def __init__(self, obj: pd.DataFrame, type_str: str, source: str,
options: GraphOptions, **kwargs):
options = copy.copy(options)
options.INDEX_NODES = False
options.COLUMN_NODES = False
options.INDEX_NAME_NODES = False
options.INDEX_EDGES = False
options.INDEX_NAME_EDGES = False
super().__init__(obj, type_str, source, options, **kwargs)
def test_index_name_nodes(self):
df = pd.DataFrame({
'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
'baz': [1, 2, 3, 4, 5, 6]
})
output = df.pivot(index='foo', columns='bar', values='baz')
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.INDEX_NAME_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = False
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df], output)
index_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.INDEX_NAME
]
column_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.COL_INDEX_NAME
]
self.assertEqual(len(index_name_nodes), 1)
self.assertEqual(len(column_name_nodes), 1)
def test_no_spurious_for_idx_arg(self):
df = pd.DataFrame([[5, 2], [2, 3], [2, 0]], columns=["A", "B"])
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = True
options.INFLUENCE_EDGES = False
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df, df.columns], df)
index_type_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.INDEX
]
column_type_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.COLUMN
]
self.assertEqual(len(index_type_nodes), 6)
self.assertEqual(len(column_type_nodes), 4)
def test_index_name_equality_edges(self):
df = pd.DataFrame({
'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
'baz': [1, 2, 3, 4, 5, 6]
})
output = df.pivot(index='foo', columns='bar', values='baz')
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.INDEX_NAME_NODES = True
options.ADJACENCY_EDGES = False
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = False
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df], output)
inp_col_nodes = [
node for node in rel_graph.nodes if
node.ntype == GraphNodeType.COLUMN and node.source.startswith("I")
]
out_idx_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.INDEX_NAME
and node.source.startswith("O")
]
out_col_idx_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.COL_INDEX_NAME
and node.source.startswith("O")
]
def check_edge_exists(in_node: GraphNode, out_node: GraphNode,
graph: RelationGraph):
for e in graph.edges:
if (e.node1 == in_node
and e.node2 == out_node) or (e.node1 == out_node
and e.node2 == in_node):
return True
return False
inp_foo_node = [i for i in inp_col_nodes
if i.identifier == '[-1,0]'][0]
inp_bar_node = [i for i in inp_col_nodes
if i.identifier == '[-1,1]'][0]
out_foo_node = [
i for i in out_idx_name_nodes if i.identifier == '[-1,-1]'
][0]
out_bar_node = [
i for i in out_col_idx_name_nodes if i.identifier == '[-1,-1]'
][0]
self.assertTrue(
check_edge_exists(inp_foo_node, out_foo_node, rel_graph))
self.assertTrue(
check_edge_exists(inp_bar_node, out_bar_node, rel_graph))
def test_groupby_has_artifacts(self):
df = pd.DataFrame([[5, 2], [2, 3], [2, 0]], columns=["A", "B"])
output = df.groupby(by="A")
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df], output)
index_type_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.INDEX
]
column_type_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.COLUMN
]
