Search Results for "python data analysis"
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Showing 169 open source projects for "python data analysis"
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EEGLAB
EEGLAB is an open source signal processing environment
EEGLAB is an open source, MATLAB-based interactive environment for analyzing electrophysiological signals such as EEG and MEG. It incorporates powerful tools for data import, preprocessing, independent component analysis (ICA), time-frequency analysis, artifact rejection, and visualization—all within a GUI framework that also supports scripting and plugin extensions. EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command line only for Octave). ... -
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FieldTrip
The MATLAB toolbox for MEG, EEG and iEEG analysis
...It supports the data formats of all major MEG systems (CTF, Neuromag/Elekta/Megin, BTi/4D, Yokogawa/Ricoh, FieldLine) and of most popular EEG systems, and new formats can be added easily. FieldTrip contains high-level functions that you can use to construct your own analysis protocols in MATLAB. Furthermore, it easily allows methods researchers to incorporate new methods for EEG/MEG analysis. -
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hctsa
Highly comparative time-series analysis
hctsa is a Matlab software package for running highly comparative time-series analysis. It extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix. -
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Peroxide
Rust numeric library with high performance and friendly syntax
Rust numeric library contains linear algebra, numerical analysis, statistics and machine learning tools with R, MATLAB, Python-like macros. Peroxide uses a 1D data structure to represent matrices, making it straightforward to integrate with BLAS (Basic Linear Algebra Subprograms). This means that Peroxide can guarantee excellent performance for linear algebraic computations by leveraging the optimized routines provided by BLAS. -
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
TIGRE is an open-source toolbox for fast and accurate 3D tomographic reconstruction for any geometry. Its focus is on iterative algorithms for improved image quality that have all been optimized to run on GPUs (including multi-GPUs) for improved speed. It combines the higher-level abstraction of MATLAB or Python with the performance of CUDA at a lower level in order to make it both fast and easy to use. TIGRE is free to download and distribute: use it, modify it, add to it, and share it. Our... -
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segyio
Fast Python library for SEGY files
Segyio is a small LGPL-licensed C library for easy interaction with SEG-Y and Seismic Unix formatted seismic data, with language bindings for Python and Matlab. Segyio is an attempt to create an easy-to-use, embeddable, community-oriented library for seismic applications. Features are added as they are needed; suggestions and contributions of all kinds are very welcome. -
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gramm
Gramm is a complete data visualization toolbox for Matlab
Gramm is a MATLAB toolbox that enables the rapid creation of complex, publication-quality figures. Its design philosophy focuses on a declarative approach, where users specify the desired end result, as opposed to the traditional imperative method involving for loops, if/else statements, etc. The MATLAB implementation of gramm is inspired by the "grammar of graphics" principles (Wilkinson 1999) and the ggplot2 library for R by Hadley Wickham. As a reference to this inspiration, gramm stands... -
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Veritas RIXS Analysis
Advanced data analysis for Veritas beamline at MAX IV
You can do advanced analysis using the raw data from RIXS .h5 file. It has several tabs using which you can do different types of analysis, thereby utilizing the full potential of the Veritas beamline. Some of the features in addition to standard RIXS data analysis are: - continuous and discrete RIXS maps, - RIXS spectromicroscopy, - radiation damage analysis, - Q calibrations. -
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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GMAT
General Mission Analysis Tool
The General Mission Analysis Tool (GMAT) is an open-source tool for space mission design and navigation. GMAT is developed by a team of NASA, private industry, and public and private contributors. The GMAT development team is pleased to announce the release of GMAT version R2026a. For a complete list of new features, compatibility changes, and bug fixes, see the R2026a Release Notes in the Users Guide. -
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MCM-ICM
Mathematical Contest resources
MCM-ICM is a curated archive of Outstanding Winner (“O-奖/特等奖”) solution papers from the Mathematical Contest in Modeling and the Interdisciplinary Contest in Modeling, spanning the early 2000s through recent years. The repository is organized by year, with per-year folders that collect the top-ranked reports and, in later years, additional materials such as problem statements or problem notes when available. It has evolved from a single-maintainer project into a collaborative effort, with... -
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JSONLab
JSONLab: compact, portable, robust JSON/binary-JSON encoder
JSONLab is a free and open-source JSON/UBJSON/MessagePack encoder and decoder written in the native MATLAB language. It can be used to convert a MATLAB data structure (array, struct, cell, struct array, cell array, and objects) into JSON/UBJSON/MessagePack formatted strings and files, or to parse a JSON/UBJSON/MessagePack file into MATLAB data structure. JSONLab supports nearly all versions of MATLAB and GNU Octave (a free MATLAB clone). The development of JSONLab is currently funded by the... -
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The Sound Description Interchange Format (SDIF) is an established standard for the interchange of sound descriptions and analysis data. This project provides libraries, SDIF (in C) and Easdif (in C++), tools, and wrappers to read and write SDIF files.
