Finding the mean of all values within a range in an array-CodePudding

I have an array:

flux = np.array(folded2_lc_binned.flux.value, dtype = 'float')

which gives me the following results:

flux = [0.99996269 1.0000602  1.00017059 1.00002182 1.00007594 0.9999696
 1.00011313 1.00012934 1.00005817 0.99997538 0.99956554 0.99896783
 0.99861592 0.99828523 0.99859077 0.9990297  0.9994933  0.99997085
 1.00000501 0.999919   1.00013363 1.00007749 1.00005972 1.00003064
 0.99999666 1.00003886 1.00002563 1.00004816]

How can I calculate the mean (average) of the array, but only including the values between 0.999 and 1.001?

CodePudding user response：

You can filter the elements on the condition that they're between 0.999 and 1.001, and then use .mean():

import numpy as np

flux = np.array([0.99996269, 1.0000602,  1.00017059, 1.00002182, 1.00007594, 0.9999696,
 1.00011313, 1.00012934, 1.00005817, 0.99997538, 0.99956554, 0.99896783,
 0.99861592, 0.99828523, 0.99859077, 0.9990297,  0.9994933,  0.99997085,
 1.00000501, 0.999919,   1.00013363, 1.00007749, 1.00005972, 1.00003064,
 0.99999666, 1.00003886, 1.00002563, 1.00004816])

print((flux[(0.999 <= flux) & (flux <= 1.001)]).mean())

CodePudding user response：

Can you a list comprenhension like this?

import statistics
statistics.mean([float(data) for data in flux if data and 0.999 < float(data) < 1.001])

CodePudding user response：

You could also use Statistics library and line comprehension as follows:

import statistics

flux = [0.99996269, 1.0000602,  1.00017059, 1.00002182, 1.00007594, 0.9999696,
 1.00011313, 1.00012934, 1.00005817, 0.99997538, 0.99956554, 0.99896783,
 0.99861592, 0.99828523, 0.99859077, 0.9990297,  0.9994933,  0.99997085,
 1.00000501, 0.999919,  1.00013363, 1.00007749, 1.00005972, 1.00003064,
 0.99999666, 1.00003886, 1.00002563, 1.00004816]

mean_lst = statistics.mean([i for i in flux if i >= 0.999 and i <= 1.001])
print(mean_lst)

This would give you the output:

0.9999554604166667