#=============================================================================== # Copyright 2014-2021 Intel Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. #=============================================================================== # daal4py cholesky example for shared memory systems import daal4py as d4p import numpy as np # let's try to use pandas' fast csv reader try: import pandas def read_csv(f, c, t=np.float64): return pandas.read_csv(f, usecols=c, delimiter=',', header=None, dtype=t) except ImportError: # fall back to numpy loadtxt def read_csv(f, c, t=np.float64): return np.loadtxt(f, usecols=c, delimiter=',', ndmin=2) def main(readcsv=read_csv, method='defaultDense'): infile = "./data/batch/cholesky.csv" # configure a cholesky object algo = d4p.cholesky() # let's provide a file directly, not a table/array return algo.compute(infile) # cholesky result objects provide choleskyFactor if __name__ == "__main__": result = main() print("\nFactor:\n", result.choleskyFactor) print('All looks good!')