- timing_tool.py - for manipulating and evaluating stimulus timing files
(-stim_times format: where each row is a separate run)
This program is meant to work with ascii files containing rows of floats ('*' characters are ignored). This is the format used by 3dDeconvolve with the -stim_times option. Some timing files do not need evaluation, such as those where the timing is very consistent. However, it may be important to examine those files from a random timing design. Recall that an ISI (inter-stimulus interval) is the interval of time between the end of one stimulus and start of the next. The basic program operations include: o reporting ISI statistics, such as min/mean/max values per run o reporting overall ISI statistics for a set of timing files o converting stim_times format to stim_file format o adding a constant offset to time o combining multiple timing files into 1 (like '1dcat' + sort) o appending additional timing runs (like 'cat') o sort times per row (though 3dDeconvolve does not require this) o converting between local and global stim times A sample stimulus timing file having 3 runs with 4 stimuli per run might look something like the following. Note that the file does not imply the durations of the stimuli, except that stimuli are generally not allowed to overlap. 17.3 24.0 66.0 71.6 11.0 30.6 49.2 68.5 19.4 28.7 53.8 69.4 The program works on either a single timing element (which can be modified), or a list of them (which cannot be modified). The only real use of a list of timing elements is to show statistics (via -multi_show_isi_stats).
timing_tool.py -help timing_tool.py -hist timing_tool.py -show_valid_opts timing_tool.py -ver
Extend one timing by another and sort. Write to a new timing file. timing_tool.py -timing stimesB_01_houses.1D \ -extend stimesB_02_faces.1D \ -sort \ -write_timing stimesB_extended.1D
For example, subtract 12 seconds to offset TRs dropped prior to the magnetization steady state. timing_tool.py -timing stimesB_01_houses.1D \ -add_offset -12.0 \ -write_timing stimesB1_offset12.1D
Scale, perhaps to account for a different TR or stimulus duration. timing_tool.py -timing stimesB_01_houses.1D \ -scale_data 0.975 \ -write_timing stimesB1_scaled.1D
This is like adding a negative offset equal to the first event time of each run. timing_tool.py -timing stimesB_01_houses.1D \ -shift_to_run_offset 0 \ -write_timing stimesB1_offset0.1D
Show timing statistics for the 3 timing files generated by example 3 from "make_random_timing -help". To be accurate, specify the run and stimulus durations. timing_tool.py -multi_timing stimesC_*.1D \ -run_len 200 -multi_stim_dur 3.5 \ -multi_show_isi_stats
Show timing statistics for the timing files generated by example 6 from "make_random_timing -help". Since both the run and stimulus durations vary, 4 run lengths and 3 stimulus durations are given. timing_tool.py -multi_timing stimesF_*.1D \ -run_len 200 190 185 225 \ -multi_stim_dur 3.5 4.5 3 \ -multi_show_isi_stats
Partition the stimulus timing file 'response_times.1D' into multiple timing files based on the labels in a partition file, partitions.1D. If partitions.txt contains (0, correct, incorrect), there will be 2 output timing files, new_times_correct.1D and new_times_incorrect.1D. Times where the partition label is '0' will be skipped. timing_tool.py -timing response_times.1D \ -partition partitions.txt new_times
Suppose the timing is random where each event lasts 2.5 seconds and runs are of lengths 360, 360 and 400 seconds. Convert timing.txt to sfile.1D on a TR grid of 0.5 seconds (oversampling), where a TR gets an event if at least 30% of the TR is is occupied by stimulus. timing_tool.py -timing timing.txt -timing_to_1D sfile.1D \ -tr 0.5 -stim_dur 2.5 -min_frac 0.3 \ -run_len 360 360 400 ** consider option -timing_to_1D_warn_ok
Use waver to convolve sfile.1D with GAM and use 3dDeconvolve to convolve the timing file with BLOCK(2.5). Then plot. waver -GAM -TR 0.5 -peak 1 -input sfile.1D > waver.1D 3dDeconvolve -nodata 2240 0.5 -concat '1D: 0 720 1440' \ -polort -1 -num_stimts 1 \ -stim_times 1 timing.txt 'BLOCK(2.5)' \ -x1D X.xmat.1D -x1D_stop 1dplot -sepscl sfile.1D waver.1D X.xmat.1D
Add option -per_run_file. timing_tool.py -timing timing.txt -timing_to_1D sfile.1D \ -tr 0.5 -stim_dur 2.5 -min_frac 0.3 \ -run_len 360 360 400 -per_run_file
Add option -timing_to_1D_mods. timing_tool.py -timing timing.txt -timing_to_1D smods.1D \ -timing_to_1D_mods \ -tr 0.5 -stim_dur 2.5 -min_frac 0.3 \ -run_len 360 360 400 -per_run_file
Given a TR of 2.5 seconds and random stimulus times, truncate those times to multiples of the TR (2.5). timing_tool.py -timing timing.txt -tr 2.5 -truncate_times \ -write_timing trunc_times.txt Here, 11.83 would get truncated down to 10, the largest multiple of 2.5 less than or equal to the original time.
