landlab.bmi.bmi_bridge

Wrap landlab component with the Basic Modeling Interface

The wrap_as_bmi function wraps a landlab component class so that it exposes a Basic Modeling Interface.

wrap_as_bmi(cls)

Wrap a landlab class so it exposes a BMI.

Section author: Eric Hutton

class TimeStepper

Bases: object

Step through time.

Parameters:

• start (float, optional) – Clock start time.

• stop (float, optional) – Stop time.

• step (float, optional) – Time step.

Examples

>>> from landlab.bmi import TimeStepper
>>> time_stepper = TimeStepper()
>>> time_stepper.start
0.0
>>> time_stepper.stop is None
True
>>> time_stepper.step
1.0
>>> time_stepper.time
0.0
>>> for _ in range(10):
...     time_stepper.advance()
...
>>> time_stepper.time
10.0
>>> time_stepper = TimeStepper(1.0, 13.0, 2.0)
>>> [time for time in time_stepper]
[1.0, 3.0, 5.0, 7.0, 9.0, 11.0]

__init__(start=0.0, stop=None, step=1.0, units='s')

__new__(**kwargs)

advance()

Advance the time stepper by one time step.

property start

Start time.

property step

Time Step.

property stop

Stop time.

property time

Current time.

property units

Time units.

wrap_as_bmi(cls)

Wrap a landlab class so it exposes a BMI.

Give a landlab component a Basic Model Interface (BMI). Since landlab components have an interface that is already in the style of BMI, this function adds just a light wrapping to landlab components. There are a number of differences that may cause some confusion to landlab users.

1. Because BMI doesn’t have a concept of a dual grid, it only defines nodes (points), edges (vectors), and faces (areas). The dual-graph of landlab is considered as two separate grids by BMI.

2. It is important to note that BMI has only three grid elements (node, edge, and face) while landlab has 6. The names used by landlab and BMI are also different.

   Thus, a BMI-wrapped landlab component will always have two grids with grid identifiers 0, and 1. Grid 0 will contain the landlab nodes, links, and patches while grid 1 will contain corners, faces, and cells.landlab and BMI refer to grid elements by different names. The mapping from landlab to BMI nomenclature is the following:

   Grid 0 (Primal)		Grid 1 (Dual)
   Landlab	BMI	Landlab	BMI
   node	node	corner	node
   link	edge	face	edge
   patch	face	cell	face

3. In BMI, the initialize method requires an input file that is used to create and setup the model for time-stepping. landlab components generally do not have anything like this; instead this task is usually done programmatically. Thus, the input file that is used by the BMI initialize method is a standard landlab input file as used by the landlab create_grid function.

Parameters:

cls (class) – A landlab class that inherits from Component.

Returns:

A wrapped class that exposes a BMI.

Return type:

class

Examples

>>> from landlab.bmi import wrap_as_bmi
>>> from landlab.components.flexure import Flexure

>>> BmiFlexure = wrap_as_bmi(Flexure)
>>> flexure = BmiFlexure()
>>> sorted(flexure.get_input_var_names())
['boundary_condition_flag', 'lithosphere__overlying_pressure_increment']
>>> flexure.get_var_units("lithosphere__overlying_pressure_increment")
'Pa'

>>> config = '''
... flexure:
...     eet: 10.e+3
...     method: flexure
... clock:
...     start: 0.
...     stop: 10.
...     step: 2.
... grid:
...     RasterModelGrid:
...     - [20, 40]
...     - xy_spacing: [2000., 1000.]
...     - fields:
...        node:
...          lithosphere__overlying_pressure_increment:
...            constant:
...              - value: 0.0
... '''
>>> flexure.initialize(config)
>>> sorted(flexure.get_output_var_names())
['boundary_condition_flag', 'lithosphere_surface__elevation_increment']
>>> flexure.get_var_grid("lithosphere_surface__elevation_increment")
0
>>> flexure.get_grid_shape(0, np.empty(flexure.get_grid_rank(0), dtype=int))
array([20, 40])
>>> dz = np.empty(flexure.get_grid_size(0))
>>> _ = flexure.get_value("lithosphere_surface__elevation_increment", dz)

>>> np.all(dz == 0.0)
True
>>> flexure.get_current_time()
0.0

>>> sorted(flexure.get_input_var_names())
['boundary_condition_flag', 'lithosphere__overlying_pressure_increment']
>>> load = np.zeros((20, 40), dtype=float)
>>> load[0, 0] = 1.0
>>> flexure.set_value("lithosphere__overlying_pressure_increment", load)
>>> flexure.update()
>>> flexure.get_current_time()
2.0
>>> _ = flexure.get_value("lithosphere_surface__elevation_increment", dz)
>>> np.all(dz == 0.0)
False