def set_functional(self):
if self.parms == 6:
self._gist_functional_ext = gist_functional_6p_ext
elif self.parms == 5:
self._gist_functional_ext = gist_functional_5p_ext
elif self.parms == 4:
self._gist_functional_ext = gist_functional_4p_ext
else:
parms_error(self.parms, self._parms)
### Note, all arrays which are passed to the functionals (such as
### gist_functional_6p_ext), must be DOUBLE (i.e. 32bit floating
### point type in C). This will not checked within the C routine
### (but should be implemented at some point ...).
if self.pairs:
self._exp_data = pair_difference_ext(self.dg.astype(DOUBLE),
self.pairidx)
self._f = np.zeros(self.N_pairs, dtype=DOUBLE)
self._g = np.zeros((self.N_pairs, self._parms), dtype=DOUBLE)
else:
self._exp_data = np.copy(self.dg.astype(DOUBLE))
self._f = np.zeros(self.N_case, dtype=DOUBLE)
self._g = np.zeros((self.N_case, self._parms), dtype=DOUBLE)
self._gradients = np.zeros((self.N_pos, self.parms), dtype=DOUBLE)
self._calc_data = np.zeros(self.N_pos, dtype=DOUBLE)
self._dx = 0.00000001
def set_step(self):
self.steps = np.zeros(self._parms, dtype=DOUBLE)
self.steps[-1] = 1.0
if self.parms == 6:
self.steps[0] = 1.
self.steps[1] = 2.0
self.steps[2] = 1.
self.steps[3] = 2.0
self.steps[4] = 2.0
elif self.parms == 5:
self.steps[0] = 1.
self.steps[1] = 2.0
self.steps[2] = 2.0
self.steps[3] = 2.0
elif self.parms == 4:
self.steps[0] = 2.0
self.steps[1] = 2.0
self.steps[2] = 2.0
else:
parms_error(self.parms, self._parms)
def set_step(self):
### x[0] = E_aff
### x[1] = e_co
### x[2] = S_aff
### x[3] = s_co
### x[4] = g_co (Rec)
### x[5] = g_co (Cplx)
### x[6] = g_co (Lig)
### x[7] = C_E
### x[8] = C_S
self.steps = np.zeros(self._parms, dtype=DOUBLE)
if not self.pairs:
self.steps[-5] = 2.0
self.steps[-4] = 2.0
self.steps[-3] = 2.0
self.steps[-2] = 1.0
self.steps[-1] = 1.0
if self.parms == 6:
self.steps[0] = 1.
self.steps[1] = 2.0
self.steps[2] = 1.
self.steps[3] = 2.0
elif self.parms == 5:
self.steps[0] = 1.
self.steps[1] = 2.0
self.steps[2] = 2.0
elif self.parms == 4:
self.steps[0] = 2.0
self.steps[1] = 2.0
else:
parms_error(self.parms, self._parms)
def set_bounds(self):
__doc__ = """
Ensures that we don't run out of bounds during MC steps.
"""
### x[0] = E_aff
### x[1] = e_co
### x[2] = S_aff
### x[3] = s_co
### x[4] = g_co (Rec)
### x[5] = g_co (Cplx)
### x[6] = g_co (Lig)
### x[7] = C
self.xmin = np.zeros(self._parms, dtype=DOUBLE)
self.xmax = np.zeros(self._parms, dtype=DOUBLE)
self._restraint_grad = np.zeros(self._parms, dtype=DOUBLE)
self._restraint = 0.
self.kforce_f = np.zeros(self._parms, dtype=DOUBLE)
if self.pairs:
_E = np.min([np.min(self.E_cplx),np.min(self.E_lig)]),\
np.max([np.max(self.E_cplx),np.max(self.E_lig)])
_S = np.min([np.min(self.S_cplx),np.min(self.S_lig)]),\
np.max([np.max(self.S_cplx),np.max(self.S_lig)])
else:
_E = np.min([np.min(self.E_cplx),np.min(self.E),np.min(self.E_lig)]),\
np.max([np.max(self.E_cplx),np.max(self.E),np.max(self.E_lig)])
_S = np.min([np.min(self.S_cplx),np.min(self.S),np.min(self.S_lig)]),\
np.max([np.max(self.S_cplx),np.max(self.S),np.max(self.S_lig)])
if isinstance(self.boundsdict, dict):
if not self.pairs:
self.xmin[-5], self.xmax[-5] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co (Rec)
self.kforce_f[-5] = 10.
self.xmin[-4], self.xmax[-4] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co (Cplx)
self.xmin[-3], self.xmax[-3] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co (Lig)
self.xmin[-2], self.xmax[-2] = self.boundsdict['C'][
0], self.boundsdict['C'][1] ### C_E
self.xmin[-1], self.xmax[-1] = self.boundsdict['C'][
0], self.boundsdict['C'][1] ### C_S
self.kforce_f[-4] = 10.
self.kforce_f[-3] = 10.
self.kforce_f[-2] = 1.
self.kforce_f[-1] = 1.
else:
_g_r = np.min(self.g), np.max(self.g)
_g_c = np.min(self.g_cplx), np.max(self.g_cplx)
_g_l = np.min(self.g_lig), np.max(self.g_lig)
if not self.pairs:
self.xmin[-5], self.xmax[-5] = np.min(_g_r), np.max(
_g_r) ### g_co (Rec)
self.kforce_f[-5] = 10.
