gondola.tof#

TOF related entities which did not fit anywhere else

Functions

`apply_settings_diff`(default, modified)	Apply a config diff
`enable_verification_run`(enabled)	Enable verfication runs before every run start
`request_liftof_setitngs`()	Custom run action foxtrott
`restart_liftofrb`(rbs)	Restart the liftof-rb clients on the given boards
`restore_default_config`()	Trigger the start of a new data run with the next active config
`run_action_alfa`()	Custom run action alfa
`run_action_bravo`()	Custom run action bravo
`run_action_charlie`()	Custom run action charlie
`run_action_foxtrott`()	Custom run action foxtrott
`run_action_tango`()	Custom run action tango
`run_action_whiskey`()	Custom run action whiskey
`shutdown_all_rbs`()	Send the 'sudo shutdown now' command to ALL RBs
`shutdown_rat`(rat)	Send the 'sudo shutdown now' command to all RBs in a RAT
`shutdown_ratpair`(pdu, pduchannel)	Send the 'sudo shutdown now' command to all RBs in a RAT
`shutdown_rb`(rb)	Send the 'sudo shutdown now' command to a single RB
`shutdown_tofcpu`()	Send the 'sudo shutdown now command to the TOF main computer ("TOFCPU")
`start_run`()	Trigger the start of a new data run with the next active config
`stop_run`()	Stop the current active run and idle

Classes

`AnalysisEngineSettings`()	Settings to change the configuration of the analysis engine (pulse extraction)
`MasterTrigger`(target_address)
`PreampBiasConfig`	Set preamp voltages
`RBChannelMaskConfig`
`RBPaddleID`()	Squeze the rb channel - paddle mapping into 5 bytes for a single RB
`TofCommand`()	A general command class with an arbitrary payload
`TofCuts`()	Sets of cuts which can be imposed on TofEvents
`TofDetectorStatus`()	Report dead channels/non-active detectors for the TOF system
`TofRunConfig`()
`TriggerConfig`()

gondola.tof.shutdown_tofcpu()#: Send the 'sudo shutdown now command to the TOF main computer ("TOFCPU")

gondola.tof.shutdown_rb(rb)#

Send the 'sudo shutdown now' command to a single RB

# Arguements:

rbThe RB id of the RB to be shutdown
(NOT RAT)

gondola.tof.shutdown_ratpair(pdu, pduchannel)#

Send the 'sudo shutdown now' command to all RBs in a RAT

This will prepare the shutdown command for the RBs in the RATs which are connected to a specific pdu channel

# Arguments:

pdu : PDU ID (0-3)
pduchannel : PDU Channel (0-7)

gondola.tof.shutdown_rat(rat)#

Send the 'sudo shutdown now' command to all RBs in a RAT

# Arguments:

ratThe RAT id for the rat the RBs to be
shutdown live in

gondola.tof.shutdown_all_rbs()#: Send the 'sudo shutdown now' command to ALL RBs

gondola.tof.restart_liftofrb(rbs)#

Restart the liftof-rb clients on the given boards

# Arguments

rbs: restart the client on the given rb ids,
if empty, restart on all of them

gondola.tof.enable_verification_run(enabled)#

Enable verfication runs before every run start

A verification run will not send any event packets, but only a TofDetectorStatus frame

gondola.tof.stop_run()#: Stop the current active run and idle

gondola.tof.start_run()#: Trigger the start of a new data run with the next active config

gondola.tof.waveform_analysis(event, rb, settings)#

Waveform analysis engine - identify waveform variables

This will populate the TofHits in an RBEvent

TofHits contain information about peak location, charge, timing.

FIXME - I think this should take a HashMap with algorithm settings, which we can load from a json file

# Arguments

eventcurrent RBEvent with waveforms to
work on
rbReadoutBoard as loaded from the DB,
with latest calibration attached
settingsParameters to configure the waveform
analysis & peak finding

class gondola.tof.MasterTrigger(target_address)#

clock_rate#

disable_cyclic_trig()#

enable_cyclic_trig()#

get_configurable_trigger()#

get_cortina_thresh()#

get_cube_bot_thresh()#

get_cube_corner_thresh()#

get_cube_side_thresh()#

get_cube_top_thresh()#

get_cyclic_trigger_interval()#

get_enable_cyclic_trig()#

get_event(read_until_footer, verbose, debug)#

get_event_cnt()#

get_event_queue_full()#

get_event_queue_size()#

get_expected_pid()#

get_gaps_trigger_prescale()#

get_inner_tof_thresh()#

get_lt_link_automask()#: get LT LINK AUTOMASK toggle status

get_lt_link_en0()#: Get the status of enabling for LTBs 0-9

get_lt_link_en02()#: Get the status of enabling for LTBs 20-29

get_lt_link_en1()#: Get the status of enabling for LTBs 10-19

get_lt_link_en3()#: Get the status of enabling for LTBs 30-39

get_lt_link_en4()#: Get the status of enabling for LTBs 40-49

get_ltb_event_cnts()#

get_ltb_links_ready()#

get_nevents_in_queue()#

get_outer_tof_thresh()#

get_packet_id()#

get_rb_event_cnts()#: Readout the RB event counter registers

get_tiu_emulation_mode()#: Check if the TIU emulation mode is on

get_total_tof_thresh()#

get_trace_suppression()#

get_umbrella_center_thresh()#

get_umbrella_thresh()#

ignore_tiu_busy#: check if the MTB is ignoring the TIU and using fixed internal busy

lost_rate#

Get the lost global trigger rate in Hz

This is the rate of triggers which got dropped due to TIU BUSY signal + those which get dropped due to the RBs being busy

prescale_bypass#

rate#: Get the global trigger rate in Hz

rb_lost_rate#: The lost rate which occured due to RB busy timeouts

realign_packet_id()#

reset_daq()#

reset_ltb_counters()#: Reset all the LTB counters

reset_rb_counters()#: Reset all the RB counters

set_any_trigger(prescale)#

set_central_track_trigger(prescale)#

set_configurable_trigger(value)#

set_corcubeside_trigger()#

set_cortina_thresh(value)#

set_cube_bot_thresh(value)#

set_cube_corner_thresh(value)#

set_cube_side_thresh(value)#

set_cube_top_thresh(value)#

set_cyclic_trigger_interval(interval)#

set_gaps422_central_track_trigger(prescale, use_beta)#

set_gaps_any_trigger(prescale, use_beta)#

set_gaps_central_track_trigger(prescale, use_beta)#

set_gaps_track_trigger(prescale, use_beta)#

set_gaps_trigger_prescale(prescale)#

set_inner_tof_thresh(value)#

set_lt_link_automask(toggle)#: set LT LINK AUTOMASK toggle status

set_lt_link_en0(value)#: Set on/off link enabling for LTBs 0-9

set_lt_link_en1(value)#: Set on/off link enabling for LTBs 10-19

set_lt_link_en2(value)#: Set on/off link enabling for LTBs 20-29

set_lt_link_en3(value)#: Set on/off link enabling for LTBs 30-39

set_lt_link_en4(value)#: Set on/off link enabling for LTBs 40-49

set_ltb_ch_mask(lt_link, mask)#

Set a channel mask for a LTB.

# Arguments * lt_link : 0-24, dsi/j connection of the LTB on the MTB * mask : bitmask 1 = ch0 2 = ch1, etc. setting a channel

to 1 will DISABLE the channel!

