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_empty_init(self):
N = 3
D = dict(
scal=np.arange(10),
vctr=np.arange(10*N).reshape((10,N)),
)
t = Table()
for label,data in D.items():
t = t.set(label,data)
assert np.allclose(t.get('scal').flatten()*3,t.get('vctr')[:,0])
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]))