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Showing 589 open source projects for "compiler python linux"

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  • 1
    pycoQC

    pycoQC

    pycoQC computes metrics and generates Interactive QC plots

    PycoQC computes metrics and generates interactive QC plots for Oxford Nanopore technologies sequencing data. PycoQC relies on the sequencing_summary.txt file generated by Albacore and Guppy, but if needed it can also generate a summary file from basecalled fast5 files. The package supports 1D and 1D2 runs generated with Minion, Gridion and Promethion devices and basecalled with Albacore 1.2.1+ or Guppy 2.1.3+. PycoQC is written in pure Python3. Python 2 is not supported.
    Downloads: 0 This Week
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  • 2
    Amazon SageMaker Examples

    Amazon SageMaker Examples

    Jupyter notebooks that demonstrate how to build models using SageMaker

    ... on-boarding for their team members, freeing them up from complex systems admin and security processes. Administrators control data access and resource provisioning for their users. Notebook Instances are another option. They have the familiar Jupyter and JuypterLab interfaces that work well for single users, or small teams where users are also administrators. Advanced users also use SageMaker solely with the AWS CLI and Python scripts using boto3 and/or the SageMaker Python SDK.
    Downloads: 0 This Week
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  • 3
    Jupytab

    Jupytab

    Display in Tableau data from Jupyter notebooks

    Jupytab allows you to explore in Tableau data which is generated dynamically by a Jupyter Notebook. You can thus create Tableau data sources in a very flexible way using all the power of Python. This is achieved by having Tableau access data through a web server created by Jupytab.
    Downloads: 2 This Week
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  • 4

    ccplot

    CloudSat and CALIPSO plotting tool

    ccplot is an open source command-line program for plotting profile, layer and earth view data sets from CloudSat, CALIPSO and Aqua MODIS products.
    Downloads: 1 This Week
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    Optimus

    Optimus

    Agile Data Preparation Workflows made easy with Pandas

    Easily write code to clean, transform, explore and visualize data using Python. Process using a simple API, making it easy to use for newcomers. More than 100 functions to handle strings, process dates, urls and emails. Easily plot data from any size. Out-of-box functions to explore and fix data quality. Use the same code to process your data in your laptop or in a remote cluster of GPUs.
    Downloads: 0 This Week
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  • 6
    Forecasting Best Practices

    Forecasting Best Practices

    Time Series Forecasting Best Practices & Examples

    ... creating implementations from scratch, we draw from existing state-of-the-art libraries and build additional utilities around processing and featuring the data, optimizing and evaluating models, and scaling up to the cloud. The examples and best practices are provided as Python Jupyter notebooks and R markdown files and a library of utility functions.
    Downloads: 0 This Week
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  • 7
    repo2docker GitHub Action

    repo2docker GitHub Action

    A GitHub action to build data science environment images

    Trigger repo2docker to build a Jupyter enabled Docker image from your GitHub repository and push this image to a Docker registry of your choice. This will automatically attempt to build an environment from configuration files found in your repository. Images generated by this action are automatically tagged with both latest and <SHA> corresponding to the relevant commit SHA on GitHub. Both tags are pushed to the Docker registry specified by the user. If an existing image with the latest tag...
    Downloads: 0 This Week
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  • 8
    StellarGraph

    StellarGraph

    Machine Learning on Graphs

    StellarGraph is a Python library for machine learning on graphs and networks. The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data. It can solve many machine learning tasks. Graph-structured data represent entities as nodes (or vertices) and relationships between them as edges (or links), and can include data associated with either as attributes. For example, a graph can...
    Downloads: 0 This Week
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  • 9

    DEPRECATED - KVFinder

    Cavity Detection PyMOL plugin

    The KVFinder software, originally published in 2014, is deprecated. We published more recent software: parKVFinder and pyKVFinder. [parKVFinder] A Linux/macOS version is available in this GitHub repository, https://github.com/LBC-LNBio/parKVFinder, while a Windows version is in this GitHub repository, https://github.com/LBC-LNBio/parKVFinder-win. Please read and cite the original paper ParKVFinder: A thread-level parallel approach in biomolecular cavity detection (10.1016/j.softx...
    Downloads: 0 This Week
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  • 10
    SageMaker Containers

    SageMaker Containers

    Create SageMaker-compatible Docker containers

    Amazon SageMaker is a fully managed service for data science and machine learning (ML) workflows. You can use Amazon SageMaker to simplify the process of building, training, and deploying ML models. To train a model, you can include your training script and dependencies in a Docker container that runs your training code. A container provides an effectively isolated environment, ensuring a consistent runtime and reliable training process. The SageMaker Training Toolkit can be easily added to...
    Downloads: 0 This Week
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  • 11
    OpenFrames

    OpenFrames

    Real-time interactive 3D graphics API for scientific simulations

    OpenFrames has moved its primary development repository to GitHub! Everything else will follow. Get it at https://github.com/ravidavi/OpenFrames/wiki OpenFrames is an Application Programming Interface (API) that allows developers to provides the ability to add interactive 3D graphics to any scientific simulation. A simulation developer can use OpenFrames to specify what they want to visualize, without having to know any details of computer graphics programming. OpenFrames is currently...
    Downloads: 0 This Week
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  • 12
    Data Science at the Command Line

    Data Science at the Command Line

    Data science at the command line

    ...-line tools to quickly obtain, scrub, explore, and model your data. To get you started, author Jeroen Janssens provides a Docker image packed with over 100 Unix power tools, useful whether you work with Windows, macOS, or Linux. You’ll quickly discover why the command line is an agile, scalable, and extensible technology. Even if you’re comfortable processing data with Python or R, you’ll learn how to greatly improve your data science workflow by leveraging the command line’s power.
    Downloads: 0 This Week
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  • 13
    GPlates

    GPlates

    Interactive visualization of plate tectonics.

