def test_results_graph_measures():
view_graph = _twonode_viewgraph()
# Mock flow data
bundle_flows = {
0:
pd.DataFrame.from_records([
('a', 'b1', 'm', 4, 2),
('a', 'b2', 'm', 7, 1),
],
columns=('source', 'target', 'material',
'value', 'another_measure')),
}
# Results assuming measure = 'value'
Gr, groups = results_graph(view_graph, bundle_flows)
assert list(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^*', ('*', '*'), {
'measures': {
'value': 11
},
'original_flows': [0, 1],
'bundles': [0]
}),
]
# Results using measure = 'another_measure'
Gr, groups = results_graph(view_graph,
bundle_flows,
measures='another_measure')
assert list(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^*', ('*', '*'), {
'measures': {
'another_measure': 3
},
'original_flows': [0, 1],
'bundles': [0]
}),
]
# Results using measure = 'value' but averaging 'another_measure'
Gr, groups = results_graph(view_graph,
bundle_flows,
measures={
'value': 'sum',
'another_measure': 'mean'
})
assert list(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^*', ('*', '*'), {
'measures': {
'value': 11,
'another_measure': 1.5
},
'original_flows': [0, 1],
'bundles': [0]
}),
]
def test_results_graph_material_key():
# Mock flow data
flows = pd.DataFrame.from_records([
('a1', 'c1', 'm', 'long', 3),
('a1', 'c1', 'n', 'long', 1),
],
columns=('source', 'target',
'material_type', 'shape',
'value'))
view_graph = LayeredGraph()
view_graph.add_node('a', node=ProcessGroup())
view_graph.add_node('c', node=ProcessGroup())
view_graph.add_edge('a', 'c', bundles=[0])
view_graph.ordering = Ordering([[['a']], [['c']]])
bundle_flows = {0: flows}
material_partition = Partition.Simple('material_type', ['m', 'n'])
shape_partition = Partition.Simple('shape', ['long', 'thin'])
# Partition based on material_type
view_graph.edges['a', 'c']['flow_partition'] = material_partition
Gr, groups = results_graph(view_graph, bundle_flows)
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'c^*', ('m', '*'), {
'measures': {
'value': 3
},
'original_flows': [0],
'bundles': [0]
}),
('a^*', 'c^*', ('n', '*'), {
'measures': {
'value': 1
},
'original_flows': [1],
'bundles': [0]
}),
]
# Partition based on shape
view_graph.edges['a', 'c']['flow_partition'] = shape_partition
Gr, groups = results_graph(view_graph, bundle_flows)
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'c^*', ('long', '*'), {
'measures': {
'value': 4
},
'original_flows': [0, 1],
'bundles': [0]
}),
]
def test_results_graph_with_extra_or_not_enough_groups():
# Mock flow data
bundle_flows = {
0:
pd.DataFrame.from_records([
('a1', 'b1', 'm', 3),
('a2', 'b1', 'm', 1),
],
columns=('source', 'target', 'material',
'value'))
}
# Group 'a3' not used. ProcessGroup 'a2' isn't in any group.
node_a = ProcessGroup(partition=Partition.Simple('process', ['a1', 'a3']))
node_b = ProcessGroup(partition=Partition.Simple('process', ['b1']))
view_graph = LayeredGraph()
view_graph.add_node('a', node=node_a)
view_graph.add_node('b', node=node_b)
view_graph.add_edges_from([
('a', 'b', {
'bundles': [0]
}),
])
view_graph.ordering = Ordering([[['a']], [['b']]])
# Do partition based on flows stored in bundles
Gr, groups = results_graph(view_graph, bundle_flows)
assert set(Gr.nodes()) == {'a^a1', 'a^_', 'b^b1'}
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^_', 'b^b1', ('*', '*'), {
'measures': {
'value': 1
},
'original_flows': [1],
'bundles': [0]
}),
('a^a1', 'b^b1', ('*', '*'), {
'measures': {
'value': 3
},
'original_flows': [0],
'bundles': [0]
}),
]
assert Gr.ordering == Ordering([
[['a^a1', 'a^_']],
[['b^b1']],
])
def test_results_graph_bands():
bundles = [
Bundle('a', 'b'),
]
# Mock flow data
bundle_flows = {
bundles[0]:
pd.DataFrame.from_records([
('a1', 'b1', 'm', 3),
],
columns=('source', 'target', 'material',
'value'))
}
view_graph = LayeredGraph()
view_graph.add_node('a', node=ProcessGroup())
view_graph.add_node('b', node=ProcessGroup())
view_graph.add_edges_from([
('a', 'b', {
'bundles': bundles
}),
])
view_graph.ordering = Ordering([
[['a'], []],
[[], ['b']],
])
# Do partition based on flows stored in bundles
Gr, groups = results_graph(view_graph, bundle_flows)
assert Gr.ordering == Ordering([
# rank 1
[['a^*'], []],
# rank 2
[[], ['b^*']],
])
def test_results_graph_samples():
view_graph = _threenode_viewgraph()
