206 lines
7.3 KiB
Python
206 lines
7.3 KiB
Python
import pytest
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import numpy as np
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from damask import Table
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@pytest.fixture
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def default():
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"""Simple Table."""
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x = np.ones((5,13),dtype=float)
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return Table({'F':(3,3),'v':(3,),'s':(1,)},
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x,
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['test data','contains five rows of only ones'])
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@pytest.fixture
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def ref_path(ref_path_base):
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"""Directory containing reference results."""
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return ref_path_base/'Table'
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class TestTable:
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def test_repr(self,default):
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print(default)
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@pytest.mark.parametrize('N',[10,40])
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def test_len(self,N):
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assert len(Table({'X':3},np.random.rand(N,3))) == N
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def test_get_scalar(self,default):
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d = default.get('s')
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assert np.allclose(d,1.0) and d.shape[1:] == (1,)
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def test_get_vector(self,default):
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d = default.get('v')
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assert np.allclose(d,1.0) and d.shape[1:] == (3,)
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def test_get_tensor(self,default):
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d = default.get('F')
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assert np.allclose(d,1.0) and d.shape[1:] == (3,3)
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def test_set(self,default):
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d = default.set('F',np.zeros((5,3,3)),'set to zero').get('F')
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assert np.allclose(d,0.0) and d.shape[1:] == (3,3)
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def test_set_component(self,default):
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d = default.set('F[0,0]',np.zeros((5)),'set to zero').get('F')
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assert np.allclose(d[...,0,0],0.0) and d.shape[1:] == (3,3)
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def test_labels(self,default):
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assert default.labels == ['F','v','s']
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def test_add(self,default):
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d = np.random.random((5,9))
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assert np.allclose(d,default.add('nine',d,'random data').get('nine'))
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def test_isclose(self,default):
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assert default.isclose(default).all()
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def test_allclose(self,default):
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assert default.allclose(default)
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@pytest.mark.parametrize('N',[1,3,4])
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def test_slice(self,default,N):
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mask = np.random.choice([True,False],len(default))
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assert len(default[:N]) == 1+N
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assert len(default[:N,['F','s']]) == 1+N
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assert len(default[mask,['F','s']]) == np.count_nonzero(mask)
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assert default[mask,['F','s']] == default[mask][['F','s']] == default[['F','s']][mask]
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assert default[np.logical_not(mask),['F','s']] != default[mask][['F','s']]
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assert default[N:].get('F').shape == (len(default)-N,3,3)
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assert default[:N,['v','s']].data.equals(default['v','s'][:N].data)
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@pytest.mark.parametrize('mode',['str','path'])
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def test_write_read(self,default,tmp_path,mode):
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default.save(tmp_path/'default.txt')
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if mode == 'path':
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new = Table.load(tmp_path/'default.txt')
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elif mode == 'str':
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new = Table.load(str(tmp_path/'default.txt'))
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assert all(default.data == new.data) and default.shapes == new.shapes
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def test_write_read_file(self,default,tmp_path):
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with open(tmp_path/'default.txt','w') as f:
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default.save(f)
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with open(tmp_path/'default.txt') as f:
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new = Table.load(f)
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assert all(default.data == new.data) and default.shapes == new.shapes
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def test_write_invalid_format(self,default,tmp_path):
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with pytest.raises(TypeError):
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default.save(tmp_path/'shouldnotbethere.txt',format='invalid')
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@pytest.mark.parametrize('mode',['str','path'])
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def test_read_ang(self,ref_path,mode):
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if mode == 'path':
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new = Table.load_ang(ref_path/'simple.ang')
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elif mode == 'str':
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new = Table.load_ang(str(ref_path/'simple.ang'))
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assert new.data.shape == (4,10) and \
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new.labels == ['eu', 'pos', 'IQ', 'CI', 'ID', 'intensity', 'fit']
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def test_read_ang_file(self,ref_path):
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f = open(ref_path/'simple.ang')
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new = Table.load_ang(f)
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assert new.data.shape == (4,10) and \
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new.labels == ['eu', 'pos', 'IQ', 'CI', 'ID', 'intensity', 'fit']
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def test_save_ang(self,ref_path,tmp_path):
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orig = Table.load_ang(ref_path/'simple.ang')
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orig.save(tmp_path/'simple.ang',with_labels=False)
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saved = Table.load_ang(tmp_path/'simple.ang')
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assert saved == orig
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@pytest.mark.parametrize('fname',['datatype-mix.txt','whitespace-mix.txt'])
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def test_read_strange(self,ref_path,fname):
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with open(ref_path/fname) as f:
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Table.load(f)
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def test_rename_equivalent(self):
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x = np.random.random((5,13))
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t = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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s = t.get('s')
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u = t.rename('s','u').get('u')
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assert np.all(s == u)
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def test_rename_gone(self,default):
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gone = default.rename('v','V')
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assert 'v' not in gone.shapes and 'v' not in gone.data.columns
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with pytest.raises(KeyError):
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gone.get('v')
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def test_delete(self,default):
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delete = default.delete('v')
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assert 'v' not in delete.shapes and 'v' not in delete.data.columns
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with pytest.raises(KeyError):
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delete.get('v')
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def test_join(self):
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x = np.random.random((5,13))
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a = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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y = np.random.random((5,3))
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b = Table({'u':(3,)},y,['random test data'])
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c = a.join(b)
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assert np.array_equal(c.get('u'), b.get('u'))
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def test_join_invalid(self):
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x = np.random.random((5,13))
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a = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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with pytest.raises(KeyError):
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a.join(a)
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def test_append(self):
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x = np.random.random((5,13))
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a = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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b = a.append(a)
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assert np.array_equal(b.data[:5].to_numpy(),b.data[5:].to_numpy())
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def test_append_invalid(self):
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x = np.random.random((5,13))
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a = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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b = Table({'F':(3,3),'u':(3,),'s':(1,)},x,['random test data'])
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with pytest.raises(KeyError):
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a.append(b)
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def test_invalid_initialization(self):
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x = np.random.random((5,10))
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with pytest.raises(ValueError):
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Table({'F':(3,3)},x)
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def test_invalid_set(self,default):
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x = default.get('v')
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with pytest.raises(ValueError):
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default.set('F',x,'does not work')
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def test_invalid_get(self,default):
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with pytest.raises(KeyError):
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default.get('n')
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def test_sort_scalar(self):
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x = np.random.random((5,13))
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t = Table({'F':(3,3),'v':(3,),'s':(1,)},x,['random test data'])
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unsort = t.get('s')
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sort = t.sort_by('s').get('s')
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assert np.all(np.sort(unsort,0)==sort)
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def test_sort_component(self):
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x = np.random.random((5,12))
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t = Table({'F':(3,3),'v':(3,)},x,['random test data'])
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unsort = t.get('F')[:,1,0]
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sort = t.sort_by('F[1,0]').get('F')[:,1,0]
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assert np.all(np.sort(unsort,0)==sort)
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def test_sort_revert(self):
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x = np.random.random((5,12))
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t = Table({'F':(3,3),'v':(3,)},x,['random test data'])
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sort = t.sort_by('F[1,0]',ascending=False).get('F')[:,1,0]
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assert np.all(np.sort(sort,0)==sort[::-1])
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def test_sort(self):
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t = Table({'v':(2,)},
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np.array([[0,1,],[2,1,]]),
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['test data'])\
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.add('s',np.array(['b','a']))\
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.sort_by('s')
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assert np.all(t.get('v')[:,0] == np.array([2,0]))
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