GazeGenie / fixations_df_columns.md
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Column names for Fixation Dataframe

Some features were adapted from the popEye R package (github) The if the column depend on a line assignment then a _ALGORITHM_NAME will be at the end of the name.

  • subject: Subject name or ID
  • trial_id: Trial ID
  • item: Item ID
  • condition: Condition (if applicable)
  • fixation_number: Index of fixation
  • start_uncorrected: Starting timestamp of event as recorded by EyeLink
  • stop_uncorrected: End timestamp of event as recorded by EyeLink
  • start_time: Start time (in ms since start of the trial)
  • end_time: End time (in ms since start of the trial)
  • corrected_start_time: Start time of the event measured from to the first fixation
  • corrected_end_time: End time of the event measured from to the first fixation
  • x: Raw x position (in pixel)
  • y: Raw y position (in pixel)
  • pupil_size: Size of pupil as recorded by EyeLink
  • distance_in_char_widths: Horizontal distance to previous fixation in number of character widths
  • y_ALGORITHM: Corrected y position (in pixel), i.e. after line assignment
  • y_ALGORITHM_correction: Difference between corrected and raw y position (in pixel)
  • duration: Duration (in ms)
  • sac_in: Incoming saccade length (in letters)
  • sac_out: Outgoing saccade length (in letters)
  • type: Whether fixation is an outlier fixation ("out"), i.e. located outside the text area (see assign.outlier and assign.outlier.dist arguments)
  • blink: Whether a blink occured directly before or after the fixation
  • run: Number of run the fixation was assigned to (if applicable)
  • linerun: Number of run on the line the fixation was assigned to (if applicable)
  • line_num: Number of line the fixation was assigned to
  • line_change: Difference between the line of the current and the last fixation
  • line_let: Number of letter on line
  • line_word: Number of word on line
  • letternum: Number of letter in trial
  • letter: Name of Letter
  • on_word_number: Number of word in trial
  • on_word: Name of Word
  • ianum: Number of IA in trial
  • ia: Name of IA
  • on_sentence_num: Number of sentence in trial
  • on_sentence: Sentence text
  • sentence_nwords: Number of words in sentence
  • trial: Name trial (abbreviated)
  • trial_nwords: Number of words in trial
  • word_fix: Number of fixation on word
  • word_run: Number of run the word the word was read
  • word_runid: Number of the word run, the fixation belongs to
  • word_run_fix: Number of fixation within the run
  • word_firstskip: Whether word has been skipped during first-pass reading
  • word_refix: Whether word has been refixated with current fixation
  • word_launch: Launch site distance from the beginning of the word
  • word_land: Landing position with word
  • word_cland: Centered landing position (e.g., calculated from the center of the word)
  • word_reg_out: Whether a regression was made out of the word
  • word_reg_in: Whether a regression was made into the word
  • sentence_word: Number of word in sentence
  • sentence_fix: Number of fixation on sentence
  • sentence_run: Number of run on sentence
  • sentence_runid: Number of the sentence run, the fixation belongs to
  • sentence_firstskip: Whether the sentence has been skipped during first-pass reading
  • sentence_refix: Whether sentence was refixated wither current fixation
  • sentence_reg_out: Whether a regression was made out the sentence
  • sentence_reg_in: Whether a regression was made into the sentence
  • sac_in_ALGORITHM_NAME: Incoming saccade length (in letters)
  • sac_out_ALGORITHM_NAME: Outgoing saccade length (in letters)
  • blink_before: Whether a blink was recorded before the event
  • blink_after: Whether a blink was recorded after the event
  • blink: Whether a blink was recorded before or after the event
  • duration: Duration of the event
  • line_change_ALGORITHM_NAME: Difference between the line of the current and the previous fixation
  • on_word_number_ALGORITHM_NAME: Index of word that the fixation has been assigned to
  • num_words_in_sentence_ALGORITHM_NAME: Number of words in sentence to which fixation has been assigned
  • word_land_ALGORITHM_NAME: Landing position of fixation within word in number of letters
  • line_let_ALGORITHM_NAME: Index of letter on line
  • line_let_from_last_letter_ALGORITHM_NAME: Letter number on line counted from last letter of line
  • line_word_ALGORITHM_NAME: Number of word on line
  • sentence_word_ALGORITHM_NAME: Number of word in sentence
  • is_far_out_of_text_uncorrected: Indicates if a fixation is far outside the stimulus area as determined by the vertical and horizontal margins
  • line_let_previous_ALGORITHM_NAME: Index of letter on line for previous fixations
  • line_let_next_ALGORITHM_NAME: Index of letter on line for next fixations
  • sentence_reg_out_to_ALGORITHM_NAME: Whether a regression was made out of the sentence
  • sentence_reg_in_from_ALGORITHM_NAME: Whether a regression was made into the sentence
  • word_reg_in_from_ALGORITHM_NAME: Whether a regression was made out of the word
  • word_reg_out_to_ALGORITHM_NAME: Whether a regression was made into the word
  • word_firstskip_ALGORITHM_NAME: Whether word has been skipped during first-pass reading
  • sentence_firstskip_ALGORITHM_NAME: Whether the sentence has been skipped during first-pass reading
  • sentence_runid_ALGORITHM_NAME: Number of the sentence run, the fixation belongs to
  • sentence_run_fix_ALGORITHM_NAME:
  • angle_incoming: Angle based on position of previous fixation
  • angle_outgoing: Angle based on position of next fixation