MATLAB vs. PyQtGraph vs. scikit-learn Comparison


MATLAB The MathWorks	PyQtGraph	scikit-learn	+
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About MATLAB® combines a desktop environment tuned for iterative analysis and design processes with a programming language that expresses matrix and array mathematics directly. It includes the Live Editor for creating scripts that combine code, output, and formatted text in an executable notebook. MATLAB toolboxes are professionally developed, rigorously tested, and fully documented. MATLAB apps let you see how different algorithms work with your data. Iterate until you’ve got the results you want, then automatically generate a MATLAB program to reproduce or automate your work. Scale your analyses to run on clusters, GPUs, and clouds with only minor code changes. There’s no need to rewrite your code or learn big data programming and out-of-memory techniques. Automatically convert MATLAB algorithms to C/C++, HDL, and CUDA code to run on your embedded processor or FPGA/ASIC. MATLAB works with Simulink to support Model-Based Design.	About PyQtGraph is a pure-python graphics and GUI library built on PyQt/PySide and NumPy. It is intended for use in mathematics/scientific/engineering applications. Despite being written entirely in python, the library is very fast due to its heavy leverage of NumPy for number crunching and Qt's GraphicsView framework for fast display. PyQtGraph is distributed under the MIT open-source license. Basic 2D plotting in interactive view boxes. Line and scatter plots. Data can be panned/scaled by mouse. Fast drawing for real-time data display and interaction. Displays most data types (int or float; any bit depth; RGB, RGBA, or luminance). Functions for slicing multidimensional images at arbitrary angles (great for MRI data). Rapid update for video display or real-time interaction. Image display with interactive lookup tables and level control. Mesh rendering with isosurface generation. Interactive viewports rotate/zoom with mouse. Basic 3D scenegraph for easier programming.	About Scikit-learn provides simple and efficient tools for predictive data analysis. Scikit-learn is a robust, open source machine learning library for the Python programming language, designed to provide simple and efficient tools for data analysis and modeling. Built on the foundations of popular scientific libraries like NumPy, SciPy, and Matplotlib, scikit-learn offers a wide range of supervised and unsupervised learning algorithms, making it an essential toolkit for data scientists, machine learning engineers, and researchers. The library is organized into a consistent and flexible framework, where various components can be combined and customized to suit specific needs. This modularity makes it easy for users to build complex pipelines, automate repetitive tasks, and integrate scikit-learn into larger machine-learning workflows. Additionally, the library’s emphasis on interoperability ensures that it works seamlessly with other Python libraries, facilitating smooth data processing.
Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook	Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook	Platforms Supported Windows Mac Linux Cloud On-Premises iPhone iPad Android Chromebook
Audience Modeling, simulation, and programming software that can be hosted in the cloud or on-premise	Audience Professional users interested in a solution offering scientific graphics and a GUI library for Python	Audience Engineers and data scientists requiring a solution to manage and improve their machine learning research
Support Phone Support 24/7 Live Support Online	Support Phone Support 24/7 Live Support Online	Support Phone Support 24/7 Live Support Online
API Offers API	API Offers API	API Offers API
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Pricing No information available. Free Version Free Trial	Pricing Free Free Version Free Trial	Pricing Free Free Version Free Trial
Reviews/Ratings Overall 4.7 / 5 ease 4.5 / 5 features 4.9 / 5 design 4.8 / 5 support 4.8 / 5 Read all reviews	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software	Reviews/Ratings Overall 0.0 / 5 ease 0.0 / 5 features 0.0 / 5 design 0.0 / 5 support 0.0 / 5 This software hasn't been reviewed yet. Be the first to provide a review: Review this Software
Training Documentation Webinars Live Online In Person	Training Documentation Webinars Live Online In Person	Training Documentation Webinars Live Online In Person
Company Information The MathWorks Founded: 1984 United States www.mathworks.com	Company Information PyQtGraph www.pyqtgraph.org	Company Information scikit-learn United States scikit-learn.org/stable/
Alternatives Posit	Alternatives NumPy	Alternatives Gensim Radim Řehůřek
PrimeSim HSPICE Synopsys	Bokeh	ML.NET Microsoft
LabVIEW NI	h5py HDF5	MLlib Apache Software Foundation
LiveLink for MATLAB Comsol Group	broot	Dask
RunMat Dystr View All	imageio View All	Keepsake Replicate View All
Categories Backtesting CAD Computer-Aided Engineering (CAE) Data Science Data Visualization Embedded Software Development Engineering Financial Risk Management Fraud Detection Mechanical Engineering Predictive Analytics Programming Languages Simulation Statistical Analysis	Categories Component Libraries	Categories Machine Learning
Show More Features CAD Features 2 1/2-Axis Milling 2D Drawing 3-Axis Milling 3D Modeling 4-Axis Milling 5-Axis Milling Civil Collaboration Database Connectivity Design Analysis Design Export Document Management Electrical Hole Making Mechanical Mechatronics Presentation Tools Simulate Cycles Spiral Output Structural Engineering Toolpath Simulation User Defined Cycles Engineering Features 2D Drawing 3D Modeling Chemical Engineering Civil Engineering Collaboration Design Analysis Design Export Document Management Electrical Engineering Mechanical Engineering Mechatronics Presentation Tools Structural Engineering Financial Risk Management Features Compliance Management Credit Risk Management For Hedge Funds Liquidity Analysis Loan Portfolio Management Market Risk Management Operational Risk Management Portfolio Management Portfolio Modeling Risk Analytics Benchmarks Stress Tests Value At Risk Calculation Simulation Features 1D Simulation 3D Modeling 3D Simulation Agent-Based Modeling Continuous Modeling Design Analysis Direct Manipulation Discrete Event Modeling Dynamic Modeling Graphical Modeling Industry Specific Database Monte Carlo Simulation Motion Modeling Presentation Tools Stochastic Modeling Turbulence Modeling Statistical Analysis Features Analytics Association Discovery Compliance Tracking File Management File Storage Forecasting Multivariate Analysis Regression Analysis Statistical Process Control Statistical Simulation Survival Analysis Time Series Visualization
Integrations Artelys Knitro Buffer Editor COMSOL Multiphysics CUDA Candera CGI Studio Codebeamer Codecov Domino Enterprise MLOps Platform Flower Guild AI Helix Editor Innoslate Meteomatics OpenText Analytics Database (Vertica) Overleaf PACE Anti-Piracy Plotly Dash SpellBox TPT VISTA Show More Integrations View All 77 Integrations	Integrations Artelys Knitro Buffer Editor COMSOL Multiphysics CUDA Candera CGI Studio Codebeamer Codecov Domino Enterprise MLOps Platform Flower Guild AI Helix Editor Innoslate Meteomatics OpenText Analytics Database (Vertica) Overleaf PACE Anti-Piracy Plotly Dash SpellBox TPT VISTA Show More Integrations View All 1 Integration	Integrations Artelys Knitro Buffer Editor COMSOL Multiphysics CUDA Candera CGI Studio Codebeamer Codecov Domino Enterprise MLOps Platform Flower Guild AI Helix Editor Innoslate Meteomatics OpenText Analytics Database (Vertica) Overleaf PACE Anti-Piracy Plotly Dash SpellBox TPT VISTA Show More Integrations View All 12 Integrations
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