Get index of the element nearest to the given value [duplicate]

Question

This question already has answers here:

Find nearest value in numpy array (20 answers)

Closed 9 years ago.

The given value is 6.6. But the value 6.6 is not in the array (data below). But the nearest value to the given value is 6.7. How can I get this position?

import numpy as np
data = np.array([[2.0, 3.0, 6.5, 6.5, 12.0],[1,2,3,4,5]],dtype=float)

Answer 1

This is the simplest way I think.

>>> data = np.array([[2.0, 3.0, 6.5, 6.5, 12.0],[1,2,3,4,5]], dtype=float)
>>> data2 = np.fabs(data - 6.6)
>>> np.unravel_index(data2.argmin(), data2.shape)
(0, 2)

See np.argmin and np.unravel_index function.

Answer 2

You can get like this:

data[(np.fabs(data-6.6)).argmin(axis=0)]

output:

6.7

1. find the absolute diff on each element
2. Find the minimum from the result and get the element from index

EDIT: for 2d:

If it is python 2.x:

map(lambda x:x[(np.fabs(x-6.6)).argmin(axis=0)], data)

python 3.x:

[r for r in map(lambda x:x[(np.fabs(x-6.6)).argmin(axis=0)], data)]

results in returning nearest value in each row.

One value from all:

data=data.flatten()
print data[(np.fabs(data-6.6)).argmin(axis=0)]

index position from each row:

ip = map(lambda x:(np.fabs(x-6.6)).argmin(axis=0), data)