def test_aggregation_avg(self):
columnName = TupleValueExpression(col_name=0)
aggr_expr = AggregationExpression(ExpressionType.AGGREGATION_AVG, None,
columnName)
tuples = Batch(pd.DataFrame({
0: [1, 2, 3],
1: [2, 3, 4],
2: [3, 4, 5]
}))
self.assertEqual(2, aggr_expr.evaluate(tuples, None))
def test_aggregation_max(self):
columnName = TupleValueExpression(col_name=0)
aggr_expr = AggregationExpression(
ExpressionType.AGGREGATION_MAX,
None,
columnName
)
tuples = Batch(pd.DataFrame(
{0: [1, 2, 3], 1: [2, 3, 4], 2: [3, 4, 5]}))
batch = aggr_expr.evaluate(tuples, None)
self.assertEqual(3, batch.frames.iloc[0][0])
def test_if_expr_tree_is_equal(self):
const_exp1 = ConstantValueExpression(0)
const_exp2 = ConstantValueExpression(0)
columnName1 = TupleValueExpression(col_name='DATA')
columnName2 = TupleValueExpression(col_name='DATA')
aggr_expr1 = AggregationExpression(ExpressionType.AGGREGATION_AVG,
None, columnName1)
aggr_expr2 = AggregationExpression(ExpressionType.AGGREGATION_AVG,
None, columnName2)
cmpr_exp1 = ComparisonExpression(ExpressionType.COMPARE_NEQ,
aggr_expr1, const_exp1)
cmpr_exp2 = ComparisonExpression(ExpressionType.COMPARE_NEQ,
aggr_expr2, const_exp2)
self.assertEqual(cmpr_exp1, cmpr_exp2)
def test_aggregation_min(self):
columnName = TupleValueExpression(0)
aggr_expr = AggregationExpression(
ExpressionType.AGGREGATION_MIN,
None,
columnName
)
frame_1 = Frame(1, np.ones((1, 1)), None)
frame_2 = Frame(2, 2 * np.ones((1, 1)), None)
frame_3 = Frame(3, 3 * np.ones((1, 1)), None)
outcome_1 = Prediction(frame_1, ["car", "bus"], [0.5, 0.6])
outcome_2 = Prediction(frame_2, ["bus"], [0.5, 0.6])
outcome_3 = Prediction(frame_3, ["car", "train"], [0.5, 0.6])
input_batch = FrameBatch(frames=[
frame_1,
frame_2,
frame_3,
], info=None)
expected_value = 1
output_value = aggr_expr.evaluate(input_batch)
self.assertEqual(expected_value, output_value)
def test_should_return_false_for_unequal_expressions(self):
const_exp1 = ConstantValueExpression(0)
const_exp2 = ConstantValueExpression(1)
func_expr = FunctionExpression(lambda x: x + 1)
cmpr_exp = ComparisonExpression(ExpressionType.COMPARE_NEQ, const_exp1,
const_exp2)
tuple_expr = TupleValueExpression(col_name='id')
aggr_expr = AggregationExpression(ExpressionType.AGGREGATION_MAX, None,
tuple_expr)
logical_expr = LogicalExpression(ExpressionType.LOGICAL_OR, cmpr_exp,
cmpr_exp)
self.assertNotEqual(const_exp1, const_exp2)
self.assertNotEqual(cmpr_exp, const_exp1)
self.assertNotEqual(func_expr, cmpr_exp)
self.assertNotEqual(tuple_expr, aggr_expr)
self.assertNotEqual(aggr_expr, tuple_expr)
self.assertNotEqual(tuple_expr, cmpr_exp)
self.assertNotEqual(logical_expr, cmpr_exp)
def test_aggregation_max(self):
columnName = TupleValueExpression(col_idx=0)
aggr_expr = AggregationExpression(ExpressionType.AGGREGATION_MAX, None,
columnName)
tuples = [[1, 2, 3], [2, 3, 4], [3, 4, 5]]
self.assertEqual(3, aggr_expr.evaluate(tuples, None))
