Difference between revisions of "CDC prototype more on timing"
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#Calculate mean pedestal over 100 samples ending 10 samples before the trigger time (every 4th of these samples also works) | #Calculate mean pedestal over 100 samples ending 10 samples before the trigger time (every 4th of these samples also works) | ||
#Search forward for sample x where adc value > high threshold n1 sigma | #Search forward for sample x where adc value > high threshold n1 sigma | ||
− | #Step back p samples to sample | + | #Step back p samples to sample x-p, take adc value of sample x-p to be local pedestal value |
#Subtract local pedestal value from a number (10+p) of samples starting at sample x-(p+5) to the LE algo for unsampling | #Subtract local pedestal value from a number (10+p) of samples starting at sample x-(p+5) to the LE algo for unsampling | ||
#Search through unsampled data, start with last sample (highest adc value) search backwards until adc value < low threshold n2 sigma | #Search through unsampled data, start with last sample (highest adc value) search backwards until adc value < low threshold n2 sigma | ||
− | #Calculate time where interpolated unsampled data cross n2 sigma, and add to time of sample | + | #Calculate time where interpolated unsampled data cross n2 sigma, and add to time of sample x-p, this is the estimated drift time. |
− | Unsampled adc values (z) using different values for p (local pedestal lead time ahead of first/high threshold crossing) for high threshold of 5 sigma. | + | Unsampled adc values (z) using different values for p (local pedestal lead time ahead of first/high threshold crossing) for high threshold of 5 sigma. x-axis=0 corresponds to sample x-p-4.2, x-xaxis=5 corresponds to 1+x-p-4.2, etc. |
5 unsampled values per 8ns sample, all events for ch17 (central straw) included (no tracking) | 5 unsampled values per 8ns sample, all events for ch17 (central straw) included (no tracking) | ||
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Revision as of 09:51, 24 October 2011
Current analysis code procedure:
- Calculate s.d. of pedestal for first 100 samples, 100 events, save for later use (sigma)
For each event...
- Calculate mean pedestal over 100 samples ending 10 samples before the trigger time (every 4th of these samples also works)
- Search forward for sample x where adc value > high threshold n1 sigma
- Step back p samples to sample x-p, take adc value of sample x-p to be local pedestal value
- Subtract local pedestal value from a number (10+p) of samples starting at sample x-(p+5) to the LE algo for unsampling
- Search through unsampled data, start with last sample (highest adc value) search backwards until adc value < low threshold n2 sigma
- Calculate time where interpolated unsampled data cross n2 sigma, and add to time of sample x-p, this is the estimated drift time.
Unsampled adc values (z) using different values for p (local pedestal lead time ahead of first/high threshold crossing) for high threshold of 5 sigma. x-axis=0 corresponds to sample x-p-4.2, x-xaxis=5 corresponds to 1+x-p-4.2, etc. 5 unsampled values per 8ns sample, all events for ch17 (central straw) included (no tracking)
High threshold 4 sigma
High threshold 6 sigma