expyriment.design.Trial¶

class expyriment.design.Trial¶

A class implementing an experimental trial.

__init__()¶: Create a Trial.

add_stimulus(stimulus)¶

Add a stimulus to the trial.

Parameters:	stimulusexpyriment stimulus stimulus to add (expyriment.stimuli.* object)

Notes

This will add references to stimuli, not copies!

clear_factors()¶: Clear all factors.

clear_stimuli()¶: Clear the stimuli.

compare(trial)¶

Compares this trial with another trail and returns True if all factors associated with both trials are identical. Added stimuli will be ignored for the comparison.

Parameters:	traildesign.Trial
Returns:	identical: boolean

copy()¶: Return a copy of the trial.

property factor_dict¶: The dictionary with all factors of the trial.

property factor_names¶: Getter for factors names.

property factors_as_text¶: Return all factor names and values as csv string line

find_stimulus(id)¶

Find the positions of a stimulus.

Parameters:	idint stimulus id to look for
Returns:	posint positions as a list or None if not in stimuli list

get_factor(name, return_none_if_not_defined=False)¶

Get a factor of the trial.

Parameters:	namestr factor name return_none_if_not_definedboolean (default: False) suppresses exception and returns None if factor is not defined.
Returns:	factor_valstr or numeric

has_factor(name)¶

Checks if a factor is defined.

Parameters:	namestr factor name (str)
Returns:	boolboolean

property id¶: Getter for id.

order_stimuli(order)¶

Order the stimuli.

Parameters:	orderlist list with the new order of positions

preload_stimuli()¶

Preload all stimuli in trial.

Returns:	timeint time it took to execute this method in ms

remove_stimulus(position)¶

Remove stimulus from trial.

Parameters:	positionint position of the stimulus

set_factor(name, value)¶

Set a factor for the trial.

Parameters:	namestr factor name valuestr or numeric factor value

shuffle_stimuli(max_repetitions=None, n_segments=None)¶

Shuffle all stimuli.

Parameters:	max_repetitionsint, optional see documentation of randomize.shuffle_list, default = None n_segmentsint, optional see documentation of randomize.shuffle_list, default = None
Returns:	successbool randomization was successful and fulfilled the specified constrains (see max_repetitions)