dedalus.core.operators

Abstract and built-in classes defining deferred operations on fields.

Module Contents

class AdvectiveCFL(operand, coords)

Calculates the scalar advective grid-crossing frequency associated with a given velocity vector.

Parameters:

operand (number or Operand object)
space (Space object)

check_conditions(): Check that operands are in full grid space.

abstractmethod compute_cfl_frequency(velocity, out): Return a scalar multi-D field of the cfl frequency everywhere in the domain.

enforce_conditions(): Require operands to be in full grid space.

new_operand(operand, **kw)

operate(out): Perform operation.

coords

domain

dtype

input_basis

name = 'cfl'

operand

tensorsig = ()

class AngularComponent(operand, index=0, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Angular'

class Average(operand, coord)

Average over operand bases.

Parameters:

operand (number or Operand object)
coords (Coordinate or CoordinateSystem object, or list of these)

coord

domain

dtype

first_axis

input_basis

last_axis

name = 'Average'

operand

output_basis

tensorsig

class AzimuthalComponent(operand, index=0, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Azimuthal'

tensorsig

class Component(operand, index=0, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

check_conditions(): Can always take components

enforce_conditions(): Can always take components

matrix_coupling(*vars)

matrix_dependence(*vars)

coordsys

domain

dtype

index = 0

input_basis

name = 'Component'

operand

tensorsig

class Convert(operand, output_basis, out=None)

Convert an operand between two bases, assuming coupling over just the last axis of the bases.

Parameters:

operand (Operand object)
output_basis (Basis object)

check_conditions(): Check that arguments are in a proper layout.

enforce_conditions(): Require arguments to be in a proper layout.

new_operand(operand, **kw)

operate(out): Perform operation.

replace(old, new): Replace specified operand/operator.

replace_dict(subs): Replace specified operands/operators according to a dictionary.

subspace_matrix(layout): Build matrix operating on global subspace data.

coords

domain

dtype

first_axis

input_basis

last_axis

name = 'Convert'

operand

output_basis

tensorsig

class Curl(*args, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Curl'

class Differentiate(operand, coord, out=None)

Differentiation along one dimension.

Parameters:

operand (number or Operand object)
space (Space object)

new_operand(operand, **kw)

axis

coord

domain

dtype

first_axis

input_basis

last_axis

name = 'Diff'

operand

output_basis

tensorsig

class Divergence(*args, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Div'

class GeneralFunction(dist, domain, tensorsig, dtype, layout, func, args=[], kw={}, out=None)

Operator wrapping a general python function to return a field.

Parameters:

dist (distributor object) – Distributor
domain (domain object) – Domain
tensorsig (tuple of coordinate systems) – Tensor signature of output field (corresponding to, e.g., scalar, vector, rank-2 tensor, etc.)
dtype (dtype) – Data type of output field
layout (layout object or identifier) – Layout of output field
func (function) – Function producing field data
args (list) – Arguments to pass to func
kw (dict) – Keywords to pass to func
out (field, optional) – Output field (default: new field)

Notes

On evaluation, this wrapper evaluates the provided function with the given arguments and keywords, and takes the output to be data in the specified layout, i.e.

check_conditions(): Check that arguments are in a proper layout.

enforce_conditions(): Require arguments to be in a proper layout.

operate(out): Perform operation.

args = []

dist

domain

dtype

func

kw

last_id = None

layout

original_args = []

out = None

tensorsig

class Gradient(*args, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Grad'

class Integrate(operand, coord)

Integrate over operand bases.

Parameters:

operand (number or Operand object)
coords (Coordinate or CoordinateSystem object, or list of these)

new_operand(operand, **kw)

coord

domain

dtype

first_axis

input_basis

last_axis

name = 'Integrate'

operand

output_basis

tensorsig

class Interpolate(operand, coord, position, out=None)

Interpolation along one dimension.

Parameters:

operand (number or Operand object)
space (Space object)
position (‘left’, ‘center’, ‘right’, or float)

new_operand(operand, **kw)

subspace_matrix(layout): Build matrix operating on global subspace data.

coord

domain

dtype

first_axis

input_basis

last_axis

name = 'interp'

operand

output_basis

position

tensorsig

class Laplacian(*args, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Lap'

class Lift(operand, output_basis, n, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

domain

dtype

first_axis

input_basis

last_axis

n

name = 'Lift'

operand

output_basis

tensorsig

class MulCosine(operand, coordsys=None, out=None)

Cosine multiplication for S2.

new_operand(operand, **kw)

radial_matrix(spinindex_in, spinindex_out, m)

spinindex_out(spinindex_in)

domain

dtype

name = 'MulCos'

tensorsig

class RadialComponent(operand, index=0, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'Radial'

tensorsig

class Skew(operand, index=0, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

check_conditions(): Can always take components

enforce_conditions(): Can always take components

matrix_coupling(*vars)

matrix_dependence(*vars)

new_operand(operand, **kw)

coordsys

domain

dtype

index = 0

name = 'Skew'

operand

tensorsig

class SphericalEllProduct(operand, coordsys)

Base class for linear operators acting on the coefficients of an individual spectral basis.

Subclasses must define the following attributes:

new_operand(operand, **kw)

name = 'SphericalEllProduct'

class TimeDerivative(operand, out=None)

Class for representing time derivative while parsing.

matrix_coupling(*vars)

matrix_dependence(*vars)

property base

domain

dtype

name = 'dt'

operand

tensorsig

class Trace(operand, out=None)

Base class for linear operators.

Subclasses must define the following attributes:

check_conditions(): Right now require grid space

enforce_conditions(): Require arguments to be in a proper layout.

matrix_coupling(*vars)

matrix_dependence(*vars)

new_operand(operand, **kw)

operate(out): Perform operation.

property base

coordsys

domain

dtype

input_basis

name = 'Trace'

operand

tensorsig

class TransposeComponents(operand, indices=(0, 1), out=None)

Base class for linear operators.

Subclasses must define the following attributes:

check_conditions(): Can always take the transpose

enforce_conditions(): Can always take the transpose

matrix_coupling(*vars)

matrix_dependence(*vars)

new_operand(operand, **kw)

coordsys

domain

dtype

indices

input_basis

name = 'TransposeComponents'

new_axis_order

operand

tensorsig

class UnaryGridFunction(func, arg, deriv=None, out=None)

Wrapper for applying unary functions to fields in grid space. This can be used with arbitrary user-defined functions, but symbolic differentiation is only implemented for some scipy/numpy universal functions.

Parameters:

func (function) – Unary function acting on grid data. Must be vectorized and include an output array argument, e.g. func(x, out).
arg (dedalus operand) – Argument field or operator.
deriv (function, optional) – Symbolic derivative of func. Defaults are provided for some common numpy/scipy ufuncs (default: None).
out (field, optional) – Output field (default: new field).

Notes

The supplied function must support an output argument called ‘out’ and act in a vectorized fashion. The action is essentially:

check_conditions(): Check that arguments are in a proper layout.

enforce_conditions(): Require arguments to be in a proper layout.

new_operand(arg)

new_operands(arg)

operate(out): Perform operation.

reinitialize(**kw)

sym_diff(var): Symbolically differentiate with respect to specified operand.

domain

dtype

func

property name

tensorsig

ufunc_derivatives

Coeff(operand)

Grid(operand)

LiftTau(*args, **kw)