23 open-source projects similar to mne-tools/mne-python, ranked by how many features they have in common. Compare stars, activity and what each one does to find the best Mne Python alternative.
CuPy is a CUDA array computing library that implements a NumPy-compatible interface for executing array operations and numerical computing on NVIDIA GPUs. It serves as a GPU-accelerated numerical library and a CUDA-based SciPy implementation, offloading heavy calculations to graphics hardware to increase processing speed for scientific and engineering workloads. The library enables multi-framework tensor exchange, allowing data buffers to be shared between different deep learning frameworks using standardized memory layouts to avoid memory copies. It also supports custom GPU kernel integratio
PyQtGraph is a scientific plotting and graphics framework built for PyQt and PySide applications, providing fast, interactive 2D and 3D visualizations with GPU-accelerated rendering. It serves as both a real-time signal monitoring system for streaming time-series data and a toolkit for constructing interactive data dashboards with dockable panels, parameter trees, and custom widgets. The library also includes a node-based visual flowchart tool for building data processing pipelines and a scientific graphics export system that saves plots as PNG, SVG, or CSV and converts items to Matplotlib for
pybind11 is a header-only C++ binding library that exposes C++ functions and classes as Python modules. It serves as a language bridge, mapping native types, inheritance hierarchies, and lambda functions into compatible Python objects to enable high-performance native code execution. The library includes specialized integration for NumPy arrays, utilizing buffer protocols to bind native C++ data without copying memory. It provides a toolkit for mapping C++ standard library data structures and smart pointers into the Python environment while maintaining cross-language memory management. The p
This project is a Python wrapper for the TA-Lib C library, serving as a financial technical analysis library and quantitative trading tool. It provides a collection of mathematical functions designed to analyze market price movements, identify trading signals, and recognize candlestick patterns within financial data. The library focuses on the computation of trend, momentum, and volume metrics. It includes specialized tools for candlestick pattern recognition to detect recurring price action shapes in both historical and real-time data. The system integrates with NumPy arrays to process cont
PHPExcel is a PHP spreadsheet library used for programmatically reading and writing spreadsheet files in various formats. It utilizes an in-memory spreadsheet model that maps spreadsheet structures to a hierarchy of objects for programmatic manipulation. The library functions as an Office Open XML processor for generating and manipulating XLSX documents and serves as a reader for extracting data and structure from legacy binary XLS files. It also includes tools for CSV data integration and importing. The project provides capabilities for automated report generation and spreadsheet data extra
pybroker is a Python algorithmic trading framework and quantitative technical analysis library designed for developing, testing, and optimizing trading strategies using historical market data. It functions as a trading strategy backtester and a financial performance evaluator, providing a structured environment to simulate trading rules and analyze their statistical reliability. The framework distinguishes itself through a market data integration layer that handles the fetching and caching of historical price data from external providers. It incorporates an event-driven backtesting engine and
Xarray is a Python multidimensional array library and labeled dataset framework. It extends the NumPy data structure by adding labels to arrays, allowing for the organization of complex N-dimensional data using named dimensions and coordinates. The library provides a NetCDF data interface for reading and writing scientific data formats such as NetCDF and Zarr. It enables scientific array computing by maintaining the relationship between data and physical coordinates during mathematical operations. The project covers multidimensional data analysis, geospatial data manipulation, and climate da
Orange3 is a visual data mining platform that provides an interactive canvas for building data analysis workflows without writing code. At its core, it offers a widget-based visual programming environment where users connect configurable components to perform data preprocessing, machine learning model training, statistical evaluation, and interactive visualization. The platform is built on NumPy-backed data tables with domain descriptors that define variable names, types, and roles, and includes a lazy SQL query proxy for working with database tables without loading all data into memory. The
xtensor is a C++ multidimensional array library for numerical computing that provides N-dimensional containers with an interface mirroring the NumPy API. It utilizes a lazy evaluation expression engine to defer numerical computations until assignment, which minimizes memory allocations and intermediate copies. The library features a foreign memory array adaptor that allows it to wrap external buffers, such as NumPy arrays, to perform numerical operations in-place without duplicating data. It further optimizes performance through lazy broadcasting and a system that manages the lifetime of temp
pysheeet is a technical reference library providing a curated collection of code snippets and implementation patterns for advanced Python development, system integration, and high-performance computing. It serves as a comprehensive guide for implementing low-level network programming, native C extensions, and asynchronous and concurrent programming. The project provides specialized frameworks for the development and deployment of large language models, including tools for distributed GPU inference and high-performance serving. It also includes detailed patterns for high-performance computing
geemap is a Python library and toolkit for interactive geospatial analysis, visualization, and satellite imagery analysis using Google Earth Engine data and cloud computing. It provides a mapping tool for displaying geospatial datasets within Jupyter notebooks and a suite of tools for classifying imagery and calculating zonal statistics. The project includes a utility to convert geospatial analysis scripts from JavaScript into Python code to facilitate data manipulation. It also enables the generation of timelapse animations and time-series visualizations from satellite imagery catalogs. The