Instead of just truncating the times, round them to the nearest TR, based on some TR fraction. In this example, round up to the next TR when a stimulus occurs at least 70% into a TR, otherwise round down to the beginning. timing_tool.py -timing timing.txt -tr 2.5 -round_times 0.7 \ -write_timing round_times.txt With no rounding, a time of 11.83 would be truncated to 10.0. But 11.83 is 1.83 seconds into the TR, or is 73.2 percent into the TR. Since it is at least 70% into the TR, it is rounded up to the next one. Here, 11.83 would get rounded up to 12.5.
The TR is 1.25s, events are ~1 TR long. Require them to occupy at least half of the given TR. Specify that rows should be per run and the run durations are all 370. timing_tool.py -multi_timing stimes.*.txt \ -multi_timing_to_events all.events.txt \ -tr 1.25 -multi_stim_dur 1 -min_frac 0.5 \ -per_run -run_len 370
Break the event list into 2, one for a sequence of changing event types, one for a sequence of ISIs (TRs from one event to the next, including the TR of the event). So if the event file from #8 shows: 0 0 3 0 0 0 0 1 0 2 2 0 0 0 ... The resulting event/ISI files would read: event: 0 3 1 2 2 ... ISI: 2 5 2 1 4 ... timing_tool.py -multi_timing stimes.*.txt \ -multi_timing_to_event_pair events.txt isi.txt \ -tr 1.25 -multi_stim_dur 1 -min_frac 0.5 \ -per_run -run_len 370
This requires knowing the run lengths, say 4 runs of 200 seconds here. The result will have 4 rows, each starting at time 0. timing_tool.py -timing stim.1D \ -global_to_local local.1D \ -run_len 200 200 200 Note that if stim.1D looks like this ( ** but as a single column ** ): 12.3 115 555 654 777 890 then local.1D will look like this: 12.3 115 155 254 377 490 It will complain about the 3 times after the last run ends (no run should have times above 200 sec).
timing_tool.py -timing local.1D \ -local_to_global global.1D \ -run_len 200 200 200
Display within-TR statistics of stimulus timing files, to show when stimuli occur within TRs. The -tr option must be specified. a. one file: show offset statistics (using -show_tr_stats) timing_tool.py -timing stim01_houses.txt -tr 2.0 -show_tr_stats b. (one or) many files (use -multi_timing) timing_tool.py -multi_timing stim*.txt -tr 2.0 -show_tr_stats c. only warn about potential problems (use -warn_tr_stats) timing_tool.py -multi_timing stim*.txt -tr 2.0 -warn_tr_stats d. create a histogram of stim time offsets within the TR (time modulo TR) (quietly output offsets, and pipe them through 3dhistog) timing_tool.py -timing stim01_houses.txt -verb 0 \ -show_tr_offsets -tr 1.25 \ | 3dhistog -nbin 20 1D:stdin consider also: 3dhistog -noempty 1D:stdin
Test a timing file for timing issues, which currently means having times that are intended to be local but might be read as global. timing_tool.py -multi_timing stim*.txt -test_local_timing
Create a simple horizontal event list (one row per run), where the event class is the (1-based) index of the given input file. This is very similar to the first file output in example 8b, but no TR information is required here. Events are simply ordered. timing_tool.py -multi_timing stimes.*.txt \ -multi_timing_to_event_list index elist12.txt
Create a vertical GE (global events) list, showing ALL fields. timing_tool.py -multi_timing stim.* -multi_timing_to_event_list GE:ALL - Note: for convenience, one can also use -show_events, as in: timing_tool.py -multi_timing stim.* -show_events This is much easier to remember, and it is a very common option.
