Search Results for "numpy"
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Showing 150 open source projects for "numpy"
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NumPy
The fundamental package for scientific computing with Python
...Nearly every scientist working in Python draws on the power of NumPy. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. -
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Awkward Array
Manipulate JSON-like data with NumPy-like idioms
Awkward Array is a library for nested, variable-sized data, including arbitrary-length lists, records, mixed types, and missing data, using NumPy-like idioms. Arrays are dynamically typed, but operations on them are compiled and fast. Their behavior coincides with NumPy when array dimensions are regular and generalizes when they're not. -
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CuPy
A NumPy-compatible array library accelerated by CUDA
...CuPy is highly compatible with NumPy, serving as a drop-in replacement in most cases. CuPy is very easy to install through pip or through precompiled binary packages called wheels for recommended environments. It also makes writing a custom CUDA kernel very easy, requiring only a small code snippet of C++. -
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Numba
NumPy aware dynamic Python compiler using LLVM
...Just apply one of the Numba decorators to your Python function, and Numba does the rest. Numba is designed to be used with NumPy arrays and functions. Numba generates specialized code for different array data types and layouts to optimize performance. Special decorators can create universal functions that broadcast over NumPy arrays just like NumPy functions do. Numba also works great with Jupyter notebooks for interactive computing, and with distributed execution frameworks, like Dask and Spark. -
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Pyodide
Pyodide is a Python distribution for the browser and Node.js
Pyodide brings the Python runtime to the browser by compiling Python and its scientific libraries to WebAssembly. It allows developers to run Python code directly in web browsers without a server, supporting packages like NumPy, Pandas, and Matplotlib. Pyodide opens up new possibilities for interactive data analysis, scientific computing, and educational tools in web environments, all while integrating seamlessly with JavaScript. -
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Librosa
Python library for audio and music analysis
Librosa is a powerful Python library for analyzing and processing audio and music signals. Built on top of NumPy, SciPy, and matplotlib, it provides a wide range of tools for feature extraction, time-series manipulation, audio display, and music information retrieval. Whether you're building machine learning models for audio classification or visualizing spectrograms, Librosa is a go-to library for researchers and developers working in audio signal processing. -
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scikit-image
Image processing in Python
scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction. We pride ourselves on high-quality, peer-reviewed code, written by an active community of volunteers. scikit-image builds on scipy.ndimage to provide a versatile set of image processing routines in Python. This library is developed by its community, and contributions are most welcome! Read about our mission, vision, and values and how we govern the project. Major proposals... -
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PyVista
3D plotting and mesh analysis through a streamlined interface
...Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. Direct access to mesh analysis and transformation routines. Intuitive plotting routines with matplotlib similar syntax. -
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TensorLy
Tensor Learning in Python
TensorLy is a Python library that aims at making tensor learning simple and accessible. It allows to easily perform tensor decomposition, tensor learning and tensor algebra. Its backend system allows to seamlessly perform computation with NumPy, PyTorch, JAX, TensorFlow, CuPy or Paddle, and run methods at scale on CPU or GPU. -
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PyMC
Bayesian Modeling and Probabilistic Programming in Python
PyMC is a Python library for probabilistic programming focused on Bayesian statistical modeling and machine learning. Built on top of computational tools like Aesara and NumPy, PyMC allows users to define models using intuitive syntax and perform inference using MCMC, variational inference, and other advanced algorithms. It’s widely used in scientific research, data science, and decision modeling. -
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MiniSom
MiniSom is a minimalistic implementation of the Self Organizing Maps
...The project initially aimed for a minimalistic implementation of the Self-Organizing Map (SOM) algorithm, focusing on simplicity in features, dependencies, and code style. Although it has expanded in terms of features, it remains minimalistic by relying only on the numpy library and emphasizing vectorization in coding style. -
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PyAV
Pythonic bindings for FFmpeg's libraries
...The library is designed for precise media manipulation, making it suitable for applications that require frame-level access or custom processing pipelines. PyAV integrates well with other Python libraries such as NumPy and Pillow, allowing seamless data transformation and analysis. It supports decoding, encoding, filtering, and resampling operations, covering a wide range of multimedia tasks. While powerful, it requires a solid understanding of FFmpeg concepts, as it prioritizes flexibility and control over abstraction. Overall, PyAV is a robust tool for developers building advanced video and audio processing systems in Python. -
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Autograd
Efficiently computes derivatives of numpy code
Autograd can automatically differentiate native Python and Numpy code. It can handle a large subset of Python's features, including loops, ifs, recursion and closures, and it can even take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation), which means it can efficiently take gradients of scalar-valued functions with respect to array-valued arguments, as well as forward-mode differentiation, and the two can be composed arbitrarily. ... -
