def test_smoothstep(self):
vals = np.linspace(5.0, 12.0, num=8)
self.assertEqual(
smoothstep(vals, edges=[0.0, 1.0]).tolist(), [1.0] * 8)
self.assertEqual(
smoothstep(vals, edges=[7.0, 11.0]).tolist(),
[0.0, 0.0, 0.0, 0.15625, 0.5, 0.84375, 1.0, 1.0])
def smoothstep(self, vals):
"""
#TODO: Missing doc
:param vals:
:return:
"""
return smoothstep(
vals, edges=[self.__dict__["lower"], self.__dict__["upper"]])
def inverse_smoothstep(self, vals):
"""Get the evaluation of the "inverse" smoothstep ratio function: f(x)=1-(3*x^2-2*x^3).
The values (i.e. "x"), are scaled between the "lower" and "upper" parameters.
:param vals: Values for which the ratio function has to be evaluated.
:return: Result of the ratio function applied to the values.
"""
return smoothstep(vals, edges=[self.__dict__["lower"], self.__dict__["upper"]], inverse=True)
def inverse_smoothstep(self, vals):
return smoothstep(
vals,
edges=[self.__dict__['lower'], self.__dict__['upper']],
inverse=True)
def smoothstep(self, vals):
return smoothstep(
vals, edges=[self.__dict__['lower'], self.__dict__['upper']])
def smoothstep(self, vals):
return smoothstep(vals, edges=[self.__dict__["lower"], self.__dict__["upper"]])
def test_smoothstep(self):
vals = np.linspace(5.0, 12.0, num=8)
self.assertEqual(smoothstep(vals, edges=[0.0, 1.0]).tolist(), [1.0]*8)
self.assertEqual(smoothstep(vals, edges=[7.0, 11.0]).tolist(),
[0.0, 0.0, 0.0, 0.15625, 0.5, 0.84375, 1.0, 1.0])
def inverse_smoothstep(self, vals):
return smoothstep(vals, edges=[self.__dict__['lower'], self.__dict__['upper']], inverse=True)
def smoothstep(self, vals):
return smoothstep(vals, edges=[self.__dict__['lower'], self.__dict__['upper']])
