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])