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Update StreamflowExample-DI
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@amirmoez98
amirmoez98 authored Jul 3, 2024
1 parent b8a149c commit a495141
Showing 1 changed file with 42 additions and 19 deletions.
61 changes: 42 additions & 19 deletions example/StreamflowExample-DI.py
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Original file line number Diff line number Diff line change
Expand Up @@ -250,10 +250,10 @@
ed = utils.time.t2dt(optData["tRange"][1]) - dt.timedelta(days=nDay)
dfdi = camels.DataframeCamels(subset=optData["subset"], tRange=[sd, ed])
datatemp = dfdi.getDataObs(
doNorm=False, rmNan=False, basinnorm=True
doNorm=False, rmNan=False, basinnorm=True, flow_regime=flow_regime
) # 'basinnorm=True': output = discharge/(area*mean_precip)
# normalize data
dadata = camels.transNormbyDic(datatemp, "runoff", statDict, toNorm=True)
dadata = camels.transNormbyDic(datatemp, "runoff", statDict, toNorm=True, flow_regime=flow_regime)
dadata[np.where(np.isnan(dadata))] = 0.0

xIn = np.concatenate([xTrain, dadata], axis=2)
Expand Down Expand Up @@ -294,8 +294,9 @@
loadtrainBuff = 0
TestEPOCH = 300 # choose the model to test after trained "TestEPOCH" epoches
# generate a folder name list containing all the tested model output folders
caseLst = ["All"]
if optData["daObs"] > 0:
caseLst = [] #If you want to test model without DI, you must write "All" in caseLst,othervise it must be empty
# optData = default.update(default.optDataCamels, daObs=1)
if optData["daObs"] == 0:
nDayLst = [1, 3] # which DI models to test: DI(1), DI(3)
for nDay in nDayLst:
caseLst.append("All-DI" + str(nDay))
Expand All @@ -314,7 +315,7 @@
# load testing data
mDict = readMasterFile(out)
optData = mDict["data"]
df = camels.DataframeCamels(subset=subset, tRange=tRange,forType=optData['forType'])
df = camels.DataframeCamels(subset=subset, tRange=tRange, forType=optData['forType'])
x = df.getDataTs(varLst=optData["varT"], doNorm=False, rmNan=False, flow_regime=flow_regime)
obs = df.getDataObs(doNorm=False, rmNan=False, basinnorm=False, flow_regime=flow_regime)
c = df.getDataConst(varLst=optData["varC"], doNorm=False, rmNan=False, flow_regime=flow_regime)
Expand Down Expand Up @@ -343,13 +344,29 @@
ed = utils.time.t2dt(tRange[1]) - dt.timedelta(days=nDay)
dfdi = camels.DataframeCamels(subset=subset, tRange=[sd, ed])
datatemp = dfdi.getDataObs(
doNorm=False, rmNan=False, basinnorm=True
) # 'basinnorm=True': output = discharge/(area*mean_precip)
doNorm=False, rmNan=False, basinnorm=True, flow_regime=flow_regime)
# 'basinnorm=True': output = discharge/(area*mean_precip)
# normalize data
dadata = camels.transNormbyDic(
datatemp, "runoff", statDict, toNorm=True
dadataTest = camels.transNormbyDic(
datatemp, "runoff", statDict, toNorm=True, flow_regime=flow_regime
)
dadata[np.where(np.isnan(dadata))] = 0.0
dadataTest[np.where(np.isnan(dadataTest))] = 0.0
dadata = dadataTest
if testTrainBuff:
nDay = optData["daObs"]
sd = utils.time.t2dt(Ttrain[0]) - dt.timedelta(days=nDay)
ed = utils.time.t2dt(Ttrain[1]) - dt.timedelta(days=nDay)
dfdi = camels.DataframeCamels(subset=subset, tRange=[sd, ed])
datatemp = dfdi.getDataObs(
doNorm=False, rmNan=False, basinnorm=True, flow_regime=flow_regime)
# 'basinnorm=True': output = discharge/(area*mean_precip)
# normalize data
dadataTrain = camels.transNormbyDic(
datatemp, "runoff", statDict, toNorm=True, flow_regime=flow_regime
)
dadataTrain[np.where(np.isnan(dadataTrain))] = 0.0
dadata = np.concatenate([dadataTrain, dadataTest], axis=1)

xIn = np.concatenate([xTest, dadata], axis=2)

else:
Expand Down Expand Up @@ -388,14 +405,21 @@
)

# change the units ft3/s to m3/s
# if testTrainBuff is True:
# obs = obs[:, 0:, :] * 0.0283168
# else:
# obs = obs * 0.0283168
# # obs = obs * 0.0283168
# pred = pred * 0.0283168
# pred = pred * 0.0283168
#######
if testTrainBuff is True:
obs = obs[:, 0:, :] * 0.0283168
pred = pred[:, TestBuff:, :] * 0.0283168
else:
obs = obs[:, TestBuff:, :] * 0.0283168
pred = pred * 0.0283168
# obs = obs * 0.0283168
pred = pred[:, TestBuff:, :] * 0.0283168
# pred = pred * 0.0283168

obs = obs * 0.0283168
##########
# prediction and obs to mm/day
obs = camels.basinTrans(obs, subset)
pred = camels.basinTrans(pred, subset)
Expand All @@ -406,7 +430,7 @@

# Show boxplots of the results
plt.rcParams["font.size"] = 14
keyLst = ["Bias", "NSE", "KGE", "FLV", "FHV", "AFLV", "AFHV", "highRMSE", "lowRMSE"]
keyLst = ["NSE", "KGE", "FLV", "FHV", "absFLV", "absFHV", "highRMSE", "lowRMSE", "midRMSE", "rdMax"]
dataBox = list()
for iS in range(len(keyLst)):
statStr = keyLst[iS]
Expand All @@ -417,10 +441,9 @@
temp.append(data)
dataBox.append(temp)
print(
"Bias (mm/day), NSE,KGE, FLV, FHV, AFLV, AFHV, highRMSE (mm/day), lowRMSE (mm/day)",
np.nanmedian(dataBox[0][0]), np.nanmedian(dataBox[1][0]), np.nanmedian(dataBox[2][0]), np.nanmedian(dataBox[3][0]), np.nanmedian(dataBox[4][0]), np.nanmedian(dataBox[5][0]),
np.nanmedian(dataBox[6][0]), np.nanmedian(dataBox[7][0]), np.nanmedian(dataBox[8][0])
f"NSE : {np.nanmedian(dataBox[0][0])}\n,KGE : {np.nanmedian(dataBox[1][0])}\n, FLV : {np.nanmedian(dataBox[2][0])}\n, FHV : {np.nanmedian(dataBox[3][0])}\n, absFLV : {np.nanmedian(dataBox[4][0])}\n, absFHV : {np.nanmedian(dataBox[5][0])}\n, highRMSE (mm/day) : {np.nanmedian(dataBox[6][0])}\n, lowRMSE : {np.nanmedian(dataBox[7][0])}\n (mm/day),midRMSE : {np.nanmedian(dataBox[8][0])}\n(mm/day),rdMax : {np.nanmedian(dataBox[9][0])} ",
)

labelname = ["LSTM"]
if optData["daObs"] > 0:
for nDay in nDayLst:
Expand Down

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