parallelize addition of datasets
threads does not work, muliprocessing shows good performance: Overhead is small compared to the performance gain. Especially useful for long running functions of the orientation class
This commit is contained in:
Martin Diehl
parent
b9966b95e0
commit
05476ff85c
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@ -1,7 +1,8 @@
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from queue import Queue
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import multiprocessing
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import re
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import glob
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import os
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from functools import partial
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import vtk
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from vtk.util import numpy_support
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@ -443,6 +444,17 @@ class DADF5():
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return f['geometry/x_c'][()]
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@staticmethod
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def _add_absolute(x):
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return {
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'data': np.abs(x['data']),
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'label': '|{}|'.format(x['label']),
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Absolute value of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_abs v{}'.format(version)
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}
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}
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def add_absolute(self,x):
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"""
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Add absolute value.
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@ -453,21 +465,24 @@ class DADF5():
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Label of scalar, vector, or tensor dataset to take absolute value of.
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"""
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def _add_absolute(x):
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self.__add_generic_pointwise(self._add_absolute,{'x':x})
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@staticmethod
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def _add_calculation(**kwargs):
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formula = kwargs['formula']
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for d in re.findall(r'#(.*?)#',formula):
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formula = formula.replace('#{}#'.format(d),"kwargs['{}']['data']".format(d))
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return {
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'data': np.abs(x['data']),
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'label': '|{}|'.format(x['label']),
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'data': eval(formula),
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'label': kwargs['label'],
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'meta': {
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'Unit': x['meta']['Unit'],
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'Description': 'Absolute value of {} ({})'.format(x['label'],x['meta']['Description']),
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'Creator': 'dadf5.py:add_abs v{}'.format(version)
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'Unit': kwargs['unit'],
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'Description': '{} (formula: {})'.format(kwargs['description'],kwargs['formula']),
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'Creator': 'dadf5.py:add_calculation v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_absolute,{'x':x})
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def add_calculation(self,label,formula,unit='n/a',description=None,vectorized=True):
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"""
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Add result of a general formula.
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@ -489,28 +504,24 @@ class DADF5():
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if not vectorized:
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raise NotImplementedError
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def _add_calculation(**kwargs):
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formula = kwargs['formula']
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for d in re.findall(r'#(.*?)#',formula):
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formula = formula.replace('#{}#'.format(d),"kwargs['{}']['data']".format(d))
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return {
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'data': eval(formula),
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'label': kwargs['label'],
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'meta': {
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'Unit': kwargs['unit'],
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'Description': '{} (formula: {})'.format(kwargs['description'],kwargs['formula']),
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'Creator': 'dadf5.py:add_calculation v{}'.format(version)
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}
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}
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dataset_mapping = {d:d for d in set(re.findall(r'#(.*?)#',formula))} # datasets used in the formula
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args = {'formula':formula,'label':label,'unit':unit,'description':description}
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self.__add_generic_pointwise(_add_calculation,dataset_mapping,args)
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self.__add_generic_pointwise(self._add_calculation,dataset_mapping,args)
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@staticmethod
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def _add_Cauchy(P,F):
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return {
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'data': mechanics.Cauchy(P['data'],F['data']),
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'label': 'sigma',
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'meta': {
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'Unit': P['meta']['Unit'],
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'Description': 'Cauchy stress calculated from {} ({}) '.format(P['label'],
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P['meta']['Description'])+\
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'and {} ({})'.format(F['label'],F['meta']['Description']),
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'Creator': 'dadf5.py:add_Cauchy v{}'.format(version)
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}
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}
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def add_Cauchy(self,P='P',F='F'):
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"""
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Add Cauchy stress calculated from first Piola-Kirchhoff stress and deformation gradient.
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@ -523,23 +534,20 @@ class DADF5():
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Label of the dataset containing the deformation gradient. Defaults to ‘F’.
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"""
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def _add_Cauchy(P,F):
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self.__add_generic_pointwise(self._add_Cauchy,{'P':P,'F':F})
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@staticmethod
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def _add_determinant(T):
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return {
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'data': mechanics.Cauchy(P['data'],F['data']),
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'label': 'sigma',
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'data': np.linalg.det(T['data']),
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'label': 'det({})'.format(T['label']),
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'meta': {
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'Unit': P['meta']['Unit'],
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'Description': 'Cauchy stress calculated from {} ({}) '.format(P['label'],
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P['meta']['Description'])+\
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'and {} ({})'.format(F['label'],F['meta']['Description']),
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'Creator': 'dadf5.py:add_Cauchy v{}'.format(version)
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'Unit': T['meta']['Unit'],
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'Description': 'Determinant of tensor {} ({})'.format(T['label'],T['meta']['Description']),
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'Creator': 'dadf5.py:add_determinant v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_Cauchy,{'P':P,'F':F})
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def add_determinant(self,T):
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"""
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Add the determinant of a tensor.
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@ -550,33 +558,11 @@ class DADF5():
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Label of tensor dataset.
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"""
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def _add_determinant(T):
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return {
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'data': np.linalg.det(T['data']),
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'label': 'det({})'.format(T['label']),
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'meta': {
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'Unit': T['meta']['Unit'],
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'Description': 'Determinant of tensor {} ({})'.format(T['label'],T['meta']['Description']),
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'Creator': 'dadf5.py:add_determinant v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_determinant,{'T':T})
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self.__add_generic_pointwise(self._add_determinant,{'T':T})
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def add_deviator(self,T):
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"""
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Add the deviatoric part of a tensor.
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Parameters
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----------
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T : str
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Label of tensor dataset.
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"""
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@staticmethod
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def _add_deviator(T):
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if not np.all(np.array(T['data'].shape[1:]) == np.array([3,3])):
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raise ValueError
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@ -589,10 +575,30 @@ class DADF5():
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'Creator': 'dadf5.py:add_deviator v{}'.format(version)
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}
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}
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def add_deviator(self,T):
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"""
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Add the deviatoric part of a tensor.
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self.__add_generic_pointwise(_add_deviator,{'T':T})
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Parameters
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----------
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T : str
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Label of tensor dataset.
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"""
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self.__add_generic_pointwise(self._add_deviator,{'T':T})
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@staticmethod
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def _add_eigenvalue(S):
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return {
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'data': mechanics.eigenvalues(S['data']),
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'label': 'lambda({})'.format(S['label']),
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'meta' : {
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'Unit': S['meta']['Unit'],
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'Description': 'Eigenvalues of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_eigenvalues v{}'.format(version)
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}
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}
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def add_eigenvalues(self,S):
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"""
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Add eigenvalues of symmetric tensor.
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@ -603,21 +609,20 @@ class DADF5():
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Label of symmetric tensor dataset.
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"""
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def _add_eigenvalue(S):
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self.__add_generic_pointwise(self._add_eigenvalue,{'S':S})
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@staticmethod
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def _add_eigenvector(S):
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return {
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'data': mechanics.eigenvalues(S['data']),
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'label': 'lambda({})'.format(S['label']),
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'data': mechanics.eigenvectors(S['data']),
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'label': 'v({})'.format(S['label']),
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'meta' : {
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'Unit': S['meta']['Unit'],
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'Description': 'Eigenvalues of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_eigenvalues v{}'.format(version)
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'Unit': '1',
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'Description': 'Eigenvectors of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_eigenvectors v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_eigenvalue,{'S':S})
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def add_eigenvectors(self,S):
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"""
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Add eigenvectors of symmetric tensor.
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@ -628,35 +633,11 @@ class DADF5():
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Label of symmetric tensor dataset.
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"""
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def _add_eigenvector(S):
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return {
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'data': mechanics.eigenvectors(S['data']),
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'label': 'v({})'.format(S['label']),
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'meta' : {
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'Unit': '1',
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'Description': 'Eigenvectors of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_eigenvectors v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_eigenvector,{'S':S})
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self.__add_generic_pointwise(self._add_eigenvector,{'S':S})
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def add_IPFcolor(self,q,l):
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"""
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Add RGB color tuple of inverse pole figure (IPF) color.
