Script to play around with efficient dBm calculations and correct logarithmic averages

dBm.py

from math import pow, log10

# ----------------------------------------------

rss = [rss for rss in range(-100, 21)]
rss_watt = [pow(10, s / 10.) for s in rss]

def get_rss_in_mwatt(rss_in_dbm):
	assert 20 >= rss_in_dbm >= -100
	return rss_watt[int(round(rss_in_dbm)) + 100]
	
def get_rss_in_dbm(rss_in_mwatt):
	return 10 * log10(rss_in_mwatt)

# ----------------------------------------------


mwatt_sum = 0
n = 0
db_sum= 0

for i in range(0, 10):
	db = -60
	db_sum += db
	mwatt_sum += get_rss_in_mwatt(db)
	n += 1.


rss_outlier_dbm = -10
db_sum += rss_outlier_dbm
mwatt_sum += get_rss_in_mwatt(rss_outlier_dbm)
n += 1

avg_mwatt = mwatt_sum/n

print 'simple avg in db (wrong)', db_sum/n
print 'avg in linear mwatt scale (correct)',get_rss_in_dbm(avg_mwatt)