24 from daal
import step1Local, step2Master
25 from daal.algorithms
import covariance
27 utils_folder = os.path.realpath(os.path.abspath(os.path.dirname(os.path.dirname(__file__))))
28 if utils_folder
not in sys.path:
29 sys.path.insert(0, utils_folder)
30 from utils
import printNumericTable, createSparseTable
32 DAAL_PREFIX = os.path.join(
'..',
'data')
38 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_1.csv'),
39 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_2.csv'),
40 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_3.csv'),
41 os.path.join(DAAL_PREFIX,
'distributed',
'covcormoments_csr_4.csv')
44 partialResult = [0] * nBlocks
48 def computestep1Local(block):
51 dataTable = createSparseTable(datasetFileNames[block])
54 algorithm = covariance.Distributed(step1Local, method=covariance.fastCSR)
57 algorithm.input.set(covariance.data, dataTable)
60 partialResult[block] = algorithm.compute()
63 def computeOnMasterNode():
67 algorithm = covariance.Distributed(step2Master, method=covariance.fastCSR)
70 for i
in range(nBlocks):
71 algorithm.input.add(covariance.partialResults, partialResult[i])
77 result = algorithm.finalizeCompute()
79 if __name__ ==
"__main__":
81 for i
in range(nBlocks):
86 printNumericTable(result.get(covariance.covariance),
"Covariance matrix (upper left square 10*10) :", 10, 10)
87 printNumericTable(result.get(covariance.mean),
"Mean vector:", 1, 10)