unifying interface
same same for same functionality, allow user to specify single integer for convenience
This commit is contained in:
Martin Diehl
parent
53fe11484d
commit
f9e04bc4cb
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@ -4,7 +4,7 @@ import warnings
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import multiprocessing as mp
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from functools import partial
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import typing
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from typing import Union, Optional, TextIO, List, Sequence
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from typing import Union, Optional, TextIO, List, Sequence, Collection
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from pathlib import Path
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import numpy as np
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@ -17,7 +17,7 @@ from . import util
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from . import grid_filters
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from . import Rotation
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from . import Table
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from ._typehints import FloatSequence, IntSequence
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from ._typehints import FloatSequence, IntSequence, IntCollection
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class Grid:
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"""
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@ -907,7 +907,8 @@ class Grid:
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def clean(self,
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stencil: int = 3,
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mutable: IntSequence = None,
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selection: IntCollection = None,
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invert_selection: bool = False,
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periodic: bool = True) -> 'Grid':
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"""
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Smooth grid by selecting most frequent material ID within given stencil at each location.
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@ -916,8 +917,10 @@ class Grid:
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----------
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stencil : int, optional
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Size of smoothing stencil. Defaults to 3.
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mutable : sequence of int, optional
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Material ID that can be altered. Defaults to all.
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selection : int or collection of int, optional
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Material IDs to consider.
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invert_selection : bool, optional
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Consider all material IDs except those in selection. Defaults to False.
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periodic : bool, optional
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Assume grid to be periodic. Defaults to True.
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@ -927,21 +930,23 @@ class Grid:
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Updated grid-based geometry.
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"""
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def mostFrequent(arr: np.ndarray, mutable = None):
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def mostFrequent(arr: np.ndarray, selection: List, invert: bool):
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me = arr[arr.size//2]
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if selection is None or me in mutable:
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unique, inverse = np.unique(arr, return_inverse=True)
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if len(selection) == 0 or np.isin(me,selection,invert=invert):
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unique, inverse = np.unique(arr,return_inverse=True)
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return unique[np.argmax(np.bincount(inverse))]
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else:
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return me
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return Grid(material = ndimage.filters.generic_filter(
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self.material,
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mostFrequent,
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size=(stencil if mutable is None else stencil//2*2+1,)*3,
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mode=('wrap' if periodic else 'nearest'),
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extra_keywords=dict(mutable=mutable),
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).astype(self.material.dtype),
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extra_keywords = dict(selection=util.tbd(selection),invert=invert_selection)
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material = ndimage.filters.generic_filter(
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self.material,
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mostFrequent,
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size=(stencil if selection is None else stencil//2*2+1,)*3,
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mode=('wrap' if periodic else 'nearest'),
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extra_keywords=extra_keywords,
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).astype(self.material.dtype)
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return Grid(material = material,
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size = self.size,
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origin = self.origin,
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comments = self.comments+[util.execution_stamp('Grid','clean')],
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@ -1061,16 +1066,16 @@ class Grid:
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def substitute(self,
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from_material: IntSequence,
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to_material: IntSequence) -> 'Grid':
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from_material: Union[int,IntSequence],
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to_material: Union[int,IntSequence]) -> 'Grid':
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"""
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Substitute material indices.
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Parameters
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----------
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from_material : sequence of int
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from_material : int or sequence of int
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Material indices to be substituted.
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to_material : sequence of int
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to_material : int or sequence of int
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New material indices.
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Returns
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@ -1080,7 +1085,8 @@ class Grid:
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"""
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material = self.material.copy()
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for f,t in zip(from_material,to_material): # ToDo Python 3.10 has strict mode for zip
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for f,t in zip(from_material if isinstance(from_material,(Sequence,np.ndarray)) else [from_material],
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to_material if isinstance(to_material,(Sequence,np.ndarray)) else [to_material]): # ToDo Python 3.10 has strict mode for zip
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material[self.material==f] = t
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return Grid(material = material,
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@ -1115,14 +1121,14 @@ class Grid:
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def vicinity_offset(self,
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vicinity: int = 1,
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offset: int = None,
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trigger: IntSequence = [],
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selection: IntCollection = None,
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invert_selection: bool = False,
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periodic: bool = True) -> 'Grid':
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"""
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Offset material ID of points in the vicinity of xxx.
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Different from themselves (or listed as triggers) within a given (cubic) vicinity,
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i.e. within the region close to a grain/phase boundary.
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ToDo: use include/exclude as in seeds.from_grid
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Parameters
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----------
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@ -1132,9 +1138,10 @@ class Grid:
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offset : int, optional
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Offset (positive or negative) to tag material indices,
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defaults to material.max()+1.
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trigger : sequence of int, optional
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List of material indices that trigger a change.
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Defaults to [], meaning that any different neighbor triggers a change.
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selection : int or collection of int, optional
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Material IDs to that triger xxx.
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invert_selection : bool, optional
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Consider all material IDs except those in selection. Defaults to False.
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periodic : bool, optional
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Assume grid to be periodic. Defaults to True.
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@ -1144,17 +1151,19 @@ class Grid:
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Updated grid-based geometry.
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"""
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def tainted_neighborhood(stencil: np.ndarray, trigger):
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def tainted_neighborhood(stencil: np.ndarray, selection):
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me = stencil[stencil.shape[0]//2]
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return np.any(stencil != me if len(trigger) == 0 else
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np.in1d(stencil,np.array(list(set(trigger) - {me}))))
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return np.any(stencil != me if len(selection) == 0 else
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np.in1d(stencil,np.array(list(set(selection) - {me}))))
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offset_ = np.nanmax(self.material)+1 if offset is None else offset
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selection_ = util.tbd(selection) if not invert_selection else \
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list(set(self.material) - set(util.tbd(selection)))
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mask = ndimage.filters.generic_filter(self.material,
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tainted_neighborhood,
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size=1+2*vicinity,
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mode='wrap' if periodic else 'nearest',
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extra_keywords={'trigger':trigger})
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extra_keywords=dict(selection=selection_))
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return Grid(material = np.where(mask, self.material + offset_,self.material),
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size = self.size,
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@ -1,6 +1,6 @@
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"""Functionality for typehints."""
