State¶

class State¶

Class gathering a collection of PhysicalParams, MomentumGrid, TimeGrid and Reference objects which point to each other according to their documentation. Can be seen as the total state and resolution at which the equation is solved for. Use this class to initiate the PhysicalParams, MomentumGrid, TimeGrid and Reference.

properties¶

VERSION¶

Version of class

Dependencies¶

physicalParams¶

PhysicalParams object shared with timeGrid and reference

reference¶

Reference object shared with all other objects in this class

momentumGrid¶

MomentumGrid object, containing a grid of momentum points

timeGrid¶

TimeGrid object containing timestep vector amongst other

Parameters for autoInitialGrid¶

NxiScalingFactor¶

uniformly rescales the predicted Nxi value from autoInitialGrid by a factor of NxiScalingFactor (default 1)

dyBulkScalingFactor¶

uniformly rescales the desired grid spacing dy at y = 0 used by autoInitialGrid (default 1, lower value yields higher resolution)

dyTailScalingFactor¶

uniformly rescales the desired grid spacing dy at y = yMax used by autoInitialGrid (default 1, lower value yields higher resolution)

Nxi_min¶

Nxi_max¶

pMax_ceiling¶

pMaxIncreaseFactor¶

minPMaxMarginFactor¶

pSwitch¶

percentBulk¶

r¶

Functions¶

Constructor¶

this = State(TRef,nRef)

Construct a new state with MomentumGrid, TimeGrid, PhysicalParams and Reference classes.

setInitialRunaway(this, Distribution)¶

Sets an initial runaway current to be used for autinitial grid. Distribution is Distribution object from which the current is calculated from. The autInitGrid then takes into account for already created runaways when estimating yMax and other parameters.

autoInitGrid(this, useScreening, useInelastic)¶

Automatically sets yMax, Nxi, Ny and gridWidth for gridMode 6 given the physical scenario. Unless Initial runaway is set, theory using a gaussian distribution as start distribution is used to estimate how far the tail will reach. Requiers that all other physical and time parameters are set to their values to give meaningfull results.