.. _scil_mrds_select_number_of_tensors:

scil_mrds_select_number_of_tensors
==================================

::

	usage: __main__.py [-h] [--out_prefix OUT_PREFIX] [--mask MASK]
	                   [--processes NBR]
	                   [--sh_basis {descoteaux07,tournier07,descoteaux07_legacy,tournier07_legacy}]
	                   [-v [{DEBUG,INFO,WARNING,ERROR}]] [-f]
	                   in_prefix in_volume
	
	Use the NUFO map information to select the plausible number of tensors
	in the Multi-Resolution Discrete Search (MRDS).
	https://link.springer.com/chapter/10.1007/978-3-031-47292-3_4
	
	scil_mrds_select_number_of_tensors uses the output from mdtmrds command.
	Some mdtmrds output files will be named differently from the expected input:
	    COMP_SIZE becomes signal_fraction
	    NUM_COMP becomes num_tensors
	    PDDs_CARTESIAN becomes evecs
	    Eigenvalues becomes evals
	
	mdtmrds: information available soon (not part of scilpy).
	
	Input:
	    Inputs are a list of 5 files for each MRDS solution (D1, D2, D3).
	    - Signal fraction of each tensor ([in_prefix]_D[1,2,3]_signal_fraction.nii.gz)
	    - Eigenvalues ($in_prefix]_D[1,2,3]_evals.nii.gz)
	    - Isotropic ([in_prefix]_D[1,2,3]_isotropic.nii.gz)
	    - Number of tensors ([in_prefix]_D[1,2,3]_num_tensors.nii.gz)
	    - Eigenvectors ([in_prefix]_D[1,2,3]_evecs.nii.gz)
	
	    Example:
	        scil_mrds_select_number_of_tensors sub-01 nufo.nii.gz
	
	positional arguments:
	  in_prefix             Prefix used for all MRDS solutions.
	  in_volume             Volume with the number of expected tensors. (Example: NUFO volume)
	
	options:
	  -h, --help            show this help message and exit
	  --out_prefix OUT_PREFIX
	                        Prefix of the MRDS results [results].
	  --mask MASK           Optional mask filename.
	  --processes NBR       Number of sub-processes to start. 
	                        Default: [1]
	  --sh_basis {descoteaux07,tournier07,descoteaux07_legacy,tournier07_legacy}
	                        Spherical harmonics basis used for the SH coefficients. 
	                        Must be either descoteaux07', 'tournier07', 
	                        'descoteaux07_legacy' or 'tournier07_legacy' [['descoteaux07_legacy']]:
	                            'descoteaux07'       : SH basis from the Descoteaux et al.
	                                                   MRM 2007 paper
	                            'tournier07'         : SH basis from the new Tournier et al.
	                                                   NeuroImage 2019 paper, as in MRtrix 3.
	                            'descoteaux07_legacy': SH basis from the legacy Dipy implementation
	                                                   of the Descoteaux et al. MRM 2007 paper
	                            'tournier07_legacy'  : SH basis from the legacy Tournier et al.
	                                                   NeuroImage 2007 paper.
	  -v [{DEBUG,INFO,WARNING,ERROR}]
	                        Produces verbose output depending on the provided level. 
	                        Default level is warning, default when using -v is info.
	  -f                    Force overwriting of the output files.
	
	2.2.2