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https://github.com/nwchemgit/nwchem.git
synced 2026-07-21 06:25:21 -04:00
removed merge debris [ci skip]
This commit is contained in:
edoapra
parent
471a9083ad
commit
c9099c8623
1 changed files with 0 additions and 152 deletions
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@ -152,17 +152,10 @@ def quadratic_step(trust, g0, h0):
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if h0 > 0:
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delta2 = -g0/h0
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if abs(delta2) > trust:
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<<<<<<< HEAD
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print(" Step restriction: %f %f " % (delta2, trust))
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delta2 = abs(trust*delta2)/delta2
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else:
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print(" Negative curvature ")
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=======
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print (" Step restriction: %12.5f %12.5f " % (delta2, trust))
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delta2 = abs(trust*delta2)/delta2
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else:
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print (" Negative curvature ")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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delta2 = -abs(trust*g0)/g0
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return delta2
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@ -176,42 +169,25 @@ def linesearch(func, x0, s, lsgrad, eps):
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# bracketed the minimum or gone downhil with enough
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# energy difference to start fitting
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<<<<<<< HEAD
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print(" Line search: step alpha grad hess value")
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print(" ---- --------- -------- -------- ----------------")
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=======
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print (" Line search: step alpha grad hess value")
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print (" ---- --------- -------- -------- ----------------")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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trust = 0.2
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alpha0 = 0.0
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f0 = func(x0)
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<<<<<<< HEAD
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print(" %9.2e %8.1e %16.8f" % (alpha0, lsgrad, f0))
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=======
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print (" %9.2e %8.1e %16.8f" % (alpha0 , lsgrad , f0))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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if lsgrad < 0:
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alpha1 = alpha0 + trust
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else:
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alpha1 = alpha0 - trust
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f1 = func(takestep(x0,s,alpha1))
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<<<<<<< HEAD
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print(" %9.2e %16.8f" % (alpha1, f1))
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while f1 > f0:
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if trust < 0.00125:
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print(" system is too badly conditioned for initial step")
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=======
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print (" %9.2e %16.8f" % \
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(alpha1, f1))
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while f1 > f0:
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if trust < 0.00125:
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print (" system is too badly conditioned for initial step")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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return (alpha0,f0) # Cannot seem to find my way
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trust = trust * 0.5
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if lsgrad < 0:
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@ -219,12 +195,8 @@ def linesearch(func, x0, s, lsgrad, eps):
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else:
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alpha1 = alpha0 - trust
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f1 = func(takestep(x0,s,alpha1))
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<<<<<<< HEAD
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print(" %9.2e %16.8f" % (alpha1, f1))
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=======
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print (" %9.2e %16.8f" % \
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(alpha1, f1))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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g0 = lsgrad
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h0 = (f1-f0-alpha1*g0)/alpha1**2
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@ -244,14 +216,6 @@ def linesearch(func, x0, s, lsgrad, eps):
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if iter == 1:
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f2prev = f2
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<<<<<<< HEAD
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print(" %9.2e %16.8f" % (alpha2, f2))
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# Check for convergence or insufficient precision to proceed further
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if (abs(f0-f1)<(10*eps)) and (abs(f1-f2)<(10*eps)):
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print(" ")
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print(" Insufficient precision ... terminating LS")
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=======
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print (" %9.2e %16.8f" % \
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(alpha2, f2))
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@ -259,20 +223,14 @@ def linesearch(func, x0, s, lsgrad, eps):
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if (abs(f0-f1)<(10*eps)) and (abs(f1-f2)<(10*eps)):
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print (" "),
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print (" Insufficient precision ... terminating LS")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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if (f2-f2prev) > 0:
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# New point is higher than previous worst
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if nbackstep < 3:
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nbackstep = nbackstep + 1
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<<<<<<< HEAD
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print(" ")
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print(" Back stepping due to uphill step")
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=======
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print (" "),
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print (" Back stepping due to uphill step")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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trust = max(0.01,0.2*abs(alpha2 - alpha0)) # Reduce trust radius
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alpha2 = alpha0 + 0.2*(alpha2 - alpha0)
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continue
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@ -292,20 +250,12 @@ def linesearch(func, x0, s, lsgrad, eps):
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alpha1, alpha2, f1, f2 = alpha2, alpha1, f2, f1
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(f0, g0, h0) = quadfit(alpha0, f0, alpha1, f1, alpha2, f2)
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<<<<<<< HEAD
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print(" %4i %9.2e %8.1e %8.1e %16.8f" %(iter, alpha0, g0, h0, f0))
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if (h0>0.0) and (abs(g0) < 0.03*abs(lsgrad)):
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print(" ")