self.xmin[-4], self.xmax[-4] = np.min(_g_c), np.max(
_g_c) ### g_co (Cplx)
self.xmin[-3], self.xmax[-3] = np.min(_g_l), np.max(
_g_l) ### g_co (Lig)
self.xmin[-2], self.xmax[-2] = -10., 10. ### C_E
self.xmin[-1], self.xmax[-1] = -10., 10. ### C_S
self.kforce_f[-4] = 10.
self.kforce_f[-3] = 10.
self.kforce_f[-2] = 1.
self.kforce_f[-1] = 1.
if self.parms == 6:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['E'][
0], self.boundsdict['E'][1] ### E_aff
self.xmin[1], self.xmax[1] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[2], self.xmax[2] = self.boundsdict['S'][
0], self.boundsdict['S'][1] ### S_aff
self.xmin[3], self.xmax[3] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
else:
self.xmin[0], self.xmax[0] = -10, 10. ### E_aff
self.xmin[1], self.xmax[1] = _E[0], _E[1] ### e_co
self.xmin[2], self.xmax[2] = -10., 10. ### S_aff
self.xmin[3], self.xmax[3] = _S[0], _S[1] ### s_co
self.kforce_f[0] = 1.
self.kforce_f[1] = 10.
self.kforce_f[2] = 1.
self.kforce_f[3] = 10.
elif self.parms == 5:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['E'][
0], self.boundsdict['E'][1] ### Aff
self.xmin[1], self.xmax[1] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[2], self.xmax[2] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
else:
self.xmin[0], self.xmax[0] = -10, 10. ### Aff
self.xmin[1], self.xmax[1] = _E[0], _E[1] ### e_co
self.xmin[2], self.xmax[2] = _S[0], _S[1] ### s_co
self.kforce_f[0] = 1.
self.kforce_f[1] = 10.
self.kforce_f[2] = 10.
elif self.parms == 4:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[1], self.xmax[1] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
else:
self.xmin[0], self.xmax[0] = _E[0], _E[1] ### e_co
self.xmin[1], self.xmax[1] = _S[0], _S[1] ### s_co
self.kforce_f[0] = 10.
self.kforce_f[1] = 10.
else:
parms_error(self.parms, self._parms)
def set_bounds(self):
__doc__ = """
Ensures that we don't run out of bounds during MC steps.
"""
self.xmin = np.zeros(self._parms, dtype=DOUBLE)
self.xmax = np.zeros(self._parms, dtype=DOUBLE)
self._restraint_grad = np.zeros(self._parms, dtype=DOUBLE)
self._restraint = 0.
self.kforce_f = np.zeros(self._parms, dtype=DOUBLE)
if isinstance(self.boundsdict, dict):
self.xmin[-2], self.xmax[-2] = self.boundsdict['C'][
0], self.boundsdict['C'][1] ### C_E
self.xmin[-1], self.xmax[-1] = self.boundsdict['C'][
0], self.boundsdict['C'][1] ### C_S
else:
self.xmin[-2], self.xmax[-2] = -10., 10. ### C
self.xmin[-1], self.xmax[-1] = -10., 10. ### C
self.kforce_f[-2] = 1.
self.kforce_f[-1] = 1.
if self.parms == 6:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['E'][
0], self.boundsdict['E'][1] ### E_aff
self.xmin[1], self.xmax[1] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[2], self.xmax[2] = self.boundsdict['S'][
0], self.boundsdict['S'][1] ### S_aff
self.xmin[3], self.xmax[3] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
self.xmin[4], self.xmax[4] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co
else:
self.xmin[0], self.xmax[0] = -10, 10. ### E_aff
self.xmin[1], self.xmax[1] = np.min(self.E), np.max(
self.E) ### e_co
self.xmin[2], self.xmax[2] = -10., 10. ### S_aff
self.xmin[3], self.xmax[3] = np.min(self.S), np.max(
self.S) ### s_co
self.xmin[4], self.xmax[4] = 1., np.max(self.g) ### g_co
self.kforce_f[0] = 1.
self.kforce_f[1] = 10.
self.kforce_f[2] = 1.
self.kforce_f[3] = 10.
self.kforce_f[4] = 10.
elif self.parms == 5:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['E'][
0], self.boundsdict['E'][1] ### Aff
self.xmin[1], self.xmax[1] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[2], self.xmax[2] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
self.xmin[3], self.xmax[3] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co
else:
self.xmin[0], self.xmax[0] = -10, 10. ### Aff
self.xmin[1], self.xmax[1] = np.min(self.E), np.max(
self.E) ### e_co
self.xmin[2], self.xmax[2] = np.min(self.S), np.max(
self.S) ### s_co
self.xmin[3], self.xmax[3] = 1., np.max(self.g) ### g_co
self.kforce_f[0] = 1.
self.kforce_f[1] = 10.
self.kforce_f[2] = 10.
self.kforce_f[3] = 10.
elif self.parms == 4:
if isinstance(self.boundsdict, dict):
self.xmin[0], self.xmax[0] = self.boundsdict['e_co'][
0], self.boundsdict['e_co'][1] ### e_co
self.xmin[1], self.xmax[1] = self.boundsdict['s_co'][
0], self.boundsdict['s_co'][1] ### s_co
self.xmin[2], self.xmax[2] = self.boundsdict['g_co'][
0], self.boundsdict['g_co'][1] ### g_co
else:
self.xmin[0], self.xmax[0] = np.min(self.E), np.max(
self.E) ### e_co
self.xmin[1], self.xmax[1] = np.min(self.S), np.max(
self.S) ### s_co
self.xmin[2], self.xmax[2] = 1., np.max(self.g) ### g_co
self.kforce_f[0] = 10.
self.kforce_f[1] = 10.
self.kforce_f[2] = 10.
else:
parms_error(self.parms)