# Mock flow data with multiple samples. NB missing data for sample 1 in
# bundle 1.
bundle_flows = {
0:
pd.DataFrame.from_records([
('a', 'b1', 'm', 0, 2),
('a', 'b1', 'm', 1, 3),
('a', 'b2', 'm', 0, 1),
('a', 'b2', 'm', 1, 1),
],
columns=('source', 'target', 'material',
'sample', 'value')),
1:
pd.DataFrame.from_records([
('a', 'c1', 'm', 1, 3),
],
columns=('source', 'target', 'material',
'sample', 'value')),
}
# Aggregation function
index = pd.Index(np.arange(2))
def measure(group):
agg = group.groupby('sample').value.agg('sum')
d = {'value': agg.reindex(index).fillna(0).values}
return d
# Results
Gr, groups = results_graph(view_graph, bundle_flows, measures=measure)
assert len(Gr.edges()) == 2
assert np.allclose(Gr['a^*']['b^*']['*', '*']['measures']['value'], [3, 4])
assert np.allclose(Gr['a^*']['c^*']['*', '*']['measures']['value'], [0, 3])
def test_results_graph_overall():
material_partition = Partition.Simple('material', ['m', 'n'])
c_partition = Partition.Simple('process', ['c1', 'c2'])
view_graph = LayeredGraph()
view_graph.add_node('a', node=ProcessGroup(title='Node a'))
view_graph.add_node('b', node=ProcessGroup())
view_graph.add_node('c', node=ProcessGroup(partition=c_partition))
view_graph.add_node('via', node=Waypoint(partition=material_partition))
view_graph.add_edges_from([
('a', 'via', {
'bundles': [0],
'flow_partition': material_partition
}),
('b', 'via', {
'bundles': [1],
'flow_partition': material_partition
}),
('via', 'c', {
'bundles': [0, 1],
'flow_partition': material_partition
}),
])
view_graph.ordering = Ordering([[['a', 'b']], [['via']], [['c']]])
# Mock flow data
bundle_flows = {
0:
pd.DataFrame.from_records([
('a1', 'c1', 'm', 3),
('a2', 'c1', 'n', 1),
],
index=(0, 1),
columns=('source', 'target', 'material',
'value')),
1:
pd.DataFrame.from_records([
('b1', 'c1', 'm', 1),
('b1', 'c2', 'm', 2),
('b1', 'c2', 'n', 1),
],
index=(2, 3, 4),
columns=('source', 'target', 'material',
'value'))
}
# Do partition based on flows stored in bundles
Gr, groups = results_graph(view_graph, bundle_flows)
assert sorted(Gr.nodes(data=True)) == [
('a^*', {
'direction': 'R',
'type': 'process',
'title': 'Node a'
}),
('b^*', {
'direction': 'R',
'type': 'process',
'title': 'b'
}),
('c^c1', {
'direction': 'R',
'type': 'process',
'title': 'c1'
}),
('c^c2', {
'direction': 'R',
'type': 'process',
'title': 'c2'
}),
('via^m', {
'direction': 'R',
'type': 'group',
'title': 'm'
}),
('via^n', {
'direction': 'R',
'type': 'group',
'title': 'n'
}),
]
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'via^m', ('m', '*'), {
'measures': {
'value': 3
},
'original_flows': [0],
'bundles': [0]
}),
('a^*', 'via^n', ('n', '*'), {
'measures': {
'value': 1
},
'original_flows': [1],
'bundles': [0]
}),
('b^*', 'via^m', ('m', '*'), {
'measures': {
'value': 3
},
'original_flows': [2, 3],
'bundles': [1]
}),
('b^*', 'via^n', ('n', '*'), {
'measures': {
'value': 1
},
'original_flows': [4],
'bundles': [1]
}),
('via^m', 'c^c1', ('m', '*'), {
'measures': {
'value': 4
},
'original_flows': [0, 2],
'bundles': [0, 1]
}),
('via^m', 'c^c2', ('m', '*'), {
'measures': {
'value': 2
},
'original_flows': [3],
'bundles': [0, 1]
}),
('via^n', 'c^c1', ('n', '*'), {
'measures': {
'value': 1
},
'original_flows': [1],
'bundles': [0, 1]
}),
('via^n', 'c^c2', ('n', '*'), {
'measures': {
'value': 1
},
'original_flows': [4],
'bundles': [0, 1]
