tardis.workflows.v_inner_solver module

class tardis.workflows.v_inner_solver.InnerVelocitySolverWorkflow(configuration, mean_optical_depth='rosseland', tau=None)

Bases: SimpleTARDISWorkflow

TAU_TARGET = -0.40546510810816444

check_convergence(estimated_values)

Check convergence status for a dict of estimated values

Parameters:

estimated_valuesdict

Estimates to check convergence

Returns:

bool

If convergence has occurred

estimate_v_inner()

Compute the Rosseland Mean Optical Depth, Estimate location where v_inner makes t=2/3 (or target) Extrapolate with exponential fits

Need some way to return and inspect the optical depths for later logging

get_convergence_estimates(transport_state)

Compute convergence estimates from the transport state

Parameters:

transport_stateMonteCarloTransportState

Transport state object to compute estimates

Returns:

dict

Convergence estimates

EstimatedRadiationFieldProperties

Dilute radiation file and j_blues dataclass

print_mask(mask)

property property_mask

reproject(array_one, mask_one, array_two, mask_two)

Reprojects two sub_arrays defined by a set of masks onto an array where the masks of both objects are true

let A1, A2 be arrays of size gemetry.no_of_shells and

a1 = A1[mask_one], a2 = A2[mask_two]

find a1*, a2* s.t.

a1* = A1[mask_one & mask_two], a2* = A2[mask_one & mask_two]

this is equivalent to

a1* = A1[mask_one][mask_two[mask_one]] = a1[mask_two[mask_one]], a2* = A2[mask_two][mask_one[mask_two]] = a2[mask_one[mask_two]]

Parameters:

array1np.ndarray

A sub array of an array with the shape of a geometry property

mask_onenp.ndarray(bool)

Mask such that the parrent array accessed at this mask gives a1

array_twonp.ndarray

A sub array of an array with the shape of a geometry property

mask_twonp.ndarray(bool)

Mask such that the parrent array accessed at this mask gives a2

Returns:

array_one*

reprojection of array_one onto mask_one & mask_two

array_two*

reprojection of array_two onto mask_one & mask_two

run()

Run the TARDIS simulation until convergence is reached

solve_plasma(estimated_radfield_properties, mask)

Update the plasma solution with the new radiation field estimates

Parameters:

estimated_radfield_propertiesEstimatedRadiationFieldProperties

The radiation field properties to use for updating the plasma

radiation_field: tardis.plasma.radiation_field.RadiationField

Current radiation field object from the last iteration

Raises:

ValueError

If the plasma solver radiative rates type is unknown

solve_simulation_state(estimated_values)

Update the simulation state with new inputs computed from previous iteration estimates.

Parameters:

estimated_valuesdict

Estimated from the previous iterations

Returns:

next_valuesdict

The next values assigned to the simulation state