def test_set_edge_label_options(test_data):
G = base.GenotypePhenotypeGraph()
# Get available options
avail_options = copy.deepcopy(G.edge_label_options)
# Set individually to 1.
for a in avail_options:
G.set_edge_label_options(**{a:1})
assert G.edge_label_options[a] == 1
# Set all at once and make sure they match
G.set_edge_label_options(**avail_options)
for a in avail_options:
assert G.edge_label_options[a] == avail_options[a]
# pass bad options
bad_options = ["not_a_key"]
for b in bad_options:
with pytest.raises(KeyError):
G.set_edge_label_options(**{b:1})
# test exotic edge_label setting
d = test_data[0]
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
def test_gpm_getter():
G = base.GenotypePhenotypeGraph()
assert G.gpm is None
gpm = gpmap.GenotypePhenotypeMap(["AA"])
G.add_gpm(gpm)
assert G.gpm is gpm
def test_constructor(test_data):
G = base.GenotypePhenotypeGraph()
assert isinstance(G,nx.DiGraph)
assert G.gpm is None
attributes = [G.node_options,G.edge_options,
G.node_label_options,G.edge_label_options]
for a in attributes:
assert type(a) is dict
assert len(a) > 0
with pytest.raises(KeyError):
G.node_options["nodelist"]
with pytest.raises(KeyError):
G.node_options["edgelist"]
assert G.node_options["node_size"] == G._default_node_size
assert G.edge_options["node_size"] == G._default_node_size
assert G.edge_options["arrows"] == False
# Test bad gpm inputs
bad_inputs = ["stupid",1,[],(1,),1.1]
for b in bad_inputs:
with pytest.raises(TypeError):
G = base.GenotypePhenotypeGraph(gpm=b)
# Send in good genotype phenotype map. does not have weights.
d = test_data[0]
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
G = base.GenotypePhenotypeGraph(gpm=gpm)
G.gpm.data
G.gpm.neighbors
# Pass bad edge weight columns
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
with pytest.raises(ValueError):
G = base.GenotypePhenotypeGraph(gpm=gpm,edge_weight_column="not_good")
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
with pytest.raises(ValueError):
G = base.GenotypePhenotypeGraph(gpm=gpm,edge_weight_column=1.1)
# Should work and have weighted edges
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
G = base.GenotypePhenotypeGraph(gpm=gpm)
for g in G.edges:
G.edges[g[0],g[1]]["weight"]
def test_set_node_label_options():
G = base.GenotypePhenotypeGraph()
# Get available options
avail_options = copy.deepcopy(G.node_label_options)
# Set individually to 1.
for a in avail_options:
G.set_node_label_options(**{a:1})
assert G.node_label_options[a] == 1
# Set all at once and make sure they match
G.set_node_label_options(**avail_options)
for a in avail_options:
assert G.node_label_options[a] == avail_options[a]
# pass bad options
bad_options = ["not_a_key"]
for b in bad_options:
with pytest.raises(KeyError):
G.set_node_label_options(**{b:1})
def test_edge_label_options_getter():
G = base.GenotypePhenotypeGraph()
assert type(G.edge_label_options) is dict
def test_node_options_getter():
G = base.GenotypePhenotypeGraph()
assert type(G.node_options) is dict
def test_add_gpm(test_data):
# Check for bad value checking
G = base.GenotypePhenotypeGraph()
bad_values = ["test",[],1.3,(1,2),base.GenotypePhenotypeGraph()]
for b in bad_values:
with pytest.raises(TypeError):
G.add_gpm(b)
for d in test_data:
G = base.GenotypePhenotypeGraph()
assert G.gpm is None
# Build with bad edge_weight_column, no neighbors
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
with pytest.raises(ValueError):
G.add_gpm(gpm,edge_weight_column="not_yet")
# Build with bad edge_weight_column, pre-built neighbors
G = base.GenotypePhenotypeGraph()
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
gpm.get_neighbors()
gpm.neighbors.loc[:,"now_here"] = np.ones(len(gpm.neighbors))
with pytest.raises(ValueError):
G.add_gpm(gpm,edge_weight_column="not_yet")
# Add with good edge_weight_column, pre-built neighbors
G = base.GenotypePhenotypeGraph()
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
gpm.get_neighbors()
gpm.neighbors.loc[:,"now_here"] = np.ones(len(gpm.neighbors))
ret = G.add_gpm(gpm,edge_weight_column="now_here")
assert ret.edge_weight_column == "now_here"
# No prebuilt neighbors
G = base.GenotypePhenotypeGraph()
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
ret = G.add_gpm(gpm)
# Test return of self
assert G is ret
# Make sure neighbors and neighbor weight construted correctly
assert G.edge_weight_column == "weight"
assert G.gpm.neighbors is not None
G.gpm.neighbors.weight
# Make sure gpm is now attached (as pointer, not copy)
assert G.gpm is gpm
# Make sure data loaded into nodes as expected
assert len(G.nodes) == len(G.gpm.data)
keys = ["genotype","binary","n_mutations","name"]
for i in range(len(G.nodes)):
for k in keys:
assert G.nodes[i][k] == G.gpm.data.iloc[i][k]
# Make sure neighbors were generated. (Do not check that the neighbors
# are right. For this, check the test_gpm.py tests.)
assert G.gpm.neighbors is not None
# Make sure edges match neighbors
assert len(G.gpm.neighbors) == len(G.edges)
for i in range(len(G.gpm.neighbors)):
edge = G.gpm.neighbors.edge[i]
G.edges[edge]
# Build neighbors differently -- make sure this still worked without
# generating neighbors on the fly.
G = base.GenotypePhenotypeGraph()
gpm = gpmap.GenotypePhenotypeMap(d["genotype"])
gpm.get_neighbors("hamming",cutoff=3)
pregen_edges = np.copy(gpm.neighbors.edge)
G.add_gpm(gpm)
assert len(pregen_edges) == len(G.gpm.neighbors.edge)
for i in range(len(G.gpm.neighbors)):
edge = G.gpm.neighbors.edge[i]
G.edges[edge]