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def get_controlfileheader( model: Union[str, 'modeltools.Model'], parameterstep: timetools.PeriodConstrArg = None, simulationstep: timetools.PeriodConstrArg = Non... |
with Parameter.parameterstep(parameterstep):
if simulationstep is None:
simulationstep = Parameter.simulationstep
else:
simulationstep = timetools.Period(simulationstep)
return (f"# -*- coding: utf-8 -*-\n\n"
f"from hydpy.models.{model} import *\n\n"
... |
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def update(self) -> None: """Call method |Parameter.update| of all "secondary" parameters. Directly after initialisation, neither the primary (`control`) paramete... |
for subpars in self.secondary_subpars:
for par in subpars:
try:
par.update()
except BaseException:
objecttools.augment_excmessage(
f'While trying to update parameter '
f'`{objectt... |
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def save_controls(self, filepath: Optional[str] = None, parameterstep: timetools.PeriodConstrArg = None, simulationstep: timetools.PeriodConstrArg = None, auxfile... |
if self.control:
variable2auxfile = getattr(auxfiler, str(self.model), None)
lines = [get_controlfileheader(
self.model, parameterstep, simulationstep)]
with Parameter.parameterstep(parameterstep):
for par in self.control:
... |
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def _get_values_from_auxiliaryfile(self, auxfile):
"""Try to return the parameter values from the auxiliary control file with the given name. Things are a little... |
try:
frame = inspect.currentframe().f_back.f_back
while frame:
namespace = frame.f_locals
try:
subnamespace = {'model': namespace['model'],
'focus': self}
break
ex... |
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def initinfo(self) -> Tuple[Union[float, int, bool], bool]: """The actual initial value of the given parameter. Some |Parameter| subclasses define another value f... |
init = self.INIT
if (init is not None) and hydpy.pub.options.usedefaultvalues:
with Parameter.parameterstep('1d'):
return self.apply_timefactor(init), True
return variabletools.TYPE2MISSINGVALUE[self.TYPE], False |
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def get_timefactor(cls) -> float: """Factor to adjust a new value of a time-dependent parameter. For a time-dependent parameter, its effective value depends on th... |
try:
parfactor = hydpy.pub.timegrids.parfactor
except RuntimeError:
if not (cls.parameterstep and cls.simulationstep):
raise RuntimeError(
f'To calculate the conversion factor for adapting '
f'the values of the time-depende... |
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def revert_timefactor(cls, values):
"""The inverse version of method |Parameter.apply_timefactor|. See the explanations on method Parameter.apply_timefactor| to ... |
if cls.TIME is True:
return values / cls.get_timefactor()
if cls.TIME is False:
return values * cls.get_timefactor()
return values |
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def compress_repr(self) -> Optional[str]: """Try to find a compressed parameter value representation and return it. |Parameter.compress_repr| raises a |NotImpleme... |
if not hasattr(self, 'value'):
return '?'
if not self:
return f"{self.NDIM * '['}{self.NDIM * ']'}"
unique = numpy.unique(self[self.mask])
if sum(numpy.isnan(unique)) == len(unique.flatten()):
unique = numpy.array([numpy.nan])
else:
... |
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def refresh(self) -> None: """Update the actual simulation values based on the toy-value pairs. Usually, one does not need to call refresh explicitly. The "magic"... |
if not self:
self.values[:] = 0.
elif len(self) == 1:
values = list(self._toy2values.values())[0]
self.values[:] = self.apply_timefactor(values)
else:
for idx, date in enumerate(
timetools.TOY.centred_timegrid(self.simulationst... |
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def interp(self, date: timetools.Date) -> float: """Perform a linear value interpolation for the given `date` and return the result. Instantiate a 1-dimensional |... |
xnew = timetools.TOY(date)
xys = list(self)
for idx, (x_1, y_1) in enumerate(xys):
if x_1 > xnew:
x_0, y_0 = xys[idx-1]
break
else:
x_0, y_0 = xys[-1]
x_1, y_1 = xys[0]
return y_0+(y_1-y_0)/(x_1-x_0)*(xnew-x_0) |
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def update(self) -> None: """Update subclass of |RelSubweightsMixin| based on `refweights`.""" |
mask = self.mask
weights = self.refweights[mask]
self[~mask] = numpy.nan
self[mask] = weights/numpy.sum(weights) |
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def alternative_initvalue(self) -> Union[bool, int, float]: """A user-defined value to be used instead of the value of class constant `INIT`. See the main documen... |
if self._alternative_initvalue is None:
raise AttributeError(
f'No alternative initial value for solver parameter '
f'{objecttools.elementphrase(self)} has been defined so far.')
