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LDMX.Ecal package

Submodules

LDMX.Ecal.digi module

Package to configure the ECal digitization pipeline

All classes are derived versions of LDMX.Framework.ldmxcfg.Producer with helpful member functions.

Two module-wide parameters are defined.

LDMX.Ecal.digi.n_kelectrons_per_mip

Number of thousand e-h pairs created for each MIP in 0.5mm thick Si

Type:

float

LDMX.Ecal.digi.mip_si_energy

Energy [MeV] of a single MIP on average in 0.5mm thick Si

Type:

float

class LDMX.Ecal.digi.EcalDigiProducer(instance_name: str = 'EcalDigiProducer', histograms: list[Histogram] = <factory>, hgcroc: HgcrocEmulator = <factory>, mev: float = 2.8497115384615386, avg_readout_threshold: float = 0.828125, avg_pedestal: float = 0.78125, avg_noise_rms: float = 0.009375, zero_suppression: bool = True, input_coll_name: str = 'EcalSimHits', input_pass_name: str = '', digi_coll_name: str = 'EcalDigis')

Bases: Processor

Configuration for EcalDigiProducer

hgcroc

Configuration for the chip emulator

Type:

HgcrocEmulator

mev

Conversion between energy [MeV] and voltage [mV] Depends on silicon thickness in simulation relative to the 0.5mm thickness that the physical constants were derived from. Default uses a silicon thickness of 0.4mm

Type:

float

avg_readout_threshold

Average readout threshold for all channels [mV], for noise emulation

Type:

float

avg_pedestal

Average pedestal for all channels [mV], for noise emulation

Type:

float

avg_noise_rms

Average noise RMS for all channels [mV], for noise emulation in empty channels Default is too optimistic, but need to mimic old noise model

Type:

float

zero_suppresion

Should we suppress pure noise “hits” below readout threshold?

Type:

bool

input_coll_name

Name of simulated ecal hits to digitize

Type:

str

input_pass_name

Name of pass to digitize

Type:

str

digi_coll_name

Output name of digis put into event bus

Type:

str

avg_noise_rms: float = 0.009375

avg_pedestal: float = 0.78125

avg_readout_threshold: float = 0.828125

class_name: str = 'ecal::EcalDigiProducer'

digi_coll_name: str = 'EcalDigis'

hgcroc: HgcrocEmulator

input_coll_name: str = 'EcalSimHits'

input_pass_name: str = ''

instance_name: str = 'EcalDigiProducer'

mev: float = 2.8497115384615386

module_name: str = 'Ecal'

zero_suppression: bool = True

class LDMX.Ecal.digi.EcalRecProducer(instance_name: str = 'EcalRecProducer', histograms: list[Histogram] = <factory>, layer_weights: list[float] = <factory>, second_order_energy_correction: float = 1.0909884355225834, mip_si_energy: float = 0.13, charge_per_mip: float = 5.9274000000000004, clock_cycle: float = 25.0, digi_coll_name: str = 'EcalDigis', digi_pass_name: str = '', sim_hit_coll_name: str = 'EcalSimHits', sim_hit_pass_name: str = '', rec_hit_coll_name: str = 'EcalRecHits')

Bases: Processor

Configuration for the EcalRecProducer

The layer weights and second order energy correction change when the ECal geometry changes, so we have setup various options for the different possible ECal geometries and their associated layer weights.

mip_si_energy

Copied from module-wide mip_si_energy [MeV]

Type:

float

charge_per_mip float

Copied from module-wide charge_per_mip [fC]

clock_cycle

Time for one DAQ clock cycle to pass [ns]

Type:

float

digi_coll_name

Name of digi collection

Type:

str

digi_pass_name

Name of digi pass

Type:

str

sim_hit_coll_name

Name of sim collection to check for pure noise hit ID

Type:

str

sim_hit_pass_name

Name of sim pass

Type:

str

rec_hit_coll_name

Name of output collection

Type:

str

second_order_energy_correction

Correction to weighted energy, default to v15 geometry

Type:

float

layer_weights

Weighting factors depending on layer index, default to v15 geometry

Type:

list of floats

charge_per_mip: float = 5.9274000000000004

class_name: str = 'ecal::EcalRecProducer'

clock_cycle: float = 25.0

digi_coll_name: str = 'EcalDigis'

digi_pass_name: str = ''

instance_name: str = 'EcalRecProducer'

layer_weights: list[float]

mip_si_energy: float = 0.13

module_name: str = 'Ecal'

rec_hit_coll_name: str = 'EcalRecHits'

static reduced_v2(**kwargs)

