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normalization_minmax.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 normalization minmax example for shared memory systems
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 / "data" / "batch"
infile = data_path / "normalization.csv"
# configure a covariance object
algo = d4p.normalization_minmax(lowerBound=-1.0, upperBound=1.0)
# let's provide a file directly, not a table/array
result1 = algo.compute(str(infile))
# We can also load the data ourselfs and provide the numpy array
data = readcsv(infile)
result2 = algo.compute(data)
# covariance result objects provide correlation, covariance and mean
assert np.allclose(result1.normalizedData, result2.normalizedData)
return result1
if __name__ == "__main__":
res = main()
print("MinMax result (first 5 rows):\n", res.normalizedData[:5])
print("All looks good!")