allensdk.brain_observatory.behavior.data_objects.trials.trials module¶
- class allensdk.brain_observatory.behavior.data_objects.trials.trials.Trials(trials: DataFrame, response_window_start: float)[source]¶
Bases:
DataObject,StimulusFileReadableInterface,NwbReadableInterface,NwbWritableInterface- property aborted: Series¶
- property catch_trial_count: int¶
Number of ‘catch’ trials
- property change_time: Series¶
- classmethod columns_to_output() List[str][source]¶
Return the list of columns to be output in this table
- property correct_reject: Series¶
- property correct_reject_trial_count: int¶
Number of trials with a correct reject behavior response
- property data: DataFrame¶
- property false_alarm: Series¶
- property false_alarm_trial_count: int¶
Number of trials where the mouse had a false alarm behavior response
- classmethod from_nwb(nwbfile: NWBFile) Trials[source]¶
Populate a DataObject from a pyNWB file object.
- Parameters:
- nwbfile:
The file object (NWBFile) of a pynwb dataset file.
- Returns:
- DataObject:
An instantiated DataObject which has name and value properties
- classmethod from_stimulus_file(stimulus_file: BehaviorStimulusFile, stimulus_timestamps: StimulusTimestamps, licks: Licks, rewards: Rewards, sync_file: SyncFile | None = None) Trials[source]¶
Populate a DataObject from the stimulus file
- Returns:
- DataObject:
An instantiated DataObject which has name and value properties
- get_engaged_trial_count(engaged_trial_reward_rate_threshold: float = 2.0) int[source]¶
Gets count of trials considered “engaged”
- Parameters:
- engaged_trial_reward_rate_threshold:
The number of rewards per minute that needs to be attained before a subject is considered ‘engaged’, by default 2.0
- Returns:
- count of trials considered “engaged”
- property go_trial_count: int¶
Number of ‘go’ trials
- property hit: Series¶
- property hit_trial_count: int¶
Number of trials with a hit behavior response
- property index: Index¶
- property lick_times: Series¶
- property miss: Series¶
- property miss_trial_count: int¶
Number of trials with a hit behavior response
- property rolling_performance: DataFrame¶
Return a DataFrame containing trial by trial behavior response performance metrics.
- Returns:
- pd.DataFrame
- A pandas DataFrame containing:
- trials_id [index]:
Index of the trial. All trials, including aborted trials, are assigned an index starting at 0 for the first trial.
- reward_rate:
Rewards earned in the previous 25 trials, normalized by the elapsed time of the same 25 trials. Units are rewards/minute.
- hit_rate_raw:
Fraction of go trials where the mouse licked in the response window, calculated over the previous 100 non-aborted trials. Without trial count correction applied.
- hit_rate:
Fraction of go trials where the mouse licked in the response window, calculated over the previous 100 non-aborted trials. With trial count correction applied.
- false_alarm_rate_raw:
Fraction of catch trials where the mouse licked in the response window, calculated over the previous 100 non-aborted trials. Without trial count correction applied.
- false_alarm_rate:
Fraction of catch trials where the mouse licked in the response window, calculated over the previous 100 non-aborted trials. Without trial count correction applied.
- rolling_dprime:
d prime calculated using the rolling hit_rate and rolling false_alarm _rate.
- property start_time: Series¶
- to_nwb(nwbfile: NWBFile) NWBFile[source]¶
Given an already populated DataObject, return an pyNWB file object that had had DataObject data added.
- Parameters:
- nwbfileNWBFile
An NWB file object
- Returns:
- NWBFile
An NWB file object that has had data from the DataObject added to it.
- property trial_count: int¶
Number of trials (including all ‘go’, ‘catch’, and ‘aborted’ trials)