pflib::algorithm Namespace Reference

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Functions
std::array< double, 72 >	get_toa_efficiencies (const std::vector< pflib::packing::SingleROCEventPacket > &data)
	calculate the highest TOA_VREF value for each link, for which there is a non-zero TOA efficiency
std::map< std::string, std::map< std::string, uint64_t > >	level_pedestals (Target *tgt, ROC roc)
	Level pedestals so that they are all within noise of their link median.
std::map< std::string, std::map< std::string, uint64_t > >	toa_vref_scan (Target *tgt, ROC roc)
	Find TOA threshold voltage reference to align TOA values.
std::map< std::string, std::map< std::string, uint64_t > >	trim_toa_scan (Target *tgt, ROC roc)
	Find trim_toa to align TOA for each channel.

Detailed Description

housing of higher-level methods for repeatable tasks

Calculate the TRIM_TOA for each channel that best aligns all of them to a common threshold voltage, charge injection pulse (calib).

Note

Not currently operational, but a good place to pickup from.

Function Documentation

get_toa_efficiencies()

std::array< double, 72 > pflib::algorithm::get_toa_efficiencies

(

const std::vector< pflib::packing::SingleROCEventPacket > &

data

)

calculate the highest TOA_VREF value for each link, for which there is a non-zero TOA efficiency

reserve a vector of the appropriate size to avoid repeating allocation time for all 72 channels

we assume that the data provided is not empty otherwise the efficiency calculation is meaningless

level_pedestals()

std::map< std::string, std::map< std::string, uint64_t > > pflib::algorithm::level_pedestals	(	Target *	tgt,
		ROC	roc )

Level pedestals so that they are all within noise of their link median.

Parameters

[in]

tgt

pointer to Target to interact with

Note

Only functional for single-ROC targets

do three runs of 100 samples each to have well defined pedestals

toa_vref_scan()

std::map< std::string, std::map< std::string, uint64_t > > pflib::algorithm::toa_vref_scan	(	Target *	tgt,
		ROC	roc )

Find TOA threshold voltage reference to align TOA values.

Parameters

[in]

tgt

pointer to Target to interact with

Note

Only functional for single-ROC targets

do a run of 100 samples per toa_vref to measure the TOA efficiency when looking at pedestal data

trim_toa_scan()

std::map< std::string, std::map< std::string, uint64_t > > pflib::algorithm::trim_toa_scan	(	Target *	tgt,
		ROC	roc )

Find trim_toa to align TOA for each channel.

Parameters

[in]

tgt

pointer to Target to interact with

Note

Only functional for single-ROC targets

Charge injection scan (100 samples) while varying TRIM_TOA. Purpose is to align TRIM_TOA for each channel. Calculates TOA efficiency while looking at charge injection data. Then uses Siegel Linear Regression to calculate the aligned TRIM_TOA value for each channel to match a common "calib" value.

Note

Reduce the sample size (ex: 100 to 10) to decrease the scan time.

Now that we have the data, we need to analyze it.

We'll be looking for the turn-on (threshold) points for each channel at each trim_toa value. The turn-on (threshold) point is the first point where toa_efficiency goes from 0 to non-zero. The toa_efficiency is simply the number of times TOA triggers divided by the sample size, for a given trim_toa/calib/channel combination.

We'll be using the Siegel Linear Regression because it's less sensitive to outliers, since sometimes changing the trim_toa causes the threshold (turn-on) points to "wrap around".