util imports need prefix instead of __all__ definition to prevent namespace pollution
This commit is contained in:
d.mentock
parent
b3b14e9104
commit
afbafd1d98
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@ -1,43 +1,25 @@
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"""Miscellaneous helper functionality."""
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import sys
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import datetime
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import os
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import subprocess
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import shlex
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import re
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import signal
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import fractions
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from collections import abc
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from functools import reduce, partial
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from typing import Callable, Union, Iterable, Sequence, Dict, List, Tuple, Literal, Any, Collection, TextIO
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from pathlib import Path
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import sys as _sys
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import datetime as _datetime
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import os as _os
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import subprocess as _subprocess
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import shlex as _shlex
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import re as _re
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import signal as _signal
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import fractions as _fractions
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from collections import abc as _abc
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from functools import reduce as _reduce, partial as _partial
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from typing import Callable as _Callable, Union as _Union, Iterable as _Iterable, Sequence as _Sequence, Dict as _Dict, \
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List as _List, Tuple as _Tuple, Literal as _Literal, Any as _Any, Collection as _Collection, TextIO as _TextIO
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from pathlib import Path as _Path
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import numpy as np
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import h5py
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import numpy as _np
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import h5py as _h5py
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from . import version
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from ._typehints import FloatSequence, NumpyRngSeed, IntCollection, FileHandle
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# limit visibility
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__all__=[
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'srepr',
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'emph', 'deemph', 'warn', 'strikeout',
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'run',
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'open_text',
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'natural_sort',
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'show_progress',
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'scale_to_coprime',
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'project_equal_angle', 'project_equal_area',
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'hybrid_IA',
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'execution_stamp',
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'shapeshifter', 'shapeblender',
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'extend_docstring', 'extended_docstring',
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'Bravais_to_Miller', 'Miller_to_Bravais',
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'DREAM3D_base_group', 'DREAM3D_cell_data_group',
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'dict_prune', 'dict_flatten',
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'tail_repack',
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]
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from . import version as _version
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from ._typehints import FloatSequence as _FloatSequence, NumpyRngSeed as _NumpyRngSeed, IntCollection as _IntCollection, \
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FileHandle as _FileHandle
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# https://svn.blender.org/svnroot/bf-blender/trunk/blender/build_files/scons/tools/bcolors.py
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# https://stackoverflow.com/questions/287871
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@ -154,8 +136,8 @@ def strikeout(msg) -> str:
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def run(cmd: str,
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wd: str = './',
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env: Dict[str, str] = None,
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timeout: int = None) -> Tuple[str, str]:
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env: _Dict[str, str] = None,
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timeout: int = None) -> _Tuple[str, str]:
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"""
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Run a command.
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@ -178,26 +160,26 @@ def run(cmd: str,
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"""
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def pass_signal(sig,_,proc,default):
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proc.send_signal(sig)
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signal.signal(sig,default)
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signal.raise_signal(sig)
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_signal.signal(sig,default)
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_signal.raise_signal(sig)
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signals = [signal.SIGINT,signal.SIGTERM]
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signals = [_signal.SIGINT,_signal.SIGTERM]
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print(f"running '{cmd}' in '{wd}'")
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process = subprocess.Popen(shlex.split(cmd),
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stdout = subprocess.PIPE,
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stderr = subprocess.PIPE,
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env = os.environ if env is None else env,
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process = _subprocess.Popen(_shlex.split(cmd),
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stdout = _subprocess.PIPE,
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stderr = _subprocess.PIPE,
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env = _os.environ if env is None else env,
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cwd = wd,
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encoding = 'utf-8')
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# ensure that process is terminated (https://stackoverflow.com/questions/22916783)
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sig_states = [signal.signal(sig,partial(pass_signal,proc=process,default=signal.getsignal(sig))) for sig in signals]
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sig_states = [_signal.signal(sig,_partial(pass_signal,proc=process,default=_signal.getsignal(sig))) for sig in signals]
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try:
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stdout,stderr = process.communicate(timeout=timeout)
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finally:
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for sig,state in zip(signals,sig_states):
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signal.signal(sig,state)
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_signal.signal(sig,state)
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if process.returncode != 0:
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print(stdout)
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@ -207,8 +189,8 @@ def run(cmd: str,
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return stdout, stderr
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def open_text(fname: FileHandle,
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mode: Literal['r','w'] = 'r') -> TextIO:
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def open_text(fname: _FileHandle,
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mode: _Literal['r','w'] = 'r') -> _TextIO:
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"""
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Open a text file.
