Skip to main content
snompy logo

PyPI - Version Conda Version DOI link

A Python package for modelling scanning near-field optical microscopy measurements.

Overview

The main purpose of snompy is to provide functions to calculate the effective polarizability, of a SNOM tip and a sample, which can be used to predict contrast in SNOM measurements. It also contains other useful features for SNOM modelling, such as an implementation of the transfer matrix method for calculating far-field reflection coefficients of multilayer samples, and code for simulating lock-in amplifier demodulation of arbitrary functions.

For more details, including tutorials and example scripts, see the snompy documentation.

Installation

Using pip:

pip install snompy

Using conda:

conda install -c conda-forge snompy

Cite us

This package is open source and free to use. We only ask that you cite our paper, to acknowledge the time and effort that went into developing snompy. Please see the section Cite us from the snompy documentation for details on how.

Release files for snompy 0.1.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for snompy 0.1.9
File Size Uploaded
snompy-0.1.9.tar.gz 42.0 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for snompy 0.1.9
File Interpreter ABI Platform
snompy-0.1.9-py3-none-any.whl Python 3 none any Details

Total release size: 66.3 kB

Release files / snompy-0.1.9.tar.gz

Download URL snompy-0.1.9.tar.gz
Size 42.0 kB
Tags Source
SHA-256 checksum
How to use checksums
aed85e217e32bfb31eae000ecfb1923f7610b290732e910bbbdc308c7e485d2a
BLAKE2b-256 checksum
How to use checksums
1c9b7f859ca9bc7cd12f7bcae3bf69667cfb1590c3722b8f7ec0a9d917b5a1d9
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.9.19

Release files / snompy-0.1.9-py3-none-any.whl

Download URL snompy-0.1.9-py3-none-any.whl
Size 24.3 kB
Tags Python 3
SHA-256 checksum
How to use checksums
ceab868654cf24a1a38bec864f4fb3153bbc2b1924ab71d60b139aa4248df9a5
BLAKE2b-256 checksum
How to use checksums
8e77e6985cce2124e87eb24da1613993b5092b11e8b217b7f1fa5f140766c525
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/5.1.0 CPython/3.9.19

Release history Release notifications | RSS feed

This release

0.1.9 This release

2 release files

0.1.7

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page