Module qc analysis tools
Project description
module-qc-analysis-tools v1.3.1rc1
A general python tool for running ITkPixV1.1 module QC test analysis. An overview of the steps in the module QC procedure is documented in the Electrical specification and QC procedures for ITkPixV1.1 modules document and in this spreadsheet. The analysis scripts in this repository require input files with measurement data. The measurement data should be collected using the module-qc-measurement-tools package.
Requirements
This tool requires users to have >python3.6 with the following packages installed:
numpyscipytabulatematplotlibjsonschema
Installation
This package may be accessed by cloning from gitlab or by installing it via pip.
via clone
Use this method if you want to use the latest version of the package from gitlab. First clone the project:
git clone https://gitlab.cern.ch/atlas-itk/pixel/module/module-qc-analysis-tools.git
Upon a successful checkout, cd to the new module-qc-analysis-tools directory
and run the following to install the necessary software:
$ python3 -m venv env
$ source env/bin/activate
$ python -m pip install --upgrade pip
$ python -m pip install -e .
via pip
Use this method if you want to use the latest stable (versioned) release of the package.
python -m venv venv
source venv/bin/activate
python -m pip install -U pip
python -m pip install -U pip module-qc-analysis-tools==1.3.1rc1
Note that users should use the latest python version (check python version via
python3 -V). Python3.7 is the minimum requirement for developers. See
For Developer section.
Scripts
Analyze ADC Calibration
This analysis script performs the ADC calibration. It produces several diagnostic plots and an output file with the ADC calibration slope and offset.
analysis-ADC-CALIBRATION --help
analysis-ADC-CALIBRATION --help
usage: analysis-ADC-CALIBRATION [-h] -i INPUT_MEAS [-o OUTPUT_DIR] [-q QC_CRITERIA] [-l LAYER] [--permodule]
[-f {root,numpy}] [-v VERBOSITY]
optional arguments:
-h, --help show this help message and exit
-i INPUT_MEAS, --input-meas INPUT_MEAS
path to the input measurement file or directory containing input measurement files.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
output directory
-q QC_CRITERIA, --qc-criteria QC_CRITERIA
path to json file with QC selection criteria (default: $(module-qc-analysis-tools --prefix)/analysis_cuts.json)
-l LAYER, --layer LAYER
Layer of module, used for applying correct QC criteria settings. Options: L0, L1, L2
(default)
--permodule Store results in one file per module (default: one file per chip)
-f {root,numpy}, --fit-method {root,numpy}
fitting method
-v VERBOSITY, --verbosity VERBOSITY
Log level [options: DEBUG, INFO (default), WARNING, ERROR]
Analyze Analog Readback
This analysis script performs the Analog Readback. It produces an output file with the calculated internal biases, temperature from the internal and external temperature sensor, and VDDA/VDDD vs Trim, including diagnostic plots with slope and offset.
analysis-ANALOG-READBACK --help
$ analysis-ANALOG-READBACK --help
usage: analysis-ANALOG-READBACK [-h] -i INPUT_MEAS [-o OUTPUT_DIR] [-q QC_CRITERIA] [-l LAYER] [--permodule]
[-f {root,numpy}] [-v VERBOSITY] [--verbose]
optional arguments:
-h, --help show this help message and exit
-i INPUT_MEAS, --input-meas INPUT_MEAS
path to the input measurement file or directory containing input measurement files.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
output directory
-q QC_CRITERIA, --qc-criteria QC_CRITERIA
path to json file with QC selection criteria (default: $(module-qc-analysis-tools --prefix)/analysis_cuts.json)
-l LAYER, --layer LAYER
Layer of module, used for applying correct QC criteria settings. Options: L0, L1, L2
(default)
--permodule Store results in one file per module (default: one file per chip)
-f {root,numpy}, --fit-method {root,numpy}
fitting method
-v VERBOSITY, --verbosity VERBOSITY
Log level [options: DEBUG, INFO (default), WARNING, ERROR]
--verbose verbose mode
Analyze SLDO
This script analyses the SLDO curve. It produces several diagnostic plots and an output file with several parameters extracted from the SLDO curves.
analysis-SLDO --help
$ analysis-SLDO --help
usage: analysis-SLDO [-h] -i INPUT_MEAS [-o OUTPUT_DIR] [-q QC_CRITERIA] [-l LAYER] [--permodule] [-n NCHIPS]
[-f {root,numpy}] [-v VERBOSITY] [--lp-enable]
optional arguments:
-h, --help show this help message and exit
-i INPUT_MEAS, --input-meas INPUT_MEAS
path to the input measurement file or directory containing input measurement files.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
output directory
-q QC_CRITERIA, --qc-criteria QC_CRITERIA
path to json file with QC selection criteria (default: $(module-qc-analysis-tools --prefix)/analysis_cuts.json)
-l LAYER, --layer LAYER
Layer of module, used for applying correct QC criteria settings. Options: L0, L1, L2
(default)
--permodule Store results in one file per module (default: one file per chip)
-n NCHIPS, --nChips NCHIPS
Number of chips powered in parallel (e.g. 4 for a quad module, 3 for a triplet, 1 for an
SCC.)
