For my astronomy homework, I need to simulate the elliptical orbit of a planet around a sun. To do this, I need to use a for loop to repeatedly calculate the motion of the planet. However, every ti... More on stackoverflow.com

If it is an array of ints, you won’t be able to “convert” one in that array to a float since the array only accepts ints. You could still get the score as a float by doing Float score = scores[i].score; More on reddit.com

What does the rest of the file look like? Looping over lines in your file should give you strings like “[1,2,3,4,5]” which you can parse by stripping brackets, splitting on commas, and mapping int or float to each thing. More on reddit.com

Take a look at the first answer to this StackOverflow post, it might help you https://stackoverflow.com/questions/1735025/how-to-normalize-a-numpy-array-to-within-a-certain-range It is pretty much what JadeSerpant is suggesting though. I don't know enough about WAVs, but you'll have been given a range of floating point values from a-->b (probably with a=0), and you want to map them to the range of integers (-32768 --> +32767), which are the limits for a signed 16 bit number. So you need to get your numbers and do some maths to shift and rescale your range to fit. (You can think of it as the integers (0 --> 65,535) shifted down by (65,535+1)/2=32768 if that helps) Assuming we want the mid-point of your range a --> b to map to exactly 0 after conversion (silence in our WAV), then we want something like: midpoint = (a+b)/2 extent = (b-a) # newsignal = (signal-midpoint)/(0.5*extent) # Gives range of floating point values from a minimum of -1 to a maximum of +1. newsignal2 = 32767*(signal-midpoint)/(0.5*extent) # Gives range of floating point values from a minimum of -32767 to a maximum of +32767. Note that I multiply by 32767 and not 32768. Otherwise, the +1 would become 32768, which would be too big. It is easier to see that this works in the simpler case where a=0, i.e., if the signal is from 0 --> b. midpoint = b/2 extent = b # newsignal = (signal-b/2)/(0.5*b) # Any values of 0 become (-b/2)/(0.5b) = -1, any value of b become (b-b/2)/(0.5b) = +1 newsignal2 = 32767*(signal-b/2)/(0.5*b) # Gives range of floating point values from a minimum of -32767 to a maximum of +32767. If you did the scaling and shifting differently to occupy the whole int16 range fully, then the midpoint of the signal cannot be exactly 0 in the wav file. While I'm not aware of a clever numpy function to do all this for you, you are already relying on using numpy arrays for the above code to work. Doing this with just Python would be harder. Before writing your data to a file, you will also likely need to round to the nearest integer and cast the values of the array to the int16 integer data type. As casting does a crude truncating rounding for you, you can probably just do: newsignal3 = newsignal2.astype('int16') and be fine, but you'll have to take a look and find out. More on reddit.com