Search Results for "blu-ray"
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Showing 58 open source projects for "blu-ray"
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Ray
A unified framework for scalable computing
Modern workloads like deep learning and hyperparameter tuning are compute-intensive and require distributed or parallel execution. Ray makes it effortless to parallelize single machine code — go from a single CPU to multi-core, multi-GPU or multi-node with minimal code changes. Accelerate your PyTorch and Tensorflow workload with a more resource-efficient and flexible distributed execution framework powered by Ray. Accelerate your hyperparameter search workloads with Ray Tune. ... -
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AWS X-Ray SDK for Python
AWS X-Ray SDK for the Python programming language
...Oftentimes, it may be useful to be able to disable X-Ray for specific use cases, whether to stop X-Ray from sending traces at any moment or to test code functionality that originally depended on X-Ray instrumented packages to begin segments prior to the code call. For example, if your application relied on an XRayMiddleware to instrument incoming web requests, and you have a method that begins subsegments based on the segment generated. -
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fugue
A unified interface for distributed computing
Fugue is a unified interface for distributed computing that lets users execute Python, Pandas, and SQL code on Spark, Dask, and Ray with minimal rewrites. -
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Map-Anything
MapAnything: Universal Feed-Forward Metric 3D Reconstruction
...The model flexibly accepts different input combinations (images, intrinsics, poses, sparse or dense depth) and produces a rich set of outputs including per-pixel 3D points, camera intrinsics, camera poses, ray directions, confidence maps, and validity masks. Its inference path is fully feed-forward with optional mixed-precision and memory-efficient modes, making it practical to scale to long image sequences while keeping latency predictable. -
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NVIDIA Isaac Sim
NVIDIA Isaac Sim is an open-source application on NVIDIA Omniverse
...It supports a wide array of robotics formats (URDF, MJCF, CAD), includes GPU-accelerated physics, and features immersive RTX rendering and multisensory simulation. Realistic physics via GPU-accelerated engines and RTX ray tracing. Multi-sensor simulation (RGB-D cameras, Lidar, Radar, IMU, contact sensors). Extensible via platform APIs and can integrate into custom USD-based simulators. -
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Smallpond
A lightweight data processing framework built on DuckDB and 3FS
...The idea is to preserve DuckDB’s fast analytics engine but lift it from single-node to multi-node settings, giving you the ability to operate on large datasets (e.g. petabyte scale) without moving to a heavyweight system like Spark. Users write Python-like code (via DataFrame APIs or SQL strings) to express their transformations; behind the scenes, tasks are scheduled (often via Ray) and pushed into DuckDB instances operating on partitioned data. Because the storage layer (3FS) is optimized for random access and high throughput, smallpond can shuffle data, repartition, and manage intermediate results across nodes. -
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mlforecast
Scalable machine learning for time series forecasting
...It supports multi-series forecasting, meaning you can train one model that forecasts many time series at once (common in retail, demand forecasting, etc.), rather than one model per series. The library is built to scale: behind the scenes, it can leverage distributed computing frameworks (Spark, Dask, Ray) when datasets or the number of series grow large. -
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PyCaret
An open-source, low-code machine learning library in Python
...PyCaret is essentially a Python wrapper around several machine learning libraries and frameworks such as scikit-learn, XGBoost, LightGBM, CatBoost, Optuna, Hyperopt, Ray, and few more. The design and simplicity of PyCaret are inspired by the emerging role of citizen data scientists, a term first used by Gartner. Citizen Data Scientists are power users who can perform both simple and moderately sophisticated analytical tasks that would previously have required more technical expertise. -
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StatsForecast
Fast forecasting with statistical and econometric models
StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery... -
MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Modin
Scale your Pandas workflows by changing a single line of code
Scale your pandas workflow by changing a single line of code. Modin uses Ray, Dask or Unidist to provide an effortless way to speed up your pandas notebooks, scripts, and libraries. Unlike other distributed DataFrame libraries, Modin provides seamless integration and compatibility with existing pandas code. Even using the DataFrame constructor is identical. It is not necessary to know in advance the available hardware resources in order to use Modin. -
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AWS Serverless Application Model
An open-source framework for building serverless applications
The AWS Serverless Application Model (SAM) is an open-source framework for building serverless applications. It provides shorthand syntax to express functions, APIs, databases, and event source mappings. With just a few lines per resource, you can define the application you want and model it using YAML. During deployment, SAM transforms and expands the SAM syntax into AWS CloudFormation syntax, enabling you to build serverless applications faster. To get started with building SAM-based... -
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Matrix
Multi-Agent daTa geneRation Infra and eXperimentation framework
Matrix is a distributed, large-scale engine for multi-agent synthetic data generation and experiments: it provides the infrastructure to run thousands of “agentic” workflows concurrently (e.g. multiple LLMs interacting, reasoning, generating content, data-processing pipelines) by leveraging distributed computing (like Ray + cluster management). The idea is to treat data generation as a “data-to-data” transformation: each input item defines a task, and the runtime orchestrates asynchronous, peer-to-peer agent workflows, avoiding global synchronization bottlenecks. That design makes Matrix particularly well-suited for large-batch inference, model benchmarking, data curation, augmentation, or generation — whether for language, code, dialogue, or multimodal tasks. ... -
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GenX
X-Ray and Neutron Reflectivity Modeling
GenX is a scientific program to refine x-ray refelcetivity, neutron reflectivity and surface x-ray diffraction data using the differential evolution algorithm. GenX is very modular and highly extensible and can be used as a general fitting program. -
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Aviary
Ray Aviary - evaluate multiple LLMs easily
...Providing an extensive suite of pre-configured open source LLMs, with defaults that work out of the box. Supporting Transformer models hosted on Hugging Face Hub or present on local disk. Aviary has native support for autoscaling and multi-node deployments thanks to Ray and Ray Serve. Aviary can scale to zero and create new model replicas (each composed of multiple GPU workers) in response to demand. Ray ensures that the orchestration and resource management is handled automatically. Aviary is able to support hundreds of replicas and clusters of hundreds of nodes, deployed either in the cloud or on-prem. -
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Stand-alone application and Python tools for interactive and/or batch processing analysis of X-Ray Fluorescence Spectra. Graphical user interface (GUI) and batch processing capabilities provided.