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from typing import Sequence, Union, Literal, TextIO
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from typing import Sequence, Union, Literal, TextIO, Collection
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from pathlib import Path
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import numpy as np
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@ -8,6 +8,7 @@ import numpy as np
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FloatSequence = Union[np.ndarray,Sequence[float]]
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IntSequence = Union[np.ndarray,Sequence[int]]
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IntCollection = Union[np.ndarray,Collection[int]]
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FileHandle = Union[TextIO, str, Path]
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CrystalFamily = Union[None,Literal['triclinic', 'monoclinic', 'orthorhombic', 'tetragonal', 'hexagonal', 'cubic']]
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CrystalLattice = Union[None,Literal['aP', 'mP', 'mS', 'oP', 'oS', 'oI', 'oF', 'tP', 'tI', 'hP', 'cP', 'cI', 'cF']]
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@ -6,7 +6,8 @@ from typing import Tuple as _Tuple
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from scipy import spatial as _spatial
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import numpy as _np
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from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence, NumpyRngSeed as _NumpyRngSeed
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from ._typehints import FloatSequence as _FloatSequence, IntSequence as _IntSequence, \
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NumpyRngSeed as _NumpyRngSeed, IntCollection as _IntCollection
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from . import util as _util
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from . import grid_filters as _grid_filters
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@ -106,7 +107,7 @@ def from_Poisson_disc(size: _FloatSequence,
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def from_grid(grid,
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selection: _IntSequence = None,
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selection: _IntCollection = None,
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invert_selection: bool = False,
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average: bool = False,
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periodic: bool = True) -> _Tuple[_np.ndarray, _np.ndarray]:
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@ -117,7 +118,7 @@ def from_grid(grid,
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----------
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grid : damask.Grid
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Grid from which the material IDs are used as seeds.
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selection : sequence of int, optional
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selection : int or collection of int, optional
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Material IDs to consider.
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invert_selection : bool, optional
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Consider all material IDs except those in selection. Defaults to False.
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@ -133,8 +134,9 @@ def from_grid(grid,
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"""
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material = grid.material.reshape((-1,1),order='F')
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mask = _np.full(grid.cells.prod(),True,dtype=bool) if selection is None else \
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_np.isin(material,selection,invert=invert_selection).flatten()
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selection_ = _util.tbd(selection)
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mask = _np.full(grid.cells.prod(),True,dtype=bool) if len(selection_) == 0 else \
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_np.isin(material,selection_,invert=invert_selection).flatten()
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coords = _grid_filters.coordinates0_point(grid.cells,grid.size).reshape(-1,3,order='F')
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if not average:
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@ -9,7 +9,7 @@ import re
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import fractions
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from collections import abc
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from functools import reduce
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from typing import Union, Tuple, Iterable, Callable, Dict, List, Any, Literal
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from typing import Union, Tuple, Iterable, Callable, Dict, List, Any, Literal, Collection
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from pathlib import Path
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import numpy as np
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@ -720,7 +720,13 @@ def dict_flatten(d: Dict) -> Dict:
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return new
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def tbd(arg) -> List:
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if arg is None:
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return []
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elif isinstance(arg,(np.ndarray,Collection)):
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return list(arg)
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else:
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return [arg]
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####################################################################################################
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# Classes
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@ -155,7 +155,7 @@ class TestGrid:
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@pytest.mark.parametrize('selection',[None,[1],[1,2,3]])
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@pytest.mark.parametrize('periodic',[True,False])
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def test_clean(self,default,update,ref_path,stencil,selection,periodic):
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current = default.clean(stencil,selection,periodic)
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current = default.clean(stencil,selection,periodic=periodic)
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reference = ref_path/f'clean_{stencil}_{"+".join(map(str,[None] if selection is None else selection))}_{periodic}.vti'
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if update and stencil > 1:
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current.save(reference)
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@ -296,8 +296,8 @@ class TestGrid:
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assert grid_equal(G_1,G_2)
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@pytest.mark.parametrize('trigger',[[1],[]])
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def test_vicinity_offset(self,trigger):
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@pytest.mark.parametrize('selection',[[1],[]])
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def test_vicinity_offset(self,selection):
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offset = np.random.randint(2,4)
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vicinity = np.random.randint(2,4)
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@ -309,17 +309,17 @@ class TestGrid:
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for i in [0,1,2]:
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m2[(np.roll(m,+vicinity,i)-m)!=0] += offset
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m2[(np.roll(m,-vicinity,i)-m)!=0] += offset
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if len(trigger) > 0:
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if len(selection) > 0:
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m2[m==1] = 1
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grid = Grid(m,np.random.rand(3)).vicinity_offset(vicinity,offset,trigger=trigger)
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grid = Grid(m,np.random.rand(3)).vicinity_offset(vicinity,offset,selection=selection)
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assert np.all(m2==grid.material)
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@pytest.mark.parametrize('periodic',[True,False])
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def test_vicinity_offset_invariant(self,default,periodic):
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offset = default.vicinity_offset(trigger=[default.material.max()+1,
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offset = default.vicinity_offset(selection=[default.material.max()+1,
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default.material.min()-1])
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assert np.all(offset.material==default.material)
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