def testapirunhr(self):
startTime = 1
stopTime = 30
currentTime = 1
# set runid, clonemap and casename. Also define the ini file
runId = "unittest"
configfile = "wflow_hbv_hr.ini"
wflow_cloneMap = "wflow_catchment.map"
caseName = "wflow_hbv"
starttime = starttime = datetime.datetime(1990, 01, 01)
myModel = wf.WflowModel(wflow_cloneMap, caseName, runId, configfile)
# initialise the framework
dynModelFw = wf.wf_DynamicFramework(myModel,
stopTime,
firstTimestep=startTime,
datetimestart=starttime)
print dynModelFw.DT
# Load model config from files and check directory structure
dynModelFw.createRunId(NoOverWrite=False, level=wf.logging.DEBUG)
# Run the initial part of the model (reads parameters and sets initial values)
dynModelFw._runInitial() # Runs initial part
dynModelFw._runResume() # gets the state variables
sump = 0.0
for ts in range(startTime, stopTime + 1):
if ts < 10:
dynModelFw.wf_setValues("P", 0.0)
elif ts <= 15:
dynModelFw.wf_setValues("P", 10.0)
sump = sump + 10.0
else:
dynModelFw.wf_setValues("P", 0.0)
dynModelFw.wf_setValues("PET", 2.0)
dynModelFw.wf_setValues("TEMP", 10.0)
dynModelFw._runDynamic(ts, ts) # runs for all timesteps
dynModelFw.logger.info("Doing step: " + str(ts))
dynModelFw._runSuspend() # saves the state variables
dynModelFw._wf_shutdown()
# nore read the csv results acn check of they match the first run
# Sum should be approx c 4.569673676
my_data = wf.genfromtxt(os.path.join(caseName, runId, "watbal.csv"),
delimiter=",")
print("Checking water budget ....")
self.assertAlmostEquals(0.0013141632080078125,
my_data[:, 2].sum(),
places=4)
my_data = wf.genfromtxt(os.path.join(caseName, runId, "run.csv"),
delimiter=",")
print("Checking discharge ....")
self.assertAlmostEquals(1811.1795542081197,
my_data[:, 2].mean(),
places=4)
def testapirun(self):
startTime = 1
stopTime = 30
currentTime = 1
# set runid, clonemap and casename. Also define the ini file
runId = "unittest"
configfile="wflow_hbv.ini"
wflow_cloneMap = 'wflow_catchment.map'
caseName="wflow_hbv"
myModel = wf.WflowModel(wflow_cloneMap, caseName,runId,configfile)
# initialise the framework
dynModelFw = wf.wf_DynamicFramework(myModel, stopTime,startTime)
# Load model config from files and check directory structure
dynModelFw.createRunId(NoOverWrite=False,level=wf.logging.ERROR)
# Run the initial part of the model (reads parameters and sets initial values)
dynModelFw._runInitial() # Runs initial part
dynModelFw._runResume() # gets the state variables
sump = 0.0
for ts in range(startTime,stopTime):
if ts <10:
dynModelFw.wf_setValues('P', 0.0)
elif ts <= 15:
dynModelFw.wf_setValues('P', 10.0)
sump = sump + 10.0
else:
dynModelFw.wf_setValues('P', 0.0)
dynModelFw.wf_setValues('PET', 2.0)
dynModelFw.wf_setValues('TEMP', 10.0)
dynModelFw._runDynamic(ts,ts) # runs for all timesteps
dynModelFw.logger.info("Doing step: " + str(ts))
dynModelFw._runSuspend() # saves the state variables
dynModelFw._wf_shutdown()
# nore read the csv results acn check of they match the first run
# Sum should be approx c 4.569673676
my_data = wf.genfromtxt(os.path.join(caseName,runId,"watbal.csv"), delimiter=',')
print("Checking water budget ....")
self.assertAlmostEquals( 0.00018204912482389091,my_data[:,2].sum())
print("Checking precip sum ....")
my_data = wf.genfromtxt(os.path.join(caseName,runId,"P.csv"), delimiter=',')
self.assertAlmostEquals(sump,my_data[:,2].sum())