WIP: LMSpace smoothing

- Cython extension to return the correct l-number for an index

nifty/spaces/gl_space/gl_space.py

@@ -173,7 +173,10 @@ class GLSpace(Space):
         return np.arctan(numerator / denominator)
 
     def get_smoothing_kernel_function(self, sigma):
-        raise NotImplementedError
+        if sigma is None:
+            sigma = np.sqrt(2) * np.pi / self.nlat
+
+        return lambda x: np.exp((-0.5 * x**2) / sigma**2)
 
     # ---Added properties and methods---
 

nifty/spaces/hp_space/hp_space.py

@@ -186,8 +186,11 @@ class HPSpace(Space):
 
         return dists
 
-    def get_smoothing_kernel_function(self, sigma, target):
-        raise NotImplementedError
+    def get_smoothing_kernel_function(self, sigma):
+        if sigma is None:
+            sigma = np.sqrt(2) * np.pi / self.nlat
+
+        return lambda x: np.exp((-0.5 * x**2) / sigma**2)
 
     # ---Added properties and methods---
 

nifty/spaces/lm_space/lm_helper.pyx

+import numpy as np
+cimport numpy as np
+
+cpdef _distance_array_helper(np.int_t x, np.ndarray[np.int_t] l,
+                             np.int_t original_size, np.int_t lmax):
+    cdef np.int size = (lmax + 1) * (lmax  + 1)
+
+    cdef np.ndarray res = np.zeros([size], dtype=np.float128)
+    res[0:lmax + 1] = np.arange(lmax + 1)
+
+    for i in xrange(original_size - lmax - 1):
+        res[i * 2 + lmax + 1] = l[i + lmax + 1]
+        res[i * 2 + lmax + 1] = l[i + lmax + 1]
+
+    return res[x]

nifty/spaces/lm_space/lm_space.py

-
 from __future__ import division
 
 import numpy as np
@@ -9,6 +8,10 @@ from nifty.config import about,\
                          nifty_configuration as gc,\
                          dependency_injector as gdi
 
+from lm_helper import _distance_array_helper
+
+from d2o import arange
+
 gl = gdi.get('libsharp_wrapper_gl')
 hp = gdi.get('healpy')
 
@@ -111,7 +114,19 @@ class LMSpace(Space):
         self._mmax = self._parse_mmax(mmax)
 
     def distance_array(self, distribution_strategy):
-        raise NotImplementedError
+        dists = arange(
+            start=0, stop=self.shape[0], dtype=np.float128,
+            distribution_strategy=distribution_strategy
+        )
+
+        l = hp.Alm.getlm(lmax=self.lmax)[0]
+        dists = dists.apply_scalar_function(
+            lambda x: _distance_array_helper(
+                int(x), l, hp.Alm.getsize(self.lmax), self.lmax
+                )
+            )
+
+        return dists
 
     def get_smoothing_kernel_function(self, sigma):
         if sigma is None:

setup.py

@@ -37,9 +37,11 @@ setup(name="ift_nifty",
       packages=find_packages(),
       package_dir={"nifty": "nifty"},
       zip_safe=False,
-      ext_modules=cythonize(
-          "nifty/operators/fft_operator/transformations/lm_transformation_factory"
-          ".pyx"),
+      ext_modules=cythonize([
+          "nifty/operators/fft_operator/transformations/"
+          "lm_transformation_factory.pyx",
+          "nifty/spaces/lm_space/lm_helper.pyx"
+      ]),
       include_dirs= [numpy.get_include()],
       dependency_links=[
         'git+https://gitlab.mpcdf.mpg.de/ift/keepers.git#egg=keepers',

[Theo Steininger]

Copy-pasted duplicated line...

[Theo Steininger]

i*2+lmax+2