def test_reject_missing_column(self): for column in DEMAND_POINT_TABLE_COLUMNS: columns = list(DEMAND_POINT_TABLE_COLUMNS) columns.remove(column) table = DataFrame([], columns=columns) with raises(ValidationError): normalize_demand_point_table(table)
def test_reject_missing_value(self): table = DataFrame([ ('a', 1, 2, 3), ], columns=DEMAND_POINT_TABLE_COLUMNS) for column in DEMAND_POINT_TABLE_COLUMNS: t = table.copy() t[column][0] = float('nan') with raises(ValidationError): normalize_demand_point_table(t)
def test_flatten_population_year(self): d = normalize_demand_point_table(DataFrame([ ('a', 1, 1, 1, 2000), ('b', 2, 2, 2, 2000), ('c', 3, 3, 3, 2000), ('c', 3, 3, 4, 2001), ], columns=DEMAND_POINT_TABLE_COLUMNS + ['population_year'])) table = d['demand_point_table'] assert table[table['name'] == 'c']['population'].values[0] == 4
def test_rename_population_year(self): d = normalize_demand_point_table(DataFrame([ ('a', 1, 1, 1, 2000), ('b', 2, 2, 2, 2000), ('c', 3, 3, 3, 2000), ], columns=DEMAND_POINT_TABLE_COLUMNS + ['year'])) table = d['demand_point_table'] assert 'year' not in table.columns assert 'population_year' in table.columns
def test_rename_population_year(self): d = normalize_demand_point_table( DataFrame([ ('a', 1, 1, 1, 2000), ('b', 2, 2, 2, 2000), ('c', 3, 3, 3, 2000), ], columns=DEMAND_POINT_TABLE_COLUMNS + ['year'])) table = d['demand_point_table'] assert 'year' not in table.columns assert 'population_year' in table.columns
def test_flatten_population_year(self): d = normalize_demand_point_table( DataFrame([ ('a', 1, 1, 1, 2000), ('b', 2, 2, 2, 2000), ('c', 3, 3, 3, 2000), ('c', 3, 3, 4, 2001), ], columns=DEMAND_POINT_TABLE_COLUMNS + ['population_year'])) table = d['demand_point_table'] assert table[table['name'] == 'c']['population'].values[0] == 4