def getSearch(rootDir):
 dataPath = os.path.abspath(os.path.join(rootDir, 'datasets', 'scalar_1.csv'))
 streamDef = dict(version=1, info='testSpatialClassification', streams=[dict(source=('file://%s' % dataPath), info='scalar_1.csv', columns=['*'])])
 expDesc = {'environment': 'nupic', 'inferenceArgs': {'predictedField': 'classification', 'predictionSteps': [0]}, 'inferenceType': 'MultiStep', 'streamDef': streamDef, 'includedFields': [{'fieldName': 'field1', 'fieldType': 'float'}, {'fieldName': 'classification', 'fieldType': 'string'}, {'fieldName': 'randomData', 'fieldType': 'float'}], 'iterationCount': (-1)}
 return expDesc

def getSearch ( rootDir ) : dataPath = os . path . abspath ( os . path . join ( rootDir , 'datasets' , 'scalar_1.csv' ) ) streamDef = dict ( version = 1 , info = 'testSpatialClassification' , streams = [ dict ( source = ( 'file://%s' % dataPath ) , info = 'scalar_1.csv' , columns = [ '*' ] ) ] ) expDesc = { 'environment' : 'nupic' , 'inferenceArgs' : { 'predictedField' : 'classification' , 'predictionSteps' : [ 0 ] } , 'inferenceType' : 'MultiStep' , 'streamDef' : streamDef , 'includedFields' : [ { 'fieldName' : 'field1' , 'fieldType' : 'float' } , { 'fieldName' : 'classification' , 'fieldType' : 'string' } , { 'fieldName' : 'randomData' , 'fieldType' : 'float' } ] , 'iterationCount' : ( - 1 ) } return expDesc
this method returns search description .