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