cutcutcodec.core.compilation.sympy_to_torch.printer_atom.c_pow¶

cutcutcodec.core.compilation.sympy_to_torch.printer_atom.c_pow(out: Symbol, indexing: defaultdict[Symbol, str], c_type: str, base: Atom, exp: Atom) → tuple[set[str], set[Symbol], list[str]][source]¶

C ** operation.

Examples¶

>>> from collections import defaultdict
>>> from sympy.abc import x, y, z
>>> import numpy as np
>>> from cutcutcodec.core.compilation.sympy_to_torch.lambdify import _lambdify_c
>>> from cutcutcodec.core.compilation.sympy_to_torch.printer import _print_atomic, _printer
>>>
>>> _print_atomic(x**y, z, defaultdict(lambda: ""), "float")
(set(), set(), ['z = powf(x, y);'])
>>> _print_atomic(1/x, z, defaultdict(lambda: ""), "float")
(set(), set(), ['z = 1.0f / x;'])
>>> _print_atomic(x**2, y, defaultdict(lambda: ""), "float")
(set(), set(), ['y = x * x;'])
>>> _print_atomic(x**.5, y, defaultdict(lambda: ""), "float")
(set(), set(), ['y = sqrtf(x);'])
>>> _print_atomic(x**(1/3), y, defaultdict(lambda: ""), "float")
(set(), set(), ['y = cbrtf(x);'])
>>> _print_atomic(x**(-7/2), y, defaultdict(lambda: ""), "double")
(set(), {_buf}, ['y = x * x;', '_buf = x * y;', 'y *= y;', 'y *= _buf;', 'y = 1.0 / sqrt(y);'])
>>>
>>> func = _lambdify_c(_printer([(x, x**y)], {}, {x, y}))
>>> func(
...     np.array([2.0   , np.nan, 0.0, 0.0,  0.0, -0.0,    2.0,     2.0]),
...     np.array([np.nan,    2.0, 0.0, 1.0, -1.0, -1.0, np.inf, -np.inf])
... )
array([ nan,  nan,   1.,   0.,  inf, -inf,  inf,   0.])
>>> func(np.array([1+1j]), np.array([1+1j]))
array([0.27395725+0.58370076j])
>>> func = _lambdify_c(_printer([(x, x**2)], {}, {x}))
>>> func(np.array([np.nan, -np.inf, -2.0, -1.0, 1.0, 2.0, np.inf]))
array([nan, inf,  4.,  1.,  1.,  4., inf])
>>> func = _lambdify_c(_printer([(x, 1/x)], {}, {x}))
>>> func(np.array([np.nan, -np.inf, -2.0, -1.0, -0.0, 0.0, 1.0, 2.0, np.inf]))
array([ nan, -0. , -0.5, -1. , -inf,  inf,  1. ,  0.5,  0. ])
>>> func = _lambdify_c(_printer([(x, x**.5)], {}, {x}))
>>> func(np.array([np.nan, -np.inf, -1.0, 0.0, 1.0, 4.0, np.inf]))
array([nan, nan, nan,  0.,  1.,  2., inf])
>>> func = _lambdify_c(_printer([(x, x**(1/3))], {}, {x}))
>>> func(np.array([np.nan, -np.inf, -8.0, -1.0, 0.0, 1.0, 8.0, np.inf]))
array([ nan, -inf,  -2.,  -1.,   0.,   1.,   2.,  inf])
>>> func = _lambdify_c(_printer([(x, x**(-7/2))], {}, {x}))
>>> func(np.array([0.820335356007638]))
array([2.])
>>>