-f {root,numpy}, --fit-method {root,numpy}
fitting method
-v VERBOSITY, --verbosity VERBOSITY
Log level [options: DEBUG, INFO (default), WARNING, ERROR]
--lp-enable low power mode
Analyze VCal Calibration
This analysis script performs the VCal calibration. It produces several diagnostic plots and an output file with the VCal calibration slope and offset.
analysis-VCAL-CALIBRATION --help
$ analysis-VCAL-CALIBRATION --help
usage: analysis-VCAL-CALIBRATION [-h] -i INPUT_MEAS [-o OUTPUT_DIR] [-q QC_CRITERIA] [-l LAYER] [--permodule]
[-f {root,numpy}] [-v VERBOSITY]
optional arguments:
-h, --help show this help message and exit
-i INPUT_MEAS, --input-meas INPUT_MEAS
path to the input measurement file or directory containing input measurement files.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
output directory
-q QC_CRITERIA, --qc-criteria QC_CRITERIA
path to json file with QC selection criteria (default: $(module-qc-analysis-tools --prefix)/analysis_cuts.json)
-l LAYER, --layer LAYER
Layer of module, used for applying correct QC criteria settings. Options: L0, L1, L2
(default)
--permodule Store results in one file per module (default: one file per chip)
-f {root,numpy}, --fit-method {root,numpy}
fitting method
-v VERBOSITY, --verbosity VERBOSITY
Log level [options: DEBUG, INFO (default), WARNING, ERROR]
Analyze Injection capacitance
This analysis script performs the injection capacitance. It produces several diagnostic plots and an output file with the measured pixel injection capacitance.
analysis-INJECTION-CAPACITANCE --help
$ analysis-INJECTION-CAPACITANCE
usage: analysis-INJECTION-CAPACITANCE [-h] -i INPUT_MEAS [-o OUTPUT_DIR] [-q QC_CRITERIA] [-l LAYER] [--permodule]
[-v VERBOSITY]
optional arguments:
-h, --help show this help message and exit
-i INPUT_MEAS, --input-meas INPUT_MEAS
path to the input measurement file or directory containing input measurement files.
-o OUTPUT_DIR, --output-dir OUTPUT_DIR
output directory
-q QC_CRITERIA, --qc-criteria QC_CRITERIA
path to json file with QC selection criteria (default: $(module-qc-analysis-tools --prefix)/analysis_cuts.json)
-l LAYER, --layer LAYER
Layer of module, used for applying correct QC criteria settings. Options: L0, L1, L2
(default)
--permodule Store results in one file per module (default: one file per chip)
-v VERBOSITY, --verbosity VERBOSITY
Log level [options: DEBUG, INFO (default), WARNING, ERROR]
Notes
Submit QC results
To submit the QC results, supply the --submit option to the analysis. You also need to supply the site where the testing took place, as written in production DB (i.e. LBNL_PIXEL_MODULES for LBNL, IRFU for Paris-Saclay, ...). This will generate a URL that is printed to the terminal and saved in "submit.txt" in the same folder as the analysis output. To submit the results, you need to copy and paste one URL for each chip / test into a browser. Once submitted, the results can be viewed here: https://docs.google.com/spreadsheets/d/1pw_07F94fg2GJQr8wlvhaRUV63uhsAuBt_S1FEFBzBU/view . While all submitted results will be recorded, only the latest results for each chip / test will be analyzed. If a mistake was realized in the submitted results, one can re-run the analysis and re-submit the results to overwrite the original results.
Example commands for a chip in a quad module (L2):
analysis-ADC-CALIBRATION -i ../module-qc-tools/emulator/outputs/Measurements/ADC_CALIBRATION/1000000001/ --layer L2
analysis-SLDO -i ../module-qc-tools/emulator/outputs/Measurements/SLDO/1000000001/ --layer L2
analysis-ANALOG-READBACK -i ../module-qc-tools/emulator/outputs/Measurements/ANALOG_READBACK/1000000001/ --layer L2
analysis-VCAL-CALIBRATION -i ../module-qc-tools/emulator/outputs/Measurements/VCAL_CALIBRATION/1000000001/ --layer L2
analysis-INJECTION-CAPACITANCE -i ../module-qc-tools/emulator/outputs/Measurements/INJECTION_CAPACITANCE/1000000001/ --layer L2
Update Chip Config
After each analysis, update the settings in the chip config by running:
analysis-update-chip-config -i <path to analysis output directory> -c <path to YARR config directory> -t <config type>
This script reads the analysis test type and update the corresponding parameters in the chip config.
JsonChecker and DataExtractor
Two classes are designed for general purposes of the module qc analysis tool.
-
JsonCheckera. Check whether the test type is implemented b. For a specific task, check if required keywords exist c. Check if lengths of measurements are identical d. Check if there are negative numbers of measurements -
DataExtractorThis class finds measurements by Vmux value and convert them to quantites.
For Developer
python version
A python version higher than 3.7 is needed for this repository. Check the local
python version with python -V.
If the local python version is lower, set up a virtual python environment following the instructions here.
versioning
In case you need to tag the version of the code, you need to have either hatch
or pipx installed.
- Activate python environment, e.g.
source venv/bin/activate. - Run
python -m pip install hatchorpython -m pip install pipx.
You can bump the version via:
pipx run hatch run tag x.y.z
# or
hatch run tag x.y.z
where x.y.z is the new version to use. This should be run from the default
branch (main / master) as this will create a commit and tag, and push for
you. So make sure you have the ability to push directly to the default branch.
pre-commit
Install pre-commit to avoid CI failure. Once pre-commit is installed, a git hook script will be run to identify simple issues before submission to code review.
Instruction for installing pre-commit in a python environment:
- Activate python environment, e.g.
source venv/bin/activate. - Run
python3 -m pip install pre-commit. - Run
pre-commit installto install the hooks in.pre-commit-config.yaml.
After installing pre-commit, .pre-commit-config.yaml will be run every time
git commit is done. Redo git add and git commit, if the pre-commit script
changes any files.
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