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@ -224,11 +206,11 @@ def open_text(fname: FileHandle,
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f : file handle
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"""
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return fname if not isinstance(fname, (str,Path)) else \
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open(Path(fname).expanduser(),mode,newline=('\n' if mode == 'w' else None))
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return fname if not isinstance(fname, (str,_Path)) else \
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open(_Path(fname).expanduser(),mode,newline=('\n' if mode == 'w' else None))
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def natural_sort(key: str) -> List[Union[int, str]]:
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def natural_sort(key: str) -> _List[_Union[int, str]]:
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"""
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Natural sort.
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@ -240,13 +222,13 @@ def natural_sort(key: str) -> List[Union[int, str]]:
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"""
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convert = lambda text: int(text) if text.isdigit() else text
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return [ convert(c) for c in re.split('([0-9]+)', key) ]
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return [ convert(c) for c in _re.split('([0-9]+)', key) ]
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def show_progress(iterable: Iterable,
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def show_progress(iterable: _Iterable,
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N_iter: int = None,
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prefix: str = '',
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bar_length: int = 50) -> Any:
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bar_length: int = 50) -> _Any:
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"""
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Decorate a loop with a progress bar.
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@ -264,7 +246,7 @@ def show_progress(iterable: Iterable,
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Length of progress bar in characters. Defaults to 50.
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"""
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if isinstance(iterable,abc.Sequence):
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if isinstance(iterable,_abc.Sequence):
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if N_iter is None:
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N = len(iterable)
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else:
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@ -285,7 +267,7 @@ def show_progress(iterable: Iterable,
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status.update(i)
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def scale_to_coprime(v: FloatSequence) -> np.ndarray:
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def scale_to_coprime(v: _FloatSequence) -> _np.ndarray:
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"""
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Scale vector to co-prime (relatively prime) integers.
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@ -304,30 +286,30 @@ def scale_to_coprime(v: FloatSequence) -> np.ndarray:
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def get_square_denominator(x):
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"""Denominator of the square of a number."""
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return fractions.Fraction(x ** 2).limit_denominator(MAX_DENOMINATOR).denominator
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return _fractions.Fraction(x ** 2).limit_denominator(MAX_DENOMINATOR).denominator
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def lcm(a,b):
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"""Least common multiple."""
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try:
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return np.lcm(a,b) # numpy > 1.18
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return _np.lcm(a,b) # numpy > 1.18
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except AttributeError:
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return a * b // np.gcd(a, b)
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return a * b // _np.gcd(a, b)
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v_ = np.array(v)
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m = (v_ * reduce(lcm, map(lambda x: int(get_square_denominator(x)),v_))**0.5).astype(np.int64)
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m = m//reduce(np.gcd,m)
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v_ = _np.array(v)
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m = (v_ * _reduce(lcm, map(lambda x: int(get_square_denominator(x)),v_))**0.5).astype(_np.int64)
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m = m//_reduce(_np.gcd,m)
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with np.errstate(invalid='ignore'):
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if not np.allclose(np.ma.masked_invalid(v_/m),v_[np.argmax(abs(v_))]/m[np.argmax(abs(v_))]):
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with _np.errstate(invalid='ignore'):
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if not _np.allclose(_np.ma.masked_invalid(v_/m),v_[_np.argmax(abs(v_))]/m[_np.argmax(abs(v_))]):
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raise ValueError(f'invalid result "{m}" for input "{v_}"')
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return m
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def project_equal_angle(vector: np.ndarray,
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direction: Literal['x', 'y', 'z'] = 'z',
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def project_equal_angle(vector: _np.ndarray,
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direction: _Literal['x', 'y', 'z'] = 'z',
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normalize: bool = True,
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keepdims: bool = False) -> np.ndarray:
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keepdims: bool = False) -> _np.ndarray:
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"""
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Apply equal-angle projection to vector.
