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MicPy 0.4.3 Changelog

This minor release further improves VTK and ParaView integration for MICRESS field data, with a new ParaView filter for extending simulation domains according to MICRESS boundary conditions.

MICRESS Boundary Extension filter

MICRESS simulations often exploit symmetries and repeating patterns to reduce the computational domain and save computation time.

• Added the MICRESS Boundary Extension filter to the ParaView plugin.
• The filter extends MICRESS datasets beyond their original simulation domain using the specified boundary conditions.
• Added support for periodic, insulating, and symmetric boundary conditions.
• Boundary conditions and extension sizes can be configured independently for each spatial direction.
• This allows symmetric and repeating structures to be reconstructed and visualized directly in ParaView.

Legacy VTK file support

• Added support for saving VTK files in the legacy format using Field.save_vti().
• This provides an additional export option for workflows and tools that rely on the legacy VTK format such as HOMAT.

Length unit conversion

Added 22 September 2026.

• Added support for length unit conversion when exporting MICRESS field data with Field.as_vti().
• Length units can also be converted directly in the ParaView plugin, making it easier to visualize MICRESS datasets using the desired spatial unit.

Field boundary extension

Added 7 October 2026.

• Added Field.extend() for extending MICRESS field data directly in Python.
• The method supports the same periodic, insulating, and symmetric boundary conditions as the ParaView Boundary Extension filter.
• Boundary conditions and extension sizes can be specified independently for each spatial direction.
• The ParaView Boundary Extension filter now uses the same underlying field extension functionality.

Field resampling

Added 7 October 2026.

• Added Field.resample() for resampling MICRESS field data to a different spatial resolution while preserving the physical extent of the field.
• Added nearest-neighbor resampling for discrete and categorical data such as grain or phase IDs.
• Added linear interpolation for continuous field data.
• Added overlap-weighted averaging for conservative coarsening of continuous field data.
• The field spacing is automatically adjusted to match the new resolution while preserving the original physical extent.

MicPy 0.4.2 Changelog

This minor release improves VTK and ParaView integration for MICRESS field data.

Expanded VTK data representation options

• Replaced the previous point_data option in Field.as_vti() with the new data_mode parameter.
• "cell" stores the original values as VTK CellData.
• "point_average" converts cell values to PointData by averaging adjacent cells.
• "point_direct" stores each field value directly as a VTK point value without averaging.
• The previous point_data parameter remains available for backward compatibility but is now deprecated.

Improved ParaView reader

• Added all three data modes to the MICRESS ParaView reader.
• Users can select between CellData, averaged PointData, and direct PointData.
• VTK array names are derived from the MICRESS file extension, making fields easier to identify in ParaView and PyVista.

MICRESS Basic Training September 2026

Following the record participation at the MICRESS Basic Training held on 11-12 March 2026, the MICRESS team has announced the next training session, scheduled for 9-10 September 2026.

As in previous editions, the program will include a combination of introductory lectures and hands-on sessions, providing participants with practical experience using MICRESS.

Further details, including the full agenda and registration, are available on the official website:

Training Details

MICRESS 7.4 Released

MICRESS 7.4 is now available, featuring improvements across simulation capabilities, performance, workflow automation, visualization, and usability throughout the MICRESS ecosystem. The release also includes updates for MICpad, DP_MICRESS, and MicPy.

For a complete list of new features and detailed release notes, please visit the official MICRESS website.

MicPy 0.4.1 Changelog

This minor release focuses on improving the usability and clarity of field visualizations.

Improved physical scaling in Field.plot()

• Plots now correctly reflect the physical dimensions of the data instead of displaying raw cell indices.
• The spacing stored in the underlying NumPy array is used to compute axis scaling.
• By default, plots are shown in micrometers (µm).
• A new length_unit parameter allows easy unit customization (e.g., "mm", "cm", "m").

Built-in scalebar for plots

• Added a scalebar to Field.plot() for better visual interpretation of sizes.
• Enabled by default and positioned in the lower right corner.
• Automatically selects clean, human-friendly lengths (e.g., 1, 2, 5 × 10ⁿ).
• Default width is 20% of the plot, with options available for customization.
• Can be disabled via scalebar=False.
• For a complete list of options, see the Reference.

These changes aim to make MicPy plots more intuitive and publication-ready with minimal effort.

MicPy 0.4 Changelog

Performance Improvements

New decompression backend for MICRESS binary field data

• Introduced a redesigned backend enabling parallel data reading.
• Added persistent on-disk indexing for field data, allowing random-access indices to be reused across sessions.
• Significantly improved load times and access performance for large datasets, especially in repeated or interactive workflows.

Improved robustness and maintainability

• Index creation and management are now handled by a dedicated backend library¹.
• Reduced internal code complexity, improving overall stability and long-term maintainability.

Visualization and Data Exchange

Native VTK support

• Added direct conversion of MICRESS field data (NumPy arrays) to VTK image data.
• Supports both CellData and PointData representations.
• Optional interpolation from cell-centered data to point-based values.
• Enables straightforward export to VTI files and direct use with VTK-based Python tools such as PyVista.

Enhanced support for interactive Python workflows

• Improved integration with Jupyter notebooks for 2D and 3D visualization and analysis.
• Facilitates seamless data exchange between MicPy and modern visualization libraries.

ParaView Integration

New ParaView plugin based on MicPy

• Allows direct loading of MICRESS binary field data into ParaView without intermediate conversion steps.
• Leverages the new decompression and indexing backend for smooth, responsive interaction with large datasets.
• Provides full access to ParaView’s filtering and data processing pipelines, with strong support for 3D visualization workflows.

MICRESS Basic Training March 2026

The MICRESS team is pleased to announce an upcoming online MICRESS training, aimed at students and researchers in computational materials science who want to get started with microstructure simulations.

The training combines a short introductory overview with in-depth lectures and hands-on sessions led by experienced experts. Participants will gain practical experience with MICRESS through guided exercises on a dedicated simulation platform, enabling direct application to their own research.

Participation is free of charge, and registration is open for either the introductory session alone or the full training program.

Training Details