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Delete the coefficients of the pure MA model and also all MA and AR coefficients of the ARMA model. Also calculate or delete the values of all secondary iuh parameters, depending on the completeness of the values of the primary parameters. def update(self): """Delete the coefficients o...
A tuple of two numpy arrays, which hold the time delays and the associated iuh values respectively. def delay_response_series(self): """A tuple of two numpy arrays, which hold the time delays and the associated iuh values respectively.""" delays = [] responses = [] sum_r...
Plot the instanteneous unit hydrograph. The optional argument allows for defining a threshold of the cumulative sum uf the hydrograph, used to adjust the largest value of the x-axis. It must be a value between zero and one. def plot(self, threshold=None, **kwargs): """Plot the instante...
The first time delay weighted statistical moment of the instantaneous unit hydrograph. def moment1(self): """The first time delay weighted statistical moment of the instantaneous unit hydrograph.""" delays, response = self.delay_response_series return statstools.calc_mean_time(d...
The second time delay weighted statistical momens of the instantaneous unit hydrograph. def moment2(self): """The second time delay weighted statistical momens of the instantaneous unit hydrograph.""" moment1 = self.moment1 delays, response = self.delay_response_series r...
Determine the values of the secondary parameters `a` and `b`. def calc_secondary_parameters(self): """Determine the values of the secondary parameters `a` and `b`.""" self.a = self.x/(2.*self.d**.5) self.b = self.u/(2.*self.d**.5)
Determine the value of the secondary parameter `c`. def calc_secondary_parameters(self): """Determine the value of the secondary parameter `c`.""" self.c = 1./(self.k*special.gamma(self.n))
Trim values in accordance with :math:`WAeS \\leq PWMax \\cdot WATS`, or at least in accordance with if :math:`WATS \\geq 0`. >>> from hydpy.models.lland import * >>> parameterstep('1d') >>> nhru(7) >>> pwmax(2.0) >>> states.waes = -1., 0., 1., -1., 5., 10., 20. >...
Trim values in accordance with :math:`WAeS \\leq PWMax \\cdot WATS`. >>> from hydpy.models.lland import * >>> parameterstep('1d') >>> nhru(7) >>> pwmax(2.) >>> states.wats = 0., 0., 0., 5., 5., 5., 5. >>> states.waes(-1., 0., 1., -1., 5., 10., 20.) >>> states.wae...
Trim values in accordance with :math:`BoWa \\leq NFk`. >>> from hydpy.models.lland import * >>> parameterstep('1d') >>> nhru(5) >>> nfk(200.) >>> states.bowa(-100.,0., 100., 200., 300.) >>> states.bowa bowa(0.0, 0.0, 100.0, 200.0, 200.0) def trim(self, lower=Non...
Clean the data and save opening hours in the database. Old opening hours are purged before new ones are saved. def post(self, request, pk): """ Clean the data and save opening hours in the database. Old opening hours are purged before new ones are saved. """ location = self.get_...
Initialize the editing form 1. Build opening_hours, a lookup dictionary to populate the form slots: keys are day numbers, values are lists of opening hours for that day. 2. Build days, a list of days with 2 slot forms each. 3. Build form initials for the 2 slots padding/tr...
Apply the routing equation. Required derived parameters: |NmbSegments| |C1| |C2| |C3| Updated state sequence: |QJoints| Basic equation: :math:`Q_{space+1,time+1} = c1 \\cdot Q_{space,time+1} + c2 \\cdot Q_{space,time} + c3 \\cdot Q_{space+1,time}` ...
Assign the actual value of the inlet sequence to the upper joint of the subreach upstream. def pick_q_v1(self): """Assign the actual value of the inlet sequence to the upper joint of the subreach upstream.""" inl = self.sequences.inlets.fastaccess new = self.sequences.states.fastaccess_new new....
Assing the actual value of the lower joint of of the subreach downstream to the outlet sequence. def pass_q_v1(self): """Assing the actual value of the lower joint of of the subreach downstream to the outlet sequence.""" der = self.parameters.derived.fastaccess new = self.sequences.states.fastacces...
Return the default system encoding. If data is passed, try to decode the data with the default system encoding or from a short list of encoding types to test. Args: data - list of lists Returns: enc - system encoding def _detect_encoding(data=None): """Return the default system enc...