else:
return self._alternative_initvalue |
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def update(self) -> None: """Reference the actual |Indexer.timeofyear| array of the |Indexer| object available in module |pub|. toyparameter(57, 58, 59, 60, 61) "... |
indexarray = hydpy.pub.indexer.timeofyear
self.shape = indexarray.shape
self.values = indexarray |
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def get_premises_model():
""" Support for custom company premises model with developer friendly validation. """ |
try:
app_label, model_name = PREMISES_MODEL.split('.')
except ValueError:
raise ImproperlyConfigured("OPENINGHOURS_PREMISES_MODEL must be of the"
" form 'app_label.model_name'")
premises_model = get_model(app_label=app_label, model_name=model_name)
if ... |
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def get_now():
""" Allows to access global request and read a timestamp from query. """ |
if not get_current_request:
return datetime.datetime.now()
request = get_current_request()
if request:
openinghours_now = request.GET.get('openinghours-now')
if openinghours_now:
return datetime.datetime.strptime(openinghours_now, '%Y%m%d%H%M%S')
return datetime.date... |
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def get_closing_rule_for_now(location):
""" Returns QuerySet of ClosingRules that are currently valid """ |
now = get_now()
if location:
return ClosingRules.objects.filter(company=location,
start__lte=now, end__gte=now)
return Company.objects.first().closingrules_set.filter(start__lte=now,
end__gte=now... |
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def is_open(location, now=None):
""" Is the company currently open? Pass "now" to test with a specific timestamp. Can be used stand-alone or as a helper. """ |
if now is None:
now = get_now()
if has_closing_rule_for_now(location):
return False
now_time = datetime.time(now.hour, now.minute, now.second)
if location:
ohs = OpeningHours.objects.filter(company=location)
else:
ohs = Company.objects.first().openinghours_set.all... |
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def refweights(self):
"""A |numpy| |numpy.ndarray| with equal weights for all segment junctions.. array([ 0.2, 0.2, 0.2, 0.2, 0.2]) """ |
# pylint: disable=unsubscriptable-object
# due to a pylint bug (see https://github.com/PyCQA/pylint/issues/870)
return numpy.full(self.shape, 1./self.shape[0], dtype=float) |
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def add(self, directory, path=None) -> None: """Add a directory and optionally its path.""" |
objecttools.valid_variable_identifier(directory)
if path is None:
path = directory
setattr(self, directory, path) |
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def basepath(self) -> str: """Absolute path pointing to the available working directories. """ |
return os.path.abspath(
os.path.join(self.projectdir, self.BASEDIR)) |
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def availabledirs(self) -> Folder2Path: """Names and paths of the available working directories. Available working directories are those beeing stored in the base... |
directories = Folder2Path()
for directory in os.listdir(self.basepath):
if not directory.startswith('_'):
path = os.path.join(self.basepath, directory)
if os.path.isdir(path):
directories.add(directory, path)
elif directory... |
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def currentdir(self) -> str: """Name of the current working directory containing the relevant files. To show most of the functionality of |property| |FileManager.... |
if self._currentdir is None:
directories = self.availabledirs.folders
if len(directories) == 1:
self.currentdir = directories[0]
elif self.DEFAULTDIR in directories:
self.currentdir = self.DEFAULTDIR
else:
prefix = ... |
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def currentpath(self) -> str: """Absolute path of the current working directory. """ |
return os.path.join(self.basepath, self.currentdir) |
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def filenames(self) -> List[str]: """Names of the files contained in the the current working directory. Files names starting with underscores are ignored: ['file1... |
return sorted(
fn for fn in os.listdir(self.currentpath)
if not fn.startswith('_')) |
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def filepaths(self) -> List[str]: """Absolute path names of the files contained in the current working directory. Files names starting with underscores are ignore... |
path = self.currentpath
return [os.path.join(path, name) for name in self.filenames] |
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def zip_currentdir(self) -> None: """Pack the current working directory in a `zip` file. |FileManager| subclasses allow for manual packing and automatic unpacking... |
with zipfile.ZipFile(f'{self.currentpath}.zip', 'w') as zipfile_:
for filepath, filename in zip(self.filepaths, self.filenames):
zipfile_.write(filename=filepath, arcname=filename)
del self.currentdir |
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def load_files(self) -> selectiontools.Selections: """Read all network files of the current working directory, structure their contents in a |selectiontools.Selec... |
devicetools.Node.clear_all()
devicetools.Element.clear_all()
selections = selectiontools.Selections()
for (filename, path) in zip(self.filenames, self.filepaths):
