
Yes, you can run Statistics in external mode from a Python or R program. You might have to add the SPSS Python directory to your Python search path, but then just do
import spss
and run your Python code. The only thing you can't do is Viewer and user interface stuff, because there is no SPSS UI in that mode. By default, you will get output as text (which you can turn off when you get the hang of things). If you want better quality output, you can use OMS to capture output in a wide variety of formats.
Note that you need a compatible version of Python if you don't use the one installed with SPSS. That would be 2.7 for most Statistics versions. The Python installed with Statistics is not registered, but you can install a standard version from Python.org and just add the SPSS Python directory to the search path.
HTH
My research group has developed python code for a new building component that we would like to co-simulate with EnergyPlus. For reuseability and market impact we would like this connection to be as easy as possible for inexperienced users and believe packing the model using the Function Mockup Interface Standard (FMI) to be the best option.
We have explored JModelica to test other Functional Mockup Units (FMUs) but found that it does not do FMU export of Python code for model exchange or co-simulation.
I was curious if there any methods for packaging python code as an FMU? If there is not, is there another way of linking Python to the FMI standard or connecting it to a building energy software like EnergyPlus?
The alternative to this would be exporting the building energy model as an FMU and import into modelica/jmodelica or using BCVTB. Although this would work for us we worry it would make it too difficult for inexperienced individuals to use our tool.
Just to be clear, JModelica does support export and import of both ME and CS FMUs and supports versions 1.0 and 2.0 of the FMI standard. I assume you mean that JModelica does not support export of Python code as FMU. I am not aware of any such solution. If you do not find a way of packaging the Python code into an FMU, perhaps setting up a proxy FMU that communicates with your Python code would work?
So I am working on setting up an agent-based model that runs over a geographic map--syria in this case. I tried writing it in python, but the performance is rather slow--even after some optimization tricks. I was thinking that I should shift to just writing the model in C++, but I don't know which visualization packages can incorporate maps? I tend to use gnuplot in C++, but I have not been able to find a way to incorporate a gis basemap in that package. I am not sure if this is possible in VTK or any other packages. I would like to find a way to run my model fast in C++ but not lose the geographic information. Any suggestions?
Perhaps this project could be useful to you ?
http://code.google.com/p/vtk-grass-bridge/
If you can handle your GIS data using GRASS, it seems that project can convert it to something VTK can render, all in one C++ application.
So I actually figured out the answer to this problem and am posting the solution for everyone. The best choice if you are using python, is to just use the mayavi and tvtk packages from Enthought. Mayavi is a gui on top of the C++ VTK libraries. And tvtk is actually a wrapper for python access to VTK objects. So this allows a person to use python GIS packages--like pyshp, Shapely, and others to manipulate GIS objects and then write them to robust and fast mayavi for visualization. At the same time, if you want to stick to C++ then you can still just write your code in C++ using gdal or ogr, etc., and then run your visualization in VTK. This seems a lot easier and more intuitive then trying to run through some other packages like GRASS, QGIS, or ArcGIS.
Here is a good example of this toolset in action.
Example
What makes you believe that a C++ implementation of your model will be dramatically faster? I suggest before being concerned with how you will visualize the results you focus first on what causes your python implementation to be slow. Is it that your algorithm won't scale? If you have tried optimization tricks, what tricks were those and why do you believe they did not work?
It all eventually comes down to machine instructions being executed on hardware, whether those instructions started out as python, C++ , or some other language source code. Unless your python was running fully interpreted all the time I don't think you will find that switching languages alone will cause you to have a fundamentally different performance profile. Premature optimization is still something to be avoided.
I'm building a rendering engine in Python for fun. I need to load 3D scenes. Any standard modern format like DAE, 3DS, or MAX would work: I can convert my files easily between standard formats.
OpenSceneGraph seems to be the most comprehensive and well-maintained solution. It would be ideal to be able to use it in Python without much hassle. Are there working Python bindings for OSG that are easy to install, work on Mac OS X (I'm on 10.8), and are compatible with the latest versions of OSG?
I searched around and came across osgswig (http://code.google.com/p/osgswig/) and PyOSG (http://sourceforge.net/projects/pyosg/), but they don't seem to be actively maintained. I don't see any recent activity related to these packages, and it seems that people had trouble running osgswig on OSX. Ideally, I'd like to find something that "just works", without major compilation hassles. I'd like to just install a package and be able to import a module that will let me load COLLADA or 3DS files.
I also came across pycollada (https://github.com/pycollada/pycollada). It seems active, but fairly early-stage. Ideally, I'd like a reasonably comprehensive package that supports specular maps, normal maps, and other reasonably advanced features. Animation would be nice as well.
In summary, I need to load 3D scenes in Python. Bindings for OSG would probably be ideal, because OSG is so comprehensive. But I need something that works on OSX. I would also prefer something that can be installed reasonably easily. Does something like this exist?
Thanks!
Take a look at Open Asset Import Library (short name: Assimp). It is a portable Open Source library to import various well-known 3D model formats in a uniform manner. http://www.assimp.org/
You should loot at panda3D (http://www.panda3d.org/), it's a game engine with extensive python bindings. It has the features you want : http://www.panda3d.org/manual/index.php/Features
I used it for a few years and it was a solid tool.
I made my own fork of a mirror of a clone of the osgswig project for a similar purpose. I have it working with OpenSceneGraph version 3.2.1 on Windows and Mac; and it's likely I will eventually polish it for linux too. I'm already delivering one product to customers based on my version of osgswig, and I'm considering making others. Find my fork here:
https://github.com/cmbruns/osgswig
If others show enough interest, I might be coaxed into creating binary installers for my version of the osgswig module, to make installation easier.
If you just want the easiest OpenSceneGraph bindings for OSG 3.2.1, you can stop reading this answer here. Read on for more of my thoughts for the future.
Though I am maintaining a fork of osgswig (as stated above), I sort of hate SWIG, and I would prefer to use bindings based on Boost.Python, rather than on SWIG. For large, complex C++ APIs, like OpenSceneGraph, Boost.Python can be much more elegant than SWIG, both for the API consumer, and for the binding maintainer (me, and me). I found one project using Boost.Python to wrap OSG, at https://code.google.com/p/osgboostpython/, but the developer is lovingly wrapping each part of the interface by hand, and has thus only completed a tiny fraction of the large OpenSceneGraph API.
Taking that Boost.Python based project as inspiration, I created yet another OpenSceneGraph Python binding project, at https://github.com/JaneliaSciComp/osgpyplusplus. Eventually, I want to use this osgpyplusplus project for all my python osg needs. And I would appreciate help in making it ready. Right now, osgpyplusplus suffers from the following weaknesses, compared to osgswig:
osgpyplusplus is not yet used in any working product
The build environment is tricky to set up, requiring both Boost.Python and Pyplusplus
I haven't paid much attention to osgpyplusplus recently, so it might rust away if I continue to ignore it.
Though osgpyplusplus probably wraps most of the OpenSceneGraph API, there are probably some important missing pieces that won't be identified until someone tries to develop a significant project with it.
It would be a lot of work for me to create a binary module installer for osgpyplusplus at this point, so please don't ask me to.