rockverse.dect.DECTGroup#

class rockverse.dect.DECTGroup(zgroup)[source]#

Manages Dual Energy Computed Tomography (DECT) processing. This class builds upon Zarr groups and is adapted for MPI (Message Passing Interface) processing, enabling parallel computation across multiple CPUs or GPUs.

For a detailed workflow, refer to the original research paper.

Note

This class should not be directly instantiated. Use the create_group() instead.

Parameters:: zgroup (zarr group) – An existing Zarr group.

Attributes#

Voxel images#

`lowECT`	The low energy computed tomography voxel image.
`highECT`	The high energy computed tomography voxel image.
`mask`	The mask voxel image.
`segmentation`	The segmentation voxel image.
`rho_min`	Voxel image with the minimum electron density per voxel.
`rho_p25`	Voxel image with the the first quartile (25th percentile) for the electron density values per voxel from the Monte Carlo inversion.
`rho_p50`	Voxel image with the the median (50th percentile) values for the electron density per voxel from the Monte Carlo inversion.
`rho_p75`	Voxel image with the the third quartile (75th percentile) for the electron density values per voxel from the Monte Carlo inversion.
`rho_max`	Voxel image with the maximum electron density per voxel.
`Z_min`	Voxel image with the minimum effective atomic number per voxel.
`Z_p25`	Voxel image with the the first quartile (25th percentile) for the effective atomic number values per voxel from the Monte Carlo inversion.
`Z_p50`	Voxel image with the the median values (50th percentile) for the effective atomic number per voxel from the Monte Carlo inversion.
`Z_p75`	Voxel image with the the third quartile (75th percentile) for the effective atomic number values per voxel from the Monte Carlo inversion.
`Z_max`	Voxel image with the maximum effective atomic number per voxel.
`valid`	Voxel image with the number of valid Monte Carlo results for each voxel.

Calibration materials#

`calibration_material`	A list containing four instances of the `CalibrationMaterial` class, each representing a different calibration material used in Dual Energy Computed Tomography (DECT) processing.
`periodic_table`	An instance of the `PeriodicTable` class that provides access to atomic number and atomic mass values for elements used in the Monte Carlo inversion.

Inversion parameters#

`maxA`	Maximum value for inversion coefficient $A$ in the broad search algorithm used during Monte Carlo simulations.
`maxB`	Maximum value for inversion coefficient $B$ in the broad search algorithm used during Monte Carlo simulations.
`maxn`	Maximum value for inversion coefficient $n$ in the broad search algorithm used during Monte Carlo simulations.
`lowE_inversion_coefficients`	Pandas DataFrame with the valid realization sets for low energy inversion coefficients.
`highE_inversion_coefficients`	Pandas DataFrame with the valid realization sets for high energy inversion coefficients.
`tol`	Tolerance value for terminating the Newton-Raphson optimizations.
`whis`	The boxplot whisker length for determining Monte Carlo outlier results.
`required_iterations`	The required number of valid Monte Carlo iterations for each voxel.
`maximum_iterations`	The maximum number of trials to get valid Monte Carlo iterations per voxel.
`threads_per_block`	Number of threads per block when processing using GPUs.

Methods#

Handling voxel images#

`copy_image`(image, name, **kwargs)	Copy an existing voxel image into the DECT group.
`create_mask`([fill_value, overwrite, ...])	Create a mask voxel image based on the lowECT one.
`delete_mask`()	Remove the mask array from the structure.
`create_segmentation`([fill_value, dtype, ...])	Create segmentation voxel image based on the lowECT array.
`delete_segmentation`()	Remove the segmentation array from the structure.

Monte Carlo Inversion#

`check`(*[, verbose])	Check the group structure for consistency and dependencies among arrays and processing parameters.
`preprocess`([restart])	Perform the preprocessing steps for Dual Energy Computed Tomography analysis:
`run`([restart])	Run the DECT analysis on the data in this group.

Visualization#

`view_pdfs`([figsize, bins, ...])	Convenience function for visualizing the probability density functions (PDFs) and cumulative density functions (CDFs) of calibration materials.
`view_inversion_coefs`([figsize])	Convenience function for visualizing the probability density functions (PDFs) for the Monte Carlo invertion coefficients.
`view_inversion_Zeff`([figsize])	Convenience function for visualizing the probability density functions (PDFs) for the Monte Carlo resulting effective atomic number for the calibration materials.