Generated for the reduced v2 geometry

TODO: The secondOrderEnergyCorrection for this geometry has yet to be calculated, so unity is being used as a placeholder.

second_order_energy_correction: float = 1.0909884355225834

sim_hit_coll_name: str = 'EcalSimHits'

sim_hit_pass_name: str = ''

static v12(**kwargs)

These layerWeights and energy correction were calculated for the v12 geometry.

The second order energy correction is determined by comparing the mean of 1M single 4GeV electron events with 4GeV.

static v14(**kwargs)

Generated for the v14 geometry

The secondOrderEnergyCorrection is deteremined by generating 1M single 4GeV or 8GeV electron events shot directly into the front of the ECal from immediately upstream. The mean of the resulting total recon energy is found by fitting a two-sided normal distribution (one mean, a low and high deviation) to the histogram.

static v15(**kwargs)

Generated for the v15 geometry

The secondOrderEnergyCorrection is deteremined by generating 1M single 4GeV or 8GeV electron events shot directly into the front of the ECal from immediately upstream. The mean of the resulting total recon energy is found by fitting a two-sided normal distribution (one mean, a low and high deviation) to the histogram.

static v2(**kwargs)

These layerWeights and energy correction were calculated at least before v3 geometry.

The second order energy correction is determined by comparing the mean of 1M single 4GeV electron events with 4GeV.

static v9(**kwargs)

These layerWeights and energy correction were calculated for the v9 geometry.

The second order energy correction is determined by comparing the mean of 1M single 4GeV electron events with 4GeV.

LDMX.Ecal.digi.calculate_energy_to_voltage_conversion(si_thickness: float)

calculate the conversion from a simulated energy [MeV] to voltage [mV]

energy [MeV] * (thousand electrons per MIP)

• (charge per thousand electrons fC)

• (avg pad capacitance pF = 1/20)

• ( 1 MIP / energy [MeV] )

= voltage [mV]

this leads to ~ 470 mV/MeV or ~6.8 MeV maximum hit (if 320 fC is max ADC range)

Parameters:

si_thickness (float) – thickness of silicon sensitive layers in mm

LDMX.Ecal.digi.charge_per_mip = 5.9274000000000004

in fC, convering number of electrons to charge

LDMX.Ecal.digi.ecal_hgcroc_emulator()

Get an HGCROC emulator configured for the ECal specifically

This sets the pulse shape parameters to the ones from a fit to a test readout of an ECal module and then thresholds to the default construction using 37k electrons as the number of electrons per MIP.

LDMX.Ecal.digi.mip_si_energy = 0.13

in MeV, corresponds to ~3.5 eV per e-h pair

derived from 0.5mm thick Si

LDMX.Ecal.digi.n_kelectrons_per_mip = 37.0

thousand e-h pairs created per MIP

derived from 0.5mm thick Si

LDMX.Ecal.ecal_clusters module

Configuration for the EcalClusterProducer

Examples

from LDMX.Ecal.ecalClusters import ecalClusters p.sequence.append( ecalClusters )

class LDMX.Ecal.ecal_clusters.EcalClusterProducer(instance_name: str = 'EcalClusterProducer', histograms: list[Histogram] = <factory>, rec_hit_coll_name: str = 'EcalRecHits', rec_hit_pass_name: str = '', cluster_coll_name: str = 'EcalClusters', cutoff: float = 10.0, seed_threshold: float = 100.0, algo_name: str = 'MyClusterAlgo', algo_coll_name: str = 'ClusterAlgoResult', clue: bool = True, nbr_of_layers: int = 1, dc: float = 5.0, rhoc: float = 550.0, deltac: float = 10.0, deltao: float = 40.0, reclustering: bool = False)

