def create_graphical_representation(steps):
""" from a an OrderedDict of steps create a Graphical reprensetation of the model we'll use """
# Rmk : il faut a priori, mettre les numero de l'etape dans le graph
# + mettre les labels correct
# comme ça on pourra avoir plusieurs noeud avec le meme nom (Ex : Scaler...)
### 1) Split Composion Steps vs Rest
all_composition_steps = []
all_others = []
for (step_name, model_name), var_type in steps.items():
if StepCategories.is_composition_step(step_name):
all_composition_steps.append((step_name, model_name, var_type))
else:
all_others.append((step_name, model_name, var_type))
### 2) Create Graph for non-composition step
new_steps = OrderedDict()
G = nx.DiGraph()
for step_name, model_name, var_type in all_others:
# for name,var_type in steps.items():
unested_var_type = unnest_tuple(var_type)
terminal_nodes = gh.get_terminal_nodes(
G
) # Terminal links : I'll add the new step on one (or more) of those
ending_node_type = {
unnest_tuple(steps[node]): node
for node in terminal_nodes
}
node_name = (step_name, model_name) # 2-uple
if node_name in G.nodes:
raise ValueError("This node already exists '(%s,%s)'" % node_name)
# 1) Soit je rattache le nouveau a UN noeud terminal
# 2) Soit je cree une nouvelle branche (nouveau noeud ratacher a rien)
# 3) Soit je rattache a PLUSIEURS noeud terminaux
elif unested_var_type in ending_node_type:
### 1) I already have a branch of this type
last_node = ending_node_type[unested_var_type]
G = gh.add_node_after(G, node_name, last_node)
### I don't have a branch ###
else:
all_candidates = [(t, n) for t, n in ending_node_type.items()
if tuple_include(t, unested_var_type)]
# I need to look where I want to plug it #
if len(all_candidates) == 0:
### 2) Je dois creer une nouvelle branche : aucun noeud ###
G = gh.add_node_after(G, node_name)
else:
### 3) Je rattache a plusieurs noeuds
### Ici : il faut parfois rajouter un noeud en AMONT, si on a des types qui n'ont pas ete rajouter
types_added = unnest_tuple([t for t, n in all_candidates])
types_not_added = diff(unested_var_type, types_added)
if len(types_not_added) > 0:
name_of_cat = "Selector_%s" % unnest_tuple(types_not_added)
new_node = (name_of_cat, (name_of_cat,
SpecialModels.ColumnsSelector))
G = gh.add_node_after(G, new_node)
new_steps[
new_node] = types_not_added # I also must dynamically add the node to the list of steps
all_candidates = all_candidates + [
(types_not_added, new_node)
]
G = gh.add_node_after(G, node_name,
*[n for t, n in all_candidates])
### 3) Include composition node on top
for step_name, model_name, _ in reversed(all_composition_steps):
starting_nodes = gh.get_starting_nodes(G)
for n in starting_nodes:
G.add_edge((step_name, model_name), n)
### 4) Verify the Graph structure
for (step_name, model_name), _ in steps.items():
if (step_name, model_name) not in G:
raise ValueError("'(%s , %s)' should be in graph" %
(step_name, model_name))
# all nodes were in the steps
for node in G.nodes():
if node not in steps and node not in new_steps:
raise ValueError("'(%s,%s)' shouldn't be in graph" % node)
assert_model_graph_structure(G)
return G, new_steps
def test_tuple_include():
assert tuple_include((1, 2), (1, 2, 3))
assert not tuple_include((1, 2, 3), (1, 2))
assert tuple_include((1, 2, 3), (1, 2, 3))
assert not tuple_include((1, 2, 4), (1, 2, 3))