I have a series of points (x,y,z) that I would like to plot as a vector in a 3D plane. Something like this.
I am successfully using QCustomPlot elsewhere, but the documentation says it cannot be used for 3D plots. Googling turned up QwtPlot3D, but it hasn't been maintained since 2007, as far as I can tell, and I don't want to run into any problems since I'm using Qt5. I was also looking at QtCharts but can't seem to find any example of plotting x,y,z data points.
Does anyone have tips for including a 3D graph in my C++/Qt application? Is there a tool that would work better with Python with Qt, rather than C++? Or another technology entirely? This graph will be part of a larger UI.
This might help, though I haven't used it:
http://doc.qt.io/QtDataVisualization/
Spend a little time looking into OpenGL. To display OpenGL scenes in Qt you would use QGLWidget (for Qt 4.x) or QOpenGLWidget (for Qt 5.x). OpenGL allows you to write graphics that run on a GPU card, meaning you can tap into the same horsepower used for 3D video games. Given time and inclination, you can build up a good 3D graphics library.
https://www.opengl.org/
http://doc.qt.io/qt-5/qopenglwidget.html
The Qt tutorials can help, but you'll also want to read other OpenGL tutorials. Here are some tutorials targeting older versions of Qt:
ftp://ftp.informatik.hu-berlin.de/pub1/Mirrors/ftp.troll.no/QT/pub/developerguides/qtopengltutorial/OpenGLTutorial.pdf
http://www.decom.ufop.br/sibgrapi2012/eproceedings/tutorials/t3-survey_paper.pdf
Tutorials tend to start with "immediate mode" examples, meaning the CPU is continually involved with updating data and writing that data to the GPU. As soon as you grasp the basics you'll want to implement "retained mode" code, meaning (very loosely) that the GPU manages the data and the need for CPU resources is minimized.
All that said, getting into OpenGL is a commitment. If you want the user to be able to change the viewpoint of the chart, or zoom in/out, or mouse over a plot to check individual values, etc., then it will take some time to implement. For a standard that's so widely use it's odd that the documentation and available textbooks aren't better--don't expect to find the OpenGL textbook equivalent of Kernighan & Ritchie or the Perl camel book.
There may be some Qt 3D graphing project somewhere that enjoys active development, and with luck maybe some other SO user will know about one.
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I am developing a 3D Graphing Calculator software in Unity3D. I am struggling to find good numerical/symbolic math libraries written in C/C#. Also, I want to make the calculator programmable (like the TI-84 Calculators everyone uses in school).
I found Python to be a very good language for the backbone of this project. SymPy and NumPy are really good math libraries. And Python would be really good for users to program the calculator. (Here is already a calculator, the Numworks, that supports Python programs. The team ported Python to the hardware.)
If I am developing for the PC, I could just use Python with openGL, or use IronPython in Unity.
However, I'm developing for the Nintendo 3DS. It may sound like a strange hardware choice, but it makes good sense. The 3DS has a stereoscopic display perfect for showing 3D functions. It has a joy stick to operate the camera. It has a touch screen to handle input. Imagine showing a height map of a 3D function on the lower display. You can use it to trace the function. You can draw a region D on it, and have the 3DS integrate over the region. You can take directional derivatives with your stylus. The possibility is endless.
The problem, of course, is that Unity doesn't support Python, and IronPython only supports Windows/Mac/Linux/Android.
Do you have any suggestions for me?
For example, any possible way to use python in unity for the 3DS? Any good math library in C/C#? Can I implement a good enough Python interpreter in C# to handle user's program (doesn't have to be complaint)?
You could try the Math.Net library for C#, it should have the functionality you need, or you could try IronPython, here is an article that might help you get started.
http://shrigsoc.blogspot.com/2016/07/ironpython-and-unity.html
I am a meteorologist, and lately I am trying to investigate the possibility of building my one sondes.
In order to do that, I have the following work plan :
I would like to generate 3D models pyformex. An alternative is openSCAD. But I start with pyformex - to generate simple cylindrical sonde shapes with associated extra features, e.g. intake tube or such.
Next, I will like to split it in Meshes, using PyDistMesh; as well as prepare a raytraced point cloud model with Xrt.
In the third step, I would like to perform the CFD works.
Now, my questions :
Are there some other simple Python Libraries to generate 3D models? I would like a very simple system, where i can issue commands like p = Parallelogram (length, height, width), or p.position(x,y,z) etc. It would be nice to have built in mouse interaction - that is, a built in drawing component, which I can use to display the model, and rotate/ zoom/pan with mouse.
Any other mesh generation tools?
For this step, I would need a multiphysics system. I tried to use OpenFOAM, it is too huge (to hack through). I have taken a look at SU2, but it seems to focus more on aerospace engineering, than Fluid Dynamics (I would like to simulate the flight of the sonde - which is closer to aerospace engineering, as well as the state of the atmosphere). Fluidity seems to suit my needs better, but I dont find a python fork thereof. So are there some general purpose, not too bloated up, multiphysics python library for geophysical and general hydrodynamic simulations? I have taken a look a MOOSE, also dont find a python binding for it.
