def test_get_stream_gaps():
"""TimeseriesUtility_test.test_get_stream_gaps()
confirms that gaps are found in a stream
"""
stream = Stream([
__create_trace('H', [numpy.nan, 1, 1, numpy.nan, numpy.nan]),
__create_trace('Z', [0, 0, 0, 1, 1, 1])
])
for trace in stream:
# set time of first sample
trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
# set sample rate to 1 second
trace.stats.delta = 1
# find gaps
gaps = TimeseriesUtility.get_stream_gaps(stream)
assert_equals(len(gaps['H']), 2)
# gap at start of H
gap = gaps['H'][0]
assert_equals(gap[0], UTCDateTime('2015-01-01T00:00:00Z'))
assert_equals(gap[1], UTCDateTime('2015-01-01T00:00:00Z'))
# gap at end of H
gap = gaps['H'][1]
assert_equals(gap[0], UTCDateTime('2015-01-01T00:00:03Z'))
assert_equals(gap[1], UTCDateTime('2015-01-01T00:00:04Z'))
# no gaps in Z channel
assert_equals(len(gaps['Z']), 0)
def test_get_stream_gaps():
"""TimeseriesUtility_test.test_get_stream_gaps()
confirms that gaps are found in a stream
"""
stream = Stream([
__create_trace('H', [numpy.nan, 1, 1, numpy.nan, numpy.nan]),
__create_trace('Z', [0, 0, 0, 1, 1, 1])
])
for trace in stream:
# set time of first sample
trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
# set sample rate to 1 second
trace.stats.delta = 1
# find gaps
gaps = TimeseriesUtility.get_stream_gaps(stream)
assert_equals(len(gaps['H']), 2)
# gap at start of H
gap = gaps['H'][0]
assert_equals(gap[0], UTCDateTime('2015-01-01T00:00:00Z'))
assert_equals(gap[1], UTCDateTime('2015-01-01T00:00:00Z'))
# gap at end of H
gap = gaps['H'][1]
assert_equals(gap[0], UTCDateTime('2015-01-01T00:00:03Z'))
assert_equals(gap[1], UTCDateTime('2015-01-01T00:00:04Z'))
# no gaps in Z channel
assert_equals(len(gaps['Z']), 0)
def test_get_stream_gaps_channels():
"""TimeseriesUtility_test.test_get_stream_gaps_channels()
test that gaps are only checked in specified channels.
"""
stream = Stream([
__create_trace("H", [numpy.nan, 1, 1, numpy.nan, numpy.nan]),
__create_trace("Z", [0, 0, 0, 1, 1, 1]),
])
for trace in stream:
# set time of first sample
trace.stats.starttime = UTCDateTime("2015-01-01T00:00:00Z")
# set sample rate to 1 second
trace.stats.delta = 1
# find gaps
gaps = TimeseriesUtility.get_stream_gaps(stream, ["Z"])
assert_equal("H" in gaps, False)
assert_equal(len(gaps["Z"]), 0)
def test_get_stream_gaps_channels():
"""TimeseriesUtility_test.test_get_stream_gaps_channels()
test that gaps are only checked in specified channels.
"""
stream = Stream
stream = Stream([
__create_trace('H', [numpy.nan, 1, 1, numpy.nan, numpy.nan]),
__create_trace('Z', [0, 0, 0, 1, 1, 1])
])
for trace in stream:
# set time of first sample
trace.stats.starttime = UTCDateTime('2015-01-01T00:00:00Z')
# set sample rate to 1 second
trace.stats.delta = 1
# find gaps
gaps = TimeseriesUtility.get_stream_gaps(stream, ['Z'])
assert_equals('H' in gaps, False)
assert_equals(len(gaps['Z']), 0)
def print_observatories(args):
"""Print all the observatories
Parameters
---------
args: dictionary
Holds all the command line arguments. See parse_args
Returns
-------
Boolean: if a warning was issued.
