expression_v1¶

Expression parser version 1 and namespace.

The syntax of an expression is as follows:

Integers or decimal numbers are denoted in the usual way. Examples: 1, 1.2, .2. A number may not start with a zero, except when followed by a dot: 0.1 is valid, but 01 is not.
Variables are denoted with a string of alphanumeric characters. The first character may not be a numeral. Unlike Python variables, underscores are not allowed, as they have a special meaning. If the variable is an array with one or more axes, all those axes should be labeled with a latin character, the index, and appended to the variable with an underscore. For example an array a with two axes can be denoted with a_ij. Optionally, a single numeral may be used to select an item at the concerning axis. Example: in a_i0 the first axis of a is labeled i and the first element of the second axis is selected. If the same index occurs twice, the trace is taken along the concerning axes. Example: the trace of the first and third axes of b is denoted by b_iji. It is invalid to specify an index more than twice. The following names cannot be used as variables: n, δ, $. The variable named x, or the value of argument default_geometry_name, has a special meaning, detailed below.
A term, the product of two or more arrays or scalars, is denoted by space-separated variables, constants or compound expressions. Example: a b c denotes the product of the scalars a, b and c. A term may start with a number, but a number is not allowed in other parts of the term. Example: 2 a denotes two times a; 2 2 a and 2 a 2` are invalid. When two arrays in a term have the same index, this index is summed. Example: a_i b_i denotes the inner product of a and b and A_ij b_j` a matrix vector product. It is not allowed to use an index more than twice in a term.
The operator / denotes a fraction. Example: in a b / c d a b is the numerator and c d the denominator. Both the numerator and the denominator may start with a number. Example: 2 a / 3 b. The denominator must be a scalar. Example: 2 / a_i b_i is valid, but 2 a_i / b_i is not.

Warning

This syntax is different from the Python syntax. In Python a*b / c*d is mathematically equivalent to a*b*d/c.
The operators + and - denote add and subtract. Both operators should be surrounded by whitespace, e.g. a + b. Both operands should have the same shape. Example: a_ij + b_i c_j is a valid, provided that the lengths of the axes with the same indices match, but a_ij + b_i is invalid. At the beginning of an expression or a compound - may be used to negate the following term. Example: in -a b + c the term a b is negated before adding c. It is not allowed to negate other terms: a + -b is invalid, so is a -b.
An expression surrounded by parentheses is a compound expression and can be used as single entity in a term. Example: (a_i + b_i) c_i denotes the inner product of a_i + b_i with c_i.
Exponentiation is denoted by a ^, where the left and right operands should be a number, variable or compound expression and the right operand should be a scalar. Example: a^2 denotes the square of a, a^-2 denotes a to the power -2 and a^(1 / 2) the square root of a.
An argument is denoted by a name — following the same rules as a variable name — prefixed with a question mark. An argument is a scalar or array with a yet unknown value. Example: basis_i ?coeffs_i denotes the inner product of a basis with unknown coefficient vector ?coeffs. If possible the shape of the argument is deduced from the expression. In the previous example the shape of ?coeffs is equal to the shape of basis. If the shape cannot be deduced from the expression the shape should be defined manually (see parse()). Arguments and variables live in separate namespaces: ?x and x are different entities.
An argument may be substituted by appending without whitespace (arg = value) to a variable of compound expression, where arg is an argument and value the substitution. The substitution applies to the variable of compound expression only. The value may be an expression. Example: 2 ?x(x = 3 + y) is equivalent to 2 (3 + y) and 2 ?x(x=y) + 3 is equivalent to 2 (y) + 3. It is possible to apply multiple substitutions. Example: (?x + ?y)(x = 1, y = )2 is equivalent to 1 + 2.
The gradient of a variable to the default geometry — the default geometry is variable x unless overriden by the argument default_geometry_name — is denoted by an underscore, a comma and an index. If the variable is an array with more than one axis, the underscore is omitted. Example: a_,i denotes the gradient of the scalar a to the geometry and b_i,j the gradient of vector b. The gradient of a compound expression is denoted by an underscore, a comma and an index. Example: (a_i + b_j)_,k denotes the gradient of a_i + b_j. The usual summation rules apply and it is allowed to use a numeral as index. The surface gradient is denoted with a semicolon instead of a comma, but follows the same rules as the gradient otherwise. Example: a_i;j is the sufrace gradient of a_i to the geometry.
The normal of the default geometry is denoted by n_i, where the index i may be replaced with an index of choice.
A dirac is denoted by δ or $ and takes two indices. The shape of the dirac is deduced from the expression. Example: let A be a square matrix with three rows and columns, then δ_ij in (A_ij - λ δ_ij) x_j has three rows and columns as well.
An expression surrounded by square brackets or curly braces denotes the jump or mean, respectively, of the enclosed expression. Example: [ a_i ] denotes the jump of a_i and { a_i + b_i } denotes the mean of a_i + b_i.
A function call is denoted by a name — following the same rules as for a variable name — optionally followed by _ and indices, optionally followed by : and indices, directly followed by the left parenthesis (, without a space. The arguments to the function are separated by a comma and at least one space. The function is applied pointwise to the arguments and summation convection is applied to the result. Example: assume mul(...) returns the product of its arguments, then mul(x_i, y_j) is equivalent to x_i y_j and mul(x_i, y_i) to x_i y_i. Functions and variables share a namespace: defining a variable with the same name as a function renders the function inaccessible. Functions of the form f_i(...) and f_ij(...) etc. generate one and two axes, respectively. Functions of the form f:i(...) and f:ij(...) etc. consume the axes labelled i and i and j respectively. If all axes are consumed, it is allowed to omit the axes: sum(u) is equivalent to sum:i(u_i).
A stack of two or more arrays along an axis is denoted by a < followed by comma and space separated arrays followed by > and an index. All arguments must have the same shape and must not have an axis labelled with the stack axis. Example: <1, 2>_i creates an array with components 1 and 2.

