Essentially I am creating various arrays to elicit tactile stimulation (string of 0s with 1s when stimulation is delivered) for a random condition where the interval between the stimulation is drawn from a uniform distribution. I am using the following code to create the arrays (which all works fine):
def rand_stim_seconds(array):
lst = list(range(0,10))
random_ints = []
for i in lst: # Creating list containing intervals drawn from distribution.
rand_int = np.random.uniform(0.1, 0.6, 1)
random_ints.append(rand_int)
values = [] # Convert list from seconds into values of array.
for j in random_ints:
d = j * 22050 # Mutiply by sampling frequency.
e = float(d)
f = int(np.round(e))
values.append(f)
add_lst = [0] # Initialise with a value.
for k in values: # Adding a '1' at specific intervals of the array.
add = add_lst[-1] + k
if add > 44100:
break
add_lst.append(add)
print(add_lst)
for l in add_lst[1:]:
array[l] = 1
return array
I am now trying to create 10 arrays using this function which will then output 10 different arrays (called "stim1" "stim2" etc) which will each have a different pattern of stimulation where each interval is randomly drawn. The following code is what I would like to convert into a loop:
rand1 = np.zeros((44100, 1))
rand2 = np.zeros((44100, 1))
rand3 = np.zeros((44100, 1))
rand4 = np.zeros((44100, 1))
rand5 = np.zeros((44100, 1))
rand6 = np.zeros((44100, 1))
rand7 = np.zeros((44100, 1))
rand8 = np.zeros((44100, 1))
rand9 = np.zeros((44100, 1))
rand10 = np.zeros((44100, 1))
stim1 = rand_stim_seconds(rand1)
stim2 = rand_stim_seconds(rand2)
stim3 = rand_stim_seconds(rand3)
stim4 = rand_stim_seconds(rand4)
stim5 = rand_stim_seconds(rand5)
stim6 = rand_stim_seconds(rand6)
stim7 = rand_stim_seconds(rand7)
stim8 = rand_stim_seconds(rand8)
stim9 = rand_stim_seconds(rand9)
stim10 = rand_stim_seconds(rand10)
I need to create new arrays of 0 for each array I wish to create otherwise it overwrites. Does anyone know how to turn the above into a neat loop as I am very aware of how amateur it is (I am new to Python)! Thank you!