def to_symbolic(self):
"""Convert to a SymPy matrix representing :math:`B(s, t)`.
.. note::
This method requires SymPy.
.. doctest:: triangle-to-symbolic
>>> nodes = np.asfortranarray([
... [0.0, 0.5, 1.0, -0.5, 0.0, -1.0],
... [0.0, 0.0, 1.0, 0.0, 0.0, 0.0],
... [0.0, 0.0, 0.0, 0.0, 0.0, 1.0],
... ])
>>> triangle = bezier.Triangle(nodes, degree=2)
>>> triangle.to_symbolic()
Matrix([
[s - t],
[ s**2],
[ t**2]])
Returns:
:class:`sympy.Matrix <sympy.matrices.dense.MutableDenseMatrix>`:
The triangle :math:`B(s, t)`.
"""
_, _, b_polynomial = _symbolic.triangle_as_polynomial(
self._nodes, self._degree)
return b_polynomial
def _call_function_under_test(nodes, degree):
from bezier import _symbolic
return _symbolic.triangle_as_polynomial(nodes, degree)