Search Results for "numpy-mkl"
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Showing 18 open source projects for "numpy-mkl"
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FFTW.jl
Julia bindings to the FFTW library for fast Fourier transforms
...Note further that MKL provides only a subset of the functionality provided by FFTW. -
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PyVista
3D plotting and mesh analysis through a streamlined interface
...Easily integrate with NumPy and create a variety of geometries and plot them. You could use any geometry to create your glyphs, or even plot the points directly. Direct access to mesh analysis and transformation routines. Intuitive plotting routines with matplotlib similar syntax. -
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VisPy
Main repository for Vispy
Vispy is an open-source, high-performance interactive visualization library in Python, designed for creating scientific visualizations and interactive plots. It leverages the power of modern Graphics Processing Units (GPUs) through OpenGL to render large datasets efficiently. Vispy supports a wide range of visualization types, including 2D plots, 3D visualizations, volume rendering, and more, making it suitable for scientific research, data analysis, and educational purposes. -
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JDF.jl
Julia DataFrames serialization format
...JDF.jl is a pure-Julia solution and there are a lot of ways to do nifty things like compression and encapsulating the underlying struture of the arrays that's hard to do in R and Python. E.g. Python's numpy arrays are C objects, but all the vector types used in JDF are Julia data types. -
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HyperTools
A Python toolbox for gaining geometric insights
...Simple API for customizing plot styles. Set of powerful data manipulation tools including hyperalignment, k-means clustering, normalizing and more. Support for lists of Numpy arrays, Pandas dataframes, text or (mixed) lists. Applying topic models and other text vectorization methods to text data. HyperTools is designed to facilitate dimensionality reduction-based visual explorations of high-dimensional data. The basic pipeline is to feed in a high-dimensional dataset (or a series of high-dimensional datasets) and, in a single function call, reduce the dimensionality of the dataset(s) and create a plot. -
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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. Postprocessing of model results will allow export... -
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Visdom
A tool for creating, organizing, and sharing data visualizations
A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy. Visdom aims to facilitate visualization of (remote) data with an emphasis on supporting scientific experimentation. Broadcast visualizations of plots, images, and text for yourself and your collaborators. Organize your visualization space programmatically or through the UI to create dashboards for live data, inspect results of experiments, or debug experimental code. ... -
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PyNanoLab
data analysis and Visualization with matplotlib
PyNanoLab contains a variety of tools to complete the data analysis, statistics, curve fitting, and basic machine learning application. Visualization in pynanolab is based on matplotlib. The setup tools is desinged to control and set-up all the details of the figure with a GUI. -
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StellarGraph
Machine Learning on Graphs
...For example, a graph can contain people as nodes and friendships between them as links, with data like a person’s age and the date a friendship was established. StellarGraph supports the analysis of many kinds of graphs. StellarGraph is built on TensorFlow 2 and its Keras high-level API, as well as Pandas and NumPy. It is thus user-friendly, modular and extensible. It interoperates smoothly with code that builds on these, such as the standard Keras layers and scikit-learn. -
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MCNPydE
MCNP data extraction and display software library
MCNPydE is a Python library for extracting data from MCNP output file. It requires Python, Matplotlib and Numpy. It is a data reduction tool for MCNP output for ease of results analysis and viewing. -
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PyVE
PyVE is image analysis and visualization environment
...At the core of it there is a powerful viewer for displaying 3D datasets (MRI, PET, CT) based on VTK. It all comes precompiled allowing painless access to Python (2.x), the ITK toolkit for image analysis, numpy/scipy for numerical calculations, Qt and PyQt4 for the development Graphical User Interfaces. It is what you need for fast prototyping and development of more complex projects. -
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Matplotlib is a python library for making publication quality plots using a syntax familiar to MATLAB users. Matplotlib uses numpy for numerics. Output formats include PDF, Postscript, SVG, and PNG, as well as screen display. As of matplotlib version 1.5, we are no longer making file releases available on SourceForge. Please visit http://matplotlib.org/users/installing.html for help obtaining matplotlib.
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wxRays
Visual x-ray data processor
Visual x-ray data processor. The routine, writed in Python using wxPython, NumPy, SciPy and mathplotlib libraries for practical and educational purpose. -
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math lib for .NET. n-dim arrays, complex numbers, linear algebra, FFT, sorting, cells- and logical arrays as well as 3D plotting classes help developing algorithms on every platform supporting .NET. Sources from SVN, binaries: http://ilnumerics.net
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PyMaTi is a simple and easy to use GUI for numerical and scientific computing in Python. It surrounds well know packages NumPy and Matplotlib and provides possibility to immediately play with numerical python from intuitive user interface.
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PyPlotSuite aims to provide immediate, easy-to-use, GUI tools to display, analyze and create publication-quality 2D plots of 1D data series, images, 2D arrays. This project is based on (and would not exist without) pygtk, matplotlib and numpy.
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Quick reference for switching between mathematical computation environments for computer algebra, numeric processing and data visualisation. Examples are Matlab, IDL, SPlus, and their open-source counterparts Octave, Scilab, Python+NumPy and R.
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