diff --git a/nifty_core.py b/nifty_core.py
index cbaf09919ffb2567299a25bf208cb947f2db1fbd..54d49c2d2e4b372b5e85d32e1dda769840eff8ac 100644
--- a/nifty_core.py
+++ b/nifty_core.py
@@ -484,7 +484,7 @@ class _about(object): ## nifty support class for global settings
"""
## version
- self._version = "0.5.5"
+ self._version = "0.5.7"
## switches and notifications
self._errors = notification(default=True,ccode=notification._code)
@@ -2911,7 +2911,7 @@ class rg_space(space):
return np.real(dot)
elif(self.para[(np.size(self.para)-1)//2]!=2):
## check imaginary part
- if(dot.imag>self.epsilon**2*dot.real):
+ if(np.absolute(dot.imag)>self.epsilon**2*np.absolute(dot.real)):
about.warnings.cprint("WARNING: discarding considerable imaginary part.")
return np.real(dot)
else:
diff --git a/nifty_tools.py b/nifty_tools.py
index 2803b5e9826f97cdb9dc4b19b6c4ca1e194a8872..01ca1f1a101f4514347ac2430608551b1e861576 100644
--- a/nifty_tools.py
+++ b/nifty_tools.py
@@ -253,6 +253,11 @@ class invertible_operator(operator):
x_.weight(power=1,overwrite=True)
return x_
+ ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+ def __repr__(self):
+ return "<nifty.invertible_operator>"
+
##-----------------------------------------------------------------------------
##-----------------------------------------------------------------------------
@@ -540,6 +545,11 @@ class propagator_operator(operator):
## evaluate
return self._debriefing(x,x_,in_codomain)
+ ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+ def __repr__(self):
+ return "<nifty.propagator_operator>"
+
##-----------------------------------------------------------------------------
##=============================================================================
@@ -720,7 +730,6 @@ class conjugate_gradient(object):
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
def _calc_without(self,tol=1E-4,clevel=1,limii=None): ## > runs cg without preconditioner
-
clevel = int(clevel)
if(limii is None):
limii = 10*self.b.domain.dim(split=False)
@@ -743,7 +752,10 @@ class conjugate_gradient(object):
self.note.cprint("\niteration : %08u alpha = NAN\n... dead."%ii)
return self.x,0
self.x += alpha*d
- if(ii%self.reset==0)or(np.signbit(np.real(alpha))):
+ if(np.signbit(np.real(alpha))):
+ about.warnings.cprint("WARNING: positive definiteness of A violated.")
+ r = self.b-self.A(self.x)
+ elif(ii%self.reset==0):
r = self.b-self.A(self.x)
else:
r -= alpha*q
@@ -757,7 +769,7 @@ class conjugate_gradient(object):
if(ii==limii):
self.note.cprint("\n... quit.")
break
- if(gamma==0):
+ elif(gamma==0):
convergence = clevel+1
self.note.cprint(" convergence level : INF\n... done.")
break
@@ -793,6 +805,8 @@ class conjugate_gradient(object):
r = self.b-self.A(self.x)
d = self.W(r)
gamma = r.dot(d)
+ if(gamma==0):
+ return self.x,clevel+1
delta_ = np.absolute(gamma)**(-0.5)
convergence = 0
@@ -804,7 +818,10 @@ class conjugate_gradient(object):
self.note.cprint("\niteration : %08u alpha = NAN\n... dead."%ii)
return self.x,0
self.x += alpha*d ## update
- if(ii%self.reset==0)or(np.signbit(np.real(alpha))):
+ if(np.signbit(np.real(alpha))):
+ about.warnings.cprint("WARNING: positive definiteness of A violated.")
+ r = self.b-self.A(self.x)
+ elif(ii%self.reset==0):
r = self.b-self.A(self.x)
else:
r -= alpha*q
@@ -819,8 +836,8 @@ class conjugate_gradient(object):
if(ii==limii):
self.note.cprint("\n... quit.")
break
- if(gamma==0):
- convergence = clevel
+ elif(gamma==0):
+ convergence = clevel+1
self.note.cprint(" convergence level : INF\n... done.")
break
elif(np.absolute(delta)<tol):
@@ -842,6 +859,11 @@ class conjugate_gradient(object):
return self.x,convergence
+ ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+ def __repr__(self):
+ return "<nifty.conjugate_gradient>"
+
##=============================================================================
@@ -1038,6 +1060,7 @@ class steepest_descent(object):
convergence += 1
self.note.cflush(" convergence level : %u"%convergence)
if(convergence==clevel):
+ convergence += int(ii==clevel)
self.note.cprint("\n... done.")
break
else:
@@ -1056,7 +1079,6 @@ class steepest_descent(object):
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
def _get_alpha(self,E,g,norm,alpha): ## > determines the new alpha
-
while(True):
## Wolfe conditions
wolfe,x_,E_,g_,a = self._check_wolfe(E,g,norm,alpha)
@@ -1071,7 +1093,6 @@ class steepest_descent(object):
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
def _check_wolfe(self,E,g,norm,alpha): ## > checks the Wolfe conditions
-
x_ = self._get_x(g,norm,alpha)
pg = norm
E_,g_ = self.eggs(x_)
@@ -1085,7 +1106,6 @@ class steepest_descent(object):
return True,x_,E_,g_,self.a[2]
# def _check_strong_wolfe(self,E,g,norm,alpha): ## > checks the strong Wolfe conditions
-#
# x_ = self._get_x(g,norm,alpha)
# pg = norm
# E_,g_ = self.eggs(x_)
@@ -1101,8 +1121,12 @@ class steepest_descent(object):
##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
def _get_x(self,g,norm,alpha): ## > updates x
-
return self.x-g*(alpha/norm)
+ ##+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+
+ def __repr__(self):
+ return "<nifty.steepest_descent>"
+
##=============================================================================
diff --git a/setup.py b/setup.py
index c29a79aa9c0593da9388ac36e4571be96056ad9f..db6741fd0f8d6f8a90a6d67796a1d5c985a8a54c 100644
--- a/setup.py
+++ b/setup.py
@@ -23,7 +23,7 @@ from distutils.core import setup
import os
setup(name="nifty",
- version="0.5.5",
+ version="0.6.0",
description="Numerical Information Field Theory",
author="Marco Selig",
author_email="mselig@mpa-garching.mpg.de",