trial_impl ========== Trial controls the running of trials and sets of trials. add_stimulus_event ================== some_trial add_stimulus_event name slot start end value... Add a stimulus clamping event named `name` to the trial sequence of `some_trial`. The stimulus will be clamped to the input of the model with the name `slot`, which should be a conventional name (e.g., orthographic) that abstracts away from particular trials and models. The elements in `value` (which may be macro variable names preceded by $) will be interpreted via the representation associated with that input slot to be converted to the representation for the corresponding input layer. Add `start` as a starting trigger event for this clamping event; add `end` as an ending trigger event for this clamping event. Both `start` and `end` are with the syntax described at `add_stimulus_start_condition`. The onset and offset of the clamping are given by `start` and `end` which are of the format `event+delay` where `delay` is a number (or $macro variable indicating the amount of time to elapse after `event` for this to occur (+0 may be omitted); `event` may be `BEGIN`, `END`, `obsname`, or `ename/start` or `ename/end`, where `obsname` is the name of an observer, or `ename` is the `name` of another stimulus event added to the trial. add_stimulus_event ================== some_trial add_stimulus_event_only name Add a stimulus clamping event named `name` to the trial sequence of `some_trial`, without setting any of the properties of this event. set_description =============== some_trial set_description blah... Associate a description `blah` with `some_trial`. set_stimulus_event_slot ======================= some_trial set_stimulus_event_slot name slot Identify the slot name that determines which layer and representation are used for clamping the event `name` of `some_trial` to be `slot`. The stimulus will be clamped to the input of the model with the name `slot`, which should be a conventional name (e.g., orthographic) that abstracts away from particular trials and models. set_stimulus_event_value ======================== some_trial set_stimulus_event_value name value... Set the list of values that are used for clamping event `name` of `some_trial` to be `value`. The elements in `value` will be interpreted via the representation associated with the prevailing input slot to be converted to the representation for the corresponding input layer. remove_stimulus_event ===================== some_trial remove_stimulus_event name Remove a stimulus clamping event named `name` from the trial sequence of `some_trial`. add_stimulus_start_condition ============================ some_trial add_stimulus_start_condition eventname starttime Indicate that `starttime` is one of the possible trigger times for the clamping event `eventname` of `some_trial` to onset; events always start when the first such time is reached. The format of `starttime` is `event+delay` where `delay` is a number (or $macro variable) indicating the amount of time to elapse after `event` for this to occur (+0 may be omitted). `event` may be literally `BEGIN` or `END`; the name of an observer; or `ename/start` or `ename/end`, where `ename` is the `name` of another stimulus event added to the trial. add_stimulus_end_condition ========================== some_trial add_stimulus_end_condition eventname endtime Indicate that `endtime` is one of the possible trigger times for the event `eventname` of `some_trial` to offset; events always start when the first such time is reached. The format of `endtime` is as for `starttime` above. remove_stimulus_start_condition =============================== some_trial remove_stimulus_start_condition eventname starttime Remove the onset tigger `starttime` for the event `eventname` of `some_trial`. remove_stimulus_end_condition ============================= some_trial remove_stimulus_end_condition eventname endtime Remove the offset condition `endtime` for the event `eventname` of `some_trial`. set_end_condition ================= some_trial set_end_condition terminationtime Indicate that the trial `some_trial` ends when the termination time/event `terminationtime` is reached. The format of `terminationtime` is as for `startime` of `add_stimulus_start_condition`. remove_end_condtion =================== some_trial remove_end_condition terminationtime Delete `terminationtime` from the list of times at which `some_trial` will end. details ======= some_trial details Emit an extensive description of events and end conditions. default_observer ================ some_trial default_observer Return the dflog\_observer that is managed by `some_trial` and whose settings (by default) record the content of any macro variables and the time that each observer mentioned in the trial description (first) becomes true. set_cap ======= some_trial set_cap timeout Establish a special `timeout` termination condition for `some_trial`. `timeout` is a number (without leading `+` symbol). Layers will not be advanced beyond this time, and once all layers reach timeout, NAN (interpreted as timeout) will be recorded as the time of all observers that have been false throughout (unless overridden by `set_cap_validity`). event_pattern ============= some_trial event_pattern name Return the pattern object that is used for clamping the event `name` during the trial `some_trial`. response ======== some_trial response name Return a string pattern that represents the state of the observer `name` when it (first) becomes true during `some_trial`. Only valid for observers named as a time/event for clamping start/end or trial end. response_time ============= some_trial response_time name Return a strength pattern that represents the time at which the observer `name` when it (first) becomes true during `some_trial`. Only valid for observers named as a time/event for clamping start/end or trial end. run_set ======= some_trial run_set df_stimset For each row in the dataframe/stimulus\_set `df_stimset`, run `some_trial` with local macro variables with the names of the columns of the `df_stimset` set to the corresponding values on the row. The `default_observer` is set up and enabled with appropriate trigger before the run, and this process is reversed after the run. run_set_multiple ================ some_trial run_set_multiple spec num df_stimset As `run_set` except that each row is used multiple times, the number of which is set by `num`, and the ordering of which is set by `spec`. A `spec` of `ABAB` indicates that the whole set should be run through before the next of the `num` repetitions, whereas `AABB` indicates that that each row should be run `num` times before proceeding to the next row. set_cap_validity ================ some_trial set_cap_validity 0 Indicate that when the cap timeout is reached, the time, not NAN (timeout), should be recorded as response_time for observers that have no become true. some_trial set_cap_validity 1 Revert to the normal behaviour of the cap, where NAN (timeout) is recorded.