# Ensure both `Node` and `Element`start with a `fresh` memory.
devicetools.Node.extract_new()
... |
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def save_files(self, selections) -> None: """Save the |Selection| objects contained in the given |Selections| instance to separate network files.""" |
try:
currentpath = self.currentpath
selections = selectiontools.Selections(selections)
for selection in selections:
if selection.name == 'complete':
continue
path = os.path.join(currentpath, selection.name+'.py')
... |
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def save_file(self, filename, text):
"""Save the given text under the given control filename and the current path.""" |
if not filename.endswith('.py'):
filename += '.py'
path = os.path.join(self.currentpath, filename)
with open(path, 'w', encoding="utf-8") as file_:
file_.write(text) |
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def load_file(self, filename):
"""Read and return the content of the given file. If the current directory is not defined explicitly, the directory name is constr... |
_defaultdir = self.DEFAULTDIR
try:
if not filename.endswith('.py'):
filename += '.py'
try:
self.DEFAULTDIR = (
'init_' + hydpy.pub.timegrids.sim.firstdate.to_string('os'))
except KeyError:
pass
... |
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def save_file(self, filename, text):
"""Save the given text under the given condition filename and the current path. If the current directory is not defined expl... |
_defaultdir = self.DEFAULTDIR
try:
if not filename.endswith('.py'):
filename += '.py'
try:
self.DEFAULTDIR = (
'init_' + hydpy.pub.timegrids.sim.lastdate.to_string('os'))
except AttributeError:
pass
... |
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def load_file(self, sequence):
"""Load data from an "external" data file an pass it to the given |IOSequence|.""" |
try:
if sequence.filetype_ext == 'npy':
sequence.series = sequence.adjust_series(
*self._load_npy(sequence))
elif sequence.filetype_ext == 'asc':
sequence.series = sequence.adjust_series(
*self._load_asc(sequence))
... |
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def save_file(self, sequence, array=None):
"""Write the date stored in |IOSequence.series| of the given |IOSequence| into an "external" data file. """ |
if array is None:
array = sequence.aggregate_series()
try:
if sequence.filetype_ext == 'nc':
self._save_nc(sequence, array)
else:
filepath = sequence.filepath_ext
if ((array is not None) and
(arr... |
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def open_netcdf_reader(self, flatten=False, isolate=False, timeaxis=1):
"""Prepare a new |NetCDFInterface| object for reading data.""" |
self._netcdf_reader = netcdftools.NetCDFInterface(
flatten=bool(flatten),
isolate=bool(isolate),
timeaxis=int(timeaxis)) |
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def open_netcdf_writer(self, flatten=False, isolate=False, timeaxis=1):
"""Prepare a new |NetCDFInterface| object for writing data.""" |
self._netcdf_writer = netcdftools.NetCDFInterface(
flatten=bool(flatten),
isolate=bool(isolate),
timeaxis=int(timeaxis)) |
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def calc_nkor_v1(self):
"""Adjust the given precipitation values. Required control parameters: |NHRU| |KG| Required input sequence: |Nied| Calculated flux sequen... |
con = self.parameters.control.fastaccess
inp = self.sequences.inputs.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
flu.nkor[k] = con.kg[k] * inp.nied |
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def calc_tkor_v1(self):
"""Adjust the given air temperature values. Required control parameters: |NHRU| |KT| Required input sequence: |TemL| Calculated flux sequ... |
con = self.parameters.control.fastaccess
inp = self.sequences.inputs.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
flu.tkor[k] = con.kt[k] + inp.teml |
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def calc_et0_v1(self):
"""Calculate reference evapotranspiration after Turc-Wendling. Required control parameters: |NHRU| |KE| |KF| |HNN| Required input sequence... |
con = self.parameters.control.fastaccess
inp = self.sequences.inputs.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
flu.et0[k] = (con.ke[k]*(((8.64*inp.glob+93.*con.kf[k]) *
(flu.tkor[k]+22.)) /
(165... |
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def calc_et0_wet0_v1(self):
"""Correct the given reference evapotranspiration and update the corresponding log sequence. Required control parameters: |NHRU| |KE|... |
con = self.parameters.control.fastaccess
inp = self.sequences.inputs.fastaccess
flu = self.sequences.fluxes.fastaccess
log = self.sequences.logs.fastaccess
for k in range(con.nhru):
flu.et0[k] = (con.wfet0[k]*con.ke[k]*inp.pet +
(1.-con.wfet0[k])*log.wet0[0, k])
... |
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def calc_evpo_v1(self):
"""Calculate land use and month specific values of potential evapotranspiration. Required control parameters: |NHRU| |Lnk| |FLn| Required... |
con = self.parameters.control.fastaccess
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
flu.evpo[k] = con.fln[con.lnk[k]-1, der.moy[self.idx_sim]] * flu.et0[k] |
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def calc_nbes_inzp_v1(self):
"""Calculate stand precipitation and update the interception storage accordingly. Required control parameters: |NHRU| |Lnk| Required... |
con = self.parameters.control.fastaccess
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
for k in range(con.nhru):
if con.lnk[k] in (WASSER, FLUSS, SEE):
flu.nbes[k] = 0.