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Parameters
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----------
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q : str
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Label of the dataset containing the crystallographic orientation as quaternions.
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l : numpy.array of shape (3)
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Lab frame direction for inverse pole figure.
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"""
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@staticmethod
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def _add_IPFcolor(q,l):
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d = np.array(l)
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d_unit = d/np.linalg.norm(d)
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m = util.scale_to_coprime(d)
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@ -678,10 +659,32 @@ class DADF5():
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'Creator': 'dadf5.py:add_IPFcolor v{}'.format(version)
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}
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}
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def add_IPFcolor(self,q,l):
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"""
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Add RGB color tuple of inverse pole figure (IPF) color.
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self.__add_generic_pointwise(_add_IPFcolor,{'q':q},{'l':l})
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Parameters
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----------
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q : str
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Label of the dataset containing the crystallographic orientation as quaternions.
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l : numpy.array of shape (3)
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Lab frame direction for inverse pole figure.
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"""
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self.__add_generic_pointwise(self._add_IPFcolor,{'q':q},{'l':l})
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@staticmethod
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def _add_maximum_shear(S):
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return {
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'data': mechanics.maximum_shear(S['data']),
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'label': 'max_shear({})'.format(S['label']),
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'meta': {
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'Unit': S['meta']['Unit'],
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'Description': 'Maximum shear component of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_maximum_shear v{}'.format(version)
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}
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}
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def add_maximum_shear(self,S):
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"""
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Add maximum shear components of symmetric tensor.
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@ -692,21 +695,23 @@ class DADF5():
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Label of symmetric tensor dataset.
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"""
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def _add_maximum_shear(S):
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self.__add_generic_pointwise(self._add_maximum_shear,{'S':S})
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@staticmethod
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def _add_Mises(S):
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t = 'strain' if S['meta']['Unit'] == '1' else \
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'stress'
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return {
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'data': mechanics.maximum_shear(S['data']),
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'label': 'max_shear({})'.format(S['label']),
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'data': mechanics.Mises_strain(S['data']) if t=='strain' else mechanics.Mises_stress(S['data']),
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'label': '{}_vM'.format(S['label']),
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'meta': {
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'Unit': S['meta']['Unit'],
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'Description': 'Maximum shear component of {} ({})'.format(S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_maximum_shear v{}'.format(version)
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'Description': 'Mises equivalent {} of {} ({})'.format(t,S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_Mises v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_maximum_shear,{'S':S})
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def add_Mises(self,S):
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"""
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Add the equivalent Mises stress or strain of a symmetric tensor.
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@ -717,37 +722,11 @@ class DADF5():
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Label of symmetric tensorial stress or strain dataset.
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"""
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def _add_Mises(S):
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t = 'strain' if S['meta']['Unit'] == '1' else \
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'stress'
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return {
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'data': mechanics.Mises_strain(S['data']) if t=='strain' else mechanics.Mises_stress(S['data']),
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'label': '{}_vM'.format(S['label']),
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'meta': {
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'Unit': S['meta']['Unit'],
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'Description': 'Mises equivalent {} of {} ({})'.format(t,S['label'],S['meta']['Description']),
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'Creator': 'dadf5.py:add_Mises v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_Mises,{'S':S})
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self.__add_generic_pointwise(self._add_Mises,{'S':S})
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def add_norm(self,x,ord=None):
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"""
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Add the norm of vector or tensor.
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Parameters
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----------
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x : str
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Label of vector or tensor dataset.
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ord : {non-zero int, inf, -inf, ‘fro’, ‘nuc’}, optional
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Order of the norm. inf means NumPy’s inf object. For details refer to numpy.linalg.norm.
