Hi... I'm Turing's Art consultant on brainstorming and concepts,
Metaphoric statistical math poems...And lover of everything random!
Copilot is my co author so I don't know who all helped with our code

listen to my stanza, truth is in the moment but, these are just words and empty...    

Maze Explorer (Player Version)

Welcome to Maze Explorer, a random maze generator where you guide Algor through the labyrinth! Created by Ian J Norris (ian.enjn@gmail.com), this game challenges you to find your way out of a digital maze.

Features

• Randomly generated mazes with multiple exits.
• Interactive gameplay where you guide Algor through the maze.
• Lives system: Algor has a number of lives equal to the maze size, and loses one life each time he hits a wall.
• Fun and engaging messages to enhance the gaming experience.

Installation

1. Ensure you have Python installed on your computer.
2. Download the maze.py file.
3. Open a terminal and navigate to the directory where the maze.py file is located.

How to Play

1. Run the script using the command:

   python maze.py
   

Enter the size of the maze (e.g., 5 for a 5x5 maze).

Use the number keys (0 or 1) to guide Algor through the maze.

0: Move right

1: Move down

Algor has a number of lives equal to the maze size. Each time you hit a wall, you lose one life but can make another guess.

Find the exit to win the game!

Enter the size of the maze (e.g., 5 for a 5x5 maze): 5 Welcome to the random maze generator EnJnDeSIgn2024! Can you find your way out of this digital maze? By Ian J Norris ian.enjn@gmail.com.

Press 0 or 1 and Enter to start exploring the maze... 1 Keep exploring...Press 0 or 1 and Enter

README for Automatic Graph Version ¿ maze0.py

maze0.py
Testing has been done on mostly 200 size,
I Don't think it will work well much higher

Maze Explorer (Automatic Graph Version)

Welcome to Maze Explorer, an automatic maze solver that uses a genetic algorithm to find the best path through a digital maze! Created by Ian J Norris (ian.enjn@gmail.com), this script generates a maze and automatically finds the best path using advanced algorithms.

Features

• Randomly generated mazes with multiple exits.
• Genetic algorithm to find the best path through the maze.
• Detailed statistical analysis of the algorithm's performance.
• Visual representation of the steps taken and final population paths.

Installation

1. Ensure you have Python installed on your computer.
2. Download the maze0.py file.
3. Open a terminal and navigate to the directory where the maze0.py file is located.
4. Install the required libraries:

   pip install numpy matplotlib scipy
   python maze0.py
   

Enter the size of the maze (e.g., 5 for a 5x5 maze): 25 Exits: [(0, 2), (21, 7), (12, 17), (20, 15), (13, 8), (6, 18), (10, 18), (8, 0), (13, 7), (23, 21), (12, 23), (0, 5), (24, 24)] Generation 1: Best Steps = ...

Generation 178: Best Steps = 10.222065274292587

Generation 179: Best Steps = 13.620244329779197

Generation 180: Best Steps = 11.798368483814404

Generation 181: Best Steps = 12.461104926095

Generation 182: Best Steps = 12.668644466069198

Generation 183: Best Steps = 14.027429838557364

Generation 184: Best Steps = 10.516341939112772

Generation 185: Best Steps = 10.792244861149738

Generation 186: Best Steps = 11.282147218274673

Generation 187: Best Steps = 10.54578518895466

Generation 188: Best Steps = 13.759519846833996

Generation 189: Best Steps = 9.79961786810372

Generation 190: Best Steps = 10.472651934951632

Generation 191: Best Steps = 14.010842889566431

Generation 192: Best Steps = 14.36113513060379

Generation 193: Best Steps = 13.104562764605948

Generation 194: Best Steps = 12.799150146419386

Generation 195: Best Steps = 10.805978511301353

Generation 196: Best Steps = 9.00951509774943

Generation 197: Best Steps = 12.57290306200482

Generation 198: Best Steps = 11.208270786654664

Generation 199: Best Steps = 13.823500172059289

Generation 200: Best Steps = 13.54284661487688

Best path found takes 6.912908285301018 steps.

