def set_circuit_size(self, new_size):
MEMS_CTRNN.set_circuit_size(self, new_size)
self.inp_alpha = np.full(7, 1.0, dtype=float)
self.inp_beta = np.full(7, 0.0, dtype=float)
self.out_alpha = np.full(2, 1.0, dtype=float)
self.out_beta = np.full(2, 0.0, dtype=float)
self.outputs = np.full(2, 0.0, dtype=float)
def test_CTRNN_load(self):
c = MEMS_CTRNN()
c.load('sample.ns')
self.assertEqual(c.size, 14)
self.assertEqual(c.mem_h, 2.6e-6)
self.assertEqual(c.mem_rho, 2330)
self.assertEqual(c.mem_ythr, -3e-5)
self.assertEqual(int(c.taus[0]), 1)
self.assertEqual(int(c.v_biases[0]), -3)
self.assertEqual(int(c.hs[0]), 2)
self.assertEqual(c.weights[13][0], 0)
def __init__(self,
new_size=0,
stability_acc=0.001,
stability_hist_bucket=3,
stability_min_iteration=7,
stability_max_iteration=150):
self.stability_acc = stability_acc
self.stability_hist_bucket = stability_hist_bucket
self.stability_min_iteration = stability_min_iteration
self.stability_max_iteration = stability_max_iteration
MEMS_CTRNN.__init__(self, new_size)
def euler_step_with_stability(self,
step_size=None,
use_dim_equation=False,
save_detail=False,
use_defelection_feedback=False,
return_states_info=False):
states_info = []
if save_detail is True:
outfile = open('duration_analysis.csv', 'a')
outfile_csv = csv.writer(outfile,
delimiter=',',
quotechar="'",
quoting=csv.QUOTE_MINIMAL)
a = [0] * self.stability_hist_bucket
b = [0] * self.stability_hist_bucket
l = self.stability_hist_bucket
t = time.time()
for i in range(self.stability_max_iteration):
MEMS_CTRNN.euler_step(self, step_size, use_dim_equation,
use_defelection_feedback)
if save_detail is True:
outfile_csv.writerow([
t, i, step_size, self.states[-2],
self.states[-1], '-', a[(i - l) % l], b[(i - l) % l], '-',
(i - l) % l, '-', a[(i - l) % l] - b[(i - l) % l], '-', a,
b
])
if return_states_info is True:
states_info.append(list(self.states))
if i >= self.stability_min_iteration and \
abs(a[(i - l) % l] - self.states[-2]) < self.stability_acc and \
abs(b[(i - l) % l] - self.states[-1]) < self.stability_acc:
# print(i)
break
elif i >= l:
a[(i - l) % l] = self.states[-2]
b[(i - l) % l] = self.states[-1]
if i >= 10:
print(i)
if save_detail is True:
outfile.close()
return states_info
def test_CTRNN_save(self):
s_fname = 'sample2.ns'
c = MEMS_CTRNN()
c.load('sample.ns')
c.save(s_fname)
c2 = MEMS_CTRNN()
c2.load(s_fname)
self.assertEqual(c.size, c2.size)
self.assertEqual(c.mem_h, c2.mem_h)
self.assertEqual(c.mem_rho, c2.mem_rho)
self.assertEqual(c.weights[13][0], c2.weights[13][0])
self.assertEqual(c.mem_ythr, c2.mem_ythr)
os.remove(s_fname)
print('The MEMCTRN {} is stablized in iteration {} for '.format(t, i) +
'input1 = {}, input2 = {} and max_variation= {}'.format(
i1, i2, max_variation))
return True
elif i >= l:
a[(i - l) % l] = c.states[-2]
b[(i - l) % l] = c.states[-1]
return False
if __name__ == "__main__":
f_name = 'sample_2n.ns'
c = MEMS_CTRNN()
c.load(f_name)
c1 = MEMS_CTRNN()
c1.load(f_name)
c2 = MEMS_CTRNN()
c2.load(f_name)
c.print_model()
c.print_model_abstract()
mem_wm = 131675.65242702136
run_duration = 0.01
step_size = 1 / mem_wm
with open('debug.csv', 'w') as fi:
def print_model_abstract(self):
MEMS_CTRNN.print_model_abstract(self)
self.print_vagent_variables()
def print_model(self):
MEMS_CTRNN.print_model(self)
self.print_vagent_variables()
import numpy as np
import csv
def gen_input(t):
i1 = 80 if t > 200 else 0
i2 = 180 if t > 400 else 0
i2 = i2 if t < 800 else 0
return (i1, i2)
if __name__ == "__main__":
f_name = 'sample_2n.ns'
c = MEMS_CTRNN()
c.load(f_name)
c.print_model()
c.print_model_abstract()
run_duration = 1000
step_size = 1
in1 = []
in2 = []
out1 = []
out2 = []
v_mem1 = []
v_mem2 = []
with open('debug.csv', 'w') as fi: