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Commit 7b463c37 authored by Martin Reinecke's avatar Martin Reinecke
Browse files

cleanup

parent 72225dd1
Show whitespace changes
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nifty/field.py
View file @ 7b463c37
......@@ -82,9 +82,7 @@ class Field(object):
def __init__(self, domain=None, val=None, dtype=None, copy=False):
self.domain = self._parse_domain(domain=domain, val=val)
self.domain_axes = self._get_axes_tuple(self.domain)
self.dtype = self._infer_dtype(dtype=dtype,
val=val)
self.dtype = self._infer_dtype(dtype=dtype, val=val)
if val is None:
self._val = None
......@@ -134,9 +132,7 @@ class Field(object):
else:
dtype = np.dtype(dtype)
dtype = np.result_type(dtype, np.float)
return dtype
return np.result_type(dtype, np.float)
# ---Factory methods---
......@@ -173,12 +169,6 @@ class Field(object):
# create a initially empty field
f = cls(domain=domain, dtype=dtype)
# now use the processed input in terms of f in order to parse the
# random arguments
random_arguments = cls._parse_random_arguments(random_type=random_type,
f=f,
**kwargs)
# extract the data from f and apply the appropriate
# random number generator to it
sample = f.get_val(copy=False)
......@@ -186,32 +176,9 @@ class Field(object):
sample[:]=generator_function(dtype=f.dtype,
shape=sample.shape,
**random_arguments)
**kwargs)
return f
@staticmethod
def _parse_random_arguments(random_type, f, **kwargs):
if random_type == "pm1":
random_arguments = {}
elif random_type == "normal":
mean = kwargs.get('mean', 0)
std = kwargs.get('std', 1)
random_arguments = {'mean': mean,
'std': std}
elif random_type == "uniform":
low = kwargs.get('low', 0)
high = kwargs.get('high', 1)
random_arguments = {'low': low,
'high': high}
else:
raise KeyError(
"unsupported random key '" + str(random_type) + "'.")
return random_arguments
# ---Powerspectral methods---
def power_analyze(self, spaces=None, binbounds=None,
......@@ -507,22 +474,8 @@ class Field(object):
def _hermitian_decomposition(domain, val, spaces, domain_axes,
preserve_gaussian_variance=False):
flipped_val = val
for space in spaces:
flipped_val = domain[space].hermitianize_inverter(
x=flipped_val,
axes=domain_axes[space])
# if no flips at all where performed `h` is a real field.
# if all spaces use the default implementation of doing nothing when
# no flips are applied, one can use `is` to infer this case.
if flipped_val is val:
h = flipped_val.real.copy()
a = 1j * flipped_val.imag.copy()
else:
flipped_val = flipped_val.conjugate()
h = (val + flipped_val)/2.
a = val - h
h = val.real.copy()
a = 1j * val.imag.copy()
# correct variance
if preserve_gaussian_variance:
......@@ -531,42 +484,6 @@ class Field(object):
h *= np.sqrt(2)
a *= np.sqrt(2)
# The code below should not be needed in practice, since it would
# only ever be called when hermitianizing a purely real field.
# However it might be of educational use and keep us from forgetting
# how these things are done ...
# if not issubclass(val.dtype.type, np.complexfloating):
# # in principle one must not correct the variance for the fixed
# # points of the hermitianization. However, for a complex field
# # the input field loses half of its power at its fixed points
# # in the `hermitian` part. Hence, here a factor of sqrt(2) is
# # also necessary!
# # => The hermitianization can be done on a space level since
# # either nothing must be done (LMSpace) or ALL points need a
# # factor of sqrt(2)
# # => use the preserve_gaussian_variance flag in the
# # hermitian_decomposition method above.
#
# # This code is for educational purposes:
# fixed_points = [domain[i].hermitian_fixed_points()
# for i in spaces]
# fixed_points = [[fp] if fp is None else fp
# for fp in fixed_points]
#
# for product_point in itertools.product(*fixed_points):
# slice_object = np.array((slice(None), )*len(val.shape),
# dtype=np.object)
# for i, sp in enumerate(spaces):
# point_component = product_point[i]
# if point_component is None:
# point_component = slice(None)
# slice_object[list(domain_axes[sp])] = point_component
#
# slice_object = tuple(slice_object)
# h[slice_object] /= np.sqrt(2)
# a[slice_object] /= np.sqrt(2)
return (h, a)
def _spec_to_rescaler(self, spec, result_list, power_space_index):
......@@ -1159,262 +1076,78 @@ class Field(object):
return working_field
def __add__(self, other):
""" x.__add__(y) <==> x+y
See Also
--------
_binary_helper
"""
return self._binary_helper(other, op='__add__')
def __radd__(self, other):
""" x.__radd__(y) <==> y+x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__radd__')
def __iadd__(self, other):
""" x.__iadd__(y) <==> x+=y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__iadd__', inplace=True)
def __sub__(self, other):
""" x.__sub__(y) <==> x-y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__sub__')
def __rsub__(self, other):
""" x.__rsub__(y) <==> y-x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__rsub__')
def __isub__(self, other):
""" x.__isub__(y) <==> x-=y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__isub__', inplace=True)
def __mul__(self, other):
""" x.__mul__(y) <==> x*y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__mul__')
def __rmul__(self, other):
""" x.__rmul__(y) <==> y*x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__rmul__')
def __imul__(self, other):
""" x.__imul__(y) <==> x*=y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__imul__', inplace=True)
def __div__(self, other):
""" x.__div__(y) <==> x/y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__div__')
def __truediv__(self, other):
""" x.__truediv__(y) <==> x/y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__truediv__')
def __rdiv__(self, other):
""" x.__rdiv__(y) <==> y/x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__rdiv__')
def __rtruediv__(self, other):
""" x.__rtruediv__(y) <==> y/x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__rtruediv__')
def __idiv__(self, other):
""" x.__idiv__(y) <==> x/=y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__idiv__', inplace=True)
def __pow__(self, other):
""" x.__pow__(y) <==> x**y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__pow__')
def __rpow__(self, other):
""" x.__rpow__(y) <==> y**x
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__rpow__')
def __ipow__(self, other):
""" x.__ipow__(y) <==> x**=y
See Also
--------
_builtin_helper
"""
return self._binary_helper(other, op='__ipow__', inplace=True)
def __lt__(self, other):
""" x.__lt__(y) <==> x<y
See Also
--------
_binary_helper
"""
return self._binary_helper(other, op='__lt__')
def __le__(self, other):
""" x.__le__(y) <==> x<=y
See Also
--------
_binary_helper
"""
return self._binary_helper(other, op='__le__')
def __ne__(self, other):
""" x.__ne__(y) <==> x!=y
See Also
--------
_binary_helper
"""
if other is None:
return True
else:
return self._binary_helper(other, op='__ne__')
def __eq__(self, other):
""" x.__eq__(y) <==> x=y
See Also
--------
_binary_helper
"""
if other is None:
return False
else:
return self._binary_helper(other, op='__eq__')
def __ge__(self, other):
""" x.__ge__(y) <==> x>=y
See Also
--------
_binary_helper
"""
return self._binary_helper(other, op='__ge__')
def __gt__(self, other):
""" x.__gt__(y) <==> x>y
See Also
--------
_binary_helper
"""
return self._binary_helper(other, op='__gt__')
def __repr__(self):
......
nifty/spaces/lm_space/lm_space.py
View file @ 7b463c37
......@@ -87,8 +87,6 @@ class LMSpace(Space):
super(LMSpace, self).__init__()
self._lmax = self._parse_lmax(lmax)
# ---Mandatory properties and methods---
def __repr__(self):
return ("LMSpace(lmax=%r)" % self.lmax)
......@@ -143,22 +141,12 @@ class LMSpace(Space):
def get_natural_binbounds(self):
return np.arange(self.lmax, dtype=np.float64) + 0.5
@staticmethod
def _distance_array_helper(index_array, lmax):
u = 2*lmax + 1
index_half = (index_array+np.minimum(lmax, index_array)+1)//2
m = (np.ceil((u - np.sqrt(u*u - 8*(index_half - lmax)))/2)).astype(int)
res = (index_half - m*(u - m)//2).astype(np.float64)
return res
def get_fft_smoothing_kernel_function(self, sigma):
# cf. "All-sky convolution for polarimetry experiments"
# by Challinor et al.
# http://arxiv.org/abs/astro-ph/0008228
return lambda x: np.exp(-0.5 * x * (x + 1) * sigma*sigma)
# ---Added properties and methods---
@property
def lmax(self):
""" Returns the maximal :math:`l` value of any spherical harmonics
......
nifty/spaces/rg_space/rg_space.py
View file @ 7b463c37
......@@ -90,32 +90,6 @@ class RGSpace(Space):
self._shape = self._parse_shape(shape)
self._distances = self._parse_distances(distances)
# This code is unused but may be useful to keep around if it is ever needed
# again in the future ...
# def hermitian_fixed_points(self):
# dimensions = len(self.shape)
# mid_index = np.array(self.shape)//2
# ndlist = [1]*dimensions
# for k in range(dimensions):
# if self.shape[k] % 2 == 0:
# ndlist[k] = 2
# ndlist = tuple(ndlist)
# fixed_points = []
# for index in np.ndindex(ndlist):
# for k in range(dimensions):
# if self.shape[k] % 2 != 0 and self.zerocenter[k]:
# index = list(index)
# index[k] = 1
# index = tuple(index)
# fixed_points += [tuple(index * mid_index)]
# return fixed_points
def hermitianize_inverter(self, x, axes):
return x
# ---Mandatory properties and methods---
def __repr__(self):
return ("RGSpace(shape=%r, distances=%r, harmonic=%r)"
% (self.shape, self.distances, self.harmonic))
......
nifty/spaces/space/space.py
View file @ 7b463c37
......@@ -148,23 +148,3 @@ class Space(DomainObject):
raise NotImplementedError(
"There is no generic co-smoothing kernel for Space base class.")
def hermitianize_inverter(self, x, axes):
""" Inverts/flips x in the context of Hermitian decomposition.
This method is only implemented for harmonic spaces.
This method is mainly used for power-synthesizing and -analyzing
Fields.
Parameters
----------
axes : tuple of ints
Specifies the axes of x which correspond to this space.
Returns
-------
numpy.ndarray
The Hermitian-flipped of x.
"""
return x
test/test_spaces/test_lm_space.py
View file @ 7b463c37
......@@ -108,13 +108,6 @@ class LMSpaceFunctionalityTests(unittest.TestCase):
for key, value in expected.items():
assert_equal(getattr(l, key), value)
def test_hermitianize_inverter(self):
l = LMSpace(5)
v = np.empty(l.shape, dtype=np.complex128)
v[:] = np.random.random(l.shape) + 1j*np.random.random(l.shape)
inverted = l.hermitianize_inverter(v, axes=(0,))
assert_array_almost_equal(inverted, v)
@expand(get_weight_configs())
def test_weight(self, x, power, axes, inplace, expected):
l = LMSpace(5)
......
test/test_spaces/test_rg_space.py
View file @ 7b463c37
......@@ -127,20 +127,6 @@ class RGSpaceFunctionalityTests(unittest.TestCase):
for key, value in expected.items():
assert_equal(getattr(x, key), value)
@expand(product([(10,), (11,), (1, 1), (4, 4), (5, 7), (8, 12), (7, 16),
(4, 6, 8), (17, 5, 3)]))
def test_hermitianize_inverter(self, shape):
try:
r = RGSpace(shape, harmonic=True)
except ValueError:
raise SkipTest
v = np.empty(shape, dtype=np.complex128)
v[:] = np.random.random(shape) + 1j*np.random.random(shape)
inverted = r.hermitianize_inverter(v, axes=range(len(shape)))
assert_array_equal(v, inverted)
@expand(get_distance_array_configs())
def test_distance_array(self, shape, distances, expected):
r = RGSpace(shape=shape, distances=distances, harmonic=True)
......
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