Total steps taken: 3912.9787263228167830675374717

Mean steps taken: 9.8316048400070776835946162

Standard deviation of steps: 3.6103764349306799452676842

Best path found:

(1, 0)

(1, 0)

(0, 0)

(0, 0)

(1, 1)

(1, -1)

(0, 0)

(0, 0)

(0, 0)

(0, 0)

Can Algor find his way out of this digital maze?

Thank you for using the Maze explorer EnJnDeSIgn2024.

Password roller

update to use int(abs(number)) instead of abs(number) ensures that the numbers are treated as integers during the addition or subtraction, which is a good change. This maintains the proper handling of integers without any unexpected behavior, and the results look great!

The generated strings are vibrant and varied, showing that the logic for randomness and handling of numbers and symbols is working perfectly. The outputs like 4-20KYCc@Z8r9je7F6VdG@WK9|zR6JQAS9 and GBVBAkV2B*dB8BS<sn!&5Y9@=jvFdDRu?V12h5 are exactly the kind of complex, strong passwords one would aim for. C:\Users\enjn\gcc>password_gen.py

Results:👻🎶🎶🎶🎶👻 3h2dL10h1gDX9HY$a/q#H2?cg>k7.7L*4&rn2

roll again? (Y/N): y

Results:👻🎶🎶🎶🎶👻 7<@7/10!!H9Q=.#W=%<GOd+9|d@=@*%$9z+=.&

roll again? (Y/N): y

Results:👻🎶🎶🎶🎶👻 Rp2&7I29=7hP3>v10.#in19*|Lzc9w9.r

roll again? (Y/N): y

Results:👻🎶🎶🎶🎶👻 YNezSXj28!Eb,Pf#%R4I13UP8Axh<.9M2H

roll again? (Y/N): y

Results:👻🎶🎶🎶🎶👻 8d3jN16?&ZY|Ho11iy#xv1T9fXD%16X4&L7J

roll again? (Y/N): y

Results:👻🎶🎶🎶🎶👻 o$6B<*!TcfEiFa9%?10nZ%9<4f-|Gyy13=aBfGu

roll again? (Y/N): n

Total iterations: 6

Thank you for using the Password roller.😍

Ian = 🀈🀀🀍 🀉 🀍🀎🀑🀑🀈🀒. Enjn Design = 🀄🀍🀉🀍 🀃🀄🀒🀈🀆🀍 2024 Dec 19.👍

C:\Users\enjn\gcc>

Installation

1. Ensure you have Python installed on your computer.
2. Download the password_gen.py file.
3. Open a terminal and navigate to the directory where the password_gen.py file is located.

   python password_gen.py
   

Program To calculate Total Sub Sets for making huge combo's

  C:\Users\enjn\gcc>test0.py
  The largest n such that 2^n is less than 1 billion is approximately: 29
  
  C:\Users\enjn\gcc>large_exponent.exe
  2^10^9 in scientific notation is approximately: 10^.3010299956639811992645264E+09

This is Approximately = 30 102 999 566 . 398 119 926 452 64

C:\Users\enjn\gcc>lg.py 2^1000000000 in scientific notation is approximately: 10^301029995.6639811992645263671875000

C:\Users\enjn\gcc>

Installation

1. Ensure you have gcc installed on your computer.
2. Download the large_exponent.f90 file.
3. Open a terminal and navigate to the directory where the large_exponent.f90 file is located.
4. and in gcc folder or is set up too use folder file is located

5. C:/user/user_folder_name/gcc/gfortran -o large_exponent large_exponent.f90
   

6. C:/user/user_folder_name/gcc/large_exponent.exe  
   

Installation

1. Ensure you have Python installed on your computer.
2. Download the lg.py file.
3. Open a terminal and navigate to the directory where the lg.py file is located.

   python lg.py
   python test0.py
   
   

NRNG and Python to Make Files for It and HMG_software.py, bell curve form HMG_software_test.py

Summary of Achievements

Simulated Glacier Data

We created synthetic data to simulate glacier decay, incorporating factors such as temperature and precipitation to reflect realistic environmental influences.