"""
intervals = args.intervals
channels = args.channels
starttime = args.starttime
endtime = args.endtime
host = args.edge_host
table_header = get_table_header()
warning_issued = False
table_end = \
'</tbody>\n' + \
'</table>\n'
for observatory in args.observatories:
summary_table = ''
gap_details = ''
print_it = False
summary_header = '<p>Observatory: %s </p>\n' % observatory
summary_table += table_header
for interval in intervals:
factory = edge.EdgeFactory(host=host,
port=2060,
observatory=observatory,
type=args.type,
channels=channels,
locationCode=args.locationcode,
interval=interval)
timeseries = factory.get_timeseries(starttime=starttime,
endtime=endtime)
gaps = TimeseriesUtility.get_stream_gaps(timeseries)
if args.gaps_only and not has_gaps(gaps):
continue
else:
print_it = True
warning = ''
warning_threshold = calculate_warning_threshold(
args.warning_threshold, interval)
summary_table += '<tr>'
summary_table += '<td style="text-align:center;">'
summary_table += ' %sS \n </td></tr>\n' % interval.upper()
gap_details += ' %sS <br>\n' % interval.upper()
for channel in channels:
gap = gaps[channel]
trace = timeseries.select(channel=channel)[0]
total = get_gap_total(gap, interval)
percentage, count = calculate_gap_percentage(total, trace)
last = get_last_time(gap, endtime)
summary_table += '<tr>\n'
summary_table += '<td style="text-align:center;">%s</td>' % \
channel
summary_table += '<td style="text-align:center;">%s</td>' % \
format_time(last)
summary_table += '<td style="text-align:center;">%d</td>' % \
len(gap)
summary_table += '<td style="text-align:center;">%d %s</td>' \
% (total, interval)
summary_table += '<td style="text-align:center;">%0.2f%%</td>'\
% percentage
summary_table += '<td style="text-align:center;">%d</td>' \
% count
summary_table += '</tr>\n'
if endtime - last > warning_threshold:
warning += '%s ' % channel
warning_issued = True
# Gap Detail
gap_details += ' Channel: %s <br>\n' % channel
gap_details += get_gaps(gap) + '\n'
if len(warning):
summary_header += 'Warning: Channels older then ' + \
'warning-threshold ' + \
'%s %ss<br>\n' % (warning, interval)
summary_table += table_end
if print_it:
print(summary_header)
print(summary_table)
print(gap_details)
return warning_issued
def print_observatories(args):
"""Print all the observatories
Parameters
---------
args: dictionary
Holds all the command line arguments. See parse_args
Returns
-------
Boolean: if a warning was issued.
"""
intervals = args.intervals
channels = args.channels
starttime = args.starttime
endtime = args.endtime
host = args.edge_host
table_header = get_table_header()
warning_issued = False
table_end = \
'</tbody>\n' + \
'</table>\n'
for observatory in args.observatories:
summary_table = ''
gap_details = ''
print_it = False
summary_header = '<p>Observatory: %s </p>\n' % observatory
summary_table += table_header
for interval in intervals:
factory = edge.EdgeFactory(
host=host,
port=2060,
observatory=observatory,
type=args.type,
channels=channels,
locationCode=args.locationcode,
interval=interval)
timeseries = factory.get_timeseries(
starttime=starttime,
endtime=endtime)
gaps = TimeseriesUtility.get_stream_gaps(timeseries)
if args.gaps_only and not has_gaps(gaps):
continue
else:
print_it = True
warning = ''
warning_threshold = calculate_warning_threshold(
args.warning_threshold, interval)
summary_table += '<tr>'
summary_table += '<td style="text-align:center;">'
summary_table += ' %sS \n </td></tr>\n' % interval.upper()
gap_details += ' %sS <br>\n' % interval.upper()
for channel in channels:
gap = gaps[channel]
trace = timeseries.select(channel=channel)[0]
total = get_gap_total(gap, interval)
percentage, count = calculate_gap_percentage(total, trace)
last = get_last_time(gap, endtime)
summary_table += '<tr>\n'
summary_table += '<td style="text-align:center;">%s</td>' % \
channel
summary_table += '<td style="text-align:center;">%s</td>' % \
format_time(last)
summary_table += '<td style="text-align:center;">%d</td>' % \
len(gap)
summary_table += '<td style="text-align:center;">%d %s</td>' \
% (total, interval)
summary_table += '<td style="text-align:center;">%0.2f%%</td>'\
% percentage
summary_table += '<td style="text-align:center;">%d</td>' \
% count
summary_table += '</tr>\n'
if endtime - last > warning_threshold:
warning += '%s ' % channel
warning_issued = True
# Gap Detail
gap_details += ' Channel: %s <br>\n' % channel
gap_details += get_gaps(gap) + '\n'
if len(warning):
summary_header += 'Warning: Channels older then ' + \
'warning-threshold ' + \
'%s %ss<br>\n' % (warning, interval)
summary_table += table_end
if print_it:
print summary_header
print summary_table
print gap_details
return warning_issued