}),
]
assert Gr.ordering == Ordering([
[['a^*', 'b^*']],
[['via^m', 'via^n']],
[['c^c1', 'c^c2']],
])
# Only includes groups where the title is not the same as the single node
# title
assert groups == [
{
'id': 'via',
'title': '',
'type': 'group',
'nodes': ['via^m', 'via^n']
},
{
'id': 'c',
'title': '',
'type': 'process',
'nodes': ['c^c1', 'c^c2']
},
]
def test_results_graph_time_partition():
time_partition = Partition.Simple('time', [1, 2])
view_graph = LayeredGraph()
view_graph.add_node('a', node=ProcessGroup())
view_graph.add_node('b', node=ProcessGroup())
view_graph.add_edges_from([
('a', 'b', {
'bundles': [0]
}),
])
view_graph.ordering = Ordering([[['a']], [['b']]])
# Mock flow data
bundle_flows = {
0:
pd.DataFrame.from_records([
('a1', 'b1', 'm', 1, 3),
('a2', 'b1', 'n', 1, 1),
('a2', 'b2', 'n', 1, 2),
('a1', 'b1', 'm', 2, 1),
('a1', 'b1', 'n', 2, 3),
],
columns=('source', 'target', 'material',
'time', 'value')),
}
# Do partition based on flows stored in bundles
Gr, groups = results_graph(view_graph,
bundle_flows,
time_partition=time_partition)
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^*', ('*', '1'), {
'measures': {
'value': 6
},
'original_flows': [0, 1, 2],
'bundles': [0]
}),
('a^*', 'b^*', ('*', '2'), {
'measures': {
'value': 4
},
'original_flows': [3, 4],
'bundles': [0]
}),
]
# Now add a material partition too
material_partition = Partition.Simple('material', ['m', 'n'])
Gr, groups = results_graph(view_graph, bundle_flows, material_partition,
time_partition)
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^*', ('m', '1'), {
'measures': {
'value': 3
},
'original_flows': [0],
'bundles': [0]
}),
('a^*', 'b^*', ('m', '2'), {
'measures': {
'value': 1
},
'original_flows': [3],
'bundles': [0]
}),
('a^*', 'b^*', ('n', '1'), {
'measures': {
'value': 3
},
'original_flows': [1, 2],
'bundles': [0]
}),
('a^*', 'b^*', ('n', '2'), {
'measures': {
'value': 3
},
'original_flows': [4],
'bundles': [0]
}),
]
def test_results_graph_elsewhere_stubs():
b_partition = Partition.Simple('process', ['b1', 'b2'])
view_graph = LayeredGraph()
view_graph.add_node('a', node=ProcessGroup())
view_graph.add_node('b',
node=ProcessGroup(partition=b_partition),
from_elsewhere_bundles=[1])
view_graph.add_edge('a', 'b', bundles=[0])
view_graph.ordering = Ordering([[['a']], [['b']]])
# Mock flow data
bundle_flows = {
0:
pd.DataFrame.from_records([
('a1', 'b1', 'm', 3),
('a2', 'b1', 'n', 1),
],
index=(0, 1),
columns=('source', 'target', 'material',
'value')),
1:
pd.DataFrame.from_records([
('x1', 'b1', 'm', 1),
('x3', 'b2', 'n', 5),
],
index=(2, 3),
columns=('source', 'target', 'material',
'value'))
}
# Do partition based on flows stored in bundles
Gr, groups = results_graph(view_graph, bundle_flows)
assert sorted(Gr.nodes(data=True)) == [
('a^*', {
'direction': 'R',
'type': 'process',
'title': 'a'
}),
('b^b1', {
'direction':
'R',
'type':
'process',
'title':
'b1',
'from_elsewhere_edges': [
(('*', '*'), {
'measures': {
'value': 1
},
'original_flows': [2],
'bundles': [1]
}),
]
}),
('b^b2', {
'direction':
'R',
'type':
'process',
'title':
'b2',
'from_elsewhere_edges': [
(('*', '*'), {
'measures': {
'value': 5
},
'original_flows': [3],
'bundles': [1]
}),
]
}),
]
assert sorted(Gr.edges(keys=True, data=True)) == [
('a^*', 'b^b1', ('*', '*'), {
'measures': {
'value': 4
},
'original_flows': [0, 1],
'bundles': [0]
}),
]
