diff --git a/nifty/spaces/power_space/power_index_factory.py b/nifty/spaces/power_space/power_index_factory.py
index 04958569703848839cc244b32b072a561c19d6e1..ab14e5662f2ec221d0cd652e71b8809be6e54cb0 100644
--- a/nifty/spaces/power_space/power_index_factory.py
+++ b/nifty/spaces/power_space/power_index_factory.py
@@ -30,7 +30,9 @@ class _PowerIndexFactory(object):
if key not in self.power_indices_storage:
self.power_indices_storage[key] = \
PowerIndices(domain, distribution_strategy,
- logarithmic=logarithmic, nbin=nbin, binbounds=binbounds)
+ logarithmic=logarithmic,
+ nbin=nbin,
+ binbounds=binbounds)
power_indices = self.power_indices_storage[key]
power_index = power_indices.get_index_dict(logarithmic=logarithmic,
nbin=nbin,
diff --git a/nifty/spaces/power_space/power_indices.py b/nifty/spaces/power_space/power_indices.py
index 73c88e4f70a1d257358c7f04fc1bc3614482948f..64018cd6b1b561caae559afc8d7af2d5a00d4690 100644
--- a/nifty/spaces/power_space/power_indices.py
+++ b/nifty/spaces/power_space/power_indices.py
@@ -113,7 +113,8 @@ class PowerIndices(object):
return self._cast_config_helper(**temp_config_dict)
else:
defaults = self.default_parameters
- temp_logarithmic = kwargs.get("logarithmic", defaults['logarithmic'])
+ temp_logarithmic = kwargs.get("logarithmic",
+ defaults['logarithmic'])
temp_nbin = kwargs.get("nbin", defaults['nbin'])
temp_binbounds = kwargs.get("binbounds", defaults['binbounds'])
diff --git a/nifty/spaces/power_space/power_space.py b/nifty/spaces/power_space/power_space.py
index efb9b716f25f2742c6d83b5a69f520f1781d0590..223404ee94467387f958a6c3fa011d7a012b6bce 100644
--- a/nifty/spaces/power_space/power_space.py
+++ b/nifty/spaces/power_space/power_space.py
@@ -27,45 +27,55 @@ from nifty.spaces.rg_space import RGSpace
class PowerSpace(Space):
+ """ NIFTY class for spaces of power spectra.
+
+ Parameters
+ ----------
+ harmonic_partner : Space
+ The harmonic Space of which this is the power space.
+ distribution_strategy : str *optional*
+ The distribution strategy used for the distributed_data_objects
+ derived from this PowerSpace, e.g. the pindex.
+ (default : 'not')
+ logarithmic : bool *optional*
+ True if logarithmic binning should be used (default : False).
+ nbin : {int, None} *optional*
+ The number of bins that should be used for power spectrum binning
+ (default : None).
+ if nbin == None, then nbin is set to the length of kindex.
+ binbounds : {list, array-like} *optional*
+ Array-like inner boundaries of the used bins of the default
+ indices.
+ (default : None)
+ if binbounds == None :
+ Calculates the bounds from the kindex while applying the
+ logarithmic and nbin keywords.
+
+ Attributes
+ ----------
+ pindex : distributed_data_object
+ TODO add description
+ kindex : numpy.ndarray
+ TODO add description
+ pundex : numpy.ndarray
+ TODO add description
+ rho : numpy.ndarray
+ The amount of k-modes that get mapped to one power bin is given by
+ rho.
+
+
+ Notes
+ -----
+ A power space is the result of a projection of a harmonic space where
+ k-modes of equal length get mapped to one power index.
+
+ """
# ---Overwritten properties and methods---
def __init__(self, harmonic_partner=RGSpace((1,)),
distribution_strategy='not',
logarithmic=False, nbin=None, binbounds=None):
- """Sets the attributes for a PowerSpace class instance.
-
- Parameters
- ----------
- harmonic_partner : Space
- The harmonic Space of which this is the power space.
- distribution_strategy : str *optional*
- The distribution strategy of a d2o-object represeting a field over this PowerSpace.
