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40 results found

Imppy3d: Image processing in python for 3D image stacks

Data provided by  National Institute of Standards and Technology

Image Processing in Python for 3D image stacks, or imppy3d, is a softwarerepository comprising mostly Python scripts that simplify post-processing and3D shape characterization of grayscale image stacks, otherwise known asvolume-based images, 3D images, or voxel models. imppy3d was originally createdfor post-processing image stacks generated from X-ray computed tomographymeasurements. However, imppy3d also contains a functions to aid inpost-processing general 2D/3D images.Python was chosen for this library because of it is a productive, easy-to-uselanguage.

Tags: python,image processing,3d,x-ray,tomography,image stack,

Modified: 2024-02-22

Views: 0

"pyproject2conda": A script to convert `pyproject.toml` dependencies to `environemnt.yaml` files.

Data provided by  National Institute of Standards and Technology

The main goal of `pyproject2conda` is to provide a means to keep all basicdependency information, for both `pip` based and `conda` based environments, in`pyproject.toml`. I often use a mix of pip and conda when developing packages,and in my everyday workflow. Some packages just aren't available on both. The application provides a simple comment based syntax to add information to dependencies when creating `environment.yaml`. This package is actively used by the author, but is still very much a work inprogress.

Tags: python,devoloper tool,python packaging,

Modified: 2024-02-22

Views: 0

Dynamic compressive stress-strain curves of aluminum alloy 6061-T6 with rapid heating

Data provided by  National Institute of Standards and Technology

This dataset contains raw mechanical data (strain, stress and strain rate curvesand initial temperatures) for compression experiments performed on aluminum alloy 6061-T6using the NIST pulse-heated Kolsky Bar at strain rates between 2400 1/s and 2700 1/s and initialtemperatures from 23 °C to 527 °C and heating times ranging between 0.2 s and 3.5 s. At this time,the thermal history of the specimen during heating is not included in the dataset but this informationmay be included in a future update.

Tags: metals,mechanical properties,high heating rate,High Strain Rate,experiments,simulations,modeling,advanced manufacturing,machining,

Modified: 2024-02-22

Views: 0

The NIST Scan Framework for ARTIQ

Data provided by  National Institute of Standards and Technology

The NIST scan framework is a framework that greatly simplifies the process of writing and maintaining scans of experimental parameters using the ARTIQ control system and language. The framework adopts the philosophy of convention over configuration where datasets are stored for analysis and plotting in a standard directory structure. The framework provides a number of useful features such as automatic calculation of statistics, fitting, validation of fits, and plotting that do not need to be performed by the user.

Tags: ARTIQ,python,Scans,

Modified: 2024-02-22

Views: 0

multicomplex: C++ and Python code for multicomplex arithmetic

Data provided by  National Institute of Standards and Technology

The library multicomplex is an implementation of multicomplex algebra in C++ to allow for higher-order derivatives of numerical functions. Many (though not all) mathematical functions are implemented, allowing for calculation of derivatives (straight and mixed) to approximately numerical precision, which is difficult or impossible to achieve in conventional double precision

Tags: mathematics,multicomplex,derivatives,C++,python,

Modified: 2024-02-22

Views: 0

Optimal Bayesian Experimental Design

Data provided by  National Institute of Standards and Technology

Python module "optbayesexpt" uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given a parametric model - analogous to a fitting function - Bayesian inference uses each measurement "data point" to refine model parameters. Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties. A TCP socket interface allows the software to be used from experimental control software written in other programming languages.

Tags: GitHub pages template,experimental design,Bayesian,optbayesexpt,python,measurement,

Modified: 2024-02-22

Views: 0

NIST Inorganic Crystal Structure Database (ICSD)

Data provided by  National Institute of Standards and Technology

Materials discovery and development necessarily begins with the preparation and identification of product phase(s). Crystalline compounds can be identified by their characteristic diffraction patterns using X-rays, neutrons, and or electrons. An estimated 20,000 X-ray diffractometers and a comparable number of electron microscopes are used daily in materials research and development laboratories for this purpose.

Tags: chemical structures,crystallography,crystal structures,diffraction,disorder,electrons,identification,inorganic,neutrons,magnetic,metals,minerals,materials,Rietveld,synchrotron,twinned,x-rays,Advanced Materials,manufacturing,Safety,Security and Forensics,

Modified: 2024-02-22

Views: 0

SEDCORR: An Algorithm for Correcting Systematic Energy Deficits in the Atom Probe Mass Spectra

Data provided by  National Institute of Standards and Technology

SEDCORR is an open-source Python module designed to correct for the systematic energy deficits in atom probe mass spectra of electrically insulating samples. The assumption of the algorithm is that the mass spectrum for a dataset is conserved throughout the dataset and that any changes to the peak positions arise from an unknown slowly-fluctuating accelerating voltage. For computational speed, the unknown accelerating voltage is determined using a template matching FFT-based cross correlation method.

Tags: atom probe microscopy,insulator,mass spectra,energy deficit correction,python,FFT,

Modified: 2024-02-22

Views: 0

pySCATMECH: A Python interface to the SCATMECH C++ library of polarized light scattering codes

Data provided by  National Institute of Standards and Technology

SCATMECH is a library of object-oriented C++ computer codes originally developed for disseminating models for polarized light scattering from surfaces and aerosols and for diffraction from gratings. The pySCATMECH package has been developed as an interface to the SCATMECH library, simplifying use of the codes and allowing for more rapid development of software for these applications.

Tags: aerosol,bidirectional reflectance,BRDF,diffuse,gratings,Mie scattering,modeling,Mueller matrix,polarization,python,roughness,scatter,surface,

Modified: 2024-02-22

Views: 0

Optimal Bayesian Experimental Design Version 1.0.1

Data provided by  National Institute of Standards and Technology

Python module 'optbayesexpt' uses optimal Bayesian experimental design methods to control measurement settings in order to efficiently determine model parameters. Given an parametric model - analogous to a fitting function - Bayesian inference uses each measurement 'data point' to refine model parameters. Using this information, the software suggests measurement settings that are likely to efficiently reduce uncertainties. A TCP socket interface allows the software to be used from experimental control software written in other programming languages.

Tags: GitHub pages template,experimental design,Bayesian,optbayesexpt,python,measurement,

Modified: 2024-02-22

Views: 0