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cleanup ThermalAFQMC class for only Generic case, by inheriting ZT AF…
…QMC class
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,193 @@ | ||
| """Driver to perform AFQMC calculation""" | ||
| import time | ||
| import uuid | ||
| from ipie.thermal.propagation.utils import get_propagator | ||
| from ipie.thermal.walkers.handler import Walkers | ||
| from ipie.qmc.options import QMCOpts | ||
| from ipie.qmc.utils import set_rng_seed | ||
| from ipie.utils.misc import get_git_info, print_env_info | ||
| from ipie.qmc.afqmc import AFQMC | ||
| from ipie.qmc.options import QMCParams | ||
| from ipie.systems.generic import Generic | ||
| from ipie.utils.mpi import MPIHandler | ||
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| ## This is now only applicable to the Generic case! | ||
| ## See test_generic.py for example. | ||
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| class ThermalAFQMC(AFQMC): | ||
| def __init__( | ||
| self, | ||
| num_elec, | ||
| mu, | ||
| beta, | ||
| hamiltonian, | ||
| trial, | ||
| num_walkers: int = 100, | ||
| seed: int = None, | ||
| num_steps_per_block: int = 25, | ||
| num_blocks: int = 100, | ||
| timestep: float = 0.005, | ||
| stabilize_freq=5, | ||
| pop_control_freq=5, | ||
| verbose=True, | ||
| ): | ||
|
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||
| mpi_handler = MPIHandler() | ||
| comm = mpi_handler.comm | ||
| params = QMCParams( | ||
| num_walkers=num_walkers, | ||
| total_num_walkers=num_walkers * comm.size, | ||
| num_blocks=num_blocks, | ||
| num_steps_per_block=num_steps_per_block, | ||
| timestep=timestep, | ||
| num_stblz=stabilize_freq, | ||
| pop_control_freq=pop_control_freq, | ||
| rng_seed=seed, | ||
| ) | ||
|
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||
| system = Generic(num_elec, verbose) | ||
| system.mu = mu | ||
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| qmc = QMCOpts() # should be removed later after walker is cleaned up | ||
| qmc.nwalkers = num_walkers | ||
| qmc.ntot_walkers = num_walkers * comm.size | ||
| qmc.beta = beta | ||
| qmc.total_steps = num_blocks | ||
| qmc.nsteps = 1 | ||
| qmc.ntime_slices = int(round(beta / timestep)) | ||
| qmc.rng_seed = set_rng_seed(seed, comm) | ||
| qmc.dt = timestep | ||
|
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||
| if comm.rank == 0: | ||
| self.uuid = str(uuid.uuid1()) | ||
| get_sha1 = True | ||
| if get_sha1: | ||
| self.sha1, self.branch, self.local_mods = get_git_info() | ||
| else: | ||
| self.sha1 = "None" | ||
| if verbose: | ||
| self.sys_info = print_env_info( | ||
| self.sha1, self.branch, self.local_mods, self.uuid, comm.size | ||
| ) | ||
|
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| self.qmc = qmc | ||
| self.qmc.nstblz = 10 | ||
| self.qmc.npop_control = 1 | ||
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| wlk_opts = {} # should be removed later after walker is cleaned up | ||
| walkers = Walkers( | ||
| system, | ||
| hamiltonian, | ||
| trial, | ||
| qmc, | ||
| walker_opts=wlk_opts, | ||
| verbose=verbose) | ||
|
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| prop_opts = {} # should be removed later after walker is cleaned up | ||
|
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| propagator = get_propagator( | ||
| prop_opts, | ||
| qmc, | ||
| system, | ||
| hamiltonian, | ||
| trial, | ||
| verbose=verbose | ||
| ) | ||
| self.propagators = propagator | ||
| self.root = True | ||
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| super().__init__(system, hamiltonian, trial, walkers, propagator, params, verbose) | ||
|
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| def run(self, walkers=None, comm=None, verbose=None): | ||
| """Perform AFQMC simulation on state object using open-ended random walk. | ||
| Parameters | ||
| ---------- | ||
| state : :class:`pie.state.State` object | ||
| Model and qmc parameters. | ||
| walk: :class:`pie.walker.Walkers` object | ||
| Initial wavefunction / distribution of walkers. | ||
| comm : MPI communicator | ||
| """ | ||
| if walkers is not None: | ||
| self.walkers = walkers | ||
| self.setup_timers() | ||
| # Calculate estimates for initial distribution of walkers. | ||
| self.estimators.estimators["mixed"].update( | ||
| self.qmc, | ||
| self.system, | ||
| self.hamiltonian, | ||
| self.trial, | ||
| self.walkers, | ||
| 0, | ||
| self.propagators.free_projection, | ||
| ) | ||
| # Print out zeroth step for convenience. | ||
| self.estimators.estimators["mixed"].print_step(comm, comm.size, 0, 1) | ||
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| for step in range(1, self.qmc.total_steps + 1): | ||
| start_path = time.time() | ||
| for ts in range(0, self.qmc.ntime_slices): | ||
| if self.verbosity >= 2 and comm.rank == 0: | ||
| print(" # Timeslice %d of %d." % (ts, self.qmc.ntime_slices)) | ||
| start = time.time() | ||
| for w in self.walkers.walkers: | ||
| self.propagators.propagate_walker(self.hamiltonian, w, ts, 0) | ||
| if (abs(w.weight) > w.total_weight * 0.10) and ts > 0: | ||
| w.weight = w.total_weight * 0.10 | ||
| self.tprop += time.time() - start | ||
| start = time.time() | ||
| if ts % self.qmc.npop_control == 0 and ts != 0: | ||
| self.walkers.pop_control(comm) | ||
| self.tpopc += time.time() - start | ||
| self.tpath += time.time() - start_path | ||
| start = time.time() | ||
| self.estimators.update( | ||
| self.qmc, | ||
| self.system, | ||
| self.hamiltonian, | ||
| self.trial, | ||
| self.walkers, | ||
| step, | ||
| self.propagators.free_projection, | ||
| ) | ||
| self.testim += time.time() - start | ||
| self.estimators.print_step( | ||
| comm, | ||
| comm.size, | ||
| step, | ||
| free_projection=self.propagators.free_projection, | ||
| ) | ||
| self.walkers.reset(self.trial) | ||
|
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| def finalise(self, verbose): | ||
| """Tidy up. | ||
| Parameters | ||
| ---------- | ||
| verbose : bool | ||
| If true print out some information to stdout. | ||
| """ | ||
| pass | ||
|
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| def determine_dtype(self, propagator, system): | ||
| """Determine dtype for trial wavefunction and walkers. | ||
| Parameters | ||
| ---------- | ||
| propagator : dict | ||
| Propagator input options. | ||
| system : object | ||
| System object. | ||
| """ | ||
| hs_type = propagator.get("hubbard_stratonovich", "discrete") | ||
| continuous = "continuous" in hs_type | ||
| twist = system.ktwist.all() is not None | ||
| return continuous or twist | ||
|
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| def setup_timers(self): | ||
| self.tpath = 0 | ||
| self.tprop = 0 | ||
| self.testim = 0 | ||
| self.tpopc = 0 |
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I modified
ThermalAFQMCby letting it inherit the Zero TemperatureAFQMC, for only generic case. But it needs to be further modified once the walker is cleaned up.