Elena Cokova, Jen Hammelman, and Naomi Zarrilli
Comp 50 Final Project

Operation----------------------------------------------------------------------
How to run:
usage: MBTI_ASModel.py [-h] [-q NUMQS] [-qfile QFILE] [-afile AFILE] [-t TIME]

optional arguments:
  -h, --help            show this help message and exit
  -q NUMQS, --numQs NUMQS
        number of questions, default 10
  -qfile QFILE, --qfile QFILE
        question file, default Data/myers-briggs.csv
  -afile AFILE, --afile AFILE
        answer file, default stdin
  -t TIME, --time TIME  
        time for waiting, default 0.2

  The question file must follow a five-line format:
  1. Question
  2. Option A
  3. Option B
  4. Statement for option A
  5. Statement for option B

  API Keys:
  The program relies on an online API that limits each user to 1000 calls a 
  day. If running the program causes a json parse error, try changing the API
  key.

  The relevant line is 63:
	'ClassifyText?readkey=*********&' + \
	
  Replace asterisks with one of the following API keys:
  qv7uGKYDBcSK
  jHP7vqc5rX83

Dependencies:
To run the program, the following must be installed:
  wn (https://wordnet.princeton.edu/)
  TKinter (https://wiki.python.org/moin/TkInter)

Files--------------------------------------------------------------------------

FlexQueue.py
This is an extension of the Python Queue implementation. We added a function
that allowed us to randomly peek into the Queue, which gives the user the
ability to view a random element without the element being removed from the
queue. We also added an update function.

action.py
The action class represents a generic cognitive process that is responsible for
moving memories from one store to the next. Memories each have an associated
frequency to control when they may be moved to the next memory story. The
action chooses a random memory to act on and checks its frequency. If the
frequency is at the action's predetermined threshold, the memory is moved to the
end of the next memory store. If not, the action increments the frequency.

memory.py
The memory class represents an individual memory bank. It has a queue which
stores memories and can be accessed by other classes. The memory class inherits
from the threading library and its run function simply removes the oldest
memory in its queue every x seconds, which represents memory decay.

retrieval.py
The retrieval class represents the process of "remembering" something from
long-term that is similar to a current short-term memory. This involves first
accessing short-term to select a random memory, finding a like-association in
long-term, and then moving said association into long-term. To determine
"likeness" we used the Wordnet package @@ for the command-line to look for
similar words between short-term and long-term.

MBTI_ASModel.py
This issues a personality test to the user, takes in user answers, and stores
the answers as sentences into memory. The processes of memories being stored,
moved, and decayed take place as the memory threads run. At various points of
the user inputting answers, an MBTI test is run on the current memories stored.
When the test is done a graph is rendered that demonstrates changes in the
user's MBTI over time.