Python Tutorial - Python Numpy Roll (np.roll)
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^Downloadable code & more! np.roll
So here we have a random array A that I created earlier.
np.roll is a numpy function that allows you to shift arrays by as many indexes as you desire. Let’s jump into this example and show you how this works.
np.roll(A,1) Now the 1 is in the 10 spot the 10 is in the three spot and so on… As you can see everything has been shifted over to the right by one.
Next let’s see A again. And lets do np.roll but this time we will shift it by two.
Now you might be wondering Why is this useful?
Let me go ahead and show you an application.
Suppose you have an array of points and you want to approximate the derivative or in other words the step at each point. np.roll can help you do that.
We just take A and subtract all the points shifted to the right by one or in other words A - np.roll(A,1)
Now make sure to ignore the first term. If we are finding the difference in 25 points then there will only be 24 differences .
The first term is the difference between the first and last point so it is not significant step. So I like to use the (A - np.roll(A,1))[1:]
So there you have it that is how to use numpy’s np.roll function in python.
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