def calc_Cv(self, NDOF):
nebins = self.nebins
visits1d = self.visits2d.sum(2)
logn_E = np.zeros(nebins)
for i in range(nebins):
logn_E[i] = wham_utils.logSum(self.logn_Eq[i,:])
return wham_utils.calc_Cv(logn_E, visits1d, self.binenergy, \
NDOF, self.Tlist, self.k_B)
def calc_Cv(self, NDOF):
nebins = self.nebins
visits1d = self.visits2d.sum(2)
logn_E = np.zeros(nebins)
for i in range(nebins):
logn_E[i] = wham_utils.logSum(self.logn_Eq[i,:])
return wham_utils.calc_Cv(logn_E, visits1d, self.binenergy, \
NDOF, self.Tlist, self.k_B)
def calc_Cv(self, NDOF, TRANGE=None, NTEMP=100, use_log_sum=None):
# return self.calc_Cv_new(NDOF, TRANGE, NTEMP)
return wham_utils.calc_Cv(self.logn_E,
self.visits1d,
self.binenergy,
NDOF,
self.Tlist,
self.k_B,
TRANGE,
NTEMP,
use_log_sum=use_log_sum)
def calc_Cv(self, ndof, Tlist=None, ntemp=100):
visits1d = self.visits2d.sum(2)
have_data = np.where(visits1d.sum(0) > 0)[0]
logn_E = scipy.misc.logsumexp(self.logn_Eq, axis=1)
# logn_E = np.zeros(nebins)
# for i in range(nebins):
# logn_E[i] = scipy.misc.logsumexp(self.logn_Eq[i,:])
if Tlist is None:
Tlist = np.linspace(self.Tlist[0], self.Tlist[-1], ntemp)
return wham_utils.calc_Cv(Tlist, self.binenergy, logn_E, ndof, have_data=have_data, k_B=self.k_B)
def calc_Cv(self, ndof, Tlist=None, ntemp=100):
visits1d = self.visits2d.sum(2)
have_data = np.where(visits1d.sum(0) > 0)[0]
logn_E = scipy.misc.logsumexp(self.logn_Eq, axis=1)
# logn_E = np.zeros(nebins)
# for i in range(nebins):
# logn_E[i] = scipy.misc.logsumexp(self.logn_Eq[i,:])
if Tlist is None:
Tlist = np.linspace(self.Tlist[0], self.Tlist[-1], ntemp)
return wham_utils.calc_Cv(Tlist,
self.binenergy,
logn_E,
ndof,
have_data=have_data,
k_B=self.k_B)
def calc_Cv(self, NDOF, TRANGE=None, NTEMP=100, use_log_sum=None):
# return self.calc_Cv_new(NDOF, TRANGE, NTEMP)
return wham_utils.calc_Cv(self.logn_E, self.visits1d, self.binenergy,
NDOF, self.Tlist, self.k_B, TRANGE, NTEMP, use_log_sum=use_log_sum)