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"""
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@staticmethod
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def _add_norm(x,ord):
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o = ord
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if len(x['data'].shape) == 2:
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axis = 1
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@ -769,24 +748,23 @@ class DADF5():
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'Creator': 'dadf5.py:add_norm v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_norm,{'x':x},{'ord':ord})
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def add_PK2(self,P='P',F='F'):
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def add_norm(self,x,ord=None):
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"""
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Add 2. Piola-Kirchhoff calculated from first Piola-Kirchhoff stress and deformation gradient.
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Add the norm of vector or tensor.
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Parameters
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----------
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P : str, optional
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Label first Piola-Kirchhoff stress dataset. Defaults to ‘P’.
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F : str, optional
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Label of deformation gradient dataset. Defaults to ‘F’.
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x : str
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Label of vector or tensor dataset.
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ord : {non-zero int, inf, -inf, ‘fro’, ‘nuc’}, optional
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Order of the norm. inf means NumPy’s inf object. For details refer to numpy.linalg.norm.
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"""
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def _add_PK2(P,F):
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self.__add_generic_pointwise(self._add_norm,{'x':x},{'ord':ord})
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@staticmethod
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def _add_PK2(P,F):
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return {
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'data': mechanics.PK2(P['data'],F['data']),
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'label': 'S',
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@ -798,26 +776,23 @@ class DADF5():
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'Creator': 'dadf5.py:add_PK2 v{}'.format(version)
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}
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}
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self.__add_generic_pointwise(_add_PK2,{'P':P,'F':F})
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def add_pole(self,q,p,polar=False):
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def add_PK2(self,P='P',F='F'):
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"""
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Add coordinates of stereographic projection of given pole in crystal frame.
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Add second Piola-Kirchhoff calculated from first Piola-Kirchhoff stress and deformation gradient.
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Parameters
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----------
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q : str
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Label of the dataset containing the crystallographic orientation as quaternions.
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p : numpy.array of shape (3)
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Crystallographic direction or plane.
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polar : bool, optional
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Give pole in polar coordinates. Defaults to False.
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P : str, optional
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Label first Piola-Kirchhoff stress dataset. Defaults to ‘P’.
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F : str, optional
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Label of deformation gradient dataset. Defaults to ‘F’.
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"""
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def _add_pole(q,p,polar):
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self.__add_generic_pointwise(self._add_PK2,{'P':P,'F':F})
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@staticmethod
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def _add_pole(q,p,polar):
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pole = np.array(p)
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unit_pole = pole/np.linalg.norm(pole)
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m = util.scale_to_coprime(pole)
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@ -839,10 +814,36 @@ class DADF5():
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'Creator' : 'dadf5.py:add_pole v{}'.format(version)
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}
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}
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def add_pole(self,q,p,polar=False):
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"""
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Add coordinates of stereographic projection of given pole in crystal frame.
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self.__add_generic_pointwise(_add_pole,{'q':q},{'p':p,'polar':polar})
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Parameters
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----------
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q : str
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||||
Label of the dataset containing the crystallographic orientation as quaternions.
|
||||
p : numpy.array of shape (3)
|
||||
Crystallographic direction or plane.
|
||||
polar : bool, optional
|
||||
Give pole in polar coordinates. Defaults to False.
|
||||
|
||||
"""
|
||||
self.__add_generic_pointwise(self._add_pole,{'q':q},{'p':p,'polar':polar})
|
||||
|
||||
|
||||
@staticmethod
|
||||
def _add_rotational_part(F):
|
||||
if not np.all(np.array(F['data'].shape[1:]) == np.array([3,3])):
|
||||
raise ValueError
|
||||
return {
|
||||
'data': mechanics.rotational_part(F['data']),
|
||||
'label': 'R({})'.format(F['label']),
|
||||
'meta': {
|
||||
'Unit': F['meta']['Unit'],
|
||||
'Description': 'Rotational part of {} ({})'.format(F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_rotational_part v{}'.format(version)
|
||||
}
|
||||
}
|
||||
def add_rotational_part(self,F):
|
||||
"""
|
||||
Add rotational part of a deformation gradient.
|
||||
|
|
@ -853,33 +854,12 @@ class DADF5():
|
|||
Label of deformation gradient dataset.
