Commit c73a3dd2 by Martin Reinecke

parent 12e3d597
Pipeline #18570 failed with stage
in 3 minutes and 55 seconds
 ... ... @@ -64,7 +64,7 @@ if __name__ == "__main__": # Choose the measurement instrument # Instrument = SmoothingOperator(s_space, sigma=0.01) Instrument = ift.DiagonalOperator(s_space, diagonal=1.) Instrument = ift.DiagonalOperator(ift.Field(s_space, 1.)) # Instrument._diagonal.val[200:400, 200:400] = 0 # Instrument._diagonal.val[64:512-64, 64:512-64] = 0 ... ... @@ -72,7 +72,7 @@ if __name__ == "__main__": R = AdjointFFTResponse(fft, Instrument) noise = 1. N = ift.DiagonalOperator(s_space, ift.Field(s_space,noise).weight(1)) N = ift.DiagonalOperator(ift.Field(s_space,noise).weight(1)) n = ift.Field.from_random(domain=s_space, random_type='normal', std=np.sqrt(noise), ... ... @@ -101,7 +101,7 @@ if __name__ == "__main__": def ps0(k): return (1./(1.+k)**2) t0 = ift.Field(p_space, val=np.log(1./(1+p_space.k)_lengths)**2)) t0 = ift.Field(p_space, val=np.log(1./(1+p_space.k_lengths)**2)) for i in range(500): S0 = ift.create_power_operator(h_space, power_spectrum=ps0) ... ...
 ... ... @@ -39,7 +39,7 @@ if __name__ == "__main__": # Setting up the noise covariance and drawing a random noise realization ndiag = ift.Field(data_domain, mock_signal.var()/signal_to_noise).weight(1) N = ift.DiagonalOperator(data_domain, ndiag) N = ift.DiagonalOperator(ndiag) noise = ift.Field.from_random(domain=data_domain, random_type='normal', std=mock_signal.std()/np.sqrt(signal_to_noise), mean=0) data = R(ift.exp(mock_signal)) + noise #|\label{code:wf_mock_data}| ... ...
 ... ... @@ -58,8 +58,7 @@ if __name__ == "__main__": diagonal = mock_power.power_synthesize_special(spaces=(0, 1))**2 diagonal = diagonal.real S = ift.DiagonalOperator(domain=(harmonic_space_1, harmonic_space_2), diagonal=diagonal) S = ift.DiagonalOperator(diagonal) np.random.seed(10) ... ... @@ -82,7 +81,7 @@ if __name__ == "__main__": # Setting up the noise covariance and drawing a random noise realization ndiag = ift.Field(data_domain, mock_signal.var()/signal_to_noise).weight(1) N = ift.DiagonalOperator(data_domain, ndiag) N = ift.DiagonalOperator(ndiag) noise = ift.Field.from_random(domain=data_domain, random_type='normal', std=mock_signal.std()/np.sqrt(signal_to_noise), mean=0) ... ...
 ... ... @@ -38,14 +38,14 @@ if __name__ == "__main__": # Setting up the noise covariance and drawing a random noise realization ndiag = ift.Field(data_domain, mock_signal.var()/signal_to_noise).weight(1) N = ift.DiagonalOperator(data_domain, ndiag) N = ift.DiagonalOperator(ndiag) noise = ift.Field.from_random(domain=data_domain, random_type='normal', std=mock_signal.std()/np.sqrt(signal_to_noise), mean=0) data = R(mock_signal) + noise #|\label{code:wf_mock_data}| # Wiener filter j = R_harmonic.adjoint_times(N.inverse_times(data)) ctrl = ift.DefaultIterationController(verbose=True,tol_abs_gradnorm=0.1,iteration_limit=10) ctrl = ift.DefaultIterationController(verbose=True,tol_abs_gradnorm=0.1) inverter = ift.ConjugateGradient(controller=ctrl) wiener_curvature = ift.library.WienerFilterCurvature(S=S, N=N, R=R_harmonic,inverter=inverter) m_k = wiener_curvature.inverse_times(j) #|\label{code:wf_wiener_filter}| ... ...
 ... ... @@ -17,7 +17,7 @@ class MultiProber(ift.DiagonalProberMixin, ift.TraceProberMixin, ift.Prober): x = ift.RGSpace((8, 8)) f = ift.Field.from_random(domain=x, random_type='normal') diagOp = ift.DiagonalOperator(domain=x, diagonal=f) diagOp = ift.DiagonalOperator(f) diagProber = DiagonalProber(domain=x) diagProber(diagOp) ... ...
 ... ... @@ -47,8 +47,7 @@ if __name__ == "__main__": data_domain = R.target[0] R_harmonic = ift.ComposedOperator([fft, R], default_spaces=[0, 0]) N = ift.DiagonalOperator(data_domain, diagonal=ift.Field(data_domain,mock_signal.var()/signal_to_noise).weight(1)) N = ift.DiagonalOperator(ift.Field(data_domain,mock_signal.var()/signal_to_noise).weight(1)) noise = ift.Field.from_random(domain=data_domain, random_type='normal', std=mock_signal.std()/np.sqrt(signal_to_noise), ... ...
 ... ... @@ -56,14 +56,14 @@ if __name__ == "__main__": # Choosing the measurement instrument # Instrument = SmoothingOperator(s_space, sigma=0.05) Instrument = ift.DiagonalOperator(s_space, diagonal=1.) Instrument = ift.DiagonalOperator(ift.Field(s_space, 1.)) # Instrument._diagonal.val[200:400, 200:400] = 0 # Adding a harmonic transformation to the instrument R = AdjointFFTResponse(fft, Instrument) signal_to_noise = 1. ndiag = ift.Field(s_space, ss.var()/signal_to_noise).weight(1) N = ift.DiagonalOperator(s_space, ndiag) N = ift.DiagonalOperator(ndiag) n = ift.Field.from_random(domain=s_space, random_type='normal', std=ss.std()/np.sqrt(signal_to_noise), ... ...
 ... ... @@ -2,7 +2,7 @@ import numpy as np from numpy import ndarray as data_object from numpy import full, empty, sqrt, ones, zeros, vdot, abs, bincount from numpy import full, empty, sqrt, ones, zeros, vdot, abs, bincount, exp, log from ..nifty_utilities import cast_iseq_to_tuple, get_slice_list from functools import reduce ... ...
 ... ... @@ -22,7 +22,7 @@ class CriticalPowerCurvature(InvertibleOperatorMixin, EndomorphicOperator): # ---Overwritten properties and methods--- def __init__(self, theta, T, inverter, preconditioner=None, **kwargs): self.theta = DiagonalOperator(theta.domain, diagonal=theta) self.theta = DiagonalOperator(theta) self.T = T if preconditioner is None: preconditioner = self.theta.inverse_times ... ...
 ... ... @@ -66,7 +66,7 @@ def create_power_operator(domain, power_spectrum, dtype=None): f = f.real f **= 2 return DiagonalOperator(domain, diagonal=Field(domain,f).weight(1)) return DiagonalOperator(Field(domain,f).weight(1)) def generate_posterior_sample(mean, covariance): ... ...
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