Search Results for "google-visualization-python"
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Showing 17 open source projects for "google-visualization-python"
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LabPlot
Data Visualization and Analysis
LabPlot is a FREE, open source and cross-platform Data Visualization and Analysis software accessible to everyone. -
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This project houses software to analyze data acquired from electrophysiology experiments. Currently, we have an Octave/MATLAB program to analyze electroneurogram traces of coupled oscillators, and a Perl library for the analysis of voltage trace data
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Yet Another Audio Feature Extractor is a toolbox for audio analysis. Easy to use and efficient at extracting a large number of audio features simultaneously. WAV and MP3 files supported, or embedding in C++, Python or Matlab applications.
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SPIW - Scanning Probe Image Wizard
Scanning Probe Image Wizard - MATLAB Toolbox
...For information on SPIW's performance see our publication ( http://dx.doi.org/10.1063/1.4827076 ) in the Review of Scientific Instruments. A related open-source project SPIEPy (https://pypi.python.org/pypi/SPIEPy/) is developing a python library to for automated SPM imaged enhancement. SPIEPy brings many SPIW algorithms to the Python user. -
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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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C++, Matlab and Python library for Hidden-state Conditional Random Fields. Implements 3 algorithms: LDCRF, HCRF and CRF. For Windows and Linux, 32- and 64-bits. Optimized for multi-threading. Works with sparse or dense input features.
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Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.
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Matlab Community Detection Toolbox
CDTB is a MATLAB toolbox which performs Community Detection
...The user can employ the functions from the MATLAB command line; or he can write his own code, incorporating the CDTB functions; or he can use the Graphical User Interface (GUI) which automates the community detection and includes some data visualization options. -
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This is the prototype version of software for robust detecting and segmentation of cell nuclei in 3D fluorescence labeled microscopy images. First release coming soon...
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BRAHMS is a Modular Execution Framework for dynamical systems. It knits together independently-authored software modules implementing dynamical processes into an integrated system, and supervises the deployment and execution of that system.
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NaRIBaS
Unix-based preparation and analysis toolbox for molecular simulations
...Task specific input and preparation or analysis function, are easy expandable to meet the scientific characteristic of constant changing properties. Concepts for efficiently storing and analysing large files in conjunction with graphical visualization and numerical data processing are presented in a Manual. A documented script collection that allows reproducing all simulations and analysis results presented in the Doctoral thesis of the author. -
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Implematation of robust depth-based inference tools for microarray data (a scale curve, to measure the dispersion of a set of curves, a rank test to decide if two groups of curves come from the same population, and classification techniques).
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The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.
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Design and develop Recommendation and Adaptive Prediction Engines to address eCommerce opportunities. Build a portfolio of engines by creating and porting algorithms from multiple disciplines to a usable form. Try to solve NetFlix and other challenges.
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imael
remove me
IMAEL stands for Image Matlab Analysis and Estimation Library. It consists in a collection of functions for image filtering, analysis, visualization, for 2D, 3D grayscale and color images. -
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nBoost is a suite of boosting algorithms designed to solve binary classification problems on data that is not linearly separable by a convex combination of base hypotheses, i.e. noisy data. WARNING: Active development. Underlying algorithm is unstable.
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This project collect several data mining methods, such as: 1) clustering methods; 2) biclustering methods; 3) FCA methods and etc.
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