fix: NaN -> nan

Author: paquiteau

src/fmri/operators/gradient.py

@@ -219,6 +219,8 @@ def __init__(self, linear_op, fourier_op, verbose=0, **kwargs):
         self.linear_op = linear_op
         n_channels = fourier_op.n_coils if not fourier_op.uses_sense else 1
         coef = linear_op.op(np.squeeze(np.zeros((n_channels, *fourier_op.shape))))
+        # Try the reverse:
+        adj_coeffs = linear_op.adj_op(coef)
         self.linear_op_coeffs_shape = coef.shape
         self.shape = coef.shape
         super().__init__(

src/fmri/operators/weighted.py

@@ -237,7 +237,7 @@ def wavelet_noise_estimate(wavelet_coeffs, coeffs_shape, sigma_est):
     xp = get_array_module(wavelet_coeffs)
 
     sigma_ret = xp.ones(len(coeffs_shape))
-    sigma_ret[0] = xp.NaN
+    sigma_ret[0] = xp.nan
     start = 0
     stop = 0
     if sigma_est is None:
@@ -263,7 +263,7 @@ def wavelet_noise_estimate(wavelet_coeffs, coeffs_shape, sigma_est):
             start = stop
     elif sigma_est == "global":
         sigma_ret *= _sigma_mad(wavelet_coeffs[-np.prod(coeffs_shape[-1]) :])
-    sigma_ret[0] = xp.NaN
+    sigma_ret[0] = np.nan
     return sigma_ret