def __init__(self,
for_log,
source,
normal_ranges=check_range.AllInclusiveRange(),
warning_ranges=check_range.AllInclusiveRange()):
self._source = source
super(BaseSeptentrioCheck, self).__init__(for_log, normal_ranges,
warning_ranges)
def __init__(self,
for_log,
gps_type_per_source,
normal_ranges=check_range.AllInclusiveRange(),
warning_ranges=check_range.AllInclusiveRange()):
assert 'FcA' in gps_type_per_source and 'FcB' in gps_type_per_source
self._gps_type_per_source = gps_type_per_source
super(AgreementCheck, self).__init__(for_log, normal_ranges,
warning_ranges)
def __init__(self,
for_log,
normal_ranges=check_range.AllInclusiveRange(),
warning_ranges=check_range.AllInclusiveRange(),
name=None,
sort_by_sequence=True):
"""Initialize a check.
Args:
for_log: True if this check targets log data. False if it checks
AIO messages.
normal_ranges: A BaseRange object in which values are regarded as normal.
warning_ranges: A BaseRange object in which values should raise warnings,
if they fall out of normal_ranges. Values falling out of
warning_ranges should raise errors.
name: Name of the check.
sort_by_sequence: If true, messages will be sorted by sequence number,
instead of orderd by time of receiving.
Raises:
ValueError: Raised if the __init__ function is not decorated with
RegisterSpecs.
"""
# Values that fall within any of the normal ranges are normal.
self._normal_ranges = check_range.BuildRanges(normal_ranges)
# Values that fall outside of all normal ranges but inside any warning
# ranges raise warnings. If the values fall even out of the warning
# ranges, then they raise errors.
self._warning_ranges = check_range.BuildRanges(warning_ranges)
# Name of the check.
self._name = name
# True if the inputs should be sorted by sequence (marked at sender).
self._sort_by_sequence = sort_by_sequence
# Results of the check.
if for_log:
# If the check processes a log file, the result is formed as
# {<check_name>:
# {<warning_level>: {"total": ..., "count": ..., "range": ...}}}.
self._results = {}
else:
# If the check processes AIO messages, the resut is formed as
# [{"name": ..., "value": ..., "stoplight": ...}, ...]
self._results = []
# Inputs needed by the check, in the form of a list of DataIndex objects.
self._fields = self._RegisterInputs()
# True if the check is performed over log data instead of AIO messages.
self._for_log = for_log
if not hasattr(self, '_kwargs'):
raise ValueError(
'%s.__init__ is missing the "@base.check.RegisterSpecs" decorate.'
% type(self).__name__)
# Merge selected regions into one section if their distance is less than
# this parameter.
self._min_gap = _DEFAULT_MIN_GAP
def CheckForFailure(values, target_ranges, error_if_fail, name):
"""Checking values against normal ranges.
Args:
values: Values of the field.
target_ranges: A BaseRange object in which values are regarded as normal.
It can also be a list of basic objects that create BaseRange objects.
Please refer to check_range.RangeChecker for details.
error_if_fail: True if failed values raise errors,
otherwise they raise warnings.
name: Name of the check.
Returns:
Check results in the form of {
warning_name: {
'total': ..., # Total number of samples.
'count': ..., # Number of samples in this range.
'range': [min_value, max_value],
},
error_name: {...}
}
"""
if error_if_fail:
return CheckByRange(values, target_ranges,
check_range.AllExclusiveRange(), name)
else:
return CheckByRange(values, target_ranges,
check_range.AllInclusiveRange(), name)
def GetChecker(mapping, check_type, default):
value = mapping.get(check_type, default)
if value == 'any':
return check_range.AllInclusiveRange()
elif value is None:
# No checks for this type.
return None
else:
return check_range.RangeChecker(value)
def __init__(self,
for_log,
window_size,
window_step,
normal_ranges,
warning_ranges=check_range.AllInclusiveRange(),
name=None):
super(FilteredCheckItem, self).__init__(for_log, normal_ranges,
warning_ranges, name)
self._window_size = window_size
assert window_size >= 1
self._window_step = window_step if window_step else window_size
if not self._for_log:
self._history = collections.defaultdict(
lambda: collections.deque(maxlen=window_size))
def _Check(self, cn0, num_obs, type_bits):
"""Check the carrier-to-noise ratio."""