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Python for Data Analysis
Materials and IPython notebooks for "Python for Data Analysis"
...It contains the datasets, examples, and IPython notebooks used throughout the book. The repository helps readers practice Python data analysis concepts directly in Jupyter Notebook. Its chapters cover Python basics, NumPy, pandas, data loading, cleaning, wrangling, visualization, time series, modeling libraries, and full analysis examples. The project includes setup options using uv or Conda, with dependency files to reproduce the working environment. It is best suited for learners, analysts, and developers who want hands-on practice with the modern Python data stack. -
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Dask
Parallel computing with task scheduling
Dask is a Python library for parallel and distributed computing, designed to scale analytics workloads from single machines to large clusters. It integrates with familiar tools like NumPy, Pandas, and scikit-learn while enabling execution across cores or nodes with minimal code changes. Dask excels at handling large datasets that don’t fit into memory and is widely used in data science, machine learning, and big data pipelines. -
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PyOpenCL
OpenCL integration for Python, plus shiny features
...It enables developers to harness the full power of heterogeneous computing directly from Python, combining Python’s ease of use with the performance benefits of OpenCL. PyOpenCL also includes convenient features for managing memory, compiling kernels, and interfacing with NumPy, making it a preferred choice in scientific computing, data analysis, and machine learning workflows that demand acceleration. -
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SciPy
SciPy library main repository
...The SciPy library contains many of the user-friendly and efficient numerical routines, including those for numerical integration, interpolation, and optimization. SciPy is built to work with NumPy, a software that provides convenient and fast N-dimensional array manipulation. Both SciPy and NumPy run on all popular operating systems, are fast and easy to install, and are powerful yet easy to use. They’re currently depended upon by numerous leading scientists and engineers all over the world. Try them for yourself! -
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JAX
Composable transformations of Python+NumPy programs
With its updated version of Autograd, JAX can automatically differentiate native Python and NumPy functions. It can differentiate through loops, branches, recursion, and closures, and it can take derivatives of derivatives of derivatives. It supports reverse-mode differentiation (a.k.a. backpropagation) via grad as well as forward-mode differentiation, and the two can be composed arbitrarily to any order. What’s new is that JAX uses XLA to compile and run your NumPy programs on GPUs and TPUs. ... -
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word_cloud
A little word cloud generator in Python
A little word cloud generator in Python. The code is tested against Python 2.7, 3.4, 3.5, 3.6 and 3.7. If you are using conda, you can install from the conda-forge channel. wordcloud depends on numpy and pillow. To save the wordcloud into a file, matplotlib can also be installed. If there are no wheels available for your version of python, installing the package requires having a C compiler set up. Before installing a compiler, report an issue describing the version of python and operating system being used. The wordcloud_cli tool can be used to generate word clouds directly from the command-line. ... -
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scikit-learn
Machine learning in Python
scikit-learn is an open source Python module for machine learning built on NumPy, SciPy and matplotlib. It offers simple and efficient tools for predictive data analysis and is reusable in various contexts. -
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QuTiP
QuTiP: Quantum Toolbox in Python
QuTiP is open-source software for simulating the dynamics of open quantum systems. The QuTiP library depends on the excellent Numpy, Scipy, and Cython numerical packages. In addition, graphical output is provided by Matplotlib. QuTiP aims to provide user-friendly and efficient numerical simulations of a wide variety of Hamiltonians, including those with arbitrary time-dependence, commonly found in a wide range of physics applications such as quantum optics, trapped ions, superconducting circuits, and quantum nanomechanical resonators. ... -
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Deep Lake
Data Lake for Deep Learning. Build, manage, and query datasets
...Store images, audios and videos in their native compression. Deeplake automatically decompresses them to raw data only when needed, e.g., when training a model. Treat your cloud datasets as if they are a collection of NumPy arrays in your system's memory. Slice them, index them, or iterate through them. -
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tslearn
The machine learning toolkit for time series analysis in Python
The machine learning toolkit for time series analysis in Python. tslearn expects a time series dataset to be formatted as a 3D numpy array. The three dimensions correspond to the number of time series, the number of measurements per time series and the number of dimensions respectively (n_ts, max_sz, d). In order to get the data in the right format. -
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spyder
The scientific Python development environment
Spyder is a free and open source scientific environment written in Python, for Python, and designed by and for scientists, engineers and data analysts. It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. Spyder’s multi-language Editor integrates a number of powerful tools... -
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pytablewriter
pytablewriter is a Python library to write a table in various formats
pytablewriter is a Python library to write a table in various formats: AsciiDoc / CSV / Elasticsearch / HTML / JavaScript / JSON / LaTeX / LDJSON / LTSV / Markdown / MediaWiki / NumPy / Excel / Pandas / Python / reStructuredText / SQLite / TOML / TSV / YAML.
