nipy_tsdiffana - Analyze, plot time series difference metrics
usage: nipy_tsdiffana [-h] [--out-file OUT_FILE] [--write-results]
- [--out-path OUT_PATH]
- [--out-fname-label OUT_FNAME_LABEL] [--time-axis TIME_AXIS] [--slice-axis SLICE_AXIS] filename
- Analyze, plot time series difference metrics
- 4D image filename
- -h, --help
- show this help message and exit
- --out-file OUT_FILE
- graphics file to write to instead of leaving image on screen
- if specified, write diagnostic images and analysis variables, plot to OUT_PATH. Mutually incompatible with OUT_FILE
- --out-path OUT_PATH
- path for output image files (default from FILENAME path
- --out-fname-label OUT_FNAME_LABEL
- mid part of output image / plot filenames
- --time-axis TIME_AXIS
- Image axis for time
- --slice-axis SLICE_AXIS
- Image axis for slice
nipy_tsdiffana runs the time series diference algorithm over a 4D image volume, often and FMRI volume.
It works in one of three modes:
* interactive : the time series difference plot appears on screen. This is the
- default mode
* non-interactive, plot only : write time series difference plot to graphic
- file. Use the "--out-file=<myfilename>" option to activate this mode
* non-interactive, write plot, images and variables : write plot to file, and
- write generated diagnostic images and variables to files as well. Use the "--write-results" flag to activate this option. The generated filenames come from the results of the "--out-path" and "--out-fname-label" options (see help).
Write-results option, generated files -------------------------------------
When doing the time point analysis, we will make a difference volume between each time point and the next time point in the series. If we have T volumes then there will be (T-1) difference volumes. Call the vector of difference volumes DV and the first difference volume DV. So DV results from subtraction of the second volume in the 4D input image from the first volume in the 4D input image. The element-wise squared values from DV is *DV2*.
The following images will be generated. <ext> is the input filename extension (e.g. '.nii'):
* "dv2_max_<label><ext>" : 3D image volume, where each slice S is slice from
- all of DV2 (slice S) throudh DV2[T-1] (slice S) that has the maximum summed squared values. This volume gives an idea of the worst (highest difference) slices across the whole time series.
* "dv2_mean_<label><ext>" : the mean of all DV2 volumes DV2 .. DV[T-1]
- across the volume (time) dimension.
- Higher voxel values in this volume mean
- that time-point to time point differences tended to be high in this voxel.
We also write the mean signal at each time point, and the mean squared difference between each slice in time, as variables to a 'npz' file named "tsdiff_<label>.npz"
The filenames for the outputs are of the form <out-path>/<some_prefix><label><file-ext> where <out-path> is the path specified by the --out-path option, or the path of the input filename; <some_prefix> is one of the standard prefixes above, <label> is given by --out-label, or by the filename of the input image (with path and extension removed), and <file-ext> is '.png' for graphics, or the extension of the input filename for volume images. For example, specifying only the input filename ``/some/path/fname.img`` will generate filenames of the form ``/some/path/tsdiff_fname.png, /some/path/dv2_max_fname.img`` etc.
|January 2020||nipy_tsdiffana 0.4.2|