sta.inzp[k] = 0.
... |
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def calc_sbes_v1(self):
"""Calculate the frozen part of stand precipitation. Required control parameters: |NHRU| |TGr| |TSp| Required flux sequences: |TKor| |NBe... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
if flu.nbes[k] <= 0.:
flu.sbes[k] = 0.
elif flu.tkor[k] >= (con.tgr[k]+con.tsp[k]/2.):
flu.sbes[k] = 0.
elif flu.tkor[k] <= (con.tgr[k]-con.tsp[k]/2.):
... |
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def calc_wgtf_v1(self):
"""Calculate the potential snowmelt. Required control parameters: |NHRU| |Lnk| |GTF| |TRefT| |TRefN| |RSchmelz| |CPWasser| Required flux ... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
for k in range(con.nhru):
if con.lnk[k] in (WASSER, FLUSS, SEE):
flu.wgtf[k] = 0.
else:
flu.wgtf[k] = (
max(con.gtf[k]*(flu.tkor[k]-con.treft[k]), 0) +
max... |
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def calc_schm_wats_v1(self):
"""Calculate the actual amount of water melting within the snow cover. Required control parameters: |NHRU| |Lnk| Required flux seque... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
for k in range(con.nhru):
if con.lnk[k] in (WASSER, FLUSS, SEE):
sta.wats[k] = 0.
flu.schm[k] = 0.
else:
sta.wats[k] += flu.sbes[k]
... |
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def calc_qbb_v1(self):
"""Calculate the amount of base flow released from the soil. Required control parameters: |NHRU| |Lnk| |Beta| |FBeta| Required derived par... |
con = self.parameters.control.fastaccess
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
for k in range(con.nhru):
if ((con.lnk[k] in (VERS, WASSER, FLUSS, SEE)) or
(sta.bowa[k] <= der.wb[k]) or (con.nfk[... |
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def calc_qdb_v1(self):
"""Calculate direct runoff released from the soil. Required control parameters: |NHRU| |Lnk| |NFk| |BSf| Required state sequence: |BoWa| R... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
aid = self.sequences.aides.fastaccess
for k in range(con.nhru):
if con.lnk[k] == WASSER:
flu.qdb[k] = 0.
elif ((con.lnk[k] in (VERS, FLUSS, SEE)) or
... |
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def calc_bowa_v1(self):
"""Update soil moisture and correct fluxes if necessary. Required control parameters: |NHRU| |Lnk| Required flux sequence: |WaDa| Updated... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
aid = self.sequences.aides.fastaccess
for k in range(con.nhru):
if con.lnk[k] in (VERS, WASSER, FLUSS, SEE):
sta.bowa[k] = 0.
else:
aid.bvl[... |
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def calc_qbgz_v1(self):
"""Aggregate the amount of base flow released by all "soil type" HRUs and the "net precipitation" above water areas of type |SEE|. Water ... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
sta.qbgz = 0.
for k in range(con.nhru):
if con.lnk[k] == SEE:
sta.qbgz += con.fhru[k]*(flu.nkor[k]-flu.evi[k])
elif con.lnk[k] not in (WASSER, FLUSS, VE... |
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def calc_qigz1_v1(self):
"""Aggregate the amount of the first interflow component released by all HRUs. Required control parameters: |NHRU| |FHRU| Required flux ... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
sta.qigz1 = 0.
for k in range(con.nhru):
sta.qigz1 += con.fhru[k]*flu.qib1[k] |
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def calc_qigz2_v1(self):
"""Aggregate the amount of the second interflow component released by all HRUs. Required control parameters: |NHRU| |FHRU| Required flux... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
sta.qigz2 = 0.