|
||||
|
||||
"""
|
||||
def _add_rotational_part(F):
|
||||
|
||||
return {
|
||||
'data': mechanics.rotational_part(F['data']),
|
||||
'label': 'R({})'.format(F['label']),
|
||||
'meta': {
|
||||
'Unit': F['meta']['Unit'],
|
||||
'Description': 'Rotational part of {} ({})'.format(F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_rotational_part v{}'.format(version)
|
||||
}
|
||||
}
|
||||
|
||||
self.__add_generic_pointwise(_add_rotational_part,{'F':F})
|
||||
self.__add_generic_pointwise(self._add_rotational_part,{'F':F})
|
||||
|
||||
|
||||
def add_spherical(self,T):
|
||||
"""
|
||||
Add the spherical (hydrostatic) part of a tensor.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
T : str
|
||||
Label of tensor dataset.
|
||||
|
||||
"""
|
||||
@staticmethod
|
||||
def _add_spherical(T):
|
||||
|
||||
if not np.all(np.array(T['data'].shape[1:]) == np.array([3,3])):
|
||||
raise ValueError
|
||||
|
||||
|
|
@ -892,10 +872,32 @@ class DADF5():
|
|||
'Creator': 'dadf5.py:add_spherical v{}'.format(version)
|
||||
}
|
||||
}
|
||||
def add_spherical(self,T):
|
||||
"""
|
||||
Add the spherical (hydrostatic) part of a tensor.
|
||||
|
||||
self.__add_generic_pointwise(_add_spherical,{'T':T})
|
||||
Parameters
|
||||
----------
|
||||
T : str
|
||||
Label of tensor dataset.
|
||||
|
||||
"""
|
||||
self.__add_generic_pointwise(self._add_spherical,{'T':T})
|
||||
|
||||
|
||||
@staticmethod
|
||||
def _add_strain_tensor(F,t,m):
|
||||
if not np.all(np.array(F['data'].shape[1:]) == np.array([3,3])):
|
||||
raise ValueError
|
||||
return {
|
||||
'data': mechanics.strain_tensor(F['data'],t,m),
|
||||
'label': 'epsilon_{}^{}({})'.format(t,m,F['label']),
|
||||
'meta': {
|
||||
'Unit': F['meta']['Unit'],
|
||||
'Description': 'Strain tensor of {} ({})'.format(F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_strain_tensor v{}'.format(version)
|
||||
}
|
||||
}
|
||||
def add_strain_tensor(self,F='F',t='V',m=0.0):
|
||||
"""
|
||||
Add strain tensor of a deformation gradient.
|
||||
|
|
@ -913,21 +915,24 @@ class DADF5():
|
|||
Order of the strain calculation. Defaults to ‘0.0’.
|
||||
|
||||
"""
|
||||
def _add_strain_tensor(F,t,m):
|
||||
self.__add_generic_pointwise(self._add_strain_tensor,{'F':F},{'t':t,'m':m})
|
||||
|
||||
|
||||
@staticmethod
|
||||
def _add_stretch_tensor(F,t):
|
||||
if not np.all(np.array(F['data'].shape[1:]) == np.array([3,3])):
|
||||
raise ValueError
|
||||
|
||||
return {
|
||||
'data': mechanics.strain_tensor(F['data'],t,m),
|
||||
'label': 'epsilon_{}^{}({})'.format(t,m,F['label']),
|
||||
'data': mechanics.left_stretch(F['data']) if t == 'V' else mechanics.right_stretch(F['data']),
|
||||
'label': '{}({})'.format(t,F['label']),
|
||||
'meta': {
|
||||
'Unit': F['meta']['Unit'],
|
||||
'Description': 'Strain tensor of {} ({})'.format(F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_strain_tensor v{}'.format(version)
|
||||
'Description': '{} stretch tensor of {} ({})'.format('Left' if t == 'V' else 'Right',
|
||||
F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_stretch_tensor v{}'.format(version)
|
||||
}
|
||||
}
|
||||
|
||||
self.__add_generic_pointwise(_add_strain_tensor,{'F':F},{'t':t,'m':m})
|
||||
|
||||
|
||||
def add_stretch_tensor(self,F='F',t='V'):
|
||||
"""
|
||||
Add stretch tensor of a deformation gradient.
