matplotplusplus
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matplotplusplus | cheatsheets | |
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26 | 126 | |
3,925 | 7,235 | |
- | 0.6% | |
6.5 | 7.1 | |
16 days ago | 14 days ago | |
C++ | Python | |
MIT License | BSD 2-clause "Simplified" License |
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matplotplusplus
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Creating k-NN with C++ (from Scratch)
cmake_minimum_required(VERSION 3.5) project(knn_cpp CXX) # Set up C++ version and properties include(CheckIncludeFileCXX) check_include_file_cxx(any HAS_ANY) check_include_file_cxx(string_view HAS_STRING_VIEW) check_include_file_cxx(coroutine HAS_COROUTINE) set(CMAKE_CXX_STANDARD 20) set(CMAKE_BUILD_TYPE Debug) set(CMAKE_CXX_STANDARD_REQUIRED ON) set(CMAKE_CXX_EXTENSIONS OFF) # Copy data file to build directory file(COPY ${CMAKE_CURRENT_SOURCE_DIR}/iris.data DESTINATION ${CMAKE_CURRENT_BINARY_DIR}) # Download library usinng FetchContent include(FetchContent) FetchContent_Declare(matplotplusplus GIT_REPOSITORY https://github.com/alandefreitas/matplotplusplus GIT_TAG origin/master) FetchContent_GetProperties(matplotplusplus) if(NOT matplotplusplus_POPULATED) FetchContent_Populate(matplotplusplus) add_subdirectory(${matplotplusplus_SOURCE_DIR} ${matplotplusplus_BINARY_DIR} EXCLUDE_FROM_ALL) endif() FetchContent_Declare( fmt GIT_REPOSITORY https://github.com/fmtlib/fmt.git GIT_TAG 7.1.3 # Adjust the version as needed ) FetchContent_MakeAvailable(fmt) # Add executable and link project libraries and folders add_executable(${PROJECT_NAME} main.cc) target_link_libraries(${PROJECT_NAME} PUBLIC matplot fmt::fmt) aux_source_directory(lib LIB_SRC) target_include_directories(${PROJECT_NAME} PRIVATE ${CMAKE_CURRENT_SOURCE_DIR}) target_sources(${PROJECT_NAME} PRIVATE ${LIB_SRC}) add_subdirectory(tests)
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Help making plot for experiment
If you want a C++ solution you can use a library like matplot++.
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Widely-used graphics library
If you want a strict C++ equivalent to SDL the clear answer is SFML. If you just want to visualize 2D/3D data there's matplot++. If you want something slightly higher-level than SDL/SFML (with pre-made UI widgets and such) there's imGUI. If you need an all-in-one GUI solution for desktop or mobile apps there's Qt.
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Embedding matplotlibcpp plot into QT QWidget
If not, then ditch Python and matplotlib and use a different C++ native plotting framework such as matplot++
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Best Library to Visualize Mathematical Concepts
The best way to visualize most mathematical concepts is by plotting a 2D graph. To do that you can use e.g. Matplot++
- Update on C++ DataFrame project
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How to implement Matplotlib in C++
If you just want to plot graphs in C++ check out https://alandefreitas.github.io/matplotplusplus/. There is extensive documentation on how to use it. But if you haven't used a library before you should start here:
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2D Animation for algorithms
Using a 3rd party UI library, you certainly can. E.g. with MatPlot++
- I want to make a program that draws a graphical function to a png and I don't know how.
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C++ plotting library for Windows + MinGW similar to matplotlib in Python?
Maybe Matplot++ is the solution. You can check more info in https://github.com/alandefreitas/matplotplusplus
cheatsheets
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Mastering Matplotlib: A Step-by-Step Tutorial for Beginners
Matplotlib - A Python 2D plotting library.
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How to retrieve and analyze crypto order book data using Python and a cryptocurrency API
Data visualization: utilizing Python's Matplotlib for visualizing order book information.
- Matplotlib
- Ask HN: What plotting tools should I invest in learning?
- Help with an array
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Getting visual studio code to work with imported library
Name: matplotlib Version: 3.7.1 Summary: Python plotting package Home-page: https://matplotlib.org Author: John D. Hunter, Michael Droettboom Author-email: [email protected] License: PSFLocation: /home/huinker/.local/lib/python3.10/site-packages
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PSA: You don't need fancy stuff to do good work.
Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses without relying on expensive or proprietary software.
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What else should I complete before applying for a data analyst role?
programming language: basic python, pandas, matplotlib -- you'll probably do these in school, but if not https://cs50.harvard.edu/python/2022/ https://matplotlib.org/
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[OC] Analyzing 15,963 Job Listings to Uncover the Top Skills for Data Analysts (update)
Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.
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[OC] Data Analyst Skills in need based on 15,963 job listings
Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.
What are some alternatives?
matplotlib - C++ wrappers around python's matplotlib
finplot - Performant and effortless finance plotting for Python
matplotlib-cpp - Extremely simple yet powerful header-only C++ plotting library built on the popular matplotlib
manim - A community-maintained Python framework for creating mathematical animations.
implot - Immediate Mode Plotting
Fast-F1 - FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry
manim - Animation engine for explanatory math videos
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
volbx - Graphical tool for data manipulation written in C++/Qt.
Keras - Deep Learning for humans
bauh - Graphical user interface for managing your Linux applications. Supports AppImage, Debian and Arch packages (including AUR), Flatpak, Snap and native Web applications
geogebra - GeoGebra apps (mirror)