if num_obs == 0:
return
if self._for_log:
avg_cn0, max_cn0 = self.GetAvgAndMaxCn0FromTimeSeries(
cn0, num_obs, type_bits)
else:
avg_cn0, max_cn0, _ = self.GetAvgAndMaxCn0(cn0, num_obs, type_bits)
avg_ranges = check_range.Interval([40.0, None])
max_ranges = check_range.Interval([45.0, None])
all_inclusive = check_range.AllInclusiveRange()
self._CheckByRange('%s (Avg)' % self._name, avg_cn0, avg_ranges,
all_inclusive)
self._CheckByRange('%s (Max)' % self._name, max_cn0, max_ranges,
all_inclusive)
def __init__(self, mode, **widget_kwargs):
super(StarboardPosChart, self).__init__(mode,
'Star Ail Pos [°]',
['A5', 'A7', 'A8'],
show_cmd=True,
**widget_kwargs)
self._SetLimits(
{
self._ObservationLabel(n):
(check_range.Interval(numpy.rad2deg(
flap_limits.FlapsToServos(
flap_limits.GetControlCrosswindLimits())[n]).tolist(),
inclusiveness=(False, False)),
check_range.AllInclusiveRange())
for n in ['A7', 'A8']
}, [
control_types.kFlightModeCrosswindNormal,
control_types.kFlightModeCrosswindPrepTransOut
])
def __init__(self, mode, **widget_kwargs):
nodes = ['E1', 'E2']
super(ElePosChart, self).__init__(mode,
'Ele Pos [°]',
nodes,
show_cmd=True,
**widget_kwargs)
limits = flap_limits.FlapsToServos(
flap_limits.GetControlCrosswindLimits())['E1']
limits = numpy.rad2deg(limits).tolist()
self._SetLimits(
{
self._ObservationLabel(n):
(check_range.Interval(limits, inclusiveness=(False, False)),
check_range.AllInclusiveRange())
for n in nodes
}, [
control_types.kFlightModeCrosswindNormal,
control_types.kFlightModeCrosswindPrepTransOut
])
def CheckForFailure(values,
target_ranges,
error_if_fail,
error_name=None,
min_gap=1000):
"""Checking values against normal ranges.
Args:
values: Values of the field.
target_ranges: A BaseRange object in which values are regarded as normal.
It can also be a list of basic objects that create BaseRange objects.
Please refer to check_range.RangeChecker for details.
error_if_fail: True if failed values raise errors,
otherwise they raise warnings.
error_name: Name of the error/warning.
min_gap: Merge selected regions into one section if their distance is less
than min_gap.
Returns:
Check results in the form of {
warning_name: {
'total': ..., # Total number of samples.
'count': ..., # Number of samples in this range.
'range': [min_value, max_value],
},
error_name: {...}
}
"""
if error_if_fail:
error_name = DEFAULT_ERROR_NAME if not error_name else error_name
return CheckByRange(values, target_ranges,
check_range.AllExclusiveRange(),
DEFAULT_WARNING_NAME, error_name, min_gap)
else:
error_name = DEFAULT_WARNING_NAME if not error_name else error_name
return CheckByRange(values, target_ranges,
check_range.AllInclusiveRange(), error_name,
DEFAULT_ERROR_NAME, min_gap)
def __init__(self, for_log, source):
normal_ranges = check_range.Interval((None, 3))
warning_ranges = check_range.AllInclusiveRange()
super(NovAtelDiffCheck, self).__init__(for_log, source, normal_ranges,
warning_ranges)