def Cv_singles(self,alpha_sets):
"""
returns the single Cvs
"""
CvSingle = np.zeros((self.nsubsets,self.T.size))
for i in xrange(self.nsubsets):
CvSingle[i][:] = compute_alpha_cv_c(self.E, np.array(alpha_sets[i][:]), float(P), self.K, float(self.Tmin), float(self.Tmax), self.nT, float(self.ndof), self.imp, self.live)
#print 'CvSingle ',CvSingle
return np.array(CvSingle)
def jack_Cv_averages(self, alphaJack):
"""
returns the M(=self.nsubsets) Cv Jackknife averages
"""
CvJack = np.zeros((self.nsubsets, self.nT))
for i in xrange(self.nsubsets):
CvJack[i][:] = compute_alpha_cv_c(self.E , np.array(alphaJack[i][:]), float(P), self.K, float(self.Tmin), float(self.Tmax), self.nT, float(self.ndof), self.imp, self.live)
#print 'CvJack ',CvJack
return np.array(CvJack)
def Cv_singles(self, alpha_sets):
"""
returns the single Cvs
"""
CvSingle = np.zeros((self.nsubsets, self.T.size))
for i in xrange(self.nsubsets):
CvSingle[i][:] = compute_alpha_cv_c(self.E,
np.array(alpha_sets[i][:]),
float(P), self.K,
float(self.Tmin),
float(self.Tmax), self.nT,
float(self.ndof), self.imp,
self.live)
#print 'CvSingle ',CvSingle
return np.array(CvSingle)
def jack_Cv_averages(self, alphaJack):
"""
returns the M(=self.nsubsets) Cv Jackknife averages
"""
CvJack = np.zeros((self.nsubsets, self.nT))
for i in xrange(self.nsubsets):
CvJack[i][:] = compute_alpha_cv_c(self.E,
np.array(alphaJack[i][:]),
float(P),
self.K, float(self.Tmin),
float(self.Tmax), self.nT,
float(self.ndof), self.imp,
self.live)
#print 'CvJack ',CvJack
return np.array(CvJack)