Each Python module has it's own namespace, so if some functions in test1.py depends on numpy, you have to import numpy in test1.py:
# test1.py
import numpy as np
def fnc():
    return np.ndarray([1,2,3,4])
If test.py doesn't directly use numpy, you don't have to import it again, ie:
# test.py
# NB: do NOT use 'from xxx import *' in production code, be explicit
# about what you import
from test1 import fnc
if __name__ == "__main__":
    result = fnc()
    print(result)
Now if test.py also wants to use numpy, it has to import it too - as I say, each module has it's own namespace:
# test.py
# NB: do NOT use 'from xxx import *' in production code, be explicit
# about what you import
import numpy as np 
from test1 import fnc
def other():
    return np.ndarray([3, 44, 5])
if __name__ == "__main__":
    result1 = fnc()
    print(result1)
    result2 = other()
    print(result2)
Note that if you were testing your code in a python shell, just modifying the source and re-importing it in the python shell will not work (modules are only loaded once per process, subsequent imports fetch the already loaded module from the sys.modules cache), so you have to exit the shell and open a new one.