`dedalus.core.operators`

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

Module Contents

parseables

parseable(op)

addname(name)

is_integer(x)

class Operator

property base

comp_order(ops, vars)

mul_order(vars)

class FieldCopy(arg, **kw)

Operator making a new field copy of data.

property base

name = 'FieldCopy'

check_conditions()

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

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

split(*vars)

class FieldCopyScalar(arg, **kw)

Operator making a new field copy of data.

argtypes

operate(out)

class FieldCopyArray(arg, **kw)

Operator making a new field copy of data.

argtypes

operate(out)

class FieldCopyField(arg, **kw)

Operator making a new field copy of data.

argtypes

operate(out)

class NonlinearOperator

expand(*vars): Return self.

canonical_linear_form(*vars): Raise if arguments contain specified variables (default: None)

split(*vars)

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

Operator wrapping a general python function.

Parameters

domain (domain object) – Domain
layout (layout object or identifier) – Layout of function output
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.

out[layout] = func(*args, **kw)

meta_constant(axis)

check_conditions()

operate(out)

class UnaryGridFunction(func, arg, **kw)

property base

arity = 1

supported

aliased

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

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

class UnaryGridFunctionScalar(func, arg, **kw)

argtypes

check_conditions()

operate(out)

class UnaryGridFunctionArray(func, arg, **kw)

argtypes

check_conditions()

operate(out)

class UnaryGridFunctionField(func, arg, **kw)

argtypes

check_conditions()

operate(out)

class Arithmetic

arity = 2

comp_order(ops, vars)

class Add

property base

name = 'Add'

str_op = ' + '

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

expand(*vars): Expand arguments containing specified variables (default: all).

canonical_linear_form(*vars): Ensure arguments have same dependency on specified variables.

split(*vars)

operator_dict(index, vars, **kw): Produce matrix-operator dictionary over specified variables.

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

mul_order(vars)

class AddScalarScalar

argtypes

check_conditions()

operate(out)

class AddArrayArray

argtypes

check_conditions()

operate(out)

class AddFieldField

argtypes

check_conditions()

operate(out)

class AddScalarArray

argtypes

check_conditions()

operate(out)

class AddArrayScalar

argtypes

check_conditions()

operate(out)

class AddScalarField

argtypes

check_conditions()

operate(out)

class AddFieldScalar

argtypes

check_conditions()

operate(out)

class AddArrayField

argtypes

check_conditions()

operate(out)

class AddFieldArray

argtypes

check_conditions()

operate(out)

class Multiply

property base

name = 'Mul'

str_op = '*'

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

expand(*vars): Distribute over sums containing specified variables (default: all).

canonical_linear_form(*vars): Eliminate nonlinear multiplications and float specified variables right.

split(*vars)

operator_dict(index, vars, **kw): Produce matrix-operator dictionary over specified variables.

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

mul_order(vars)

class MultiplyScalarScalar

argtypes

check_conditions()

operate(out)

class MultiplyArrayArray

argtypes

check_conditions()

operate(out)

class MultiplyFieldField

argtypes

check_conditions()

operate(out)

class MultiplyScalarArray

argtypes

check_conditions()

operate(out)

class MultiplyArrayScalar

argtypes

check_conditions()

operate(out)

class MultiplyScalarField

argtypes

check_conditions()

operate(out)

class MultiplyFieldScalar

argtypes

check_conditions()

operate(out)

class MultiplyArrayField

argtypes

check_conditions()

operate(out)

class MultiplyFieldArray

argtypes

check_conditions()

operate(out)

class Power

property base

name = 'Pow'

str_op = '**'

mul_order(vars)

class PowerDataScalar

argtypes

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

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

class PowerScalarScalar

argtypes

check_conditions()

operate(out)

class PowerArrayScalar

argtypes

check_conditions()

operate(out)

class PowerFieldScalar

argtypes

check_conditions()

operate(out)

class LinearOperator

kw

expand(*vars): Distribute over sums containing specified variables (default: all).

canonical_linear_form(*vars): Change argument to canonical linear form.

split(*vars)

operator_dict(index, vars, **kw): Produce matrix-operator dictionary over specified variables.

abstract operator_form(index)

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

class TimeDerivative

property base

name = 'dt'

meta_constant(axis)

meta_parity(axis)

meta_envelope(axis)

operator_form(index)

operate(out)

class LinearBasisOperator

meta()

class Separable

operator_form(index)

check_conditions()

operate(out)

apply_vector_form(out)

abstract explicit_form(input, output, axis)

abstract vector_form()

class Coupled

operator_form(index)

check_conditions()

operate(out)

apply_matrix_form(out)

abstract explicit_form(input, output, axis)

abstract matrix_form()

operator_dict(index, vars, **kw): Produce matrix-operator dictionary over specified variables.

class Integrate(arg0, **kw)

name = 'integ'

meta_constant(axis)

integrate(arg0, *bases, out=None)

class Interpolate(arg0, position, out=None)

name = 'interp'

distribute()

meta_constant(axis)

interpolate(arg0, out=None, **basis_kw)

left(arg0, out=None): Shortcut for left interpolation along last axis.

right(arg0, out=None): Shortcut for right interpolation along last axis.

class Differentiate(arg0, **kw)

name = 'd'

meta_constant(axis)

expand(*vars): Distribute over sums and apply the product rule to arguments containing specified variables (default: all).

differentiate(arg0, *bases, out=None, **basis_kw)

class HilbertTransform(arg0, **kw)

name = 'Hilbert'

meta_constant(axis)

hilberttransform(arg0, *bases, out=None, **basis_kw)

dedalus.core.operators

Module Contents

`dedalus.core.operators`