#!/usr/bin/env python
#
# Workload Automation v2 for LAVA
#
# Copyright (C) 2014, Linaro Limited.
#
# This program is free software; you can redistribute it and/or
# modify it under the terms of the GNU General Public License
# as published by the Free Software Foundation; either version 2
# of the License, or (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program; if not, write to the Free Software
# Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301, USA.
#
# Author: Milosz Wasilewski <milosz.wasilewski@linaro.org>
#

import sqlite3
from copy import deepcopy
from numpy import array, mean
from optparse import OptionParser

SQLITE_DB_GLOBAL_PATH = "/root/db_results/"

modes_prepares_statement = "select distinct(id) from workload_specs;"
metric_prepared_statement = """SELECT label as workload, metric, value, units, wsr.spec_id
FROM metrics AS m INNER JOIN (
SELECT ws.OID as spec_oid, ws.id as spec_id, uuid, label
FROM workload_specs AS ws INNER JOIN runs AS r ON ws.run_oid = r.OID
) AS wsr ON wsr.spec_oid = m.spec_oid
WHERE metric = ? AND spec_id = ?;"""

metrics_common = ['execution_time', 'arm,vexpress-energy A7 Jcore', 'arm,vexpress-energy A15 Jcore']
metrics_bbench = ['Performance']

if __name__ == '__main__':

    usage = "usage: %prog [OPTIONS]"
    parser = OptionParser(usage=usage)
    parser.add_option("-n", "--job-name", dest="job_name",
                  help="Job name to be used as db name in agenda file")
    (options, args) = parser.parse_args()

    if not options.job_name:
        parser.error("Job name missing")

    conn = sqlite3.connect(SQLITE_DB_GLOBAL_PATH + options.job_name + ".db")
    modes_cursor = conn.cursor()
    for mode_row in modes_cursor.execute(modes_prepares_statement):
        metrics_local = deepcopy(metrics_common)
        if 'bbench' in mode_row[0]:
            metrics_local = metrics_local + metrics_bbench
        for metric in metrics_local:
            params = (metric, mode_row[0])
            metric_values = []
            metric_cursor = conn.cursor()
            units = ""
            for metric_row in metric_cursor.execute(metric_prepared_statement, params):
                metric_values.append(float(metric_row[2]))
                units = metric_row[3]
            print "%s_%s Measurement:%s Units:%s Result:pass" % (
                mode_row[0], 
                metric.replace(" ", "_").replace(",", "_"), 
                mean(array(metric_values)), 
                units)
            metric_cursor.close()
    modes_cursor.close()
    conn.close()