Bases: Processor

Configure the clustering

rec_hit_coll_name

name of input rec hits to use for cluster

Type:

str

rec_hit_pass_name

name of pass of rec hits to use

Type:

str

cluster_coll_name

name of output collection of clusters

Type:

str

cutoff

not clue, minimum rec energy threshold to consider for clustering

Type:

float

seed_threshold

not clue, minimum rec energy threshold to consider as a seed

Type:

float

algo_name

not clue, name of algorithm used to calculate “distance”

Type:

str

algo_coll_name

not clue, output collection to store algorithm information

Type:

str

clue

enable using the CLUE algorithm instead of default

Type:

bool

nbr_of_layers

number of layers to perform CLUE on if equals 1 (default), collapse all hits inot the same z-dimension

Type:

int

dc

cutoff distance in calculation of local desnity only used if nbr_of_layers > 1

Type:

float

rhoc

minimum seed energy (aka maximum outlier energy) not used when nbr_of_layers > 1

Type:

float

deltac

minimum seed separation not used when nbr_of_layers > 1

Type:

float

deltao

minimum outlier separation

Type:

float

recluster

recluster merged clusters or not No reclustering leads to more undercounting reclustering leads to more overcounting

Type:

bool

algo_coll_name: str = 'ClusterAlgoResult'

algo_name: str = 'MyClusterAlgo'

class_name: str = 'ecal::EcalClusterProducer'

clue: bool = True

cluster_coll_name: str = 'EcalClusters'

cutoff: float = 10.0

dc: float = 5.0

deltac: float = 10.0

deltao: float = 40.0

instance_name: str = 'EcalClusterProducer'

module_name: str = 'Ecal'

nbr_of_layers: int = 1

rec_hit_coll_name: str = 'EcalRecHits'

rec_hit_pass_name: str = ''

reclustering: bool = False

rhoc: float = 550.0

seed_threshold: float = 100.0

LDMX.Ecal.ecal_detector_map module

Conditions object providers for a mapping between ecal electronics IDs and detector IDs

class LDMX.Ecal.ecal_detector_map.EcalDetectorMap(cell_map: str, motherboard_map: str, layer_map: str, want_d2e: bool = False, tag_name: str = '')

Bases: ConditionsObjectProvider

The COP that maps between Electronic and Detector IDs.

The mapping is defined in three ‘tiers’.

1. cell - Each cell of a module has specific ROC elink and channel

2. motherboard - Each module has a specific ROC elink and polarfire

3. layer - Each layer has specific daq optical link

So three CSV tables are necessary for providing this mapping. We can’t have multiple different detector maps during a single run, so this class is meant to be a singleton.

cell_map: str

class_name: str = 'ecal::EcalDetectorMap'

layer_map: str

module_name: str = 'Ecal'

motherboard_map: str

object_name: str = 'EcalDetectorMap'

tag_name: str = ''

want_d2e: bool = False

LDMX.Ecal.ecal_geometry module

ConditionsProvider for EcalGeometry and other Ecal geometry-related aspects

class LDMX.Ecal.ecal_geometry.EcalGeometryProvider(geometries: list[EcalGeometry] = <factory>, tag_name: str = '')

Bases: ConditionsObjectProvider

Provider that provides access to Ecal geometry (ecal::EcalGeometry)

Parameters:

tag_name (str) – tag for generator of information

EcalGeometry

Actual class providing precision cellular layout in Ecal

Type:

EcalGeometry

__instance

Singleton instance of this object

Type:

EcalGeometryProvider

class_name: str = 'ecal::EcalGeometryProvider'

geometries: list[EcalGeometry]

get_instance()

Get the single instance of the EcalGeometryProvider

Returns:

Single instance of the provider

Return type:

EcalGeometryProvider

module_name: str = 'Ecal'

object_name: str = 'EcalGeometry'

tag_name: str = ''

class LDMX.Ecal.ecal_geometry.EcalTriggerGeometryProvider(tag_name: str = '')

Bases: ConditionsObjectProvider

Provider that provides access to Ecal geometry (ldmx::EcalGeometry)

