#===============================================================================
# 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 SVD example for streaming on 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, s=0, n=None, t=np.float64):
        return pandas.read_csv(f, usecols=c, delimiter=',',
                               header=None, skiprows=s, nrows=n, dtype=t)
except:
    # fall back to numpy genfromtxt
    def read_csv(f, c, s=0, n=np.iinfo(np.int64).max):
        a = np.genfromtxt(f, usecols=c, delimiter=',', skip_header=s, max_rows=n)
        if a.shape[0] == 0:
            raise Exception("done")
        if a.ndim == 1:
            return a[:, np.newaxis]
        return a


def main(readcsv=read_csv, method='defaultDense'):
    infiles = ["./data/distributed/svd_{}.csv".format(i) for i in range(1, 5)]

    # configure a SVD object
    algo = d4p.svd(streaming=True)

    # let's provide files directly, not a tables/arrays
    # Feed file by file
    for infile in infiles:
        algo.compute(infile)

    # All files are done, now finalize the computation
    result = algo.finalize()

    # SVD result objects provide leftSingularMatrix,
    # rightSingularMatrix and singularValues
    return result


if __name__ == "__main__":
    result = main()
    print("\nSingular values:\n", result.singularValues)
    print("\nRight orthogonal matrix V:\n", result.rightSingularMatrix)
    print(
        "\nLeft orthogonal matrix U (first 10 rows):\n",
        result.leftSingularMatrix[0:10]
    )
    print('All looks good!')