a few typos & keywords corrected

demos/wiener_filter_harmonic.py

@@ -85,9 +85,12 @@ if __name__ == "__main__":
     a_s = sigma_s ** 2. * lambda_s * total_volume
 
     # creation of spaces
-    x1 = RGSpace([npix,npix], distances=total_volume / npix,
-                 zerocenter=False)
-    k1 = RGRGTransformation.get_codomain(x1)
+    # x1 = RGSpace([npix,npix], distances=total_volume / npix,
+    #              zerocenter=False)
+    # k1 = RGRGTransformation.get_codomain(x1)
+
+    x1 = HPSpace(64)
+    k1 = HPLMTransformation.get_codomain(x1)
     p1 = PowerSpace(harmonic_domain=k1, log=False)
 
     # creating Power Operator with given spectrum
@@ -96,14 +99,15 @@ if __name__ == "__main__":
     S_op = create_power_operator(k1, spec)
 
     # creating FFT-Operator and Response-Operator with Gaussian convolution
+    # adjust dtype_target probperly
     Fft_op = FFTOperator(domain=x1, target=k1,
                         domain_dtype=np.float64,
-                        target_dtype=np.complex128)
+                        target_dtype=np.float64)
     R_op = ResponseOperator(x1, sigma=[length_convolution],
                             exposure=[exposure])
 
     # drawing a random field
-    sk = p_field.power_synthesize(real_signal=True, mean=0.)
+    sk = p_field.power_synthesize(decompose_power=True, mean=0.)
     s = Fft_op.adjoint_times(sk)
 
     signal_to_noise = 1
@@ -123,12 +127,12 @@ if __name__ == "__main__":
 
     m = Fft_op.adjoint_times(mk)
 
-    z={}
-    z["signal"] = s
-    z["reconstructed_map"] = m
-    z["data"] = d
-    z["lambda"] = R_op(s)
-
-    plot_maps(z, "Wiener_filter.html")
+    # z={}
+    # z["signal"] = s
+    # z["reconstructed_map"] = m
+    # z["data"] = d
+    # z["lambda"] = R_op(s)
+    #
+    # plot_maps(z, "Wiener_filter.html")
 
 

nifty/field.py

@@ -304,7 +304,7 @@ class Field(Loggable, Versionable, object):
         return result_obj
 
     def power_synthesize(self, spaces=None, real_power=True,
-                         real_signal=False, mean=None, std=None):
+                         decompose_power=False, mean=None, std=None):
 
         # check if the `spaces` input is valid
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
@@ -363,7 +363,7 @@ class Field(Loggable, Versionable, object):
                                             lambda x: x * local_rescaler.imag,
                                             inplace=True)
 
-        if real_signal:
+        if decompose_power:
             for power_space_index in spaces:
                 harmonic_domain = result_domain[power_space_index]
                 result_val_list = [harmonic_domain.hermitian_decomposition(

nifty/operators/response_operator/response_operator.py

@@ -58,7 +58,9 @@ class ResponseOperator(LinearOperator):
     """
 
     def __init__(self, domain,
-                 sigma=[1.], exposure=[1.]):
+                 sigma=[1.], exposure=[1.],
+                 default_spaces=None):
+        super(ResponseOperator, self).__init__(default_spaces)
 
         self._domain = self._parse_domain(domain)