def set_unitary(self, V):
"""Parse input and set the unitary operator attributes.
This also sets up the potential function
attributes in the process.
"""
if isinstance(V, str):
try:
if V.strip().replace(".",
"").replace("-",
"").replace("e",
"").isnumeric():
self.V_name = ""
self.V_latex = str(np.round(float(V), 2))
if float(V) == 0:
V = 1e-30
V_f = float(V) * np.ones([self.N])
self.U_t = UnitaryOperator1D(np.copy(V_f))
self.V_x = 0.0 * V_f
else:
V_f = scale(float(V) * np.ones([self.N]), 15)
self.V_x = V_f
self.U_t = UnitaryOperator1D(np.copy(V_f))
self.V_latex = "%sk" % (self.V_latex) if V_f[0] > 0\
else " %sk" % (self.V_latex)
self.V_params = {}
self.V_base = None
else:
V = V.replace("^", "**")
f = Function(V, "x")
self.V = lambda x: f(x, *f.get_tupled_default_values())
self.V_x = scale(self.V(self.x), 15)
self.V_name = str(f)
self.V_latex = "$" + f.multiply_latex_string("k") + "$"
self.U_t = UnitaryOperator1D(self.V)
self.V_base = f
self.V_params = f.get_enumerated_default_values()
except (TypeError, AttributeError, SyntaxError, ValueError,
NameError) as E:
print(E)
elif isinstance(V, np.ndarray):
self.V_params = {}
self.V_base = None
self.V = None
self.V_x = scale(V, 15)
self.V_name = "V(x)"
self.V_latex = "$V(x)$"
self.U_t = UnitaryOperator1D(V)
else:
print("Unable to parse input")
if hasattr(self, "lines"):
self.update_draw_potential()