tff_manipulate_datatype.py1

Manipulate trx file array to change data type

Overview

usage: tff_manipulate_datatype.py [-h]

[--positions_dtype {float16,float32,float64}]: [--offsets_dtype {uint32,uint64}] [--dpv NAME DTYPE] [--dps NAME DTYPE] [--groups NAME DTYPE] [--dpg GROUP NAME DTYPE] [-f] in_tractogram out_tractogram

Manipulate a TRX file internal array to change their data type.

Each instance of --dps, --dpv, --groups require 2 arguments (FILE, DTYPE). --dpg requires 3 arguments (GROUP, FILE, DTYPE). The choice of DTYPE are:

: - (u)int8, (u)int16, (u)int32, (u)int64 - float16, float32, float64 - bool

Example command: tff_manipulate_datatype.py input.trx output.trx --position float16 --offsets uint64 --dpv color_x uint8 --dpv color_y uint8 --dpv color_z uint8 --dpv fa float16 --dps algo uint8 --dps clusters_QB uint16 --dps commit_colors uint8 --dps commit_weights float16 --group CC uint64 --dpg CC mean_fa float64

positional arguments:

`in_tractogram`	Input TRX file.
`out_tractogram`	Output filename. Format must be one of trk, tck, vtk, fib, dpy, trx.

options:

-h, --help: show this help message and exit

-f: Force overwriting of the output files.

Data type options:

--positions_dtype {float16,float32,float64}: Specify the datatype for positions for trx. [float16, float32, float64]

--offsets_dtype {uint32,uint64}: Specify the datatype for offsets for trx. [uint32, uint64]

Streamlines metadata options:

`--dpv NAME DTYPE`	Specify the datatype for a specific data_per_vertex.
`--dps NAME DTYPE`	Specify the datatype for a specific data_per_streamline.
`--groups NAME DTYPE`	Specify the datatype for a specific group.
`--dpg GROUP NAME DTYPE`	Specify the datatype for a specific data_per_group.