Borg2Lpt

class aquila_borg.forward.models.Borg2Lpt
Parameters

  • box (BoxModel) – BORG 3d box descriptor of the input

  • box_out (BoxMOdel) – BORG 3d box descriptor of the output

Keyword Arguments

  • rsd (bool) – Apply redshift distortion at particle level Default to False

  • supersampling (float) – Number of times to supersample the initial condition before generating Lagrangian particles. (default 1)

  • particle_factor (float) – For MPI purpose, memory overallocation per task of the particle arrays (default 1.1)

  • ai (float) – Input scale factor (default 0.1)

  • af (float) – Output scale factor (default 1.0)

  • lightcone (bool) – Whether to generate particle on lightcone at zero order (default False)

Methods

__init__(self, box, box_out, rsd, …)

accumulateAdjoint(self, do_accumulate)

Request the model to accumulate adjoint vectors instead of resetting at each call.

adjointModel_v2(self, adjoint_gradient)

Pushes the adjoint gradient from a deeper part of the computation.

clearAdjointGradient(self)

Clear accumulated information to compute the adjoint gradient vector.

forwardModel(self, arg0, arg1)

forwardModel_v2(self, arg0)

Run the first part of the forward model (v2 API).

getAdjointModel(self, arg0)

getBoxModel(self)

Return the box on which is defined the input of the model is defined.

getCommunicator(self)

Build and return an MPI4PY communicator object that is linked to the internal MPI communicator of that object.

getDensityFinal(self, arg0)

Obtain the density field produced by the forward model (part 2 of the evaluation, v2 API).

getMPISlice(self)

Returns a tuple of integer indicating the way the slab is distributed among the node.

getModelParam(self, model, keyname)

This queries the current state of the parameters ‘keyname’ in model ‘model’.

getNumberOfParticles(self)

Return the number of particles present on the current MPI task

getOutputBoxModel(self)

Return the box on which is defined the output of the model is defined.

getOutputMPISlice(self)

Return a tuple indicating what is the expected output MPI slicing (startN0,localN0,N1,N2) (Warning! unstable API)

getParticlePositions(self, positions)

Return the positions of the particles in the provided numpy array

getParticleVelocities(self, velocities)

Return the velocities of the particles in the provided numpy array

getPreferredInput(self)

Returns the preferred output format (i.e.

getPreferredOutput(self)

Returns the preferred output format (i.e.

holdParticles(self)

setAdjointRequired(self, arg0)

Indicate whether the caller require the adjoint gradient to be computed later.

setCosmoParams(self, cosmo_params)

Setup the cosmological parameters that this model requires.

setModelParams(self, params)

Allow changing model parameters for different model indexed by the dictionnary key, each item is another dictionnary with key/value pairs.

setName(self, name)

Give a to localize more easily a model instance.

setStepNotifier(self, arg0)

Setup a callback when a new step is being computed for particles.