| Title: |
Title:
PTB_ISO_14999-4_KPI_Uncertainty_Tool
|
| Authors: |
Authors:
Schake, Markus, Physikalisch-Technische Bundesanstalt (PTB), Fachbereich 4.2, Bild- und Wellenoptik, ORCID: 0000-0002-9883-3494
|
| Contributors: |
Contributors:
HostingInstitution: Physikalisch-Technische Bundesanstalt (PTB)
|
| Languages: |
Languages:
de
|
| DOI: |
DOI:
10.7795/740.20260128
|
| Resource Type: |
Resource Type:
PTB: Software,
DINI: Software,
DataCite: Software
|
| Publisher: |
Publisher:
Physikalisch-Technische Bundesanstalt (PTB)
|
| Rights: |
Rights:
https://creativecommons.org/licenses/by/4.0/CC-BY 4.0 International |
| Dates: |
Dates:
Available:
2026-02-03
|
| Classifications: |
Classifications:
OCIS 120.3180 Interferometry ; OCIS 120.2830 Height measurements ; OCIS 120.4800 Optical standards and testing ; OCIS 120.6650 Surface measurements, figure
|
| File: |
File:
Download File
(application/zip)
20.5 MB
MD5 Checksum: 2a885cd62d8464f4a81868dcb857f3da SHA256 Checksum: c53d3c40b4d8b9d210e8057b17218c1af37ee8bfd43feeda6b7f959a5fa6fd56 |
| Keywords: |
Keywords:
ISO 14999-4 ;
peak-to-valley ;
robust Peak-to-valley ;
root-mean-square ;
irregularity ;
interferometry ;
calibration ;
measurement uncertainty
|
| Abstract: |
Abstract:
The provided python software and Simulation data "PTB_ISO_14999-4_Zernike_Surface_Tool" enables the simulation and/or fitting of surface topographies on circular or rectangular apertures.
The provided python software and Simulation data "PTB_ISO_14999-4_KPI_Uncertainty_Tool" enables the user to determine the expanded measurement uncertainties of characteristic ISO 14999-4 KPIs (PV, PV%, PVr, RMS) in dependence of specified input uncertainties for topography height uncertainty at each Pixel and lateral displacement uncertainty for a specified sample under test (SUT) topography. The user is enabled to: -generate simulated custom topographies based on Zernike coefficients -fit custom measurement data provided in a specified format and use it as input data -receive the expanded measurement uncertainties of the ISO 14999-4 KPIs (PV, PV%, PVr, RMS) for the selected input data The main executable files are: -"ISO_14999-4_KPI_Uncertainty_Tool.py" -"ISO_14999-4_Zernike_Tool_15_01_2026.py" User data should be provided via the *.json files as explained in "Instruction for Input data.txt" For more details about the specific folders and files contained in the package see section "Description of the individual files". |
| Table of Contents: |
Table of Contents:
Description of the individual files:The subfolders contain: -"PTB_ISO_14999-4_Zernike_Surface_Tool": To generate and fit topography data and check the implementation of Zernike polynomial fitting. -"Instruction for Input data.txt" File with explanation about how to use the software. -Executable python script "ISO_14999-4_Zernike_Tool_15_01_2026.py" -Auxiliary python script "zernike_poly_xy_cartesian_V16012026.py" with functions used in "ISO_14999-4_Zernike_Tool_15_01_2026.py" to perform the fitting. -"parameter_dict.json" a generic *.json file with an example of the data structure for user input, which is evaluated in "ISO_14999-4_Zernike_Tool_15_01_2026.py" most of the relevant user modifications may be performed by changing parameters in the "parameter_dict.json" as explained in "Instruction for Input data.txt". -Three *.json files "Example_Measurement_data_Masterball.json", "Example_Measurement_data_ZeissDK7417.json","Synthetic_Topodata_rectangle.json" with topography input data examples, which may be replaced by custom topography data in the same format. -"PTB_ISO_14999-4_KPI_Uncertainty_Tool": To generate and fit topography data, and evaluate ISO 14999-4 KPI uncertainties in specified scenarios. -"Instruction for Input data.txt" File with explanation about how to use the software. -Executable python script "ISO_14999-4_KPI_Uncertainty_Tool.py" -Auxiliary python script "zernike_poly_xy_cartesian_V16012026.py" with functions used in "ISO_14999-4_KPI_Uncertainty_Tool.py" to perform the fitting. -"parameter_dict.json" a generic *.json file with an example of the data structure for user input, which would be evaluated in "ISO_14999-4_KPI_Uncertainty_Tool.py" most of the relevant user modifications may be performed by changing parameters in the "parameter_dict.json" as explained in "Instruction for Input data.txt". -Three *.json files "Example_Measurement_data_Masterball.json", "Example_Measurement_data_ZeissDK7417.json", "Synthetic_Topodata_rectangle.json" with topography input data examples, which may be replaced by custom topography data in the same format. -6 Subfolders "results_*" containing graphical depictions of KPI uncertainties for reference and a "parameter_dict_***.json" file, which may be used to repeat the specific experiment using "ISO_14999-4_KPI_Uncertainty_Tool.py". -1 "Nominal_KPIs" folder containing results for the nominal KPIs of the example topographies and "parameter_dict_***.json" files to repeat the experiments using "ISO_14999-4_KPI_Uncertainty_Tool.py". |
| Remark: |
Remark:
recommended software for execution:The Software was tested with -IDE Spyder 6.1.2 -Visual Studio Code Version: 1.107.1 -Python 3.11.4 All software required to run the simulation is open access. The python toolboxes required are: sys, os, numpy, matplotlib and json, which all may be installed using the "conda" package manager |
-OAR
