Knyazev's cg-like extension of PINVIT
(mata, matm, pre, num=1, maxit=20, initial=None, printrates=True, largest=False)
| 111 | |
| 112 | |
| 113 | def LOBPCG(mata, matm, pre, num=1, maxit=20, initial=None, printrates=True, largest=False): |
| 114 | """Knyazev's cg-like extension of PINVIT""" |
| 115 | import scipy.linalg |
| 116 | |
| 117 | r = mata.CreateRowVector() |
| 118 | |
| 119 | if initial: |
| 120 | num=len(initial) |
| 121 | uvecs = initial |
| 122 | else: |
| 123 | uvecs = MultiVector(r, num) |
| 124 | |
| 125 | vecs = MultiVector(r, 3*num) |
| 126 | for v in vecs: |
| 127 | r.SetRandom() |
| 128 | v.data = pre * r |
| 129 | |
| 130 | if initial: |
| 131 | vecs[0:num] = uvecs |
| 132 | |
| 133 | lams = Vector(num * [1]) |
| 134 | |
| 135 | for i in range(maxit): |
| 136 | uvecs.data = mata * vecs[0:num] - (matm * vecs[0:num]).Scale (lams) |
| 137 | vecs[2*num:3*num] = pre * uvecs |
| 138 | |
| 139 | vecs.Orthogonalize(matm) |
| 140 | |
| 141 | asmall = InnerProduct (vecs, mata * vecs) |
| 142 | msmall = InnerProduct (vecs, matm * vecs) |
| 143 | |
| 144 | ev,evec = scipy.linalg.eigh(a=asmall, b=msmall) |
| 145 | |
| 146 | if not largest: |
| 147 | lams = Vector(ev[0:num]) |
| 148 | if printrates: |
| 149 | print (i, ":", list(lams), flush=True) |
| 150 | |
| 151 | uvecs[:] = vecs * Matrix(evec[:,0:num]) |
| 152 | vecs[num:2*num] = vecs[0:num] |
| 153 | vecs[0:num] = uvecs |
| 154 | else: |
| 155 | lams = Vector(ev[2*num:3*num]) |
| 156 | if printrates: |
| 157 | print (i, ":", list(lams), flush=True) |
| 158 | |
| 159 | uvecs[:] = vecs * Matrix(evec[:,2*num:3*num]) |
| 160 | vecs[num:2*num] = vecs[0:num] |
| 161 | vecs[0:num] = uvecs |
| 162 | |
| 163 | return lams, uvecs |
| 164 | |
| 165 | |
| 166 |
nothing calls this directly
no test coverage detected