# this is the path to the message file in PyHSPF (hspfmsg.wdm)
# the HSPF main routine needs the location of this file and the UCI file
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# before running the examples, we have to create the WDM files used by the
# test runs, which we will do with the WDMUtil class
wdm = WDMUtil(verbose=True)
# the name of the WDM file used in the test UCIs is test.wdm
# open it up for write access
wdm.open('test.wdm', 'w')
# the first few test runs write data to the WDM files, but they assume the
# datasets already exist so we need to create them. have a look at the test
# UCI files if you are curious
attributes = {
'TCODE ': 4,
'TSSTEP': 1,
'TSTYPE': 'WTMP',
'TSFORM': 3,
}
# what these attributes mean:
#
# the time series type for the first dataset is "WTMP" (water temperature)
# import from exp to wdm
wdm.import_exp(huntday, f)
# copy the data to the hspfmodel using WDMUtil. in general climate
# data would need to come from some other place (not a wdm file);
# e.g., an NCDC file. the preprocessing modules can automate this
# for the hspexp example, only one timeseries for precip and evap
# are provided. the file also contains the observed flow at the outlet.
# this is set up to find the dsns, time steps etc, though if they were
# known they could be provided directly.
# open the wdm for read access
wdm.open(f, 'r')
# find all the dsns
dsns = wdm.get_datasets(f)
# find all the time series types
# (this is how they are identified in the exp file)
tstypes = [wdm.get_attribute(f, n, 'TSTYPE') for n in dsns]
# find the precip and evap timeseries (we could also just look at the exp files
# to figure this out, but this illustrates some of the flexibility of PyHSPF)
precip_dsn = dsns[tstypes.index('HPCP')]
evap_dsn = dsns[tstypes.index('EVAP')]
# this is the path to the message file in PyHSPF (hspfmsg.wdm)
# the HSPF main routine needs the location of this file and the UCI file
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# before running the examples, we have to create the WDM files used by the
# test runs, which we will do with the WDMUtil class
wdm = WDMUtil(verbose = True)
# the name of the WDM file used in the test UCIs is test.wdm
# open it up for write access
wdm.open('test.wdm', 'w')
# the first few test runs write data to the WDM files, but they assume the
# datasets already exist so we need to create them. have a look at the test
# UCI files if you are curious
attributes = {'TCODE ': 4,
'TSSTEP': 1,
'TSTYPE': 'WTMP',
'TSFORM': 3,
}
# what these attributes mean:
#
# the time series type for the first dataset is "WTMP" (water temperature)
# the time code is 4 (the units of the time step for the dataset are days)
# external targets
targets = ['reach_outvolume', 'evaporation', 'reach_volume', 'runoff']
# build the input files and run
hspfmodel.build_uci(targets, start, end, hydrology=True, verbose=False)
hspfmodel.run(verbose=True)
# retrieve results using WDMUtil
wdm = WDMUtil()
# open the file for read access
wdm.open(wdmoutfile, 'r')
# pull up the flow at the outlet and plot it along with the precipitation
# and evapotranspiration
dsns = wdm.get_datasets(wdmoutfile)
idconss = [wdm.get_attribute(wdmoutfile, n, 'IDCONS') for n in dsns]
staids = [wdm.get_attribute(wdmoutfile, n, 'STAID ') for n in dsns]
# find the dsn
n = [
dsn for dsn, idcons, staid in zip(dsns, idconss, staids)
if idcons == 'ROVOL' and staid == '101'
][0]
# make sure the PyHSPF data have been generated
for d in (climatedata, pdata, edata, cdata):
if not os.path.isdir(d):
print(('error: required data in {} do not exist!\n'.format(d)))
raise
# use WDMUtil to read the BASINS data
wdm = WDMUtil(verbose=verbose)
# open the precipitation file and the other climate data file
wdm.open(f1, 'r')
wdm.open(f2, 'r')
# make a list of the datasets and numbers
dsns = wdm.get_datasets(f2)
tstypes = [wdm.get_attribute(f2, n, 'TSTYPE') for n in dsns]
# start date for the BASINS data (after the warmup period)
bstart = start + datetime.timedelta(days=warmup)
# get the precipitation data
i = tstypes.index('PREC')
if not os.path.isfile('test.wdm'):
print('warning, this simulation assumes the test.wdm file from test01')
print('and test02 exists; please run these examples first')
raise
# this is the path to the message file in PyHSPF (hspfmsg.wdm)
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# the 3rd simulation adds more data to "test.wdm," so we need to create the
