I was using the NumPy np.empty() to get an array with a random value, but it doesn't work when I define a normal np.array() before.
Here is the two functions I used:
import numpy as np
def create_float_array(x):
return np.array([float(x)])
def get_empty_array():
return np.empty((), dtype=np.float).tolist()
Just to test the get_empty_array(), I wrote in the console:
>>> get_empty_array() # Should return a random float
>>> 0.007812501848093234
I was pleased with the result, so I tried this, but it didn't work the way I wanted:
>>> create_float_array(3.1415) # Create a NumPy array with the float given
>>> array([3.1415])
>>> get_empty_array() # Should return another random value in a NumPy array
>>> 3.1415
I am not too sure as to why creating a NumPy array affects the np.empty() method from giving a random value. Apparently, it gives the same value as the value in the np.array(), in this case, 3.1415.
Note that I chose to leave the shape of the np.empty() to nothing for testing purposes, but in reality it would have some shape.
Finally, I know this is not the correct way of getting random values, but I need to use the np.empty() in my program, but don't exactly know why this behaviour occurs.
