Showing 6 open source projects for "python mini project"

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  • 1
    PI-Based Image Encoder / Converter

    PI-Based Image Encoder / Converter

    Python code able to convert / compress image to PI (3.14, π) Indexes

    ...Features high-performance Numba-accelerated search and a signature 'film-grain' aesthetic upon reconstruction. ZIP also include 16 MB file with 16,7 mil numbers of PI Benchmark(Single-Thread): Hardware & Environment Apple Silicon: Apple M2 (Mac mini/MacBook) x86_64 Platform: Intel Core Ultra 5 225F (Arrow Lake, 10 Cores) OS 1: Fedora 43 (GNOME) OS 2: Windows 11 Pro (23H2/24H2) Software: Python 3.14.3 + Numba JIT (latest) Results (Lower is better) Platform / OS CPU Time (Seconds) macOS (Native) Apple M2 52.151311 s (in default setup) Fedora Linux Intel Core Ultra 5 225F 58.536457 s (in default Power Management: Balanced) Windows 11 Intel Core Ultra 5 225F 59.681427 s (important! ...
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  • 2
    jHepWork

    jHepWork

    jHepWork was a name of the DataMelt program in 2005-20013

    jHepWork (2005-2013) was an environment for scientific computation, data analysis and data visualization for scientists, engineers and students. The program is fully multiplatform (100% Java) and integrated with the Jython (Python) scripting language. Currently the project is known under the name DataMelt (https://datamelt.org)
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  • 3
    This project contains applications which allow the user the draw the common geometry graphics (both 2D and 3D) which is available from the library.
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  • 4
    The Wolfram Machine project is an effort to create a set of documentation and useful modules (both hardware and software) for a computing architecture based on the mathematical theories presented in Steven Wolfram's book _A_New_Kind_of_Science_.
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  • 5
    Project VDW serves as a repository for all things pertaining to Van Der Waerden sequences. Volunteers to run the distributed client, mathematicians to help with theory, and anyone interested in VDW sequences are welcome!
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  • 6
    This project collect several data mining methods, such as: 1) clustering methods; 2) biclustering methods; 3) FCA methods and etc.
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