diff --git a/nifty/operators/smoothing_operator/Cython 2/test2.py b/nifty/operators/smoothing_operator/Cython 2/test2.py
deleted file mode 100644
index db2507b01417f6ae01768ff3f21c128eb82c1419..0000000000000000000000000000000000000000
--- a/nifty/operators/smoothing_operator/Cython 2/test2.py
+++ /dev/null
@@ -1,50 +0,0 @@
-import pyximport; pyximport.install()
-import extended
-
-import numpy as np
-
-
-print "///////////////////////////////////////First thing ////////////////////////"
-
-n=8
-
-ksq=np.sqrt(np.arange(n))
-kk=np.arange(n)
-power = np.ones(n**3).reshape((n,n,n))
-# power[0][4][4]=1000
-# power[1][4][4]=1000
-# power[2][4][4]=1000
-# power[3][4][4]=1000
-power[n/2][n/2][n/2]=10000
-# power[5][4][4]=1000
-# power[6][4][4]=1000
-# power[7][4][4]=1000
-k = kk
-sigma=k[1]-k[0]
-mirrorsize=7
-startindex=mirrorsize/2
-endindex=n-mirrorsize/2
-print power, k, power.shape
-smooth = extended.smooth_something(datablock=power, axis=(2),
- startindex=startindex, endindex=endindex,
- kernelfunction=extended.GaussianKernel, k=k,
- sigma=sigma)
-
-print "Smoooooth", smooth
-
-doublesmooth = extended.smooth_something(datablock=smooth, axis=(1),
- startindex=startindex, endindex=endindex,
- kernelfunction=extended.GaussianKernel,
- k=k, sigma=sigma)
-
-print "DoubleSmooth", doublesmooth
-
-tripplesmooth = extended.smooth_something(datablock=doublesmooth, axis=(0),
- startindex=startindex, endindex=endindex,
- kernelfunction=extended.GaussianKernel,
- k=k, sigma=sigma)
-
-print "TrippleSmooth", tripplesmooth
-
-print "///////////////////////////////////////Final thing ////////////////////////"
-print "smooth.len == power.len" , smooth.shape, power.shape, power.shape==smooth.shape
\ No newline at end of file
diff --git a/nifty/operators/smoothing_operator/Cython 2/extended.py b/nifty/operators/smoothing_operator/Cython/extended.py
similarity index 90%
rename from nifty/operators/smoothing_operator/Cython 2/extended.py
rename to nifty/operators/smoothing_operator/Cython/extended.py
index 9c3ef619ebb20f684657c39796b5ab486c62c773..6fbf41aebbebd353007793744a584be522de0981 100644
--- a/nifty/operators/smoothing_operator/Cython 2/extended.py
+++ b/nifty/operators/smoothing_operator/Cython/extended.py
@@ -50,8 +50,7 @@ def GaussianKernel(mpower, mk, mu,smooth_length):
return np.sum(C * mpower) / np.sum(C)
-def smoothie(power, startindex, endindex, k, kernelfunction, exclude=1,
- smooth_length=None):
+def smoothie(power, startindex, endindex, k, exclude=1, smooth_length=None):
if smooth_length == 0:
# No smoothing requested, just return the input array.
@@ -70,7 +69,7 @@ def smoothie(power, startindex, endindex, k, kernelfunction, exclude=1,
for i in xrange(startindex, endindex):
l = max(i-int(2*smooth_length)-1,0)
u = min(i+int(2*smooth_length)+2,len(p_smooth))
- p_smooth[i-startindex] = kernelfunction(power[l:u], k[l:u], k[i],
+ p_smooth[i-startindex] = GaussianKernel(power[l:u], k[l:u], k[i],
smooth_length)
if (exclude > 0):
@@ -87,6 +86,6 @@ def smooth_something(datablock, axis=0, startindex=None, endindex=None,
print kernelfunction
return np.apply_along_axis(smoothie, axis, datablock,
startindex=startindex, endindex=endindex, k=k,
- smooth_length=sigma, kernelfunction=kernelfunction)
+ smooth_length=sigma)
\ No newline at end of file
diff --git a/nifty/operators/smoothing_operator/Cython 2/original.py b/nifty/operators/smoothing_operator/Cython/original.py
similarity index 100%
rename from nifty/operators/smoothing_operator/Cython 2/original.py
rename to nifty/operators/smoothing_operator/Cython/original.py
diff --git a/nifty/operators/smoothing_operator/Cython 2/test.py b/nifty/operators/smoothing_operator/Cython/test.py
similarity index 100%
rename from nifty/operators/smoothing_operator/Cython 2/test.py
rename to nifty/operators/smoothing_operator/Cython/test.py
diff --git a/nifty/operators/smoothing_operator/Cython/test2.py b/nifty/operators/smoothing_operator/Cython/test2.py
new file mode 100644
index 0000000000000000000000000000000000000000..9556ef2bc8553ef651d60b8003feb18682636c28
--- /dev/null
+++ b/nifty/operators/smoothing_operator/Cython/test2.py
