Moments¶
Module Overview¶
This module provides functions to
generate moments according to certain patterns
compute moments of discrete probability distribution functions
create transformation rules into moment space
orthogonalize moment bases
Moment Representation¶
Moments can be represented in two ways:
by an index \(i,j\): defined as \(m_{ij} := \sum_{\mathbf{d} \in stencil} <\mathbf{d}, \mathbf{x}> f_i\)
or by a polynomial in the variables x,y and z. For example the polynomial \(x^2 y^1 z^3 + x + 1\) is describing the linear combination of moments: \(m_{213} + m_{100} + m_{000}\)
The polynomial description is more powerful, since one polynomial can express a linear combination of single moments.
All moment polynomials have to use MOMENT_SYMBOLS
(which is a module variable) as degrees of freedom.
Example
>>> from lbmpy.moments import MOMENT_SYMBOLS
>>> x, y, z = MOMENT_SYMBOLS
>>> second_order_moment = x*y + y*z
Functions¶

moment_multiplicity
(exponent_tuple)¶ Returns number of permutations of the given moment tuple
Example: >>> moment_multiplicity((2,0,0)) 3 >>> list(moment_permutations((2,0,0))) [(0, 0, 2), (0, 2, 0), (2, 0, 0)]

pick_representative_moments
(moments)¶ Picks the representative i.e. of each permutation group only one is kept

moment_permutations
(exponent_tuple)¶ Returns all (unique) permutations of the given tuple

moments_of_order
(order, dim=3, include_permutations=True)¶ All tuples of length ‘dim’ which sum equals ‘order’

moments_up_to_order
(order, dim=3, include_permutations=True)¶ All tuples of length ‘dim’ which sum is smaller than ‘order’

moments_up_to_component_order
(order, dim=3)¶ All tuples of length ‘dim’ where each entry is smaller or equal to ‘order’

extend_moments_with_permutations
(exponent_tuples)¶ Returns all permutations of the given exponent tuples

contained_moments
(exponent_tuple, min_order=0, exclude_original=True)¶ Returns all moments contained in exponent_tuple, in the sense that their exponents are less than or equal to the corresponding exponents in exponent_tuple.

exponent_to_polynomial_representation
(exponent_tuple)¶ Converts an exponent tuple to corresponding polynomial representation
Example
>>> exponent_to_polynomial_representation( (2,1,3) ) x**2*y*z**3

exponents_to_polynomial_representations
(sequence_of_exponent_tuples)¶ Applies
exponent_to_polynomial_representation()
to given sequence

polynomial_to_exponent_representation
(polynomial, dim=3)¶ Converts a linear combination of moments in polynomial representation into exponent representation
:returns list of tuples where the first element is the coefficient and the second element is the exponent tuple
Example
>>> x , y, z = MOMENT_SYMBOLS >>> set(polynomial_to_exponent_representation(1 + (42 * x**2 * y**2 * z) )) == {(42, (2, 2, 1)), (1, (0, 0, 0))} True

moment_sort_key
(moment)¶ Sort key function for moments to sort them by (in decreasing priority) order, number of occuring symbols, length of string representation, string representation

sort_moments_into_groups_of_same_order
(moments)¶ Returns a dictionary mapping the order (int) to a list of moments with that order.

is_even
(moment)¶ A moment is considered even when under sign reversal nothing changes i.e. \(m(x,y,z) = m(x,y,z)\)
 For the exponent tuple representation that means that the exponent sum is even e.g.
>>> x , y, z = MOMENT_SYMBOLS >>> is_even(x**2 * y**2) True >>> is_even(x**2 * y) False >>> is_even((1,0,0)) False >>> is_even(1) True

get_moment_indices
(moment_exponent_tuple)¶ Returns indices for a given exponent tuple:
Example
>>> get_moment_indices((2,1,0)) [0, 0, 1] >>> get_moment_indices((0,0,3)) [2, 2, 2]

get_order
(moment)¶ Computes polynomial order of given moment.
Examples
>>> x , y, z = MOMENT_SYMBOLS >>> get_order(x**2 * y + x) 3 >>> get_order(z**4 * x**2) 6 >>> get_order((2,1,0)) 3

non_aliased_moment
(moment_tuple)¶ Takes a moment exponent tuple and returns the nonaliased version of it.
For first neighborhood stencils, all moments with exponents 3, 5, 7… are equal to exponent 1, and exponents 4, 6, 8… are equal to exponent 2. This is because first neighborhood stencils only have values d ∈ {+1, 0, 1}. So for example d**5 is always the same as d**3 and d, and d**6 == d**4 == d**2
Example
>>> non_aliased_moment((5, 4, 2)) (1, 2, 2) >>> non_aliased_moment((9, 1, 2)) (1, 1, 2)

is_bulk_moment
(moment, dim)¶ The bulk moment is x**2+y**2+z**2

is_shear_moment
(moment, dim)¶ Shear moments are the quadratic polynomials except for the bulk moment. Linear combinations with lowerorder polynomials don’t harm because these correspond to conserved moments.