self.assertEqual(len(index_type_nodes), 6)
self.assertEqual(len(column_type_nodes), 6)
def process(cls, raw_data: Dict):
if raw_data is None:
return None
try:
graph = RelationGraph(GraphOptions())
inputs = raw_data['inputs']
output = raw_data['output']
graph.from_input_output(inputs, output)
encoding = graph.get_encoding()
encoding['label'] = raw_data['function_sequence']
return encoding
except SilentException:
return None
except Exception as e:
try:
logger.warn("Failed for {}".format(raw_data))
logging.exception(e)
return None
except:
pass
return None
def iter_func_seqs(self) -> Generator[List[BaseGenerator], None, None]:
generators: Dict[str, BaseGenerator] = load_generators()
if self.model_store is None or 'function-model' not in self.model_store:
model = ModelStore({'function-model': self.model_path})
else:
model = self.model_store
if self.use_old_featurization:
from autopandas_v2.ml.featurization_old.featurizer import RelationGraph
from autopandas_v2.ml.featurization_old.options import GraphOptions
else:
from autopandas_v2.ml.featurization.featurizer import RelationGraph
from autopandas_v2.ml.featurization.options import GraphOptions
options = GraphOptions()
graph: RelationGraph = RelationGraph(options)
graph.from_input_output(self.iospec.inputs, self.iospec.output)
encoding = graph.get_encoding(get_mapping=False)
str_seqs, probs = list(
zip(*model.predict_graphs('function-model', [encoding],
top_k=self.top_k)[0]))
str_seqs = [i.split(':') for i in str_seqs]
model.close()
for str_seq in str_seqs:
result = [generators[i] for i in str_seq]
if self.typecheck(result, self.iospec.output):
logger.info(str_seq)
yield result
else:
logger.warn("Skipping", str_seq)
def test_basic_max(self):
input_df = pd.DataFrame([[1, 2], [2, 3], [2, 0]])
input_00 = GraphNode("I0", '[0,0]', get_node_type(input_df.iat[0, 0]))
input_01 = GraphNode("I0", '[0,1]', get_node_type(input_df.iat[0, 1]))
input_10 = GraphNode("I0", '[1,0]', get_node_type(input_df.iat[1, 0]))
input_11 = GraphNode("I0", '[1,1]', get_node_type(input_df.iat[1, 1]))
input_20 = GraphNode("I0", '[2,0]', get_node_type(input_df.iat[2, 0]))
input_21 = GraphNode("I0", '[2,1]', get_node_type(input_df.iat[2, 1]))
output_df = pd.DataFrame([[2, 3]])
output_00 = GraphNode("O0", '[0,0]', get_node_type(output_df.iat[0,
0]))
output_01 = GraphNode("O0", '[0,1]', get_node_type(output_df.iat[0,
1]))
options = GraphOptions()
options.NODE_TYPES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([input_df], output_df)
rel_graph_edges = rel_graph.edges
# positional edges
positional_edges = [
GraphEdge(input_00, input_01, GraphEdgeType.ADJACENCY),
GraphEdge(input_00, input_10, GraphEdgeType.ADJACENCY),
GraphEdge(input_10, input_11, GraphEdgeType.ADJACENCY),
GraphEdge(input_10, input_20, GraphEdgeType.ADJACENCY),
GraphEdge(input_20, input_21, GraphEdgeType.ADJACENCY),
GraphEdge(input_01, input_11, GraphEdgeType.ADJACENCY),
GraphEdge(input_11, input_21, GraphEdgeType.ADJACENCY),
GraphEdge(output_00, output_01, GraphEdgeType.ADJACENCY)
]
for edge in positional_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
# equality edges
equality_edges = [
GraphEdge(input_10, output_00, GraphEdgeType.EQUALITY),
GraphEdge(input_20, output_00, GraphEdgeType.EQUALITY),
GraphEdge(input_01, output_00,
GraphEdgeType.EQUALITY), # redundant
