class TestRockPyData(TestCase):
def setUp(self):
# run before each test
self.testdata = ((1, 2, 3, 4),
(1, 6, 7, 8),
(1, 2, 11, 12),
(1, 6, 55, 66))
self.col_names = ('F', 'Mx', 'My', 'Mz')
self.row_names = ('1.Zeile', '2.Zeile_A', '3.Zeile', '4.Zeile_A')
self.units = ('T', 'mT', 'fT', 'pT')
self.RPD = RockPyData(column_names=self.col_names, row_names=self.row_names, units=self.units,
data=self.testdata)
def test_column_names(self):
self.assertEqual(self.RPD.column_names, list(self.col_names))
def test_column_count(self):
self.assertEqual(self.RPD.column_count, len(self.col_names))
def test__find_duplicate_variable_rows(self):
# self.assertTrue((self.RPD._find_duplicate_variables()[0] == np.array([0, 1, 2])).all())
self.assertEqual(self.RPD._find_duplicate_variable_rows(), [(0, 1, 2, 3)])
# redefine variabe alias to the first two columns
self.RPD.define_alias('variable', ('F', 'Mx'))
self.assertEqual(self.RPD._find_duplicate_variable_rows(), [(0, 2), (1, 3)])
def test_rename_column(self):
self.RPD.rename_column('Mx', 'M_x')
self.assertEqual(self.RPD.column_names, ['F', 'M_x', 'My', 'Mz'])
def test_append_rows(self):
d1 = [[5, 6, 7, 8], [9, 10, 11, 12]]
self.RPD = self.RPD.append_rows(d1, ('5.Zeile', '6.Zeile'))
self.assertTrue(np.array_equal(self.RPD.v[-2:, :], np.array(d1)))
d2 = [5, 6, 7, 8]
self.RPD = self.RPD.append_rows(d2, '5.Zeile')
self.assertTrue(np.array_equal(self.RPD.v[-1, :], np.array(d2)))
# lets try with other RockPyData object
rpd = copy.deepcopy(self.RPD)
rpd.rename_column('Mx', 'M_x')
self.RPD = self.RPD.append_rows(rpd)
# TODO: add assert
#print self.RPD
def test_delete_rows(self):
self.RPD = self.RPD.delete_rows((0, 2))
self.assertTrue(np.array_equal(self.RPD.v, np.array(self.testdata)[(1, 3), :]))
def test_eliminate_duplicate_variable_rows(self):
# check for one variable column
self.RPD = self.RPD.eliminate_duplicate_variable_rows()
self.assertTrue(np.array_equal(self.RPD.v, np.array([]).reshape(0, 4)))
def test_eliminate_duplicate_variable_rows2(self):
# check for two variable columns
self.RPD.define_alias('variable', ('F', 'Mx'))
rpd = self.RPD.eliminate_duplicate_variable_rows(substfunc='mean')
self.assertTrue(np.array_equal(rpd.v, np.array([[1., 2., 7., 8.], [1., 6., 31., 37.]])))
self.assertTrue(np.array_equal(rpd.e, np.array([[0., 0., 4., 4.], [0., 0., 24., 29.]])))
rpd = self.RPD.eliminate_duplicate_variable_rows(substfunc='last')
self.assertTrue(np.array_equal(rpd.v, np.array([[1., 2., 11., 12.], [1., 6., 55., 66.]])))
def test_mean(self):
self.RPD = self.RPD.mean()
self.assertTrue(np.array_equal(self.RPD.v, np.array([[1., 4., 19., 22.5]])))
np.testing.assert_allclose(self.RPD.e, np.array([[0., 2., 20.976, 25.273]]), atol=0.01)
def test_max(self):
self.RPD = self.RPD.max()
self.assertTrue(np.array_equal(self.RPD.v, np.array([[1., 6., 55., 66.]])))
def test_filter_row_names(self):
self.assertEqual(self.RPD.filter_row_names(('1.Zeile', '3.Zeile')).row_names, ['1.Zeile', '3.Zeile'])
def test_filter_match_row_names(self):
# get all rows ending with '_A'
self.assertEqual(self.RPD.filter_match_row_names('.*_A').row_names, ['2.Zeile_A', '4.Zeile_A'])
def test_append_columns(self):
cb = self.RPD.column_count
d = (8, 7, 6, 5)
self.RPD = self.RPD.append_columns('neue Spalte', d)
self.assertEqual(cb + 1, self.RPD.column_count)
self.assertTrue(np.array_equal(self.RPD['neue Spalte'].v, np.array(d)))
def test_sort(self):
self.assertTrue(np.array_equal(self.RPD.sort('Mx')['Mx'].v, np.array((2, 2, 6, 6))))
#def test_interpolate(self):
# self.RPD.define_alias('variable', 'My')
# iv = (1, 11, 33, 55, 100)
# self.assertTrue(np.array_equal((self.RPD.interpolate(iv))['My'].v, np.array(iv)))
# self.assertTrue(np.array_equal((self.RPD.interpolate(iv))['Mx'].v[1:-1], np.array([2., 4., 6.])))
def test_magnitude(self):
self.RPD.define_alias('m', ('Mx', 'My', 'Mz'))
self.RPD = self.RPD.append_columns('mag', self.RPD.magnitude('m'))
np.testing.assert_allclose(self.RPD['mag'].v, np.array([5.38516481, 12.20655562, 16.40121947, 86.12200648]), atol=1e-5)
def test_column_names_to_indices(self):
self.assertEqual( self.RPD.column_names_to_indices(('Mx', 'Mz')), [1,3])
def test_interation(self):
# TODO: add proper assertion
for l in self.RPD:
#print l
pass
def test_add_errors(self):
d = RockPyData(column_names=['A', 'B'])
#d['A'].v = 1 # Attribute Error NoneType has no attribute, maybe initialize to np.nan?
#d['B'] = 2
#d['A'].e = 4
#d['B'].e = 5
d = d.append_rows([1, 2])
#print d
d.e = [[4, 5]]
self.assertEqual(5., d['B'].e)
def test_data_assignment(self):
print self.RPD
# set only values
self.RPD['Mx'] = [1.1, 1.2, 1.3, 1.4]
print self.RPD
# set values and errors
self.RPD['Mx'] = [[[1.1, 0.11]], [[1.2, 0.12]], [[1.3, 0.13]], [[1.4, 0.14]]]
print self.RPD
