def mean_f(M):
nodes = listify_nodes(M)
avg = 0
for n in nodes:
avg += f_(n)
return avg / len(nodes)
def median_f(M):
nodes = listify_nodes(M)
nodes.sort(key=f_)
num = len(nodes)
n1 = nodes[math.ceil((num-1)/2)]
n2 = nodes[math.floor((num-1)/2)]
med = (f_(n1)+f_(n2))/2
return med
def find_root(T):
nodes = listify_nodes(T)
max_ = f_(nodes[0])
max_node = nodes[0]
for n in nodes:
if(f_(n) > max_):
max_ = f_(n)
max_node = n
return max_node['name']
def shift_f(M, center = "median"):
if center == "median":
center = median_f(M)
elif center == "mean":
center = mean_f(M)
else:
print("Invalid center parameter. Valid choices are 'median' and 'mean'. Using median for shifting.")
center = median_f(M)
nodes = listify_nodes(M)
for n in nodes:
n['value'] = n['value'] - center
def calc_values_height_reorient(G, pos, angle=None):
#Get the list of node objects
n = listify_nodes(G)
if(angle!=None):
reorient(pos, angle)
#Set all of the function values by height
for i in range(0, len(n)):
n[i]['value'] = height(pos[n[i]['name']], math.pi / 2)
else:
for i in range(0, len(n)):
n[i]['value'] = pos[n[i]['name']][1]
def calc_values_height(G, pos, angle):
direction = [math.cos(angle), math.sin(angle)]
x = direction[0]
y = direction[1]
if(len(direction) > 2 or (x==0 and y==0)):
print("Faulty input direction!")
return
#Get the list of node objects
n = listify_nodes(G)
#Set all of the function values by height
for i in range(0, len(n)):
n[i]['value'] = height(pos[n[i]['name']], angle)
def merge_tree(G, shift=True):
preprocess(G)
#Get the nodes from the networkx graph
nodes = listify_nodes(G)
nodes.sort(key=f_)
#The legendary Merge Tree
M = nx.Graph()
for i in range(0, len(nodes)):
add_node(nodes[i]['name'], G, M)
reduce(M)
if(shift):
shift_f(M)
return M