A Kotlin implementation of Numpy's random number generator... it'll spit out the same numbers given the same seed

NumpyLikeRandomState.kt

package com.eagleeyessearch

/**
 * Mersenne Twister (MR19937) random number generator
 * Translated from Numpy source code https://github.com/numpy/numpy/tree/main/numpy/random/src/mt19937
 *
 * This class is designed to mimic the behavior of the numpy random number generator.  I.e. when given
 * the same seed, it should produce the same sequence of random numbers as numpy.
 *
 *      val rng = NumpyLikeRandomState(intSeed)
 *      val values = rng.randomByteArray(size=5, high=255).map { it.toInt().mod(256) }
 *      Assert.assertEquals(listOf<Int>(47, 107, 7, 49, 211), values)
 *
 * Currently it only supports generating random bytes, so you'll need to add more methods to generate floats/ints.
 *
 * Thank you ChatGPT for making this work, it would have been a damn nightmare to figure out on my own.
 * Oh also thank you  Makoto Matsumoto (松本 眞) and Takuji Nishimura (西村 拓士) for coming up with this thing.
 * 
 * License (from Numpy): 
 * Copyright (c) 2003-2005, Jean-Sebastien Roy ([email protected])

The rk_random and rk_seed functions algorithms and the original design of the Mersenne Twister RNG:
Copyright (C) 1997 - 2002, Makoto Matsumoto and Takuji Nishimura, All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
3. The names of its contributors may not be used to endorse or promote products derived from this software without specific prior written permission.
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
Original algorithm for the implementation of rk_interval function from Richard J. Wagner's implementation of the Mersenne Twister RNG, optimised by Magnus Jonsson.
Constants used in the rk_double implementation by Isaku Wada.
Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
 */
class NumpyLikeRandomState(seed: Any) {
    private val N = 624
    private val M = 397
    private val MATRIX_A = 0x9908b0df.toInt()
    private val UPPER_MASK = 0x80000000.toInt()
    private val LOWER_MASK = 0x7fffffff

    private var mt = IntArray(N)
    private var mti = N + 1

    init {
        when (seed) {
            is Int -> seedMT(seed)
            is Long -> seedMT(seed.toInt())
            is IntArray -> initByArray(seed)
            is ByteArray -> {
                val seedInts = seed.map { it.toInt() and 0xff }.toIntArray()
                initByArray(seedInts)
            }
            else -> throw IllegalArgumentException("Unsupported seed type")
        }
    }

    private fun seedMT(seed: Int) {
        var seedVar = seed
        seedVar = seedVar and 0xffffffff.toInt()
        mt[0] = seedVar
        for (i in 1 until N) {
            mt[i] = (1812433253L * (mt[i - 1] xor (mt[i - 1] ushr 30)) + i).toInt()
            mt[i] = mt[i] and 0xffffffff.toInt()
        }
        mti = N
    }

    private fun initByArray(initKey: IntArray) {
        seedMT(19650218)
        var i = 1
        var j = 0
        var k = if (N > initKey.size) N else initKey.size
        while (k > 0) {
            mt[i] = ((mt[i] xor ((mt[i - 1] xor (mt[i - 1] ushr 30)) * 1664525)) + initKey[j] + j).toInt()
            mt[i] = mt[i] and 0xffffffff.toInt()
            i++
            j++
            if (i >= N) {
                mt[0] = mt[N - 1]
                i = 1
            }
            if (j >= initKey.size) {
                j = 0
            }
            k--
        }
        k = N - 1
        while (k > 0) {
            mt[i] = ((mt[i] xor ((mt[i - 1] xor (mt[i - 1] ushr 30)) * 1566083941)) - i).toInt()
            mt[i] = mt[i] and 0xffffffff.toInt()
            i++
            if (i >= N) {
                mt[0] = mt[N - 1]
                i = 1
            }
            k--
        }
        mt[0] = 0x80000000.toInt() // MSB is 1; assuring non-zero initial array
    }

    private fun extractNumber(): Int {
        if (mti >= N) {
            twist()
        }
        var y = mt[mti]
        mti++

        // Tempering
        y = y xor (y ushr 11)
        y = y xor ((y shl 7) and 0x9d2c5680.toInt())
        y = y xor ((y shl 15) and 0xefc60000.toInt())
        y = y xor (y ushr 18)
        return y and 0xffffffff.toInt()
    }

    private fun twist() {
        for (i in 0 until N) {
            val y = (mt[i] and UPPER_MASK) + (mt[(i + 1) % N] and LOWER_MASK)
            var yA = y ushr 1
            if (y and 0x1 != 0) { // y is odd
                yA = yA xor MATRIX_A
            }
            mt[i] = mt[(i + M) % N] xor yA
        }
        mti = 0
    }

    fun randomByteArray(size: Int, high: Int = 255): ByteArray {
        val rng = high - 1
        val out = ByteArray(size)
        var mask = rng
        mask = mask or (mask shr 1)
        mask = mask or (mask shr 2)
        mask = mask or (mask shr 4)
        var bcnt = 0
        var buf = 0
        for (i in 0 until size) {
            var valInt: Int
            while (true) {
                if (bcnt == 0) {
                    buf = extractNumber()
                    bcnt = 3
                } else {
                    buf = buf shr 8
                    bcnt--
                }
                valInt = buf and mask
                if (valInt <= rng) {
                    break
                }
            }
            out[i] = valInt.toByte()
        }
        return out
    }
}