diff --git a/demos/demo_faraday.py b/demos/demo_faraday.py
index ee8037853b1cde41f042de6b77e1699e2f9f1edd..0a9679973a8977cdfc2169bf8d2df72ed6358c78 100644
--- a/demos/demo_faraday.py
+++ b/demos/demo_faraday.py
@@ -48,7 +48,7 @@ about.infos.off()
##-----------------------------------------------------------------------------
# (global) Faraday map
-m = field(hp_space(128), val=np.load("demo_faraday_map.npy"))
+m = field(hp_space(128), val=np.load(os.path.join(get_demo_dir(),"demo_faraday_map.npy")))
##-----------------------------------------------------------------------------
diff --git a/demos/demos_core.py b/demos/demos_core.py
index 664e25a6eb93461d637c5942608d75f8376ca639..e4acb2f44e5e3b2b947233cf4d698f02db91bff8 100644
--- a/demos/demos_core.py
+++ b/demos/demos_core.py
@@ -1,7 +1,7 @@
## NIFTY (Numerical Information Field Theory) has been developed at the
## Max-Planck-Institute for Astrophysics.
##
-## Copyright (C) 2014 Max-Planck-Society
+## Copyright (C) 2015 Max-Planck-Society
##
## Author: Marco Selig
## Project homepage: <http://www.mpa-garching.mpg.de/ift/nifty/>
diff --git a/nifty_core.py b/nifty_core.py
index 044a186b4034ea53dd11f7e22fdfd39acbc63bca..bddfe50f3ad2d6a5923922a552e7ec9f45179149 100644
--- a/nifty_core.py
+++ b/nifty_core.py
@@ -163,7 +163,7 @@ import powerspectrum as gp
pi = 3.1415926535897932384626433832795028841971693993751058209749445923078164062862089986280348253421170679
-__version__ = "0.9.6"
+__version__ = "0.9.7"
##-----------------------------------------------------------------------------
@@ -5954,7 +5954,7 @@ class nested_space(space):
for ii in xrange(len(self.nest)):
reorder += range(lim[ii][0],lim[ii][1])
## permute
- Tx = np.copy(x,order='C')
+ Tx = np.copy(x)
for ii in xrange(len(reorder)):
while(reorder[ii]!=ii):
Tx = np.swapaxes(Tx,ii,reorder[ii])
@@ -9176,7 +9176,7 @@ class diagonal_operator(operator):
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
- def get_random_field(self,domain=None,target=None,**kwargs):
+ def get_random_field(self,domain=None,target=None):
"""
Generates a Gaussian random field with variance equal to the
diagonal.
@@ -9196,8 +9196,6 @@ class diagonal_operator(operator):
Random field.
"""
- if(len(kwargs)): ## TODO: remove **kwargs in future version
- about.warnings.cprint("WARNING: deprecated keyword(s).")
## weight if ...
if(not self.domain.discrete):
diag = self.domain.calc_weight(self.val,power=-1)
@@ -10404,36 +10402,47 @@ class response_operator(operator):
self.sigma = sigma
## check assignment(s)
- if(np.size(self.domain.dim(split=True))==1):
- if(assign is None):
- assign = np.arange(self.domain.dim(split=False),dtype=np.int)
- elif(np.isscalar(assign)):
- assign = np.array([assign],dtype=np.int)
+ if(assign is None):
+ ## 1:1 assignment
+ assignments = self.domain.dim(split=False)
+ self.assign = None
+ elif(np.size(self.domain.dim(split=True))==1):
+ if(np.isscalar(assign)):
+ ## X:1 assignment
+ assignments = 1
if(assign[0]>=self.domain.dim(split=False))or(assign[0]<-self.domain.dim(split=False)):
raise IndexError(about._errors.cstring("ERROR: invalid bounds."))
+ self.assign = [int(assign)]
else:
assign = np.array(assign,dtype=np.int)
+ assignments = len(assign)
if(np.ndim(assign)!=1):
raise ValueError(about._errors.cstring("ERROR: invalid input."))
elif(np.any(assign>=self.domain.dim(split=False)))or(np.any(assign<-self.domain.dim(split=False))):
raise IndexError(about._errors.cstring("ERROR: invalid bounds."))
+ if(assignments==len(np.unique(assign,return_index=False,return_inverse=False))):
+ self.assign = assign.tolist()
+ else:
+ self.assign = assign
else:
- if(assign is None):
- assign = np.array([ii for ii in np.ndindex(tuple(self.domain.dim(split=True)))],dtype=np.int)
- elif(np.isscalar(assign)):
+ if(np.isscalar(assign)):
raise ValueError(about._errors.cstring("ERROR: invalid input."))
else:
assign = np.array(assign,dtype=np.int)
+ assignments = np.size(assign,axis=0)
if(np.ndim(assign)!=2)or(np.size(assign,axis=1)!=np.size(self.domain.dim(split=True))):
raise ValueError(about._errors.cstring("ERROR: invalid input."))
for ii in xrange(np.size(assign,axis=1)):
if(np.any(assign[:,ii]>=self.domain.dim(split=True)[ii]))or(np.any(assign[:,ii]<-self.domain.dim(split=True)[ii])):
raise IndexError(about._errors.cstring("ERROR: invalid bounds."))
