def compareTimelines(self, data, reference, fields):
"""Compare timeline data and return the statistics
@param data: the name of the data directory
@param reference:the name of the directory with the reference data
@param fields: list of the fields to compare"""
sample = TimelinePlot(args=[
self.caseDir, "--silent", "--dir=" + data, "--reference-dir=" +
reference, "--compare", "--basic-mode=lines", "--metrics"
] + ["--field=" + f for f in fields])
return Data2DStatistics(metrics=sample["metrics"],
compare=sample["compare"],
noStrings=True,
failureValue=0)
def compareSamples(self,
data,
reference,
fields,
time=None,
line=None,
scaleData=1,
offsetData=0,
scaleX=1,
offsetX=0,
useReferenceForComparison=False):
"""Compare sample data and return the statistics
@param data: the name of the data directory
@param reference:the name of the directory with the reference data
@param fields: list of the fields to compare
@param time: the time to compare for. If empty the latest time is used"""
timeOpt=["--latest-time"]
if time:
timeOpt=["--time="+str(time)]
if line:
timeOpt+=["--line=%s" % line]
addOpt=[]
if useReferenceForComparison:
addOpt.append("--use-reference-for-comparison")
sample=SamplePlot(args=[self.caseDir,
"--silent",
"--dir="+data,
"--reference-dir="+reference,
"--tolerant-reference-time",
"--compare",
"--index-tolerant-compare",
"--common-range-compare",
"--metrics",
"--scale-data=%f" % scaleData,
"--scale-x=%f" % scaleX,
"--offset-data=%f" % offsetData,
"--offset-x=%f" % offsetX
]+
timeOpt+
addOpt+
["--field="+f for f in fields])
return Data2DStatistics(metrics=sample["metrics"],
compare=sample["compare"],
noStrings=True,
failureValue=0)
def postRunTestVelocityProfilesOldSchool(self):
# Just as an example how to do it detailed
sample = SamplePlot(args=[
self.caseDir, "--silent", "--dir=sets",
"--reference-dir=referenceSet", "--latest-time",
"--tolerant-reference-time", "--field=U", "--compare", "--metrics"
])
stat = Data2DStatistics(metrics=sample["metrics"],
compare=sample["compare"],
noStrings=True)
relError = stat.relativeError()
for l in relError.columns():
for com in relError.rows():
self.isEqual(value=relError[(com, l)],
tolerance=self["velocityRelativeTolerance"],
message="Match velocty component %s on line %s" %
(com, l))
def run(self):
data = self.readPickledData()
result = {"originalData": data}
if self.opts.metricsName in data:
metrics = data[self.opts.metricsName]
else:
self.error("Metrics set", self.opts.metricsName, "not in",
list(data.keys()))
if self.opts.metricsName == self.opts.compareName:
self.warning("Metrics and comparison", self.opts.compareName,
"are the same. No comparison used")
self.opts.compareName = None
if self.opts.compareName == None:
compare = None
elif self.opts.compareName in data:
compare = data[self.opts.compareName]
else:
self.error("Compare set", self.opts.compareName, "not in",
list(data.keys()))
stat = Data2DStatistics(metrics,
compare=compare,
small=self.opts.smallThreshold)
result["statistics"] = stat
for f in self.opts.field:
print_("\nField", f)
try:
val = stat[f]
print_(val)
result[f] = val
except KeyError:
print_(" .... not present in", stat.names())
for f in self.opts.function:
for v in self.opts.field:
print_("\nFunction", f, "on field", v)
try:
val = stat.func(f, v)
print_(val)
result["%s on %s" % (f, v)] = val
except KeyError:
print_(" .... not present in", stat.names())
if self.opts.relativeError:
print_("\nRelative Error")
val = stat.relativeError()
print_(val)
result["relativeError"] = val
if self.opts.relativeAverageError:
print_("\nRelative Average Error")
val = stat.relativeAverageError()
print_(val)
result["relativeAverageError"] = val
if self.opts.range:
print_("\nData range")
val = stat.range()
print_(val)
result["dataRange"] = val
self.setData(result)