set_outer_tof_thresh(value)#

set_packet_id(pid)#

set_poisson_trigger(rate)#

set_total_tof_thresh(value)#

set_trace_suppression(trace_sup)#

set_track_trigger(prescale)#

set_track_trigger_is_global()#

set_umb3cube_trigger()#

set_umbcorcube_trigger()#

set_umbcube_trigger()#

set_umbcubez_trigger()#

set_umbrella_center_thresh(value)#

set_umbrella_thresh(value)#

stop_all_triggers()#

swap_rb_link_ids#

tiu_bad#

tiu_busy_ignore#

tiu_busy_rate#: get tiu busy rate in Hz

tiu_busy_stuck#

tiu_emulation_mode#

tiu_emulation_mode_bsy_cnt#

tiu_lost_rate#: The lost rate which occured due to the tracker BUSY signal

tiu_timeout_cnt#: the amount of fixed deadtime used by the tiu in units of 10ns

trg_lost_trg_rate#: the lost rate due to the trigger internal busy

trigger()#: Issue a one-time forced trigger

use_tiu_aux_link(use_it)#

class gondola.tof.TofAnalysis(skip_mangled=True, skip_timeout=True, beta_analysis=True, nbins=90, cuts=<TofCuts: <TofCuts: (void)>>, use_offsets=False, pid_inner=None, pid_outer=None, active=False)#

A container (yeah I know, don't like it either) to keep a bunch of plots together.

This does have some use as a pre-compiled analysis for gander, and as a quick look kind of thing.

The gist here it is independent of the data source, as long as some kind of TofEvent can be plugged in.

define_bins(nbins=70)#: Set the bins for the different histograms for the variables. Only the number of bins can be set

pretty_print_statistics()#: A textual representation for some important numbers, e.g. seen events, cut efficiencies, etc.

property occupancy#

property occupancy_t#

property n_events#

property rate#

property rate_nocut#

property run_time#: Get run time from last - first event in seconds

reinit(nbins=90)#: Re-run the initialization routine. This will clear all plots, and reset the binning. This needs to be run in case the binning has been changed

__init__(skip_mangled=True, skip_timeout=True, beta_analysis=True, nbins=90, cuts=<TofCuts: <TofCuts: (void)>>, use_offsets=False, pid_inner=None, pid_outer=None, active=False)#

Start a new TofAnalysis. This will add create histograms for 'interesting' variables and count mangled and timed out events. While not complete, this can provide a conciese, first look for a run. Events can be added to this analysis through the .add_event(ev) method. When all events are added, a call to .finish() is needed to make sure all events in the caches are added to the histograms. Caching is used to massively improve performance, since adding individual numbers to dashi.histograms is painfully slow.

# Arguments:

skip_mangledIgnore events which have the "AnyDataMangling"
flag set

skip_timeoutIgnore events which have the "EventTimedOut"
flag set

beta_analysisLook for first hit on outer tof/inner tof and
use these for a beta calculation. If pid_outer and pid_inner are given, use these paddles instead.

nbinsThe number of bins for the histograms getting
created

cutsGive a cut instance to reject events & hits.
Default: None (no cuts)

pid_outerSelect a specific paddle instead of the first on the outer TOF
for the beta/timing analysis

pid_innerSelect a specific paddle instead of the first on the inner TOF
for the beta/timing analysis

activeif True, this analysis will actually "do something"
and acquire events

property no_hitmiss#

property one_hitmiss#

property two_hitmiss#

property extra_hits#

property n_mangled_frac#

property n_timed_out_frac#

property event_stati#

fill_histograms()#: Fill the histograms with the cached values

finish()#: Ensure the remainder in the caches is histogrammed

add_event(ev)#

Fills the associated histograms

# Arguments:

ev : Any kind of TofEvent or TofEventSummary

gondola.tof.to_board_id_string(rb_id)#: Convert an int value to the board ID string.

