code: def ReadNistData(dataset):
      """NIST STRD data is in a simple, fixed format with
      line numbers being significant!
      """
      finp = open(os.path.join(NIST_DIR, f"{dataset}.dat"))
      lines = [line[:-1] for line in finp.readlines()]
      finp.close()
      ModelLines = lines[30:39]
      ParamLines = lines[40:58]
      DataLines = lines[60:]
  
      words = ModelLines[1].strip().split()
      nparams = int(words[0])
  
      start1 = [0] * nparams
      start2 = [0] * nparams
      certval = [0] * nparams
      certerr = [0] * nparams
      for i, text in enumerate(ParamLines[:nparams]):
          [s1, s2, val, err] = [
              float(x) for x in text.split("=")[1].split()
          ]
          start1[i] = s1
          start2[i] = s2
          certval[i] = val
          certerr[i] = err
  
      for t in ParamLines[nparams:]:
          t = t.strip()
          if ":" not in t:
              continue
          val = float(t.split(":")[1])
          if t.startswith("Residual Sum of Squares"):
              sum_squares = val
          elif t.startswith("Residual Standard Deviation"):
              std_dev = val
          elif t.startswith("Degrees of Freedom"):
              nfree = int(val)
          elif t.startswith("Number of Observations"):
              ndata = int(val)
  
      y, x = [], []
      for d in DataLines:
          vals = [float(i) for i in d.strip().split()]
          y.append(vals[0])
          if len(vals) > 2:
              x.append(vals[1:])
          else:
              x.append(vals[1])
  
      y = array(y)
      x = array(x)
      out = {
          "y": y,
          "x": x,
          "nparams": nparams,
          "ndata": ndata,
          "nfree": nfree,
          "start1": start1,
          "start2": start2,
          "sum_squares": sum_squares,
          "std_dev": std_dev,
          "cert": certval,
          "cert_values": certval,
          "cert_stderr": certerr,
      }
      return out
  
imports: import os
  from numpy import arctan, array, cos, exp, log, sin
  from lmfit import Parameters
label_desc: Use image node_id 24 for calling a global function with example usage: ReadNistData(dataset) and returns: out