def make_validation_disconnectivity_graph(system, database):
from pele.utils.disconnectivity_graph import DisconnectivityGraph, database2graph
import matplotlib.pyplot as plt
inputs, targets = get_validation_data()
""" make validation_energy a minimum object"""
pot = system.get_potential()
validation_energy = lambda m: pot.getValidationEnergy(m.coords, inputs, targets)
graph = database2graph(database)
for m in graph.nodes():
m.validation_energy = validation_energy(m)
for u,v,data in graph.edges(data=True):
ts = data["ts"]
ve = max([validation_energy(ts), u.validation_energy, v.validation_energy])
ts.validation_energy = ve
gmin = min(graph.nodes(), key=lambda m:m.energy)
# smin = graph.nodes().sort(key=lambda m:m.energy)
smin = sorted(graph.nodes(), key=lambda m:m.energy)
# gmax = max(graph.nodes(), key=lambda m:m.energy)
labels = dict()
for i,s in enumerate(smin):
if i % 10 == 0: labels[s] = str(i)
# labels = {gmin : "gmin"}
dg = DisconnectivityGraph(graph, nlevels=10, center_gmin=True, energy_attribute="validation_energy", subgraph_size=3)
dg.calculate()
# minimum_to_validation_energy = lambda m: pot.getValidationEnergy(m.coords, inputs, targets)
# dg.color_by_value(validation_energy)
dg.plot()
dg.label_minima(labels)
print labels
plt.show()
# dg.color_by_value(validation_energy)
dg.plot()
dg.label_minima(labels)
print labels
plt.show()
# dg.savefig("/home/ab2111/machine_learning_landscapes/neural_net/dg.png")
from NNSystem import NNSystem
""" load training data"""
inputs = np.loadtxt("../handwriting/X2_100samples.dat")
targets = np.loadtxt("../handwriting/y2_100samples.dat")
from ffnet_validation import get_validation_data
vinputs, vtargets = get_validation_data()
""" define network topology """
conec = mlgraph((inputs.shape[1],10,1))
print inputs.shape
# exit()
net = ffnet(conec)
system = NNSystem(net, inputs, targets)
database = system.create_database(db="../db/db_ffnet_100samples.sqlite")
# make_disconnectivity_graph(system, database, vinputs, vtargets)
# plt.plot(ts.coords,'x')
# plt.plot(ts.eigenvec,'o')
# plt.show()
