diff --git a/demos/wiener_filter_hamiltonian.py b/demos/wiener_filter_hamiltonian.py index 325402e14de3cebce37a9279fa9abc90522a8403..85c14d937ef2c3c4d5bea9249d8348e2c04c337b 100644 --- a/demos/wiener_filter_hamiltonian.py +++ b/demos/wiener_filter_hamiltonian.py @@ -27,7 +27,7 @@ class WienerFilterEnergy(Energy): @property def value(self): D_inv_x = self.D_inverse_x() - H = 0.5 * D_inv_x.vdot(self.position) - self.j.dot(self.position) + H = 0.5 * D_inv_x.vdot(self.position) - self.j.vdot(self.position) return H.real @property @@ -75,7 +75,7 @@ if __name__ == "__main__": ss = fft.inverse_times(sh) # model the measurement process - R = SmoothingOperator(s_space, sigma=0.01) + R = SmoothingOperator.make(s_space, sigma=0.01) # R = DiagonalOperator(s_space, diagonal=1.) # R._diagonal.val[200:400, 200:400] = 0 @@ -95,7 +95,7 @@ if __name__ == "__main__": def distance_measure(energy, iteration): x = energy.position - print((iteration, (x-ss).norm()/ss.norm()).real)) + print(iteration, (x-ss).norm()/ss.norm().real) # minimizer = SteepestDescent(convergence_tolerance=0, # iteration_limit=50, diff --git a/demos/wiener_filter_unit.py b/demos/wiener_filter_unit.py index 732155a5a560b4aec4a8f717a41351a2c975ebc9..1441d264603cf2593687c5ab899cbbd8536c2f64 100644 --- a/demos/wiener_filter_unit.py +++ b/demos/wiener_filter_unit.py @@ -88,7 +88,7 @@ if __name__ == "__main__": x1 = RGSpace(npix, distances=total_volume / npix, zerocenter=False) k1 = RGRGTransformation.get_codomain(x1) - p1 = PowerSpace(harmonic_domain=k1, log=False) + p1 = PowerSpace(harmonic_partner=k1, logarithmic=False) # creating Power Operator with given spectrum spec = (lambda k: a_s / (1 + (k / k_0) ** 2) ** 2) diff --git a/nifty/field.py b/nifty/field.py index ed1235d8a70a93ff96df77aeb85b5b54d82897da..c139d79afa7f3a159206a54a6573f9c1825f78cd 100644 --- a/nifty/field.py +++ b/nifty/field.py @@ -1104,7 +1104,7 @@ class Field(Loggable, Versionable, object): The Lq-norm of the field values. """ - return np.sqrt(np.abs(self.dot(x=self))) + return np.sqrt(np.abs(self.vdot(x=self))) def conjugate(self, inplace=False): """ Retruns the complex conjugate of the field.