for k in range(con.nhru):
sta.qigz2 += con.fhru[k]*flu.qib2[k] |
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def calc_qdgz_v1(self):
"""Aggregate the amount of total direct flow released by all HRUs. Required control parameters: |Lnk| |NHRU| |FHRU| Required flux sequenc... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
flu.qdgz = 0.
for k in range(con.nhru):
if con.lnk[k] == FLUSS:
flu.qdgz += con.fhru[k]*(flu.nkor[k]-flu.evi[k])
elif con.lnk[k] not in (WASSER, SEE):
flu.qdgz += con.fhru[k]*flu.qdb[... |
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def calc_qdgz1_qdgz2_v1(self):
"""Seperate total direct flow into a small and a fast component. Required control parameters: |A1| |A2| Required flux sequence: |Q... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
if flu.qdgz > con.a2:
sta.qdgz2 = (flu.qdgz-con.a2)**2/(flu.qdgz+con.a1-con.a2)
sta.qdgz1 = flu.qdgz-sta.qdgz2
else:
sta.qdgz2 = 0.
sta.qdgz1 = flu.... |
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def calc_qbga_v1(self):
"""Perform the runoff concentration calculation for base flow. The working equation is the analytical solution of the linear storage equa... |
der = self.parameters.derived.fastaccess
old = self.sequences.states.fastaccess_old
new = self.sequences.states.fastaccess_new
if der.kb <= 0.:
new.qbga = new.qbgz
elif der.kb > 1e200:
new.qbga = old.qbga+new.qbgz-old.qbgz
else:
d_temp = (1.-modelutils.exp(-1./der.kb))
... |
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def calc_qiga1_v1(self):
"""Perform the runoff concentration calculation for the first interflow component. The working equation is the analytical solution of th... |
der = self.parameters.derived.fastaccess
old = self.sequences.states.fastaccess_old
new = self.sequences.states.fastaccess_new
if der.ki1 <= 0.:
new.qiga1 = new.qigz1
elif der.ki1 > 1e200:
new.qiga1 = old.qiga1+new.qigz1-old.qigz1
else:
d_temp = (1.-modelutils.exp(-1./de... |
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def calc_qiga2_v1(self):
"""Perform the runoff concentration calculation for the second interflow component. The working equation is the analytical solution of t... |
der = self.parameters.derived.fastaccess
old = self.sequences.states.fastaccess_old
new = self.sequences.states.fastaccess_new
if der.ki2 <= 0.:
new.qiga2 = new.qigz2
elif der.ki2 > 1e200:
new.qiga2 = old.qiga2+new.qigz2-old.qigz2
else:
d_temp = (1.-modelutils.exp(-1./de... |
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def calc_qdga1_v1(self):
"""Perform the runoff concentration calculation for "slow" direct runoff. The working equation is the analytical solution of the linear ... |
der = self.parameters.derived.fastaccess
old = self.sequences.states.fastaccess_old
new = self.sequences.states.fastaccess_new
if der.kd1 <= 0.:
new.qdga1 = new.qdgz1
elif der.kd1 > 1e200:
new.qdga1 = old.qdga1+new.qdgz1-old.qdgz1
else:
d_temp = (1.-modelutils.exp(-1./de... |
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def calc_qdga2_v1(self):
"""Perform the runoff concentration calculation for "fast" direct runoff. The working equation is the analytical solution of the linear ... |
der = self.parameters.derived.fastaccess
old = self.sequences.states.fastaccess_old
new = self.sequences.states.fastaccess_new
if der.kd2 <= 0.:
new.qdga2 = new.qdgz2
elif der.kd2 > 1e200:
new.qdga2 = old.qdga2+new.qdgz2-old.qdgz2
else:
d_temp = (1.-modelutils.exp(-1./de... |
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def calc_q_v1(self):
"""Calculate the final runoff. Note that, in case there are water areas, their |NKor| values are added and their |EvPo| values are subtracte... |
con = self.parameters.control.fastaccess
flu = self.sequences.fluxes.fastaccess
sta = self.sequences.states.fastaccess
aid = self.sequences.aides.fastaccess
flu.q = sta.qbga+sta.qiga1+sta.qiga2+sta.qdga1+sta.qdga2
if (not con.negq) and (flu.q < 0.):
d_area = 0.
for k in range(co... |
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def calc_outputs_v1(self):
"""Performs the actual interpolation or extrapolation. Required control parameters: |XPoints| |YPoints| Required derived parameter: |N... |
con = self.parameters.control.fastaccess
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
# Search for the index of the two relevant x points...
for pdx in range(1, der.nmbpoints):
if con.xpoints[pdx] > flu.input:
break
# ...and use it for line... |
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def pick_input_v1(self):
"""Updates |Input| based on |Total|.""" |
flu = self.sequences.fluxes.fastaccess
inl = self.sequences.inlets.fastaccess
flu.input = 0.