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print(" gradient reduced 30-fold ... terminating LS")
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=======
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print (" %4i %9.2e %8.1e %8.1e %16.8f" % \
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(iter, alpha0, g0, h0, f0))
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if (h0>0.0) and (abs(g0) < 0.03*abs(lsgrad)):
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print (" "),
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print (" gradient reduced 30-fold ... terminating LS")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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# Determine the next step
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@ -313,13 +263,8 @@ def linesearch(func, x0, s, lsgrad, eps):
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alpha2 = alpha0 + delta
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df = g0*delta + 0.5*h0*delta*delta
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if abs(df) < 10.0*eps:
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<<<<<<< HEAD
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print(" ")
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print(" projected energy reduction < 10*eps ... terminating LS")
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=======
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print (" "),
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print (" projected energy reduction < 10*eps ... terminating LS")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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@ -458,11 +403,7 @@ def hessian_update_bfgs(hp, dx, g, gp):
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for j in range(n):
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h[i][j] = h[i][j] + dg[i]*dg[j]/dxdg - hdx[i]*hdx[j]/dxhdx
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else:
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<<<<<<< HEAD
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print(' BFGS not updating dxdg (%e), dgdg (%e), dxhdx (%f), dxdx(%e)' % (dxdg, dgdg, dxhdx, dxdx))
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=======
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print (' BFGS not updating dxdg (%e), dgdg (%e), dxhdx (%f), dxdx(%e)' % (dxdg, dgdg, dxhdx, dxdx))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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return h
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@ -500,27 +441,16 @@ def quasinr(func, guess, tol, eps, printvar=None):
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(value,g,h) = numderiv(func, x, step, eps)
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gmax = max(map(abs,g))
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<<<<<<< HEAD
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print(' ')
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print(' iter gmax value ')
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print(' ---- --------- ----------------')
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print("%4i %9.2e %16.8f" % (iter,gmax,value))
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=======
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print (' ')
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print (' iter gmax value ')
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print (' ---- --------- ----------------')
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print ("%4i %9.2e %16.8f" % (iter,gmax,value))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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if (printvar):
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printvar(x)
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if gmax < tol:
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<<<<<<< HEAD
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print(' Converged!')
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=======
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print (' Converged!')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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if iter == 0:
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@ -532,22 +462,14 @@ def quasinr(func, guess, tol, eps, printvar=None):
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(v,e) = jacobi(hessian)
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emax = max(map(abs,e))
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emin = emax*1e-4 # Control noise in small eigenvalues
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<<<<<<< HEAD
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print('\n Eigenvalues of the Hessian:')
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=======
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print ('\n Eigenvalues of the Hessian:')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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printvector(e)
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# Transform to spectral form, take step, transform back
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gs = mxv(v,g)
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for i in range(n):
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if e[i] < emin:
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<<<<<<< HEAD
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print(' Mode %d: small/negative eigenvalue (%f).' % (i, e[i]))
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=======
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print (' Mode %d: small/negative eigenvalue (%f).' % (i, e[i]))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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s[i] = -gs[i]/emin
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else:
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s[i] = -gs[i]/e[i]
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@ -558,12 +480,8 @@ def quasinr(func, guess, tol, eps, printvar=None):
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for i in range(n):
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trust = max(abs(x[i]),abs(x[i]/sqrt(max(1e-4,abs(hessian[i][i])))))
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if abs(s[i]) > trust:
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<<<<<<< HEAD
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print(' restricting ', i, trust, abs(x[i]), abs(x[i]/sqrt(abs(hessian[i][i]))), s[i])
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=======
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print (' restricting ', i, trust, abs(x[i]), \
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abs(x[i]/sqrt(abs(hessian[i][i]))), s[i])
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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scale = min(scale,trust/abs(s[i]))
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if scale != 1.0:
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for i in range(n):
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@ -572,11 +490,7 @@ def quasinr(func, guess, tol, eps, printvar=None):
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(alpha,value) = linesearch(func, x, s, dot(s,g), eps)
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if alpha == 0.0:
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<<<<<<< HEAD
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print(' Insufficient precision to proceed further')
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=======
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print (' Insufficient precision to proceed further')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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for i in range(n):
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@ -601,15 +515,6 @@ def cgminold(func, dfunc, guess, tol):
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g = dfunc(x)
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gmax = max(map(abs,g))
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<<<<<<< HEAD
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print(' ')
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print(' iter gmax value ')
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print(' ---- --------- ----------------')
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print("%4i %9.2e %16.8f" % (iter,gmax,value))
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if gmax < tol:
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print(' Converged!')