Restrict global events list to: event index (i), duration (d), offset from previous (o), start time (t), and stim file (f) Also, write the output to elist13b.txt, rather than the screen. timing_tool.py -multi_timing stimes.*.txt \ -multi_timing_to_event_list GE:idotf elist13b.txt
Class '1' (from the first input) is partitioned based on the class that precedes it. If none precede an early class 1 event, event INIT is used as the default (else consider '-part_init 2', for example). timing_tool.py -multi_timing stimes.*.txt \ -multi_timing_to_event_list part part1.pred.txt The result could be applied to actually partition the first timing file, akin to Example 5: timing_tool.py -timing stimes.1.txt \ -partition part1.pred.txt stimes.1.part
For modulation across a run, add the event modulator as the event time divided by the run length, meaning the fraction the run that has passed before the event time. timing_tool.py -timing stim_times.txt -run_len 300 \ -marry_AM lin_run_fraq -write_timing stim_mod.txt
Given timing files A.txt and B.txt, suppose that B always follows A and that there is no rest between them. Then the durations of the A events would be defined by the B-A differences. To apply durations to class A events as such, use -apply_end_times_as_durations. timing_tool.py -timing A.txt -apply_end_times_as_durations B.txt \ -write_timing A_with_durs.txt
Given a timing file with durations, show the min, mean, max and stdev of the list of event durations. timing_tool.py -timing stimes.txt -show_duration_stats
A set of FSL timing files (for a single class), one file per run, can be read using -fsl_timing_files (rather than -timing, say). At that point, it internally becomes like a normal timing element. If the files have varying durations, the result will be in AFNI duration modulation format. If the files have amplitudes that are not constant 0 or constant 1, the result will have amplitude modulators. timing_tool.py -fsl_timing_files fsl_r1.txt fsl_r2.txt fsl_r3.txt \ -write_timing combined.txt
timing_tool.py -fsl_timing_files fsl_r1.txt fsl_r2.txt fsl_r3.txt \ -write_timing combined.txt -write_as_married
timing_tool.py -fsl_timing_files fsl_r1.txt \ -select_runs 0 0 1 0 -write_timing NEW.txt
The original runs can be duplicated, put into a new order or omitted. Also, truncate the event times to 1 place after the decimal (-nplaces), and similarly truncate the married terms (durations and/or amplitudes) to 1 place after the decimal (-mplaces). timing_tool.py -fsl_timing_files fsl_r1.txt fsl_r2.txt \ -nplaces 1 -mplaces 1 -write_as_married \ -select_runs 0 0 1 2 0 -write_timing NEW.txt
A tab separated value file contains events for all classes for a single run. Such files might exist in a BIDS dataset. Convert a single run to multiple AFNI timing files (or convert multiple runs). timing_tool.py -multi_timing_ncol_tsv sing_weather.run*.tsv \ -write_multi_timing AFNI_timing.weather Consider -write_as_married, if useful.
timing_tool.py -multi_timing_ncol_tsv sing_weather.run*.tsv \ -multi_show_isi_stats -multi_show_duration_stats timing_tool.py -multi_timing_ncol_tsv sing_weather.run*.tsv \ -tr 2 -show_tr_stats
The default column labels were assumed in the prior examples: onset duration trial_type in this example, RT is used for duration, and participant_response is used for trial_type. These TSV files are from the ds001205 dataset from openneuro.org. Output is just to an event list. timing_tool.py -tsv_labels onset RT participant_response \ -multi_timing_ncol_tsv sub-001_task-MGT_run*.tsv \ -write_multi_timing timing.sub-001.C.
Like 19c, but include "gain" and "loss" as amplitude modulators. timing_tool.py -tsv_labels onset RT participant_response gain loss \ -multi_timing_ncol_tsv sub-001_task-MGT_run*.tsv \ -write_multi_timing timing.sub-001.D.
timing_tool.py -tsv_labels 0 4 5 2 3 \ -multi_timing_ncol_tsv sub-001_task-MGT_run*.tsv \ -write_multi_timing timing.sub-001.E.
