nipy_tsdiffana - Online in the Cloud

PROGRAM:

NAME

nipy_tsdiffana - Analyze, plot time series difference metrics

DESCRIPTION

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

positional arguments:
filename
4D image filename

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

--out-file OUT_FILE
graphics file to write to instead of leaving image on screen

--write-results
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[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

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

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.

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