luminarycloud.simulation¶

Classes¶

Simulation

Represents a simulation object.

Functions¶

get_simulation(→ Simulation)

Retrieve a specific simulation by ID.

Module Contents¶

class luminarycloud.simulation.Simulation(proto_type: google.protobuf.message.Message | None = None)¶

Represents a simulation object.

id: str¶: Simulation ID.

name: str¶: Simulation name.

description: str¶: Simulation description.

status: luminarycloud.enum.SimulationStatus¶: Simulation status. May not reflect current status.

mesh_id: str¶: ID of the simulation mesh.

property create_time: datetime.datetime¶

property update_time: datetime.datetime¶

update(*, name: str = None) → None¶

Update/Edit simulation attributes.

Mutates self.

Parameters:

namestr, optional: New project name.

wait(*, print_residuals: bool = False, interval_seconds: float = 5, timeout_seconds: float = float('inf')) → luminarycloud.enum.SimulationStatus¶

Wait until the simulation is completed, failed, or suspended.

Parameters:

print_residualsbool, optional: If true, residual values for the latest completed iteration will be printed. Frequency is based on interval_seconds.
intervalfloat, optional: Number of seconds between polls.
timeoutfloat, optional: Number of seconds before timeout.

Returns:

luminarycloud.enum.SimulationStatus: Current status of the simulation.

download_global_residuals(normalization: luminarycloud.enum.ResidualNormalization = ResidualNormalization.RELATIVE) → _DownloadedTextFile¶

Download global residuals in csv format.

Parameters:

normalizationResidualNormalization, optional: The type of normalization to use. Default is relative normalization.

Returns:

io.StringIO: Stream of text. The filename can be retrieved from the “filename” attribute of the object.

Examples

Create a Pandas dataframe:

>>> from luminarycloud.enum import ResidualType
>>> import pandas as pd
>>> with simulation.download_global_residuals() as dl:
...     residuals_df = pd.read_csv(dl)

Save to disk:

>>> with download_global_residuals() as dl:
...     with open(dl.filename, "wb") as fp:
...         fp.write(dl.read())

download_surface_output(quantity_type: luminarycloud.enum.QuantityType, surface_ids: list[str], *, reference_values: luminarycloud.reference_values.ReferenceValues = None, calculation_type: luminarycloud.enum.CalculationType = CalculationType.PER_SURFACE, frame_id: str = '', force_direction: luminarycloud.vector3.Vector3 | None = None, moment_center: luminarycloud.vector3.Vector3 | None = None, averaging_type: luminarycloud.enum.AveragingType = AveragingType.UNSPECIFIED) → _DownloadedTextFile¶

Downloads surface outputs (e.g. lift, drag, …) in csv format.

Parameters:

quantity_typeluminarycloud.enum.QuantityType: Surface quantity type to compute (e.g. lift, drag).
surface_idslist of str: List of names of the surfaces to compute the quantities for. Should have at least one element.

Returns:

io.StringIO: Stream of text. The filename can be retrieved from the “filename” attribute of the object.

Other Parameters:

reference_valuesReferenceValues, optional: Reference values used for computing forces, moments and other non-dimensional output quantities. If not provided, default reference values will be used.
calculation_typeCalculationType, optional: Whether the calculation should be done for all the surfaces together or each surface individually. Default is PER_SURFACE.
frame_id: str, optional: The ID of the reference frame that this output should be reported in for “force” quantity types.
force_directionVector3, optional: The direction of the query component for “force” quantity types. Required for certain quantity types.
moment_centerVector3, optional: The center of moment for “force” quantity types. Required for certain quantity types. Ignored if not applicable.
averaging_typeAveragingType, optional: The averaging method used to compute “surface average” quantity types. Ignored if not applicable.

Examples

Create a Pandas dataframe:

>>> from luminarycloud.enum import QuantityType
>>> import pandas as pd
>>> with simulation.download_surface_output(QuantityType.LIFT, ["0/bound/airfoil"], frame_id="body_frame_id") as dl:
...     outputs_df = pd.read_csv(dl)

Save to disk:

>>> with simulation.download_surface_output(QuantityType.LIFT, ["0/bound/airfoil"]) as dl:
...     with open(dl.filename, "w") as fp:
...         fp.write(dl.read())

delete() → None¶

Delete the simulation.

The simulation will be stopped first if running. This operation cannot be reverted and all the simulation data will be deleted as part of this request.

suspend() → None¶: Suspend the simulation.

list_solutions() → list[luminarycloud.solution.Solution]¶: List all solutions for this simulation in ascending order of iteration.

luminarycloud.simulation.get_simulation(id: str) → Simulation¶

Retrieve a specific simulation by ID.

Parameters:

idstr: Simulation ID.