archimedes.sym_like¶

archimedes.sym_like(x: ArrayLike, name: str, dtype: DTypeLike | None = None, kind: str = 'MX') → SymbolicArray¶

Create a symbolic array with the same shape and dtype as an existing array.

Parameters:

x (array_like) – Array to copy shape and dtype from. Can be a NumPy ndarray, SymbolicArray, or any array-like object that can be converted to an ndarray.
name (str) – Name of the symbolic variable. This name is used for display purposes and debugging, and appears in symbolic expression representations.
dtype (numpy.dtype, optional) – Data type of the array. If None (default), uses the dtype of x.
kind ({"SX", "MX"}, optional) –
Kind of symbolic variable to create. Default is “MX”.
- SX: Scalar-based symbolic type. Each element has its own symbolic representation. Generally more efficient for element-wise operations.
- MX: Matrix-based symbolic type. The entire array is represented by a single symbolic object. Supports a broader range of operations.

Returns:

Symbolic array with the given name and kind, matching the shape and (optionally) dtype of the input array x.

Return type:

SymbolicArray

Notes

This function is useful when:

Creating symbolic representations of existing numeric data
Building symbolic functions that need to match the structure of numeric inputs
Prototyping symbolic algorithms using existing arrays as templates

The function automatically converts non-array inputs to NumPy arrays before extracting their shape information.

Examples

>>> import numpy as np
>>> import archimedes as arc
>>>
>>> # Create a symbolic variable with the same shape as a numeric array
>>> data = np.array([[1.0, 2.0], [3.0, 4.0]])
>>> M_sym = arc.sym_like(data, "M")
>>> print(M_sym.shape)
(2, 2)
>>>
>>> # Use with a vector
>>> v = np.ones(5)
>>> v_sym = arc.sym_like(v, "v")
>>> print(v_sym.shape)
(5,)
>>>
>>> # Works with scalar inputs too
>>> scalar = 42.0
>>> x = arc.sym_like(scalar, "x")
>>> print(x.shape)
()
>>>
>>> # Create a symbolic matrix based on another symbolic array
>>> original_sym = arc.sym("y", shape=(3, 3))
>>> another_sym = arc.sym_like(original_sym, "z", kind="SX")
>>> print(another_sym.shape)
(3, 3)