chop0

#include <complex.h>
#include <stdint.h>
#include <assert.h>
#include <stddef.h>
#include <stdlib.h>
#include <limits.h>
#include <tgmath.h>
#include <stdio.h>
#include <stdbool.h>

chop0

//
// Created by alec on 11/25/24.
//

#include <stddef.h>
#include <assert.h>
#include <limits.h>
#include <string.h>
#include <math.h>
#include <stdlib.h>

chop0

`timescale 1ns / 1ps

module reservation_station
	#(parameter int RS_ID, int DATA_WIDTH)
	(
        input logic clk,
        input logic rst,

        register_file register_file,
        issue_bus issue,

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#!/usr/bin/java --source 21

import java.io.*;
import java.net.*;
import java.nio.file.*;

import com.sun.net.httpserver.*;

public class FileUploadServer implements HttpHandler {
	public static void main(String[] args) throws IOException {

chop0

[bits 16]

load:
	mov ah, 0x02 ; read disk sectors
	mov al, 0x01 ; 1 sector (probably should statically calculate this somehow, or use linker script)
	mov ch, 0x00 ; track
	mov cl, 0x02 ; sector
	mov dh, 0x00; head
;	mov dl, 0x00
	mov bx, 0

chop0

package ax.xz.census.proxy;

import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.io.Closeable;
import java.io.IOException;
import java.net.InetAddress;
import java.net.InetSocketAddress;
import java.net.SocketAddress;

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import java.io.IOException;
import java.net.InetAddress;
import java.net.InetSocketAddress;
import java.net.SocketAddress;
import java.nio.ByteBuffer;
import java.nio.channels.SelectionKey;
import java.nio.channels.Selector;
import java.nio.channels.ServerSocketChannel;
import java.nio.channels.SocketChannel;
import java.nio.charset.StandardCharsets;

chop0

import numpy as np
import scipy as sp

def tcp_siggen(samp_rate, freq, amp, noise_var, N):
    t = np.arange(start=0, stop=N / samp_rate, step=1 / samp_rate, dtype=np.complex64)
    # Create the phase of the sin wave at each samples
    phase = 2 * np.pi * freq * t
    # create a complex sin wave
    carrier = amp * np.exp(phase * 1j)
    # generate complex white(ish) gaussian noise with the right variance

chop0

import numpy as np
import scipy as sp

def finite_difference_coefficients(k, xbar, x):
    """
    based on the maths in Finite Difference Methods for Ordinary and Partial Differential Equations
    :param k: the order of the derivative
    :param xbar: the point at which the derivative is to be evaluated
    :param x: the set of points at which the function is known
    :return: the coefficients of the finite difference approximation

chop0

@nb.njit
def z(theta):  # funny bromwich contour
    return (
            .1446 + 3.0232 * theta ** 2 / (theta ** 2 - 3.0767 * np.pi ** 2)
            + 0.2339 * 1j * theta
    )


@nb.njit
def z_dash(theta, h=.001):