virtualargofleet.VirtualFleet

class VirtualFleet(plan: dict, fieldset: FieldSet | VelocityField, mission: dict | FloatConfiguration | Iterable[dict] | Iterable[FloatConfiguration], isglobal: bool = False, **kwargs)

Argo Virtual Fleet simulator.

This class makes it easy to process and analyse a simulation.

__init__(plan: dict, fieldset: FieldSet | VelocityField, mission: dict | FloatConfiguration | Iterable[dict] | Iterable[FloatConfiguration], isglobal: bool = False, **kwargs)

Create an Argo Virtual Fleet simulator

Parameters:

• plan (dict) – A dictionary with the deployment plan coordinates as keys: lat, lon, time, [depth] Each value are Numpy arrays describing where Argo floats are deployed. Depth is optional, if not provided it will be set to 1m.

• fieldset (parcels.fieldset.FieldSet or VelocityField) – A velocity field

• mission (dict or FloatConfiguration or an iterable of those) –

  A dictionary with the following Argo float mission parameters: parking_depth, profile_depth, vertical_speed and cycle_duration. A FloatConfiguration instance can also be passed.

  An iterable of dictionaries or FloatConfiguration can be passed to specified mission parameters for each virtual floats. In this case, the length of the iterable must match the length of the deployment plan.

• isglobal (bool, optional, default=False) – A boolean indicating weather the velocity field is global or not

Methods

__init__(plan, fieldset, mission[, isglobal])	Create an Argo Virtual Fleet simulator
plot_positions()	Plot the last position of virtual Argo Floats
simulate(duration[, step, record, output, ...])	Execute a Virtual Fleet simulation
to_index([file_name])	Return last simulated profile index dataframe

Attributes

ParticleSet	Return ParticleSet
fieldset	Return FieldSet
output	Return absolute path to the last simulation trajectory output file