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What is Igor Pro?

Igor Pro 8 is an interactive platform that facilitates the investigation of scientific and engineering data, along with the production of high-quality graphs and layouts suitable for publishing purposes. Since its inception in 1989, it has gained popularity among tens of thousands of professionals across various technical disciplines. The software combines powerful tools with an intuitive point-and-click interface that appeals to casual users, while also providing a programming environment that meets the needs of more experienced users. Moreover, Igor Pro's extensible plugin capabilities augment its fundamental features, allowing users to create custom tools for tasks such as data acquisition, instrument management, and intricate computations. The latest version, Igor Pro 8, brings hundreds of improvements, including 20 new operations, five new functions, and a novel NetCDF XOP, enhancing its versatility significantly. For those interested, a detailed list of all the updates is available for review. This ongoing development process ensures that Igor Pro continues to serve effectively and remains pertinent to its varied user community. As technology and scientific needs evolve, Igor Pro adapts, reinforcing its position as a vital tool in the toolkit of researchers and engineers alike.

What is DataMelt?

DataMelt, commonly referred to as "DMelt," is a versatile environment designed for numerical computations, data analysis, data mining, and computational statistics. It facilitates the plotting of functions and datasets in both 2D and 3D, enables statistical testing, and supports various forms of data analysis, numeric computations, and function minimization. Additionally, it is capable of solving linear and differential equations, and provides methods for symbolic, linear, and non-linear regression. The Java API included in DataMelt integrates neural network capabilities alongside various data manipulation techniques utilizing different algorithms. Furthermore, it offers support for symbolic computations through Octave/Matlab programming elements. As a computational environment based on a Java platform, DataMelt is compatible with multiple operating systems and supports various programming languages, distinguishing it from other statistical tools that often restrict users to a single language. This software uniquely combines Java, the most prevalent enterprise language globally, with popular data science scripting languages such as Jython (Python), Groovy, and JRuby, thereby enhancing its versatility and user accessibility. Consequently, DataMelt emerges as an essential tool for researchers and analysts seeking a comprehensive solution for complex data-driven tasks.

Media

Media

Integrations Supported

Cohesion

Integrations Supported

Apache NetBeans
Eclipse BIRT

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

$0
Access to full documentation (examples, Java API documentation, online manual) requires one-time membership payment (20$/user)
Free Version

Supported Platforms

Windows
Mac

Supported Platforms

Android
Windows
Mac
Linux

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support

Training Options

Documentation Hub

Training Options

Documentation Hub
On-Site Training

Company Facts

Organization Name

WaveMetrics

Date Founded

1988

Company Location

United States

Company Website

www.wavemetrics.com

Company Facts

Organization Name

jWork.ORG

Date Founded

2005

Company Location

United States

Company Website

datamelt.org

Categories and Features

Data Analysis

High Volume Processing

Categories and Features

Artificial Intelligence

For Healthcare
Image Recognition
Machine Learning
Natural Language Processing
Predictive Analytics

Data Analysis

Data Discovery
Data Visualization
Predictive Analytics
Regression Analysis
Statistical Modeling
Text Analytics

Data Mining

Data Extraction
Data Visualization
Machine Learning
Predictive Modeling
Statistical Analysis
Text Mining

Data Visualization

Analytics
Simulation Models
Visual Discovery

Deep Learning

Convolutional Neural Networks
Document Classification
ML Algorithm Library
Model Training
Self-Learning
Visualization

Education

Not specified

Neural Network

Not specified

Statistical Analysis

Analytics
Association Discovery
Compliance Tracking
File Management
File Storage
Forecasting
Multivariate Analysis
Regression Analysis
Statistical Simulation
Survival Analysis
Time Series
Visualization

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