class gondola.tof.TofCuts#

Sets of cuts which can be imposed on TofEvents

acc_frac_cos_theta#

acc_frac_fh_must_be_umb#

acc_frac_fhi_not_bot#

acc_frac_fho_must_panel7#

acc_frac_hit_all#

acc_frac_hit_cbe#

acc_frac_hit_cor#

acc_frac_hit_umb#

acc_frac_lh_must_panel2#

accept(event)#

clear_stats()#

copy()#: Return a literal full deep copy of the instance

cos_theta_acc#

fh_must_be_umb#

fh_umb_acc#

fhi_not_bot#

fhi_not_bot_acc#

fho_must_panel7#

fho_must_panel7_acc#

static from_toml(filename)#

get_frac_thru_going#

hit_all_acc#

hit_cbe_acc#

hit_cor_acc#

hit_high_edep#

hit_high_edep_acc#

hit_umb_acc#

hits_rmvd_csl#

hits_rmvd_ls#

hits_total#

is_compatible(other)#

lh_must_panel2#

lh_must_panel2_acc#

ls_cleaning_t_err#

max_cos_theta#

max_hit_all#

max_hit_cbe#

max_hit_cor#

max_hit_umb#

min_cos_theta#

min_hit_all#

min_hit_cbe#

min_hit_cor#

min_hit_umb#

nevents#

only_causal_hits#

pretty_print_efficiency()#: Return a prettily formated string with the efficiency information for all the individual cuts

thru_going#

thru_going_acc#

to_toml(filename)#

void#

class gondola.tof.TofRunConfig#

static from_bytestream(bytestream, pos)#

static from_random()#

static from_tofpacket(packet)#

pack()#: Pack self into a TofPacket to be written on disk or sent over network

runtime#

set_runtime#

class gondola.tof.TriggerConfig#

combo_trigger_prescale#

combo_trigger_type#

static from_bytestream(bytestream, pos)#

static from_random()#

static from_tofpacket(packet)#

gaps_trigger_use_beta#

hb_send_interval#

mtb_moni_interval#

pack()#: Pack self into a TofPacket to be written on disk or sent over network

prescale#

set_combo_trigger_prescale#

set_combo_trigger_type#

set_gaps_trigger_use_beta#

set_hb_send_interval#

set_mtb_moni_interval#

set_prescale#

set_tiu_ignore_busy#

set_trace_suppression#

set_trigger_type#

set_use_combo_trigger#

tiu_ignore_busy#

to_bytestream()#

trace_suppression#

trigger_type#

use_combo_trigger#

class gondola.tof.RBChannelMaskConfig#

class gondola.tof.PreampBiasConfig#: Set preamp voltages

class gondola.tof.TofCommand#

A general command class with an arbitrary payload

Since the commands should in general be small the maixmal payload size is limited to 256 bytes

All commands will get broadcasted and the receiver has to figure out if they have to rect to that command

command_code#

static from_bytestream(bytestream, pos)#

static from_random()#

static from_tofpacket(packet)#

get_cc_u8()#: An explicit getter for the command code, to interface with BFSW/GSE systems

pack()#: Pack self into a TofPacket to be written on disk or sent over network

to_bytestream()#

wrap_n_pack()#

Pack myself nicely in a TofPacket and serialize myself

Can be used to interface with BFSW/GSE systems

class gondola.tof.TofOperationMode#

How to operate the readout Default mode is to request events from the MasterTrigger. However, we can also stream all the waveforms. CAVEAT: For the whole tof, this will cap the rate at 112 Hz, because of the capacity of the switches.

