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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 probes_used_extract_scores(full_scores, same_probes):
 """Extracts a matrix of scores for a model, given a probes_used row vector of boolean"""

  if full_scores.shape[1] != same_probes.shape[0]: raise "Size mismatch"
  import numpy as np
  model_scores = np.ndarray((full_scores.shape[0],np.sum(same_probes)), 'float64')
  c=0
  for i in range(0,full_scores.shape[1]):
    if same_probes[i]:
      for j in range(0,full_scores.shape[0]):
        model_scores[j,c] = full_scores[j,i]
      c+=1
  return model_scores