Search Results for "source" - Page 16
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Showing 3246 open source projects for "source"
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Reduce.jl
Symbolic parser for Julia language term rewriting using REDUCE algebra
...It can be used interactively for simple calculations (as illustrated in the screenshot below) but also provides a full programming language, with a syntax similar to other modern programming languages. REDUCE supports alternative user interfaces including Run-REDUCE, TeXmacs and GNU Emacs. REDUCE (and its complete source code) is available free of charge for most common computing systems, in some cases in more than one version for the same machine. The manual and other support documents and tutorials are also included in the distributions. -
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DataQualityDashboard
A tool to help improve data quality standards in data science
The goal of the Data Quality Dashboard (DQD) project is to design and develop an open-source tool to expose and evaluate observational data quality. This package will run a series of data quality checks against an OMOP CDM instance (currently supports v5.4, v5.3 and v5.2). It systematically runs the checks, evaluates the checks against some pre-specified threshold, and then communicates what was done in a transparent and easily understandable way. -
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Koop
Transform, query, and download geospatial data on the web
..."Provider" plugins to connect to novel data formats and translate to a common format (GeoJSON), while "output" plugins then transform that GeoJSON to other specifications. See a list of plugins already authored and maintained here. If you have a novel data source or require an as-yet unsupported output format, new plugins can be easily developed and integrated. -
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Union Pandera
Light-weight, flexible, expressive statistical data testing library
The open-source framework for precision data testing for data scientists and ML engineers. Pandera provides a simple, flexible, and extensible data-testing framework for validating not only your data but also the functions that produce them. A simple, zero-configuration data testing framework for data scientists and ML engineers seeking correctness. -
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rudderstack
Privacy and Security focused Segment-alternative, in Golang
...Our 180+ integrations, along with custom webhook sources and destinations, save data teams hundred of hours. Say goodbye to different versions of the truth. Our SDKs track anonymous and known users at the source and reconcile users in your warehouse and SaaS tools. Go beyond event streaming and control all of your customer data on your own terms. Learn how we can help you build a customer data platform. RudderStack treats your data warehouse as a first-class citizen among destinations, with advanced features and configurable, near real-time sync. ... -
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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 associated with all the products they export, but only for what they consume. ... -
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Cassandra Spark Connector
Apache Spark to Apache Cassandra connector
The Apache Cassandra Spark Connector allows Spark jobs (RDDs or DataFrames/Datasets) to read from and write to Cassandra tables. Compatible with Apache Cassandra (v2.1+), Spark 1.0–3.5, and Scala 2.11–2.13, it supports mapping Cassandra rows to Scala case classes, saving results back to Cassandra, and executing arbitrary CQL within Spark applications. -
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miepython
Mie scattering of light by perfect spheres
miepython is a pure Python module to calculate light scattering for non-absorbing, partially-absorbing, or perfectly-conducting spheres. Mie theory is used, following the procedure described by Wiscombe. This code has been validated against his results. This code provides functions for calculating the extinction efficiency, scattering efficiency, backscattering, and scattering asymmetry. Moreover, a set of angles can be given to calculate the scattering for a sphere at each of those angles. -
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leafmap
A Python package for interactive mapping and geospatial analysis
...However, not everyone in the geospatial community has access to the GEE cloud computing platform. Leafmap is designed to fill this gap for non-GEE users. It is a free and open-source Python package that enables users to analyze and visualize geospatial data with minimal coding in a Jupyter environment, such as Google Colab, Jupyter Notebook, and JupyterLab. Leafmap is built upon several open-source packages, such as folium and ipyleaflet (for creating interactive maps), WhiteboxTools and whiteboxgui (for analyzing geospatial data), and ipywidgets (for designing interactive graphical user interface [GUI]). -
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ExponentialUtilities.jl
Fast and differentiable implementations of matrix exponentials
ExponentialUtilities is a package of utility functions for matrix functions of exponential type, including functionality for the matrix exponential and phi-functions. These methods are more numerically stable, generic (thus support a wider range of number types), and faster than the matrix exponentiation tools in Julia's Base. The tools are used by the exponential integrators in OrdinaryDiffEq. The package has no external dependencies, so it can also be used independently. -
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AppleAccelerate.jl
Julia interface to the macOS Accelerate framework
Julia interface to the macOS Accelerate framework. This provides a Julia interface to some of the macOS Accelerate frameworks. At the moment, this package provides access to Accelerate BLAS and LAPACK using the libblastrampoline framework, an interface to the array-oriented functions, which provide a vectorized form for many common mathematical functions. The performance is significantly better than using standard libm functions in some cases, though there does appear to be some reduced... -
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Braket.jl
Experimental Julia implementation of the Amazon Braket SDK
Braket.jl is not an officially supported AWS product. This package is a Julia implementation of the Amazon Braket SDK allowing customers to access Quantum Hardware and Simulators. This is experimental software, and support may be discontinued in the future. For a fully supported SDK, please use the Python SDK. We may change, remove, or deprecate parts of the API when making new releases. Please review the CHANGELOG for information about changes in each release. -
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GDAL.jl
Thin Julia wrapper for GDAL - Geospatial Data Abstraction Library