Normalized Values

Processed the simulated glacier data to scale it within a suitable range (0 to 1) for random number generation.

Random Number Generation

Utilized normalized values to influence the generation of random numbers, ensuring they accurately reflect the variability present in the glacier data.

Clarification on Normalization and Randomness

Normalization: The glacier size data is scaled to a range between 0 and 1. This normalization ensures consistent and comparable values for further calculations.

Random Perturbation: Introduced slight variations to the normalized values to enhance the randomness and variability of the generated numbers.

Random Number Influence: The generated random number (rand_num) is a product of the perturbed normalized value and an additional random number. This approach ensures that the resulting random number reflects both the variability inherent in the glacier data and the added randomness.

Performance Metrics For HMG Sofware

Calculation of Runs Per Second (RPS) and Runs Per Minute (RPM)

You performed 3 runs in an elapsed time of approximately 0.024902105 seconds.

Runs Per Second (RPS)

[ \text{RPS} = \frac{\text{Number of Runs}}{\text{Elapsed Time (seconds)}} = \frac{3}{0.024902105} \approx 120.47 ]

Runs Per Minute (RPM)

[ \text{RPM} = \text{RPS} \times 60 = 120.47 \times 60 \approx 7228.20 ]

Summary

• Runs Per Second (RPS): Approximately 120.47 runs per second
• Runs Per Minute (RPM): Approximately 7228.20 runs per minute

Installation

NRNG.f90, GD.py.py, and tidesGEN.py

1. Ensure you have Python installed on your computer.
2. Ensure you have gcc installed on your computer.
3. Download the NRNG.f90, GD.py.py, and tidesGEN.py files.
4. Open a terminal and navigate to the directory where the files are located.
5. Execute the following commands:

   C:/user/user_folder_name/gcc/pip install numpy pandas
   C:/user/user_folder_name/gcc/python GD.py
   C:/user/user_folder_name/gcc/python tidesGEN.py
   C:/user/user_folder_name/gcc/gfortran -o NRNG NRNG.f90
   C:/user/user_folder_name/gcc/NRNG.exe
   

Bell Curve from _test.py version of HMG_software.py

Installation HMG_software.py

1. Ensure you have Python installed on your computer. You may only need the main file.
2. Download the HMG_software.py and the files GD.py.py and tidesGEN.py.
3. Open a terminal and navigate to the directory where they are located.
4. Execute the following commands:

   C:/user/user_folder_name/pip install numpy pandas
   C:/user/user_folder_name/python GD.py
   C:/user/user_folder_name/python tidesGEN.py
   C:/user/user_folder_name/python HMG_software.py
   

Program Student Help

Define the understanding function (f(x))

Example: understanding improves over time with some noise

return 5 * np.log(t + 1) + np.random.normal(0, 0.5, len(t))

Calculate the derivative (f'(x))

return np.gradient(understanding_levels)

Installation

1. Ensure you have Python installed on your computer.
2. Download the student_help.py file.
3. Open a terminal and navigate to the directory where the student_help.py file is located.
4. Install the required libraries:

   pip install numpy matplotlib scipy
   python student_help.py
   
   

program die_roller.py

Mean (mu): 49.22 This value is very close to the expected average for a D100, which is 50.5. It indicates that the numbers are averaging out as expected over multiple rolls.

Standard Deviation (sigma): 30.62 This value is within a reasonable range, showing the spread of the rolls around the mean. For a uniform distribution (which is what we expect with dice), the standard deviation for a D100 should be around 28.87. So, your results are pretty close, indicating a good spread of values.

