nipy_tsdiffana1
Analyze, plot time series difference metrics
Overview
usage: nipy_tsdiffana [-h] [--out-file OUT_FILE] [--write-results]
- [--out-path OUT_PATH]
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[--out-fname-label OUT_FNAME_LABEL] [--time-axis TIME_AXIS] [--slice-axis SLICE_AXIS] filename
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Analyze, plot time series difference metrics
positional arguments:
- filename
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4D image filename
optional arguments:
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-h, --help -
show this help message and exit
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--out-file OUT_FILE -
graphics file to write to instead of leaving image on screen
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--write-results -
if specified, write diagnostic images and analysis variables, plot to OUT_PATH. Mutually incompatible with OUT_FILE
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--out-path OUT_PATH -
path for output image files (default from FILENAME path
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--out-fname-label OUT_FNAME_LABEL -
mid part of output image / plot filenames
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--time-axis TIME_AXIS -
Image axis for time
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--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
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default mode
* non-interactive, plot only : write time series difference plot to graphic
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file. Use the "--out-file=<myfilename>" option to activate this mode
* non-interactive, write plot, images and variables : write plot to file, and
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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[0]. So DV[0] 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[0] is *DV2[0]*.
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
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all of DV2[0] (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[0] .. DV[T-1]
across the volume (time) dimension.
|
Higher voxel values in this volume mean |
|---|---|
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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.