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Overriding Configuration Parameters

The WCT configuration language Jsonnet allows to exploit software development patterns such as "don't repeat yourself" (DRY) and object inheritance. They are exploited to factor a configuration into layers so that it may, in total, serve many uses. This post describes how to override a parameter from a base object.

Frames and Traces and Ticks

First, just to set the stage, one of the main data types in WCT is a "frame" which is a collection of "traces" and each "trace" is associated with a channel and contains some contiguous charge samples (eg, ADC or voltage). A frame may also hold a superposition of traces by giving them "tags". For example, one may store partial traces tagged by the true particle ID that led to their creation by the simulation. In principle, a WCT frame need not have a well specified end and it may also be sparse (not every "tick" nor channel need have a sample).

Some applications can not work with this generalization of a "frame" but rather assume a concept of "frame" being a dense 2D array with fixed channel and tick extent and ordering. WCT has ways to slice its frame to match this more limited concept. For simulation and signal processing there are a number of parameters that govern this. Expressed in the configuration schema implemented in the pgrapher config these are the relevant parameters:

number of (time) ticks in one "readout" of the detector. This is relevant for WCT sim producing frames and for WCT noise filter consuming them.
number of (frequency) bins used to perform noise filtering (NF). It is typically different from daq.nticks.

MicroBooNE Case

MicroBooNE has a somewhat confusing set of numbers that come into play here.

WCT's default number of ticks into which frames may be sliced.
number of ticks in a LArSoft simulated frame
number of ticks in actual detector data

These three numbers are set in the daq.nticks. Another parameter, nf.nsamples currently takes one value:

number of frequency bins for performing NF filtering/convolutions

This value for nf.nsamples can probably work more or less okay when paired with any nearby value of daq.nticks although will be a small source of data loss due to tick-truncation or a small source of artifacts due to zero-padding (when made larger than daq.nticks).

Overriding parameters

Finally, we must have a way to override the default value of daq.nticks in multiple contexts. Already it is overridden for MicroBooNE in the ~params.jsonnet file to be 9595 but that only works for data. For jobs which wish to emulate LArSoft simulation's 9600 they need to further override.

Notes about what not to do:

  • do not directly edit the MicroBooNE params.jsonnet file to change this value as this will break other users that rely on it to stay as-is.
  • do not copy params.jsonnet to another file as this will cause divergence and make it difficult to fix bug.

Instead, what one should do is derive from the MicroBooNE params.jsonnet data structure to make yet another data structure that contains just the desired changes.

This overriding is actually already being done for many parameters for MicroBooNE in that experiment's params.jsonnet file. There, (at time of this blog bpost) daq.nticks is set to 9595. Instead of editing this file and modifying the parameter in place, which would then break its use for data, it should be overridden in another context.

Overriding in the main Jsonnet file

On a case-by-case basis one can override specific MicroBooNE parameters inside the "main" Jsonnet file following the exact same patter as is using the MicroBooNE params.jsonnet file itself.

The params are used as – well, parameters – to parameterize other configuration. They are created in the main Jsonnet file with a line like:

local params = import "pgrapher/experiment/uboone/params.jsonnet";

Just after creation, one can override using a pattern like:

local default_params = import "pgrapher/experiment/uboone/params.jsonnet";
local params = default_params {
  daq: super.daq {
    nticks: 9600,

Overriding many parameters

It may come to pass that many parameters must be overriden in common for many uses. For example, we must pick 9600 ticks for simulation. It's possible other parameters will need to be modified for all or a subset of common simulation goals. It becomes tedious to do the above few lines inside ever main file and would be cleaner to move this overriding into its own file to be shared by many mains. One might then create pgrapher/experiment/uboone/params-sim.jsonnet with something like:

local default_params = import "pgrapher/experiment/uboone/params.jsonnet";
default_params {
  daq: super.daq {
    nticks: 9600,
  // extend as needed for simulation

Then, inside the "main" Jsonnet file one would have just one line:

local params = import "pgrapher/experiment/uboone/params-sim.jsonnet";