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@ -367,15 +349,15 @@ def project_equal_angle(vector: np.ndarray,
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"""
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shift = 'zyx'.index(direction)
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v = np.roll(vector/np.linalg.norm(vector,axis=-1,keepdims=True) if normalize else vector,
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v = _np.roll(vector/_np.linalg.norm(vector,axis=-1,keepdims=True) if normalize else vector,
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shift,axis=-1)
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return np.roll(np.block([v[...,:2]/(1.0+np.abs(v[...,2:3])),np.zeros_like(v[...,2:3])]),
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return _np.roll(_np.block([v[...,:2]/(1.0+_np.abs(v[...,2:3])),_np.zeros_like(v[...,2:3])]),
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-shift if keepdims else 0,axis=-1)[...,:3 if keepdims else 2]
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def project_equal_area(vector: np.ndarray,
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direction: Literal['x', 'y', 'z'] = 'z',
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def project_equal_area(vector: _np.ndarray,
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direction: _Literal['x', 'y', 'z'] = 'z',
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normalize: bool = True,
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keepdims: bool = False) -> np.ndarray:
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keepdims: bool = False) -> _np.ndarray:
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"""
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Apply equal-area projection to vector.
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@ -416,22 +398,22 @@ def project_equal_area(vector: np.ndarray,
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"""
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shift = 'zyx'.index(direction)
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v = np.roll(vector/np.linalg.norm(vector,axis=-1,keepdims=True) if normalize else vector,
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v = _np.roll(vector/_np.linalg.norm(vector,axis=-1,keepdims=True) if normalize else vector,
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shift,axis=-1)
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return np.roll(np.block([v[...,:2]/np.sqrt(1.0+np.abs(v[...,2:3])),np.zeros_like(v[...,2:3])]),
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return _np.roll(_np.block([v[...,:2]/_np.sqrt(1.0+_np.abs(v[...,2:3])),_np.zeros_like(v[...,2:3])]),
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-shift if keepdims else 0,axis=-1)[...,:3 if keepdims else 2]
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def execution_stamp(class_name: str,
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function_name: str = None) -> str:
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"""Timestamp the execution of a (function within a) class."""
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now = datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S%z')
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now = _datetime.datetime.now().astimezone().strftime('%Y-%m-%d %H:%M:%S%z')
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_function_name = '' if function_name is None else f'.{function_name}'
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return f'damask.{class_name}{_function_name} v{version} ({now})'
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return f'damask.{class_name}{_function_name} v{_version} ({now})'
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def hybrid_IA(dist: np.ndarray,
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def hybrid_IA(dist: _np.ndarray,
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N: int,
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rng_seed: NumpyRngSeed = None) -> np.ndarray:
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rng_seed: _NumpyRngSeed = None) -> _np.ndarray:
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"""
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Hybrid integer approximation.
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@ -446,23 +428,23 @@ def hybrid_IA(dist: np.ndarray,
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If None, then fresh, unpredictable entropy will be pulled from the OS.
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"""
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N_opt_samples,N_inv_samples = (max(np.count_nonzero(dist),N),0) # random subsampling if too little samples requested
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N_opt_samples,N_inv_samples = (max(_np.count_nonzero(dist),N),0) # random subsampling if too little samples requested
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scale_,scale,inc_factor = (0.0,float(N_opt_samples),1.0)
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while (not np.isclose(scale, scale_)) and (N_inv_samples != N_opt_samples):
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repeats = np.rint(scale*dist).astype(np.int64)
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N_inv_samples = np.sum(repeats)
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while (not _np.isclose(scale, scale_)) and (N_inv_samples != N_opt_samples):
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repeats = _np.rint(scale*dist).astype(_np.int64)
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N_inv_samples = _np.sum(repeats)
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scale_,scale,inc_factor = (scale,scale+inc_factor*0.5*(scale - scale_), inc_factor*2.0) \
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if N_inv_samples < N_opt_samples else \
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(scale_,0.5*(scale_ + scale), 1.0)
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return np.repeat(np.arange(len(dist)),repeats)[np.random.default_rng(rng_seed).permutation(N_inv_samples)[:N]]
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return _np.repeat(_np.arange(len(dist)),repeats)[_np.random.default_rng(rng_seed).permutation(N_inv_samples)[:N]]
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def shapeshifter(fro: Tuple[int, ...],
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to: Tuple[int, ...],
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mode: Literal['left','right'] = 'left',
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keep_ones: bool = False) -> Tuple[int, ...]:
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def shapeshifter(fro: _Tuple[int, ...],
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to: _Tuple[int, ...],
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mode: _Literal['left','right'] = 'left',
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keep_ones: bool = False) -> _Tuple[int, ...]:
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"""
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Return dimensions that reshape 'fro' to become broadcastable to 'to'.
