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correlation_distance.py
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# ==============================================================================
# Copyright 2014 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 correlation distance example for shared memory systems
import os
from pathlib import Path
import numpy as np
from readcsv import pd_read_csv
import daal4py as d4p
def main(readcsv=pd_read_csv):
data_path = Path(__file__).parent.parent / "daal4py" / "data" / "batch"
data_file = data_path / "distance.csv"
data = readcsv(data_file, usecols=range(10))
# Create algorithm to compute correlation distance (no parameters)
algorithm = d4p.correlation_distance()
# Computed correlation distance with file or numpy array
res1 = algorithm.compute(str(data_file))
res2 = algorithm.compute(data)
assert np.allclose(res1.correlationDistance, res2.correlationDistance)
return res1
if __name__ == "__main__":
res = main()
print(
"\nCorrelation distance (first 15 rows/columns):\n",
res.correlationDistance[0:15, 0:15],
)
print("All looks good!")