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Difference between the methods mod and fmod in NumPy

schedule Aug 12, 2023
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local_offer
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Both `mod(~)` and `fmod(~)` methods compute the remainder of given two arrays of dividend and divisor.

What differentiates `mod(~)` from Numpy's `fmod(~)` is confusingly not whether or not one is for floating numbers; they are both capable of parsing floating numbers. The defining difference is how they handle negative numbers.

Let's take a look at a simple example.

``` x = [3, 8.5, -7]np.mod(x, 3) array([0. , 2.5, 2. ]) ```

Here, `mod(-7,3)=2`, which is equivalent to Python's `%` implementation `(-7%3=2)`. Also notice how 8.5, which is a floating number, was parsed correctly.

Now, let's do the same thing using the fmod method:

``` x = [3, 8.5, -7]np.fmod(x, 3) array([ 0. , 2.5, -1. ]) ```

Here, we see that `fmod(-7,3)=-1`, which is a different answer from above. In fact, Numpy's `fmod(~)` method follows the main C library's `fmod(~)` implementation.

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