Commit cf107b1d authored by Davison's avatar Davison
Browse files

main file for imsrg3

parent b05b46c1
# Main program for IM-SRG(3).
# Author: Jacob Davison
# Date: 07/10/2019
# import packages, libraries, and modules
# libraries
from scipy.integrate import odeint, ode
import numpy as np
import time
import pickle
import tracemalloc
import os, sys
from memory_profiler import profile
import itertools
import random
# user files
# sys.path.append('C:\\Users\\davison\\Research\\exact_diagonalization\\')
from oop_imsrg.hamiltonian import *
from oop_imsrg.occupation_tensors import *
from oop_imsrg.generator import *
from oop_imsrg.flow import *
from oop_imsrg.plot_data import *
# from oop_imsrg.display_memory import *
import oop_imsrg.ci_pairing.cipy_pairing_plus_ph as ci_matrix
def derivative(t, y, hamiltonian, occ_tensors, generator, flow):
"""Defines the derivative to pass into ode object.
(required by scipy.integrate.ode)
t -- points at which to solve for y
y -- in this case, 1D array that contains E, f, G
(additional parameters)
hamiltonian -- Hamiltonian object
occ_tensors -- OccupationTensors object
generator -- Generator object
flow -- Flow object
dy -- next step in flow"""
assert isinstance(hamiltonian, Hamiltonian), "Arg 2 must be Hamiltonian object"
assert isinstance(occ_tensors, OccupationTensors), "Arg 3 must be OccupationTensors object"
assert isinstance(generator, Generator), "Arg 4 must be Generator object"
assert isinstance(flow, Flow), "Arg 5 must be a Flow object"
E, f, G, W = ravel(y, hamiltonian.n_sp_states)
generator.f = f
generator.G = G
generator.W = W
dE, df, dG, dW = flow.flow(generator)
dy = unravel(dE, df, dG, dW)
return dy
# @profile
def unravel(E, f, G, W):
"""Transforms E, f, G and W into a 1D array. Facilitates
compatability with scipy.integrate.ode.
E, f, G, W -- normal-ordered pieces of Hamiltonian
concatenation of tensors peeled into 1D arrays"""
unravel_E = np.reshape(E, -1)
unravel_f = np.reshape(f, -1)
unravel_G = np.reshape(G, -1)
unravel_W = np.reshape(W, -1)
return np.concatenate([unravel_E, unravel_f, unravel_G, unravel_W], axis=0)
# @profile
def ravel(y, bas_len):
"""Transforms 1D array into E, f, G, and W. Facilitates
compatability with scipy.integrate.ode.
y -- 1D data array (output from unravel)
bas_len -- length of single particle basis
E, f, G, W -- normal-ordered pieces of Hamiltonian"""
# bas_len = len(np.append(holes,particles))
ravel_E = np.reshape(y[0], ())
ravel_f = np.reshape(y[1:bas_len**2+1], (bas_len, bas_len))
ravel_G = np.reshape(y[bas_len**2+1:bas_len**2+1+bas_len**4],
(bas_len, bas_len, bas_len, bas_len))
ravel_W = np.reshape(y[bas_len**2+1+bas_len**4:bas_len**2+1+bas_len**4+bas_len**6],
return(ravel_E, ravel_f, ravel_G, ravel_W)
def main3b(n_holes, n_particles, ref=None, d=1.0, g=0.5, pb=0.0):
"""Main method uses scipy.integrate.ode to solve the IMSRG3 flow
start = time.time()
initi = time.time()
if ref == None:
ha = PairingHamiltonian2B(n_holes, n_particles, d=d, g=g, pb=pb)
ref = [1,1,1,1,0,0,0,0] # this is just for printing
ha = PairingHamiltonian2B(n_holes, n_particles, ref=ref, d=d, g=g, pb=pb)
ot = OccupationTensors(ha.sp_basis, ha.reference)
wg = WegnerGenerator3B(ha, ot)
fl = Flow_IMSRG3(ha, ot)
initf = time.time()
print("Initialized objects in {:2.4f} seconds\n".format(initf-initi))
print("""Pairing model IM-SRG flow:
d = {:2.4f}
g = {:2.4f}
pb = {:2.4f}
SP basis size = {:2d}
n_holes = {:2d}
n_particles = {:2d}
ref = {d}""".format(ha.d, ha.g, ha.pb, ha.n_sp_states,
len(ha.holes), len(ha.particles),
d=ref) )
# --- Solve the IM-SRG flow
y0 = unravel(ha.E, ha.f, ha.G, wg.W)
solver = ode(derivative,jac=None)
solver.set_integrator('vode', method='bdf', order=5, nsteps=500)
solver.set_f_params(ha, ot, wg, fl)
solver.set_initial_value(y0, 0.)
sfinal = 50
ds = 0.1
s_vals = []
E_vals = []
iters = 0
convergence = 0
while solver.successful() and solver.t < sfinal:
ys = solver.integrate(sfinal, step=True)
Es, fs, Gs, Ws = ravel(ys, ha.n_sp_states)
iters += 1
# if iters %10 == 0: print("iter: {:>6d} \t scale param: {:0.4f} \t E = {:0.9f}".format(iters, solver.t, Es))
if len(E_vals) > 100 and abs(E_vals[-1] - E_vals[-2]) < 10**-8 and E_vals[-1] != E_vals[0]:
print("---- Energy converged at iter {:>06d} with energy {:1.8f}\n".format(iters,E_vals[-1]))
convergence = 1
if len(E_vals) > 100 and abs(E_vals[-1] - E_vals[-2]) > 1:
print("---- Energy diverged at iter {:>06d} with energy {:3.8f}\n".format(iters,E_vals[-1]))
if iters > 20000:
print("---- Energy diverged at iter {:>06d} with energy {:3.8f}\n".format(iters,E_vals[-1]))
if iters % 1000 == 0:
print('Iteration {:>06d}'.format(iters))
end = time.time()
time_str = "{:2.5f}\n".format(end-start)
del ha, ot, wg, fl, solver, y0, sfinal, ds
return (convergence, iters, d, g, pb, n_holes+n_particles, s_vals, E_vals, time_str)
if __name__ == '__main__':
test = main3b(4,4)
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