src/nupic/data/aggregator.py
def _aggr_mode(inList):
  """ Returns most common value seen in the non-None elements of the list
  """

  valueCounts = dict()
  nonNone = 0

  for elem in inList:
    if elem == SENTINEL_VALUE_FOR_MISSING_DATA:
      continue

    nonNone += 1
    if elem in valueCounts:
      valueCounts[elem] += 1
    else:
      valueCounts[elem] = 1

  # Get the most common one
  if nonNone == 0:
    return None

  # Sort by counts
  sortedCounts = valueCounts.items()
  sortedCounts.sort(cmp=lambda x,y: x[1] - y[1], reverse=True)
  return sortedCounts[0][0]
def _aggr_mode(inList):
  """ Returns most common value seen in the non-None elements of the list
  """

  valueCounts = dict()
  nonNone = 0

  for elem in inList:
    if elem == SENTINEL_VALUE_FOR_MISSING_DATA:
      continue

    nonNone += 1
    if elem in valueCounts:
      valueCounts[elem] += 1
    else:
      valueCounts[elem] = 1

  # Get the most common one
  if nonNone == 0:
    return None

  # Sort by counts
  sortedCounts = valueCounts.items()
  sortedCounts.sort(cmp=lambda x,y: x[1] - y[1], reverse=True)
  return sortedCounts[0][0]
def _aggr_mode ( inList ) : valueCounts = dict ( ) nonNone = 0 for elem in inList : if elem == SENTINEL_VALUE_FOR_MISSING_DATA : continue nonNone += 1 if elem in valueCounts : valueCounts [ elem ] += 1 else : valueCounts [ elem ] = 1 # Get the most common one if nonNone == 0 : return None # Sort by counts sortedCounts = valueCounts . items ( ) sortedCounts . sort ( cmp = lambda x , y : x [ 1 ] - y [ 1 ] , reverse = True ) return sortedCounts [ 0 ] [ 0 ]
Returns most common value seen in the non-None elements of the list
Returns most common value seen in the non - None elements of the list