def make_edges(latlondf, **kwargs):
edgelambda = lambda x: find_closest(x, latlondf, *kwargs)
n = latlondf.apply(edgelambda, axis = 1)
edges = pd.DataFrame(columns=['node1', 'node2'])
for node1 in n.index:
for node2 in n.ix[node1]:
newrow = {'node1':node1, 'node2':node2}
edges = edges.append(newrow, ignore_index=True)
edges.index.name = 'edge'
return edges.astype('int')
def make_edges(latlondf, **kwargs):
edgelambda = lambda x: find_closest(x, latlondf, *kwargs)
n = latlondf.apply(edgelambda, axis=1)
edges = pd.DataFrame(columns=['node1', 'node2'])
for node1 in n.index:
for node2 in n.ix[node1]:
newrow = {'node1': node1, 'node2': node2}
edges = edges.append(newrow, ignore_index=True)
edges.index.name = 'edge'
return edges.astype('int')
def edgelambda(x):
"""featurize.find_closest for use in apply to dataframe"""
return find_closest(x, latlondf)