File size: 3,131 Bytes
557a17a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 | # Text-to-Object-Name
* Text-to-Object-Name (T2ON) is a set of algorithms that converts a file to the set of a certain number of words, and a word frequency counter. It does not breason out words.
* To breason out words, one needs to finish an Education short course and read the instructions in <a href="https://github.com/luciangreen/Text-to-Object-Name/blob/main/Instructions_for_Breasoning.txt">Instructions_for_Breasoning.txt</a>.
* Generally, 80 word breasonings are needed to earn a high distinction at undergraduate level and below, have healthy children or sell products. This increases to 2 * 15 * 80=2400 breasonings per Honours level chapter, approximately 2 * 50 * 80=8000 breasonings per Masters level assignment and approximately 2 * 4 * 50 * 80=32,000 breasonings per PhD level assignment.
* 50 As (50 * 80=4000 breasonings) are required to earn a job.
# Getting Started
Please read the following instructions on how to install the project on your computer for preparing for breasoning.
# Prerequisites
* Please download and install SWI-Prolog for your machine at `https://www.swi-prolog.org/build/`.
# 1. Install manually
Download <a href="http://github.com/luciangreen/Text-to-Object-Name/">this repository</a>, <a href="http://github.com/luciangreen/Text-to-Breasonings/">Text to Breasonings repository</a>, the <a href="http://github.com/luciangreen/Lucian-Academy-Data/">Lucian Academy Data repository</a>, and the <a href="https://github.com/luciangreen/listprologinterpreter">List Prolog Interpreter Repository</a>.
# 2. Or Install from List Prolog Package Manager (LPPM)
* Download the <a href="https://github.com/luciangreen/List-Prolog-Package-Manager">LPPM Repository</a>:
```
mkdir GitHub
cd GitHub/
git clone https://github.com/luciangreen/List-Prolog-Package-Manager.git
cd List-Prolog-Package-Manager
swipl
['lppm'].
lppm_install("luciangreen","Text-to-Object-Name").
halt
```
# Running
* In Shell:
`cd Text-to-Object-Name`
`swipl`
* Enter:
`['text_to_object_name.pl'].`
* In the SWI-Prolog environment, enter:
`t2on(N,File,String,M).`
where N is the number of times to output the file, File is the file name, String is the string to output and M is the number of words in the file to output, e.g.:
* `t2on(u,"file.txt",u,u).` or `t2on(u,u,u,u).`
Outputs file.txt.
* `t2on(2,"file.txt",u,u).`
Outputs file.txt twice.
* `t2on(u,u,"Hello world.",u).`
Breason out "Hello world.".
* `t2on(3,u,"a b c",2).`
Outputs the first two words in "a b c" ("a" and "b") 3 times.
# Reading Algorithm
* The algorithm often runs too quickly. To notice a number of words ("read them") in unread texts, where Master=6 algorithms, PhD=~16 algorithms and professor/politician=~50 algorithms, run with:
```
`['text_to_object_name.pl'].`
W is 50*4,t2on(u,u,u,u,W).
% where W is the number of words to read
% 50 is the number of algorithms,
% and there are approximately 4 words per algorithm.
```
# Authors
Lucian Green - Initial programmer - <a href="https://www.lucianacademy.com/">Lucian Academy</a>
# License
I licensed this project under the BSD3 License - see the LICENSE.md file for details
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