def test_validation_multiindex_unique(orca_session):
"""
Table validation should pass with a MultiIndex whose combinations are unique.
"""
d = {'id': [1, 1, 1], 'sub_id': [1, 2, 3], 'value': [4, 4, 4]}
orca.add_table('tab', pd.DataFrame(d).set_index(['id', 'sub_id']))
validate_table('tab')
def test_validation_table_not_registered(orca_session):
"""
Table validation should raise a ValueError if the table isn't registered.
"""
try:
validate_table('tab')
except ValueError as e:
print(e)
return
pytest.fail() # fail is ValueError wasn't raised
def test_validation_index_unique(orca_session):
"""
Table validation should pass if the index is unique.
These tests of the validate() method generate Orca tables directly, which is just a
shortcut for testing -- the intended use is for the method to validate the table
loaded by the TableStep.
"""
d = {'id': [1, 2, 3], 'value': [4, 4, 4]}
orca.add_table('tab', pd.DataFrame(d).set_index('id'))
validate_table('tab')
def test_validation_index_vs_other_columns(orca_session):
"""
Table validation should compare the 'households.building_id' column to
'buildings.build_id'.
"""
d = {'building_id': [1, 2, 3, 4], 'value': [4, 4, 4, 4]}
orca.add_table('buildings', pd.DataFrame(d).set_index('building_id'))
d = {'household_id': [1, 2, 3], 'building_id': [2, 3, 5]}
orca.add_table('households', pd.DataFrame(d).set_index('household_id'))
validate_table('buildings')
def test_validation_reciprocal_false(orca_session):
"""
This combination should not produce any column comparisons.
"""
d = {'building_id': [1, 2, 3, 4], 'value': [4, 4, 4, 4]}
orca.add_table('buildings', pd.DataFrame(d).set_index('building_id'))
d = {'household_id': [1, 2, 3], 'building_id': [2, 3, 5]}
orca.add_table('households', pd.DataFrame(d).set_index('household_id'))
print("Begin reciprocal test")
validate_table('buildings', reciprocal=False)
print("End reciprocal test")
def test_validation_index_not_unique(orca_session):
"""
Table validation should raise a ValueError if the index is not unique.
"""
d = {'id': [1, 1, 3], 'value': [4, 4, 4]}
orca.add_table('tab', pd.DataFrame(d).set_index('id'))
try:
validate_table('tab')
except ValueError as e:
print(e)
return
pytest.fail() # fail if ValueError wasn't raised
def test_validation_index_unnamed(orca_session):
"""
Table validation should raise a ValueError if index is unnamed.
"""
d = {'id': [1, 1, 3], 'value': [4, 4, 4]}
orca.add_table('tab',
pd.DataFrame(d)) # generates auto index without a name
try:
validate_table('tab')
except ValueError as e:
print(e)
return
pytest.fail() # fail if ValueError wasn't raised
def test_validation_multiindex_not_unique(orca_session):
"""
Table validation should raise a ValueError if the MultiIndex combinations are not
unique.
"""
d = {'id': [1, 1, 1], 'sub_id': [2, 2, 3], 'value': [4, 4, 4]}
orca.add_table('tab', pd.DataFrame(d).set_index(['id', 'sub_id']))
try:
validate_table('tab')
except ValueError as e:
print(e)
return
pytest.fail() # fail if ValueError wasn't raised
def test_validation_duplicate_colnames(orca_session):
"""
Table validation should raise a ValueError if columns share a name with index.
"""
d = {'id1': [1, 1, 3], 'id2': [3, 3, 9], 'value': [4, 4, 4]}
df = pd.DataFrame(d).set_index(['id1', 'id2'])
df['id2'] = [10, 10,
10] # column with same name as one of the multi-index levels
orca.add_table('tab', df)
try:
validate_table('tab')
except ValueError as e:
print(e)
return
pytest.fail() # fail if ValueError wasn't raised
def test_validation_with_multiindexes(orca_session):
"""
Here, table validation should compare 'choice_table.[home_tract,work_tract]' to
'distances.[home_tract,work_tract]'.
"""
d = {
'obs_id': [1, 1, 1, 1],
'alt_id': [1, 2, 3, 4],
'home_tract': [55, 55, 55, 55],
'work_tract': [17, 46, 19, 55]
}
orca.add_table('choice_table',
pd.DataFrame(d).set_index(['obs_id', 'alt_id']))
d = {
'home_tract': [55, 55, 55],
'work_tract': [17, 18, 19],
'dist': [1, 1, 1]
}
orca.add_table('distances',
pd.DataFrame(d).set_index(['home_tract', 'work_tract']))
validate_table('choice_table')