211 lines
10 KiB
Python
211 lines
10 KiB
Python
import sys
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import random
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import pytest
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import numpy as np
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from scipy import stats
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import h5py
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from damask import util
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class TestUtil:
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@pytest.mark.xfail(sys.platform == 'win32', reason='echo is not a Windows command')
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def test_run_direct(self):
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out,err = util.run('echo test')
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assert out=='test\n' and err==''
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@pytest.mark.xfail(sys.platform == 'win32', reason='echo is not a Windows command')
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def test_run_env(self):
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out,err = util.run('sh -c "echo $test_for_execute"',env={'test_for_execute':'test'})
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assert out=='test\n' and err==''
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@pytest.mark.xfail(sys.platform == 'win32', reason='false is not a Windows command')
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def test_run_runtime_error(self):
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with pytest.raises(RuntimeError):
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util.run('false')
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@pytest.mark.parametrize('input,output',
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[
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([0,-2],[0,-1]),
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([-0.5,0.5],[-1,1]),
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([1./2.,1./3.],[3,2]),
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([2./3.,1./2.,1./3.],[4,3,2]),
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])
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def test_scale2coprime(self,input,output):
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assert np.allclose(util.scale_to_coprime(np.array(input)),
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np.array(output).astype(int))
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def test_lackofprecision(self):
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with pytest.raises(ValueError):
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util.scale_to_coprime(np.array([1/333.333,1,1]))
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@pytest.mark.parametrize('rv',[stats.rayleigh(),stats.weibull_min(1.2),stats.halfnorm(),stats.pareto(2.62)])
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def test_hybridIA(self,rv):
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bins = np.linspace(0,10,100000)
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centers = (bins[1:]+bins[:-1])/2
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N_samples = bins.shape[0]-1000
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dist = rv.pdf(centers)
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selected = util.hybrid_IA(dist,N_samples)
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dist_sampled = np.histogram(centers[selected],bins)[0]/N_samples*np.sum(dist)
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assert np.sqrt(((dist - dist_sampled) ** 2).mean()) < .025 and selected.shape[0]==N_samples
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@pytest.mark.parametrize('point,direction,normalize,keepdims,answer',
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[
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([1,0,0],'z',False,True, [1,0,0]),
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([1,0,0],'z',True, False,[1,0]),
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([0,1,1],'z',False,True, [0,0.5,0]),
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([0,1,1],'y',True, False,[0.41421356,0]),
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([1,1,0],'x',False,False,[0.5,0]),
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([1,1,1],'y',True, True, [0.3660254, 0,0.3660254]),
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])
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def test_project_equal_angle(self,point,direction,normalize,keepdims,answer):
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assert np.allclose(util.project_equal_angle(np.array(point),direction=direction,
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normalize=normalize,keepdims=keepdims),answer)
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@pytest.mark.parametrize('point,direction,normalize,keepdims,answer',
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[
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([1,0,0],'z',False,True, [1,0,0]),
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([1,0,0],'z',True, False,[1,0]),
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([0,1,1],'z',False,True, [0,0.70710678,0]),
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([0,1,1],'y',True, False,[0.5411961,0]),
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([1,1,0],'x',False,False,[0.70710678,0]),
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([1,1,1],'y',True, True, [0.45970084,0,0.45970084]),
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])
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def test_project_equal_area(self,point,direction,normalize,keepdims,answer):
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assert np.allclose(util.project_equal_area(np.array(point),direction=direction,
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normalize=normalize,keepdims=keepdims),answer)
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@pytest.mark.parametrize('fro,to,mode,answer',
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[
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((),(1,),'left',(1,)),
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((1,),(7,),'right',(1,)),
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((1,2),(1,1,2,2),'right',(1,1,2,1)),
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((1,2),(1,1,2,2),'left',(1,1,1,2)),
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((1,2,3),(1,1,2,3,4),'right',(1,1,2,3,1)),
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((10,2),(10,3,2,2,),'right',(10,1,2,1)),
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((10,2),(10,3,2,2,),'left',(10,1,1,2)),
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((2,2,3),(2,2,2,3,4),'left',(1,2,2,3,1)),
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((2,2,3),(2,2,2,3,4),'right',(2,2,1,3,1)),
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])
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def test_shapeshifter(self,fro,to,mode,answer):
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assert util.shapeshifter(fro,to,mode) == answer
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@pytest.mark.parametrize('fro,to,mode',
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[
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((10,3,4),(10,3,2,2),'left'),
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((2,3),(10,3,2,2),'right'),
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])
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def test_invalid_shapeshifter(self,fro,to,mode):
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with pytest.raises(ValueError):
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util.shapeshifter(fro,to,mode)
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@pytest.mark.parametrize('a,b,answer',
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[
