values = (data_["input"][:, 0]).astype(int)

text = [chr(ord("0")+i) for i in values]

Z, I = str_to_bmp(text, size = size)

data = np.zeros(Z.shape[1], dtype = [ ("input", float, (1 + Z.shape[0],)),

("output", float, ( 1,))])

data["input"][:, :-1] = Z.T

n = Z.shape[1]//len(text)

data["input"][:,-1] = np.repeat(data_["input"][:, 1], n)

data["output"][:, 0] = np.repeat(data_["output"], n) / 10

"""

values = np.array(values)

if len(values.shape) == 1:

values = values.reshape(len(values), 1)

n_values = values.shape[1]

gates = np.array(gates)

if len(gates.shape) == 1:

gates = gates.reshape(len(gates), 1)

n_gates = gates.shape[1]

size = len(values)

data = np.zeros(size, dtype = [ ("input", float, (n_values + n_gates,)),

("output", float, ( n_gates,))])

# Input signals

data["input"][:, 0:n_values ] = values

data["input"][:, n_values: ] = gates

wm = np.zeros(n_gates)

# If no last activity set gate=1 at time t=0

if last is None:

wm[:] = data["input"][0, 0]

data["input"][0, 1:] = 1

else:

wm[:] = last

# Output value(s) according to gates

for i in range(size):

for j in range(n_gates):

# Output at time of gate is not changed

# data["output"][i,j] = wm[j]

if data["input"][i,n_values+j] > 0:

wm[j] = data["input"][i,0]

# Output at time of gate is changed

data["output"][i,j] = wm[j]