Julia wrapper for GDAL - Geospatial Data Abstraction Library. This package is a binding to the C API of GDAL/OGR. It provides only a C style usage, where resources must be closed manually, and datasets are pointers. Other packages can build on top of this to provide a more Julian user experience. See for example ArchGDAL.jl. Most users will want to use ArchGDAL.jl instead of using GDAL.jl directly. -
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JUDI.jl
Julia Devito inversion
JUDI is a framework for large-scale seismic modeling and inversion and is designed to enable rapid translations of algorithms to fast and efficient code that scales to industry-size 3D problems. The focus of the package lies on seismic modeling as well as PDE-constrained optimization such as full-waveform inversion (FWI) and imaging (LS-RTM). Wave equations in JUDI are solved with Devito, a Python domain-specific language for automated finite-difference (FD) computations. JUDI's modeling... -
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ScientificTypes.jl
An API for dispatching on the "scientific" type of data
This package makes a distinction between machine type and scientific type of a Julia object. The machine type refers to the Julia type being used to represent the object (for instance, Float64). The scientific type is one of the types defined in ScientificTypesBase.jl reflecting how the object should be interpreted (for instance, Continuous or Multiclass). -
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ConformalPrediction.jl
Predictive Uncertainty Quantification through Conformal Prediction
ConformalPrediction.jl is a package for Predictive Uncertainty Quantification (UQ) through Conformal Prediction (CP) in Julia. It is designed to work with supervised models trained in MLJ (Blaom et al. 2020). Conformal Prediction is easy-to-understand, easy-to-use and model-agnostic and it works under minimal distributional assumptions. Intuitively, CP works under the premise of turning heuristic notions of uncertainty into rigorous uncertainty estimates through repeated sampling or the use... -
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CBinding.jl
Automatic C interfacing for Julia
Use CBinding.jl to automatically create C library bindings with Julia at runtime. In order to support the fully automatic conversion and avoid name collisions, the names of C types or functions are mangled a bit to work in Julia. Therefore everything generated by CBinding.jl can be accessed with the c"..." string macro to indicate that it lives in C-land. As an example, the function func above is available in Julia as c"func". It is possible to store the generated bindings to more... -
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CausalityTools.jl
Algorithms for detecting associations, dynamical influences
CausalityTools.jl is a package for quantifying associations and dynamical coupling between datasets, independence testing, and causal inference. Association measures from conventional statistics, information theory, and dynamical systems theory, for example, distance correlation, mutual information, transfer entropy, convergent cross mapping and a lot more. A dedicated API for independence testing, which comes with automatic compatibility with every measure-estimator combination you can... -
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Compat.jl
Compatibility across Julia versions
The Compat package is designed to ease interoperability between older and newer versions of the Julia language. In particular, in cases where it is impossible to write code that works with both the latest Julia master branch and older Julia versions, or impossible to write code that doesn't generate a deprecation warning in some Julia version, the Compat package provides a macro that lets you use the latest syntax in a backward-compatible way. This is primarily intended for use by other... -
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NCDatasets.jl
Load and create NetCDF files in Julia
NCDatasets allows one to read and create netCDF files. NetCDF data set and attribute list behave like Julia dictionaries and variables like Julia arrays. This package implements the CommonDataModel.jl interface, which means that the datasets can be accessed in the same way as GRIB files opened with GRIBDatasets.jl. -
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GLFW.jl
Julia interface to GLFW, a multi-platform library for creating windows
Julia interface to GLFW 3, a multi-platform library for creating windows with OpenGL or OpenGL ES contexts and receiving many kinds of input. GLFW has native support for Windows, OS X and many Unix-like systems using the X Window System, such as Linux and FreeBSD. -
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SimpleTraits.jl
Simple Traits for Julia
This package provides a macro-based implementation of traits, using Tim Holy's trait trick. The main idea behind traits is to group types outside the type-hierarchy and to make dispatch work with that grouping. The difference to Union-types is that types can be added to a trait after the creation of the trait, whereas Union types are fixed after creation. The cool thing about Tim's trick is that there is no performance impact compared to using ordinary dispatch. For a bit of background and a... -
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ChaosTools.jl
Tools for the exploration of chaos and nonlinear dynamics
A Julia module that offers various tools for analyzing nonlinear dynamics and chaotic behavior. It can be used as a standalone package, or as part of DynamicalSystems.jl. All further information is provided in the documentation, which you can either find online or build locally by running the docs/make.jl file. ChaosTools.jl is the jack-of-all-trades package of the DynamicalSystems.jl library: methods that are not extensive enough to be a standalone package are added here. You should see the... -
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LaTeXStrings.jl
convenient input and display of LaTeX equation strings for Julia
This is a small package to make it easier to type LaTeX equations in string literals in the Julia language, written by Steven G. Johnson. With ordinary strings in Julia, to enter a string literal with embedded LaTeX equations you need to manually escape all backslashes and dollar signs: for example, $\alpha^2$ is written \$\\alpha^2\$. Also, even though IJulia is capable of displaying formatted LaTeX equations (via MathJax), an ordinary string will not exploit this. -
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ReverseDiff
Reverse Mode Automatic Differentiation for Julia
ReverseDiff is a fast and compile-able tape-based reverse mode automatic differentiation (AD) that implements methods to take gradients, Jacobians, Hessians, and higher-order derivatives of native Julia functions (or any callable object, really). While performance can vary depending on the functions you evaluate, the algorithms implemented by ReverseDiff generally outperform non-AD algorithms in both speed and accuracy.
