Compare estimation methods more reliably with the new “Use local anisotropies” option in Quick Interpolation.

By allowing local parameters for neighborhood search, you ensure consistency with kriging-based approaches, isolating the true impact of the estimation method. Local geostatistics is utilized to identify and address varying local parameters, accounting for non-stationarity and local anisotropies, while emphasizing local particularities.

Plus, the neighborhood parameter definition is now decoupled from the interpolation method, giving you complete control and clarity in your modeling workflows.

Gain deeper insights from your simulation results with a revamped Simulations post-processing.

New result tabs include:
– The coefficient of variation,
– A brand-new “Between two thresholds” mode with outputs like tonnage and benefit,
– New indicators like relative-to-mean/median errors, probability within tolerance, and tolerance width, ideal for Parker’s classification.

In Pluri-Gaussian Simulations, define lithotype rules with more confidence thanks to the new “Print transition probabilities” button that shows domain contact probabilities in a clear matrix format.

Isatis.neo now supports Datamine’s DMX format for both import and export:
With enhanced compression, full Unicode compatibility, and support for up to 2048 columns, this modern format is built to handle today’s complex datasets and high-volume simulation results, making your workflow more robust and scalable.

Enjoy a more intuitive and versatile experience with thoughtful additions:
– Convert variables into coordinates to adapt your geographic reference system.
– In the Map Picking Table, invert table layout or create selection variables from picked samples, instantly reusable across tasks.
– In Cross-Validation, store error variables for all variables in a multivariate set at once, and easily toggle which variable to visualize.

Break free from the UI with seamless Python access to your Isatis.neo database, even outside the software.

With this powerful early-access feature, you can browse, read, extract data, and update your project database using Python. Utilizing Python enables you to automate repetitive tasks, conduct advanced analyses, and build custom tools.