In some cases (e.g. as reaction_time), duration might have a value of "n/a". Specify an alternate column to use for duration when this occurs. timing_tool.py -tsv_labels onset reaction_time task \ -tsv_def_dur_label duration \ -multi_timing_ncol_tsv s10517-pamenc_events.tsv \ -write_multi_timing timing.sub-001.F.
timing_tool.py -tsv_labels onset reaction_time task \ -tsv_def_dur_label duration \ -multi_timing_ncol_tsv s10517-pamenc_events.tsv \ -show_tsv_label_details Consider "-show_events" to view event list.
Suppose one has timing files for conditions Pre, BPress and Post, and one wants to set the duration for each Pre condition based on whatever comes next (usually a BPress, but if that does not happen, Post is the limit). Suppose the inputs are 3 timing files stim.Pre.txt, stim.BPress.txt and stim.Post.txt, and we want to create stim.Pre_DM.txt to be the same as stim.Pre.txt, but with that variable duration attached. Then use the -multi_durations_from_offsets option as follows, providing the old label (file name) and the new file name for the class to change. timing_tool.py \ -multi_timing stim.Pre.txt stim.BPress.txt stim.Post.txt \ -multi_durations_from_offsets stim.Pre.txt stim.Pre_DM.txt
1. Action options are performed in the order of the options. Note: -chrono has been removed. 2. One of -timing or -multi_timing or -fsl_timing_files is required for processing. 3. Option -run_len applies to single or multiple stimulus classes. A single parameter would be used for all runs. Otherwise one duration per run should be supplied.
-help : show this help -help_basis : describe various basis functions -hist : show the module history -show_valid_opts : show all valid options -ver : show the version number
e.g. -timing stimesB_01_houses.1D Use this option to specify a single stimulus timing file. The user can modify this timing via some of the action options listed below.
With this option, the program will display timing statistics for the single (possibly modified) timing element. If -tr is included, TR offset statistics are also shown.
With this option, the program will display information regarding the single (possibly modified) timing element.
e.g. -stim_dur 3.5 This option allows the user to specify the duration of the stimulus, as applies to the single timing element. The only use of this is in conjunction with -show_isi_stats. Consider '-show_isi_stats' and '-run_len'.
e.g. -fsl_timing_files fsl.s1.run1.txt fsl.s1.run2.txt fsl.s1.run3.txt e.g. -fsl_timing_files fsl.stim.class.A.run.*.txt This is essentially an alternative to -timing, as the result is a single multi-run timing element. Each input file should have FSL formatted timing for a single run, and all for the same stimulus class. Each file should contain a list of entries like: event_time duration amplitude e.g. with varying durations and amplitudes (fully married) 0 5 3 17.4 4.6 2.5 e.g. with constant durations and (ignored) amplitudes (so not married) 0 2 1 17.4 2 1 e.g. empty (no events) 0 0 0 If all durations are the same, the result will not have duration modulators. If all amplitudes are 0 or all are 1, the result will not have amplitude modulators. An empty file or one with a single line of '0 0 0' is considered to have no events (note that 0 0 0 means duration and amplitude of zero). Comment lines are okay (starting with #). Consider -write_as_married.
e.g. -timing stimesB_*.1D Use this option to specify a list of stimulus timing files. The user cannot modify this data, but can display the overall ISI statistics from it. Options that pertain to this timing list include: -multi_show_isi_stats -multi_show_timing_ele -multi_stim_dur -run_len -write_all_rest_times
** this option was previously called -multi_timing_3col_tsv (both work) e.g. -multi_timing_ncol_tsv sing_weather_run*.tsv e.g. -multi_timing_ncol_tsv tones.tsv Tab separated value (TSV) files, as one might find in OpenFMRI data, are formatted with a possible header line and 3 tab-separated columns: onset duration stim_class Timing for all event classes is contained in a single file, per run.
Show the minimum, mean, maximum and standard deviation of the list of all event durations, for each timing element.
With this option, the program will display timing statistics for the multiple timing files. If -tr is included, TR offset statistics are also shown. If -write_all_rest_times is included, write a file of rest durations.
With this option, the program will display information regarding the multiple timing element list.
e.g. -multi_stim_dur 3.5 e.g. -multi_stim_dur 3.5 4.5 3 This option allows the user to specify the durations of the stimulus classes, as applies to the multiple timing elements. The only use of this is in conjunction with -multi_show_isi_stats. If only one duration is specified, it is applied to all elements. Otherwise, there should be as many stimulus durations as files specified with -multi_timing. Consider '-multi_show_isi_stats' and '-run_len'.
e.g. -write_multi_timing MT. After modifying the timing data, the multiple timing instances can be written out. Consider '-write_as_married'.
e.g. -write_simple_tsv MT. Akin to -write_multi_timing, this writes out what is seen as the stored (and pertinent) timing information. The (tab-delimited) output is of the form: onset duration class [optional modulators...] If there are known modulators, they will be output. If some classes have modulators and some do not (or have fewer), the output will still be rectangular, with such modulators output as zeros. Consider '-write_multi_timing'.
