Calculating energy output of a pellet stove using time series I want to know which brand of wood pellets (i.e., the fuel) is best suited for my stove, to know this I had 2 temperature loggers installed at the air intake and hot air vent. Essentially, if you know how cold the intake air was and how hot it came out, it should be possible to calculate the energy that was achieved during the given time interval.
Now, I don't need to know how much kW was developed during this time, a simple 'points' system would suffice, e.g., I could award 0.1 points for each minute for each degree the outgoing air is hotter than the ingoing air. For example, if the ingoing air was 20°C and the outgoing air was 60°C for one minute that would 'earn' this brand of pellets 4 points.
For each type of pellet brand, I've burned about 30kg of it and had my 2 temperature loggers on the whole time, which is approximately 27 hours for each brand of pellets. If I could calculate the points each brand has 'earned', it would allow me to see what's the best pellet brand for me.
The problem I'm facing, however, is that the temperature loggers log data samples each 30-60 seconds and not each time with the same interval, and also not at the same timestamps with respect to each other.
So my data looks kinda like this:
In  - 10/03/2012 - 00.01.15h : 20°C
Out - 10/03/2012 - 00.00.55h : 60°C
In  - 10/03/2012 - 00.01.50h : 21°C
Out - 10/03/2012 - 00.01.35h : 63°C

Now I've hit a wall in trying to apply my points system over this data, since the time stamps do not match up.
How can I process data like the samples above to achieve my points value for each burning session?
 A: Did you try using an interpolation? I don't know what (programming) environment you are using, but I would do it like this in Python :
from numpy import *
from scipy import *
import numpy as np

# Read data however you want and store them
# in variables `time`, `temperature_in` and `temperature_out`.
# Time should be in consistent numerical units (seconds, minutes or hours, whatever).
# For the following, I'll assume the units are in seconds
time, temperature_in, temperature_out = readData()

# Interpolate data using quadratic functions
ftin = interp1d (time, temperature_in, kind='quadratic')
ftout = interp1d (time, temperature_out, kind='quadratic')

# You want to add points
# from 0 seconds to the maximum recorded time.
ft = arange (0, np.max(time))

# What you want is add 0.1 point per minute per degree when the outgoing temperature
# (ftout) is greater than the incoming temperature (ftin), thus when ftout-ftin > 0.
points = sum (ftout(ft) - ftin(ft) * 0.1 * 1./60.)

Basically, what I am doing here is an approximation of (with $t$ in minutes) :
$Points = \int_0^{T_{\max}} \left( T_{out} - T_{in} \right)_+ \times 0.1
   \mathrm{d} t$.
You can see the docs on interp1d here: http://docs.scipy.org/doc/scipy/reference/generated/scipy.interpolate.interp1d.html