Parameters:

tag_name (str) – tag for generator of information

__instance

Singleton instance of this object

Type:

EcalTriggerGeometryProvider

class_name: str = 'ecal::EcalTriggerGeometryProvider'

get_instance()

Get the single instance of the EcalTriggerGeometryProvider

Returns:

Single instance of the provider

Return type:

EcalTriggerGeometryProvider

module_name: str = 'Ecal'

object_name: str = 'EcalTriggerGeometry'

tag_name: str = ''

LDMX.Ecal.ecal_hardcoded_conditions module

Package to provide hard-coded conditions sources for Ecal reconstruction and simulation

LDMX.Ecal.ecal_hardcoded_conditions.EcalTrigPrimConditionsHardcode

Provides a table of integer conditions for ecal trigger primitives producer

Type:

simple_csv_integer_table_provider

LDMX.Ecal.ecal_hardcoded_conditions.EcalReconConditionsHardcode

Provides a table of double conditions for ecal precision reconstruction

Type:

simple_csv_double_table_provider

LDMX.Ecal.ecal_trig_digi module

Package to configure the ECal trigger digitization

class LDMX.Ecal.ecal_trig_digi.EcalTrigPrimDigiProducer(instance_name: str = 'EcalTrigPrimDigiProducer', histograms: list[LDMX.Framework._histogram.Histogram] = <factory>, digi_coll_name: str = 'EcalDigis', digi_pass_name: str = '')

Bases: Processor

class_name: str = 'ecal::EcalTrigPrimDigiProducer'

digi_coll_name: str = 'EcalDigis'

digi_pass_name: str = ''

instance_name: str = 'EcalTrigPrimDigiProducer'

module_name: str = 'Ecal'

LDMX.Ecal.ecal_wab_rec_processor module

Configuration for reconstructing WABs in the Ecal

class LDMX.Ecal.ecal_wab_rec_processor.EcalWABRecProcessor(instance_name: str = 'EcalWABRecProcessor', histograms: list[LDMX.Framework._histogram.Histogram] = <factory>, sp_pass_name: str = '', collection_name: str = 'EcalWABRec', rec_coll_name: str = 'EcalRecHits', rec_pass_name: str = '', track_coll_name: str = 'LinearRecoilTracks', track_pass_name: str = '', sim_particles_passname: str = '')

Bases: Processor

class_name: str = 'ecal::EcalWABRecProcessor'

collection_name: str = 'EcalWABRec'

instance_name: str = 'EcalWABRecProcessor'

module_name: str = 'Ecal'

rec_coll_name: str = 'EcalRecHits'

rec_pass_name: str = ''

sim_particles_passname: str = ''

sp_pass_name: str = ''

track_coll_name: str = 'LinearRecoilTracks'

track_pass_name: str = ''

LDMX.Ecal.make_path module

Helpful python configuration functions for getting the path to installed data files.

This file was configured by cmake for the installation of ldmx-sw at

/home/runner/work/ldmx-sw/ldmx-sw/install

LDMX.Ecal.make_path.make_bdt_path(bdt_name)

Get the full path to the installed BDT files

Exits entire python script if file does not exist.

Parameters:

bdt_name (str) – Name of BDT file to make path for (no extension)

Returns:

full path to installed data file

Return type:

str

Examples

ecal_veto.bdt_file = make_bdt_path( ‘gabrielle’ )

LDMX.Ecal.make_path.make_roc_path(roc_name)

Get the full path to the RoC csv file

Exits entire python script if file does not exist.

