ResearchAnalyzer

Open-source python API under GNU license for automation of ResearchLoggers' logs analysis. It offers reports on:

Also it analyzes the final document, providing information on the final result.

How to use

The LogInfo object provides information on the data by using descriptive statistics. It must be instantiated by providing:
- A clicks log.
- A keystroke log.
- A system log.
The TextInfo object provides information on the final document. It must be instantiated by providing:
- The final document.

get_unique_pressed_clicks(): Returns a set with all unique types of clicks used during the logging session.
get_all_pressed_clicks(): Returns a list of pairs for each event in the session. Format:

(x coordinate, y coordinate, screen resolution, button type, click type, program name, window title)

get_click_info(): Returns a list of tuples. Each tuple has the following format:

(button type, [down times], up time, press duration, [down x], [down y], up x, 'up y)

print_click_summary(): It displays a summary of the click data:
- Total amount of clicks.
- Windows in which clicks are pressed.
- Types of clicks used.
- Mean click press time.
- Click press time variance.
- Click press time standard deviation.
plot_clicks_in_screenshot(): Marks in a screenshot where clicks were made.

get_unique_pressed_keys(): Returns a set with all unique types of keystrokes used during the logging session. Examples: period, comma, a, c, z, downarrow, etc.
get_all_pressed_keys(): Returns a list of pairs for each key event that occurred in the session. Format:

(key name, key type, window name, window title)

get_letter_info(): Returns a list of tuples. Each tuple has the following format:

(key type, [down times], up time, press time, [down x], [down y], up x, up y)

print_key_summary(): It displays a summary of the keystroke data:
- Total amount of pressed keys.
- Unique pressed keys.
- Windows in which keys are pressed.
- Mean key press time.
- Key press time variance.
- Key press time standard deviation.
- Unique function keys used.
- Unique erase keys used.
- Unique movement keys used.
- Unique key combos used.
plot_keystroke_progression_graph(bin_size): It plots the amount of pressed down keys against time. Each of the bin size can be specified in seconds.

plot_clicks_progression_graph(bin_size): It plots the amount of pressed down clicks against time. Each of the bin size can be specified in seconds.

get_time_by_active_window(): It returns a dictionary whose key is the name of a window used and its value is the time spent in it (in milliseconds). A special entry "total" contains the total session time.
plot_window_distribution_pie_chart(): Plots a pie chart of the times spent in each window in the session.

get_orientation_info(): Returns a tuple with the format (start time, start end).
get_drafting_info(): Returns a tuple with the format (start time, start end).
get_orientation_info(): Returns a tuple with the format (start time, start end).
get_total_session_time(): Returns an integer with the total session time.
print_phases_summary(): Prints a summary of the phases (orientation, drafting, revision and the whole session).
- Start and end time.
- Phase duration.
- Percentage of the session dedicated to the phase.

print_pauses(): Prints an enumeration of all the pauses in the session, including the start and end of each one.
print_pause_summary(begin, end): Prints a summary of the pauses in the interval [begin, end]. It includes:
- Total amount of pauses in the session.
- Amount of:
  - Short pauses.
  - Medium pauses.
  - Large pauses.
  - Non significant pauses.
- Mean pause time.
- Pause time variance.

get_words_by_part_of_speech(): Returns a dictionary, the key is a part of speech and the value is a list with all the words that were used that can be as that part of speech.
get_sentences(): Returns the sentences in the final document as a list of strings.
get_n_most_frequent_words(n): Returns a list of strings containing the n most frequent words in the final document.
plot_frequency_distribution(n): Plots the frequency distribution plot of the most common n words.

An usage example of ResearchAnalyzer can be found in main.py; it uses the ResearchLogger's example log files on the "example_log" folder.

The keystrokes summary looks like:

The clicks summary looks like:

Note: You need to collect your own data with ResearchLogger to analyze your own datasets.