small efficiency tweaks

README.md

@@ -90,7 +90,7 @@ The current version of Nifty3 can be obtained by cloning the repository:
 
 It is possible to simply install NIFTy with all its dependencies via the command
 
-pip install --user --process-dependency-links git+https://gitlab.mpcdf.mpg.de/ift/NIFTy.git@nifty2go
+pip install --user --process-dependency-links --egg git+https://gitlab.mpcdf.mpg.de/ift/NIFTy.git@nifty2go
 
 ### Running the tests
 

demos/paper_demos/wiener_filter.py

@@ -57,7 +57,7 @@ if __name__ == "__main__":
 
     sm = ift.FFTSmoothingOperator(signal_space, sigma=0.03)
     variance = ift.sqrt(sm(proby.diagonal.weight(-1)))  #|\label{code:wf_variance_weighting}|
-
+    exit()
     # Plotting #|\label{code:wf_plotting}|
     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')

nifty2go/field.py

@@ -226,7 +226,7 @@ class Field(object):
         # check if the `spaces` input is valid
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
         if spaces is None:
-            spaces = list(range(len(self.domain)))
+            spaces = range(len(self.domain))
 
         if len(spaces) == 0:
             raise ValueError("No space for analysis specified.")
@@ -297,8 +297,8 @@ class Field(object):
     @staticmethod
     def _shape_up_pindex(pindex, target_shape, axes):
         semiscaled_local_shape = [1] * len(target_shape)
-        for i in range(len(axes)):
-            semiscaled_local_shape[axes[i]] = pindex.shape[i]
+        for i, ax in enumerate(axes):
+            semiscaled_local_shape[ax] = pindex.shape[i]
         result_obj = np.empty(target_shape, dtype=pindex.dtype)
         result_obj[()] = pindex.reshape(semiscaled_local_shape)
         return result_obj
@@ -356,7 +356,7 @@ class Field(object):
         # check if the `spaces` input is valid
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
         if spaces is None:
-            spaces = list(range(len(self.domain)))
+            spaces = range(len(self.domain))
 
         for i in spaces:
             if not isinstance(self.domain[i], PowerSpace):
@@ -536,7 +536,7 @@ class Field(object):
 
         spaces = utilities.cast_axis_to_tuple(spaces, len(self.domain))
         if spaces is None:
-            spaces = list(range(len(self.domain)))
+            spaces = range(len(self.domain))
 
         fct = 1.
         for ind in spaces:

nifty2go/operators/composed_operator/composed_operator.py

@@ -131,7 +131,7 @@ class ComposedOperator(LinearOperator):
     def _times_helper(self, x, spaces, func):
         space_index = 0
         if spaces is None:
-            spaces = list(range(len(self.domain)))
+            spaces = range(len(self.domain))
         for op in self._operator_store:
             active_spaces = spaces[space_index:space_index+len(op.domain)]
             space_index += len(op.domain)
@@ -142,7 +142,7 @@ class ComposedOperator(LinearOperator):
     def _inverse_times_helper(self, x, spaces, func):
         space_index = 0
         if spaces is None:
-            spaces = list(range(len(self.target)))
+            spaces = range(len(self.target))
         rev_spaces = spaces[::-1]
         for op in reversed(self._operator_store):
             active_spaces = rev_spaces[space_index:space_index+len(op.target)]

nifty2go/operators/diagonal_operator/diagonal_operator.py

@@ -208,7 +208,7 @@ class DiagonalOperator(EndomorphicOperator):
             return operation(self._diagonal)(x)
 
         if spaces is None:
-            active_axes = list(range(len(x.shape)))
+            active_axes = range(len(x.shape))
         else:
             active_axes = []
             for space_index in spaces:

nifty2go/operators/fft_operator/fft_operator_support.py

@@ -49,18 +49,14 @@ class RGRGTransformation(Transformation):
         nlast = res.shape[lastaxis]
         ntmplast = tmp.shape[lastaxis]
         nrem = nlast - ntmplast
-        slice1 = [slice(None)]*res.ndim
-        slice2 = list(slice1)
-        for i in axes:
+        slice1 = [slice(None)]*lastaxis + [slice(ntmplast, None)]
+        slice2 = [slice(None)]*lastaxis + [slice(nrem, 0, -1)]
+        for i in axes[:-1]:
             slice1[i] = slice(1, None)
             slice2[i] = slice(None, 0, -1)
-        slice1[lastaxis] = slice(ntmplast, None)
-        slice2[lastaxis] = slice(nrem, 0, -1)
         res[slice1] = tmp[slice2].real-tmp[slice2].imag
-        for i in range(len(axes)-1):
-            ax = axes[i]
-            dim1 = [slice(None)]*res.ndim
-            dim1[ax]=slice(0,1)
+        for i, ax in enumerate(axes[:-1]):
+            dim1 = [slice(None)]*ax + [slice(0,1)]
             axes2 = axes[:i] + axes[i+1:]
             RGRGTransformation._fill_upper_half(tmp[dim1], res[dim1], axes2)
 
@@ -68,7 +64,7 @@ class RGRGTransformation(Transformation):
     def _hartley(a, axes=None):
         # Check if the axes provided are valid given the shape
         if axes is not None and \
-                not all(axis in range(len(a.shape)) for axis in axes):
+                not all(axis<len(a.shape) for axis in axes):
             raise ValueError("Provided axes does not match array shape")
 
         from pyfftw.interfaces.numpy_fft import rfftn
@@ -77,15 +73,14 @@ class RGRGTransformation(Transformation):
         tmp = rfftn(a, axes=axes)
         res = np.empty_like(a)
         if axes is None:
-            axes = list(range(a.ndim))
+            axes = range(a.ndim)
         lastaxis = axes[-1]
         nlast = a.shape[lastaxis]
         ntmplast = tmp.shape[lastaxis]
         nrem = nlast - ntmplast
-        slice1 = [slice(None)]*a.ndim
-        slice1[lastaxis] = slice(0, ntmplast)
+        slice1 = [slice(None)]*lastaxis + [slice(0, ntmplast)]
         res[slice1] = tmp.real+tmp.imag
-        RGRGTransformation._fill_upper_half (tmp, res, axes)
+        RGRGTransformation._fill_upper_half(tmp, res, axes)
         return res
 
     def transform(self, val, axes=None):

nifty2go/sugar.py

@@ -120,8 +120,7 @@ def create_composed_fft_operator(domain, codomain=None, all_to='other'):
 
     if codomain is None:
         codomain = [None]*len(domain)
-    for i in range(len(domain)):
-        space = domain[i]
+    for i, space in enumerate(domain):
         cospace = codomain[i]
         if not isinstance(space, Space):
             continue