def get_length_in_ring_rough(exp, t, args):
length = 0
for edge in exp.nx_graph[t].edges:
edge_obj = Edge(Node(edge[0], exp), Node(edge[1], exp), exp)
is_in_end = np.all(is_in_study_zone(edge_obj.end, t, 1000, 150))
is_in_begin = np.all(is_in_study_zone(edge_obj.begin, t, 1000, 150))
if is_in_end and is_in_begin:
length += np.linalg.norm(edge.end.pos(t) - edge.begin.pos(t)) * 1.725
return ("tot_length_study_rough", length)
def get_length_study_zone(exp, t, args):
length = 0
for edge in exp.nx_graph[t].edges:
edge_obj = Edge(Node(edge[0], exp), Node(edge[1], exp), exp)
is_in_end = np.all(is_in_study_zone(edge_obj.end, t, 1000, 150))
is_in_begin = np.all(is_in_study_zone(edge_obj.begin, t, 1000, 150))
if is_in_end and is_in_begin:
length += get_length_um_edge(edge_obj, t)
return ("tot_length_study", length)
def get_hulls(exp, ts):
hulls = []
for t in ts:
nx_graph = exp.nx_graph[t]
threshold = 0.1
S = [
nx_graph.subgraph(c).copy()
for c in nx.connected_components(nx_graph)
]
selected = [
g for g in S
if g.size(weight="weight") * len(g.nodes) / 10**6 >= threshold
]
polys = Polygon()
if len(selected) >= 0:
area_max = 0
for g in selected:
nodes = np.array([
node.pos(t) for node in exp.nodes if node.is_in(t)
and np.all(is_in_study_zone(node, t, 1000, 150)) and (
node.label in g.nodes)
])
if len(nodes) > 3:
hull = spatial.ConvexHull(nodes)
poly = Polygon(
[nodes[vertice] for vertice in hull.vertices])
area_hull = poly.area * 1.725**2 / (1000**2)
polys = polys.union(poly)
print(t, len(selected), polys.area)
hulls.append(polys)
return hulls
def get_hyphae_in_ring(hull1, hull2, t, exp):
hyphae = [
hyph for hyph in exp.hyphaes
if hyph.end.is_in(t) and hull2.contains(Point(hyph.end.pos(t)))
and not hull1.contains(Point(hyph.end.pos(t)))
and np.all(is_in_study_zone(hyph.end, t, 1000, 200))
]
return hyphae
def get_nodes_in_ring(hull1, hull2, t, exp):
nodes = [
node for node in exp.nodes
if node.is_in(t) and hull2.contains(Point(node.pos(t)))
and not hull1.contains(Point(node.pos(t)))
and np.all(is_in_study_zone(node, t, 1000, 200))
]
return nodes
def get_num_nodes_study_zone(exp, t, args):
return (
"num_nodes_study",
len(
[
node
for node in exp.nodes
if node.is_in(t) and np.all(is_in_study_zone(node, t, 1000, 150))
]
),
)
def get_area_study_zone(exp, t, args):
nodes = np.array(
[
node.pos(t)
for node in exp.nodes
if node.is_in(t) and np.all(is_in_study_zone(node, t, 1000, 150))
]
)
if len(nodes) > 3:
hull = spatial.ConvexHull(nodes)
poly = Polygon([nodes[vertice] for vertice in hull.vertices])
area = poly.area * 1.725**2 / (1000**2)
else:
area = 0
return ("area_study", area)
def get_area_separate_connected_components(exp, t, args):
nx_graph = exp.nx_graph[t]
threshold = 0.1
S = [nx_graph.subgraph(c).copy() for c in nx.connected_components(nx_graph)]
selected = [
g for g in S if g.size(weight="weight") * len(g.nodes) / 10**6 >= threshold
]
area = 0
for g in selected:
nodes = np.array(
[
node.pos(t)
for node in exp.nodes
if node.is_in(t)
and np.all(is_in_study_zone(node, t, 1000, 150))
and (node.label in g.nodes)
]
)
if len(nodes) > 3:
hull = spatial.ConvexHull(nodes)
poly = Polygon([nodes[vertice] for vertice in hull.vertices])
area += poly.area * 1.725**2 / (1000**2)
return ("area_sep_comp", area)
def gets_out_of_ROI(hyph, args):
for t in hyph.ts:
if not np.all(is_in_study_zone(hyph.end, t, 1000, 150)):
return ('out_of_ROI', t)
return ('out_of_ROI', None)
def in_ROI(hypha, t, tp1, args):
return ('in_ROI', str(np.all(is_in_study_zone(hypha.end, t, 1000, 150))))