XPost: comp.lang.c++   
   From: lynnmcguire5@gmail.com   
      
   On 2/4/2026 7:54 AM, Chris Ahlstrom wrote:   
   > Lawrence D’Oliveiro wrote this post by blinking in Morse code:   
   >   
   >> On Tue, 3 Feb 2026 20:17:04 -0600, Lynn McGuire wrote:   
   >>   
   >>> On 2/3/2026 6:14 PM, Lawrence D’Oliveiro wrote:   
   >>>>   
   >>>> On Tue, 3 Feb 2026 17:28:35 -0600, Lynn McGuire wrote:   
   >>>>   
   >>>>> I am swinging huge datasets for simulation models from 1 MB to   
   >>>>> 1,000 MB. Nothing besides C++ has the oomph and speed to make this   
   >>>>> happen.   
   >>>>   
   >>>> Lots of Pythoneers are doing data science at this sort of scale.   
   >>>   
   >>> Been there, done that. I really doubt that any Python apps are doing   
   >>> the level of what I do. I would be careful telling people that   
   >>> Python apps run anywhere near the speed of C++.   
   >>   
   >> Python has number-crunching engines like NumPy to do the grunt work.   
   >> The question is, how long does the overall job take: the C++ code may   
   >> run a bit faster, but it takes several times longer to write.   
   >   
   > Bullshit.   
   >   
   >> You can   
   >> get a lot of analyses done in that time in Python. Particularly since   
   >> it is very easy to experiment with just a few lines of code, before   
   >> committing yourself to more elaborate analyses along particular lines.   
   >   
   > You can   
   > do that in any language.   
   >   
   >> And then you have access to visualization tools like Matplotlib to   
   >> view the results. And again, it is much quicker to generate displays   
   >> from that in Python than it would be to write C++ code.   
   >   
   > AI Overview   
   >   
   >      Several C++ plotting libraries are available, ranging from   
   >      simple, header-only solutions to comprehensive, feature-rich   
   >      systems. Key options include general-purpose libraries,   
   >      wrappers for existing tools, and those designed for real-time   
   >      visualization.   
   >   
   >      Here are some popular C++ plotting libraries:   
   >   
   >      Matplotlib-cpp: This is possibly the simplest C++ plotting   
   >      library, designed to mimic the API of the popular Python   
   >      matplotlib library. It is a header-only library that acts as a   
   >      C++ wrapper around the Python matplotlib backend, so a Python   
   >      installation is required at runtime.   
   >   
   >      Matplot++: A modern C++ graphics library that offers   
   >      interactive plotting and a compact syntax, supporting generic   
   >      backends including gnuplot and the web-optimized Bokeh. It   
   >      provides a wide range of plot categories suitable for   
   >      scientific data visualization.   
   >   
   >      sciplot: Another modern, header-only library that aims to make   
   >      plotting in C++ as easy as in higher-level languages like   
   >      Python. It uses gnuplot as a backend dependency at runtime to   
   >      generate high-quality graphs and requires a C++17 capable   
   >      compiler.   
   >   
   >      Gnuplot (via C++ interface): You can directly interface with   
   >      the standalone, classic plotting program gnuplot using   
   >      libraries like gnuplot-iostream or similar wrappers. This   
   >      approach leverages gnuplot's powerful, domain-specific   
   >      plotting language.   
   >   
   >      Qt Charts: If you are already building a cross-platform   
   >      desktop application using the Qt framework, the Qt Charts   
   >      module is a well-integrated option that provides robust   
   >      charting capabilities.   
   >   
   >      ImPlot: An extension for the popular Dear ImGui library, ideal   
   >      for integrating plots directly into performance-oriented,   
   >      real-time GUI applications, such as internal tools or game   
   >      development debugging interfaces.   
   >   
   >      Visualization Toolkit (VTK): A powerful open-source library   
   >      for 3D graphics, image processing, and visualization. It is a   
   >      comprehensive, low-level option best suited for complex   
   >      scientific visualization needs.   
      
   We use gnuplot to generate graphs in our software.   
      
   Lynn   
      
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