GraphEdge(input_11, output_01, GraphEdgeType.EQUALITY)
]
for edge in equality_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
def test_groupby_input(self):
df = pd.DataFrame({
"Name": ["Alice", "Bob", "Mallory", "Mallory", "Bob", "Mallory"],
"City": [
"Seattle", "Seattle", "Portland", "Seattle", "Seattle",
"Portland"
]
})
input_ = df.groupby("Name")
output = input_.count().reset_index()
options = GraphOptions()
options.NODE_TYPES = True
options.ADJACENCY_EDGES = False
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([input_], output)
rel_graph_edges = rel_graph.edges
alice_nodes_in = [GraphNode("I0_0", '[0,0]', GraphNodeType.STR)]
alice_nodes_out = [GraphNode("O0", '[0,0]', GraphNodeType.STR)]
bob_nodes_in = [
GraphNode("I0_1", '[0,0]', GraphNodeType.STR),
GraphNode("I0_1", '[1,0]', GraphNodeType.STR)
]
bob_nodes_out = [GraphNode("O0", '[1,0]', GraphNodeType.STR)]
mallory_nodes_in = [
GraphNode("I0_2", '[0,0]', GraphNodeType.STR),
GraphNode("I0_2", '[1,0]', GraphNodeType.STR),
GraphNode("I0_2", '[2,0]', GraphNodeType.STR)
]
mallory_nodes_out = [GraphNode("O0", '[2,0]', GraphNodeType.STR)]
def check_edges(in_nodes, out_nodes):
for in_node in in_nodes:
for out_node in out_nodes:
edge = GraphEdge(in_node, out_node, GraphEdgeType.EQUALITY)
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
check_edges(alice_nodes_in, alice_nodes_out)
check_edges(bob_nodes_in, bob_nodes_out)
check_edges(mallory_nodes_in, mallory_nodes_out)
def predict(self, dpoints: List[Tuple[List[Any], Any]], with_confidence=True) -> List[List[Tuple[str, float]]]:
relgraphs = []
for dpoint in dpoints:
inputs, output = dpoint
graph = RelationGraph(GraphOptions())
graph.from_input_output(inputs, output)
relgraphs.append(graph.get_encoding(get_mapping=False))
return self.predict_graphs(relgraphs, with_confidence=with_confidence)
def test_dict(self):
input_df = pd.DataFrame([[1, 2], [3, 4]])
input_00 = GraphNode("I0", '[0,0]', get_node_type(input_df.iat[0, 0]))
input_01 = GraphNode("I0", '[0,1]', get_node_type(input_df.iat[0, 1]))
input_10 = GraphNode("I0", '[1,0]', get_node_type(input_df.iat[1, 0]))
input_11 = GraphNode("I0", '[1,1]', get_node_type(input_df.iat[1, 1]))
output = {"A": [1, 3], "B": [2, 4]}
output_00 = GraphNode("O0", '[0,0]', get_node_type(output['A'][0]))
output_01 = GraphNode("O0", '[0,1]', get_node_type(output['B'][0]))
output_10 = GraphNode("O0", '[1,0]', get_node_type(output['A'][1]))
output_11 = GraphNode("O0", '[1,1]', get_node_type(output['B'][1]))
options = GraphOptions()
options.NODE_TYPES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([input_df], output)
rel_graph_edges = rel_graph.edges
positional_edges = [
GraphEdge(input_00, input_01, GraphEdgeType.ADJACENCY),
GraphEdge(input_00, input_10, GraphEdgeType.ADJACENCY),
GraphEdge(input_10, input_11, GraphEdgeType.ADJACENCY),
GraphEdge(input_01, input_11, GraphEdgeType.ADJACENCY),
GraphEdge(output_00, output_01, GraphEdgeType.ADJACENCY),
GraphEdge(output_00, output_10, GraphEdgeType.ADJACENCY),
GraphEdge(output_10, output_11, GraphEdgeType.ADJACENCY),
GraphEdge(output_01, output_11, GraphEdgeType.ADJACENCY)
]
for edge in positional_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
equality_edges = [
GraphEdge(input_00, output_00, GraphEdgeType.EQUALITY),
