reevik

object Knapsack {
  val W = 10000 // capacity
  val n = 100   // number of items 
  val file = "path-to-your-file-contains-<size> <weight> lines"
  val c = Array.ofDim[Int](n, W)
  val lines = Source.fromFile(file).getLines.drop(1).toList.map(_.split(" ").map(_.toInt))
  def main(args: Array[String]) {
    0 until W foreach { x =>  c(0)(x) = 0 }
    for (i <- 1 until n; x <- 0 until W) c(i)(x) = math.max(c(i - 1)(x), { if (lines(i)(1) > x) 0 else c(i - 1)(x - lines(i)(1)) + lines(i)(0) })
    print(c(n-1)(W-1))

reevik

^[[1;31m
        yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy
        yyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyyy
        yyyyy/                  +yyyyyyyyyyyyyy+                  +y///y
        yyyyy/                 /yyyyyyyyyyyyyyyy:                 +yo+oy
        yyyyy/                -yyyyyyyyyyyyyyyyyy-                +yyyyy
        yyyyy/               .syyyyyyyyyyyyyyyyyys.               +yyyyy
        yyyyy/              `syyyyyyyyyyyyyyyyyyyys`              +yyyyy
        yyyyy/             `oyyyyyyyyyyyyyyyyyyyyyy+`             +yyyyy
        yyyyy/             +yyyyyyyyyyyyyyyyyyyyyyyy/             +yyyyy

reevik

package io.moo.training.akka
 
import akka.actor.{Actor, Props}
 
class CounterActor extends Actor {
  var counter: Int = 0
 
  override def receive: Receive = {
    case "incr" => counter += 1
    case "get" => sender ! counter

reevik

def get_numpy_data(data_sframe, features, output):
    data_sframe['constant'] = 1 # this is how you add a constant column to an SFrame
    # add the column 'constant' to the front of the features list so that we can extract it along with the others:
    features = ['constant'] + features # this is how you combine two lists
    # select the columns of data_SFrame given by the features list into the SFrame features_sframe (now including constant):
    features_sframe = data_sframe[features]
    # the following line will convert the features_SFrame into a numpy matrix:
    feature_matrix = features_sframe.to_numpy()
    # assign the column of data_sframe associated with the output to the SArray output_sarray
    output_sarray = data_sframe['price']

reevik

package io.ryos.demos.fibers;

import static java.lang.System.out;

import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.SynchronousQueue;

public class FiberDemo {

reevik

package io.ryos.demos.continuations;

import static java.lang.System.out;
import java.util.Arrays;
import java.util.List;

public class ContinuationDemo {

  public static void main(String[] args) {
    var scope = new ContinuationScope("my-scope");

reevik

# The meeting matrix can be improved with constraints e.g output has minimum waiting person and 
# shortest total duration by using constraing programming or linear optimization. 
# The problem is very similar to N-Queens.
# Right now you can find optimum solution by running the code multiple times. 

import itertools
import random
from datetime import datetime, timedelta

team  = ['Erhan', 'Brown', 'Mustermann', 'Jack', 'Joe', 'Rambo', 'Steve']

reevik

package io.ryos.rhino.sdk.simulations;

import static io.ryos.rhino.sdk.dsl.specs.DSLSpec.http;
import static io.ryos.rhino.sdk.dsl.specs.HttpSpec.from;
import static io.ryos.rhino.sdk.dsl.specs.UploadStream.file;
import static io.ryos.rhino.sdk.dsl.specs.builder.SessionAccessor.session;
import static io.ryos.rhino.sdk.utils.TestUtils.getEndpoint;

import io.ryos.rhino.sdk.SimulationConfig;
import io.ryos.rhino.sdk.annotations.Dsl;

reevik

@RampUp(startRps = 1, targetRps = 60, durationInMins = 1)
ohne max. connection und mit 1 sec response zeit, 
würde sowas erwarten:
   10s  20s  30s  40s  50s  60s
   55   210  465  820  1275 1830

weil pro Sekunde, +1 request Anstieg:
   1s 2s 3s ... 10s 
   1  2  3      10 = 55 total
   

reevik

sudo defaults write bluetoothaudiod "Enable AptX codec" -bool true
sudo defaults read bluetoothaudiod