** Note that these options are processed in the order they are read.
e.g. -add_offset -12.0 Use this option to add a single offset to all of the times in the main timing element. For example, if the user deletes 3 4-second TRs from the EPI data, they may wish to subtract 12 seconds from every stimulus time, so that the times match the modified EPI data. Consider '-write_timing'.
e.g. -apply_end_times_as_durations next_events.txt Treat each NEW_FILE event time as the ending of the corresponding INPUT (via -timing) event time to create a duration list. So they should have the same number of events, and each NEW_FILE time should be just after the corresponding INPUT time. Consider '-write_timing' and '-show_duration_stats'. Consider example 16. Update: this method (while still available) can be applied via the newer -multi_durations_from_offsets option. See also, -multi_durations_from_offsets.
e.g. -add_rows more_times.1D Use this option to append rows from NEW_FILE to those of the main timing element. If the user then wrote out the result, it would be identical to using cat: "cat times1.txt times2.txt > both_times.txt". Consider '-write_timing'.
e.g. -extend more_times.1D Use this option to extend each row (run) with the times in NEW_FILE. This has an effect similar to that of '1dcat'. Sorting the times is optional, done via '-sort'. Note that 3dDeconvolve does not need the times to be sorted, though it is more understandable to the user. Consider '-sort' and '-write_timing'.
e.g. -global_to_local local_times.1D Use this option to convert from global stimulus timing (in a single column format) to local stimulus timing. Run durations must be given of course, to determine which run each stimulus occurs in. Each stimulus time will be adjusted to be an offset into the current run, e.g. if each run is 120 s, a stimulus at time 143.6 would occur in run #2 (1-based) at time 23.6 s. Consider example 9a and options '-run_len' and '-local_to_global'.
e.g. -local_to_global global_times.1D Use this option to convert from local stimulus timing (one row of times per run) to global stimulus timing (a single column of times across the runs, where time is considered continuous across the runs). Run durations must be given of course, to determine which run each stimulus occurs in. Each stimulus time will be adjusted to be an offset from the beginning of the first run, as if there were no breaks between the runs. e.g. if each run is 120 s, a stimulus in run #2 (1-based) at time 23.6 s would be converted to a stimulus at global time 143.6 s. Consider example 9b and options '-run_len' and '-global_to_local'.
e.g. -marry_AM lin_run_fraq e.g. -marry_AM lin_event_index Use this option to add a simple amplitude modulator to events. Current modulator types are: linear modulators (across events or time): lin_event_index : event index, per run (1, 2, 3, ...) lin_run_fraq : event time, as fractional offset into run (in [0,1]) Non-index modulators require use of -run_len. Consider example 15.
e.g. -partition partitions.txt new_times Use this option to partition the input timing file into multiple timing files based on the labels in a partition file, PART_FILE. The partition file would have the same number of rows and entries on each row as the timing file, but would contain labels to use in partitioning the times into multiple output files. A label of 0 will cause that timing entry to be dropped. Otherwise, each distinct label will have those times put into its timing file. e.g. timing file: 23.5 46.0 79.3 84.9 116.2 11.4 38.2 69.7 93.5 121.8 partition file: correct 0 0 incorrect incorrect 0 correct 0 correct correct ==> results in new_times_good.1D and new_times_bad.1D new_times_correct.1D: 23.5 0 0 0 0 0 38.2 0 93.5 121.8 new_times_incorrect.1D: 0 0 0 84.9 116.2
0.0 <= FRAC <= 1.0 e.g. -round_times 0.7 All stimulus times will be rounded to a multiple TR, rounding down if the fraction of the TR that has passed is less than FRAC, rounding up otherwise. Using the example of FRAC=0.7, if the TR is 2.5 seconds, then times are rounded down if they occur earlier than 1.75 seconds into the TR. So 11.83 would get rounded up to 12.5, while 11.64 would be rounded down to 10. FRAC = 1.0 is essentially floor() (as in -truncate_times), while FRAC = 0.0 is essentially ceil(). This option requires -tr. Consider example 7b. See also -truncate_times.
e.g. -scale_data 0.975 Use this option to scale (multiply) all times by a single value. This might be useful in effectively changing the TR, or changing the stimulus frequency, if it is regular. Consider '-write_timing'.