Scientific visualization : Are there some 3 or 4 (or may be higher dimensional) visualization libraries? I would prefer to issue simple commands as Plot instead of first generating a window / form, and then putting the graphs on it, if possible.
FINALLY, and most importantly, if the same can be done by C++ or Fortan, or some other language besides java, I would also consider using those.
Have a look at http://freecadweb.org/. This seems to be under active development. It is a fairly complete open source CAD package written in python. I believe it also has tools for meshing.
For cfd, you might want to consider openfoam - http://www.openfoam.com/. This is an open source cfd package with the obligatory steep learning curve. There seem to be some python libraries to be available that link to it, however I'm not sure how active these are:
http://openfoamwiki.net/index.php/Contrib/PyFoam
http://pythonflu.wikidot.com/
I am currently in a project where a lot of 3D printing designs need to be done. They are all parameterized, so I'd like to write a python code to generate those design files (in .STL format) for me. I was wondering that, is there a python package that can do this? Because currently I am all doing those by hand using SolidWorks.
Thanks!
Yes there is... It's called FreeCAD.
The assembly module is already in the devel version (as of 06/15/2014) and will be of production quality really soon for real assemblies!
http://freecadweb.org/
Yes, more than one.
In my humble experience, I tried many Open Source tools for parametric CAD modeling using Python (FreeCAD, Rhino-Grasshopper, Blender, Salome).
All of them are valid options and the best one is represented by your ability to either model or code.
I recently favour SALOME (www.salome-platform.org) because of the straight forward "dump study" option, the continue development and the good API documentation.
Particularly I did some 3d prints using the exportSTL command once I had a solid worthy of printing and it was ok.
Nevertheless, if you intend to work on surfaces rather than solids, I don't think you will find anything worthy Open Source (Rhino has a little price to pay).
There is also a new one ! called pymadcad
It's a library meant to do complete CAD stuff only with python scripts.
At contrary to FreeCAD, Pymadcad is natively dealing with triangular meshes so it makes it very easy to import/export .stl files.
There is a growing amount of surface generation functions (extrusion, revolution, tube, screw, smooth surface, ...). And there is also all the stuff to generate and deal with 3D primtives such as Lines, Arc, ...
Here is a brief look at the features
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I'm using Python in an attempt to analyse a large chunk of empiric measurements. In essence, I've two functions transforming the empiric data which also takes 3 'count' parameters - and returns a sequence of floats in each configuration. I'm expecting (hoping) to see some interesting patterns emerge when appropriate parameters are selected. I anticipate that the patterns might be relative between sequences returned for each function - and/or relate to patterns of some kind in the parameters. In case it's relevant, the 3 'count' parameters roughly correspond to:
A 'window size' on the underlying data over which summary statistics are calculated
A number of consecutive windows used to compute a single summary statistic (i.e. the trade-off between greater spatial or greater temporal accuracy)
An 'minimum age' - an offset into history of the underlying data.
The summary statistics (which generate the resulting sequences of floats for each parameter configuration) are non-trivial but will be independently sensitive to all three parameters.
I'm interested in visualisation techniques - suited to RAD/ad-hoc enquiry that will help me experiment with this multi-dimensional data.
So far, I've tinkered with MatPlotLib but find being restricted generating two graphs of 2/3 dimensions in the style of batch processing makes investigation very tedious. Ideally, I'd find a tool that would allow me to visualise more than two dimensions... perhaps allowing me to switch real-time between dimensions in an interactive GUI.
I'd really appreciate hints from any visualisation gurus as to suitable tools I should investigate - ideally to integrate with my existing Python functions - or in other languages. I'd especially like to hear any anecdotes of success with similar visualisation problems.
EDIT to add: One possible approach I'm considering is to use animation on 2 or 3D plots (to capture another dimension... leaving 1 or 2 for manual selection)... though I've found no good tools to help me achieve this, yet.
RGL is a visualization device system for R, using OpenGL as the rendering backend. An rgl device at its core is a real-time 3D engine written in C++. It provides an interactive viewpoint navigation facility (mouse + wheel support) and an R programming interface.
GGobi is an open source visualization program for exploring high-dimensional data. It provides highly dynamic and interactive graphics such as tours, as well as familiar graphics such as the scatterplot, barchart and parallel coordinates plots. Plots are interactive and linked with brushing and identification.
There's a tutorial that covers both of the above systems here.
RPy is a very simple, yet robust, Python interface to the R Programming Language. It can manage all kinds of R objects and can execute arbitrary R functions (including the graphic functions). All errors from the R language are converted to Python exceptions. Any module installed for the R system can be used from within Python.
You might want to look at outputting SVG with animation, in which case this question might interest you. I suspect the animation aspects will require a lot of work on your part. Another option is maybe visualizing the data as a graph, although I'm don't know enough about your data to know whether this would be useful to you. If it is, cytoscape is python scriptable
If all you want is an animated surface, then gnuplot can do it. A quick intro on it can be found here, or from the gnuplot FAQ. More detail can obviously be found in the gnuplot docs.