|
||||
|
|
@ -941,77 +946,54 @@ class DADF5():
|
|||
Defaults to ‘V’.
|
||||
|
||||
"""
|
||||
def _add_stretch_tensor(F,t):
|
||||
|
||||
return {
|
||||
'data': mechanics.left_stretch(F['data']) if t == 'V' else mechanics.right_stretch(F['data']),
|
||||
'label': '{}({})'.format(t,F['label']),
|
||||
'meta': {
|
||||
'Unit': F['meta']['Unit'],
|
||||
'Description': '{} stretch tensor of {} ({})'.format('Left' if t == 'V' else 'Right',
|
||||
F['label'],F['meta']['Description']),
|
||||
'Creator': 'dadf5.py:add_stretch_tensor v{}'.format(version)
|
||||
}
|
||||
}
|
||||
|
||||
self.__add_generic_pointwise(_add_stretch_tensor,{'F':F},{'t':t})
|
||||
self.__add_generic_pointwise(self._add_stretch_tensor,{'F':F},{'t':t})
|
||||
|
||||
|
||||
def __add_generic_pointwise(self,func,dataset_mapping,args={}):
|
||||
"""
|
||||
General function to add pointwise data.
|
||||
def job(self,group,func,datasets,args,lock):
|
||||
try:
|
||||
d = self._read(group,datasets,lock)
|
||||
r = func(**d,**args)
|
||||
return [group,r]
|
||||
except Exception as err:
|
||||
print('Error during calculation: {}.'.format(err))
|
||||
return None
|
||||
|
||||
Parameters
|
||||
----------
|
||||
func : function
|
||||
Function that calculates a new dataset from one or more datasets per HDF5 group.
|
||||
dataset_mapping : dictionary
|
||||
Mapping HDF5 data label to callback function argument
|
||||
extra_args : dictionary, optional
|
||||
Any extra arguments parsed to func.
|
||||
|
||||
"""
|
||||
def job(args):
|
||||
"""Call function with input data + extra arguments, returns results + group."""
|
||||
args['results'].put({**args['func'](**args['in']),'group':args['group']})
|
||||
def _read(self,group,datasets,lock):
|
||||
datasets_in = {}
|
||||
lock.acquire()
|
||||
with h5py.File(self.fname,'r') as f:
|
||||
for k,v in datasets.items():
|
||||
loc = f[group+'/'+v]
|
||||
datasets_in[k]={'data':loc[()],
|
||||
'label':v,
|
||||
'meta':{k2:v2.decode() for k2,v2 in loc.attrs.items()}}
|
||||
lock.release()
|
||||
return datasets_in
|
||||
|
||||
def __add_generic_pointwise(self,func,datasets,args={}):
|
||||
|
||||
env = Environment()
|
||||
N_threads = int(env.options['DAMASK_NUM_THREADS'])
|
||||
N_threads //=N_threads # disable for the moment
|
||||
pool = multiprocessing.Pool(N_threads)
|
||||
m = multiprocessing.Manager()
|
||||
lock = m.Lock()
|
||||
|
||||
results = Queue(N_threads)
|
||||
pool = util.ThreadPool(N_threads)
|
||||
N_added = N_threads + 1
|
||||
|
||||
todo = []
|
||||
# ToDo: It would be more memory efficient to read only from file when required, i.e. do to it in pool.add_task
|
||||
for group in self.groups_with_datasets(dataset_mapping.values()):
|
||||
with h5py.File(self.fname,'r') as f:
|
||||
datasets_in = {}
|
||||
for arg,label in dataset_mapping.items():
|
||||
loc = f[group+'/'+label]
|
||||
data = loc[()]
|
||||
meta = {k:loc.attrs[k].decode() for k in loc.attrs.keys()}
|
||||
datasets_in[arg] = {'data': data, 'meta': meta, 'label': label}
|
||||
|
||||
