Source code for netket.hilbert.homogeneous
# Copyright 2021 The NetKet Authors - All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
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# limitations under the License.
from typing import Optional, List, Callable
from numbers import Real
import numpy as np
from numba import jit
from .discrete_hilbert import DiscreteHilbert
from .hilbert_index import HilbertIndex
@jit(nopython=True)
def _gen_to_bare_numbers(conditions):
return np.nonzero(conditions)[0]
@jit(nopython=True)
def _to_constrained_numbers_kernel(bare_numbers, numbers):
found = np.searchsorted(bare_numbers, numbers)
if np.max(found) >= bare_numbers.shape[0]:
raise RuntimeError("The required state does not satisfy the given constraints.")
return found
class HomogeneousHilbert(DiscreteHilbert):
r"""The Abstract base class for homogeneous hilbert spaces.
This class should only be subclassed and should not be instantiated directly.
"""
[docs] def __init__(
self,
local_states: Optional[List[Real]],
N: int = 1,
constraint_fn: Optional[Callable] = None,
):
r"""
Constructs a new ``HomogeneousHilbert`` given a list of eigenvalues of the
states and a number of sites, or modes, within this hilbert space.
This method should only be called from the subclasses `__init__` method.
Args:
local_states (list or None): Eigenvalues of the states. If the allowed
states are an infinite number, None should be passed as an argument.
N: Number of modes in this hilbert space (default 1).
constraint_fn: A function specifying constraints on the quantum numbers.
Given a batch of quantum numbers it should return a vector of bools
specifying whether those states are valid or not.
"""
assert isinstance(N, int)
self._size = N
self._is_finite = local_states is not None
if self._is_finite:
self._local_states = np.asarray(local_states)
assert self._local_states.ndim == 1
self._local_size = self._local_states.shape[0]
self._local_states = self._local_states.tolist()
self._local_states_frozen = frozenset(self._local_states)
else:
self._local_states = None
self._local_states_frozen = None
self._local_size = np.iinfo(np.intp).max
self._has_constraint = constraint_fn is not None
self._constraint_fn = constraint_fn
self._hilbert_index = None
shape = tuple(self._local_size for _ in range(self.size))
super().__init__(shape=shape)
@property
def size(self) -> int:
r"""The total number number of degrees of freedom."""
return self._size
@property
def local_size(self) -> int:
r"""Size of the local degrees of freedom that make the total hilbert space."""
return self._local_size
[docs] def size_at_index(self, i: int) -> int:
return self.local_size
@property
def local_states(self) -> Optional[List[float]]:
r"""A list of discreet local quantum numbers.
If the local states are infinitely many, None is returned."""
return self._local_states
[docs] def states_at_index(self, i: int):
return self.local_states
@property
def n_states(self) -> int:
r"""The total dimension of the many-body Hilbert space.
Throws an exception iff the space is not indexable."""
hind = self._get_hilbert_index()
if not self._has_constraint:
return hind.n_states
else:
return self._bare_numbers.shape[0]
@property
def is_finite(self) -> bool:
r"""Whether the local hilbert space is finite."""
return self._is_finite
@property
def constrained(self) -> bool:
r"""Returns True if the hilbert space is constrained."""
return self._has_constraint
def _numbers_to_states(self, numbers: np.ndarray, out: np.ndarray) -> np.ndarray:
hind = self._get_hilbert_index()
return hind.numbers_to_states(self._to_bare_numbers(numbers), out)
def _states_to_numbers(self, states, out):
hind = self._get_hilbert_index()
hind.states_to_numbers(states, out)
if self._has_constraint:
out[:] = _to_constrained_numbers_kernel(
self._bare_numbers,
out,
)
return out
def _get_hilbert_index(self):
if self._hilbert_index is None:
if not self.is_indexable:
raise RuntimeError("The hilbert space is too large to be indexed.")
self._hilbert_index = HilbertIndex(
np.asarray(self.local_states, dtype=np.float64), self.size
)
if self._has_constraint:
self._bare_numbers = _gen_to_bare_numbers(
self._constraint_fn(self._hilbert_index.all_states())
)
else:
self._bare_numbers = np.empty(0, dtype=np.intp)
return self._hilbert_index
def _to_bare_numbers(self, numbers):
if self._constraint_fn is None:
return numbers
else:
return self._bare_numbers[numbers]
def __repr__(self):
constr = (
", has_constraint={}".format(self._has_constraint)
if self._has_constraint
else ""
)
clsname = type(self).__name__
return f"{clsname}(local_size={self._local_size}, N={self.size}{constr})"
@property
def _attrs(self):
return (
self.size,
self.local_size,
self._local_states_frozen,
self._has_constraint,
self._constraint_fn,
)