def testAddRowsToCache(self):
self._AddMockData()
rows = []
stored_object.Set(
'externally_visible__num_revisions_ChromiumPerf/win7/dromaeo/dom',
[[10, 2, 3], [15, 4, 5], [100, 6, 7]])
test_key = utils.TestKey('ChromiumPerf/win7/dromaeo/dom')
test_container_key = utils.GetTestContainerKey(test_key)
ts1 = datetime.datetime(2013, 1, 1)
row1 = graph_data.Row(parent=test_container_key,
id=1, value=9, timestamp=ts1)
rows.append(row1)
ts2 = datetime.datetime(2013, 1, 2)
row2 = graph_data.Row(parent=test_container_key,
id=12, value=90, timestamp=ts2)
rows.append(row2)
ts3 = datetime.datetime(2013, 1, 3)
row3 = graph_data.Row(parent=test_container_key,
id=102, value=99, timestamp=ts3)
rows.append(row3)
graph_revisions.AddRowsToCache(rows)
self.assertEqual(
[[1, 9, utils.TimestampMilliseconds(ts1)],
[10, 2, 3],
[12, 90, utils.TimestampMilliseconds(ts2)],
[15, 4, 5], [100, 6, 7],
[102, 99, utils.TimestampMilliseconds(ts3)]],
stored_object.Get('externally_visible__num_revisions_'
'ChromiumPerf/win7/dromaeo/dom'))
def testPost_ReturnsAndCachesCorrectRevisions(self):
self._AddMockData()
response = self.testapp.post(
'/graph_revisions', {'test_path': 'ChromiumPerf/win7/dromaeo/dom'})
cached_rows = stored_object.Get(
'externally_visible__num_revisions_ChromiumPerf/win7/dromaeo/dom')
for index, row in enumerate(json.loads(response.body)):
expected_rev = 15000 + (index * 5)
expected_value = int(expected_rev) * 2.5
expected_timestamp = utils.TimestampMilliseconds(
datetime.datetime(2013, 8, 1))
self.assertEqual([expected_rev, expected_value, expected_timestamp], row)
self.assertEqual([expected_rev, expected_value, expected_timestamp],
cached_rows[index])
def _GetFlotJson(revision_map, tests):
"""Constructs JSON in the format expected by Flot.
Args:
revision_map: A dict which maps revision numbers to data point info.
tests: A list of TestMetadata entities.
Returns:
JSON serialization of a dict with line data, annotations, error range data,
(This data may not be passed exactly as-is to the Flot plot function, but
it will all be used when plotting.)
"""
# Each entry in the following dict is one Flot series object. The actual
# x-y values will be put into the 'data' properties for each object.
cols = {i: _FlotSeries(i, test) for i, test in enumerate(tests)}
flot_annotations = {}
flot_annotations['series'] = _GetSeriesAnnotations(tests)
# For each TestMetadata (which corresponds to a trace line), the shaded error
# region is specified by two series objects. For a demo, see:
# http://www.flotcharts.org/flot/examples/percentiles/index.html
error_bars = {
x: [{
'id': 'bottom_%d' % x,
'data': [],
'color': x,
'clickable': False,
'hoverable': False,
'lines': {
'show': True,
'lineWidth': 0,
'fill': 0.2,
},
'fillBetween': 'line_%d' % x,
}, {
'id': 'top_%d' % x,
'data': [],
'color': x,
'clickable': False,
'hoverable': False,
'lines': {
'show': True,
'lineWidth': 0,
'fill': 0.2,
},
'fillBetween': 'line_%d' % x,
}]
for x, _ in enumerate(tests)
}
test_keys = [t.key.urlsafe() for t in tests]
for revision in sorted(revision_map.keys()):
for series_index, key in enumerate(test_keys):
point_info = revision_map[revision].get(key, None)
if not point_info:
continue
timestamp = point_info.get('timestamp')
if timestamp and isinstance(timestamp, datetime.datetime):
point_info['timestamp'] = utils.TimestampMilliseconds(
timestamp)
# TODO(simonhatch): Need to filter out NaN values.
# https://github.com/catapult-project/catapult/issues/3474
point_list = [revision, point_info['value']]
if math.isnan(point_info['value']):
continue
if 'error' in point_info:
error = point_info['error']
error_bars[series_index][0]['data'].append(
[revision, point_info['value'] - error])
error_bars[series_index][1]['data'].append(
[revision, point_info['value'] + error])
cols[series_index]['data'].append(point_list)
data_index = len(cols[series_index]['data']) - 1
series_dict = flot_annotations.setdefault(series_index, {})
data_dict = copy.deepcopy(point_info)
del data_dict['value']
series_dict.setdefault(data_index, data_dict)
return json.dumps(
{
'data': cols,
'annotations': flot_annotations,
'error_bars': error_bars,
},
allow_nan=False)
def _MakeTriplet(row):
"""Makes a 3-item list of revision, value and timestamp for a Row."""
timestamp = utils.TimestampMilliseconds(row.timestamp)
return [row.revision, row.value, timestamp]
def _GetLastMondayTimestamp(): """Gets timestamp of 00:00 last Monday in milliseconds as an integer.""" today = datetime.date.today() monday = today - datetime.timedelta(days=today.weekday()) return utils.TimestampMilliseconds(monday)
def _FormatTimestampMilliseconds(self, timestamp_string): time = datetime.datetime.strptime(timestamp_string, '%Y-%m-%dT%H:%M:%S') return utils.TimestampMilliseconds(time)
