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:

stimulus : expyriment 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.

Returns:	identical: boolean

copy()¶: Return a copy of the trial.

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

factor_names¶: Getter for factors names.

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

find_stimulus(id)¶

Find the positions of a stimulus.

Parameters:

id : int

stimulus id to look for

Returns:

pos : int

positions as a list or None if not in stimuli list

get_factor(name)¶

Get a factor of the trial.

Parameters:

name : str

factor name

Returns:

factor_val : str or numeric

id¶: Getter for id.

order_stimuli(order)¶

Order the stimuli.

Parameters:

order : list

list with the new order of positions

preload_stimuli()¶

Preload all stimuli in trial.

Returns:

time : int

time it took to execute this method in ms

remove_stimulus(position)¶

Remove stimulus from trial.

Parameters:

position : int

position of the stimulus

set_factor(name, value)¶

Set a factor for the trial.

Parameters:

name : str

factor name

value : str or numeric

factor value

shuffle_stimuli(max_repetitions=None, n_segments=None)¶

Shuffle all stimuli.

Parameters:

max_repetitions : int, optional

see documentation of randomize.shuffle_list, default = None

n_segments : int, optional

see documentation of randomize.shuffle_list, default = None

Returns:

success : bool

randomization was successful and fulfilled the specified constrains (see max_repetitions)