nutils.expression_v1.parse(expression, variables, indices, arg_shapes={}, default_geometry_name='x', fixed_lengths=None, fallback_length=None, functions=None)¶

Parse expression and return AST.

This function parses a tensor expression according to the syntax described in module nutils.expression_v1 and returns an Abstract Syntax Tree (AST).

Parameters:

expression (str) – The expression to parse. See expression_v1 for the expression syntax.
variables (dict of str and nutils.function.Array pairs) – A dict of variable names and array pairs. All variables used in the expression should exist in variables.
indices (str) – The indices used for aligning the resulting array. For example, let expression be 'a_ij'. If indices is 'ij', then the returned array is simply variables['a'], but if indices is 'ji' the transpose of variables['a'] is returned. All indices of the expression should be listed precisely once.
arg_shapes (dict of str and tuple or ints pairs) – A dict of argument names and shapes. If expression contains an argument not present in arg_shapes the shape will be decuded from the expression and added to a copy of arg_shapes.
default_geometry_name (str) – The name of the default geometry variable. When computing a gradient or the normal, e.g. 'f_,i' or 'n_i', this variable is used as the geometry, unless the geometry is explicitly mentioned in the expression. Default: 'x'.
fixed_lengths (dict of str and int pairs, optional) – A dict of indices and lengths. All axes in the expression marked with an index of fixed length are asserted to have the fixed length.
fallback_length (int, optional) – The fallback length of an axis if the length cannot be determined from the expression.

Returns:

ast (tuple) – The parsed expression as an abstract syntax tree (AST). The AST is a tuple of an opcode and arguments. The special opcode None indicates that the single argument is used verbatim. All other opcodes have AST as arguments. The following opcodes exist:

(None, const)
('group', group)
('arg', name, *shape)
('substitute', array, arg, value)
('call', func, arg)
('eye', length)
('normal', geom)
('getitem', array, dim, index)
('trace', array, n1, n2)
('sum', array, axis)
('concatenate', *args)
('grad', array, geom)
('surfgrad', array, geom)
('derivative', func, target)
('append_axis', array, length)
('transpose', array, trans)
('jump', array)
('mean', array)
('neg', array)
('add', left, right)
('sub', left, right)
('mul', left, right)
('truediv', left, right)
('pow', left, right)

arg_shapes (dict of str and tuple of ints pairs) – A copy of arg_shapes updated with shapes of arguments present in this expression.

class nutils.expression_v1.Namespace(*, default_geometry_name='x', fallback_length=None, functions=None, **kwargs)¶

Bases: object

Namespace for Array objects supporting assignments with tensor expressions.

The Namespace object is used to store Array objects.