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@ -509,7 +491,7 @@ def shapeshifter(fro: Tuple[int, ...],
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fro = (1,) if len(fro) == 0 else fro
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to = (1,) if len(to) == 0 else to
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try:
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match = re.match(beg[mode]
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match = _re.match(beg[mode]
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+f',{sep[mode]}'.join(map(lambda x: f'{x}'
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if x>1 or (keep_ones and len(fro)>1) else
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'\\d+',fro))
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@ -518,14 +500,14 @@ def shapeshifter(fro: Tuple[int, ...],
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grp = match.groups()
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except AssertionError:
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raise ValueError(f'shapes cannot be shifted {fro} --> {to}')
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fill: Any = ()
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fill: _Any = ()
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for g,d in zip(grp,fro+(None,)):
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fill += (1,)*g.count(',')+(d,)
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return fill[:-1]
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def shapeblender(a: Tuple[int, ...],
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b: Tuple[int, ...]) -> Tuple[int, ...]:
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def shapeblender(a: _Tuple[int, ...],
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b: _Tuple[int, ...]) -> _Tuple[int, ...]:
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"""
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Return a shape that overlaps the rightmost entries of 'a' with the leftmost of 'b'.
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@ -553,7 +535,7 @@ def shapeblender(a: Tuple[int, ...],
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return a + b[i:]
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def extend_docstring(extra_docstring: str) -> Callable:
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def extend_docstring(extra_docstring: str) -> _Callable:
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"""
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Decorator: Append to function's docstring.
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@ -569,8 +551,8 @@ def extend_docstring(extra_docstring: str) -> Callable:
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return _decorator
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def extended_docstring(f: Callable,
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extra_docstring: str) -> Callable:
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def extended_docstring(f: _Callable,
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extra_docstring: str) -> _Callable:
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"""
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Decorator: Combine another function's docstring with a given docstring.
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@ -588,7 +570,7 @@ def extended_docstring(f: Callable,
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return _decorator
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def DREAM3D_base_group(fname: Union[str, Path]) -> str:
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def DREAM3D_base_group(fname: _Union[str, _Path]) -> str:
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"""
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Determine the base group of a DREAM.3D file.
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@ -606,7 +588,7 @@ def DREAM3D_base_group(fname: Union[str, Path]) -> str:
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Path to the base group.
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"""
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with h5py.File(Path(fname).expanduser(),'r') as f:
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with _h5py.File(_Path(fname).expanduser(),'r') as f:
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base_group = f.visit(lambda path: path.rsplit('/',2)[0] if '_SIMPL_GEOMETRY/SPACING' in path else None)
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if base_group is None:
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@ -614,7 +596,7 @@ def DREAM3D_base_group(fname: Union[str, Path]) -> str:
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return base_group
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def DREAM3D_cell_data_group(fname: Union[str, Path]) -> str:
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def DREAM3D_cell_data_group(fname: _Union[str, _Path]) -> str:
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"""
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Determine the cell data group of a DREAM.3D file.
