Isatis.neo - What's New?

• Isatis.neo - What's New?
• • Isatis.neo 2025.1
  • • Consistent settings for estimation method comparison
    • Improvements in simulations
    • New Datamine format already supported
    • More quality-of-life improvements
    • Seamless Python access to Isatis.neo database from anywhere - Early access

Isatis.neo 2025.1

Consistent settings for estimation method comparison

A new Use local anisotropies option is now part of the Quick Interpolation task. This feature allows local parameters for neighborhood search. It ensures that the same neighbors are used as in a kriging using local anisotropies to see the impact of the estimation method only. You can also choose between Simplified and Neighborhood Parameters Definition - now decoupled from interpolation method selection.

Improvements in simulations

• The post-processing of numerical Simulations has been enhanced with new outputs. It now offers three result tabs: General including the coefficient of variation, Cutoffs with a new Between two thresholds mode plus extra outputs like tonnage and benefit, Uncertainties with the addition of the relative-to-mean/median estimation errors, probability within tolerance and tolerance width, useful for Parker’s classification.
• In Pluri-Gaussian Simulations, a new Print transition probabilities button shows domain contact probabilities in matrix form. This assists with lithotype rule definition.

New Datamine format already supported

The new DMX file format is now supported for Import Datamine and Export Datamine. With improved compression, Unicode compatibility, and support for up to 2048 columns, it offers a modern, efficient alternative to the legacy .dm format—ready to handle today’s demanding datasets and Isatis.neo simulations.

More quality-of-life improvements

• A new Convert variables into coordinates tool enables transforming variables into coordinates to switch the geographic coordinate system.
• In the Picking Table of the Map, two actions have been added, one invert table layout, and the other to generate, from picked samples, new selection variables directly usable across tasks.
• In Cross-Validation, you can now store error variables for all variables of a multivariate geostatistical set simultaneously. A Display variable list lets you easily switch which variable to visualize in plots.

Seamless Python access to Isatis.neo database from anywhere - Early access

Browse, access, and modify your Isatis.neo database directly through Python – whether you are working within the software environment or entirely outside of it. This powerful functionality enables seamless integration into your data workflows, allowing you to programmatically read, update, or extract information from your project database using standard Python scripts. Perfect for automation, advanced analysis, or building custom tools, this feature gives you full flexibility and control over your geostatistical data – wherever you are.