tags 625154 + patch
tags 625154 + pending
thanks
Dear maintainer,
I've prepared an NMU for pyentropy (versioned as 0.4-1.1) and uploaded
it to DELAYED/5. Please feel free to tell me if I should delay it
longer.
--
Jakub Wilk
diffstat for pyentropy_0.4-1 pyentropy_0.4-1.1
pyentropy-0.4/debian/changelog | 8 ++++++++
pyentropy/maxent.py | 14 +++++++-------
2 files changed, 15 insertions(+), 7 deletions(-)
diff -u pyentropy-0.4/debian/changelog pyentropy-0.4/debian/changelog
--- pyentropy-0.4/debian/changelog
+++ pyentropy-0.4/debian/changelog
@@ -1,3 +1,11 @@
+pyentropy (0.4-1.1) unstable; urgency=low
+
+ * Non-maintainer upload.
+ * Use multiplication operator rather then deprecated (and eventually
+ removed) matvec method (closes: #625154).
+
+ -- Jakub Wilk <jw...@debian.org> Mon, 15 Aug 2011 14:45:49 +0200
+
pyentropy (0.4-1) unstable; urgency=low
* New upstream release
only in patch2:
unchanged:
--- pyentropy-0.4.orig/pyentropy/maxent.py
+++ pyentropy-0.4/pyentropy/maxent.py
@@ -354,7 +354,7 @@
if eta_given:
eta_sampled = Pr[:l]
else:
- eta_sampled = Asmall.matvec(Pr[1:])
+ eta_sampled = Asmall * Pr[1:]
if jacobian:
self.optout = opt.fsolve(sf, x0, (Asmall,Bsmall,eta_sampled, l),
@@ -382,13 +382,13 @@
return Psolve
def _solvefunc(self, theta_un, Asmall, Bsmall, eta_sampled, l):
- b = np.exp(Bsmall.matvec(theta_un))
- y = eta_sampled - ( Asmall.matvec(b) / (b.sum()+1) )
+ b = np.exp(Bsmall * theta_un)
+ y = eta_sampled - ( Asmall * b / (b.sum()+1) )
return y
def _jacobian(self, theta, Asmall, Bsmall, eta_sampled, l):
- x = np.exp(Bsmall.matvec(theta))
- p = Asmall.matvec(x)
+ x = np.exp(Bsmall * theta)
+ p = Asmall * x
q = x.sum() + 1
J = np.outer(p,p)
@@ -403,7 +403,7 @@
def _p_from_theta(self, theta):
"""Internal version - stays in dim space (missing p[0])"""
pnorm = lambda p: ( p / (p.sum()+1) )
- return pnorm(np.exp(self.A.T.matvec(theta)))
+ return pnorm(np.exp(self.A.T * theta))
def p_from_theta(self, theta):
"""Return full ``fdim`` p-vector from ``fdim-1`` length theta"""
@@ -425,7 +425,7 @@
def eta_from_p(self, p):
"""Return eta-vector (marginals) from full probability vector"""
- return self.A.matvec(p[1:])
+ return self.A * p[1:]
def inscol(x,h,n):
