Search Results for "python-gtksourceview2" - Page 2
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Showing 338 open source projects for "python-gtksourceview2"
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ConcurrentSim.jl
Discrete event process oriented simulation framework written in Julia
A discrete event process-oriented simulation framework written in Julia inspired by the Python library SimPy. One of the longest-lived Julia packages (originally under the name SimJulia). -
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GemGIS
Spatial data processing for geomodeling
GemGIS is a Python-based, open-source geographic information processing library. It is capable of preprocessing spatial data such as vector data (shape files, geojson files, geopackages,…), raster data (tif, png,…), data obtained from online services (WCS, WMS, WFS) or XML/KML files (soon). Preprocessed data can be stored in a dedicated Data Class to be passed to the geomodeling package GemPy in order to accelerate the model-building process. -
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BertViz
BertViz: Visualize Attention in NLP Models (BERT, GPT2, BART, etc.)
BertViz is an interactive tool for visualizing attention in Transformer language models such as BERT, GPT2, or T5. It can be run inside a Jupyter or Colab notebook through a simple Python API that supports most Huggingface models. BertViz extends the Tensor2Tensor visualization tool by Llion Jones, providing multiple views that each offer a unique lens into the attention mechanism. The head view visualizes attention for one or more attention heads in the same layer. It is based on the excellent Tensor2Tensor visualization tool. ... -
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Sweetviz
Visualize and compare datasets, target values and associations
Sweetviz is an open-source Python library that generates beautiful, high-density visualizations to kickstart EDA (Exploratory Data Analysis) with just two lines of code. Output is a fully self-contained HTML application. The system is built around quickly visualizing target values and comparing datasets. Its goal is to help quick analysis of target characteristics, training vs testing data, and other such data characterization tasks. -
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EllipsisNotation.jl
Julia-based implementation of ellipsis array indexing notation
Julia-based implementation of ellipsis array indexing notation. This implements the notation .. for indexing arrays. It's similar to Python, in that it means "all the columns before (or after)". Note: .. slurps dimensions greedily, meaning that the first occurrence of .. in an index expression creates as many slices as possible. Other instances of .. afterward are treated simply as slices. Usually, you should only use one instance of .. in an indexing expression to avoid possible confusion. -
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nb-clean
Clean Jupyter notebooks of outputs, metadata, and empty cells
...It provides both a Git filter and pre-commit hook to automatically clean notebooks before they're staged, and can also be used with other version control systems, as a command line tool, and as a Python library. It can determine if a notebook is clean or not, which can be used as a check in your continuous integration pipelines. nb-clean can also be used as a pre-commit hook. You may prefer this to the Git filter if your project already uses the pre-commit framework. Note that the Git filter and pre-commit hook work differently, with different effects on your working directory. ... -
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Run Page
Make your own running home page
GitHub Actions manages automatic synchronization of runs and generation of new pages. Gatsby-generated static pages, fast. Support for Vercel (recommended) and GitHub Pages automated deployment. React Hooks. Mapbox for map display. Supports most sports apps such as nike strava. Automatically backup gpx data for easy backup and uploading to other software. -
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classic.tplx
A more accurate representation of jupyter notebooks
A more accurate representation of Jupyter notebooks when converting to pdfs. This template was designed to make converted Jupyter notebooks look (almost) identical to the actual notebook. If something doesn't exist in the original notebook then it doesn't belong in the conversion. As of nbconvert 5.5.0, the majority of these improvements have been merged into nbconvert's default template. Version 3.x of this package will continue to support nbconvert 5.5.0 and lower, whereas in the future... -
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Perspective
A data visualization and analytics component
Perspective is a high-performance data visualization library for building real-time, interactive analytics dashboards. Developed by FINOS, it supports WebAssembly-powered pivot tables and can handle large streaming datasets with speed and flexibility. Perspective is ideal for fintech, trading, and IoT applications where insights from live data need to be visualized, sliced, and explored quickly in a browser. -
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TIGRE
TIGRE: Tomographic Iterative GPU-based Reconstruction Toolbox
...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 aim is to provide a wide range of easy-to-use algorithms for the tomographic community "off the shelf". We would like to build a stronger bridge between algorithm developers and imaging researchers/clinicians by encouraging and supporting contributions from both sides to TIGRE. -
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Bayesian Optimization
Python implementation of global optimization with gaussian processes
This is a constrained global optimization package built upon bayesian inference and gaussian process, that attempts to find the maximum value of an unknown function in as few iterations as possible. This technique is particularly suited for optimization of high cost functions, situations where the balance between exploration and exploitation is important. More detailed information, other advanced features, and tips on usage/implementation can be found in the examples folder. Follow the basic... -
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GoldenCheetah
Performance Software for Cyclists, Runners, Triathletes and Coaches
Analyze using summary metrics like BikeStress, TRIMP, or RPE. Extract insight via models like Critical Power and W'bal. Track and predict performance using models like Banister and PMC. Optimize aerodynamics using Virtual Elevation. Train indoors with ANT and BTLE trainers. Upload and Download with many cloud services including Strava, Withings, and Today's Plan. Import and export data to and from a wide range of bike computers and file formats. Track body measures, and equipment use and set... -
