#### Column names for Fixation Dataframe
Some features were adapted from the popEye R package ([github](https://github.com/sascha2schroeder/popEye))
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