More data exchange interfaces

• [All editions] Load several meshes at once to speed up the import. Save them in as many objects in a single file or separate mesh files. Check their open/closed status and detect problematic edges such as winglet, internal walls, extra face, and errant vertex.
• [Standard and Mining editions] Import Leapfrog meshes through a dedicated interface.

Additional capabilities in Exploratory Data Analysis

• [All editions] Quickly select points in the basemap by drawing a polygon to highlight and mask them.
• [All editions] Refine the automatic variogram fitting using a new constrained mode that allows locking some variogram parameters’ values or range of values (sills, ranges, nugget, anisotropy) and getting optimized values for the parameters that are not blocked. Scale the variogram variance to 1. Compare the goodness of fit of different models.

Additional capabilities in estimation and simulations

• [All editions] Fine-tune kriging neighborhoods, further defining new advanced parameters. Edit neighborhoods quickly or create ones from scratch using the new Neighborhood Explorer and associate them with existing Geostatistical Sets. Display the neighborhood ellipsoid in the 3D view.
• [All editions] Reduce the risk of negative estimates in multivariate environments using the new kriging option Rescaled cokriging (also called Standardized ordinary cokriging).
• [All editions] Check the quality of your simulation outputs with the new Simulation Validation task. Compare one, several, or all realizations to any data through their statistics (min, max, mean), histograms, and variograms.

Useful tools and various improvements

• [All editions] Draw polylines and polygons in basemaps and use them as possible faults when kriging.
• [All editions] Set the graphical bound axes to your desired values.
• [All editions] Easily exchange color scales between Isatis.neo projects through the import/export of files.
• [All editions] Regularize non-vertical drill holes by benches. Assign the sample value to the first or last composited sample. When regularizing samples by length, additional advanced parameters based on the length of the residuals allow precise control of the composited samples.
• [All editions]  Set a rotation for the moving window in the Declustering tool.
• [All editions] Calculate weighted histograms.
• [All editions] Access the openpyxl Python library for reading/writing Excel 2010 xlsx/xlsm/xltx/xltm files. This library complements the already available ones – Scikit Learn, Matplotlib, Numpy, Pandas, PySide2, and Scipy – to help you further customize the software to your needs.

This version offers a new tool ‘Neighborhood statistics’ letting you store a wealth of statistics. Among them:

• Basic statistics: number of neighbors, the neighborhood search index, and status code.
• Distance-based statistics: sample number of the nearest sample, distance to the nearest sample, sample number of the furthest sample, distance to the furthest sample, mean distance to the neighbors, and the minimum distance between two neighbors.
• Variable statistics: the value of the nearest sample, the value of the furthest sample, mean value of the neighbors, variance value of the neighbors, minimum and maximum values of the neighbors, standard deviation value of the neighbors, the weighted sum of the neighbors, the quantiles of the neighbor values.
• Multivariate statistics: correlation between the variable and an auxiliary variable
• Categorical statistics: number of neighbors in each category, number of categories used, the proportion of neighbors in each category.