Finding the nearest value from a given value in an array is a common task in data analysis and scientific computing. NumPy is a popular Python library for numerical computing that provides efficient and powerful functions for manipulating arrays. NumPy provides several methods to find the nearest value in an array, which are mentioned below:
1. Using "np.argpartition()":
- The code creates a NumPy array
arr
and variable with value6
, this value is not in the array but we will find the one closest to it. - It then calculates the absolute difference between each element of the array and the given value using
np.abs(arr - value)
. - The
np.argpartition()
function is used to get the index of the element with the smallest absolute difference. The1
in the function call specifies that we only need the index of the first smallest element. - Finally, the index is used to retrieve the nearest value from the array, which is printed using
print(nearest)
.
2. Using "np.searchsorted()":
- The initialization of variables
arr
andvalue
is done in the same way as in the method above. - The
searchsorted()
method of the NumPy array is used to find the index wherevalue
would be inserted intoarr
to maintain sorted order. This method returns the index of the first element inarr
that is greater thanvalue
. - A boolean conditional expression is used to get the nearest value to where,
→ if the index is greater than 0 (meaning thatvalue
is not less than the first element ofarr
) and
→ either the index is equal to the length ofarr
(meaning thatvalue
is greater than or equal to the last element ofarr
) or
→ the absolute difference betweenvalue
and the element at the index before the found index is less than the absolute difference betweenvalue
and the element at the found index, then the value at the index before the found index is assigned tonearest
. Otherwise, the value at the found index is assigned tonearest
.
With these functions, it is easy to find the nearest value from a given value in a NumPy array efficiently and accurately.