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guess-it-2

Program

Given a number as standard input, this program prints out a range in which the next number provided should be.

The data received by the program (via the tester), is presented as the following example:

    189
    123
    121
    114
    145
    110
    ...

This data represents a graph in which the values of the x axis are the number of the lines (0, 1, 2, 3, 4, 5 ...) and the values of the y axis are the actual numbers (189, 113, 121, 114, 145, 110...).

Each of the numbers will be your standard input and the purpose of your program is for you to find the range in which the next number will be in. This range should have a space separating the lower limit from the upper one like in the example:

189    --> Standard input
<120 132>    --> The guessed range
next value: 123    --> The range was correct

Algorithm

To guess a correct and small range for a next value, I used regression line +/- 6.

linear/concept linear/formula

Usage & Testing

Make sure to install the used NumPy Library:

pip install numpy

To test the program, make sure that student folder is inside the tester extracted file.

Make the script inside the student folder executable:

cd student && chmod +x script.sh && cd ..

To run program, these commands should be ran to have the dependencies needed and to start the webpage on the port 3000:

  1. Using node:
npm install express
npm start
  1. Using docker compose:
docker-compose up

To reload the server use:

docker-compose down -v && docker-compose up --build
  1. Using dockerfile:
docker build -t guesser .
docker run -p 3000:3000 guesser

After opening your browser of preference in the port port 3000, if you try clicking on any of the Test Data buttons, you will notice that in the Dev Tool/ Console there is a message which tells you that you need another guesser besides the student.

Adding a guesser is simple. You need to add in the URL a guesser, in other words, the name of one of the files present in the ai/ folder:

localhost:3000?guesser=<name_of_guesser>

Choose from big-range, linear-regr, correlation-coef, mse, and nic. For example:

localhost:3000?guesser=big-range

Note that for this project, only data set 4, 5 are considered.

After that, choose which of the random data set to test. After that you can wait for the program to test all of the values (boooooring), or you can click Quick to skip the waiting and be presented with the results.

Since the website uses big data sets, we advise you to clear the displays clicking on the Clean button after each test.