def test_smootherstep(self):
vals = np.linspace(5.0, 12.0, num=8)
self.assertEqual(
smootherstep(vals, edges=[0.0, 1.0]).tolist(), [1.0] * 8)
self.assertEqual(
smootherstep(vals, edges=[7.0, 11.0]).tolist(),
[0.0, 0.0, 0.0, 0.103515625, 0.5, 0.896484375, 1.0, 1.0])
def smootherstep(self, vals):
"""
#TODO: Missing doc
:param vals:
:return:
"""
return smootherstep(
vals, edges=[self.__dict__["lower"], self.__dict__["upper"]])
def smootherstep(self, vals):
"""Get the evaluation of the smootherstep ratio function: f(x)=6*x^5-15*x^4+10*x^3.
The DeltaCSM values (i.e. "x"), are scaled between the "delta_csm_min" and "delta_csm_max" parameters.
:param vals: DeltaCSM values for which the ratio function has to be evaluated.
:return: Result of the ratio function applied to the DeltaCSM values.
"""
return smootherstep(vals, edges=[self.__dict__["delta_csm_min"], self.__dict__["delta_csm_max"]])
def inverse_smootherstep(self, vals):
"""Get the evaluation of the "inverse" smootherstep ratio function: f(x)=1-(6*x^5-15*x^4+10*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 smootherstep(vals, edges=[self.__dict__["lower"], self.__dict__["upper"]], inverse=True)
def smootherstep(self, vals):
"""
#TODO: Missing doc
:param vals:
:return:
"""
return smootherstep(vals,
edges=[
self.__dict__["delta_csm_min"],
self.__dict__["delta_csm_max"]
])
def smoothstep(self, vals):
"""Get the evaluation of the smoothstep ratio function: f(x)=3*x^2-2*x^3.
The CSM values (i.e. "x"), are scaled between the "lower_csm" and "upper_csm" parameters.
:param vals: CSM values for which the ratio function has to be evaluated.
:return: Result of the ratio function applied to the CSM values.
"""
return smootherstep(
vals,
edges=[self.__dict__["lower_csm"], self.__dict__["upper_csm"]],
inverse=True,
)
def smootherstep(self, vals):
return smootherstep(vals, edges=[self.__dict__['lower'], self.__dict__['upper']])
def smootherstep(self, vals):
return smootherstep(vals, edges=[self.__dict__['delta_csm_min'], self.__dict__['delta_csm_max']])
def smoothstep(self, vals):
return smootherstep(vals, edges=[self.__dict__['lower_csm'], self.__dict__['upper_csm']], inverse=True)
def smootherstep(self, vals):
return smootherstep(
vals,
edges=[self.__dict__['lower_csm'], self.__dict__['upper_csm']],
inverse=True)
def smootherstep(self, vals):
return smootherstep(vals,
edges=[
self.__dict__['delta_csm_min'],
self.__dict__['delta_csm_max']
])
def smootherstep(self, vals):
return smootherstep(
vals, edges=[self.__dict__['lower'], self.__dict__['upper']])
def smootherstep(self, vals):
return smootherstep(
vals, edges=[self.__dict__["delta_csm_min"], self.__dict__["delta_csm_max"]]
)
def smoothstep(self, vals):
return smootherstep(
vals,
edges=[self.__dict__["lower_csm"], self.__dict__["upper_csm"]],
inverse=True,
)
def smootherstep(self, vals):
return smootherstep(
vals, edges=[self.__dict__["lower"], self.__dict__["upper"]]
)
def test_smootherstep(self):
vals = np.linspace(5.0, 12.0, num=8)
self.assertEqual(smootherstep(vals, edges=[0.0, 1.0]).tolist(), [1.0]*8)
self.assertEqual(smootherstep(vals, edges=[7.0, 11.0]).tolist(),
[0.0, 0.0, 0.0, 0.103515625, 0.5, 0.896484375, 1.0, 1.0])