def get_graph(d, i):
""" get all graphs from a directory
return [("event<id1>", graph1, size), ...]
"""
files = os.listdir(d)
f = files[i]
return load_graph(d+f)
def get_graphs(d, idxs):
""" get all graphs from a directory
return [("event<id1>", graph1, size), ...]
"""
files = np.array(os.listdir(d))
files = files[idxs]
return [load_graph(d+f) for f in files]
"{0}/{1}".format(model_dir, model) for model in models if job_name in model
]
# load in test graph paths
graph_dir = "/tigress/jdezoort/IN_samples_large/IN_{0}_{1}/".format(
prep, pt_cut)
graph_files = []
if (phi_reflect):
phi_graph_dir = "/tigress/jdezoort/IN_samples_large/IN_{0}_{1}_phi_reflect/".format(
prep, pt_cut)
graph_files += os.listdir(phi_graph_dir)[0:800]
graph_files += os.listdir(graph_dir)
print("len(graph_files)={0}".format(len(graph_files)))
test_graphs = np.array([(int(f.split('_')[0].split('t00000')[1]),
load_graph(graph_dir + f))
for f in graph_files[train_size:]])
# prepare test graphs
size = len(test_graphs)
print("size={0}".format(size))
test_O = [
Variable(torch.FloatTensor(test_graphs[i][1].X)) for i in range(size)
]
test_Rs = [
Variable(torch.FloatTensor(test_graphs[i][1].Ro)) for i in range(size)
]
test_Rr = [
Variable(torch.FloatTensor(test_graphs[i][1].Ri)) for i in range(size)
]
test_Ra = [
def get_graphs(d):
""" get all graphs from a directory
return [("event<id1>", graph1, size), ...]
"""
files = os.listdir(d)
return [load_graph(d + f) for f in files]
graph_dir = '/scratch/gpfs/jdezoort/hitgraphs_2/{}_{}/'.format(
method, pt_cut_str[pt_cut])
truth = {}
purities, efficiencies = [], []
sizes, nodes, edges = [], [], []
for i, evtid in enumerate(evt_ids):
#if (int(evtid.split("00000")[1].split(".")[0]) > 1010): continue
print("evtid", evtid)
#if (i == N_avg): break
print('...', evtid)
# load in graph
graph_path = graph_dir + evtid + '_g000.npz'
graph = load_graph(graph_path)
X, Ra = graph.X, graph.Ra
Ri, Ro = graph.Ri, graph.Ro
y = graph.y
size = sys.getsizeof(X) + sys.getsizeof(Ra)
size += sys.getsizeof(Ri) + sys.getsizeof(Ro) + sys.getsizeof(y)
for j, Ri_row in enumerate(Ri):
Ri_row = Ri_row[y > 0.5]
if (np.sum(Ri_row) > 1):
print("ERREREREREREROR!!!!")
print("graph.X: {}, graph.Ra: {}, graph.Ri: {}, graph.y: {}".format(
graph.X.shape, graph.Ra.shape, graph.Ri.shape, graph.y.shape))
n_edges, n_nodes = Ri.shape[0], Ri.shape[1]