GraphEdge(input_10, output_10, GraphEdgeType.EQUALITY),
GraphEdge(input_01, output_01, GraphEdgeType.EQUALITY),
GraphEdge(input_11, output_11, GraphEdgeType.EQUALITY)
]
for edge in equality_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
def process(cls, raw_data: Dict):
if raw_data is None:
return None
try:
inputs = raw_data['inputs']
output = raw_data['output']
intermediates = raw_data['intermediates']
program: Program = raw_data['program']
function_seq = raw_data['function_sequence']
unused_inputs = set(range(len(inputs)))
unused_intermediates = set()
encodings = []
for depth, func in enumerate(function_seq, 1):
graph = RelationGraph(GraphOptions())
depth_inputs = [inputs[i] for i in unused_inputs]
depth_intermediates = [
intermediates[i] for i in unused_intermediates
]
graph_inputs = depth_inputs + depth_intermediates
graph.from_input_output(graph_inputs, output)
encoding = graph.get_encoding()
encoding['label'] = func
encodings.append(encoding)
unused_inputs -= program.call_seq[depth -
1].get_used_inputs()
unused_intermediates -= program.call_seq[
depth - 1].get_used_intermediates()
unused_intermediates.add(depth - 1)
return encodings
except SilentException:
return None
except Exception as e:
try:
logger.warn("Failed for {}".format(raw_data))
logging.exception(e)
return None
except:
pass
return None
def test_index_name_nodes_multiindex(self):
df = pd.DataFrame(
[(389.0, 'fly'), (24.0, 'fly'), (80.5, 'run'), (np.nan, 'jump')],
index=pd.MultiIndex.from_tuples([('bird', 'falcon'),
('bird', 'parrot'),
('mammal', 'lion'),
('mammal', 'monkey')],
names=['class', 'name']),
columns=pd.MultiIndex.from_tuples([('speed', 'max'),
('species', 'type')]))
df.columns.names = ['name1', 'name2']
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.INDEX_NAME_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = False
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df], df)
index_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.INDEX_NAME
]
column_name_nodes = [
node for node in rel_graph.nodes
if node.ntype == GraphNodeType.COL_INDEX_NAME
]
self.assertEqual(len(index_name_nodes),
4) # Both in the input and output, so x2
self.assertEqual(len(column_name_nodes),
4) # Both in the input and output, so x2
def test_idx_multi(self):
tuples = [("bar", "one"), ("bar", "two")]
index = pd.MultiIndex.from_tuples(tuples)
data = [[0], [1]]
input_df = pd.DataFrame(data, index=index)
# 0
# bar one 0
# two 1
output_df = input_df.unstack()
# 0
# one two
# bar 0 1
options = GraphOptions()
options.COLUMN_NODES = True
options.INDEX_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([input_df], output_df)
rel_graph_edges = rel_graph.edges
bar_in_0 = GraphNode("I0", '[0,-2]', GraphNodeType.INDEX)
bar_in_1 = GraphNode("I0", '[1,-2]', GraphNodeType.INDEX)
bar_out = GraphNode("O0", '[0,-1]', GraphNodeType.INDEX)
one_in = GraphNode("I0", '[0,-1]', GraphNodeType.INDEX)
two_in = GraphNode("I0", '[1,-1]', GraphNodeType.INDEX)
one_out = GraphNode("O0", '[-1,0]', GraphNodeType.COLUMN)
two_out = GraphNode("O0", '[-1,1]', GraphNodeType.COLUMN)
in_0 = GraphNode("I0", '[0,0]', GraphNodeType.INT)
in_1 = GraphNode("I0", '[1,0]', GraphNodeType.INT)
out_0 = GraphNode("O0", '[0,0]', GraphNodeType.INT)
out_1 = GraphNode("O0", '[0,1]', GraphNodeType.INT)
adjacency_edges = [