@@ -0,0 +1,58 @@
+import pyximport; pyximport.install()
+import extended
+import util
+
+import numpy as np
+
+
+print "///////////////////////////////////////First thing ////////////////////////"
+
+n=8
+
+ksq=np.sqrt(np.arange(n))
+kk=np.arange(n)
+power = np.ones(n**3).reshape((n,n,n))
+# power[0][4][4]=1000
+# power[1][4][4]=1000
+# power[2][4][4]=1000
+# power[3][4][4]=1000
+power[n/2][n/2][n/2]=10000
+# power[5][4][4]=1000
+# power[6][4][4]=1000
+# power[7][4][4]=1000
+k = kk
+sigma=k[1]-k[0]
+mirrorsize=7
+startindex=mirrorsize/2
+endindex=n-mirrorsize/2
+print power, k, power.shape
+# smooth = extended.smooth_something(datablock=power, axis=(2),
+# startindex=startindex, endindex=endindex,
+# kernelfunction=extended.GaussianKernel, k=k,
+# sigma=sigma)
+smooth = util.apply_along_axis(extended.smoothie, (2), power,
+ startindex=startindex, endindex=endindex, k=k,
+ smooth_length=sigma)
+print "Smoooooth", smooth
+
+# doublesmooth = extended.smooth_something(datablock=smooth, axis=(1),
+# startindex=startindex, endindex=endindex,
+# kernelfunction=extended.GaussianKernel,
+# k=k, sigma=sigma)
+doublesmooth = util.apply_along_axis(extended.smoothie, (1), smooth,
+ startindex=startindex, endindex=endindex, k=k,
+ smooth_length=sigma)
+
+print "DoubleSmooth", doublesmooth
+
+# tripplesmooth = extended.smooth_something(datablock=doublesmooth, axis=(0),
+# startindex=startindex, endindex=endindex,
+# kernelfunction=extended.GaussianKernel,
+# k=k, sigma=sigma)
+tripplesmooth = util.apply_along_axis(extended.smoothie, (0), doublesmooth,
+ startindex=startindex, endindex=endindex, k=k,
+ smooth_length=sigma)
+print "TrippleSmooth", tripplesmooth
+
+print "///////////////////////////////////////Final thing ////////////////////////"
+print "smooth.len == power.len" , tripplesmooth.shape, power.shape, power.shape==smooth.shape
\ No newline at end of file
diff --git a/nifty/operators/smoothing_operator/Cython/util.py b/nifty/operators/smoothing_operator/Cython/util.py
new file mode 100644
index 0000000000000000000000000000000000000000..b8f7b6aa9bb74e1c05283492be27351ef38f16d8
--- /dev/null
+++ b/nifty/operators/smoothing_operator/Cython/util.py
@@ -0,0 +1,70 @@
+import numpy as np
+
+def apply_along_axis(func1d, axis, arr, *args, **kwargs):
+ """
+ Apply a function to 1-D slices along the given axis.
+
+ Execute `func1d(a, *args)` where `func1d` operates on 1-D arrays and `a`
+ is a 1-D slice of `arr` along `axis`.
+
+ Parameters
+ ----------
+ func1d : function
+ This function should accept 1-D arrays. It is applied to 1-D
+ slices of `arr` along the specified axis.
+ axis : integer
+ Axis along which `arr` is sliced.
+ arr : ndarray
+ Input array.
+ args : any
+ Additional arguments to `func1d`.
+ kwargs: any
+ Additional named arguments to `func1d`.
+
+ .. versionadded:: 1.9.0
+
+
+ Returns
+ -------
+ apply_along_axis : ndarray
+ The output array. The shape of `outarr` is identical to the shape of
+ `arr`, except along the `axis` dimension, where the length of `outarr`
+ is equal to the size of the return value of `func1d`. If `func1d`
+ returns a scalar `outarr` will have one fewer dimensions than `arr`.
+ """
+ arr = np.asarray(arr)
+ nd = arr.ndim
+ if axis < 0:
+ axis += nd
+ if (axis >= nd):
+ raise ValueError("axis must be less than arr.ndim; axis=%d, rank=%d."
+ % (axis, nd))
+ ind = [0]*(nd-1)
+ i = np.zeros(nd, 'O')
+ indlist = list(range(nd))
+ indlist.remove(axis)
+ i[axis] = slice(None, None)
+ outshape = np.asarray(arr.shape).take(indlist)
+ i.put(indlist, ind)
+ res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
+
+ Ntot = np.product(outshape)
+ holdshape = outshape
+ outshape = list(arr.shape)
+ outshape[axis] = len(res)
+ outarr = np.zeros(outshape, np.asarray(res).dtype)
+ outarr[tuple(i.tolist())] = res
+ k = 1
+ while k < Ntot:
+ # increment the index
+ ind[-1] += 1
+ n = -1
+ while (ind[n] >= holdshape[n]) and (n > (1-nd)):
+ ind[n-1] += 1
+ ind[n] = 0
+ n -= 1
+ i.put(indlist, ind)
+ res = func1d(arr[tuple(i.tolist())], *args, **kwargs)
+ outarr[tuple(i.tolist())] = res
+ k += 1
+ return outarr
\ No newline at end of file