diff --git a/nifty2go/field.py b/nifty2go/field.py
index 13b836b55eaf6f7f52ea4cb72b013ac845341b2e..bed92012ef57c2d99c488292973f49f1d06c2406 100644
--- a/nifty2go/field.py
+++ b/nifty2go/field.py
@@ -17,10 +17,8 @@
# and financially supported by the Studienstiftung des deutschen Volkes.
from __future__ import division
-from builtins import zip
from builtins import range
-import ast
import numpy as np
from .domain_object import DomainObject
@@ -84,24 +82,24 @@ class Field(object):
self.domain_axes = self._get_axes_tuple(self.domain)
shape_tuple = tuple(sp.shape for sp in self.domain)
- if len(shape_tuple)==0:
+ if len(shape_tuple) == 0:
global_shape = ()
else:
global_shape = reduce(lambda x, y: x + y, shape_tuple)
dtype = self._infer_dtype(dtype=dtype, val=val)
if isinstance(val, Field):
- if self.domain!=val.domain:
+ if self.domain != val.domain:
raise ValueError("Domain mismatch")
- self._val = np.array(val.val,dtype=dtype,copy=copy)
+ self._val = np.array(val.val, dtype=dtype, copy=copy)
elif (np.isscalar(val)):
- self._val=np.full(global_shape,dtype=dtype,fill_value=val)
+ self._val = np.full(global_shape, dtype=dtype, fill_value=val)
elif isinstance(val, np.ndarray):
- if global_shape==val.shape:
- self._val = np.array(val,dtype=dtype,copy=copy)
+ if global_shape == val.shape:
+ self._val = np.array(val, dtype=dtype, copy=copy)
else:
raise ValueError("Shape mismatch")
elif val is None:
- self._val = np.empty(global_shape,dtype=dtype)
+ self._val = np.empty(global_shape, dtype=dtype)
else:
raise TypeError("unknown source type")
@@ -130,7 +128,7 @@ class Field(object):
axes_list = []
for thing in things_with_shape:
nax = len(thing.shape)
- axes_list += [tuple(range(i,i+nax))]
+ axes_list += [tuple(range(i, i+nax))]
i += nax
return tuple(axes_list)
@@ -138,7 +136,7 @@ class Field(object):
if val is None:
return np.float64 if dtype is None else dtype
if dtype is None:
- if isinstance(val,Field):
+ if isinstance(val, Field):
return val.dtype
return np.result_type(val)
@@ -176,7 +174,7 @@ class Field(object):
f = cls(domain=domain, dtype=dtype)
generator_function = getattr(Random, random_type)
- f.val=generator_function(dtype=f.dtype, shape=f.shape, **kwargs)
+ f.val = generator_function(dtype=f.dtype, shape=f.shape, **kwargs)
return f
# ---Powerspectral methods---
@@ -294,7 +292,7 @@ class Field(object):
result_domain = list(work_field.domain)
result_domain[space_index] = power_domain
- return Field(domain=result_domain,val=power_spectrum,
+ return Field(domain=result_domain, val=power_spectrum,
dtype=power_spectrum.dtype)
@classmethod
@@ -308,7 +306,7 @@ class Field(object):
axes=axes)
power_spectrum = utilities.bincount_axis(pindex, weights=field_val,
- axis=axes)
+ axis=axes)
rho = pdomain.rho
if axes is not None:
new_rho_shape = [1, ] * len(power_spectrum.shape)
@@ -420,10 +418,10 @@ class Field(object):
result_list[1].val *= spec.imag
if real_signal:
- result_list=[Field(i.domain,self._hermitian_decomposition(
+ result_list = [Field(i.domain, self._hermitian_decomposition(
i.val,
preserve_gaussian_variance=True)[0])
- for i in result_list]
+ for i in result_list]
if real_power:
result = result_list[0]
@@ -479,21 +477,21 @@ class Field(object):
if new_val is None:
pass
elif isinstance(new_val, Field):
- if self.domain!=new_val.domain:
+ if self.domain != new_val.domain:
raise ValueError("Domain mismatch")
if copy:
self._val[()] = new_val.val
else:
- self._val = np.array(new_val.val,dtype=self.dtype,copy=False)
+ self._val = np.array(new_val.val, dtype=self.dtype, copy=False)
elif (np.isscalar(new_val)):
- self._val[()]=new_val
+ self._val[()] = new_val
elif isinstance(new_val, np.ndarray):
if copy:
self._val[()] = new_val
else:
- if self.shape!=new_val.shape:
+ if self.shape != new_val.shape:
raise ValueError("Shape mismatch")
- self._val = np.array(new_val,dtype=self.dtype,copy=False)
+ self._val = np.array(new_val, dtype=self.dtype, copy=False)
else:
raise TypeError("unknown source type")
return self
@@ -514,14 +512,13 @@ class Field(object):
See Also
--------
val
-
"""
-
return self._val.copy() if copy else self._val
@property
def val(self):
""" Returns the data object associated with this Field.
+ No copy is made.
Returns
-------
@@ -530,9 +527,7 @@ class Field(object):
See Also
--------
get_val
-
"""
-
return self._val
@val.setter
@@ -552,12 +547,7 @@ class Field(object):
out : tuple
The output object. The tuple contains the dimensions of the spaces
in domain.
-
- See Also
- --------
- dim
-
- """
+ """
return self._val.shape
@property
@@ -570,11 +560,6 @@ class Field(object):
-------
out : int
The dimension of the Field.
-
- See Also
- --------
- shape
-
"""
return self._val.size
@@ -595,7 +580,6 @@ class Field(object):
def total_volume(self):
""" Returns the total volume of all spaces in the domain.
"""
-
volume_tuple = tuple(sp.total_volume for sp in self.domain)
try:
return reduce(lambda x, y: x * y, volume_tuple)
@@ -606,17 +590,16 @@ class Field(object):
def real(self):
""" The real part of the field (data is not copied).
"""
- return Field(self.domain,self.val.real)
+ return Field(self.domain, self.val.real)
@property
def imag(self):
""" The imaginary part of the field (data is not copied).
"""
- return Field(self.domain,self.val.imag)
+ return Field(self.domain, self.val.imag)
# ---Special unary/binary operations---
-
def copy(self, domain=None, dtype=None):
""" Returns a full copy of the Field.
@@ -645,7 +628,7 @@ class Field(object):
if domain is None:
domain = self.domain
- return Field(domain=domain,val=self._val,dtype=dtype,copy=True)
+ return Field(domain=domain, val=self._val, dtype=dtype, copy=True)
def copy_empty(self, domain=None, dtype=None):
""" Returns an empty copy of the Field.
@@ -747,7 +730,7 @@ class Field(object):
y = self if bare else self.weight(power=1)
if spaces is None:
- return np.vdot(y.val.flatten(),x.val.flatten())
+ return np.vdot(y.val.flatten(), x.val.flatten())
else:
# create a diagonal operator which is capable of taking care of the
# axes-matching
@@ -785,10 +768,10 @@ class Field(object):
"""
if inplace:
- self.imag*=-1
+ self.imag *= -1
return self
else:
- return Field(self.domain,np.conj(self.val),self.dtype)
+ return Field(self.domain, np.conj(self.val), self.dtype)
# ---General unary/contraction methods---
@@ -796,10 +779,10 @@ class Field(object):
return self.copy()
def __neg__(self):
- return Field(self.domain,-self.val,self.dtype)
+ return Field(self.domain, -self.val, self.dtype)
def __abs__(self):
- return Field(self.domain,np.abs(self.val),self.dtype)
+ return Field(self.domain, np.abs(self.val), self.dtype)
def _contraction_helper(self, op, spaces):
if spaces is None:
@@ -868,9 +851,9 @@ class Field(object):
if isinstance(other, Field):
if other.domain != self.domain:
raise ValueError("domains are incompatible.")
- return Field(self.domain,getattr(self.val,op)(other.val))
+ return Field(self.domain, getattr(self.val, op)(other.val))
- return Field(self.domain,getattr(self.val,op)(other))
+ return Field(self.domain, getattr(self.val, op)(other))
def __add__(self, other):
return self._binary_helper(other, op='__add__')