nifty5 -> nifty7 (4/n)

1_wiener_filter.py

+# This program is free software: you can redistribute it and/or modify
+# it under the terms of the GNU General Public License as published by
+# the Free Software Foundation, either version 3 of the License, or
+# (at your option) any later version.
+#
+# This program is distributed in the hope that it will be useful,
+# but WITHOUT ANY WARRANTY; without even the implied warranty of
+# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+# GNU General Public License for more details.
+#
+# You should have received a copy of the GNU General Public License
+# along with this program.  If not, see <http://www.gnu.org/licenses/>.
+#
+# Copyright(C) 2013-2021 Max-Planck-Society
+#
+# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
+
 import numpy as np
 
 import nifty7 as ift

1_wiener_filter_solution.py

@@ -32,7 +32,7 @@ data_space = R.target
 data = ift.makeField(data_space, data)
 
 ground_truth = ift.makeField(position_space, ground_truth)
-plot_WF('data', ground_truth, data)
+plot_WF('1_data', ground_truth, data)
 
 N = ift.ScalingOperator(data_space, 0.1)
 
@@ -45,12 +45,12 @@ S = HT @ S_h @ HT.adjoint
 D_inv = S.inverse + R.adjoint @ N.inverse @ R
 j = (R.adjoint @ N.inverse)(data)
 
-IC = ift.GradientNormController(iteration_limit=1, tol_abs_gradnorm=1e-7)
+IC = ift.GradientNormController(iteration_limit=100, tol_abs_gradnorm=1e-7)
 D = ift.InversionEnabler(D_inv.inverse, IC, approximation=S)
 
 m = D(j)
 
-plot_WF('result', ground_truth, data, m)
+plot_WF('1_result', ground_truth, data, m)
 
 N = ift.SamplingDtypeSetter(N, np.float64)
 S_h = ift.SamplingDtypeSetter(S_h, np.float64)
@@ -59,4 +59,4 @@ Dinv = ift.WienerFilterCurvature(R, N, S, IC, IC)
 N_samples = 10
 samples = [Dinv.draw_sample(from_inverse=True) + m for i in range(N_samples)]
 
-plot_WF('result', ground_truth, data, m=m, samples=samples)
+plot_WF('1_result_with_uncertainty', ground_truth, data, m=m, samples=samples)

2_critical_filter.py

@@ -15,25 +15,27 @@
 #
 # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
 
-import numpy as np
-
 import nifty7 as ift
+from helpers import (checkerboard_response, generate_gaussian_data,
+                     plot_prior_samples_2d, plot_reconstruction_2d)
 
 position_space = ift.RGSpace(2*(256,))
-harmonic_space = position_space.get_default_codomain()
-HT = ift.HarmonicTransformOperator(harmonic_space, target=position_space)
-power_space = ift.PowerSpace(harmonic_space)
-
-A = ift.SLAmplitude(
-    **{
-        'target': power_space,
-        'n_pix': 64,  # 64 spectral bins
-        # Smoothness of spectrum
-        'a': 10,  # relatively high variance of spectral curvature
-        'k0': .2,  # quefrency mode below which cepstrum flattens
-        # Power-law part of spectrum
-        'sm': -4,  # preferred power-law slope
-        'sv': .6,  # low variance of power-law slope
-        'im': -2,  # y-intercept mean, in-/decrease for more/less contrast
-        'iv': 2.  # y-intercept variance
-    })
+
+args = {
+    'offset_mean': 0,
+    'offset_std': (1e-3, 1e-6),
+
+    # Amplitude of field fluctuations
+    'fluctuations': (1., 0.8),  # 1.0, 1e-2
+
+    # Exponent of power law power spectrum component
+    'loglogavgslope': (-3., 1),  # -6.0, 1
+
+    # Amplitude of integrated Wiener process power spectrum component
+    'flexibility': (2, 1.),  # 1.0, 0.5
+
+    # How ragged the integrated Wiener process component is
+    'asperity': (0.5, 0.4)  # 0.1, 0.5
+}
+
+signal = ift.SimpleCorrelatedField(position_space, **args)