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"""Implements the :class:`PeriodicSet` class representing a periodic set, |
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defined by a motif and unit cell. This models a crystal with a point at the |
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center of each atom. |
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This is the object type yielded by the readers :class:`.io.CifReader` and |
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:class:`.io.CSDReader`. The :class:`PeriodicSet` can be passed as the first argument |
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to :func:`.calculate.AMD` or :func:`.calculate.PDD` to calculate its invariants. |
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""" |
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from typing import Optional |
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import numpy as np |
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class PeriodicSet: |
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"""A periodic set is the mathematical representation of a crystal by putting a |
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single point in the center of every atom. A periodic set is defined by a basis |
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(unit cell) and collection of points (motif) which repeats according to the basis. |
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:class:`PeriodicSet` s are returned by the readers in the :mod:`.io` module. |
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Instances of this object can be passed to :func:`.calculate.AMD` or |
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:func:`.calculate.PDD` to calculate the invariant. |
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""" |
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def __init__( |
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self, |
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motif: np.ndarray, |
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cell: np.ndarray, |
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name: Optional[str] = None, |
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**kwargs): |
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self.motif = motif |
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self.cell = cell |
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self.name = name |
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self.tags = kwargs |
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def __str__(self): |
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m, dims = self.motif.shape |
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return f"PeriodicSet({self.name}: {m} motif points in {dims} dimensions)" |
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def __repr__(self): |
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return f"PeriodicSet(name: {self.name}, cell: {self.cell}, motif: {self.motif}, tags: {self.tags})" |
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# used for debugging, checks if the motif/cell agree point for point |
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# (disregarding order), NOT up to isometry. |
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def __eq__(self, other): |
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if self.cell.shape != other.cell.shape or self.motif.shape != other.motif.shape: |
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return False |
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if not np.allclose(self.cell, other.cell): |
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return False |
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# this is the part that'd be confused by overlapping sites |
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# just checks every motif point in either have a neighbour in the other |
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diffs = np.amax(np.abs(other.motif[:, None] - self.motif), axis=-1) |
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if not np.all((np.amin(diffs, axis=0) <= 1e-6) & (np.amin(diffs, axis=-1) <= 1e-6)): |
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return False |
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shared_tags = set(self.tags.keys()).intersection(set(other.tags.keys())) |
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for tag in shared_tags: |
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if np.isscalar(self.tags[tag]): |
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if self.tags[tag] != other.tags[tag]: |
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return False |
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elif isinstance(self.tags[tag], np.ndarray): |
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if not np.allclose(self.tags[tag], other.tags[tag]): |
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return False |
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elif isinstance(self.tags[tag], list): |
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for i, i_ in zip(self.tags[tag], other.tags[tag]): |
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if i != i_: |
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return False |
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return True |
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def __getattr__(self, attr): |
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if 'tags' not in self.__dict__: |
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self.tags = {} |
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if attr in self.tags: |
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return self.tags[attr] |
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raise AttributeError(f"{self.__class__.__name__} object has no attribute or tag {attr}") |
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def __ne__(self, other): |
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return not self.__eq__(other) |
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dwiddo /
average-minimum-distance
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