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((),(1,),(1,)),
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((1,),(),(1,)),
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((1,),(7,),(1,7)),
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((2,),(2,2),(2,2)),
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((1,2),(2,2),(1,2,2)),
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((1,2,3),(2,3,4),(1,2,3,4)),
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((1,2,3),(1,2,3),(1,2,3)),
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])
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def test_shapeblender(self,a,b,answer):
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assert util.shapeblender(a,b) == answer
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@pytest.mark.parametrize('style',[util.emph,util.deemph,util.warn,util.strikeout])
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def test_decorate(self,style):
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assert 'DAMASK' in style('DAMASK')
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@pytest.mark.parametrize('lst',[1,[1,2],set([1,2,3]),np.arange(4)])
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def test_aslist(self,lst):
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assert len(util.aslist(lst)) > 0
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@pytest.mark.parametrize('complete',[True,False])
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def test_D3D_base_group(self,tmp_path,complete):
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base_group = ''.join(random.choices('DAMASK', k=10))
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with h5py.File(tmp_path/'base_group.dream3d','w') as f:
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f.create_group('/'.join((base_group,'_SIMPL_GEOMETRY')))
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if complete:
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f['/'.join((base_group,'_SIMPL_GEOMETRY'))].create_dataset('SPACING',data=np.ones(3))
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if complete:
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assert base_group == util.DREAM3D_base_group(tmp_path/'base_group.dream3d')
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else:
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with pytest.raises(ValueError):
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util.DREAM3D_base_group(tmp_path/'base_group.dream3d')
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@pytest.mark.parametrize('complete',[True,False])
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def test_D3D_cell_data_group(self,tmp_path,complete):
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base_group = ''.join(random.choices('DAMASK', k=10))
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cell_data_group = ''.join(random.choices('KULeuven', k=10))
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cells = np.random.randint(1,50,3)
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with h5py.File(tmp_path/'cell_data_group.dream3d','w') as f:
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f.create_group('/'.join((base_group,'_SIMPL_GEOMETRY')))
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f['/'.join((base_group,'_SIMPL_GEOMETRY'))].create_dataset('SPACING',data=np.ones(3))
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f['/'.join((base_group,'_SIMPL_GEOMETRY'))].create_dataset('DIMENSIONS',data=cells[::-1])
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f[base_group].create_group(cell_data_group)
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if complete:
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f['/'.join((base_group,cell_data_group))].create_dataset('data',shape=np.append(cells,1))
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if complete:
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assert cell_data_group == util.DREAM3D_cell_data_group(tmp_path/'cell_data_group.dream3d')
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else:
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with pytest.raises(ValueError):
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util.DREAM3D_cell_data_group(tmp_path/'cell_data_group.dream3d')
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@pytest.mark.parametrize('full,reduced',[({}, {}),
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({'A':{}}, {}),
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({'A':{'B':{}}}, {}),
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({'A':{'B':'C'}},)*2,
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({'A':{'B':{},'C':'D'}}, {'A':{'C':'D'}})])
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def test_prune(self,full,reduced):
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assert util.dict_prune(full) == reduced
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@pytest.mark.parametrize('full,reduced',[({}, {}),
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({'A':{}}, {}),
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({'A':'F'}, 'F'),
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({'A':{'B':{}}}, {}),
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({'A':{'B':'C'}}, 'C'),
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({'A':1,'B':2},)*2,
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({'A':{'B':'C','D':'E'}}, {'B':'C','D':'E'}),
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({'B':'C','D':'E'},)*2,
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({'A':{'B':{},'C':'D'}}, {'B':{},'C':'D'})])
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def test_flatten(self,full,reduced):
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assert util.dict_flatten(full) == reduced
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def test_double_Bravais_to_Miller(self):
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with pytest.raises(KeyError):
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util.Bravais_to_Miller(uvtw=np.ones(4),hkil=np.ones(4))
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def test_double_Miller_to_Bravais(self):
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with pytest.raises(KeyError):
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util.Miller_to_Bravais(uvw=np.ones(4),hkl=np.ones(4))
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@pytest.mark.parametrize('vector',np.array([
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[1,0,0],
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[1,1,0],
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[1,1,1],
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[1,0,-2],
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]))
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@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
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def test_Miller_Bravais_Miller(self,vector,kw_Miller,kw_Bravais):
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assert np.all(vector == util.Bravais_to_Miller(**{kw_Bravais:util.Miller_to_Bravais(**{kw_Miller:vector})}))
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@pytest.mark.parametrize('vector',np.array([
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[1,0,-1,2],
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[1,-1,0,3],
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[1,1,-2,-3],
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[0,0,0,1],
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]))
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@pytest.mark.parametrize('kw_Miller,kw_Bravais',[('uvw','uvtw'),('hkl','hkil')])
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def test_Bravais_Miller_Bravais(self,vector,kw_Miller,kw_Bravais):
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assert np.all(vector == util.Miller_to_Bravais(**{kw_Miller:util.Bravais_to_Miller(**{kw_Bravais:vector})}))
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