for idx in range(inl.len_total):
flu.input += inl.total[idx][0] |
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def pass_outputs_v1(self):
"""Updates |Branched| based on |Outputs|.""" |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
out = self.sequences.outlets.fastaccess
for bdx in range(der.nmbbranches):
out.branched[bdx][0] += flu.outputs[bdx] |
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def connect(self):
"""Connect the |LinkSequence| instances handled by the actual model to the |NodeSequence| instances handled by one inlet node and multiple oul... |
nodes = self.element.inlets
total = self.sequences.inlets.total
if total.shape != (len(nodes),):
total.shape = len(nodes)
for idx, node in enumerate(nodes):
double = node.get_double('inlets')
total.set_pointer(double, idx)
for (idx, name) in e... |
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def update(self):
"""Determine the number of response functions. nmb(2) Note that updating parameter `nmb` sets the shape of the flux sequences |QPIn|, |QPOut|, ... |
pars = self.subpars.pars
responses = pars.control.responses
fluxes = pars.model.sequences.fluxes
self(len(responses))
fluxes.qpin.shape = self.value
fluxes.qpout.shape = self.value
fluxes.qma.shape = self.value
fluxes.qar.shape = self.value |
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def update(self):
"""Determine the total number of AR coefficients. ar_order(2, 1) """ |
responses = self.subpars.pars.control.responses
self.shape = len(responses)
self(responses.ar_orders) |
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def update(self):
"""Determine all AR coefficients. ar_coefs([[1.0, 2.0], [1.0, nan]]) Note that updating parameter `ar_coefs` sets the shape of the log sequence... |
pars = self.subpars.pars
coefs = pars.control.responses.ar_coefs
self.shape = coefs.shape
self(coefs)
pars.model.sequences.logs.logout.shape = self.shape |
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def update(self):
"""Determine all MA coefficients. ma_coefs([[1.0, nan, nan], [1.0, 2.0, 3.0]]) Note that updating parameter `ar_coefs` sets the shape of the lo... |
pars = self.subpars.pars
coefs = pars.control.responses.ma_coefs
self.shape = coefs.shape
self(coefs)
pars.model.sequences.logs.login.shape = self.shape |
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def __getiterable(value):
# ToDo: refactor """Try to convert the given argument to a |list| of |Selection| objects and return it. """ |
if isinstance(value, Selection):
return [value]
try:
for selection in value:
if not isinstance(selection, Selection):
raise TypeError
return list(value)
except TypeError:
raise TypeError(
f'Binar... |
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def search_upstream(self, device: devicetools.Device, name: str = 'upstream') -> 'Selection': """Return the network upstream of the given starting point, includin... |
try:
selection = Selection(name)
if isinstance(device, devicetools.Node):
node = self.nodes[device.name]
return self.__get_nextnode(node, selection)
if isinstance(device, devicetools.Element):
element = self.elements[device.nam... |
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def select_upstream(self, device: devicetools.Device) -> 'Selection': """Restrict the current selection to the network upstream of the given starting point, inclu... |
upstream = self.search_upstream(device)
self.nodes = upstream.nodes
self.elements = upstream.elements
return self |
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def search_modeltypes(self, *models: ModelTypesArg, name: str = 'modeltypes') -> 'Selection': """Return a |Selection| object containing only the elements currentl... |
try:
typelist = []
for model in models:
if not isinstance(model, modeltools.Model):
model = importtools.prepare_model(model)
typelist.append(type(model))
typetuple = tuple(typelist)
selection = Selection(name)
... |
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def search_nodenames(self, *substrings: str, name: str = 'nodenames') -> \ 'Selection': """Return a new selection containing all nodes of the current selection wi... |
try:
selection = Selection(name)
for node in self.nodes:
for substring in substrings:
if substring in node.name:
selection.nodes += node
break
return selection
except BaseException:
... |
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def search_elementnames(self, *substrings: str, name: str = 'elementnames') -> 'Selection': """Return a new selection containing all elements of the current selec... |
try:
selection = Selection(name)
for element in self.elements:
for substring in substrings:
if substring in element.name:
selection.elements += element
break
return selection
except B... |
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def copy(self, name: str) -> 'Selection': """Return a new |Selection| object with the given name and copies of the handles |Nodes| and |Elements| objects based on... |
return type(self)(name, copy.copy(self.nodes), copy.copy(self.elements)) |
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def save_networkfile(self, filepath: Union[str, None] = None, write_nodes: bool = True) -> None: """Save the selection as a network file. In most cases, one shoul... |
if filepath is None:
filepath = self.name + '.py'
with open(filepath, 'w', encoding="utf-8") as file_:
file_.write('# -*- coding: utf-8 -*-\n')
file_.write('\nfrom hydpy import Node, Element\n\n')
if write_nodes:
for node in self.nodes:
... |
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def calc_qpin_v1(self):
"""Calculate the input discharge portions of the different response functions. Required derived parameters: |Nmb| |MaxQ| |DiffQ| Required... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
for idx in range(der.nmb-1):
if flu.qin < der.maxq[idx]:
flu.qpin[idx] = 0.
