Question

Often, I am building an array by iterating through some data, e.g.:

my_array = []
for n in range(1000):
  # do operation, get value 
  my_array.append(value)
# cast to array
my_array = array(my_array)

I find that I have to first build a list and then cast it (using “array”) to an array. Is there a way around these? All these casting calls clutter the code… how can I iteratively build up “my_array”, with it being an array from the start?

Answer 1

If i understand your question correctly, this should do what you want:

# the array passed into your function
ax = NP.random.randint(10, 99, 20).reshape(5, 4)

# just define a function to operate on some data
fnx = lambda x : NP.sum(x)**2

# apply the function directly to the numpy array
new_row = NP.apply_along_axis(func1d=fnx, axis=0, arr=ax)

# 'append' the new values to the original array
new_row = new_row.reshape(1,4)
ax = NP.vstack((ax, new_row))