/usr/share/pyshared/openopt/solvers/UkrOpt/interalgT.py is in python-openopt 0.38+svn1589-1.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 | from numpy import isnan, take, any, all, logical_or, logical_and, logical_not, atleast_1d, where, \
asarray, inf, nan, argmin, argsort, tile, searchsorted, isfinite
from bisect import bisect_right
from FuncDesigner.Interval import adjust_lx_WithDiscreteDomain, adjust_ux_WithDiscreteDomain
try:
from bottleneck import nanargmin, nanmin, nanargmax, nanmax
except ImportError:
from numpy import nanmin, nanargmin, nanargmax, nanmax
def r42(o, a):
# n_where_lx_2 = where(y <=-0.5)[0].size
# n_where_ux_2 = where(e >=-0.5)[0].size
# nn = n_where_lx_2 + n_where_ux_2
m, N = o.shape
n = N / 2
o_l, o_u = o[:, :n], o[:, n:]
a_l, a_u = a[:, :n], a[:, n:]
o_m = where(logical_or(o_l < o_u, isnan(o_u)), o_l, o_u)
a_m = where(logical_or(a_l < a_u, isnan(a_l)), a_u, a_l)
o_M = nanmax(o_m, 1)
a_M = nanmin(a_m, 1)
# TODO: make it matrix-vector componentwise
o_M = tile(o_M.reshape(m, 1), (1, 2*n))
ind = o < o_M
if any(ind):
o[ind] = o_M[ind]
a_M = tile(a_M.reshape(m, 1), (1, 2*n))
ind = a > a_M
if any(ind):
a[ind] = a_M[ind]
# n_where_lx_2 = where(y <=-0.5)[0].size
# n_where_ux_2 = where(e >=-0.5)[0].size
# nn2 = n_where_lx_2 + n_where_ux_2
# print nn, nn2
# assert nn == nn2
def adjustDiscreteVarBounds(y, e, p):
n = p.n
# TODO: remove the cycle, use vectorization
for i in p._discreteVarsNumList:
v = p._freeVarsList[i]
adjust_lx_WithDiscreteDomain(y[:, i], v)
adjust_ux_WithDiscreteDomain(e[:, i], v)
ind = any(y>e, 1)
if any(ind):
ind = where(logical_not(ind))[0]
s = ind.size
y = take(y, ind, axis=0, out=y[:s])
e = take(e, ind, axis=0, out=e[:s])
def func7(y, e, o, a, _s, nlhc, residual):
r10 = logical_and(all(isnan(o), 1), all(isnan(a), 1))
if any(r10):
j = where(logical_not(r10))[0]
lj = j.size
y = take(y, j, axis=0, out=y[:lj])
e = take(e, j, axis=0, out=e[:lj])
o = take(o, j, axis=0, out=o[:lj])
a = take(a, j, axis=0, out=a[:lj])
_s = _s[j]
if nlhc is not None:
nlhc = take(nlhc, j, axis=0, out=nlhc[:lj])
if residual is not None:
residual = take(residual, j, axis=0, out=residual[:lj])
return y, e, o, a, _s, nlhc, residual
def func9(an, fo, g, p):
#ind = searchsorted(ar, fo, side='right')
if p.probType in ('NLSP', 'SNLE') and p.maxSolutions != 1:
mino = atleast_1d([node.key for node in an])
ind = mino > 0
if not any(ind):
return an, g
else:
g = nanmin((g, nanmin(mino[ind])))
ind2 = where(logical_not(ind))[0]
#an = take(an, ind2, axis=0, out=an[:ind2.size])
an = asarray(an[ind2])
return an, g
elif p.solver.dataHandling == 'sorted':
#OLD
mino = [node.key for node in an]
ind = bisect_right(mino, fo)
if ind == len(mino):
return an, g
else:
g = nanmin((g, nanmin(atleast_1d(mino[ind]))))
return an[:ind], g
elif p.solver.dataHandling == 'raw':
#NEW
mino = [node.key for node in an]
mino = atleast_1d(mino)
r10 = mino > fo
if not any(r10):
return an, g
else:
ind = where(r10)[0]
g = nanmin((g, nanmin(atleast_1d(mino)[ind])))
an = asarray(an)
ind2 = where(logical_not(r10))[0]
#an = take(an, ind2, axis=0, out=an[:ind2.size])
an = asarray(an[ind2])
return an, g
# NEW 2
# curr_tnlh = [node.tnlh_curr for node in an]
# import warnings
# warnings.warn('! fix g')
return an, g
else:
assert 0, 'incorrect nodes remove approach'
def func5(an, nn, g, p):
m = len(an)
if m <= nn: return an, g
mino = [node.key for node in an]
if nn == 1: # box-bound probs with exact interval analysis
ind = argmin(mino)
assert ind in (0, 1), 'error in interalg engine'
g = nanmin((mino[1-ind], g))
an = atleast_1d([an[ind]])
elif m > nn:
if p.solver.dataHandling == 'raw':
ind = argsort(mino)
th = mino[ind[nn]]
ind2 = where(mino < th)[0]
g = nanmin((th, g))
#an = take(an, ind2, axis=0, out=an[:ind2.size])
an = an[ind2]
else:
g = nanmin((mino[nn], g))
an = an[:nn]
return an, g
def func4(p, y, e, o, a, fo, tnlhf_curr = None):
if fo is None and tnlhf_curr is None: return # used in IP
cs = (y + e)/2
n = y.shape[1]
if tnlhf_curr is not None:
tnlh_modL = tnlhf_curr[:, 0:n]
ind = logical_not(isfinite(tnlh_modL))
else:
s = o[:, 0:n]
ind = logical_or(s > fo, isnan(s)) # TODO: assert isnan(s) is same to isnan(a_modL)
indT = any(ind, 1)
if any(ind):
y[ind] = cs[ind]
# Changes
# ind = logical_and(ind, logical_not(isnan(a[:, n:2*n])))
## ii = len(where(ind)[0])
## if ii != 0: print ii
if p.probType != 'MOP':
a[:, 0:n][ind] = a[:, n:2*n][ind]
o[:, 0:n][ind] = o[:, n:2*n][ind]
if tnlhf_curr is not None:
tnlhf_curr[:, 0:n][ind] = tnlhf_curr[:, n:2*n][ind]
# for arr in arrays:
# if arr is not None:
# arr[:, 0:n][ind] = arr[:, n:2*n][ind]
if tnlhf_curr is not None:
tnlh_modU = tnlhf_curr[:, n:2*n]
ind = logical_not(isfinite(tnlh_modU))
else:
q = o[:, n:2*n]
ind = logical_or(q > fo, isnan(q)) # TODO: assert isnan(q) is same to isnan(a_modU)
indT = logical_or(any(ind, 1), indT)
if any(ind):
# copy is used to prevent y and e being same array, that may be buggy with discret vars
e[ind] = cs[ind].copy()
# Changes
# ind = logical_and(ind, logical_not(isnan(a[:, n:])))
## ii = len(where(ind)[0])
## if ii != 0: print ii
if p.probType != 'MOP':
a[:, n:2*n][ind] = a[:, 0:n][ind]
o[:, n:2*n][ind] = o[:, 0:n][ind]
if tnlhf_curr is not None:
tnlhf_curr[:, n:2*n][ind] = tnlhf_curr[:, 0:n][ind]
# for arr in arrays:
# if arr is not None:
# arr[:, n:2*n][ind] = arr[:, 0:n][ind]
return indT
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