elif flu.qin < der.maxq[idx+1]:
flu.qpin[idx] = flu.qin-der.maxq[idx]
else:
flu.qpin[idx] =... |
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def calc_login_v1(self):
"""Refresh the input log sequence for the different MA processes. Required derived parameters: |Nmb| |MA_Order| Required flux sequence: ... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
log = self.sequences.logs.fastaccess
for idx in range(der.nmb):
for jdx in range(der.ma_order[idx]-2, -1, -1):
log.login[idx, jdx+1] = log.login[idx, jdx]
for idx in range(der.nmb):
log.login... |
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def calc_qma_v1(self):
"""Calculate the discharge responses of the different MA processes. Required derived parameters: |Nmb| |MA_Order| |MA_Coefs| Required log ... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
log = self.sequences.logs.fastaccess
for idx in range(der.nmb):
flu.qma[idx] = 0.
for jdx in range(der.ma_order[idx]):
flu.qma[idx] += der.ma_coefs[idx, jdx] * log.login[idx, jdx] |
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def calc_qar_v1(self):
"""Calculate the discharge responses of the different AR processes. Required derived parameters: |Nmb| |AR_Order| |AR_Coefs| Required log ... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
log = self.sequences.logs.fastaccess
for idx in range(der.nmb):
flu.qar[idx] = 0.
for jdx in range(der.ar_order[idx]):
flu.qar[idx] += der.ar_coefs[idx, jdx] * log.logout[idx, jdx] |
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def calc_qpout_v1(self):
"""Calculate the ARMA results for the different response functions. Required derived parameter: |Nmb| Required flux sequences: |QMA| |QA... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
for idx in range(der.nmb):
flu.qpout[idx] = flu.qma[idx]+flu.qar[idx] |
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def calc_logout_v1(self):
"""Refresh the log sequence for the different AR processes. Required derived parameters: |Nmb| |AR_Order| Required flux sequence: |QPOu... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
log = self.sequences.logs.fastaccess
for idx in range(der.nmb):
for jdx in range(der.ar_order[idx]-2, -1, -1):
log.logout[idx, jdx+1] = log.logout[idx, jdx]
for idx in range(der.nmb):
if der.... |
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def calc_qout_v1(self):
"""Sum up the results of the different response functions. Required derived parameter: |Nmb| Required flux sequences: |QPOut| Calculated ... |
der = self.parameters.derived.fastaccess
flu = self.sequences.fluxes.fastaccess
flu.qout = 0.
