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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def computeScaledProbabilities( listOfScales=[1.0, 1.5, 2.0, 2.5, 3.0, 3.5, 4.0], listofkValues=[64, 128, 256], kw=32, n=1000, numWorkers=10, nTrials=1000, ):
 """ Compute the impact of S on match probabilities for a fixed value of n. """

  # Create arguments for the possibilities we want to test
  args = []
  theta, _ = getTheta(kw)
  for ki, k in enumerate(listofkValues):
    for si, s in enumerate(listOfScales):
      args.append({
          "k": k, "kw": kw, "n": n, "theta": theta,
          "nTrials": nTrials, "inputScaling": s,
          "errorIndex": [ki, si],
          })

  result = computeMatchProbabilityParallel(args, numWorkers)

  errors = np.zeros((len(listofkValues), len(listOfScales)))
  for r in result:
    errors[r["errorIndex"][0], r["errorIndex"][1]] = r["pctMatches"]

  print("Errors using scaled inputs, for kw=", kw)
  print(repr(errors))
  plotScaledMatches(listofkValues, listOfScales, errors,
              "images/scalar_effect_of_scale_kw" + str(kw) + ".pdf")