Rounding values in a numpy array resulting from matrix calculation

Question

I have some calculation involving two matrices both represented in numpy arrays.

After the calculation, i obtain a vector of floats represented in another numpy array.

I want to round up/down the values in this resultant vector, e.g. if the calculation gives:

array([1.33333, 2.56, 9.99999, 16.0])

then it should be rounded to:

array([1, 3, 10, 16])

What is the fastest way to do this?

unutbu · Accepted Answer · 2012-11-02 19:23:03Z

10

NumPy arrays have a round method:

In [73]: x = np.array([1.33333, 2.56, 9.99999, 16.0])

In [74]: x.round()
Out[76]: array([  1.,   3.,  10.,  16.])

answered Nov 2, 2012 at 19:23

unutbu

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2 Comments

MLister Over a year ago

does this method depend on the type of floats in the array? e.g. float32 vs. float64?

unutbu Over a year ago

If x is of dtype float32, then x.round() will also be of dtype float32. And similarly for float64. The round method is not implemented for some dtypes, for example, string dtypes.

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