- self.assign = assign ## transpose
+ if(assignments==len(np.unique(np.ravel_multi_index(assign.T,self.domain.dim(split=True),mode="raise",order='C'),return_index=False,return_inverse=False))):
+ self.assign = assign.T.tolist()
+ else:
+ self.assign = assign
if(target is None):
## set target
- target = point_space(np.size(self.assign,axis=0),datatype=self.domain.datatype)
+ target = point_space(assignments,datatype=self.domain.datatype)
else:
## check target
if(not isinstance(target,space)):
@@ -10442,8 +10451,8 @@ class response_operator(operator):
raise ValueError(about._errors.cstring("ERROR: continuous codomain.")) ## discrete(!)
elif(np.size(target.dim(split=True))!=1):
raise ValueError(about._errors.cstring("ERROR: structured codomain.")) ## unstructured(!)
- elif(np.size(self.assign,axis=0)!=target.dim(split=False)):
- raise ValueError(about._errors.cstring("ERROR: dimension mismatch ( "+str(np.size(self.assign,axis=0))+" <> "+str(target.dim(split=False))+" )."))
+ elif(assignments!=target.dim(split=False)):
+ raise ValueError(about._errors.cstring("ERROR: dimension mismatch ( "+str(assignments)+" <> "+str(target.dim(split=False))+" )."))
self.target = target
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
@@ -10492,15 +10501,24 @@ class response_operator(operator):
x_ = self.domain.calc_smooth(x.val,sigma=self.sigma)
## mask
x_ *= self.mask
- ## assign
- #return x_[self.assign.T.tolist()]
- return field(self.target,val=x_[self.assign.T.tolist()],target=kwargs.get("target",None))
+ ## assign and return
+ if(self.assign is None):
+ return field(self.target,val=x_,target=kwargs.get("target",None))
+ elif(isinstance(self.assign,list)):
+ return field(self.target,val=x_[self.assign],target=kwargs.get("target",None))
+ else:
+ return field(self.target,val=x_[self.assign.T.tolist()],target=kwargs.get("target",None))
def _adjoint_multiply(self,x,**kwargs): ## > applies the adjoint operator to a given field
x_ = np.zeros(self.domain.dim(split=True),dtype=self.domain.datatype,order='C')
## assign (transposed)
- for ii in xrange(np.size(self.assign,axis=0)):
- x_[np.array([self.assign[ii]]).T.tolist()] += x[ii]
+ if(self.assign is None):
+ x_ = np.copy(x.val.flatten(order='C'))
+ elif(isinstance(self.assign,list)):
+ x_[self.assign] += x.val.flatten(order='C')
+ else:
+ for ii in xrange(np.size(self.assign,axis=0)):
+ x_[np.array([self.assign[ii]]).T.tolist()] += x[ii]
## mask
x_ *= self.mask
## smooth
diff --git a/nifty_explicit.py b/nifty_explicit.py
index 09fe1dae57b137168d014f0d48a25e012cd0070f..36caae3b692aafacbea2f58fcdd72605bf5c96f1 100644
--- a/nifty_explicit.py
+++ b/nifty_explicit.py
@@ -38,20 +38,20 @@
"""
from __future__ import division
-from nifty_core import *
-#from sys import stdout as so
-#import numpy as np
-#import pylab as pl
-#from matplotlib.colors import LogNorm as ln
-#from matplotlib.ticker import LogFormatter as lf
-#from multiprocessing import Pool as mp
-#from multiprocessing import Value as mv
-#from multiprocessing import Array as ma
-#from nifty_core import about, \
-# space, \
-# field, \
-# operator,diagonal_operator,identity,vecvec_operator, \
-# probing
+#from nifty_core import *
+from sys import stdout as so
+import numpy as np
+import pylab as pl
+from matplotlib.colors import LogNorm as ln
+from matplotlib.ticker import LogFormatter as lf
+from multiprocessing import Pool as mp
+from multiprocessing import Value as mv
+from multiprocessing import Array as ma
+from nifty_core import about, \
+ space, \
+ field, \
+ operator,diagonal_operator,identity,vecvec_operator, \
+ probing
##-----------------------------------------------------------------------------
diff --git a/nifty_power.py b/nifty_power.py
index 9c46ab0e364013afef61f9ff6066bc82cf01bafe..1c78439a7b1aa71b4d5e6f41dddd732812801dc3 100644
--- a/nifty_power.py
+++ b/nifty_power.py
@@ -42,12 +42,12 @@
"""
from __future__ import division
from scipy.interpolate import interp1d as ip ## FIXME: conflicts with sphinx's autodoc
-from nifty_core import *
-#import numpy as np
-#from nifty_core import about, \
-# space, \
-# field, \
-# projection_operator
+#from nifty_core import *
+import numpy as np
+from nifty_core import about, \
+ space, \
+ field, \
+ projection_operator
import smoothing as gs
diff --git a/nifty_tools.py b/nifty_tools.py
index 255fec648a57f601ddd5cf7d17bba961e0d31265..39edcea32cab540456cc148fac10bacbf308b9dc 100644
--- a/nifty_tools.py
+++ b/nifty_tools.py
@@ -37,12 +37,12 @@
"""
from __future__ import division
-from nifty_core import *
-#import numpy as np
-#from nifty_core import notification,about, \
-# space, \
-# field, \
-# operator,diagonal_operator
+#from nifty_core import *
+import numpy as np
+from nifty_core import notification,about, \
+ space, \
+ field, \
+ operator,diagonal_operator
##-----------------------------------------------------------------------------