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=======
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print (' ')
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print (' iter gmax value ')
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print (' ---- --------- ----------------')
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@ -617,7 +522,6 @@ def cgminold(func, dfunc, guess, tol):
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if gmax < tol:
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print (' Converged!')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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if (iter == 0) or ((iter%20) == 0):
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@ -658,15 +562,6 @@ def cgmin(func, dfunc, guess, tol, precond=None, reset=None):
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g = dfunc(x)
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gmax = max(map(abs,g))
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<<<<<<< HEAD
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print(' ')
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print(' iter gmax value ')
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print(' ---- --------- ----------------')
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print("%4i %9.2e %16.8f" % (iter,gmax,value))
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if gmax < tol:
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print(' Converged!')
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=======
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print (' ')
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print (' iter gmax value ')
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print (' ---- --------- ----------------')
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@ -674,7 +569,6 @@ def cgmin(func, dfunc, guess, tol, precond=None, reset=None):
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if gmax < tol:
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print (' Converged!')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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if precond:
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@ -742,27 +636,16 @@ def cgmin2(func, guess, tol, eps, printvar=None,reset=None):
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(value,g,hh) = numderiv(func, x, step, eps)
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gmax = max(map(abs,g))
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<<<<<<< HEAD
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print(' ')
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print(' iter gmax value ')
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print(' ---- --------- ----------------')
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print("%4i %9.2e %16.8f" % (iter,gmax,value))
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=======
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print (' ')
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print (' iter gmax value ')
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print (' ---- --------- ----------------')
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print ("%4i %9.2e %16.8f" % (iter,gmax,value))
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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if (printvar):
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printvar(x)
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if gmax < tol:
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<<<<<<< HEAD
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print(' Converged!')
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=======
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print (' Converged!')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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if (iter % reset) == 0:
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@ -793,20 +676,12 @@ def cgmin2(func, guess, tol, eps, printvar=None,reset=None):
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if alpha == 0.0:
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# LS failed, probably due to lack of precision.
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if beta != 0.0:
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<<<<<<< HEAD
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print("LS failed - trying preconditioned steepest descent direction")
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=======
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print ("LS failed - trying preconditioned steepest descent direction")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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for i in range(n):
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s[i] = -g[i]
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(alpha,value) = linesearch(func, x, s, dot(s,g), eps)
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if alpha == 0.0:
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<<<<<<< HEAD
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print(" Insufficient precision to proceed further")
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=======
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print (" Insufficient precision to proceed further")
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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break
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for i in range(n):
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@ -843,24 +718,6 @@ if __name__ == '__main__':
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return sum
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<<<<<<< HEAD
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print('\n\n TESTING QUASI-NR SOLVER \n\n')
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quasinr(f, [1.,0.5,0.3,-0.4], 1e-4, 1e-10)
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print('\n\n TESTING GC WITH NUM. GRAD. AND DIAG. PRECOND.\n\n')
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cgmin2(f, [1.,0.5,0.3,-0.4], 1e-4, 1e-10, reset=20)
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print('\n\n TESTING GC WITH ANAL. GRAD. AND WITHOUT OPTIONAL PRECOND.\n\n')
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cgmin(f, df, [1.,0.5,0.3,-0.4], 1e-4)
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print('\n\n TESTING GC WITH ANAL. GRAD. AND WITH OPTIONAL PRECOND.\n\n')
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cgmin(f, df, [1.,0.5,0.3,-0.4], 1e-4, precond=precond)
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print('\n\n TESTING GC WITH ANAL. GRAD. AND NO PRECOND.\n\n')
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cgminold(f, df, [1.,0.5,0.3,-0.4], 1e-4)
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print('\n\n TESTING JACOBI EIGENSOLVER\n\n')
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=======
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print ('\n\n TESTING QUASI-NR SOLVER \n\n')
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quasinr(f, [1.,0.5,0.3,-0.4], 1e-4, 1e-10)
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@ -877,7 +734,6 @@ if __name__ == '__main__':
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cgminold(f, df, [1.,0.5,0.3,-0.4], 1e-4)
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print ('\n\n TESTING JACOBI EIGENSOLVER\n\n')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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n = 50
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a = zeromatrix(n,n)
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for i in range(n):
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@ -886,11 +742,7 @@ if __name__ == '__main__':
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(v,e)= jacobi(a)
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<<<<<<< HEAD
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print(' eigenvalues')
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=======
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print (' eigenvalues')
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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printvector(e)
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#print ' v '
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#printmatrix(v)
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@ -901,8 +753,4 @@ if __name__ == '__main__':
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err = max(err,abs(ev[i][j] - e[i]*v[i][j]))
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err = err/(n*max(1.0,abs(e[i])))
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if err > 1e-12:
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<<<<<<< HEAD
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print(' Error in eigenvector ', i, err)
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=======
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print (' Error in eigenvector ', i, err)
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>>>>>>> b1a8eff3c66eb281ed1c2ac4f342fd72cd2a7e46
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