Show the minimum, mean, maximum and standard deviation of the list of all event durations.
This prints the current (possibly modified) single timing data to the terminal. If the user is making multiple modifications to the timing data, they may wish to display the updated timing after each step.
Displays all stimulus times, modulo the TR. Some examples: stim time offset (using TR = 2s) --------- ------ 0.7 0.7 9.7 1.7 10.3 0.3 15.8 1.8 Use -verb 0 to get only the times (in case of scripting). See also '-show_tr_stats', '-warn_tr_stats'.
This displays the mean, max and stdev of stimulus times modulo the TR, both in seconds and as fractions of the TR. See '-warn_tr_stats' for more details.
Use this option to display label information for TSV files. It should be used in conjunction with -multi_timing_ncol_tsv and related options.
This is akin to -show_tr_stats, but output is only displayed if there might be a warning based on the timing. Warnings occur when the minimum fraction is positive and the maximum fraction is small (less than -min_frac, 0.3). If such warnings are encountered, particularly in the case of TENT basis functions used in the linear regression, they can affect the X-matrix, essentially scaling beta #0 by the reciprocal of the fraction (noise dependent). In such a case the stimuli are almost TR-locked, and the user might be better off making them exactly TR-locked (by creating new timing files using "timing_tool.py -round_times"). See also '-show_tr_stats', '-min_frac' and '-round_times'.
This will cause each row (run) of the main timing element to be sorted (from smallest to largest). Such a step may be highly desired after using '-extend', or after some external manipulation that causes the times to be unsorted. Note that 3dDeconvolve does not require sorted timing. Consider '-write_timing'.
The main purpose of this is to test for timing files that are intended to be interpreted by 3dDeconvolve as being LOCAL TIMES, but might actually be interpreted as being GLOBAL TIMES. Note that as of 18 Feb, 2014, any '*' in a timing file will cause it to be interpreted by 3dDeconvolve as LOCAL TIMES, even if the file is only a single column.
e.g. -timing_to_1D stim_file.1D This action is used to convert stimulus times to set (i.e. 1) values in a 1D stim_file. Besides an input -timing file, -tr is needed to specify the timing grid of the output 1D file, -stim_dur is needed to specify the duration of each stimulus (which might cross many output TRs), and -run_len is needed to specify the duration of each (or all) of the runs. The -min_frac option may be applied to give a minimum cutoff for the fraction of a TR occupied by a stimulus required to label that TR as a 1. If not, the default cutoff is 0.3. For example, assume options: '-tr 2', '-stim_dur 4.2', '-min_frac 0.2'. A stimulus at time 9.7 would last until 13.9. TRs 0..4 would certainly be 0, TR 5 would also be 0 as the stimulus covers only .15 of the TR (.3 seconds out of 2 seconds). TR 6 would be 1 since it is completely covered, and TR 7 would be 1 since .95 (1.9/2) would be covered. So the resulting 1D file would start with: The main use of this operation is for PPI analysis, to partition the time series (maybe on a fine grid) with 1D files that are 1 when the given stimulus is on and 0 otherwise. Consider -timing_to_1D_warn_ok. Consider -tr, -stim_dur, -min_frac, -run_len, -per_run_file. Consider example 6a or 6c.
For -timing_to_1D, instead of writing a binary 0/1 file, write the (first) amplitude modulators to the 1D file. This only applies to -timing_to_1D.
Conditions from -timing_to_1D that this makes non-fatal: o stimuli ending after the end of a run o stimuli overlapping This only applies to -timing_to_1D.
This works exactly like 1dtranspose, and requires each row to have the same number of entries (rectangular data). The first row would be swapped with the first column, etc. Consider '-write_timing'.
