85 lines
2.8 KiB
Python
85 lines
2.8 KiB
Python
# Copyright 2014 Hewlett-Packard Development Company, L.P.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import matplotlib
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import matplotlib.dates as dates
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import matplotlib.pyplot as plt
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from oslo_config import cfg
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import pandas as pd
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from subunit2sql.analysis import utils
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from subunit2sql.db import api
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CONF = cfg.CONF
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matplotlib.style.use('ggplot')
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def set_cli_opts(parser):
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parser.add_argument('test_id', nargs='?',
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help='Test id to extract time series for. This '
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'previously took a UUID from the tests.id '
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'column, however this will no longer work. It '
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'only works with a value from tests.test_id.')
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def generate_series():
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session = api.get_session()
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test_id = api.get_id_from_test_id(CONF.command.test_id, session)
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if not test_id:
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print("The test_id %s was not found in the database" %
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CONF.command.test_id)
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exit(2)
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run_times = api.get_test_run_time_series(test_id, session)
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if not run_times:
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print("There was no data found in the database")
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exit(3)
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if not CONF.title:
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test = api.get_test_by_id(test_id, session)
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session.close()
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ts = pd.Series(run_times)
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ts = utils.filter_dates(ts)
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if ts.count() == 0:
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print("No data available. Check your query and try again.")
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exit(-1)
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roll = ts.rolling(window=20, center=False)
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mean = roll.mean()
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rolling_std = roll.std()
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plt.figure()
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if not CONF.title:
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plt.title(test.test_id)
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else:
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plt.title(CONF.title)
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plt.ylabel('Time (sec.)')
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# format x-axis with dates
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fig, ax = plt.subplots(1)
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fig.autofmt_xdate()
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xfmt = dates.DateFormatter("%b %d %Y")
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ax.xaxis_date()
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ax.xaxis.set_major_formatter(xfmt)
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plt.plot(ts.index, ts, 'ko', label='Run Time', markersize=0.45)
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plt.plot(mean.index, mean, 'b', label='Avg. Run Time', linewidth=0.45)
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upper_std_dev = mean + 2 * rolling_std
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lower_std_dev = mean - 2 * rolling_std
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# Set negative numbers to 0
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lower_std_dev[lower_std_dev < 0] = 0
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plt.fill_between(rolling_std.index, upper_std_dev,
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lower_std_dev, color='b', alpha=0.2,
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label='std dev')
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plt.legend()
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plt.savefig(CONF.output, dpi=CONF.dpi)
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return ts
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