    GPlates is a plate-tectonics program. Manipulate reconstructions of geological and paleo-geographic features through geological time. Interactively visualize vector, raster and volume data. PyGPlates is the GPlates Python library. Get fine-grained access to GPlates functionality in your Python scripts.
    Downloads: 16 This Week
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  • 14

    Spectral Python

    A python module for hyperspectral image processing

    Spectral Python (SPy) is a python package for reading, viewing, manipulating, and classifying hyperspectral image (HSI) data. SPy includes functions for clustering, dimensionality reduction, supervised classification, and more.
    Downloads: 2 This Week
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  • 15

    QuiclickRNAseq

    An integrated pipeline for RNA-seq analysis

    Quiclick is a python framework for RNA-seq data analysis, including data trimming, mapping, counting and RNA editing analysis.
    Downloads: 0 This Week
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  • 16
    NYCOpenData-Profiling-Analysis

    NYCOpenData-Profiling-Analysis

    Open Data Profiling, Quality and Analysis on NYC OpenData dataset

    Open data often comes with little or no metadata. You will profile a large collection of open data sets and derive metadata that can be used for data discovery, querying, and identification of data quality problems. For each column, identify and summarize the semantic types present in the column. These can be generic types (e.g., city, state) or collection-specific types (NYU school names, NYC agency). For each semantic type T identified, enumerate all the values encountered for T in all...
    Downloads: 0 This Week
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  • 17
    Crystalsim -  XRD hkl simulation

    Crystalsim - XRD hkl simulation

    X-ray diffraction (XRD) analysis for hkl simulation of any crystal.

    Crystalsim is a simple freeware program with a neat graphical user interface for X-ray diffraction (XRD) data analysis . It can simulates all possible {hkl} planes data for the selected crystal. Crystallographic Information File (.cif) can also be used. Analyze both powder diffraction and single crystal data . Indexed at International Union of Crystallography (IUCR). Crystalline lattice parameters such as ‘a’, ‘b’, ‘c’ as well as interfacial angles such as alpha, beta,...
    Downloads: 2 This Week
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  • 18
    Deep Learning with PyTorch

    Deep Learning with PyTorch

    Latest techniques in deep learning and representation learning

    ... (a minimal version of Anaconda) and several Python packages installed. The following instruction would work as is for Mac or Ubuntu Linux users, Windows users would need to install and work in the Git BASH terminal. JupyterLab has a built-in selectable dark theme, so you only need to install something if you want to use the classic notebook interface.
    Downloads: 0 This Week
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  • 19
    QtiPlot
    QtiPlot is a user-friendly, platform independent data analysis and visualization application similar to the non-free Windows program Origin.
    Downloads: 34 This Week
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  • 20
    An Open Source IEC 61131-3 Integrated Development Environment, providing PLCOpen SoftPLC programming, CanOpen IO's, and SVG based HMI.
    Downloads: 0 This Week
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  • 21
    SCiDA Pro

    SCiDA Pro

    Program for solar cell production data analysis

    The purpose of the SCiDA Pro program is to help with processing solar cell production data. It has the following features: - Able to handle large data sets in a fast way (e.g. plotting 100k cell data takes a few seconds) - Easy data filtering - Easy generation of a data summary report - Extensive data plotting features - Cross-platform (Windows/Linux/MacOS) - Supports multiple languages
    Downloads: 1 This Week
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  • 22
    istSOS

    istSOS

    Free and Open Source Sensor Observation Service Data Management System

    istSOS is an OGC SOS server implementation written in Python. istSOS allows for managing and dispatch observations from monitoring sensors according to the Sensor Observation Service standard. The project provides also a Graphical user Interface that allows for easing the daily operations and a RESTful Web api for automatizing administration procedures. istSOS is released under the GPL License, and runs on all major platforms (Windows, Linux, Mac OS X), even though tests were conducted...
    Downloads: 4 This Week
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  • 23
    Inviwo

    Inviwo

    Interactive Visualization Workshop

    Inviwo is a modern, open-source visualization framework designed for interactive visual data analysis and scientific computing. Built in C++ with a modular, extensible architecture, Inviwo combines a visual editor (for creating data pipelines) with a powerful runtime engine that supports real-time rendering, interaction, and GPU-accelerated processing. It’s widely used in scientific domains for building and sharing visualizations of complex data such as medical imaging, simulations, and...
    Downloads: 1 This Week
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  • 24
    The TRANSIMS Studio application is an integrated development environment for the TRansportation ANalysis and SIMulation System (TRANSIMS). Components include a run time environment to execute TRANSIMS in parallel, as well as a full featured GUI.
    Downloads: 3 This Week
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  • 25
    nonechucks

    nonechucks

    Deal with bad samples in your dataset dynamically

    nonechucks is a library that provides wrappers for PyTorch's datasets, samplers and transforms to allow for dropping unwanted or invalid samples dynamically. What if you have a dataset of 1000s of images, out of which a few dozen images are unreadable because the image files are corrupted? Or what if your dataset is a folder full of scanned PDFs that you have to OCRize, and then run a language detector on the resulting text, because you want only the ones that are in English? Or maybe you...
    Downloads: 0 This Week
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