All stimulus times will be truncated to the largest multiple of the TR that is less than or equal to each respective time. That is to say, shift each stimulus time to the beginning of its TR. This is particularly important when stimulus times are at a constant offset into each TR and at the same time using TENT basis functions for regression (in 3dDeconvolve, say). The shorter the (non-zero) offset, the more correlated the first two tent regressors will be, possibly leading to unpredictable results. This option requires -tr. Consider example 7.
e.g. -write_as_married If all durations are equal, the default is to not write with duration modulation (as the constant duration would likely be provided as part of a basis function). Use -write_as_married to include any constant duration as a modulator.
e.g. -write_tsv_cols_of_interest cols_of_interest.tsv This is an esoteric function that goes with -multi_timing_ncol_tsv. Since the input TSV files often have many columns that make viewing difficult, this option can be used to extract only the relevant columns and write them to a new TSV file. Consider '-multi_timing_ncol_tsv'.
e.g. -write_timing new_times.1D After modifying the timing data, the user will probably want to write out the result. Alternatively, the user could use -show_timing and cut-and-paste to write such a file. Consider '-write_as_married'.
e.g. -multi_durations_from_offsets stim.Pre.txt stim.Pre_DM.txt Given a set of timing files input via -multi_timing, set the durations for the events in one file to be based on when the next even happens. For example, the 'Pre' condition could be ended at the next button press event (or any other event that follows). Specify the OLD input to modify and the name of the NEW timing file to write. NEW will be the same as OLD, except for each event duration. This option is similar to -apply_end_times_as_durations, except That -apply_end_times_as_durations requires 2 inputs to be exactly matched, one event following the other. The newer -multi_durations_from_offsets option allows for any follower event, and makes the older option unnecessary. If the condition to modify comes as the last event in a run, the program will whine and set that duration to 0. Consider example 20. See also -apply_end_times_as_durations.
e.g. -multi_timing_to_events all.events.txt Decide which TR each stimulus event belongs to and make an event file (of TRs) containing a sequence of values between 0 (no event) and N (the index of the event class, for the N timing files). This option requires -tr, -multi_stim_dur, -min_frac and -run_len. Consider example 8.
e.g. -multi_timing_to_event_pair events.txt isi.txt Similar to -multi_timing_to_events, but break the output event file into 2 pieces, an event list and an ISI list. Each event E followed by K zeros in the previous events file would be broken into a single E (in the new event file) and K+1 (in the ISI file). Note that K+1 is appropriate from the assumption that events are 0-duration. The ISI entries should sum to the total number of TRs per run. Suppose the event file shows 2 TRs of rest, event type 3 followed by 4 TRs of rest, event type 1 followed by 1 TR of rest, type 2 and no rest, type 2 and 3 TRs of rest. So it would read: all events: 0 0 3 0 0 0 0 1 0 2 2 0 0 0 ... Then the event_pair files would read: events: 0 3 1 2 2 ... ISIs: 2 5 2 1 4 ... Note that the only 0 events occur at the beginnings of runs. Note that the ISI is always at least 1, for the TR of the event. This option requires -tr, -multi_stim_dur, -min_frac and -run_len. Consider example 8b.
e.g. -multi_timing_to_event_list index events.txt e.g. -multi_timing_to_event_list GE:itodf event.list.txt Similar to -multi_timing_to_events, but make a more simple event list that does not require knowing the TR or run lengths. The output is written to FILE, where 'stdout' or '-' mean to write to the terminal window. The information and format is specified by the STYLE field: index : write event index classes, in order, one row per run part : partition the first class of events according to the predecessor classes - the output is a list of class indices for events the precede those of the first class (this STYLE is esoteric, written for W Tseng) GE:TYPE : write a vertical list of events, according to TYPE TYPE is a list comprised of the following specifiers, where column output is in order specified (e.g. if i comes first, then the first column of output will be the class index). i : event class index p : previous event class index t : event onset time d : event duration o : offset from previous event (including previous duration) f : event class file name * note: -show_events is short for '-multi_timing_to_event_list GE:ALL -' See also -show_events.
e.g. -min_frac 0.1 This option applies to either -timing_to_1D action or -warn_tr_stats. For -warn_tr_stats (or -show), if the maximum tr fraction is below this limit, TRs are considered to be approximately TR-locked. For -timing_to_1D, when a random timing stimulus is converted to part of a 0/1 1D file, if the stimulus occupies at least FRAC of a TR, then that TR gets a 1 (meaning it is "on"), else it gets a 0 ("off"). FRAC is required to be within [0,1], though clearly 0 is not very useful. Also, 1 is not recommended unless that TR can be stored precisely as a floating point number. For example, 0.1 cannot be stored exactly, so 0.999 might be safer to basically mean 1.0. Consider -timing_to_1D.