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@ -634,10 +616,10 @@ def DREAM3D_cell_data_group(fname: Union[str, Path]) -> str:
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"""
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base_group = DREAM3D_base_group(fname)
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with h5py.File(Path(fname).expanduser(),'r') as f:
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with _h5py.File(_Path(fname).expanduser(),'r') as f:
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cells = tuple(f['/'.join([base_group,'_SIMPL_GEOMETRY','DIMENSIONS'])][()][::-1])
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cell_data_group = f[base_group].visititems(lambda path,obj: path.split('/')[0] \
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if isinstance(obj,h5py._hl.dataset.Dataset) and np.shape(obj)[:-1] == cells \
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if isinstance(obj,_h5py._hl.dataset.Dataset) and _np.shape(obj)[:-1] == cells \
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else None)
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if cell_data_group is None:
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@ -647,8 +629,8 @@ def DREAM3D_cell_data_group(fname: Union[str, Path]) -> str:
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def Bravais_to_Miller(*,
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uvtw: np.ndarray = None,
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hkil: np.ndarray = None) -> np.ndarray:
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uvtw: _np.ndarray = None,
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hkil: _np.ndarray = None) -> _np.ndarray:
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"""
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Transform 4 Miller–Bravais indices to 3 Miller indices of crystal direction [uvw] or plane normal (hkl).
|
||||
|
||||
|
|
@ -665,19 +647,19 @@ def Bravais_to_Miller(*,
|
|||
"""
|
||||
if (uvtw is not None) ^ (hkil is None):
|
||||
raise KeyError('specify either "uvtw" or "hkil"')
|
||||
axis,basis = (np.array(uvtw),np.array([[1,0,-1,0],
|
||||
axis,basis = (_np.array(uvtw),_np.array([[1,0,-1,0],
|
||||
[0,1,-1,0],
|
||||
[0,0, 0,1]])) \
|
||||
if hkil is None else \
|
||||
(np.array(hkil),np.array([[1,0,0,0],
|
||||
(_np.array(hkil),_np.array([[1,0,0,0],
|
||||
[0,1,0,0],
|
||||
[0,0,0,1]]))
|
||||
return np.einsum('il,...l',basis,axis)
|
||||
return _np.einsum('il,...l',basis,axis)
|
||||
|
||||
|
||||
def Miller_to_Bravais(*,
|
||||
uvw: np.ndarray = None,
|
||||
hkl: np.ndarray = None) -> np.ndarray:
|
||||
uvw: _np.ndarray = None,
|
||||
hkl: _np.ndarray = None) -> _np.ndarray:
|
||||
"""
|
||||
Transform 3 Miller indices to 4 Miller–Bravais indices of crystal direction [uvtw] or plane normal (hkil).
|
||||
|
||||
|
|
@ -694,19 +676,19 @@ def Miller_to_Bravais(*,
|
|||
"""
|
||||
if (uvw is not None) ^ (hkl is None):
|
||||
raise KeyError('specify either "uvw" or "hkl"')
|
||||
axis,basis = (np.array(uvw),np.array([[ 2,-1, 0],
|
||||
axis,basis = (_np.array(uvw),_np.array([[ 2,-1, 0],
|
||||
[-1, 2, 0],
|
||||
[-1,-1, 0],
|
||||
[ 0, 0, 3]])/3) \
|
||||
if hkl is None else \
|
||||
(np.array(hkl),np.array([[ 1, 0, 0],
|
||||
(_np.array(hkl),_np.array([[ 1, 0, 0],
|
||||
[ 0, 1, 0],
|
||||
[-1,-1, 0],
|
||||
[ 0, 0, 1]]))
|
||||
return np.einsum('il,...l',basis,axis)
|
||||
return _np.einsum('il,...l',basis,axis)
|
||||
|
||||
|
||||
def dict_prune(d: Dict) -> Dict:
|
||||
def dict_prune(d: _Dict) -> _Dict:
|
||||
"""
|
||||
Recursively remove empty dictionaries.
|
||||
|
||||
|
|
@ -732,7 +714,7 @@ def dict_prune(d: Dict) -> Dict:
|
|||
return new
|
||||
|
||||
|
||||
def dict_flatten(d: Dict) -> Dict:
|
||||
def dict_flatten(d: _Dict) -> _Dict:
|
||||
"""
|
||||
Recursively remove keys of single-entry dictionaries.
|
||||
|
||||
|
|
@ -756,8 +738,8 @@ def dict_flatten(d: Dict) -> Dict:
|
|||
return new
|
||||
|
||||
|
||||
def tail_repack(extended: Union[str, Sequence[str]],
|
||||
existing: List[str] = []) -> List[str]:
|
||||
def tail_repack(extended: _Union[str, _Sequence[str]],
|
||||
existing: _List[str] = []) -> _List[str]:
|
||||
"""
|
||||
Repack tailing characters into single string if all are new.
