Roger setup class

class roger.RogerSetup(override=None)

Bases: object

Main class for roger, used for building a model and running it.

Note

This class is meant to be subclassed. Subclasses need to implement the methods set_parameters(), set_topography(), set_grid(), set_coriolis(), set_initial_conditions(), set_forcing(), and set_diagnostics().

Example

>>> import matplotlib.pyplot as plt
>>> from roger import RogerSetup
>>>
>>> class MyModel(RogerSetup):
>>>     ...
>>>
>>> model = MyModel()
>>> model.run()
>>> plt.imshow(model.state.variables.theta[..., 1])
>>> plt.show()

abstract set_settings(state)

To be implemented by subclass.

First function to be called during setup. Use this functions to set the model settings and define physical constants.

Example

>>> def set_settings(self, state):
>>>     settings = state.settings
>>>     settings.nx, settings.ny, settings.nz = (360, 120, 2)

abstract set_look_up_tables(state)

To be implemented by subclass.

Use this function to set the look-up tables.

Example

>>> def set_look_up_tables(self, state):
>>>     vs = state.variables
>>>     vs.lut_ilu = update(vs.lut_ilu, at[:, :], lut.ARR_ILU)

abstract set_parameters_setup(state)

To be implemented by subclass.

Use this function to set initial or constant model parameters.

Example

>>> def set_parameters_setup(self, state):
>>>     vs = state.variables
>>>     vs.dmpv = update(vs.dmpv, at[:, :, :, vs.tau], npx.random.rand(vs.dmpv.shape[:-1]))

abstract set_parameters(state)

To be implemented by subclass.

Use this function to modify the model parameters.

Example

>>> def set_parameters(self, state):
>>>     vs = state.variables
>>>     vs.dmpv = update(vs.dmpv, at[:, :, :, vs.tau], npx.random.rand(vs.dmpv.shape[:-1]))

abstract set_initial_conditions_setup(state)

To be implemented by subclass.

Use this function to set the initial conditions.

Example

>>> @roger_method
>>> def set_initial_conditions_setup(self, state):
>>>     vs = state.variables
>>>     vs.theta_rz = update(vs.theta_rz, at[:, :, :, vs.tau], 0.4)

abstract set_initial_conditions(state)

To be implemented by subclass.

May be used to set initial conditions.

Example

>>> @roger_method
>>> def set_initial_conditions(self, state):
>>>     vs = state.variables
>>>     vs.theta_rz = update(vs.theta_rz, at[:, :, :, vs.tau], 0.4)

abstract set_boundary_conditions_setup(state)

To be implemented by subclass.

Use this function to set the boundary conditions.

Example

>>> @roger_method
>>> def set_boundary_conditions_setup(self, state):
>>>     vs = state.variables
>>>     vs.z_gw = update(vs.z_gw, at[:, :, :, :vs.taup1], 5)

abstract set_boundary_conditions(state)

To be implemented by subclass.

May be used to set boundary conditions.

Example

>>> @roger_method
>>> def set_boundary_conditions(self, state):
>>>     vs = state.variables
>>>     vs.z_gw = update(vs.z_gw, at[:, :, :, :vs.taup1], 5)

abstract set_grid(state)

To be implemented by subclass.

Has to set the grid spacings x and y, along with the coordinates of the grid origin, x_origin and y_origin.

Example

>>> @roger_method
>>> def set_grid(self, state):
>>>     vs = state.variables
>>>     vs.x_origin, vs.y_origin = 0, 0
>>>     vs.x = 1.
>>>     vs.y = 1.

abstract set_topography(state)

To be implemented by subclass.

Must specify the model topography by setting slope.

Example

>>> @roger_method
>>> def set_topography(self, state):
>>>     vs = state.variables
>>>     vs.slope = update(vs.slope, at[...], 10)

abstract set_forcing_setup(state)

To be implemented by subclass.

Called within setup, e.g. through PREC, TA, PET.

Example

>>> @roger_method
>>> def set_forcing_setup(self, state):
>>>     vs = state.variables
>>>     vs.TA = vs._ta_data

abstract set_forcing(state)

To be implemented by subclass.

Called before every time step to update the external forcing, e.g. through prec, ta, pet.

Example

>>> @roger_method
>>> def set_forcing(self, state):
>>>     vs = state.variables
>>>     vs.ta = vs.TA[:, :, vs.itt]

abstract set_diagnostics(vs, base_path=None)

To be implemented by subclass.

Called before setting up the diagnostics. Use this method e.g. to mark additional variables for output.

Example

>>> @roger_method
>>> def set_diagnostics(self, state):
>>>     state.diagnostics['snapshot'].output_variables += ['drho', 'dsalt', 'dtemp']

abstract after_timestep(state)

Called at the end of each time step. Can be used to define custom, setup-specific events.

warmup(repeat=1)

Warmup routine of the simulation.

Parameters:

repeat (int, optional) – Number of warmup runs. Default is 1.

Note

Make sure to call setup() prior to this function.

run(show_progress_bar=None)

Main routine of the simulation.

:param show_progress_bar (bool: By default, only show if stdout is a terminal and roger is running on a single process. :type show_progress_bar (bool: Whether to show fancy progress bar via tqdm. :param optional): By default, only show if stdout is a terminal and roger is running on a single process. :type optional): Whether to show fancy progress bar via tqdm.

Note

Make sure to call setup() (and warmup() if offline transport) prior to this function.