import numpy as np
import matplotlib.pyplot as plt
from hydroDL.model import rnn, crit, trainTS
import torch
dataName = 'ssW'
wqData = waterQuality.DataModelWQ(dataName)
code = '00945'
label = 'plain'
trainSet = '{}-Y1'.format(code)
testSet = '{}-Y2'.format(code)
outName = '{}-{}-{}-{}'.format(dataName, code, label, trainSet)
outFolder = basins.nameFolder(outName)
dictP = basins.loadMaster(outName)
# load data
rmFlag = dictP['rmFlag'] if 'rmFlag' in dictP else False
wqData = waterQuality.DataModelWQ(dictP['dataName'], rmFlag)
varTup = (dictP['varX'], dictP['varXC'], dictP['varY'], dictP['varYC'])
dataTup, statTup = wqData.transIn(subset=dictP['trainName'], varTup=varTup)
dataTup = trainTS.dealNaN(dataTup, dictP['optNaN'])
# wrapStat(outName, statTup)
[nx, nxc, ny, nyc, nt, ns] = trainTS.getSize(dataTup)
model = basins.loadModel(outName, ep=500)
lossFun = crit.RmseLoss()
lossFun = lossFun.cuda()
model = model.cuda()
import torch
import os
import json
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
wqData = waterQuality.DataModelWQ('basinRef', rmFlag=True)
outName = 'basinRef-Yeven-opt2'
trainSet = 'Yeven'
testSet = 'Yodd'
siteNoLst = wqData.info['siteNo'].unique().tolist()
master = basins.loadMaster(outName)
ep = 300
yP1, ycP1 = basins.testModel(outName, trainSet, wqData=wqData, ep=ep)
yP2, ycP2 = basins.testModel(outName, testSet, wqData=wqData, ep=ep)
errMatC1 = wqData.errBySiteC(ycP1,
varC=master['varYC'],
subset=trainSet,
rmExt=True)
errMatC2 = wqData.errBySiteC(ycP2,
varC=master['varYC'],
subset=testSet,
rmExt=True)
dirWrtds = os.path.join(kPath.dirWQ, 'modelStat', 'WRTDS-F')
dfCorr1 = pd.read_csv(os.path.join(dirWrtds,
'{}-{}-corr'.format(trainSet, trainSet)),
from hydroDL import kPath
from hydroDL.master import basins
from hydroDL.app import waterQuality
from hydroDL.data import gridMET, usgs, gageII
import json
import os
import pandas as pd
import numpy as np
modelFolder = os.path.join(kPath.dirWQ, 'model')
outLst = os.listdir(modelFolder)
for out in outLst:
master = basins.loadMaster(out)
master['varYC'] = usgs.varC
master['varXC'] = gageII.lstWaterQuality
if 'optQ' in master.keys():
if master['optQ'] == 1:
master['varX'] = gridMET.varLst
master['varY'] = usgs.varQ
if master['optQ'] == 2:
master['varX'] = usgs.varQ+gridMET.varLst
master['varY'] = None
if master['optQ'] == 3:
master['varX'] = gridMET.varLst
master['varY'] = None
if master['optQ'] == 4:
master['varX'] = usgs.varQ
master['varY'] = None
outFolder = os.path.join(modelFolder, out)
with open(os.path.join(outFolder, 'master.json'), 'w') as fp:
