From 5e42cb29f4d30b74fb5c05ac4d9dfcc692e3b72d Mon Sep 17 00:00:00 2001
From: Martin Reinecke <martin@mpa-garching.mpg.de>
Date: Wed, 25 Oct 2017 21:49:59 +0200
Subject: [PATCH] rearranging
---
nifty/__init__.py | 4 +--
nifty/data_objects/numpy_do.py | 9 +++++--
nifty/{ => data_objects}/random.py | 0
nifty/field.py | 7 +++---
nifty/spaces/power_space.py | 2 +-
nifty/sugar.py | 40 +++++++++++++++++++-----------
6 files changed, 38 insertions(+), 24 deletions(-)
rename nifty/{ => data_objects}/random.py (100%)
diff --git a/nifty/__init__.py b/nifty/__init__.py
index 2f6ad33dc..8595f2c0c 100644
--- a/nifty/__init__.py
+++ b/nifty/__init__.py
@@ -8,8 +8,6 @@ from .domain_tuple import DomainTuple
from .domain_object import DomainObject
-from .random import Random
-
from .basic_arithmetics import *
from .nifty_utilities import *
@@ -32,6 +30,6 @@ from . import plotting
from . import library
-from .data_objects import numpy_do as dobj
+from . import dobj
from .memoization import memo
diff --git a/nifty/data_objects/numpy_do.py b/nifty/data_objects/numpy_do.py
index f311a1657..49f6da1c3 100644
--- a/nifty/data_objects/numpy_do.py
+++ b/nifty/data_objects/numpy_do.py
@@ -3,8 +3,13 @@
import numpy as np
from numpy import ndarray as data_object
from numpy import full, empty, sqrt, ones, zeros, vdot, abs, bincount, exp, log
-from ..nifty_utilities import cast_iseq_to_tuple, get_slice_list
-from functools import reduce
+from .random import Random
+
def from_object(object, dtype=None, copy=True):
return np.array(object, dtype=dtype, copy=copy)
+
+
+def from_random(random_type, shape, dtype=np.float64, **kwargs):
+ generator_function = getattr(Random, random_type)
+ return generator_function(dtype=dtype, shape=shape, **kwargs)
diff --git a/nifty/random.py b/nifty/data_objects/random.py
similarity index 100%
rename from nifty/random.py
rename to nifty/data_objects/random.py
diff --git a/nifty/field.py b/nifty/field.py
index 76b50259c..c7f371955 100644
--- a/nifty/field.py
+++ b/nifty/field.py
@@ -20,7 +20,6 @@ from __future__ import division, print_function
from builtins import range
import numpy as np
from . import nifty_utilities as utilities
-from .random import Random
from .domain_tuple import DomainTuple
from functools import reduce
from . import dobj
@@ -184,9 +183,9 @@ class Field(object):
"""
domain = DomainTuple.make(domain)
- generator_function = getattr(Random, random_type)
- return Field(domain=domain, val=generator_function(dtype=dtype,
- shape=domain.shape, **kwargs))
+ return Field(domain=domain,
+ val=dobj.from_random(random_type, dtype=dtype,
+ shape=domain.shape, **kwargs))
# ---Properties---
diff --git a/nifty/spaces/power_space.py b/nifty/spaces/power_space.py
index 01c3543eb..07f2f910c 100644
--- a/nifty/spaces/power_space.py
+++ b/nifty/spaces/power_space.py
@@ -141,7 +141,7 @@ class PowerSpace(Space):
harmonic_partner=self.harmonic_partner,
k_length_array=k_length_array,
binbounds=binbounds)
- temp_rho = dobj.bincount(temp_pindex.ravel())
+ temp_rho = np.bincount(temp_pindex.ravel())
assert not np.any(temp_rho == 0), "empty bins detected"
temp_k_lengths = np.bincount(temp_pindex.ravel(),
weights=k_length_array.ravel()) \
diff --git a/nifty/sugar.py b/nifty/sugar.py
index 6aaefeb0e..d5542282b 100644
--- a/nifty/sugar.py
+++ b/nifty/sugar.py
@@ -17,14 +17,15 @@
# and financially supported by the Studienstiftung des deutschen Volkes.
import numpy as np
-
from . import Space,\
- PowerSpace,\
- Field,\
- ComposedOperator,\
- DiagonalOperator,\
- FFTOperator,\
- sqrt
+ PowerSpace,\
+ Field,\
+ ComposedOperator,\
+ DiagonalOperator,\
+ PowerProjectionOperator,\
+ FFTOperator,\
+ sqrt,\
+ DomainTuple
from . import nifty_utilities as utilities
__all__ = ['power_analyze',
@@ -223,16 +224,16 @@ def create_power_field(domain, power_spectrum, dtype=None):
power_domain = PowerSpace(domain)
fp = Field(power_domain, val=power_spectrum(power_domain.k_lengths),
dtype=dtype)
- f = power_synthesize_special(fp)
+ P = PowerProjectionOperator(domain, power_domain)
+ f = P.adjoint_times(fp)
if not issubclass(fp.dtype.type, np.complexfloating):
f = f.real
- f **= 2
return f
-def create_power_operator(domain, power_spectrum, dtype=None):
+def create_power_operator(domain, power_spectrum, space=None, dtype=None):
""" Creates a diagonal operator with the given power spectrum.
Constructs a diagonal operator that lives over the specified domain.
@@ -241,9 +242,10 @@ def create_power_operator(domain, power_spectrum, dtype=None):
----------
domain : DomainObject
Domain over which the power operator shall live.
- power_spectrum : callable
- A method that implements the square root of a power spectrum as a
- function of k.
+ power_spectrum : callable of Field
+ An object that implements the power spectrum as a function of k.
+ space : int
+ the domain index on which the power operator will work
dtype : type *optional*
dtype that the field holding the power spectrum shall use
(default : None).
@@ -254,8 +256,18 @@ def create_power_operator(domain, power_spectrum, dtype=None):
DiagonalOperator : An operator that implements the given power spectrum.
"""
+ domain = DomainTuple.make(domain)
+ if space is None:
+ if len(domain)!=1:
+ raise ValueError("space keyword must be set")
+ else:
+ space = 0
+ space = int(space)
return DiagonalOperator(
- create_power_field(domain, power_spectrum, dtype).weight(1))
+ create_power_field(domain[space],
+ power_spectrum, dtype).weight(1),
+ domain=domain,
+ spaces=space)
def generate_posterior_sample(mean, covariance):
--
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