matplotlib-cpp
Numba
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matplotlib-cpp | Numba | |
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10 | 124 | |
4,173 | 9,452 | |
- | 1.8% | |
0.0 | 9.9 | |
5 months ago | 3 days ago | |
C++ | Python | |
MIT License | BSD 2-clause "Simplified" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
matplotlib-cpp
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Any user of Matplotlibcpp here? Need some help with updating plots
The library (matplotlibcpp) on GitHub
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C++ DSP Tools
I am aware of this excellent matplotlib C++ wrapper. Are there any C/C++ tools similar to scipy.signals? I currently use the python tools to generate header files and can translate algorithms to C++, but I would like a more direct well to develop in C++.
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Matplotlib-cpp install in Visual Studio???
I want to plot graphs in C++ with matplotlib-cpp (https://github.com/lava/matplotlib-cpp). But I dont know how to install it in Visual Studio. I followed the instruction on website. But I got Errors like 'Python.h not found' ...
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I want to make a program that draws a graphical function to a png and I don't know how.
If you want it to be as simple as possible I’d recommend this matplotlib wrapper
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C++ plotting library for Windows + MinGW similar to matplotlib in Python?
THere is also this one, which is header only, so it's much simpler to install https://github.com/lava/matplotlib-cpp
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Is there an efficient way to give parameters to a non-Python script and get a return value to use back in Python?
There's actually a wrapper for matplotlib for cpp https://github.com/lava/matplotlib-cpp, so it's more or less doing exactly what you asked. Cpp doing all the heavy lifting, then matplotlib making the graphs.
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How to plot graphs in C++
There's matplotlib-cpp if you want to use the same kind of interface as with python.
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Best scientific graphing library?
or https://github.com/lava/matplotlib-cpp
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(Clion, macOS, arm64) What is the "easiest" way of plotting 2D graphs that can be added to already finished project?
well I usually use Python's matplotlib to do the plottings. It was the easiest I think. Before that, I attempted this library, which is a somewhat wrapper for C++: https://github.com/lava/matplotlib-cpp
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Which Plotting Libraryheaderframework Do You
Since you mentioned it, there is a wrapper for matplotlib: https://github.com/lava/matplotlib-cpp
Numba
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Mojo🔥: Head -to-Head with Python and Numba
Around the same time, I discovered Numba and was fascinated by how easily it could bring huge performance improvements to Python code.
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Is anyone using PyPy for real work?
Simulations are, at least in my experience, numba’s [0] wheelhouse.
[0]: https://numba.pydata.org/
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Any data folks coding C++ and Java? If so, why did you leave Python?
That's very cool. Numba introduces just-in-time compilation to Python via decorators and its sole reason for being is to turn everything it can into abstract syntax trees.
- Using Matplotlib with Numba to accelerate code
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Python Algotrading with Machine Learning
A super-fast backtesting engine built in NumPy and accelerated with Numba.
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PYTHON vs OCTAVE for Matlab alternative
Regarding speed, I don't agree this is a good argument against Python. For example, it seems no one here has yet mentioned numba, a Python JIT compiler. With a simple decorator you can compile a function to machine code with speeds on par with C. Numba also allows you to easily write cuda kernels for GPU computation. I've never had to drop down to writing C or C++ to write fast and performant Python code that does computationally demanding tasks thanks to numba.
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Codon: Python Compiler
Just for reference,
* Nuitka[0] "is a Python compiler written in Python. It's fully compatible with Python 2.6, 2.7, 3.4, 3.5, 3.6, 3.7, 3.8, 3.9, 3.10, and 3.11."
* Pypy[1] "is a replacement for CPython" with builtin optimizations such as on the fly JIT compiles.
* Cython[2] "is an optimising static compiler for both the Python programming language and the extended Cython programming language... makes writing C extensions for Python as easy as Python itself."
* Numba[3] "is an open source JIT compiler that translates a subset of Python and NumPy code into fast machine code."
* Pyston[4] "is a performance-optimizing JIT for Python, and is drop-in compatible with ... CPython 3.8.12"
[0] https://github.com/Nuitka/Nuitka
[1] https://www.pypy.org/
[2] https://cython.org/
[3] https://numba.pydata.org/
[4] https://github.com/pyston/pyston
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This new programming language has the potential to make python (the dominant language for AI) run 35,000X faster.
For the benefit of future readers: https://numba.pydata.org/
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Two-tier programming language
Taichi (similar to numba) is a python library that allows you to write high speed code within python. So your program consists of slow python that gets interpreted regularly, and fast python (fully type annotated and restricted to a subset of the language) that gets parallellized and jitted for CPU or GPU. And you can mix the two within the same source file.
- Numba Supports Python 3.11
What are some alternatives?
matplotplusplus - Matplot++: A C++ Graphics Library for Data Visualization 📊🗾
NetworkX - Network Analysis in Python
plotly - The interactive graphing library for Python :sparkles: This project now includes Plotly Express!
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
feedgnuplot - Tool to plot realtime and stored data from the commandline, using gnuplot.
Dask - Parallel computing with task scheduling
Pangolin - Pangolin is a lightweight portable rapid development library for managing OpenGL display / interaction and abstracting video input.
cupy - NumPy & SciPy for GPU
matplotlib - C++ wrappers around python's matplotlib
Pyjion - Pyjion - A JIT for Python based upon CoreCLR
implot - Immediate Mode Plotting
SymPy - A computer algebra system written in pure Python