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graph_stats.py
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import json
import argparse
import os.path as osp
import networkx as nx
import operator
import matplotlib.pyplot as plt
class graph_stats:
def __init__(self, data, merged):
"""
Create a graph from a given .json and compute statistics on that.
:param data: <dict> Loaded database as a dictionary of samples.
"""
self.G = nx.DiGraph()
self.missing_family = []
self.missing_subfamily = []
self.missing_genus = []
self.missing_specific_epithet = []
self.missing_genus_specific_epithet = []
label_levels = ['family', 'subfamily', 'genus', 'specific_epithet']
if merged:
label_levels = ['family', 'subfamily', 'genus_specific_epithet']
for sample_id in data:
sample = data[sample_id]
if "" not in [sample['family'], sample['subfamily'], sample['genus'], sample['specific_epithet']]:
self.G.add_edge(sample['family'], sample['subfamily'])
if not merged:
self.G.add_edge(sample['subfamily'], sample['genus'])
self.G.add_edge(sample['genus'], sample['specific_epithet'])
else:
self.G.add_edge(sample['subfamily'], '{}_{}'.format(sample['genus'], sample['specific_epithet']))
data[sample_id]['genus_specific_epithet'] = '{}_{}'.format(sample['genus'], sample['specific_epithet'])
for label_level in label_levels:
if 'count' not in self.G.nodes[sample[label_level]]:
self.G.nodes[sample[label_level]]['count'] = 0
self.G.nodes[sample[label_level]]['level'] = label_level
self.G.nodes[sample[label_level]]['count'] += 1
for label_level in label_levels:
if sample[label_level] == "":
getattr(self, 'missing_{}'.format(label_level)).append(sample_id)
self.family_nodes = [node_data for node_data in self.G.nodes.data() if node_data[1]['level'] == 'family']
self.subfamily_nodes = [node_data for node_data in self.G.nodes.data() if node_data[1]['level'] == 'subfamily']
self.genus_nodes = [node_data for node_data in self.G.nodes.data() if node_data[1]['level'] == 'genus']
self.specific_epithet_nodes = [node_data for node_data in self.G.nodes.data() if
node_data[1]['level'] == 'specific_epithet']
self.genus_specific_epithet_nodes = [node_data for node_data in self.G.nodes.data()
if node_data[1]['level'] == 'genus_specific_epithet']
family_names = [node[0] for node in self.family_nodes]
subfamily_names = [node[0] for node in self.subfamily_nodes]
genus_names = [node[0] for node in self.genus_nodes]
species_names = [node[0] for node in self.specific_epithet_nodes]
genus_species_names = [node[0] for node in self.genus_specific_epithet_nodes]
colors = []
for node in self.G.nodes():
if node in family_names:
colors.append('b')
elif node in subfamily_names:
colors.append('r')
elif node in genus_names:
colors.append('y')
else:
colors.append('m')
nx.draw_networkx(self.G, arrows=True, node_size=100, node_color=colors)
plt.show()
# for i, node in enumerate(self.G.nodes()):
# print(self.G.node[node])
nodes = [{'name': str(node), 'count': self.G.node[node]['count'], 'level': self.G.node[node]['level'],
'color': colors[i]} for i, node in enumerate(self.G.nodes())]
links = [{'source': u[0], 'target': u[1]}
for u in self.G.edges()]
with open('visualize_graph/graph_for_d3_{}.json'.format('merged' if merged else ''), 'w') as f:
json.dump({'nodes': nodes, 'links': links}, f, indent=4)
self.in_degree = self.G.in_degree
self.out_degree = self.G.out_degree
self.print_stats()
def get_max_degree(self, level=None):
"""
Function to compute the max in and out degree for a given hierarchy level, otherwise computes them for the
complete graph.
:param level: <str> One of the following: ['family', 'subfamily', 'genus', 'specific_epithet', None]
:return: <int, int> max_in_degree, max_out_degree
"""
if level not in ['family', 'subfamily', 'genus', 'specific_epithet', None]:
raise ValueError('Invalid option {}. Use one of {}'
.format(level, ['family', 'subfamily', 'genus', 'specific_epithet', None]))
if level is None:
max_in_degree = max(dict(self.in_degree).items(), key=operator.itemgetter(1))
max_out_degree = max(dict(self.out_degree).items(), key=operator.itemgetter(1))
print("Max in degree: {}".format(max_in_degree))
print("Max out degree: {}".format(max_out_degree))
else:
d = dict(self.in_degree)
max_in_degree = max({f[0]: d[f[0]] for f in getattr(self, '{}_nodes'.format(level))}.items(),
key=operator.itemgetter(1))
print("Max in degree for {}: {}".format(level, max_in_degree))
d = dict(self.out_degree)
max_out_degree = max({f[0]: d[f[0]] for f in getattr(self, '{}_nodes'.format(level))}.items(),
key=operator.itemgetter(1))
print("Max out degree for {}: {}".format(level, max_out_degree))
return max_in_degree, max_out_degree
def print_stats(self):
"""
Print stats for the loaded dataset.
:return: None
"""
print("Number of edges: {}".format(self.G.size()))
print("Number of nodes: {}".format(len(self.G)))
print("Number of families: {}".format(len(self.family_nodes)))
print("Number of subfamilies: {}".format(len(self.subfamily_nodes)))
print("Number of genera: {}".format(len(self.genus_nodes)))
print("Number of specific epithets: {}".format(len(self.specific_epithet_nodes)))
for label_level in ['family', 'subfamily', 'genus', 'specific_epithet']:
max_val = None
for node in getattr(self, '{}_nodes'.format(label_level)):
if max_val is None:
max_val = node
if max_val[1]['count'] < node[1]['count']:
max_val = node
print("Maximum specimens belong to the {} {}".format(label_level, max_val))
self.get_max_degree(level='family')
self.get_max_degree(level='subfamily')
self.get_max_degree(level='genus')
self.get_max_degree(level='specific_epithet')
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--mini", help='Use the mini database for testing/debugging.', action='store_true')
parser.add_argument("--merged", help='Use the merged database for testing/debugging.', action='store_true')
args = parser.parse_args()
infile = 'sub_database'
if args.mini:
infile = 'mini_database'
if osp.isfile('../database/{}.json'.format(infile)):
with open('../database/{}.json'.format(infile)) as json_file:
data = json.load(json_file)
else:
print("File does not exist!")
exit()
gs = graph_stats(data, args.merged)