- (default : 'not')
- logarithmic : bool *optional*
- True if logarithmic binning should be used.
- (default : False)
- nbin : {int, None} *optional*
- The number of bins this space has.
- (default : None) if nbin == None : It takes the nbin from its harmonic_partner
- binbounds : {list, array} *optional*
- Array-like inner boundaries of the used bins of the default
- indices.
- (default : None) if binbounds == None : Calculates the bounds from the kindex and corrects for logartihmic scale
- Notes
- -----
- A power space is the result of a projection of a harmonic space where multiple k-modes get mapped to one power index.
- This can be regarded as a response operator :math:`R` going from harmonic space to power space.
- An array giving this map is stored in pindex (array which says in which power box a k-mode gets projected)
- An array for the adjoint of :math:`R` is given by kindex, which is an array of arrays stating which k-mode got mapped to a power index
- The a right-inverse to :math:`R` is given by the pundex which is an array giving one k-mode that maps to a power bin for every power bin.
- The amount of k-modes that get mapped to one power bin is given by rho. This is :math:`RR^\dagger` in the language of this projection operator
- Returns
- -------
- None.
-
- """
- #FIXME: default probably not working for log and normal scale
super(PowerSpace, self).__init__()
self._ignore_for_hash += ['_pindex', '_kindex', '_rho', '_pundex',
'_k_array']
@@ -97,22 +107,28 @@ class PowerSpace(Space):
self._k_array = power_index['k_array']
def pre_cast(self, x, axes):
- """Casts power spectra to discretized power spectra.
-
- This function takes an array or a function. If it is an array it does nothing,
- otherwise it intepretes the function as power spectrum and evaluates it at every
- k-mode.
+ """ Casts power spectrum functions to discretized power spectra.
+
+ This function takes an array or a function. If it is an array it does
+ nothing, otherwise it interpretes the function as power spectrum and
+ evaluates it at every k-mode.
+
Parameters
----------
x : {array-like, function array-like -> array-like}
- power spectrum given either in discretized form or implicitly as a function
- axes : {tuple, int} *optional*
- does nothing
- (default : None)
+ power spectrum given either in discretized form or implicitly as a
+ function
+ axes : tuple of ints
+ Specifies the axes of x which correspond to this space. For
+ explicifying the power spectrum function, this is ignored.
+
Returns
-------
- array-like : discretized power spectrum
+ array-like
+ discretized power spectrum
+
"""
+
if callable(x):
return x(self.kindex)
else:
@@ -176,86 +192,60 @@ class PowerSpace(Space):
@property
def harmonic_partner(self):
- """Returns the Space of which this is the power space.
- Returns
- -------
- Space : The harmonic Space of which this is the power space.
+ """ Returns the Space of which this is the power space.
"""
return self._harmonic_partner
@property
def logarithmic(self):
- """Returns a True if logarithmic binning is used.
- Returns
- -------
- Bool : True if for this PowerSpace logarithmic binning is used.
+ """ Returns True if logarithmic binning is used.
"""
return self._logarithmic
@property
def nbin(self):
- """Returns the number of power bins.
- Returns
- -------
- int : The number of bins this space has.
+ """ Returns the number of power bins if specfied during initialization.
"""
return self._nbin
@property
def binbounds(self):
- """ Inner boundaries of the used bins of the default
- indices.
- Returns
- -------
- {list, array} : the inner boundaries of the used bins in the used scale, as they were
- set in __init__ or computed.
+ """ Inner boundaries of the used bins if specfied during initialization.
"""
- # FIXME check wether this returns something sensible if 'None' was set in __init__
return self._binbounds
@property
def pindex(self):
- """Index of the Fourier grid points that belong to a specific power index
- Returns
- -------
- distributed_data_object : Index of the Fourier grid points in a distributed_data_object.
- """
+ """ A distributed_data_objects having the shape of the harmonic partner
+ space containing the indices of the power bin a pixel belongs to.
+ """
return self._pindex
@property
def kindex(self):
- """Array of all k-vector lengths.
- Returns
- -------
- ndarray : Array which states for each k-mode which power index it maps to (adjoint to pindex)
- """
+ """ Sorted array of all k-modes.
+ """
return self._kindex
@property
def rho(self):
- """Degeneracy factor of the individual k-vectors.
-
- ndarray : Array stating how many k-modes are mapped to one power index for every power index
- """
+ """Degeneracy factor of the individual k-vectors.
+ """
return self._rho
@property
def pundex(self):
- """List of one k-mode per power bin which is in the bin.
- Returns
- -------
- array-like : An array for which the n-th entry is an example one k-mode which belongs to the n-th power bin
- """
+ """ An array for which the n-th entry gives the flat index of the
+ first occurence of a k-vector with length==kindex[n] in the
+ k_array.
+ """
return self._pundex
@property
def k_array(self):
- """This contains distances to zero for every k-mode of the harmonic partner.
-
- Returns
- -------
- array-like : An array containing distances to the zero mode for every k-mode of the harmonic partner.
- """
+ """ An array containing distances to the grid center (i.e. zero-mode)
+ for every k-mode in the grid of the harmonic partner space.
+ """
return self._k_array
# ---Serialization---
@@ -284,7 +274,8 @@ class PowerSpace(Space):
# call instructor so that classes are properly setup
super(PowerSpace, new_ps).__init__()
# set all values
- new_ps._harmonic_partner = repository.get('harmonic_partner', hdf5_group)
+ new_ps._harmonic_partner = repository.get('harmonic_partner',
+ hdf5_group)
new_ps._logarithmic = hdf5_group['logarithmic'][()]
exec('new_ps._nbin = ' + hdf5_group.attrs['nbin'])
exec('new_ps._binbounds = ' + hdf5_group.attrs['binbounds'])
diff --git a/test/test_spaces/test_power_space.py b/test/test_spaces/test_power_space.py
index 50664d1e13ec4cecdf88f4cf9130a8ba24509174..20fba9a7dd34c77e2b3271c24e724d135f401c8b 100644
--- a/test/test_spaces/test_power_space.py
+++ b/test/test_spaces/test_power_space.py
@@ -29,7 +29,7 @@ from types import NoneType
from test.common import expand
# [harmonic_domain, distribution_strategy,
-# log, nbin, binbounds, expected]
+# logarithmic, nbin, binbounds, expected]
CONSTRUCTOR_CONFIGS = [
[1, 'not', False, None, None, {'error': ValueError}],
[RGSpace((8,)), 'not', False, None, None, {'error': ValueError}],
@@ -95,7 +95,7 @@ def get_weight_configs():
class PowerSpaceInterfaceTest(unittest.TestCase):
@expand([
['harmonic_domain', Space],
- ['log', bool],
+ ['logarithmic', bool],
['nbin', (int, NoneType)],
['binbounds', (list, NoneType)],
['pindex', distributed_data_object],
@@ -112,17 +112,19 @@ class PowerSpaceInterfaceTest(unittest.TestCase):
class PowerSpaceFunctionalityTest(unittest.TestCase):
@expand(CONSTRUCTOR_CONFIGS)
- def test_constructor(self, harmonic_domain, distribution_strategy, log,
- nbin, binbounds, expected):
+ def test_constructor(self, harmonic_domain, distribution_strategy,
+ logarithmic, nbin, binbounds, expected):
if 'error' in expected:
with assert_raises(expected['error']):
PowerSpace(harmonic_domain=harmonic_domain,
distribution_strategy=distribution_strategy,
- log=log, nbin=nbin, binbounds=binbounds)
+ logarithmic=logarithmic, nbin=nbin,
+ binbounds=binbounds)
else:
p = PowerSpace(harmonic_domain=harmonic_domain,
distribution_strategy=distribution_strategy,
- log=log, nbin=nbin, binbounds=binbounds)
+ logarithmic=logarithmic, nbin=nbin,
+ binbounds=binbounds)
for key, value in expected.iteritems():
if isinstance(value, np.ndarray):
assert_almost_equal(getattr(p, key), value)