This project is a performance measurement framework and microbenchmarking library designed for C++ and Python. It provides a toolset for measuring the execution time of small code fragments using high-resolution timers, calculating statistical aggregates, and analyzing asymptotic complexity. The framework distinguishes itself through specialized capabilities for multithreaded performance testing, using synchronized execution to measure parallel throughput. It includes mechanisms to prevent compiler optimizations from removing benchmarked code and supports complex parameterization via Cartesia
DataFrame is a C++ tabular data library and manipulation engine designed for managing heterogeneous data in contiguous memory. It functions as a statistical analysis framework and time series analysis toolkit, providing the means to store, index, and transform multidimensional datasets. The project distinguishes itself through a high-performance execution model that utilizes column-major storage, SIMD-aligned memory allocation, and a thread-pool for parallel computations. It employs a visitor-based algorithm dispatch system and policy-driven transformations to decouple data processing logic f
Warp is a Python framework that JIT-compiles Python functions into CUDA kernels for GPU-accelerated parallel computation, with built-in automatic differentiation and multi-framework array interoperability. At its core, it provides a GPU kernel compilation system that enables writing and executing custom GPU kernels directly from Python, while supporting automatic gradient computation through those kernels for integration with machine learning pipelines. The framework also includes tile-based cooperative computing, where thread blocks partition into tiles for shared-memory and tensor-core opera
This project is a web-based log viewer and management interface designed specifically for Laravel applications. It serves as a centralized dashboard for browsing, searching, and managing system logs without requiring direct access to raw files or SSH. The system functions as a multi-host log aggregator, utilizing a remote proxy to view and index logs from multiple servers in one location. It includes a regular expression-based parser that interprets structured data from non-standard log files, allowing for custom log format definitions and severity level mapping. Broad capabilities include i
RecBole is a PyTorch-based recommendation framework designed for building, training, and evaluating a wide variety of recommendation algorithms. It serves as a standardized benchmark environment that allows for the comparison of different model architectures using public datasets and consistent evaluation metrics. The project provides specialized toolkits for sequential recommendation and knowledge-graph integration, enabling the prediction of item sequences based on user history or the incorporation of structured external knowledge. It includes a dedicated hyperparameter optimization engine
lmms-eval is a benchmarking system and performance analysis suite designed to measure the capabilities of large multimodal models. It provides a framework for evaluating models across text, image, audio, and video datasets, serving as a multimodal dataset orchestrator and benchmarking tool to quantify accuracy and efficiency. The project distinguishes itself through a unified multimodal message protocol that structures diverse media inputs for consistent model consumption. It features specialized benchmarking for audio, video, visual, document, and spatial reasoning, alongside tools for model
Einops is a tensor manipulation library that provides a framework-agnostic interface for reshaping, Einstein summation, and multi-dimensional array operations. It serves as an abstraction layer that works across NumPy, PyTorch, TensorFlow, and JAX, allowing for tensor transformations without changing the API. The library distinguishes itself through a declarative notation system that uses readable string patterns to describe tensor rearrangements and reductions. This approach includes an extended Einstein summation interface that supports multi-letter axis names and a named dimension mapping
dlt is a Python data ingestion tool and ETL pipeline framework designed to fetch data from diverse sources and persist it into structured destinations. It functions as a schema inference engine that automatically detects data types and flattens nested JSON structures into relational tables, moving data from sources to lakehouses, warehouses, or vector databases. The project distinguishes itself through AI-powered pipeline generation, using large language models to scaffold extraction code and connectors for REST APIs. It also supports multimodal vector storage and specialized population of ve
quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model
ExecuTorch is a lightweight C++ runtime for deploying PyTorch models on mobile, embedded, and edge hardware. It provides an ahead-of-time compilation pipeline that exports, quantizes, and lowers model graphs into compact serialized programs, then executes them through a minimal runtime with hardware acceleration and on-device large language model inference capabilities. The project distinguishes itself through a hardware accelerator delegate system that partitions model subgraphs and offloads computation to specialized backends including NPUs, GPUs, and DSPs from Apple, Arm, Intel, MediaTek,
AiNiee is an LLM-based localization tool that automates the translation of games, books, subtitles, and documents across multiple languages. It operates as a batch processing engine, translating entire folders of files in parallel while preserving directory structure, and includes a glossary management system that enforces terminology consistency using AI-powered glossaries, forbidden terms, and user-defined text substitution rules. The tool differentiates itself through key architectural decisions: it distributes translation requests across multiple API keys to bypass rate limits and acceler
pyAudioAnalysis is a Python library and framework for audio signal processing and analysis. It provides tools for extracting mathematical representations of sound, such as spectrograms, and implements a system for training and evaluating machine learning models to classify audio segments based on acoustic patterns. The project includes dedicated utilities for audio segmentation, which allow for the removal of silence and the detection of specific audio events to divide recordings into meaningful sections. It also provides data visualization capabilities that use dimensionality reduction to ma