e.g. -part_init 2 e.g. -part_init frogs default: -part_init INIT This option applies to '-multi_timing_to_event_list part'. In the case of generating a partition based on the previous events, this option allow the user to specify the partition class to be used when the class in question comes first (i.e. there is no previous event). The default class is the label INIT (the other classes will be small integers, from 1 to #inputs).
e.g. -nplaces 1 This option allows the user to specify the number of places to the right of the decimal that are used when printing a stimulus time (to the screen via -show_timing or to a file via -write_timing). The default is -1, which uses the minimum needed for accuracy. Consider '-show_timing' and '-write_timing'.
e.g. -mplaces 1 Akin to -nplaces, this option controls the number of places to the right of the decimal that are used when printing stimulus event modulators (amplitude and duration modulators). The default is -1, which uses the minimum needed for accuracy. Consider '-nplaces', '-show_timing' and '-write_timing'.
example a: Convert a single run into the second of 4 runs. -select_runs 0 1 0 0 example b: Get the last 2 runs out of a 4-run timing file. -select_runs 3 4 example c: Reverse the order of a 4 run timing file. -select_runs 4 3 2 1 example d: Make a 6 run timing file, where they are all the same as the original run 2, except the new run 4 is empty. -select_runs 2 2 2 0 2 2 example e: Convert 3 runs into positions 4, 5 and 2 of 5 runs. So 1 -> posn 4, 2 -> posn 5, and 3 -> posn 2. The other 2 runs are empty. -select_runs 0 3 0 1 2 Use this option to create a new timing element by selecting runs of an old one. Runs are 1-based (from 1 to #runs), and 0 means to use an empty run (no events). For example, if the original timing element has 5 runs, then use 1..5 to select them, and 0 to select an empty run. Original runs can be any number of times, and in any order. The number of runs in the result is equal to the number of runs listed as parameters to this option. Consider '-nplaces', '-show_timing' and '-write_timing'.
e.g. -per_run This option applies to -timing_to_1D, so that each 0/1 array is one row per run, as opposed to a single column across runs.
e.g. -per_run_file This option applies to -timing_to_1D, so that the 0/1 array goes in a separate file per run. With -per_run, each run is just a separate row.
e.g. -run_len 300 e.g. -run_len 300 320 280 300 This option allows the user to specify the duration of each run. If only one duration is provided, it is assumed that all runs are of that length of time. Otherwise, the user must specify the same number of runs that are found in the timing files (one run per row). This option applies to both -timing and -multi_timing files. The run durations only matter for displaying ISI statistics. Consider '-show_isi_stats' and '-multi_show_isi_stats'.
This option, since it is so useful, it shorthand for -multi_timing_to_event_list GE:ALL - This option works for both -timing and -multi_timing. It is terminal. See also -multi_timing_to_event_list.
(in seconds) e.g. -tr 2.0 e.g. -tr 0.1 For any action that write out 1D formatted data (currently just the -timing_to_1D action), this option is used to set the temporal resolution of the data. For example, given -run_len 200 and -tr 0.5, one run would be 400 time points. Consider -timing_to_1D and -run_len.
e.g. -tsv_labels onset RT response e.g. -tsv_labels onset RT response gain loss e.g. -tsv_labels 0 4 5 2 3 default: -tsv_labels onset duration trial_type Use this option to specify columns to be used for: stimulus onset time stimulus duration stimulus class optionally: any amplitude modulators ... TSV (tab separated value) event timing files typically have column headers, including stimulus timing information such as event onset time, duration, stimulus type, response time, etc. Unless specified, the default column headers that are processed are: onset duration trial_type But in some cases they do not exist, so the user must specify alternate headers (or indices). Columns can be specified by labels, or 0-based indices.
e.g. -verb 3 This option allows the user to specify how verbose the program is. The default level is 1, 0 is quiet, and the maximum is (currently) 4.
e.g. -write_all_rest_times all_rest.txt In the case of a show_isi_stats option, the user can opt to save all rest (pre-stim, isi, post-stim) durations to a timing-style file. Each row (run) would have one more entry than the number of stimuli (for pre- and post- rest). Note that pre- and post- might be 0. R Reynolds December 2008