for idx in range(der.nmb):
flu.qout += flu.qpout[idx] |
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def update(self):
"""Determine the number of branches""" |
con = self.subpars.pars.control
self(con.ypoints.shape[0]) |
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def update(self):
"""Update value based on the actual |calc_qg_v1| method. Required derived parameter: |H| Note that the value of parameter |lstream_derived.QM| ... |
mod = self.subpars.pars.model
con = mod.parameters.control
flu = mod.sequences.fluxes
flu.h = con.hm
mod.calc_qg()
self(flu.qg) |
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def update(self):
"""Determines in how many segments the whole reach needs to be divided to approximate the desired lag time via integer rounding. Adjusts the sh... |
pars = self.subpars.pars
self(int(round(pars.control.lag)))
pars.model.sequences.states.qjoints.shape = self+1 |
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def view(data, enc=None, start_pos=None, delimiter=None, hdr_rows=None, idx_cols=None, sheet_index=0, transpose=False, wait=None, recycle=None, detach=None, metav... |
global WAIT, RECYCLE, DETACH, VIEW
model = read_model(data, enc=enc, delimiter=delimiter, hdr_rows=hdr_rows,
idx_cols=idx_cols, sheet_index=sheet_index,
transpose=transpose)
if model is None:
warnings.warn("cannot visualize the supplied data type: {}".... |
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def gather_registries() -> Tuple[Dict, Mapping, Mapping]: """Get and clear the current |Node| and |Element| registries. Function |gather_registries| is thought to... |
id2devices = copy.copy(_id2devices)
registry = copy.copy(_registry)
selection = copy.copy(_selection)
dict_ = globals()
dict_['_id2devices'] = {}
dict_['_registry'] = {Node: {}, Element: {}}
dict_['_selection'] = {Node: {}, Element: {}}
return id2devices, registry, selection |
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def reset_registries(dicts: Tuple[Dict, Mapping, Mapping]):
"""Reset the current |Node| and |Element| registries. Function |reset_registries| is thought to be us... |
dict_ = globals()
dict_['_id2devices'] = dicts[0]
dict_['_registry'] = dicts[1]
dict_['_selection'] = dicts[2] |
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def startswith(self, name: str) -> List[str]: """Return a list of all keywords starting with the given string. ['keyword_3', 'keyword_4'] """ |
return sorted(keyword for keyword in self if keyword.startswith(name)) |
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def endswith(self, name: str) -> List[str]: """Return a list of all keywords ending with the given string. ['first_keyword', 'second_keyword'] """ |
return sorted(keyword for keyword in self if keyword.endswith(name)) |
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def contains(self, name: str) -> List[str]: """Return a list of all keywords containing the given string. ['first_keyword', 'keyword_3', 'keyword_4', 'second_keyw... |
return sorted(keyword for keyword in self if name in keyword) |
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def update(self, *names: Any) -> None: """Before updating, the given names are checked to be valid variable identifiers. Traceback (most recent call last):
Value... |
_names = [str(name) for name in names]
self._check_keywords(_names)
super().update(_names) |
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def add(self, name: Any) -> None: """Before adding a new name, it is checked to be valid variable identifiers. Traceback (most recent call last):
ValueError: Whi... |
self._check_keywords([str(name)])
super().add(str(name)) |
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def add_device(self, device: Union[DeviceType, str]) -> None: """Add the given |Node| or |Element| object to the actual |Nodes| or |Elements| object. You can pass... |
try:
if self.mutable:
_device = self.get_contentclass()(device)
self._name2device[_device.name] = _device
_id2devices[_device][id(self)] = self
else:
raise RuntimeError(
f'Adding devices to immutable '
... |
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def remove_device(self, device: Union[DeviceType, str]) -> None: """Remove the given |Node| or |Element| object from the actual |Nodes| or |Elements| object. You ... |
try:
if self.mutable:
_device = self.get_contentclass()(device)
try:
del self._name2device[_device.name]
except KeyError:
raise ValueError(
f'The actual {objecttools.classname(self)} '
... |
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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
def keywords(self) -> Set[str]: """A set of all keywords of all handled devices. In addition to attribute access via device names, |Nodes| and |Elements| objects ... |
return set(keyword for device in self
for keyword in device.keywords if
keyword not in self._shadowed_keywords) |
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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
def copy(self: DevicesTypeBound) -> DevicesTypeBound: """Return a shallow copy of the actual |Nodes| or |Elements| object. Method |Devices.copy| returns a semi-fl... |
new = type(self)()
vars(new).update(vars(self))
vars(new)['_name2device'] = copy.copy(self._name2device)
vars(new)['_shadowed_keywords'].clear()
for device in self:
_id2devices[device][id(new)] = new
return new |
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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
def prepare_allseries(self, ramflag: bool = True) -> None: """Call methods |Node.prepare_simseries| and |Node.prepare_obsseries|.""" |
self.prepare_simseries(ramflag)
self.prepare_obsseries(ramflag) |
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Description:
def prepare_simseries(self, ramflag: bool = True) -> None: """Call method |Node.prepare_simseries| of all handled |Node| objects.""" |
for node in printtools.progressbar(self):
node.prepare_simseries(ramflag) |
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Description:
def prepare_obsseries(self, ramflag: bool = True) -> None: """Call method |Node.prepare_obsseries| of all handled |Node| objects.""" |
for node in printtools.progressbar(self):
node.prepare_obsseries(ramflag) |
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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
def init_models(self) -> None: """Call method |Element.init_model| of all handle |Element| objects. We show, based the `LahnH` example project, that method |Eleme... |
try:
for element in printtools.progressbar(self):
element.init_model(clear_registry=False)
finally:
hydpy.pub.controlmanager.clear_registry() |
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