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Blueprint MCP
Diagram generation for understanding codebases and system architecture
Blueprint MCP is a modular control plane designed for managing and orchestrating multiple game-server clusters in real time, giving operators fine-grained control over scaling, configuration, and deployment workflows across distributed infrastructure. It provides a central management REST API and dashboard where teams can view cluster health, adjust instance fleets, set auto-scaling policies, and monitor usage metrics in a unified interface. Blueprint-MCP also supports templated server... -
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BetaML.jl
Beta Machine Learning Toolkit
The Beta Machine Learning Toolkit is a package including many algorithms and utilities to implement machine learning workflows in Julia, Python, R and any other language with a Julia binding. All models are implemented entirely in Julia and are hosted in the repository itself (i.e. they are not wrapper to third-party models). If your favorite option or model is missing, you can try to implement it yourself and open a pull request to share it (see the section Contribute below) or request its implementation. ... -
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The Julia Programming Language
High-level, high-performance dynamic language for technical computing
...Julia has more than 2,800 community-registered packages including various mathematical libraries, data manipulation tools, and packages for general purpose computing. Libraries from Python, R, C/Fortran, C++, and Java can also be used. -
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Briefer
Dashboards and notebooks in a single place
Briefer is an open-source collaborative data platform that brings notebooks, dashboards, and interactive data apps into a unified workspace that combines the flexibility of code with the simplicity of visual exploration. It’s designed so technical users can write Markdown, SQL, and Python side by side for data analysis, visualization, and reporting, while non-technical viewers can interact with results through inputs, dropdowns, and date pickers without writing any code. Users work in a Notion-style interface where they can build, organize, and share pages that contain executable code blocks, charts, text explanations, and interactive elements within the same document, enabling rich data storytelling and reproducible analytics. ... -
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electricityMap
A real-time visualisation of the CO2 emissions of electricity
Real-time visualization of the Greenhouse Gas (in terms of CO2 equivalent) footprint of electricity consumption built with d3.js and mapbox GL. Real-time data is defined as a data source with an hourly (or better) frequency, delayed by less than 2hrs. It should provide a breakdown by generation type. Often fossil fuel generation (coal/gas/oil) is combined under a single heading like 'thermal' or 'conventional', this is not a problem. Citizens should not be responsible for the emissions... -
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Digital Earth Australia notebooks
Repository for Digital Earth Australia Jupyter Notebooks
...Browse our catalog of data products to find supporting information and ways to access the data. The Digital Earth Australia notebooks and tools repository (dea-notebooks) hosts Jupyter Notebooks, Python scripts and workflows for analyzing Digital Earth Australia (DEA) satellite data and derived products. This documentation is designed to provide a guide to getting started with DEA, and to showcase the wide range of geospatial analyses that can be achieved using DEA data and open-source software including Open Data Cube and xarray. -
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ArviZ.jl
Exploratory analysis of Bayesian models with Julia
ArviZ.jl (pronounced "AR-vees") is a Julia package for exploratory analysis of Bayesian models. It includes functions for posterior analysis, model checking, comparison and diagnostics. -
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D-Tale
Visualizer for pandas data structures
D-Tale is the combination of a Flask backend and a React front-end to bring you an easy way to view & analyze Pandas data structures. It integrates seamlessly with ipython notebooks & python/ipython terminals. Currently, this tool supports such Pandas objects as DataFrame, Series, MultiIndex, DatetimeIndex & RangeIndex. D-Tale was the product of a SAS to Python conversion. What was originally a perl script wrapper on top of SAS's insight function is now a lightweight web client on top of Pandas data structures. To help guard against users loading the same data to D-Tale multiple times and thus eating up precious memory, we have a loose check for duplicate input data. ... -
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UnROOT.jl
Native Julia I/O package to work with CERN ROOT files objects
UnROOT.jl is a reader for the CERN ROOT file format written entirely in Julia, without any dependence on ROOT or Python. -
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OptimalTransport.jl
Optimal transport algorithms for Julia
This package provides some Julia implementations of algorithms for computational optimal transport, including the Earth-Mover's (Wasserstein) distance, Sinkhorn algorithm for entropically regularized optimal transport as well as some variants or extensions. Notably, OptimalTransport.jl provides GPU acceleration through CUDA.jl and NNlibCUDA.jl. -
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Sundials.jl
Julia interface to Sundials, including a nonlinear solver
This is a suite for numerically solving differential equations written in Julia and available for use in Julia, Python, and R. The purpose of this package is to supply efficient Julia implementations of solvers for various differential equations. -
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OpenCL.jl
OpenCL Julia bindings
Julia interface for the OpenCL parallel computation API. This package aims to be a complete solution for OpenCL programming in Julia, similar in scope to PyOpenCL for Python. It provides a high level API for OpenCL to make programing hardware accelerators, such as GPUs, FPGAs, and DSPs, as well as multicore CPUs much less onerous. -
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CounterfactualExplanations.jl
A package for Counterfactual Explanations and Algorithmic Recourse
...While the package is written purely in Julia, it can be used to explain machine learning algorithms developed and trained in other popular programming languages like Python and R. See below for a short introduction and other resources or dive straight into the docs.