# datasets as before.
wdm = WDMUtil(verbose=True)
wdm.open('test.wdm', 'rw')
attributes = {
'TCODE ': 4, # hourly units
'TSSTEP': 1, # one unit (hourly) time step
'TSFORM': 1 # cloud cover is an average across the step
}
attributes['TSTYPE'] = 'CLND'
wdm.create_dataset('test.wdm', 140, attributes)
attributes['TSTYPE'] = 'CLDC'
wdm.create_dataset('test.wdm', 135, attributes)
os.path.abspath(os.path.curdir) + '\\siletz_HSPF_pet.csv')
flwData = pd.read_csv(
os.path.abspath(os.path.curdir) + '\\siletz_HSPF_flw.csv')
ts_to_wdmFile(wdmFile=wdmFile,
pcpData=pcpData,
petData=petData,
flwData=flwData)
# See if you can read the data from the WDM file
wdm = WDMUtil(verbose=True, messagepath=mssgpath)
# ADD BASIN TIMESERIES FROM THE WDM TO HSPFMODEL
# open the wdm for read access
wdm.open(wdmFile, 'r')
start, end = wdm.get_dates(wdmFile, 101)
x = 1
# Add specific basin met data
for basin in range(0, len(basinRecords)):
# The DSNs are known from the exp file so just use those this time
prcp = wdm.get_data(wdmFile, 100 + x)
evap = wdm.get_data(wdmFile, 200 + x)
# Add and assign timeseries data
hspfmodel.add_timeseries('precipitation', ('prcp_' + str(x)),
if not os.path.isfile('test.wdm'):
print('warning, this simulation assumes the test.wdm file from test01')
print('and test02 exists; please run these examples first')
raise
# this is the path to the message file in PyHSPF (hspfmsg.wdm)
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# the 3rd simulation adds more data to "test.wdm," so we need to create the
# datasets as before.
wdm = WDMUtil(verbose = True)
wdm.open('test.wdm', 'rw')
attributes = {'TCODE ': 4, # hourly units
'TSSTEP': 1, # one unit (hourly) time step
'TSFORM': 1 # cloud cover is an average across the step
}
attributes['TSTYPE'] = 'CLND'
wdm.create_dataset('test.wdm', 140, attributes)
attributes['TSTYPE'] = 'CLDC'
wdm.create_dataset('test.wdm', 135, attributes)
wdm.close('test.wdm')
print('please update the path and re-run\n')
raise
# the path to the wdm file to create
f = 'hunting.wdm'
# import from exp to wdm
wdm.import_exp(hunthour, f)
# copy the data to the hspfmodel using WDMUtil
# open the wdm for read access
wdm.open(f, 'r')
# the dsns are known from the exp file so just use those this time
precip = wdm.get_data(f, 106)
evap = wdm.get_data(f, 111)
oflow = wdm.get_data(f, 281)
start, end = wdm.get_dates(f, 106)
# close up the wdm file (forgetting this WILL cause trouble)
wdm.close('hunting.wdm')
# the evaporation data is daily so it needs to be disaggregated to hourly for
# an hourly simulation (see how easy this is with Python)
if not os.path.isfile(ucifile):
print('file does not exist')
raise
# find the path to the HSPF message file
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# run the simulation
hspf.hsppy(ucifile, messagepath)
wdm = WDMUtil()
wdm.open(wdmfile, 'r')
dsns = wdm.get_datasets(wdmfile)
# see the datasets in the WDM file
#for n in dsns: print(n, wdm.get_attribute(wdmfile, n, 'TSTYPE'))
# look at the UCI file to get more info on the datasets
precip = wdm.get_data(wdmfile, 106)
evap = wdm.get_data(wdmfile, 426)
pet = wdm.get_data(wdmfile, 425)
rovol = wdm.get_data(wdmfile, 420) # acre-ft
oflow = wdm.get_data(wdmfile, 281) # cfs
print('reading year', y)
p = '{}/{}_{}/{}'.format(directory, y, y + 2, NWISgage)
with open(p, 'rb') as f: hspfmodel = pickle.load(f)
