tweaks

demos/paper_demos/cartesian_wiener_filter.py

@@ -101,7 +101,7 @@ if __name__ == "__main__":
 
     # Probing the variance
     class Proby(ift.DiagonalProberMixin, ift.Prober): pass
-    proby = Proby((signal_space_1, signal_space_2), probe_count=2,ncpu=2)
+    proby = Proby((signal_space_1, signal_space_2), probe_count=2,ncpu=1)
     proby(lambda z: fft(wiener_curvature.inverse_times(fft.inverse_times(z))))
 #    sm = SmoothingOperator(signal_space, sigma=0.02)
 #    variance = sm(proby.diagonal.weight(-1))

demos/paper_demos/wiener_filter.py

@@ -52,7 +52,7 @@ if __name__ == "__main__":
 
     # Probing the uncertainty |\label{code:wf_uncertainty_probing}|
     class Proby(ift.DiagonalProberMixin, ift.Prober): pass
-    proby = Proby(signal_space, probe_count=800,ncpu=1)
+    proby = Proby(signal_space, probe_count=1,ncpu=1)
     proby(lambda z: fft(wiener_curvature.inverse_times(fft.inverse_times(z))))  #|\label{code:wf_variance_fft_wrap}|
 
     sm = ift.FFTSmoothingOperator(signal_space, sigma=0.03)
@@ -62,3 +62,5 @@ if __name__ == "__main__":
     ift.plotting.plot(variance,name="uncertainty.pdf",xlabel='Pixel index', ylabel='Pixel index')
     ift.plotting.plot(mock_signal,name="mock_signal.pdf",xlabel='Pixel index', ylabel='Pixel index')
     ift.plotting.plot(ift.Field(signal_space, val=data.val),name="data.pdf",xlabel='Pixel index', ylabel='Pixel index')
+    ift.plotting.plot(m,name="map.pdf",xlabel='Pixel index', ylabel='Pixel index')
+

nifty2go/probing/prober/prober.py

@@ -107,7 +107,7 @@ class Prober(object):
         """ a random-probe generator """
         f = Field.from_random(random_type=self.random_type,
                               domain=self.domain,
-                              dtype=self.probe_dtype)
+                              dtype=self.probe_dtype.type)
         uid = self._uid_counter
         self._uid_counter += 1
         return (uid, f)