# 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.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Optional, Callable
from numbers import Real
import numpy as np
from .discrete_hilbert import DiscreteHilbert
from .index import HilbertIndex, UnconstrainedHilbertIndex, ConstrainedHilbertIndex
class HomogeneousHilbert(DiscreteHilbert):
r"""The Abstract base class for homogeneous hilbert spaces.
This class should only be subclassed and should not be instantiated directly.
.. note::
To override the logic to index into constrained hilbert spaces, it is
possible to use an informal interface built on top of non-public
indexing classes.
In particular, you can override the following properties and methods:
- Do not specify the :code:`constraint_fn` keyword argument when
calling the init method of this abstract class.
- Override the property :py:attr:`~nk.hilbert.HomogeneousHilbert.constrained`,
to return `True` or `False` depending on your own logic.
- Override the property :py:attr:`~nk.hilbert.HomogeneousHilbert._hilbert_index`
to return an hilbert index object (see the discussion in the source code of
the folder :code:`netket/hilbert/index/__init__.py`).
"""
[docs] def __init__(
self,
local_states: Optional[list[Real]],
N: int = 1,
constraint_fn: Optional[Callable] = None,
):
r"""
Constructs a new :class:`~netket.hilbert.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: 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._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._constraint_fn = constraint_fn
self.__hilbert_index = None
shape = tuple(self._local_size for _ in range(N))
super().__init__(shape=shape)
@property
def size(self) -> int:
r"""The total number number of degrees of freedom."""
return len(self.shape)
@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 discrete 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."""
return self._hilbert_index.n_states
@property
def is_finite(self) -> bool:
r"""Whether the local hilbert space is finite."""
return self._is_finite
@property
def constrained(self) -> bool:
r"""The hilbert space does not contains `prod(hilbert.shape)`
basis states.
Typical constraints are population constraints (such as fixed
number of bosons, fixed magnetization...) which ensure that
only a subset of the total unconstrained space is populated.
Typically, objects defined in the constrained space cannot be
converted to QuTiP or other formats.
"""
return self._constraint_fn is not None
def _numbers_to_states(self, numbers: np.ndarray, out: np.ndarray) -> np.ndarray:
# this is guaranteed
# numbers = concrete_or_error(
# np.asarray, numbers, HilbertIndexingDuringTracingError
# )
return self._hilbert_index.numbers_to_states(numbers, out)
def _states_to_numbers(self, states: np.ndarray, out: np.ndarray):
# guaranteed
# states = concrete_or_error(
# np.asarray, states, HilbertIndexingDuringTracingError
# )
self._hilbert_index.states_to_numbers(states, out)
return out
[docs] def all_states(self, out: Optional[np.ndarray] = None) -> np.ndarray:
r"""Returns all valid states of the Hilbert space.
Throws an exception if the space is not indexable.
Args:
out: an optional pre-allocated output array
Returns:
A (n_states x size) batch of states. this corresponds
to the pre-allocated array if it was passed.
"""
return self._hilbert_index.all_states(out)
@property
def _hilbert_index(self) -> HilbertIndex:
"""
Returns the `HilbertIndex` object, which is a numba jitclass used to convert
integers to states and vice-versa.
"""
if self.__hilbert_index is None:
if not self.is_indexable:
raise RuntimeError("The hilbert space is too large to be indexed.")
if self.constrained:
self.__hilbert_index = ConstrainedHilbertIndex(
np.asarray(self.local_states, dtype=np.float64),
self.size,
self._constraint_fn,
)
else:
self.__hilbert_index = UnconstrainedHilbertIndex(
np.asarray(self.local_states, dtype=np.float64), self.size
)
return self.__hilbert_index
def __repr__(self):
constr = f", constrained={self.constrained}" if self.constrained 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.constrained,
self._constraint_fn,
)
