Skip to main content

Sandia PSL Uncertainty Calculator

Project description

Uncertainty Calculator

Sandia UNcertainty CALculator (SUNCAL)

Copyright 2019-2021 National Technology & Engineering Solutions of Sandia, LLC (NTESS). Under the terms of Contract DE-NA0003525 with NTESS, the U.S. Government retains certain rights in this software. This software is distributed under the GNU General Public License.


This tool was developed by the Primary Standards Lab at Sandia National Laboratories to calculate the combined uncertainty of a multi-variable system. Contact uncertainty@sandia.gov.

Installation

Installation of the Python package and command line interface requires Python 3.7+ with the following packages:

  • numpy
  • scipy
  • sympy
  • matplotlib
  • pyqt5
  • pyyaml
  • markdown
  • pint

To install (on Windows, Mac, or Linux), from a command prompt, run:

pip install suncal

Example Usage

From a python terminal, script, or notebook:

import suncal
u = suncal.UncertaintyCalc('A*B')
u.set_input('A', nom=100, unc=0.1)
u.set_input('B', nom=2, unc=0.01)
u.calculate()

See the PDF user's manual and the example notebook files in the docs folder for a complete reference guide.

Command-line script

A script named suncal will be installed to your system path. From a command line, run:

suncal file

where file is the filename of a setup file. See doc/examples folder for example setup files. Refer to the PDF user's manual for other commands.

User interface

A graphical user interface is installed with the Python package. Pre-built executables are available from https://sandiapsl.github.io.

To launch the user interface from a command line, run:

suncalui

A shortcut to this can be put on your desktop, etc.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

suncal-1.5.5.tar.gz (14.7 MB view details)

Uploaded Source

Built Distribution

suncal-1.5.5-py3-none-any.whl (496.7 kB view details)

Uploaded Python 3

File details

Details for the file suncal-1.5.5.tar.gz.

File metadata

  • Download URL: suncal-1.5.5.tar.gz
  • Upload date:
  • Size: 14.7 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.7.9

File hashes

Hashes for suncal-1.5.5.tar.gz
Algorithm Hash digest
SHA256 23e7643ed471558c9fd92a5bae4e7a8d755e6cba6b9892127bfe8bc3cab0a0e0
MD5 2395864ffdd4f7f30ecdaa97a3339cfa
BLAKE2b-256 31489787c978258398775d00b61e10ab65f0da08db9ddf7b11bdc7f549288cfc

See more details on using hashes here.

File details

Details for the file suncal-1.5.5-py3-none-any.whl.

File metadata

  • Download URL: suncal-1.5.5-py3-none-any.whl
  • Upload date:
  • Size: 496.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/3.10.0 pkginfo/1.7.1 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.61.2 CPython/3.7.9

File hashes

Hashes for suncal-1.5.5-py3-none-any.whl
Algorithm Hash digest
SHA256 5f24d516a0f7dd122563849cd7e0f0ac2dafe6728dfdc126a496e56fb7e8bd95
MD5 b8d101d86e255adcd507265b92d43171
BLAKE2b-256 8fd04281ac2698a4ec6476d4b1e143050eb628247c2c38b413dd06172e66ee67

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page