GraphEdge(bar_in_0, bar_in_1, GraphEdgeType.ADJACENCY),
GraphEdge(bar_in_0, one_in, GraphEdgeType.ADJACENCY),
GraphEdge(bar_in_1, two_in, GraphEdgeType.ADJACENCY),
GraphEdge(one_in, two_in, GraphEdgeType.ADJACENCY)
]
for edge in adjacency_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
indexing_edges = [
GraphEdge(bar_in_0, in_0, GraphEdgeType.INDEX),
GraphEdge(one_in, in_0, GraphEdgeType.INDEX),
GraphEdge(bar_in_1, in_1, GraphEdgeType.INDEX),
GraphEdge(two_in, in_1, GraphEdgeType.INDEX),
GraphEdge(bar_out, out_0, GraphEdgeType.INDEX),
GraphEdge(bar_out, out_1, GraphEdgeType.INDEX)
]
for edge in indexing_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
equality_edges = [
GraphEdge(bar_in_0, bar_out, GraphEdgeType.EQUALITY),
GraphEdge(bar_in_1, bar_out, GraphEdgeType.EQUALITY),
GraphEdge(one_in, one_out, GraphEdgeType.EQUALITY),
GraphEdge(two_in, two_out, GraphEdgeType.EQUALITY)
]
for edge in equality_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
def test_substr_edges(self):
df = pd.DataFrame({
'foo': ['one', 'one', 'one', 'two', 'two', 'two'],
'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
'baz': [1, 2, 3, 4, 5, 6]
})
out = pd.DataFrame({
"mrr": ["wo", "no"],
'asdasd': ["A_1", "B_4"],
'nostr': [33, 12]
})
options = GraphOptions()
options.SUBSTR_EDGES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([df], out)
def check_edges(in_nodes, out_nodes):
for in_node in in_nodes:
for out_node in out_nodes:
edge = GraphEdge(in_node, out_node, GraphEdgeType.SUBSTR)
self.assertTrue(
edge in rel_graph.edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph.edges))
# test substrings from out to in
two_nodes = [
GraphNode("I0", '[3,0]', GraphNodeType.STR),
GraphNode("I0", '[4,0]', GraphNodeType.STR),
GraphNode("I0", '[5,0]', GraphNodeType.STR)
]
wo_node = GraphNode("O0", '[0,0]', GraphNodeType.STR)
check_edges(two_nodes, [wo_node])
# test substrings from in to out
A_in = [
GraphNode("I0", '[0,1]', GraphNodeType.STR),
GraphNode("I0", '[3,1]', GraphNodeType.STR)
]
A_out = [GraphNode("O0", '[0,1]', GraphNodeType.STR)]
B_in = [
GraphNode("I0", '[1,1]', GraphNodeType.STR),
GraphNode("I0", '[4,1]', GraphNodeType.STR)
]
B_out = [GraphNode("O0", '[1,1]', GraphNodeType.STR)]
check_edges(A_in, A_out)
check_edges(B_in, B_out)
# test substrings involving non-strings
one_in = [
GraphNode("I0", '[0,2]', GraphNodeType.INT),
GraphNode("I0", '[1,-1]', GraphNodeType.INDEX)
]
one_out = [GraphNode("O0", '[0,1]', GraphNodeType.STR)]
four_in = [
GraphNode("I0", '[3,2]', GraphNodeType.INT),
GraphNode("I0", '[4,-1]', GraphNodeType.INDEX)
]
four_out = [GraphNode("O0", '[1,1]', GraphNodeType.STR)]
check_edges(one_in, one_out)
check_edges(four_in, four_out)
# test nothing else
self.assertEqual(
11,
len([
e for e in rel_graph.edges if e.etype == GraphEdgeType.SUBSTR
]))
def debug(self, dpoint: Tuple[List[Any], Any]):
inputs, output = dpoint
graph = RelationGraph(GraphOptions())
graph.from_input_output(inputs, output)
self.debug_graph(graph.get_encoding(get_mapping=False))
def test_column_multi(self):
column_labels = [['bar', 'bar', 'baz', 'baz'],
['one', 'two', 'one', 'two']]
tuples = list(zip(*column_labels))
col_index = pd.MultiIndex.from_tuples(tuples)
data = [[0, 1, 2, 3], [4, 5, 6, 7]]
input_df = pd.DataFrame(data, columns=col_index)
