pymvpa2-mkevds(1)
NAME
pymvpa2-mkevds - extract (multi-sample) events from a dataset
SYNOPSIS
pymvpa2 mkevds [--version] [-h] -i DATASET [DATASET ...] [--event-attrs
ATTR [ATTR ...] | --onsets [TIME [TIME ...]] | --csv-events FILENAME |
--fsl-ev3 FILENAME [FILENAME ...]] [--time-attr ATTR] [--onset-column
ATTR] [--offset VALUE] [--duration VALUE] [--match-strategy
{prev,next,closest}] [--event-compression {mean,median,min,max}]
[--add-sa VALUE [VALUE ...]] [--add-fa VALUE [VALUE ...]] [--add-sa-txt
VALUE [VALUE ...]] [--add-fa-txt VALUE [VALUE ...]] [--add-sa-attr
FILENAME] [--add-sa-npy VALUE [VALUE ...]] [--add-fa-npy VALUE [VALUE
...]] -o OUTPUT [--hdf5-compression TYPE]
DESCRIPTION
Extract (multi-sample) events from a dataset An arbitrary number of input datasets is loaded from HDF5 storage. All loaded datasets are concatenated along the samples axis. Based on information about onset and duration of a sequence of events corresponding samples are extracted from the input datasets and converted into event samples. It is possible for an event sample to consist of multiple input samples (i.e. temporal windows). Events are defined by onset sample ID and number of consecutive samples that comprise an event. However, events can also be defined as temporal onsets and durations, which will be translated into sample IDs using time stamp information in the input datasets. Analogous to the 'mkds' command the event-related dataset can be extended with arbitrary feature and sample attributes (one value per event for the latter). The finished event-related dataset is written to an HDF5 file.
OPTIONS
--version
show program's version and license information and exit
-h, --help, --help-np
show this help message and exit. --help-np forcefully disables
the use of a pager for displaying the help.
-i DATASET [DATASET ...], --input DATASET [DATASET ...]
path(s) to one or more PyMVPA dataset files. All datasets will
be merged into a single dataset (vstack'ed) in order of
specification. In some cases this option may need to be
specified more than once if multiple, but separate, input
datasets are required.
Options for defining events (choose one):
--event-attrs ATTR [ATTR ...]
define events as a unique combinations of values from a set of
sample attributes. Going through all samples in the order in
which they appear in the input dataset, onset of events are
determined by changes in the combination of attribute values.
The length of an event is determined by the number of identical
consecutive value combinations.
--onsets [TIME [TIME ...]]
reads a list of event onsets (float) from the command line
(space-separated). If this option is given, but no arguments are
provided, onsets will be read from STDIN (one per line). If
--time-attr is also given, onsets will be interpreted as time
stamps, otherwise they are treated a integer ID of samples.
--csv-events FILENAME
read event information from a CSV table. A variety of dialects
are supported. A CSV file must contain a header line with field
names as a first row. The table must include an 'onset' column,
and can optionally include an arbitrary number of additional
columns (e.g. duration, target). All values are passed on to the
event-related samples. If '-' is given as a value the CSV table
is read from STDIN.
--fsl-ev3 FILENAME [FILENAME ...]
read event information from a text file in FSL's EV3 format (one
event per line, three columns: onset, duration, intensity). One
of more filenames can be given.
Options for modifying or converting events:
--time-attr ATTR
dataset attribute with time stamps for input samples. Onset and
duration for all events will be converted using this
information. All values are assumed to be of the same units.
--onset-column ATTR
name of the column in the CSV event table that indicates event
onsets
--offset VALUE
fixed uniform event offset for all events. If no --time-attr
option is given, this value indicates the number of input
samples all event onsets shall be shifted. If --time-attr is
given, this is treated as a temporal offset that needs to be
given in the same unit as the time stamp attribute (see
--time-attr).
--duration VALUE
fixed uniform duration for all events. If no --timeattr option
is given, this value indicates the number of consecutive input
samples following an onset that belong to an event. If
--time-attr is given, this is treated as a temporal duration
that needs to be given in the same unit as the time stamp
attribute (see --time-attr).
--match-strategy {prev,next,closest}
strategy used to match time-based onsets to sample indices.
'prev' chooses the closes preceding samples, 'next' the closest
following sample and 'closest' to absolute closest sample.
Default: 'prev'
--event-compression {mean,median,min,max}
specify whether and how events spanning multiple input samples
shall be compressed. A number of methods can be chosen.
Selecting, for example, 'mean' will yield the mean of all
relevant input samples for an event. By default (when this
option is not given) an event will comprise of all concatenated
input samples.
Options for attributes from the command line:
--add-sa VALUE [VALUE ...]
compose a sample attribute from the command line input. The
first value is the desired attribute name, the second value is a
comma-separated list (appropriately quoted) of actual attribute
values. An optional third value can be given to specify a data
type. Additional information on defining dataset attributes on
the command line are given in the section "Compose attributes on
the command line.
--add-fa VALUE [VALUE ...]
compose a feature attribute from the command line input. The
first value is the desired attribute name, the second value is a
comma-separated list (appropriately quoted) of actual attribute
values. An optional third value can be given to specify a data
type. Additional information on defining dataset attributes on
the command line are given in the section "Compose attributes on
the command line.
Options for attributes from text files:
--add-sa-txt VALUE [VALUE ...]
load sample attribute from a text file. The first value is the
desired attribute name, the second value is the filename the
attribute will be loaded from. Additional values modifying the
way the data is loaded are described in the section "Load data
from text files".
--add-fa-txt VALUE [VALUE ...]
load feature attribute from a text file. The first value is the
desired attribute name, the second value is the filename the
attribute will be loaded from. Additional values modifying the
way the data is loaded are described in the section "Load data
from text files".
--add-sa-attr FILENAME
load sample attribute values from an legacy 'attributes file'.
Column data is read as "literal". Only two column files
('targets' + 'chunks') without headers are supported. This
option allows for reading attributes files from early PyMVPA
versions.
Options for attributes from stored Numpy arrays:
--add-sa-npy VALUE [VALUE ...]
load sample attribute from a Numpy .npy file. Compressed files
(i.e. .npy.gz) are supported as well. The first value is the
desired attribute name, the second value is the filename the
data will be loaded from. Additional values modifying the way
the data is loaded are described in the section "Load data from
Numpy NPY files".
--add-fa-npy VALUE [VALUE ...]
load feature attribute from a Numpy .npy file. Compressed files
(i.e. .npy.gz) are supported as well. The first value is the
desired attribute name, the second value is the filename the
data will be loaded from. Additional values modifying the way
the data is loaded are described in the section "Load data from
Numpy NPY files".
Output options:
-o OUTPUT, --output OUTPUT
output filename ('.hdf5' extension is added automatically if
necessary). NOTE: The output format is suitable for data
exchange between PyMVPA commands, but is not recommended for
long-term storage or exchange as its specific content may vary
depending on the actual software environment. For long-term
storage consider conversion into other data formats (see 'dump'
command).
--hdf5-compression TYPE
compression type for HDF5 storage. Available values depend on
the specific HDF5 installation. Typical values are: 'gzip',
'lzf', 'szip', or integers from 1 to 9 indicating gzip
compression levels.
EXAMPLES
Extract two events comprising of four consecutive samples from a
dataset.
$ pymvpa2 mkevds --onsets 3 9 --duration 4 -o evds.hdf5 -i
'mydata*.hdf5'
AUTHOR
Written by Michael Hanke & Yaroslav Halchenko, and numerous other contributors.
COPYRIGHT
Copyright 2006-2016 PyMVPA developers Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
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