|
||||
|
||||
|
|
@ -782,11 +764,11 @@ def tail_repack(extended: Union[str, Sequence[str]],
|
|||
|
||||
"""
|
||||
return [extended] if isinstance(extended,str) else existing + \
|
||||
([''.join(extended[len(existing):])] if np.prod([len(i) for i in extended[len(existing):]]) == 1 else
|
||||
([''.join(extended[len(existing):])] if _np.prod([len(i) for i in extended[len(existing):]]) == 1 else
|
||||
list(extended[len(existing):]))
|
||||
|
||||
|
||||
def aslist(arg: Union[IntCollection,int,None]) -> List:
|
||||
def aslist(arg: _Union[_IntCollection, int, None]) -> _List:
|
||||
"""
|
||||
Transform argument to list.
|
||||
|
||||
|
|
@ -801,7 +783,7 @@ def aslist(arg: Union[IntCollection,int,None]) -> List:
|
|||
Entity transformed into list.
|
||||
|
||||
"""
|
||||
return [] if arg is None else list(arg) if isinstance(arg,(np.ndarray,Collection)) else [arg]
|
||||
return [] if arg is None else list(arg) if isinstance(arg,(_np.ndarray,_Collection)) else [arg]
|
||||
|
||||
|
||||
####################################################################################################
|
||||
|
|
@ -834,11 +816,11 @@ class ProgressBar:
|
|||
self.total = total
|
||||
self.prefix = prefix
|
||||
self.bar_length = bar_length
|
||||
self.time_start = self.time_last_update = datetime.datetime.now()
|
||||
self.time_start = self.time_last_update = _datetime.datetime.now()
|
||||
self.fraction_last = 0.0
|
||||
|
||||
sys.stderr.write(f"{self.prefix} {'░'*self.bar_length} 0% ETA n/a")
|
||||
sys.stderr.flush()
|
||||
_sys.stderr.write(f"{self.prefix} {'░'*self.bar_length} 0% ETA n/a")
|
||||
_sys.stderr.flush()
|
||||
|
||||
def update(self,
|
||||
iteration: int) -> None:
|
||||
|
|
@ -846,17 +828,17 @@ class ProgressBar:
|
|||
fraction = (iteration+1) / self.total
|
||||
|
||||
if (filled_length := int(self.bar_length * fraction)) > int(self.bar_length * self.fraction_last) or \
|
||||
datetime.datetime.now() - self.time_last_update > datetime.timedelta(seconds=10):
|
||||
self.time_last_update = datetime.datetime.now()
|
||||
_datetime.datetime.now() - self.time_last_update > _datetime.timedelta(seconds=10):
|
||||
self.time_last_update = _datetime.datetime.now()
|
||||
bar = '█' * filled_length + '░' * (self.bar_length - filled_length)
|
||||
remaining_time = (datetime.datetime.now() - self.time_start) \
|
||||
remaining_time = (_datetime.datetime.now() - self.time_start) \
|
||||
* (self.total - (iteration+1)) / (iteration+1)
|
||||
remaining_time -= datetime.timedelta(microseconds=remaining_time.microseconds) # remove μs
|
||||
sys.stderr.write(f'\r{self.prefix} {bar} {fraction:>4.0%} ETA {remaining_time}')
|
||||
sys.stderr.flush()
|
||||
remaining_time -= _datetime.timedelta(microseconds=remaining_time.microseconds) # remove μs
|
||||
_sys.stderr.write(f'\r{self.prefix} {bar} {fraction:>4.0%} ETA {remaining_time}')
|
||||
_sys.stderr.flush()
|
||||
|
||||
self.fraction_last = fraction
|
||||
|
||||
if iteration == self.total - 1:
|
||||
sys.stderr.write('\n')
|
||||
sys.stderr.flush()
|
||||
_sys.stderr.write('\n')
|
||||
_sys.stderr.flush()
|
||||
|
|
|
|||
Loading…
Reference in New Issue