def compute_expectations(self):
self.Ew, self.Ewinv = _gap.compute_gig_expectations(
self.a, self.rhow, self.tauw)
self.Ewinvinv = 1. / self.Ewinv
self.Eh, self.Ehinv = _gap.compute_gig_expectations(
self.b, self.rhoh, self.tauh)
self.Ehinvinv = 1. / self.Ehinv
self.Et, self.Etinv = _gap.compute_gig_expectations(
self.alpha / self.K, self.rhot, self.taut)
self.Etinvinv = 1. / self.Etinv
def compute_expectations(self):
self.Ew, self.Ewinv = _gap.compute_gig_expectations(self.a, self.rhow,
self.tauw)
self.Ewinvinv = 1./self.Ewinv
self.Eh, self.Ehinv = _gap.compute_gig_expectations(self.b, self.rhoh,
self.tauh)
self.Ehinvinv = 1./self.Ehinv
self.Et, self.Etinv = _gap.compute_gig_expectations(self.alpha/self.K,
self.rhot,
self.taut)
self.Etinvinv = 1./self.Etinv
def update_theta(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk)**(-1)
self.rhot[goodk] = self.alpha + np.sum(
np.dot(self.Ew[:, goodk].T, xbarinv) * self.Eh[goodk, :], axis=1)
self.taut[goodk] = self.Etinvinv[goodk]**2 * \
np.sum(np.dot(self.Ewinvinv[:, goodk].T, xxtwidinvsq) *
self.Ehinvinv[goodk, :], axis=1)
self.taut[self.taut < 1e-100] = 0
self.Et[goodk], self.Etinv[goodk] = _gap.compute_gig_expectations(
self.alpha / self.K, self.rhot[goodk], self.taut[goodk])
self.Etinvinv[goodk] = 1. / self.Etinv[goodk]
def update_theta(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk) ** (-1)
self.rhot[goodk] = self.alpha + np.sum(np.dot(self.Ew[:, goodk].T,
xbarinv) *
self.Eh[goodk, :], axis=1)
self.taut[goodk] = self.Etinvinv[goodk]**2 * \
np.sum(np.dot(self.Ewinvinv[:, goodk].T, xxtwidinvsq) *
self.Ehinvinv[goodk, :], axis=1)
self.taut[self.taut < 1e-100] = 0
self.Et[goodk], self.Etinv[goodk] = _gap.compute_gig_expectations(
self.alpha/self.K, self.rhot[goodk], self.taut[goodk])
self.Etinvinv[goodk] = 1./self.Etinv[goodk]
def update_w(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk) ** (-1)
dEt = self.Et[goodk]
dEtinvinv = self.Etinvinv[goodk]
self.rhow[:, goodk] = self.a + np.dot(xbarinv, dEt *
self.Eh[goodk, :].T)
self.tauw[:, goodk] = self.Ewinvinv[:, goodk]**2 * \
np.dot(xxtwidinvsq, dEtinvinv * self.Ehinvinv[goodk, :].T)
self.tauw[self.tauw < 1e-100] = 0
self.Ew[:, goodk], self.Ewinv[:, goodk] = _gap.compute_gig_expectations(
self.a, self.rhow[:, goodk], self.tauw[:, goodk])
self.Ewinvinv[:, goodk] = 1./self.Ewinv[:, goodk]
def update_w(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk)**(-1)
dEt = self.Et[goodk]
dEtinvinv = self.Etinvinv[goodk]
self.rhow[:,
goodk] = self.a + np.dot(xbarinv, dEt * self.Eh[goodk, :].T)
self.tauw[:, goodk] = self.Ewinvinv[:, goodk]**2 * \
np.dot(xxtwidinvsq, dEtinvinv * self.Ehinvinv[goodk, :].T)
self.tauw[self.tauw < 1e-100] = 0
self.Ew[:,
goodk], self.Ewinv[:, goodk] = _gap.compute_gig_expectations(
self.a, self.rhow[:, goodk], self.tauw[:, goodk])
self.Ewinvinv[:, goodk] = 1. / self.Ewinv[:, goodk]
def update_h(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk) ** (-1)
dEt = self.Et[goodk]
dEtinvinv = self.Etinvinv[goodk]
self.rhoh[goodk, :] = self.b + np.dot(dEt[:, np.newaxis] *
self.Ew[:, goodk].T, xbarinv)
self.tauh[goodk, :] = self.Ehinvinv[goodk, :]**2 * \
np.dot(dEtinvinv[:, np.newaxis] * self.Ewinvinv[:, goodk].T,
xxtwidinvsq)
self.tauh[self.tauh < 1e-100] = 0
self.Eh[goodk, :], self.Ehinv[goodk, :] = _gap.compute_gig_expectations(
self.b, self.rhoh[goodk, :], self.tauh[goodk, :])
self.Ehinvinv[goodk, :] = 1./self.Ehinv[goodk, :]
def update_h(self):
goodk = self.goodk()
xxtwidinvsq = self.X * self._xtwid(goodk)**(-2)
xbarinv = self._xbar(goodk)**(-1)
dEt = self.Et[goodk]
dEtinvinv = self.Etinvinv[goodk]
self.rhoh[goodk, :] = self.b + np.dot(
dEt[:, np.newaxis] * self.Ew[:, goodk].T, xbarinv)
self.tauh[goodk, :] = self.Ehinvinv[goodk, :]**2 * \
np.dot(dEtinvinv[:, np.newaxis] * self.Ewinvinv[:, goodk].T,
xxtwidinvsq)
self.tauh[self.tauh < 1e-100] = 0
self.Eh[goodk, :], self.Ehinv[
goodk, :] = _gap.compute_gig_expectations(self.b,
self.rhoh[goodk, :],
self.tauh[goodk, :])
self.Ehinvinv[goodk, :] = 1. / self.Ehinv[goodk, :]