# bar baz
# one two one two
# 0 0 1 2 3
# 1 4 5 6 7
output_df = input_df.stack().reset_index()
# level_0 level_1 bar baz
# 0 0 one 0 2
# 1 0 two 1 3
# 2 1 one 4 6
# 3 1 two 5 7
options = GraphOptions()
options.COLUMN_NODES = True
options.ADJACENCY_EDGES = True
options.EQUALITY_EDGES = True
options.NODE_TYPES = True
options.INDEX_EDGES = True
rel_graph: RelationGraph = RelationGraph(options)
rel_graph.from_input_output([input_df], output_df)
rel_graph_edges = rel_graph.edges
col_nodes = [
[
GraphNode("I0", '[-2,0]', GraphNodeType.COLUMN),
GraphNode("I0", '[-2,1]', GraphNodeType.COLUMN),
GraphNode("I0", '[-2,2]', GraphNodeType.COLUMN),
GraphNode("I0", '[-2,3]', GraphNodeType.COLUMN)
],
[
GraphNode("I0", '[-1,0]', GraphNodeType.COLUMN),
GraphNode("I0", '[-1,1]', GraphNodeType.COLUMN),
GraphNode("I0", '[-1,2]', GraphNodeType.COLUMN),
GraphNode("I0", '[-1,3]', GraphNodeType.COLUMN)
],
]
adjacency_edges = [
GraphEdge(col_nodes[0][0], col_nodes[1][0],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][0], col_nodes[0][1],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[1][0], col_nodes[1][1],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[1][1], col_nodes[1][2],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][1], col_nodes[1][1],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][1], col_nodes[0][2],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][2], col_nodes[1][2],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][2], col_nodes[0][3],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[1][2], col_nodes[1][3],
GraphEdgeType.ADJACENCY),
GraphEdge(col_nodes[0][3], col_nodes[1][3],
GraphEdgeType.ADJACENCY)
]
for edge in adjacency_edges:
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
# indexing edges
input_coli_elems = [[
GraphNode("I0", '[0,0]', GraphNodeType.INT),
GraphNode("I0", '[1,0]', GraphNodeType.INT)
],
[
GraphNode("I0", '[0,1]', GraphNodeType.INT),
GraphNode("I0", '[1,1]', GraphNodeType.INT)
],
[
GraphNode("I0", '[0,2]', GraphNodeType.INT),
GraphNode("I0", '[1,2]', GraphNodeType.INT)
],
[
GraphNode("I0", '[0,3]', GraphNodeType.INT),
GraphNode("I0", '[1,3]', GraphNodeType.INT)
]]
def check_edges(in_nodes, out_nodes, edge_type):
for in_node in in_nodes:
for out_node in out_nodes:
edge = GraphEdge(in_node, out_node, edge_type)
self.assertTrue(
edge in rel_graph_edges,
"Could not find edge %s in set of edges:\n%s" %
(edge, rel_graph_edges))
for i in range(4):
in_nodes = [col_nodes[0][i], col_nodes[1][i]]
out_nodes = input_coli_elems[i]
check_edges(in_nodes, out_nodes, GraphEdgeType.INDEX)
# equality_edges
bars = [col_nodes[0][0], col_nodes[0][1]]
bazs = [col_nodes[0][2], col_nodes[0][3]]
ones = [col_nodes[1][0], col_nodes[1][2]]
twos = [col_nodes[1][1], col_nodes[1][3]]
out_01 = GraphNode("O0", '[0,1]', GraphNodeType.STR)
out_11 = GraphNode("O0", '[1,1]', GraphNodeType.STR)
out_21 = GraphNode("O0", '[2,1]', GraphNodeType.STR)
out_31 = GraphNode("O0", '[3,1]', GraphNodeType.STR)
out_col_2 = GraphNode("O0", '[-1,2]', GraphNodeType.COLUMN)
out_col_3 = GraphNode("O0", '[-1,3]', GraphNodeType.COLUMN)
check_edges(bars, [out_col_2], GraphEdgeType.EQUALITY)
check_edges(bazs, [out_col_3], GraphEdgeType.EQUALITY)
check_edges(ones, [out_01, out_21], GraphEdgeType.EQUALITY)
check_edges(twos, [out_11, out_31], GraphEdgeType.EQUALITY)
