diff --git a/demos/log_normal_wiener_filter.py b/demos/log_normal_wiener_filter.py
index f5bcccf64e4bd7b2c8c00f493d4c7452b58398b0..d69150c7f6cb2d488a9da4a1569e9e4899cb29d3 100644
--- a/demos/log_normal_wiener_filter.py
+++ b/demos/log_normal_wiener_filter.py
@@ -41,7 +41,7 @@ if __name__ == "__main__":
 
     # Setting up the noise covariance and drawing a random noise realization
     noiseless_data = R(mock_signal)
-    noise_amplitude = noiseless_data.std()/signal_to_noise
+    noise_amplitude = noiseless_data.val.std()/signal_to_noise
     N = ift.DiagonalOperator(
         ift.Field.full(data_domain, noise_amplitude**2))
     noise = ift.Field.from_random(
@@ -56,9 +56,9 @@ if __name__ == "__main__":
     inverter = ift.ConjugateGradient(controller=ctrl)
     energy = ift.library.LogNormalWienerFilterEnergy(m0, data, R,
                                                      N, S, inverter=inverter)
-    # minimizer = ift.VL_BFGS(controller=ctrl2, max_history_length=20)
+    #minimizer = ift.VL_BFGS(controller=ctrl2, max_history_length=20)
     minimizer = ift.RelaxedNewton(controller=ctrl2)
-    # minimizer = ift.SteepestDescent(controller=ctrl2)
+    #minimizer = ift.SteepestDescent(controller=ctrl2)
 
     me = minimizer(energy)
     m = ht(me[0].position)
diff --git a/demos/paper_demos/cartesian_wiener_filter.py b/demos/paper_demos/cartesian_wiener_filter.py
index 849d793aa89e93a77bf0f625445ccb2fc9bf760b..d4a2159b857a604af39d782b834b6fef40bbad6c 100644
--- a/demos/paper_demos/cartesian_wiener_filter.py
+++ b/demos/paper_demos/cartesian_wiener_filter.py
@@ -81,7 +81,7 @@ if __name__ == "__main__":
     data_domain = R.target
 
     noiseless_data = R(mock_signal)
-    noise_amplitude = noiseless_data.std()/signal_to_noise
+    noise_amplitude = noiseless_data.val.std()/signal_to_noise
     # Setting up the noise covariance and drawing a random noise realization
     ndiag = ift.Field.full(data_domain, noise_amplitude**2)
     N = ift.DiagonalOperator(ndiag)
diff --git a/demos/paper_demos/wiener_filter.py b/demos/paper_demos/wiener_filter.py
index 78cffc3fb7cd0ffbcaa8b98b1104b14c58c3b577..aa873d35a4fe8e311910aa002caf2e51c128af74 100644
--- a/demos/paper_demos/wiener_filter.py
+++ b/demos/paper_demos/wiener_filter.py
@@ -42,7 +42,7 @@ if __name__ == "__main__":
     data_domain = R.target[0]
 
     noiseless_data = R(mock_signal)
-    noise_amplitude = noiseless_data.std()/signal_to_noise
+    noise_amplitude = noiseless_data.val.std()/signal_to_noise
     # Setting up the noise covariance and drawing a random noise realization
     ndiag = ift.Field.full(data_domain, noise_amplitude**2)
     N = ift.DiagonalOperator(ndiag)
diff --git a/demos/wiener_filter_easy.py b/demos/wiener_filter_easy.py
index 2867161e24a63e0bfe5d11581963d4ef86d01b43..4de310c8da651fbdc3664a75821eb9fdd65ccc39 100644
--- a/demos/wiener_filter_easy.py
+++ b/demos/wiener_filter_easy.py
@@ -42,7 +42,7 @@ if __name__ == "__main__":
 
     noiseless_data = R(sh)
     signal_to_noise = 1.
-    noise_amplitude = noiseless_data.std()/signal_to_noise
+    noise_amplitude = noiseless_data.val.std()/signal_to_noise
     N = ift.DiagonalOperator(ift.Field.full(s_space, noise_amplitude**2))
     n = ift.Field.from_random(domain=s_space,
                               random_type='normal',
diff --git a/demos/wiener_filter_via_hamiltonian.py b/demos/wiener_filter_via_hamiltonian.py
index e3a22db3afbbffeeb51e211093fb61cfa10effd6..0e73cafbebe6fec9b4a316170aa09e2863de7502 100644
--- a/demos/wiener_filter_via_hamiltonian.py
+++ b/demos/wiener_filter_via_hamiltonian.py
@@ -36,7 +36,7 @@ if __name__ == "__main__":
     R = Instrument*ht
     noiseless_data = R(sh)
     signal_to_noise = 1.
-    noise_amplitude = noiseless_data.std()/signal_to_noise
+    noise_amplitude = noiseless_data.val.std()/signal_to_noise
     N = ift.DiagonalOperator(ift.Field.full(s_space, noise_amplitude**2))
     n = ift.Field.from_random(domain=s_space,
                               random_type='normal',