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gVirtualXRay
Virtual X-Ray Imaging Library on GPU
gVirtualXRay is a C++ library to simulate X-ray imaging. It is based on the Beer-Lambert law to compute the absorption of light (i.e. photons) by 3D objects (here polygon meshes). It is implemented on the graphics processing unit (GPU) using the OpenGL Shading Language (GLSL). SimpleGVXR is a smaller library build on the top of gVirtualXRay. It provides wrappers to Python, R, Ruby, Tcl, C#, Java, and GNU Octave. -
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. ... -
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sidmon5.net
Sudden ionospheric disturbance monitor with Stokes data product
This package is a VLF receiver for monitoring VLF transmitter signals for evidence of transients indicating ionospheric disturbances, usually caused by x-ray bursts from the sun. It takes sample pairs from dual-channel sound cards and spectrally processes them to Stokes parameters. Data are plotted as time series and in scatter plots. -
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xrayutilities
a package with useful scripts for X-ray diffraction physicists
xrayutilities is a python package used to analyze x-ray diffraction data. It can support with performing diffraction experiments and used for common steps in the data analysis. It can read experimental data from several data formats (spec, edf, xrdml, ...); convert them to reciprocal space for arbitrary goniometer geometries and different detector systems (point, linear as well as area detectors); for further processing the data can be gridded (transformed to a regular grid). ... -
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KherveFitting
Fit X-ray Photoelectron Spectroscopy (XPS) and XAS data
KherveFitting is a full featured XPS, XAS and Raman fitting software for Windows & macOS that is simple and easy to use. KherveFitting can open Excel files (.xlsx) or import/convert .vms, .avg, .kal, .spe (Thermo, Kratos, Specs, Scienta, Omicron, Phi) files into Excel format. 5 background types available: Tougaard, Shirley, Smart, Adaptive Smart. Various peak fitting models: Product and Sum of Gaussian and Lorentzian (GL & SGL), Voigt, Asymmetric Lorentzian (LA), Doniac-Sunjic (G*DS) and... -
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Hero Planner
An easy to use GUI for creating team rotas and scheduling absences.
...Your Utility Belt: ✓ Super Speed: Intuitive drag-and-drop & bulk actions for lightning-fast updates. ✓ Compliance Shield: Real-time alerts guard against labour law violations and overtime risks. ✓ X-Ray Vision: Instantly visualize coverage gaps, conflicts, and staff availability. ✓ Universal Export: PDF, CSV, and HTML formats. ✓ Stealth Mode: Sleek Dark Mode & customizable themes. Built on Electron, React & Vite for blazing performance. Whether managing a small squad or a legion of 200+ staff, HERO Planner gives you the tools to save the day. ... -
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LLM Applications
A comprehensive guide to building RAG-based LLM applications
...It provides step-by-step guidance for constructing systems that ingest documents, split them into chunks, generate embeddings, index them in vector databases, and retrieve relevant context during inference. The repository also shows how these components can be scaled and deployed using distributed computing frameworks such as Ray. In addition to development workflows, the project includes notebooks, datasets, and evaluation tools that help developers experiment with different retrieval strategies and model configurations. -
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Alpa
Training and serving large-scale neural networks
Alpa is a system for training and serving large-scale neural networks. Scaling neural networks to hundreds of billions of parameters has enabled dramatic breakthroughs such as GPT-3, but training and serving these large-scale neural networks require complicated distributed system techniques. Alpa aims to automate large-scale distributed training and serving with just a few lines of code. -
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XRD CUBIC
Simulate crystal cell length (a), Miller indices {h, k, l}, d-spacing
This is a basic computer program (coded in Python) to simulate possible unit crystal cell length (a), Miller indices - {h, k, l} and interplanar spacing (d) for cubic crystals from observed (experimental) X-ray diffraction (XRD) angle, 2-theta. It can simulate all these possible crystal lattice parameters for cubic crystal systems between the given 2–theta values within the range of specified cell length (a) limits. 1. Enter wavelength of X-ray (in Angstroms) 2. Enter minimum and maximum diffraction angle as 2-theta (in Degrees) 3. ... -
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XISMuS
X-Ray Imaging Software for Multiple Samples
...IMPORTANT FIXES in respect to base v2.0.0 version: v.2.5.0 introduces the Differential Attenuation and Cube Viewer utilities, and migrates user database to *.json files v2.4.3 fixes a with K element in the fit-approx method v2.4.3 fixes and issue where saving plots with fit-approx or a auto-wizard could freeze the software v2.4.2 introduces Image Viewer to Mosaic v2.4.1 fixes an issue in merging H5 or EDF datasets with Mosaic Full changelog at https://linssab.github.io/history X-Ray Fluorescence Imaging Software for Multiple Samples is an open source software to manipulate and study macro-X-Ray Fluorescence (MA-XRF) datasets. XISMuS also works as a sample management tool, where you can easily change between datasets (samples) and compare, cross-interact and normalize them.
