CODEWITHSUNDEEP
pythonnumpyrounding
mike
mike

Reputation: 23811

Round to a given number in Python

I'm running a simulation in which people age in small (month, week) increments. However, I have hazards in non-consistent age-intervals. Is there an simple/efficient way to round my age at any time to the nearest age-group (for the purpose of extracting the hazards for that age?

age_groups = np.array([0, .01, .1, 5, 10, 15, 20, 25, 30, 35, 40])

Upvotes: 3

Views: 1583

Answers (3)

unutbu
unutbu

Reputation: 879361

Suppose you want to group the ages into bins defined by age_groups. Then you can find which age range each age falls into using np.searchsorted:

import numpy as np

ages=np.array([0,0.05,1,3,5,10,13,19,25,35])

age_groups = np.array([0, .01, .1, 5, 10, 15, 20, 25, 30, 35, 40])

index=age_groups.searchsorted(ages,side='left')
for age,nearest_age in zip(ages,age_groups[index]):
    print('{a} --> {n}'.format(a=age,n=nearest_age))

yields

0.0 --> 0.0
0.05 --> 0.1
1.0 --> 5.0
3.0 --> 5.0
5.0 --> 5.0
10.0 --> 10.0
13.0 --> 15.0
19.0 --> 20.0
25.0 --> 25.0
35.0 --> 35.0

Upvotes: 2

user671110
user671110

Reputation:

I assume you have ages such as .5, 5, 6, 10, 32, 32.5, ect. that need to fall into the age_groups array you have.

This is an easy one-liner :)

Assuming you have:

age_groups = np.array([0, .01, .1, 5, 10, 15, 20, 25, 30, 35, 40])
age = .5

The solution is:

nearest_age = age_groups[(np.abs(age_groups-age)).argmin()]

Put that line into a function, passing it the age_groups array and the age you want rounded :)

Upvotes: 3

BrainStorm
BrainStorm

Reputation: 2046

You would want to clusterize these elements, probably with the k-mean algorithm, here are some answers: Python k-means algorithm

Upvotes: 0

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