discrete_moment
(func, moment, stencil, shift_velocity=None)¶ Computes discrete moment of given distribution function
\[\sum_{d \in stencil} p(d) f_i\]where \(p(d)\) is the moment polynomial where \(x, y, z\) have been replaced with the components of the stencil direction, and \(f_i\) is the i’th entry in the passed function sequence
 Parameters
func – list of distribution functions for each direction
moment – can either be a exponent tuple, or a sympy polynomial expression
stencil – sequence of directions
shift_velocity – velocity vector u to compute central moments, the lattice velocity is replaced by (lattice_velocity  shift_velocity)

moment_matrix
(moments, stencil, shift_velocity=None)¶ Returns transformation matrix to moment space
each row corresponds to a moment, each column to a direction of the stencil The entry i,j is the i’th moment polynomial evaluated at direction j

set_up_shift_matrix
(moments, stencil, velocity_symbols=None)¶ Sets up a shift matrix to shift raw moments to central moment space.
 Parameters
moments () – Sequence of polynomials or sequence of exponent tuples, sorted ascendingly by moment order.
stencil () – Nested tuple of lattice velocities
velocity_symbols () – Sequence of symbols corresponding to the shift velocity

gram_schmidt
(moments, stencil, weights=None)¶ Computes orthogonal set of moments using the method by GramSchmidt
 Parameters
moments – sequence of moments, either in tuple or polynomial form
stencil – stencil as sequence of directions
weights – optional weights, that define the scalar product which is used for normalization. Scalar product \(< a,b > = \sum a_i b_i w_i\) with weights \(w_i\). Passing no weights sets all weights to 1.
 Returns
set of orthogonal moments in polynomial form

get_default_moment_set_for_stencil
(stencil)¶ Returns a sequence of moments that are commonly used to construct a LBM equilibrium for the given stencil

extract_monomials
(sequence_of_polynomials, dim=3)¶ Returns a set of exponent tuples of all monomials contained in the given set of polynomials
 Parameters
sequence_of_polynomials – sequence of polynomials in the MOMENT_SYMBOLS
dim – length of returned exponent tuples
>>> x, y, z = MOMENT_SYMBOLS >>> extract_monomials([x**2 + y**2 + y, y + y**2]) == {(0, 1, 0),(0, 2, 0),(2, 0, 0)} True >>> extract_monomials([x**2 + y**2 + y, y + y**2], dim=2) == {(0, 1), (0, 2), (2, 0)} True

monomial_to_polynomial_transformation_matrix
(monomials, polynomials)¶ Returns a transformation matrix from a monomial to a polynomial representation
 Parameters
monomials – sequence of exponent tuples
polynomials – sequence of polynomials in the MOMENT_SYMBOLS
>>> x, y, z = MOMENT_SYMBOLS >>> polys = [7 * x**2 + 3 * x + 2 * y **2, 9 * x**2  5 * x] >>> mons = list(extract_monomials(polys, dim=2)) >>> mons.sort() >>> monomial_to_polynomial_transformation_matrix(mons, polys) Matrix([ [2, 3, 7], [0, 5, 9]])

moment_equality_table
(stencil, discrete_equilibrium=None, continuous_equilibrium=None, max_order=4, truncate_order=3)¶ Creates a table showing which moments of a discrete stencil/equilibrium coincide with the corresponding continuous moments
 Parameters
stencil – list of stencil velocities
discrete_equilibrium – list of sympy expr to compute discrete equilibrium for each direction, if left to default the standard discrete Maxwellian equilibrium is used
continuous_equilibrium – continuous equilibrium, if left to default, the continuous Maxwellian is used
max_order – compare moments up to this order (number of rows in table)
truncate_order – moments are considered equal if they match up to this order
 Returns
Object to display in an Jupyter notebook

moment_equality_table_by_stencil
(name_to_stencil_dict, moments, truncate_order=3)¶ Creates a table for display in IPython notebooks that shows which moments agree between continuous and discrete equilibrium, group by stencils
 Parameters
name_to_stencil_dict – dict from stencil name to stencil
moments – sequence of moments to compare  assumes that permutations have similar properties so just one representative is shown labeled with its multiplicity
truncate_order – compare up to this order