Peak Algorithm
- Found peak using second derivative of data. Double differential used as it enables us to find some hidden peaks.
- Picked a cut off point for second derivative of data to give a range,
and
, where the values inside the range would be considered a peak
- Used equation,
to find the weighted average, peak, of the for each spectrum.
- RMS was obtained by the equation,
- FWHM can be obtained by
.
- Peak locator algorithm used for camera angle at 1.50mm:
Error Bars and Chi Squared
- First attempt at error bars, setting y error as the square root of the count:
- Error bars are tiny due to incorrect assumption that data follows a poison distribution.
- Chi squared function used:
- Cd spectrum at 06.50mm with Gaussian fits, error bars and Chi squared values:
- Array of test parameters passed to fucntion : test_array_Cd650 = [[8E6, 150, 30, 3E5], [1.6E7, 270, 30, 3E5], [1.6E7, 520, 30, 3E5]]
- Chi squared values are huge as expected due to poor fit. Once errors and fit equation are correct, Chi squared should reduce.
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JamesAngthopo - 03 Nov 2016