Define a parameter time step size within a parameter control file. Argument: * timestep(|Period|): Time step size. Function parameterstep should usually be be applied in a line immediately behind the model import. Defining the step size of time dependent parameters is a prerequisite to access a...
Clear the local namespace from a model wildcard import. Calling this method should remove the critical imports into the local namespace due the last wildcard import of a certain application model. It is thought for securing the successive preperation of different types of models via wildcard imports. ...
Prepare and return the model of the given module. In usual HydPy projects, each hydrological model instance is prepared in an individual control file. This allows for "polluting" the namespace with different model attributes. There is no danger of name conflicts, as long as no other (wildcard) import...
Define a simulation time step size for testing purposes within a parameter control file. Using |simulationstep| only affects the values of time dependent parameters, when `pub.timegrids.stepsize` is not defined. It thus has no influence on usual hydpy simulations at all. Use it just to check your...
Define the corresponding control file within a condition file. Function |controlcheck| serves similar purposes as function |parameterstep|. It is the reason why one can interactively access the state and/or the log sequences within condition files as `land_dill.py` of the example project `LahnH`. It ...
Update |RelSoilArea| based on |Area|, |ZoneArea|, and |ZoneType|. >>> from hydpy.models.hland import * >>> parameterstep('1d') >>> nmbzones(4) >>> zonetype(FIELD, FOREST, GLACIER, ILAKE) >>> area(100.0) >>> zonearea(10.0, 20.0, 30.0, 40.0) >>> derived.relsoilarea...
Update |TTM| based on :math:`TTM = TT+DTTM`. >>> from hydpy.models.hland import * >>> parameterstep('1d') >>> nmbzones(1) >>> zonetype(FIELD) >>> tt(1.0) >>> dttm(-2.0) >>> derived.ttm.update() >>> derived.ttm ttm(-1.0) def update(self): ...
Update |UH| based on |MaxBaz|. .. note:: This method also updates the shape of log sequence |QUH|. |MaxBaz| determines the end point of the triangle. A value of |MaxBaz| being not larger than the simulation step size is identical with applying no unit hydrograph at all: ...
Update |QFactor| based on |Area| and the current simulation step size. >>> from hydpy.models.hland import * >>> parameterstep('1d') >>> simulationstep('12h') >>> area(50.0) >>> derived.qfactor.update() >>> derived.qfactor qfactor(1.157407) def update(sel...
Number of neurons of the hidden layers. >>> from hydpy import ANN >>> ann = ANN(None) >>> ann(nmb_inputs=2, nmb_neurons=(2, 1), nmb_outputs=3) >>> ann.nmb_neurons (2, 1) >>> ann.nmb_neurons = (3,) >>> ann.nmb_neurons (3,) >>> del ann.nmb_neurons ...
Shape of the array containing the activation of the hidden neurons. The first integer value is the number of connection between the hidden layers, the second integer value is maximum number of neurons of all hidden layers feeding information into another hidden layer (all except the las...
Number of hidden weights. >>> from hydpy import ANN >>> ann = ANN(None) >>> ann(nmb_inputs=2, nmb_neurons=(4, 3, 2), nmb_outputs=3) >>> ann.nmb_weights_hidden 18 def nmb_weights_hidden(self) -> int: """Number of hidden weights. >>> from hydpy import ANN ...
Raise a |RuntimeError| if the network's shape is not defined completely. >>> from hydpy import ANN >>> ANN(None).verify() Traceback (most recent call last): ... RuntimeError: The shape of the the artificial neural network \ parameter `ann` of element `?` has not been def...
Return a string representation of the actual |anntools.ANN| object that is prefixed with the given string. def assignrepr(self, prefix) -> str: """Return a string representation of the actual |anntools.ANN| object that is prefixed with the given string.""" prefix = '%s%s(' % (prefix, se...
Plot the relationship between a certain input (`idx_input`) and a certain output (`idx_output`) variable described by the actual |anntools.ANN| object. Define the lower and the upper bound of the x axis via arguments `xmin` and `xmax`. The number of plotting points can be modified ...
Prepare the actual |anntools.SeasonalANN| object for calculations. Dispite all automated refreshings explained in the general documentation on class |anntools.SeasonalANN|, it is still possible to destroy the inner consistency of a |anntools.SeasonalANN| instance, as it stores its |annt...
Raise a |RuntimeError| and removes all handled neural networks, if the they are defined inconsistently. Dispite all automated safety checks explained in the general documentation on class |anntools.SeasonalANN|, it is still possible to destroy the inner consistency of a |anntools.Season...
