added docstrings for attributes in space classes, moved some existing docstrings from init

nifty/spaces/lm_space/lm_space.py

@@ -37,7 +37,7 @@ class LMSpace(Space):
         NIFTY subclass for spherical harmonics components, for representations
         of fields on the two-sphere.
 
-        Parameters
+        Attributes
         ----------
         lmax : int
             The maximal :math:`l` value of any spherical harmonics
@@ -45,6 +45,14 @@ class LMSpace(Space):
         mmax : int
             The maximal :math:`m` value of any spherical harmonic
             :math:`Y_{lm}` that is represented in this Space.
+        dim : np.int
+            Total number of dimensionality, i.e. the number of pixels.
+        harmonic : bool
+            Specifies whether the space is a signal or harmonic space.
+        total_volume : np.float
+            The total volume of the space.
+        shape : tuple of np.ints
+            The shape of the space's data array.
 
         See Also
         --------

nifty/spaces/power_space/power_indices.py

@@ -25,32 +25,33 @@ from d2o.config import configuration as d2o_config
 
 
 class PowerIndices(object):
+    """Computes helpful quantities to deal with power spectra.
+    
+    Given the shape and the density of a underlying rectangular grid this 
+    class provides the user
+    with the pindex, kindex, rho and pundex. The indices are binned
+    according to the supplied parameter scheme. If wanted, computed
+    results are stored for future reuse.
+
+    Attributes
+    ----------
+    shape : tuple, list, ndarray
+        Array-like object which specifies the shape of the underlying
+        rectangular grid
+    dgrid : tuple, list, ndarray
+        Array-like object which specifies the step-width of the
+        underlying grid
+    logarithmic : bool *optional*
+        Flag specifying if the binning of the default indices is
+        performed on logarithmic scale.
+    nbin : integer *optional*
+        Number of used bins for the binning of the default indices.
+    binbounds : {list, array}
+        Array-like inner boundaries of the used bins of the default
+        indices.
+    """
     def __init__(self, domain, distribution_strategy,
                  logarithmic=False, nbin=None, binbounds=None):
-        """
-            Returns an instance of the PowerIndices class. Given the shape and
-            the density of a underlying rectangular grid it provides the user
-            with the pindex, kindex, rho and pundex. The indices are binned
-            according to the supplied parameter scheme. If wanted, computed
-            results are stored for future reuse.
-
-            Parameters
-            ----------
-            shape : tuple, list, ndarray
-                Array-like object which specifies the shape of the underlying
-                rectangular grid
-            dgrid : tuple, list, ndarray
-                Array-like object which specifies the step-width of the
-                underlying grid
-            logarithmic : bool *optional*
-                Flag specifying if the binning of the default indices is
-                performed on logarithmic scale.
-            nbin : integer *optional*
-                Number of used bins for the binning of the default indices.
-            binbounds : {list, array}
-                Array-like inner boundaries of the used bins of the default
-                indices.
-        """
         self.domain = domain
         self.distribution_strategy = distribution_strategy
 

nifty/spaces/power_space/power_space.py

@@ -54,14 +54,24 @@ class PowerSpace(Space):
     Attributes
     ----------
     pindex : distributed_data_object
-        TODO add description
+        This holds the information which pixel of the harmonic partner gets
+        mapped to which power bin
     kindex : numpy.ndarray
-        TODO add description
+        Sorted array of all k-modes.
     pundex : numpy.ndarray
-        TODO add description
+        Flat index of the first occurence of a k-vector with length==kindex[n] 
+        in the k_array.
     rho : numpy.ndarray
         The amount of k-modes that get mapped to one power bin is given by
         rho.
+    dim : np.int
+        Total number of dimensionality, i.e. the number of pixels.
+    harmonic : bool
+        Specifies whether the space is a signal or harmonic space.
+    total_volume : np.float
+        The total volume of the space.
+    shape : tuple of np.ints
+        The shape of the space's data array.
 
 
     Notes
@@ -216,7 +226,7 @@ class PowerSpace(Space):
 
     @property
     def pindex(self):
-        """ A distributed_data_objects having the shape of the harmonic partner
+        """ A distributed_data_object having the shape of the harmonic partner
         space containing the indices of the power bin a pixel belongs to.
         """
         return self._pindex