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AtomProbeLab
Matlab-based analysis of Atom Probe Data
A collection of scripts and functions for the analysis of atom probe tomography data. Currently, this includes: standard file operations, plotting mass spectra, mass spectra analysis and mass peak overlap solving. For more information see the Wiki: https://sourceforge.net/p/atomprobelab/wiki/Home/ Quick overview video: https://youtu.be/8rJHce7M5UU More in-depth video using the APT school demos live script: https://www.youtube.com/watch? -
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MatCont
Numerical Bifurcation Analysis Toolbox in Matlab
...There is a manual with detailed descriptions of the data. -
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Eventer
Rapid, unbiased, reproducible analysis of synaptic events
...The software combines deconvolution for detection, and variable length template matching approaches for screening out false positive events. Eventer also includes a machine learning-based approach allowing users to train a model to implement their ‘expert’ selection criteria across data sets without bias. Sharing models allows users to implement consistent analysis procedures. The software is coded in MATLAB, but has been compiled as standalone applications for Windows, Mac and Linux. Please visit the official Eventer website for more info https://eventerneuro.netlify.app/ While the paper is in preparation, please cite as; Winchester, G., Liu, S., Steele, O.G., Aziz, W. and Penn, A.C. (2020) Eventer. ... -
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BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.
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Software developed for the analysis of Neutron Reflectivity data.
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NeuroJSON
Scalable, searchable and verifiable neuroimaging data exchange platfor
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
FEATool Multiphysics (https://www.featool.com) is a fully integrated toolbox for computer aided engineering CAE, finite element analysis & fluid dynamics simulations. With a very easy-to-use GUI, anyone is now able to quickly set up and perform large scale dynamical and complex engineering physics simulations, with coupled fluid flow, heat transfer, structural mechanics, chemical transport, and electromagnetics effects, without having to learn complex programming. -
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PROPER Optical Propagation Library
Routines for wavefront propagation in IDL, Matlab, and Python
...It was developed at the Jet Propulsion Laboratory for modeling stellar coronagraphs, but it can be applied to other optical systems were diffraction propagation is of concern. It is currently available for IDL (Interactive Data Language), Matlab and Python (3.x). It includes routines for generating complex apertures and obscurations and aberrations (Zernike & PSD-defined). It includes a model of a deformable mirror for wavefront control. The routines perform near and far field propagation with automatic selection of propagators. The latest version is v3.3.1 (IDL & Matlab) and v3.3.4 (Python). ... -
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CometAnalyser
CometAnalyser, for quantitative comet assay analysis.
Description: Comet assay provides an easy solution to estimate DNA damage in single cells through microscopy assessment. To obtain reproducible and reliable quantitative data, we developed an easy-to-use tool named CometAnalyser. CometAnalyser is an open-source deep-learning tool designed for the analysis of both fluorescent and silver-stained wide-field microscopy images. Once the comets are segmented and classified, several intensity/morphological features are automatically exported as a spreadsheet file. ... -
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SpectraViever
GUI app to view Veritas, MAX IV data
Data visualization, generate metadata log files, save spectra in .txt format for further advanced analysis. -
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The Multivariate Regression Composer, a Matlab toolbox. It generates a regression model of the optimal structure. Uses the source data set, the initial models and the primitive functions.
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The auditory modeling toolbox (AMT) is a Matlab/Octave toolbox for the development and application of auditory computational models. Over 50 auditory models implemented in Matlab, Octave, C, C++, and Python can be run from Matlab and Octave, on Windows and Linux. The AMT provides a well-structured in-code documentation, includes auditory data required to run the models. It integrates functionality to reproduce the model predictions. Model implementations can be evaluated in two stages, by running so-called demonstrations which are quick presentations of a model and by starting so-called experiments aimed at reproducing results from the corresponding publications. ...