>>> from nutils import expression_v1, function
>>> ns = expression_v1.Namespace()
>>> ns.A = function.zeros([3, 3])
>>> ns.x = function.zeros([3])
>>> ns.c = 2

In addition to the assignment of Array objects, it is also possible to specify an array using a tensor expression string — see nutils.expression_v1 for the syntax. All attributes defined in this namespace are available as variables in the expression. If the array defined by the expression has one or more dimensions the indices of the axes should be appended to the attribute name. Examples:

>>> ns.cAx_i = 'c A_ij x_j'
>>> ns.xAx = 'x_i A_ij x_j'

It is also possible to simply evaluate an expression without storing its value in the namespace by passing the expression to the method eval_ suffixed with appropriate indices:

>>> ns.eval_('2 c')
Array<>
>>> ns.eval_i('c A_ij x_j')
Array<3>
>>> ns.eval_ij('A_ij + A_ji')
Array<3,3>

For zero and one dimensional expressions the following shorthand can be used:

>>> '2 c' @ ns
Array<>
>>> 'A_ij x_j' @ ns
Array<3>

Sometimes the dimension of an expression cannot be determined, e.g. when evaluating the identity array:

>>> ns.eval_ij('δ_ij')
Traceback (most recent call last):
...
nutils.expression_v1.ExpressionSyntaxError: Length of axis cannot be determined from the expression.
δ_ij
  ^

There are two ways to inform the namespace of the correct lengths. The first is to assign fixed lengths to certain indices via keyword argument length_<indices>:

>>> ns_fixed = expression_v1.Namespace(length_ij=2)
>>> ns_fixed.eval_ij('δ_ij')
Array<2,2>

Note that evaluating an expression with an incompatible length raises an exception:

>>> import numpy
>>> ns = expression_v1.Namespace(length_i=2)
>>> ns.a = numpy.array([1,2,3])
>>> 'a_i' @ ns
Traceback (most recent call last):
...
nutils.expression_v1.ExpressionSyntaxError: Length of index i is fixed at 2 but the expression has length 3.
a_i
  ^

The second is to define a fallback length via the fallback_length argument:

>>> ns_fallback = expression_v1.Namespace(fallback_length=2)
>>> ns_fallback.eval_ij('δ_ij')
Array<2,2>

When evaluating an expression through this namespace the following functions are available: opposite, sin, cos, tan, sinh, cosh, tanh, arcsin, arccos, arctan2, arctanh, exp, abs, ln, log, log2, log10, sqrt and sign.

Additional pointwise functions can be passed to argument functions. All functions should take Array objects as arguments and must return an Array with as shape the sum of all shapes of the arguments.

>>> def sqr(a):
...   return a**2
>>> def mul(a, b):
...   return a[(...,)+(None,)*b.ndim] * b[(None,)*a.ndim]
>>> ns_funcs = expression_v1.Namespace(functions=dict(sqr=sqr, mul=mul))
>>> ns_funcs.a = numpy.array([1,2,3])
>>> ns_funcs.b = numpy.array([4,5])
>>> 'sqr(a_i)' @ ns_funcs # same as 'a_i^2'
Array<3>
>>> ns_funcs.eval_ij('mul(a_i, b_j)') # same as 'a_i b_j'
Array<3,2>
>>> 'mul(a_i, a_i)' @ ns_funcs # same as 'a_i a_i'
Array<>

Parameters:

default_geometry_name (str) – The name of the default geometry. This argument is passed to nutils.expression_v1.parse(). Default: 'x'.
fallback_length (int, optional) – The fallback length of an axis if the length cannot be determined from the expression.
length_<indices> (int) – The fixed length of <indices>. All axes in the expression marked with one of the <indices> are asserted to have the specified length.
functions (dict, optional) – Pointwise functions that should be available in the namespace, supplementing the default functions listed above. All functions should return arrays with as shape the sum of all shapes of the arguments.

arg_shapes¶

A readonly map of argument names and shapes.

Type:: dict

default_geometry_name¶

The name of the default geometry. See argument with the same name.

Type:: str

__getstate__(self)¶: Pickle instructions

__setstate__(self, d)¶: Unpickle instructions

property default_geometry: str¶

The default geometry, shorthand for getattr(ns, ns.default_geometry_name).

Type:: nutils.function.Array

__call__(*args, **subs)¶

Return a copy with arguments replaced by subs.

Return a copy of this namespace with Argument objects replaced according to subs.

Parameters:: **subs (dict of str and nutils.function.Array objects) – Replacements of the Argument objects, identified by their names.
Returns:: ns – The copy of this namespace with replaced Argument objects.
Return type:: Namespace

copy_(self, *, default_geometry_name=None)¶: Return a copy of this namespace.

__getattr__(self, name)¶: Get attribute name.

__setattr__(self, name, value)¶: Set attribute name to value.

__delattr__(self, name)¶: Delete attribute name.

__rmatmul__(expr: str) → Array¶
__rmatmul__(expr: Union[Tuple[str, ...], List[str]]) → Tuple[Array, ...]: Evaluate zero or one dimensional expr or a list of expressions.