22 from daal
import step1Local, step2Master
23 from daal.algorithms
import covariance
25 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
26 if utils_folder
not in sys.path:
27 sys.path.insert(0, utils_folder)
28 from utils
import printNumericTable, createSparseTable
30 DAAL_PREFIX = os.path.join(
'..',
'data')
36 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_1.csv'),
37 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_2.csv'),
38 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_3.csv'),
39 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_4.csv')
42 partialResult = [0] * nBlocks
46 def computestep1Local(block):
49 dataTable = createSparseTable(datasetFileNames[block])
52 algorithm = covariance.Distributed(step1Local, method=covariance.fastCSR)
55 algorithm.input.set(covariance.data, dataTable)
58 partialResult[block] = algorithm.compute()
61 def computeOnMasterNode():
65 algorithm = covariance.Distributed(step2Master, method=covariance.fastCSR)
68 for i
in range(nBlocks):
69 algorithm.input.add(covariance.partialResults, partialResult[i])
72 algorithm.parameter.outputMatrixType = covariance.correlationMatrix
78 result = algorithm.finalizeCompute()
80 if __name__ ==
"__main__":
82 for i
in range(nBlocks):
87 printNumericTable(result.get(covariance.correlation),
"Correlation matrix (upper left square 10*10) :", 10, 10)
88 printNumericTable(result.get(covariance.mean),
"Mean vector:", 1, 10)