Default = TofOperationMode.Default#

RBCalcCRC32 = TofOperationMode.RBCalcCRC32#

RBHighThroughput = TofOperationMode.RBHighThroughput#

RBWaveform = TofOperationMode.RBWaveform#

Unknown = TofOperationMode.Unknown#

static from_u8(byte)#

class gondola.tof.BuildStrategy#

Build Strategy

Adaptive = BuildStrategy.Adaptive#

AdaptiveGreedy = BuildStrategy.AdaptiveGreedy#

AdaptiveThorough = BuildStrategy.AdaptiveThorough#

Smart = BuildStrategy.Smart#

Unknown = BuildStrategy.Unknown#

WaitForNBoards = BuildStrategy.WaitForNBoards#

static from_u8(byte)#

class gondola.tof.TofCommandCode#

ChangeNextRunConfig = TofCommandCode.ChangeNextRunConfig#

DataRunStart = TofCommandCode.DataRunStart#

DataRunStop = TofCommandCode.DataRunStop#

GetFullWaveforms = TofCommandCode.GetFullWaveforms#

Kill = TofCommandCode.Kill#

Listen = TofCommandCode.Listen#

Lock = TofCommandCode.Lock#

Moni = TofCommandCode.Moni#

NoSendRBWaveforms = TofCommandCode.NoSendRBWaveforms#

NoSendTofEvents = TofCommandCode.NoSendTofEvents#

Ping = TofCommandCode.Ping#

RBCalibration = TofCommandCode.RBCalibration#

RequestLiftofSettings = TofCommandCode.RequestLiftofSettings#

ResetConfigWDefault = TofCommandCode.ResetConfigWDefault#

RestartLiftofRBClients = TofCommandCode.RestartLiftofRBClients#

RunScriptAlfa = TofCommandCode.RunScriptAlfa#

RunScriptBravo = TofCommandCode.RunScriptBravo#

RunScriptCharlie = TofCommandCode.RunScriptCharlie#

RunScriptFoxtrott = TofCommandCode.RunScriptFoxtrott#

RunScriptTango = TofCommandCode.RunScriptTango#

RunScriptWhiskey = TofCommandCode.RunScriptWhiskey#

SendRBWaveforms = TofCommandCode.SendRBWaveforms#

SendTofEvents = TofCommandCode.SendTofEvents#

SetAnalysisEngineConfig = TofCommandCode.SetAnalysisEngineConfig#

SetDataPublisherConfig = TofCommandCode.SetDataPublisherConfig#

SetLTBThresholds = TofCommandCode.SetLTBThresholds#

SetMTConfig = TofCommandCode.SetMTConfig#

SetPreampBias = TofCommandCode.SetPreampBias#

SetRBChannelMask = TofCommandCode.SetRBChannelMask#

SetTOFEventBuilderConfig = TofCommandCode.SetTOFEventBuilderConfig#

SetTofRBConfig = TofCommandCode.SetTofRBConfig#

SetTofRunConfig = TofCommandCode.SetTofRunConfig#

ShutdownCPU = TofCommandCode.ShutdownCPU#

ShutdownRAT = TofCommandCode.ShutdownRAT#

ShutdownRATPair = TofCommandCode.ShutdownRATPair#

ShutdownRB = TofCommandCode.ShutdownRB#

Staging = TofCommandCode.Staging#

StartValidationRun = TofCommandCode.StartValidationRun#

SubmitConfig = TofCommandCode.SubmitConfig#

Unknown = TofCommandCode.Unknown#

Unlock = TofCommandCode.Unlock#

UnspoolEventCache = TofCommandCode.UnspoolEventCache#

UploadConfig = TofCommandCode.UploadConfig#

UploadConfigDiff = TofCommandCode.UploadConfigDiff#

static from_u8(byte)#

class gondola.tof.AnalysisEngineSettings#

Settings to change the configuration of the analysis engine (pulse extraction)

cfd_fraction#

find_pks_t_start#

find_pks_t_window#

find_pks_thresh#

integration_start#

integration_window#

max_peaks#

min_peak_size#

pedestal_begin_bin#

pedestal_thresh#

pedestal_win_bins#

tot_threshold_high#

tot_threshold_low#

use_zscore#

class gondola.tof.TofDetectorStatus#

Report dead channels/non-active detectors for the TOF system

This is a very simple approach A channels are the paddle_id - 1 while B channels are encoded as paddle_id - 159

Dead channels will be 0, active channels will be 1

channels000_031#

channels032_063#

channels064_095#

channels096_127#

channels128_159#

channels160_191#

channels192_223#

channels224_255#

channels256_297#

channels298_319#

static from_bytestream(bytestream, pos)#

static from_random()#

static from_tofpacket(packet)#

pack()#: Pack self into a TofPacket to be written on disk or sent over network

class gondola.tof.RBPaddleID#

Squeze the rb channel - paddle mapping into 5 bytes for a single RB

get_paddle_id(channel)#

Modules

analysis

gondola.tof#

This Page