def jenkinsTests():
try:
isHPCC = PathFinder.isHPCCRun()
# Run just the matching cases for now
testNames = ['steady', 'open_base', 'open_counter', 'closed_base', 'closed_counter']
for o in testNames:
if o == 'steady':
scenario = Scenario(ModelTester.test_params).currentPolicy().steady()
elif o == 'open_base':
scenario = Scenario(ModelTester.test_params).currentPolicy().open()
elif o == 'open_counter':
scenario = Scenario(ModelTester.test_params).open()
elif o == 'closed_base':
scenario = Scenario(ModelTester.test_params).currentPolicy().closed()
elif o == 'closed_counter':
scenario = Scenario(ModelTester.test_params).closed()
else:
scenario = []
typeDeviation = ModelTester.testOutput( scenario, o, 0 )
if typeDeviation != ModelTester.DEVIATION_NONE:
if typeDeviation == ModelTester.DEVIATION_TINY and isHPCC:
continue
else:
exit(1)
# Test writing the 'series' interface with the last scenario
# Requires that 'baseline' scenario exists
PathFinder.setToTestingMode()
print( 'TESTING OutputWriter.writeScenarios\n' )
ModelSolver.solve( scenario.baseline() )
OutputWriter.writeScenarios( [scenario] )
PathFinder.setToDevelopmentMode()
print( 'ALL TESTS PASSED.\n' )
exit(0)
except:
exit(1)
def testOutput(scenario, testName, isInteractive):
# Set to testing environment
PathFinder.setToTestingMode()
# Clear the old results and solve
ModelSolver.removeCached(scenario)
taggedDir = ModelSolver.solve(scenario)
cacheDir = PathFinder.getCacheDir(scenario)
# Set to development environment
# TBD: Set back to original environment?
PathFinder.setToDevelopmentMode()
# testSet depends on type of scenario
if( scenario.isSteady() ):
setNames = ['market', 'dynamics']
elif( scenario.isCurrentPolicy() ):
setNames = ['market', 'dynamics' ]
else:
setNames = ['market', 'dynamics', 'statics']
# Load target values
targetfile = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'ModelTester.pkl')
with open(targetfile, 'rb') as handle:
s = pickle.load(handle)
target = s.target
# Initialize match flag
typeDeviation = ModelTester.DEVIATION_NONE
# Define function to flag issues
# NOTE: Relies on severity of deviation to be increasing
def flag(str, deviation):
print('\t%-15s%-20s%s\n' % (setname, valuename, str))
global typeDeviation
if deviation > typeDeviation:
typeDeviation = deviation
print('\n[Test results]\n')
for i in range(len(setNames)):
# Extract output and target values by set
setname = setNames[i]
output = {}
with open(os.path.join(cacheDir, ('%s.pkl' % setname)), 'rb') as handle:
output[testName][setname] = pickle.load(handle)
outputset = output[testName][setname]
targetset = target[testName][setname]
# Iterate over target values
targetvaluenames = targetset.keys()
for j in range(len(targetvaluenames)):
valuename = targetvaluenames[j]
if not valuename in outputset.keys():
# Flag missing value
flag('Not found', ModelTester.DEVIATION_FATAL)
continue
if isinstance(outputset[valuename], dict):
# Skip checking of structs -- it is currently just
# priceindex which does not need to be checked
print('\tSkipping %s because it is a struct.\n' % valuename)
continue
if np.any(np.isnan(outputset[valuename][:])):
# Flag NaN value
flag('NaN value', ModelTester.DEVIATION_FATAL)
continue
if np.any(outputset[valuename].shape != targetset[valuename].shape):
# Flag for size mismatch
flag('Size mismatch', ModelTester.DEVIATION_FATAL)
continue
# Classify deviation
deviation = ModelTester.calculateDeviation(outputset[valuename][:], targetset[valuename][:])
if deviation > 0:
if (deviation < 1e-6):
msg = 'TINY : %06.16f%% deviation' % deviation*100
flag(msg, ModelTester.DEVIATION_TINY)
elif deviation < 1e-4:
msg = 'SMALL: %06.16f%% deviation' % deviation*100
flag( msg, ModelTester.DEVIATION_SMALL )
else:
msg = 'LARGE: %06.4f%% deviation' % deviation*100
flag( msg, ModelTester.DEVIATION_FATAL )
# Identify new values, if any
outputvaluenames = outputset.keys()
for j in range(len(outputvaluenames)):
valuename = outputvaluenames[j]
if not valuename in targetset.keys():
flag('New', ModelTester.DEVIATION_FATAL)
# Check for match
if typeDeviation == ModelTester.DEVIATION_NONE:
print('\tTarget matched.\n\n')
else:
if not isInteractive:
print( '\tTarget not matched.\n\n' )
return
# Query user for target update
ans = input('\n\tUpdate test target with new values? Y/[N]: ')
if ans == 'Y':
target[testName] = output[testName]
with open(targetfile) as f:
pickle.dump(target, f)
print('\tTarget updated.\n\n')
else:
print('\tTarget retained.\n\n')
return typeDeviation