The shape of array |anntools.SeasonalANN.ratios|. def shape(self) -> Tuple[int, ...]: """The shape of array |anntools.SeasonalANN.ratios|.""" return tuple(int(sub) for sub in self.ratios.shape)
Private on purpose. def _set_shape(self, shape): """Private on purpose.""" try: shape = (int(shape),) except TypeError: pass shp = list(shape) shp[0] = timetools.Period('366d')/self.simulationstep shp[0] = int(numpy.ceil(round(shp[0], 10))) ...
A sorted |tuple| of all contained |TOY| objects. def toys(self) -> Tuple[timetools.TOY, ...]: """A sorted |tuple| of all contained |TOY| objects.""" return tuple(toy for (toy, _) in self)
Call method |anntools.ANN.plot| of all |anntools.ANN| objects handled by the actual |anntools.SeasonalANN| object. def plot(self, xmin, xmax, idx_input=0, idx_output=0, points=100, **kwargs) -> None: """Call method |anntools.ANN.plot| of all |anntools.ANN| objects handled by the ac...
The string corresponding to the current values of `subgroup`, `state`, and `variable`. >>> from hydpy.core.itemtools import ExchangeSpecification >>> spec = ExchangeSpecification('hland_v1', 'fluxes.qt') >>> spec.specstring 'fluxes.qt' >>> spec.series = True >>> ...
Apply method |ExchangeItem.insert_variables| to collect the relevant target variables handled by the devices of the given |Selections| object. We prepare the `LahnH` example project to be able to use its |Selections| object: >>> from hydpy.core.examples import prepare_full_exam...
Determine the relevant target or base variables (as defined by the given |ExchangeSpecification| object ) handled by the given |Selections| object and insert them into the given `device2variable` dictionary. def insert_variables( self, device2variable, exchangespec, selections) -> N...
Assign the given value(s) to the given target or base variable. If the assignment fails, |ChangeItem.update_variable| raises an error like the following: >>> from hydpy.core.examples import prepare_full_example_2 >>> hp, pub, TestIO = prepare_full_example_2() >>> item = SetItem...
Assign the current objects |ChangeItem.value| to the values of the target variables. We use the `LahnH` project in the following: >>> from hydpy.core.examples import prepare_full_example_2 >>> hp, pub, TestIO = prepare_full_example_2() In the first example, a 0-dimensional |Se...
Apply method |ChangeItem.collect_variables| of the base class |ChangeItem| and also apply method |ExchangeItem.insert_variables| of class |ExchangeItem| to collect the relevant base variables handled by the devices of the given |Selections| object. >>> from hydpy.core.examples import pr...
Add the general |ChangeItem.value| with the |Device| specific base variable and assign the result to the respective target variable. >>> from hydpy.core.examples import prepare_full_example_2 >>> hp, pub, TestIO = prepare_full_example_2() >>> from hydpy.models.hland_v1 import FIELD ...
Apply method |ExchangeItem.collect_variables| of the base class |ExchangeItem| and determine the `ndim` attribute of the current |ChangeItem| object afterwards. The value of `ndim` depends on whether the values of the target variable or its time series is of interest: >>> from ...
Sequentially return name-value-pairs describing the current state of the target variables. The names are automatically generated and contain both the name of the |Device| of the respective |Variable| object and the target description: >>> from hydpy.core.examples import prepare...
Returns the weekday's name given a ISO weekday number; "today" if today is the same weekday. def iso_day_to_weekday(d): """ Returns the weekday's name given a ISO weekday number; "today" if today is the same weekday. """ if int(d) == utils.get_now().isoweekday(): return _("today") f...
Returns False if the location is closed, or the OpeningHours object to show the location is currently open. def is_open(location=None, attr=None): """ Returns False if the location is closed, or the OpeningHours object to show the location is currently open. """ obj = utils.is_open(location) ...
Returns False if the location is closed, or the OpeningHours object to show the location is currently open. Same as `is_open` but passes `now` to `utils.is_open` to bypass `get_now()`. def is_open_now(location=None, attr=None): """ Returns False if the location is closed, or the OpeningHours object ...
Creates a rendered listing of hours. def opening_hours(location=None, concise=False): """ Creates a rendered listing of hours. """ template_name = 'openinghours/opening_hours_list.html' days = [] # [{'hours': '9:00am to 5:00pm', 'name': u'Monday'}, {'hours... # Without `location`, choose the ...
Convenience method to make the actual |HydPy| instance runable. def prepare_everything(self): """Convenience method to make the actual |HydPy| instance runable.""" self.prepare_network() self.init_models() self.load_conditions() with hydpy.pub.options.warnmissingobsfile(False): ...
Load all network files as |Selections| (stored in module |pub|) and assign the "complete" selection to the |HydPy| object. def prepare_network(self): """Load all network files as |Selections| (stored in module |pub|) and assign the "complete" selection to the |HydPy| object.""" hydpy.pu...
Call method |Elements.save_controls| of the |Elements| object currently handled by the |HydPy| object. We use the `LahnH` example project to demonstrate how to write a complete set parameter control files. For convenience, we let function |prepare_full_example_2| prepare a fully functi...
Print out some properties of the network defined by the |Node| and |Element| objects currently handled by the |HydPy| object. def networkproperties(self): """Print out some properties of the network defined by the |Node| and |Element| objects currently handled by the |HydPy| object.""" ...
The number of distinct networks defined by the|Node| and |Element| objects currently handled by the |HydPy| object. def numberofnetworks(self): """The number of distinct networks defined by the|Node| and |Element| objects currently handled by the |HydPy| object.""" sels1 = selectiontool...
|Nodes| object containing all |Node| objects currently handled by the |HydPy| object which define a downstream end point of a network. def endnodes(self): """|Nodes| object containing all |Node| objects currently handled by the |HydPy| object which define a downstream end point of a network."""...
Sorted list of strings summarizing all variables handled by the |Node| objects def variables(self): """Sorted list of strings summarizing all variables handled by the |Node| objects""" variables = set([]) for node in self.nodes: variables.add(node.variable) r...
Tuple containing the start and end index of the simulation period regarding the initialization period defined by the |Timegrids| object stored in module |pub|. def simindices(self): """Tuple containing the start and end index of the simulation period regarding the initialization period ...
Call method |Devices.open_files| of the |Nodes| and |Elements| objects currently handled by the |HydPy| object. def open_files(self, idx=0): """Call method |Devices.open_files| of the |Nodes| and |Elements| objects currently handled by the |HydPy| object.""" self.elements.open_files(idx...
Determines the order, in which the |Node| and |Element| objects currently handled by the |HydPy| objects need to be processed during a simulation time step. Optionally, a |Selection| object for defining new |Node| and |Element| objects can be passed. def update_devices(self, selection=None): ...
A list containing all methods of all |Node| and |Element| objects that need to be processed during a simulation time step in the order they must be called. def methodorder(self): """A list containing all methods of all |Node| and |Element| objects that need to be processed during a simu...
Perform a simulation run over the actual simulation time period defined by the |Timegrids| object stored in module |pub|. def doit(self): """Perform a simulation run over the actual simulation time period defined by the |Timegrids| object stored in module |pub|.""" idx_start, idx_end = ...
Update the inlet link sequence. Required inlet sequence: |dam_inlets.Q| Calculated flux sequence: |Inflow| Basic equation: :math:`Inflow = Q` def pic_inflow_v1(self): """Update the inlet link sequence. Required inlet sequence: |dam_inlets.Q| Calculated flux sequence...
Update the inlet link sequences. Required inlet sequences: |dam_inlets.Q| |dam_inlets.S| |dam_inlets.R| Calculated flux sequence: |Inflow| Basic equation: :math:`Inflow = Q + S + R` def pic_inflow_v2(self): """Update the inlet link sequences. Required inlet sequenc...
Update the receiver link sequence. def pic_totalremotedischarge_v1(self): """Update the receiver link sequence.""" flu = self.sequences.fluxes.fastaccess rec = self.sequences.receivers.fastaccess flu.totalremotedischarge = rec.q[0]
Update the receiver link sequence. def pic_loggedrequiredremoterelease_v1(self): """Update the receiver link sequence.""" log = self.sequences.logs.fastaccess rec = self.sequences.receivers.fastaccess log.loggedrequiredremoterelease[0] = rec.d[0]
Update the receiver link sequence. def pic_loggedrequiredremoterelease_v2(self): """Update the receiver link sequence.""" log = self.sequences.logs.fastaccess rec = self.sequences.receivers.fastaccess log.loggedrequiredremoterelease[0] = rec.s[0]
Update the receiver link sequence. def pic_loggedallowedremoterelieve_v1(self): """Update the receiver link sequence.""" log = self.sequences.logs.fastaccess rec = self.sequences.receivers.fastaccess log.loggedallowedremoterelieve[0] = rec.r[0]
Log a new entry of discharge at a cross section far downstream. Required control parameter: |NmbLogEntries| Required flux sequence: |TotalRemoteDischarge| Calculated flux sequence: |LoggedTotalRemoteDischarge| Example: The following example shows that, with each new method...
Determine the water level based on an artificial neural network describing the relationship between water level and water stage. Required control parameter: |WaterVolume2WaterLevel| Required state sequence: |WaterVolume| Calculated aide sequence: |WaterLevel| Example: ...
Calculate the allowed maximum relieve another location is allowed to discharge into the dam. Required control parameters: |HighestRemoteRelieve| |WaterLevelRelieveThreshold| Required derived parameter: |WaterLevelRelieveSmoothPar| Required aide sequence: |WaterLevel| Calc...
Calculate the required maximum supply from another location that can be discharged into the dam. Required control parameters: |HighestRemoteSupply| |WaterLevelSupplyThreshold| Required derived parameter: |WaterLevelSupplySmoothPar| Required aide sequence: |WaterLevel| Cal...
Try to estimate the natural discharge of a cross section far downstream based on the last few simulation steps. Required control parameter: |NmbLogEntries| Required log sequences: |LoggedTotalRemoteDischarge| |LoggedOutflow| Calculated flux sequence: |NaturalRemoteDischarge| ...
Estimate the discharge demand of a cross section far downstream. Required control parameter: |RemoteDischargeMinimum| Required derived parameters: |dam_derived.TOY| Required flux sequence: |dam_derived.TOY| Calculated flux sequence: |RemoteDemand| Basic equation: :...
Estimate the shortfall of actual discharge under the required discharge of a cross section far downstream. Required control parameters: |NmbLogEntries| |RemoteDischargeMinimum| Required derived parameters: |dam_derived.TOY| Required log sequence: |LoggedTotalRemoteDischarge| ...
Guess the required release necessary to not fall below the threshold value at a cross section far downstream with a certain level of certainty. Required control parameter: |RemoteDischargeSafety| Required derived parameters: |RemoteDischargeSmoothPar| |dam_derived.TOY| Required flux...
Get the required remote release of the last simulation step. Required log sequence: |LoggedRequiredRemoteRelease| Calculated flux sequence: |RequiredRemoteRelease| Basic equation: :math:`RequiredRemoteRelease = LoggedRequiredRemoteRelease` Example: >>> from hydpy.models.da...
Get the allowed remote relieve of the last simulation step. Required log sequence: |LoggedAllowedRemoteRelieve| Calculated flux sequence: |AllowedRemoteRelieve| Basic equation: :math:`AllowedRemoteRelieve = LoggedAllowedRemoteRelieve` Example: >>> from hydpy.models.dam imp...
Calculate the total water release (immediately and far downstream) required for reducing drought events. Required control parameter: |NearDischargeMinimumThreshold| Required derived parameters: |NearDischargeMinimumSmoothPar2| |dam_derived.TOY| Required flux sequence: |Require...
Calculate the water release (immediately downstream) required for reducing drought events. Required control parameter: |NearDischargeMinimumThreshold| Required derived parameter: |dam_derived.TOY| Calculated flux sequence: |RequiredRelease| Basic equation: :math:`Required...
Calculate the highest possible water release that can be routed to a remote location based on an artificial neural network describing the relationship between possible release and water stage. Required control parameter: |WaterLevel2PossibleRemoteRelieve| Required aide sequence: |WaterLeve...
Calculate the actual amount of water released to a remote location to relieve the dam during high flow conditions. Required control parameter: |RemoteRelieveTolerance| Required flux sequences: |AllowedRemoteRelieve| |PossibleRemoteRelieve| Calculated flux sequence: |ActualRemo...
Calculate the targeted water release for reducing drought events, taking into account both the required water release and the actual inflow into the dam. Some dams are supposed to maintain a certain degree of low flow variability downstream. In case parameter |RestrictTargetedRelease| is set to `T...
Calculate the actual water release that can be supplied by the dam considering the targeted release and the given water level. Required control parameter: |WaterLevelMinimumThreshold| Required derived parameters: |WaterLevelMinimumSmoothPar| Required flux sequence: |TargetedRelease|...
Calculate the portion of the required remote demand that could not be met by the actual discharge release. Required flux sequences: |RequiredRemoteRelease| |ActualRelease| Calculated flux sequence: |MissingRemoteRelease| Basic equation: :math:`MissingRemoteRelease = max( ...
Calculate the actual remote water release that can be supplied by the dam considering the required remote release and the given water level. Required control parameter: |WaterLevelMinimumRemoteThreshold| Required derived parameters: |WaterLevelMinimumRemoteSmoothPar| Required flux sequenc...
Constrain the actual relieve discharge to a remote location. Required control parameter: |HighestRemoteDischarge| Required derived parameter: |HighestRemoteSmoothPar| Updated flux sequence: |ActualRemoteRelieve| Basic equation - discontinous: :math:`ActualRemoteRelieve = min(...
Calculate the discharge during and after a flood event based on an |anntools.SeasonalANN| describing the relationship(s) between discharge and water stage. Required control parameter: |WaterLevel2FloodDischarge| Required derived parameter: |dam_derived.TOY| Required aide sequence: ...
Calculate the total outflow of the dam. Note that the maximum function is used to prevent from negative outflow values, which could otherwise occur within the required level of numerical accuracy. Required flux sequences: |ActualRelease| |FloodDischarge| Calculated flux sequence: ...
Update the actual water volume. Required derived parameter: |Seconds| Required flux sequences: |Inflow| |Outflow| Updated state sequence: |WaterVolume| Basic equation: :math:`\\frac{d}{dt}WaterVolume = 1e-6 \\cdot (Inflow-Outflow)` Example: >>> from hydpy....
Update the outlet link sequence |dam_outlets.Q|. def pass_outflow_v1(self): """Update the outlet link sequence |dam_outlets.Q|.""" flu = self.sequences.fluxes.fastaccess out = self.sequences.outlets.fastaccess out.q[0] += flu.outflow
Update the outlet link sequence |dam_outlets.S|. def pass_actualremoterelease_v1(self): """Update the outlet link sequence |dam_outlets.S|.""" flu = self.sequences.fluxes.fastaccess out = self.sequences.outlets.fastaccess out.s[0] += flu.actualremoterelease
Update the outlet link sequence |dam_outlets.R|. def pass_actualremoterelieve_v1(self): """Update the outlet link sequence |dam_outlets.R|.""" flu = self.sequences.fluxes.fastaccess out = self.sequences.outlets.fastaccess out.r[0] += flu.actualremoterelieve
Update the outlet link sequence |dam_senders.D|. def pass_missingremoterelease_v1(self): """Update the outlet link sequence |dam_senders.D|.""" flu = self.sequences.fluxes.fastaccess sen = self.sequences.senders.fastaccess sen.d[0] += flu.missingremoterelease
Update the outlet link sequence |dam_outlets.R|. def pass_allowedremoterelieve_v1(self): """Update the outlet link sequence |dam_outlets.R|.""" flu = self.sequences.fluxes.fastaccess sen = self.sequences.senders.fastaccess sen.r[0] += flu.allowedremoterelieve
Update the outlet link sequence |dam_outlets.S|. def pass_requiredremotesupply_v1(self): """Update the outlet link sequence |dam_outlets.S|.""" flu = self.sequences.fluxes.fastaccess sen = self.sequences.senders.fastaccess sen.s[0] += flu.requiredremotesupply
Log a new entry of discharge at a cross section far downstream. Required control parameter: |NmbLogEntries| Required flux sequence: |Outflow| Calculated flux sequence: |LoggedOutflow| Example: The following example shows that, with each new method call, the three m...
(Re)calculate the MA coefficients based on the instantaneous unit hydrograph. def update_coefs(self): """(Re)calculate the MA coefficients based on the instantaneous unit hydrograph.""" coefs = [] sum_coefs = 0. moment1 = self.iuh.moment1 for t in itertools.count...
Turning point (index and value tuple) in the recession part of the MA approximation of the instantaneous unit hydrograph. def turningpoint(self): """Turning point (index and value tuple) in the recession part of the MA approximation of the instantaneous unit hydrograph.""" coefs = self....
The first two time delay weighted statistical moments of the MA coefficients. def moments(self): """The first two time delay weighted statistical moments of the MA coefficients.""" moment1 = statstools.calc_mean_time(self.delays, self.coefs) moment2 = statstools.calc_mean_time_d...