def network_properties(command):
subj_props = command['data_parameters']
command = command['network_parameters']
Xs, items, irts, numnodes = rw.readX(subj_props['subject'],
subj_props['category'],
subj_props['fullpath'])
def no_persev(x):
seen = set()
seen_add = seen.add
return [i for i in x if not (i in seen or seen_add(i))]
toydata = rw.Data({
'numx': len(Xs),
'trim': 1,
'jump': 0.0,
'jumptype': "stationary",
'priming': 0.0,
'startX': "stationary"
})
fitinfo = rw.Fitinfo({
'startGraph': "goni_valid",
'goni_size': 2,
'goni_threshold': 2,
'followtype': "avg",
'prior_samplesize': 10000,
'recorddir': "records/",
'prune_limit': 100,
'triangle_limit': 100,
'other_limit': 100
})
if command['network_method'] == "RW":
bestgraph = rw.noHidden(Xs, numnodes)
elif command['network_method'] == "Goni":
bestgraph = rw.goni(Xs, numnodes, td=toydata, valid=0, fitinfo=fitinfo)
elif command['network_method'] == "U-INVITE":
no_persev_Xs = [no_persev(x) for x in Xs
] # U-INVITE doesn't work with perseverations
bestgraph, ll = rw.uinvite(no_persev_Xs,
toydata,
numnodes,
fitinfo=fitinfo,
debug=False)
nxg = nx.to_networkx_graph(bestgraph)
node_degree = np.mean(nxg.degree().values())
nxg_json = jsonGraph(nxg, items)
clustering_coefficient = nx.average_clustering(nxg)
try:
aspl = nx.average_shortest_path_length(nxg)
except:
aspl = "disjointed graph"
return {
"type": "network_properties",
"node_degree": node_degree,
"clustering_coefficient": clustering_coefficient,
"aspl": aspl,
"graph": nxg_json
}
#!/usr/bin/python
import pickle
import numpy as np
import rw
import networkx as nx
import sys
filename = sys.argv[1]
usf_graph, usf_items = rw.read_csv("./snet/USF_animal_subset.snet")
usf_graph_nx = nx.from_numpy_matrix(usf_graph)
usf_numnodes = len(usf_items)
td=rw.Data({
'numx': 3,
'trim': 35})
fh = open(filename,'r')
alldata = pickle.load(fh)
Xs = alldata['datab'][0:10]
graphs = alldata['uinvite_graphs']
items = alldata['items'][0:10]
priordict = alldata['priordict']
# for old pickles. ha, that's kinda funny.
if 'DEFAULTPRIOR' not in priordict.keys():
priordict['DEFAULTPRIOR'] = 0.5
# recompute for halfa... should be identical for a=1
import rw
import networkx as nx
import numpy as np
usf_graph, usf_items = rw.read_csv("./snet/USF_animal_subset.snet")
usf_graph_nx = nx.from_numpy_matrix(usf_graph)
usf_numnodes = len(usf_items)
numsubs = 50
numlists = 3
listlength = 35
numsims = 1
#methods=['rw','goni','chan','kenett','fe']
methods = ['uinvite']
toydata = rw.Data({'numx': numlists, 'trim': listlength})
fitinfo = rw.Fitinfo({
'startGraph': "goni_valid",
'goni_size': 2,
'goni_threshold': 2,
'followtype': "avg",
'prune_limit': np.inf,
'triangle_limit': np.inf,
'other_limit': np.inf
})
#toygraphs=rw.Graphs({
# 'numgraphs': 1,
# 'graphtype': "steyvers",
# 'numnodes': 280,