main.py

# Copyright (c) 2016, MD2K Center of Excellence
# All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are met:
#
# * Redistributions of source code must retain the above copyright notice, this
# list of conditions and the following disclaimer.
#
# * Redistributions in binary form must reproduce the above copyright notice,
# this list of conditions and the following disclaimer in the documentation
# and/or other materials provided with the distribution.
#
# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

import argparse
import gzip
import time
import uuid


import os
import copy
from cerebralcortex.CerebralCortex import CerebralCortex
from cerebralcortex.data_processor.cStress import cStress
from cerebralcortex.data_processor.preprocessor import parser
from cerebralcortex.kernel.datatypes.datapoint import DataPoint
from cerebralcortex.kernel.datatypes.datastream import DataStream
from cerebralcortex.legacy import find
from cerebralcortex.model_development.model_development import cstress_model


argparser = argparse.ArgumentParser(description="Cerebral Cortex Test Application")
argparser.add_argument('--base_directory')
args = argparser.parse_args()

# To run this program, please specific a program argument for base_directory that is the path to the test data files.
# e.g. --base_directory /Users/hnat/data/
basedir = args.base_directory

configuration_file = os.path.join(os.path.dirname(__file__), 'cerebralcortex.yml')

CC = CerebralCortex(configuration_file, master="local[*]", name="Memphis cStress Development App")


def readfile(filename):
    data = []
    with gzip.open(filename, 'rt') as f:
        count = 0
        for l in f:
            dp = parser.data_processor(l)
            if isinstance(dp, DataPoint):
                data.append(dp)
                count += 1
            if count > 200000:
                break
    return data

def readfile_ground_truth(filename):
    data = []
    with gzip.open(filename, 'rt') as f:
        count = 0
        for l in f:
            dp = parser.ground_truth_data_processor(l)
            if isinstance(dp, DataPoint):
                data.append(dp)

    return data

def loader(identifier: int):
    participant = "SI%02d" % identifier

    participant_uuid = uuid.uuid4()

    try:
        ecg = DataStream(None, participant_uuid)
        ecg.data = readfile(find(basedir, {"participant": participant, "datasource": "ecg"}))

        rip = DataStream(None, participant_uuid)
        rip.data = readfile(find(basedir, {"participant": participant, "datasource": "rip"}))

        accelx = DataStream(None, participant_uuid)
        accelx.data = readfile(find(basedir, {"participant": participant, "datasource": "accelx"}))

        accely = DataStream(None, participant_uuid)
        accely.data = readfile(find(basedir, {"participant": participant, "datasource": "accely"}))

        accelz = DataStream(None, participant_uuid)
        accelz.data = readfile(find(basedir, {"participant": participant, "datasource": "accelz"}))

        stress_marks = DataStream(None, participant_uuid)
        stress_marks.data = readfile_ground_truth(find(basedir, {"participant": participant, "datasource": "stress_marks"}))

        return {"participant": participant, "ecg": ecg, "rip": rip, "accelx": accelx, "accely": accely,
                "accelz": accelz, "stress_marks": stress_marks}

    except Exception as e:
        print("File missing for %s" % participant)

        return {"ERROR": 'missing data file'}




start_time = time.time()

ids = CC.sparkSession.sparkContext.parallelize([i for i in range(3, 5)])

data = ids.map(lambda i: loader(i)).filter(lambda x: 'participant' in x)

cstress_feature_vector = cStress(data)

features = cstress_feature_vector.collect()

features2 = copy.deepcopy(features)

cstress_model = cstress_model(features=features2)

# results = ids.map(loader)
# pprint(results.collect())
end_time = time.time()
print(end_time - start_time)