def test_GN_06():
conf = hearsay.Parser()
conf.load_config(['nran'], ['1'])
G = hearsay.C3Net(conf)
G.set_parameters()
A = [20000, 30000]
S = [10000, 12000]
D = [10000]
lista = [A, S, D]
G.set_parameters(spars=lista)
res = G.run(interactive=True)
R = hearsay.Results(G)
R.load()
res = R.redux_2d()
assert len(res) == 2
def test_results_01():
conf = hearsay.Parser()
conf.load_config(['nran'], ['1'])
G = hearsay.C3Net(conf)
G.set_parameters()
A = [20000, 30000]
S = [10000, 12000]
D = [10000]
lista = [A, S, D]
G.set_parameters(spars=lista)
res = G.run(interactive=True)
R = hearsay.Results(G)
R.load()
res = R.show_ccns(0, True)
assert isinstance(res, dict)
config = hearsay.Parser('F2b.ini')
config.load_config()
G = hearsay.C3Net(config)
G.set_parameters(df)
G.run()
# 2) Leer las simulaciones :::::::::::::::::::::
dfa = pd.read_csv('F2b.csv')
config = hearsay.Parser('F2b.ini')
config.load_config()
G = hearsay.C3Net(config)
G.set_parameters(dfa)
R = hearsay.Results(G)
R.load()
res = R.redux()
ib = res['lI']
fig = plt.figure()
ax = fig.add_subplot()
for k, inbox in enumerate(ib):
imax = max(inbox)
breaks = np.array(range(imax + 1)) + 0.5
hy, hx = np.histogram(inbox, breaks, density=True)
xx = breaks[:-1] + 0.5
yy = np.cumsum(hy)
lbl = (f"A={R.params.iloc[k]['tau_awakening']},"