todo.append({'in':{**datasets_in,**args},'func':func,'group':group,'results':results})
|
||||
|
||||
pool.map(job, todo[:N_added]) # initialize
|
||||
|
||||
N_not_calculated = len(todo)
|
||||
while N_not_calculated > 0:
|
||||
result = results.get()
|
||||
with h5py.File(self.fname,'a') as f: # write to file
|
||||
dataset_out = f[result['group']].create_dataset(result['label'],data=result['data'])
|
||||
for k in result['meta'].keys():
|
||||
dataset_out.attrs[k] = result['meta'][k].encode()
|
||||
N_not_calculated-=1
|
||||
|
||||
if N_added < len(todo): # add more jobs
|
||||
pool.add_task(job,todo[N_added])
|
||||
N_added +=1
|
||||
|
||||
pool.wait_completion()
|
||||
groups = self.groups_with_datasets(datasets.values())
|
||||
default_arg = partial(self.job,func=func,datasets=datasets,args=args,lock=lock)
|
||||
for result in pool.imap_unordered(default_arg,groups):
|
||||
if not result: continue
|
||||
lock.acquire()
|
||||
with h5py.File(self.fname, 'a') as f:
|
||||
try:
|
||||
dataset = f[result[0]].create_dataset(result[1]['label'],data=result[1]['data'])
|
||||
for l,v in result[1]['meta'].items():
|
||||
dataset.attrs[l]=v.encode()
|
||||
except OSError as err:
|
||||
print('Could not add dataset: {}.'.format(err))
|
||||
lock.release()
|
||||
pool.close()
|
||||
pool.join()
|
||||
|
||||
|
||||
def to_vtk(self,labels,mode='cell'):
|
||||
|
|
|
|||
|
|
@ -201,57 +201,3 @@ class return_message():
|
|||
def __repr__(self):
|
||||
"""Return message suitable for interactive shells."""
|
||||
return srepr(self.message)
|
||||
|
||||
|
||||
class ThreadPool:
|
||||
"""Pool of threads consuming tasks from a queue."""
|
||||
|
||||
class Worker(Thread):
|
||||
"""Thread executing tasks from a given tasks queue."""
|
||||
|
||||
def __init__(self, tasks):
|
||||
"""Worker for tasks."""
|
||||
Thread.__init__(self)
|
||||
self.tasks = tasks
|
||||
self.daemon = True
|
||||
self.start()
|
||||
|
||||
def run(self):
|
||||
while True:
|
||||
func, args, kargs = self.tasks.get()
|
||||
try:
|
||||
func(*args, **kargs)
|
||||
except Exception as e:
|
||||
# An exception happened in this thread
|
||||
print(e)
|
||||
finally:
|
||||
# Mark this task as done, whether an exception happened or not
|
||||
self.tasks.task_done()
|
||||
|
||||
|
||||
def __init__(self, num_threads):
|
||||
"""
|
||||
Thread pool.
|
||||
|
||||
Parameters
|
||||
----------
|
||||
num_threads : int
|
||||
number of threads
|
||||
|
||||
"""
|
||||
self.tasks = Queue(num_threads)
|
||||
for _ in range(num_threads):
|
||||
self.Worker(self.tasks)
|
||||
|
||||
def add_task(self, func, *args, **kargs):
|
||||
"""Add a task to the queue."""
|
||||
self.tasks.put((func, args, kargs))
|
||||
|
||||
def map(self, func, args_list):
|
||||
"""Add a list of tasks to the queue."""
|
||||
for args in args_list:
|
||||
self.add_task(func, args)
|
||||
|
||||
def wait_completion(self):
|
||||
"""Wait for completion of all the tasks in the queue."""
|
||||
self.tasks.join()
|
||||
|
|
|
|||
Loading…
Reference in New Issue