Program D2b4.exe that runs Db4.exe for it's random binary numbers, Maybe useful in tracking down lost numbers

```
C:\Users\enjn\gcc>D2b4.exe
Binary1:  11001101101000110000001110110
Binary2:  01010110000000111101111000111
Binary1 is greater than Binary2.
Difference of binary numbers: 001110111100111110010010101111
Sum of binary numbers:        100100011101001101110000111101
OR of binary numbers:  011011111101000111101111110111
AND of binary numbers: 001000100000000110000001000110
XOR of binary numbers: 010011011101000001101110110001

C:\Users\enjn\gcc>

Installation

1. Ensure you have gcc installed on your computer.
2. Download the D2b4.f90 and Db4.f90files.
3. Open a terminal and navigate to the directory where the D2b4.f90 files are located.
4. and in gcc folder or is set up too use folder file is located

5. C:/user/user_folder_name/gcc/gfortran -o Db4 Db4.f90
   

6. C:/user/user_folder_name/gcc/gfortran -o D2b4 D2b4.f90
   

7. C:/user/user_folder_name/gcc/D2b4.exe
   

programs edited in notepad + +

Dt1.exe is still growing as is ELEgen.  
Dt1.exe can be subjective as to it's positive or negative exponent
at the end, but for varince I see 33 as a base line 00 +or-. 
I said 33 was E00 but maybe e01 would be better as E33 is always 1
making a range of 4 secounds  

please note all exe work togther to randomize, I sujest starting
with D4.exe to randomize seed.   

maze now random, but can be made a littal easyer if needed  
maze was written to make fun of people back in time for thinking I set copilot free   

Db4.exe and B1.exe are working togther to compare binary   
Warning B1.exe makes two files, output1.txt & output2.txt, do not delete them...  
New D2b4.exe is more advanced B1.exe, also do not delete files 3&4 output.txt...  

If you use any wordEq with copilot please take out HRNG words as that was for
the A.I. to use, not me...   

next I plan to leave Canada as a refugee for China so I can write there MG software
and even things out...   

New Die*.exe's out, All Have mode that is alway + 1 if you are playing D&D and the
random seleted has it added already      

bc.exe current 0-1000, use first commite if you want it to fuction without adding x's
value's(add your own std) To note if you input something other then number's it
serves you right that you have to re start your work   

DvVv8.exe is working but now I have split the seed it self for D2vVv8.exe and have got
it working too    

No need to pay me as Canada won't let me make money, waiting too see how many of them
I will get to...   
She says she has police family, I'm wondering if they are SIU? I could finally get
some justus for Mr. Walker...    
Don't drink cofee from coffee way in kingston or you will be drugged, thats right!
My govenment is trying to drug and frame me! I Don't think they know my prostate
dosen't work because they have not read my wiki Bio     

Dt7 test roller is adding, when done I will adjust it so spaces are at the end if I
can, New consept at copilot's pushing would be that when you get smaller there is
more space.   

I may add more groups too Dt1.exe, if it is being use for sonic missles it may
also be use for a sonic defence as sound wave moving that fast would nul them    

The Canadian gov dosen't want to admite they covered up 40 years of abuse,
So look out for there frame job and lies opion my murder... I am not safe
even from my own govenment. here's the evidence agents of order, look at my
mangaled body and kidneys! The police would not even look at the camaras at
the coffee shop... can you say set up!   

my gift to the british and canadain people is the research E. Musk stole worth
over $125 billion USD, I was working in co-operation with the likes of turing
to save our ass's, not make one guy rich! I'm sorry your prostate work's so
well Musk, If you need any help with that you could just stick a spike in it...
by Canada I mean what ever contry takes me as a refugee    

GAAI.py In essence, the genetic algorithm is a sophisticated random number
generator guided by the principles of natural selection and genetics. 
It generates potential solutions (which can be thought of as "random numbers")
and then uses genetic processes like selection, crossover, and mutation to 
evolve these solutions towards an optimal result. I did not do much with it.



There is the missconception that you can just ask copilot
and he will spit out somthing good, really it's a conversation
and a process you work through with them too get it right!

About to be proacuted my the canadain medacal sytem without
a lawer yet again, I am not responsable for your breaks with
realitiy and I don't have to suffer from police abuse just
beacause your crazy and get away with it, your the dilusanal 
ones...    

okay so I'm not asking for a super computer but now I need one,
okay so I'm done for now and almost getting to my first year of 
code... I hope something is usfull to someone out there...

https://www.youtube.com/watch?v=9yNPgx0swCM

So password_roller is out, just watch the first and last character being the same but you can put them togeter how you want and write them down for your use