Parameters:

roc_name (str) – Name of RoC file to make path for (no extension)

Returns:

full path to installed data file

Return type:

str

Examples

ecal_veto.roc_file = make_roc_path( ‘RoC_v14_8gev’ )

LDMX.Ecal.vetos module

class LDMX.Ecal.vetos.EcalMipProcessor(instance_name: str = 'EcalMipTrackingProcessor', histograms: list[LDMX.Framework._histogram.Histogram] = <factory>, num_ecal_layers: int = 32, linreg_radius: float = 35.0, ecal_collection_name: str = 'EcalVeto', ecal_pass_name: str = '', mip_collection_name: str = 'EcalTrajectoryInfo', mip_pass_name: str = '', mip_result_name: str = 'EcalMipInfo')

Bases: Processor

class_name: str = 'ecal::EcalMipTrackingProcessor'

ecal_collection_name: str = 'EcalVeto'

ecal_pass_name: str = ''

instance_name: str = 'EcalMipTrackingProcessor'

linreg_radius: float = 35.0

mip_collection_name: str = 'EcalTrajectoryInfo'

mip_pass_name: str = ''

mip_result_name: str = 'EcalMipInfo'

module_name: str = 'Ecal'

num_ecal_layers: int = 32

class LDMX.Ecal.vetos.EcalPnetVetoProcessor(instance_name: str = 'EcalPnetVetoProcessor', histograms: list[Histogram] = <factory>, model_path: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/particle_net_ecal_v10.onnx', disc_cut: float = 0.65, collection_name: str = 'EcalPnetVeto', rec_coll_name: str = 'EcalRecHits', ecal_rec_hits_passname: str = '', ecal_sp_coll_name: str = 'EcalScoringPlaneHits', ecal_sp_hits_passname: str = '', track_collection: str = 'RecoilTracksClean', track_pass_name: str = '', recoil_from_tracking: bool = True)

Bases: Processor

Configuration for ParticleNet Ecal Veto

ParticleNet trained on v14 geometry ecalPN + signal

class_name: str = 'ecal::EcalPnetVetoProcessor'

collection_name: str = 'EcalPnetVeto'

disc_cut: float = 0.65

ecal_rec_hits_passname: str = ''

ecal_sp_coll_name: str = 'EcalScoringPlaneHits'

ecal_sp_hits_passname: str = ''

instance_name: str = 'EcalPnetVetoProcessor'

model_path: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/particle_net_ecal_v10.onnx'

module_name: str = 'Ecal'

rec_coll_name: str = 'EcalRecHits'

recoil_from_tracking: bool = True

track_collection: str = 'RecoilTracksClean'

track_pass_name: str = ''

class LDMX.Ecal.vetos.EcalVetoProcessor(instance_name: str = 'EcalVetoProcessor', histograms: list[LDMX.Framework._histogram.Histogram] = <factory>, num_ecal_layers: int = 32, verbose: bool = False, feature_list_name: str = 'input', bdt_file: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/segmip.onnx', roc_file: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/RoC_v14_8gev.csv', beam_energy: float = 8000.0, disc_cut: float = 0.99741, ecal_sp_coll_name: str = 'EcalScoringPlaneHits', target_sp_coll_name: str = 'TargetScoringPlaneHits', sp_pass_name: str = '', sim_particles_coll_name: str = 'SimParticles', sim_particles_passname: str = '', collection_name: str = 'EcalVeto', rec_coll_name: str = 'EcalRecHits', rec_pass_name: str = '', recoil_from_tracking: bool = True, track_collection: str = 'RecoilTracksClean', track_pass_name: str = '', inverse_skim: bool = False)

Bases: Processor

bdt_file: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/segmip.onnx'

beam_energy: float = 8000.0

class_name: str = 'ecal::EcalVetoProcessor'

collection_name: str = 'EcalVeto'

disc_cut: float = 0.99741

ecal_sp_coll_name: str = 'EcalScoringPlaneHits'

feature_list_name: str = 'input'

instance_name: str = 'EcalVetoProcessor'

inverse_skim: bool = False

module_name: str = 'Ecal'

num_ecal_layers: int = 32

rec_coll_name: str = 'EcalRecHits'

rec_pass_name: str = ''

recoil_from_tracking: bool = True

roc_file: str = '/home/runner/work/ldmx-sw/ldmx-sw/install/data/Ecal/RoC_v14_8gev.csv'

sim_particles_coll_name: str = 'SimParticles'

sim_particles_passname: str = ''

sp_pass_name: str = ''

target_sp_coll_name: str = 'TargetScoringPlaneHits'

track_collection: str = 'RecoilTracksClean'

track_pass_name: str = ''

verbose: bool = False

Module contents