Prototype-to-Production Development Environment for Analytical Applications
PyIMSL Studio contains both open source and proprietary components in Python and C, that create a fully supported and documented platform for analytic prototyping and production application development.
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90-Day Evaluation
Free for non-commercial use. |
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See PyIMSL Studio in use
This 11 minute video shows how PyIMSL Studio can be used to quickly prototype a pattern recognition application in Python, and how the prototype is easily taken to the C language using the same machine learning algorithms. |
PyIMSL Studio is a collection of development tools and numerical algorithms for modelers and implementation teams creating analytic applications. WIth PyIMSL Studio, prototype work is transformed into production faster and with less complexity, cost and risk than using multiple tools. The key component of PyIMSL Studio is PyIMSL, a set of Python wrappers to the algorithms in the IMSL C Library. Functional areas include:
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- Matrix Operations
- Linear Algebra
- Eigensystems
- Interpolation & Approximation
- Numerical Quadrature
- Differential Equations
- Nonlinear Equations
- Optimization
- Special Functions
- Finance & Bond Calculations
- Genetic Algorithm
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- Basic Statistics
- Time Series & Forecasting
- Nonparametric Tests
- Correlation & Covariance
- Data Mining
- Regression
- Analysis of Variance
- Transforms
- Goodness of Fit
- Distribution Functions
- Random Number Generation
- Neural Networks
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Components
PyIMSL Studio contains both open source and proprietary components that create a fully supported and documented platform for analytic prototyping and production development.
- For prototyping, a number of open source tools including Python, NumPy, Eclipse, matplotlib and commercial components from Visual Numerics, Inc. are available for Python, including PyIMSL Python wrappers to the mathematics and statistics algorithms in the IMSL C Library. This combination of tools provides a rich environment for prototype development.
- For production deployment, PyIMSL Studio includes the IMSL C Library. Other I/O and data filtering components are available in both Python and C to further support deployment. Using the IMSL C Library provides parity between prototype and production code.
