24 from daal
import step1Local, step2Master
25 from daal.algorithms
import covariance
26 from daal.data_management
import FileDataSource, DataSourceIface
28 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
29 if utils_folder
not in sys.path:
30 sys.path.insert(0, utils_folder)
31 from utils
import printNumericTable
33 DAAL_PREFIX = os.path.join(
'..',
'data')
39 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_dense_1.csv'),
40 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_dense_2.csv'),
41 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_dense_3.csv'),
42 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_dense_4.csv')
45 partialResult = [0] * nBlocks
49 def computestep1Local(block):
53 dataSource = FileDataSource(
54 datasetFileNames[block], DataSourceIface.doAllocateNumericTable,
55 DataSourceIface.doDictionaryFromContext
59 dataSource.loadDataBlock()
62 algorithm = covariance.Distributed(step1Local)
65 algorithm.input.set(covariance.data, dataSource.getNumericTable())
68 partialResult[block] = algorithm.compute()
71 def computeOnMasterNode():
75 algorithm = covariance.Distributed(step2Master)
78 for i
in range(nBlocks):
79 algorithm.input.add(covariance.partialResults, partialResult[i])
82 algorithm.parameter.outputMatrixType = covariance.correlationMatrix
88 result = algorithm.finalizeCompute()
90 if __name__ ==
"__main__":
92 for i
in range(nBlocks):
97 printNumericTable(result.get(covariance.correlation),
"Correlation matrix:")
98 printNumericTable(result.get(covariance.mean),
"Mean vector:")