pyoculus.solvers.poincare_plot.PoincarePlot Class Reference

Class that used to setup the Poincare plot. More...

Inheritance diagram for pyoculus.solvers.poincare_plot.PoincarePlot:

Public Member Functions
	__init__ (self, problem, params=dict(), integrator=None, integrator_params=dict())
	Sets up the Poincare plot.
	compute (self)
	Computes the Poincare plot.
	compute_iota (self)
	Compute the iota profile.
	compute_q (self)
	Compute the q profile.
	plot (self, plottype=None, xlabel=None, ylabel=None, xlim=None, ylim=None, **kwargs)
	plot_iota (self, xlim=None, ylim=None, **kwargs)
	Generates the iota plot.
	plot_q (self, xlim=None, ylim=None, **kwargs)
	Generates the q plot.
Public Member Functions inherited from pyoculus.solvers.base_solver.BaseSolver
	is_successful (self)
	Returns True if the computation is successfully completed.

Public Attributes
	Nfp = problem.Nfp
bool	iota_successful = False
	x
	y = np.zeros_like(self.x)
	z = np.zeros_like(self.x)
	s = np.zeros_like(self.x)
	theta = np.zeros_like(self.x)
	zeta = np.zeros_like(self.x)
bool	successful = False
int	dt = 2 * np.pi / float(self.Nfp)
	siota = self.x[:,0]
	iota = np.zeros_like(self.siota)
int	_is_cylindrical_problem = 20)
Public Attributes inherited from pyoculus.solvers.base_solver.BaseSolver
bool	successful = False
	flagging if the computation is done and successful

Static Protected Member Functions
	_run_poincare (params)

Protected Attributes
bool	_is_cylindrical_problem = False
	_begin = params["sbegin"]
	_end = params["send"]
	_fixed_coords = params["theta"]
Protected Attributes inherited from pyoculus.solvers.base_solver.BaseSolver
	_integrator_type = RKIntegrator
	_params = dict(params)
	_integrator = self._integrator_type(integrator_params)
	_problem = problem
	_integrator_params = dict(integrator_params)

Detailed Description

Class that used to setup the Poincare plot.

Constructor & Destructor Documentation

__init__()

pyoculus.solvers.poincare_plot.PoincarePlot.__init__	(		self,
			problem,
			params = dict(),
			integrator = None,
			integrator_params = dict() )

Sets up the Poincare plot.

Parameters

problem	must inherit pyoculus.problems.BaseProblem, the problem to solve
params	dict, the parameters for the solver
integrator	the integrator to use, must inherit \pyoculus.integrators.BaseIntegrator, if set to None by default using RKIntegrator
integrator_params	dict, the parmaters passed to the integrator

params['theta']=0 – the Poincare plots starts from theta

params['zeta']=0 – the Poincare plots for which toroidal section: zeta

params['nPpts']=500 – the number of iterations

params['nPtrj']=10 – the number of equidistant points in s coordinates

params['sbegin']=-1.0 – the lower bound of s

params['send']=-1.0 – the upper bound of s

params['nthreads']=1 – the number of threads

Reimplemented from pyoculus.solvers.base_solver.BaseSolver.

Member Function Documentation

_run_poincare()

pyoculus.solvers.poincare_plot.PoincarePlot._run_poincare ( params )

staticprotected

A function called in parallel to generate the Poincare plot for one starting point
Called in PoincarePlot.compute, do not call otherwise

compute()

pyoculus.solvers.poincare_plot.PoincarePlot.compute

(

self

)

Computes the Poincare plot.

Returns

pdata – a class that contains the results

pdata.x,pdata.y,pdata,z – the Poincare data in xyz coordinates pdata.s,pdata,theta,pdata,zeta – the Poincare data in s,theta,zeta coordinates

compute_iota()

pyoculus.solvers.poincare_plot.PoincarePlot.compute_iota

(

self

)

Compute the iota profile.

compute_q()

pyoculus.solvers.poincare_plot.PoincarePlot.compute_q

(

self

)

Compute the q profile.

plot()

pyoculus.solvers.poincare_plot.PoincarePlot.plot	(		self,
			plottype = None,
			xlabel = None,
			ylabel = None,
			xlim = None,
			ylim = None,
		**	kwargs )

plot_iota()

pyoculus.solvers.poincare_plot.PoincarePlot.plot_iota	(		self,
			xlim = None,
			ylim = None,
		**	kwargs )

Generates the iota plot.

Parameters

xlim,ylim	the range of plotting, by default plotting the range of all data
**kwargs	passed to the plotting routine "plot"

plot_q()

pyoculus.solvers.poincare_plot.PoincarePlot.plot_q	(		self,
			xlim = None,
			ylim = None,
		**	kwargs )

Generates the q plot.

Parameters

xlim,ylim	the range of plotting, by default plotting the range of all data
**kwargs	passed to the plotting routine "plot"

Member Data Documentation

_begin

pyoculus.solvers.poincare_plot.PoincarePlot._begin = params["sbegin"]

protected

_end

pyoculus.solvers.poincare_plot.PoincarePlot._end = params["send"]

protected

_fixed_coords

pyoculus.solvers.poincare_plot.PoincarePlot._fixed_coords = params["theta"]

protected

_is_cylindrical_problem [1/2]

int pyoculus.solvers.poincare_plot.PoincarePlot._is_cylindrical_problem = False

protected

_is_cylindrical_problem [2/2]

int pyoculus.solvers.poincare_plot.PoincarePlot._is_cylindrical_problem = 20)

dt

int pyoculus.solvers.poincare_plot.PoincarePlot.dt = 2 * np.pi / float(self.Nfp)

iota

pyoculus.solvers.poincare_plot.PoincarePlot.iota = np.zeros_like(self.siota)

iota_successful

pyoculus.solvers.poincare_plot.PoincarePlot.iota_successful = False

Nfp

pyoculus.solvers.poincare_plot.PoincarePlot.Nfp = problem.Nfp

s

pyoculus.solvers.poincare_plot.PoincarePlot.s = np.zeros_like(self.x)

siota

pyoculus.solvers.poincare_plot.PoincarePlot.siota = self.x[:,0]

successful

bool pyoculus.solvers.poincare_plot.PoincarePlot.successful = False

theta

pyoculus.solvers.poincare_plot.PoincarePlot.theta = np.zeros_like(self.x)

x

pyoculus.solvers.poincare_plot.PoincarePlot.x

Initial value:

=  np.zeros(
            [self._params["nPtrj"] + 1, self._params["nPpts"] + 1], dtype=np.float64
        )

y

pyoculus.solvers.poincare_plot.PoincarePlot.y = np.zeros_like(self.x)

z

pyoculus.solvers.poincare_plot.PoincarePlot.z = np.zeros_like(self.x)

zeta

pyoculus.solvers.poincare_plot.PoincarePlot.zeta = np.zeros_like(self.x)

---

The documentation for this class was generated from the following file:

• pyoculus/solvers/poincare_plot.py