examples/daal4py/low_order_moms_spmd.py

# ==============================================================================
# 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
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# ==============================================================================

# daal4py low order moments example for distributed memory systems; SPMD mode
# run like this:
#    mpirun -n 4 python ./low_order_moms_spmd.py

from pathlib import Path

from readcsv import pd_read_csv

# let's use a reading of file in chunks (defined in spmd_chunks_read.py)
from spmd_chunks_read import get_chunk_params

import daal4py as d4p


def main(readcsv=pd_read_csv):
    data_path = Path(__file__).parent / "data" / "batch"
    infile = data_path / "covcormoments_dense.csv"

    # We know the number of lines in the file
    # and use this to separate data between processes
    skiprows, nrows = get_chunk_params(
        lines_count=200, chunks_count=d4p.num_procs(), chunk_number=d4p.my_procid()
    )

    # Each process reads its chunk of the file
    data = readcsv(infile, skip_header=skiprows, max_rows=nrows)

    # Create algorithm with distributed mode
    alg = d4p.low_order_moments(distributed=True)

    # Perform computation
    res = alg.compute(data)

    # result provides minimum, maximum, sum, sumSquares, sumSquaresCentered,
    # mean, secondOrderRawMoment, variance, standardDeviation, variation
    assert all(
        getattr(res, name).shape == (1, data.shape[1])
        for name in [
            "minimum",
            "maximum",
            "sum",
            "sumSquares",
            "sumSquaresCentered",
            "mean",
            "secondOrderRawMoment",
            "variance",
            "standardDeviation",
            "variation",
        ]
    )

    return res


if __name__ == "__main__":
    # Initialize SPMD mode
    d4p.daalinit()
    res = main()
    # result is available on all processes - but we print only on root
    if d4p.my_procid() == 0:
        print(res)
    d4p.daalfini()