VatsaDev VatsaDev

## ras.py
import matplotlib.pyplot as plt
import numpy as np

def rastrigin(x, y, A=10):
  """
  Rastrigin function definition.
  """
  return A * 2 + (x**2 - A * np.cos(2 * np.pi * x)) + (y**2 - A * np.cos(2 * np.pi * y))

def generate_randomized_rastrigin_landscape(x_range, y_range, num_points,

## plagcheck.js
import { pipeline } from '@xenova/transformers';

const clipThresh = 0.7; // Threshold for overall similarity
const ssrchThresh = 0.8; // Threshold for sentence-level similarity

// Initialize the feature extraction pipeline
let extractor;

async function initializeExtractor() {
  extractor = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2');

## plagcheck.py
from sentence_transformers import SentenceTransformer
import re

# Initialize the sentence transformer model
smod = SentenceTransformer("all-MiniLM-L6-v2")

clip_thresh = 0.7  # Threshold for overall similarity
ssrch_thresh = 0.8  # Threshold for sentence-level similarity

def clip_sim(text1, text2):

## dungeon.ml
(*
  Ocaml text dungeon game
  easy way to make something fun and learn the ropes of the language
  srsly though whoever made this language was really just quirky
*)

let room_sizes_arr = [|
  "a couple planck lengths wide"; "miniscule"; "kinda tiny"; "miniature"; "normal"; "large"; "unexpectedly large";
  "unnatural"; "gigantic"; "immense"; "titanic"; "massive"; "measurable in AU"; "spanning the cosmos";
|];;

## code.js
//UI
    var tabs = this.rexUI.add
      .tabs({
        x: 400,
        y: 1600,

        panel: this.rexUI.add.gridTable({
          background: this.rexUI.add.roundRectangle(
            0,
            0,

## mdto.html
<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Markdown to html</title>
    <script src="https://cdn.jsdelivr.net/remarkable/1.7.1/remarkable.min.js"></script>
</head>
<body>
    <p>Enter markdown for conversion</p>

## onlyhtml.html
<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>Html Only</title>
  </head>
  <body>
    <center><h1>Making A website with HTML 5 & 4</h1></center>
    <center>

## Spin.html
<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <link
      rel="stylesheet"
      href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/4.7.0/css/font-awesome.min.css"
    />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>Spinny pencil</title>

## stripnav.html
<!DOCTYPE html>
<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>stripnav</title>
    <link rel="stylesheet" href="styles.css" />
    <style>
      .dropbtn {
        background-color: #4caf50;
	import matplotlib.pyplot as plt
	import numpy as np

	def rastrigin(x, y, A=10):
	"""
	Rastrigin function definition.
	"""
	return A * 2 + (x*2 - A np.cos(2 * np.pi * x)) + (y*2 - A np.cos(2 * np.pi * y))

	def generate_randomized_rastrigin_landscape(x_range, y_range, num_points,
	import { pipeline } from '@xenova/transformers';

	const clipThresh = 0.7; // Threshold for overall similarity
	const ssrchThresh = 0.8; // Threshold for sentence-level similarity

	// Initialize the feature extraction pipeline
	let extractor;

	async function initializeExtractor() {
	extractor = await pipeline('feature-extraction', 'Xenova/all-MiniLM-L6-v2');
	from sentence_transformers import SentenceTransformer
	import re

	# Initialize the sentence transformer model
	smod = SentenceTransformer("all-MiniLM-L6-v2")

	clip_thresh = 0.7 # Threshold for overall similarity
	ssrch_thresh = 0.8 # Threshold for sentence-level similarity

	def clip_sim(text1, text2):
	(*
	Ocaml text dungeon game
	easy way to make something fun and learn the ropes of the language
	srsly though whoever made this language was really just quirky
	*)

	let room_sizes_arr = [\|
	"a couple planck lengths wide"; "miniscule"; "kinda tiny"; "miniature"; "normal"; "large"; "unexpectedly large";
	"unnatural"; "gigantic"; "immense"; "titanic"; "massive"; "measurable in AU"; "spanning the cosmos";
	\|];;
	//UI
	var tabs = this.rexUI.add
	.tabs({
	x: 400,
	y: 1600,

	panel: this.rexUI.add.gridTable({
	background: this.rexUI.add.roundRectangle(
	0,
	0,
	<!DOCTYPE html>
	<html lang="en">
	<head>
	<meta charset="UTF-8">
	<meta name="viewport" content="width=device-width, initial-scale=1.0">
	<title>Markdown to html</title>
	<script src="https://cdn.jsdelivr.net/remarkable/1.7.1/remarkable.min.js"></script>
	</head>
	<body>
	<p>Enter markdown for conversion</p>