You could try guiqwt. It's aimed for 2D graphs, but targets more specifically interactive plots (as opposed to Matplotlib, although it can handle some degree of interaction too). From the guiqwt documentation:
Overview
Based on PyQwt (plotting widgets for PyQt4 graphical user interfaces)
and on the scientific modules NumPy and SciPy, guiqwt is a Python
library providing efficient 2D data-plotting features (curve/image
visualization and related tools) for interactive computing and
signal/image processing application development.
Performances
The most popular Python module for data plotting is currently
matplotlib, an open-source library providing a lot of plot types and
an API (the pylab interface) which is very close to MATLAB’s plotting
interface.
guiqwt plotting features are quite limited in terms of plot types
compared to matplotlib. However the currently implemented plot types
are much more efficient. For example, the guiqwt image showing
function (guiqwt.pyplot.imshow()) do not make any copy of the
displayed data, hence allowing to show images which are much larger
than with its matplotlib‘s counterpart. In other terms, when showing a
30-MB image (16-bits unsigned integers for example) with guiqwt, no
additional memory is wasted to display the image (except for the
offscreen image of course which depends on the window size) whereas
matplotlib takes more than 600-MB of additional memory (the original
array is duplicated four times using 64-bits float data types).
(I haven't tried it, so I can't comment on these claims.)
Okay, now that I understand your data I can definitely suggest a method of visualisation. A coloured 3D surface density plot. Use a0, a1 and a2 as standard x,y,z axes, use a3 as the time axis, and plot different colours over a monochromatic range (or cold to hot). That way the only thing that needs an interactive slider is a3.
As far as tools to do this are concerned
I don't know whether gnuplot can do colour density plots, if it can this is your best bet. Generate an set of gifs across domain of a3, use imagemagick to make a single animated gif out of them, then use an animated .gif editor that allows you to move back and forth between frames
Again, with matplotlib, I'm not certain whether it is possible to do colour density plots
SVG can definitely do everything you need to do, including the animation aspects, but as I've said before, is going to be a lot of hard work.
Sounds like Mayavi might fit your needs. It is written in Python, can be used interactively and supports 3D graphs and animations. You can have a look at this tutorial to see if it fits your needs.
I have done an interactive 3D visualization with animation in Python using the older version 1 of mayavi, see this page.
Edit
Unfortunately, most Mayavi examples show off too much advanced functionality. Here are two examples that demonstrate more basic applications. If these two do not fit your needs, then Mayavi may not be a good choice in your case. My understanding is that you have arrays of floats that you want to visualize.
Example 1
Here is a specific example from the older page on what you can do with a 3D array of floats: 3D data example. This example shows the use of isocontour surfaces, one solid cut plane through the data and another cut plane with isocontour lines. You can interactively move the cut planes around or choose different visualization tools. (In my case I had added another dimension and an animation that presented the data as 3D-cube slices through the hypercube.)
Example 2
Here is another example of what a more "conventional" plot with Mayavi could look like: Fourier transform example. This is quite similar to what the many other plotting libraries do.
Go download a free trial of Tableau (www.tableausofware.com). It will encode your data on X, Y, size, color and shape, and you can create small multiples any other dimensions you have -- i.e. you can look at lots of dimensions at once. You can try lots and lots of visualizations very rapidly. There is free training on the company website.
Disclaimer: I work for them.
The simplest visualization for 3+dimensions is bubble chart or motion chart. On top of the x and y axis you can use the bubble size and the bubble color for the extra dimensions.
Google visualization (http://code.google.com/apis/chart/interactive/docs/gallery/motionchart.html) and its google spreadsheet interactive mode give a simple interface to play with which of the dimensions is on which of the axis/size/color.
It is not aimed at handling too many data points, but you can use it to identify patterns on samples of the data with ease.
I have a 3d model that consists of points, lines and balls in space. For debugging, it would be nice to render these objects in real time and rotateable.
What are my easiest options to achieve this in python?
Since I know nothing about graphical programming, I'd like to write as litte boilerplate code as possible.
The easiest way to get 3d graphics on screen in python is VPython, though if your model is stored in a CAD file format, you'll need some other library to load the data. With just VPython, you will either need to hard-code the model or implement your own loader.
Two options I'd consider myself (depends what you're trying to do in the end):
Blender has fairly amazing Python integration. Simple example here. As I understand it, Blender's own file save format is executable python which prods the Blender Python API to reconstruct the scene. There's also a mechanism for introducing gamey logic into the Blender world but I know even little about it. Blender does have a crazy steep learning curve though.
Get into OpenGL using the Python OpenGL bindings. "Simple" example.
If you're more interested in creating the models, go with the former; if you're more interested in the rendering of them, go with the latter.
The first thing that springs to mind is processing which is an easy to use visualization toolkit. Although you actually implement your visualizations in java, a quick google found this which lets you write your sketches in python instead.