task_args.append(
"subtract.kernel.active.detectionConfig.fpGrowMin=%d" %
(fpGrowPix - 1))
task_args.append(
"subtract.kernel.active.detectionConfig.fpGrowPix=%d" %
(fpGrowPix))
task_args.append(
"subtract.kernel.active.detectionConfig.fpGrowMax=%d" %
(fpGrowPix + 1))
task_args.append("doDetection=False")
task_args.append("doMeasurement=False")
## Hack around the lack of metadata being returned in cmdLineTask
tmp = ImageDifferenceTask()
parsedCmd = tmp._makeArgumentParser().parse_args(
config=tmp.ConfigClass(),
args=task_args,
log=tmp.log,
override=tmp.applyOverrides)
task = ImageDifferenceTask(name=ImageDifferenceTask._DefaultName,
config=parsedCmd.config,
log=parsedCmd.log)
results = task.run(parsedCmd.dataRefList[0])
try:
kSum = task.subtract.metadata.get("spatialKernelSum")
cNum = task.subtract.metadata.get("spatialConditionNum")
except Exception:
kSums.append(np.inf)
cNums.append(np.inf)
else:
for gSize in gSizes:
fpGrowPix = int(gSize * kSize / 2 + 0.5) # this is a grow radius
# Specializations for this test
task_args = sys.argv[1:]
task_args.append("--config")
task_args.append("subtract.kernel.active.kernelSize=%d" % (kSize))
task_args.append("subtract.kernel.active.detectionConfig.fpGrowMin=%d" % (fpGrowPix-1))
task_args.append("subtract.kernel.active.detectionConfig.fpGrowPix=%d" % (fpGrowPix))
task_args.append("subtract.kernel.active.detectionConfig.fpGrowMax=%d" % (fpGrowPix+1))
task_args.append("doDetection=False")
task_args.append("doMeasurement=False")
## Hack around the lack of metadata being returned in cmdLineTask
tmp = ImageDifferenceTask()
parsedCmd = tmp._makeArgumentParser().parse_args(config=tmp.ConfigClass(), args=task_args, log=tmp.log, override=tmp.applyOverrides)
task = ImageDifferenceTask(name = ImageDifferenceTask._DefaultName, config=parsedCmd.config, log=parsedCmd.log)
results = task.run(parsedCmd.dataRefList[0])
try:
kSum = task.subtract.metadata.get("spatialKernelSum")
cNum = task.subtract.metadata.get("spatialConditionNum")
except Exception:
kSums.append(np.inf)
cNums.append(np.inf)
else:
kSums.append(kSum)
cNums.append(cNum)
fig = plt.figure()
data = np.array(kSums).reshape(len(kSizes), len(gSizes)).T