# calculate the runoff components in each land segment and store
# the results in a structure as [subbasin][landuse][runoff/area]
results = {}
# use WDMUtil to read the data
output = hspfmodel.filename + '_out.wdm'
wdmutil = WDMUtil()
wdmutil.open(output, 'r')
# read the metadata for each timeseries in the WDM file
dsns = wdmutil.get_datasets(output)
idconss = [wdmutil.get_attribute(output, n, 'IDCONS') for n in dsns]
descrps = [wdmutil.get_attribute(output, n, 'DESCRP') for n in dsns]
staids = [wdmutil.get_attribute(output, n, 'STAID ') for n in dsns]
# go through the impervious land segments to get the surface runoff
for o in hspfmodel.implnds:
c = o.subbasin
# make a data dictionary for each subbasin
if not os.path.isfile(ucifile):
print('file does not exist')
raise
# find the path to the HSPF message file
pyhspfdirectory = os.path.dirname(hspf.__file__)
messagepath = '{}/pyhspf/core/hspfmsg.wdm'.format(pyhspfdirectory)
# run the simulation
hspf.hsppy(ucifile, messagepath)
wdm = WDMUtil()
wdm.open(wdmfile, 'r')
dsns = wdm.get_datasets(wdmfile)
# see the datasets in the WDM file
#for n in dsns: print(n, wdm.get_attribute(wdmfile, n, 'TSTYPE'))
# look at the UCI file to get more info on the datasets
precip = wdm.get_data(wdmfile, 106)
evap = wdm.get_data(wdmfile, 426)
pet = wdm.get_data(wdmfile, 425)
rovol = wdm.get_data(wdmfile, 420) # acre-ft
oflow = wdm.get_data(wdmfile, 281) # cfs
# make sure the PyHSPF data have been generated
for d in (climatedata, pdata, edata, cdata):
if not os.path.isdir(d):
print('error: required data in {} do not exist!\n'.format(d))
raise
# use WDMUtil to read the BASINS data
wdm = WDMUtil(verbose = verbose)
# open the precipitation file and the other climate data file
wdm.open(f1, 'r')
wdm.open(f2, 'r')
# make a list of the datasets and numbers
dsns = wdm.get_datasets(f2)
tstypes = [wdm.get_attribute(f2, n, 'TSTYPE') for n in dsns]
# start date for the BASINS data (after the warmup period)
bstart = start + datetime.timedelta(days = warmup)
# get the precipitation data
i = tstypes.index('PREC')
print('please update the path and re-run\n')
raise
# the path to the wdm file to create
f = 'hunting.wdm'
# import from exp to wdm
wdm.import_exp(hunthour, f)
# copy the data to the hspfmodel using WDMUtil
# open the wdm for read access
wdm.open(f, 'r')
# the dsns are known from the exp file so just use those this time
precip = wdm.get_data(f, 106)
evap = wdm.get_data(f, 111)
oflow = wdm.get_data(f, 281)
start, end = wdm.get_dates(f, 106)
# close up the wdm file (forgetting this WILL cause trouble)
wdm.close('hunting.wdm')
# the evaporation data is daily so it needs to be disaggregated to hourly for
# an hourly simulation (see how easy this is with Python)
str_wdm_new = 'siletz.wdm'
# need to set variable for HSPF message file. WDMItil uses this file
messagepath = os.path.abspath(os.path.curdir) + '\\hspfmsg.wdm'
df_prec = pd.read_csv(str_precip)
df_prec.head()
df_pet = pd.read_csv(str_pet)
df_pet.head()
# create an instance of WDMUtil class
wdm = WDMUtil(verbose=True, messagepath='hspfmsg.wdm')
# create a new wdm file
wdm.open(str_wdm_new, 'w')
# take from pyHSPF test01.py example
#
# the first few test runs write data to the WDM files, but they assume the
# datasets already exist so we need to create them. have a look at the test
# UCI files if you are curious
attributes = {
'TCODE ': 4,
'TSSTEP': 1,
'TSTYPE': 'WTMP',
'TSFORM': 3,
}
# what these attributes mean:
