Model

class Model(oseries, constant=True, noisemodel=True, name=None, metadata=None)

Class that initiates a Pastas time series model.

Parameters

• oseries (pandas.Series or pastas.TimeSeries) – pandas Series object containing the dependent time series. The observation can be non-equidistant.

• constant (bool, optional) – Add a constant to the model (Default=True).

• noisemodel (bool, optional) – Add the default noisemodel to the model. A custom noisemodel can be added later in the modelling process as well.

• name (str, optional) – String with the name of the model, used in plotting and saving.

• metadata (dict, optional) – Dictionary containing metadata of the oseries, passed on the to oseries when creating a pastas TimeSeries object. hence, ml.oseries.metadata will give you the metadata.

Returns

ml – Pastas Model instance, the base object in Pastas.

Return type

pastas.model.Model

Examples

A minimal working example of the Model class is shown below:

>>> oseries = pd.Series([1,2,1], index=pd.to_datetime(range(3), unit="D"))
>>> ml = Model(oseries)

Methods

__init__	Initialize self.
add_constant	Add a Constant to the time series Model.
add_noisemodel	Adds a noisemodel to the time series Model.
add_stressmodel	Add a stressmodel to the main model.
add_transform	Add a Transform to the time series Model.
copy	Method to copy a model.
del_constant	Method to safely delete the Constant from the Model.
del_noisemodel	Method to safely delete the noise model from the Model.
del_stressmodel	Method to safely delete a stress model from the Model.
del_transform	Method to safely delete the transform from the Model.
fit_report	Method that reports on the fit after a model is optimized.
get_block_response	Method to obtain the block response for a stressmodel.
get_contribution	Method to get the contribution of a stressmodel.
get_contributions	Method to get contributions of all stressmodels.
get_init_parameters	Method to get all initial parameters from the individual objects.
get_parameters	Method to obtain the parameters needed for calculation.
get_response_tmax	Method to get the tmax used for the response function.
get_step_response	Method to obtain the step response for a stressmodel.
get_stress	Method to obtain the stress(es) from the stressmodel.
get_stressmodel_names	Returns list of stressmodel names
get_tmax	Method that checks and returns valid values for tmax.
get_tmin	Method that checks and returns valid values for tmin.
get_transform_contribution	Method to get the contribution of a transform.
initialize	Method to initialize the model.
noise	Method to simulate the noise when a noisemodel is present.
noise_weights	Internal method to calculate the noise weights.
observations	Method that returns the observations series used for calibration.
residuals	Method to calculate the residual series.
set_initial	Method to set the initial value of any parameter.
set_parameter	Method to change the parameter properties.
set_pmax	Method to set the maximum values of a parameter.
set_pmin	Method to set the minimum value of a parameter.
set_vary	Method to set if the parameter is allowed to vary.
simulate	Method to simulate the time series model.
solve	Method to solve the time series model.
to_dict	Method to export a model to a dictionary.
to_file	Method to save the Pastas model to a file.

API-docs pastas.model.Model.__init__