A Python package for reading STM experimental data files obtained from Nanonis, based on nanonispy
Project description
nanonis-reader package 
nanonis-reader is a Python library designed to help you analyze and visualize data with ease.
Installation
From PyPI
You can install the latest stable release from PyPI:
pip install nanonis-reader
Usage
Example
When you input Nanonis file numbers, corresponding files will be automatically generated as a pptx file.
import nanonis-reader as nr
path = 'your_folder_path'
ppt_maker = nr.util.DataToPPT(base_path=path, keyword='your_file_keyword', output_filename='your_file_name.pptx')
ppt_maker.generate_ppt()
Then, you will get below:
Maximum file number in directory: XXXX
Enter start number (or 'q' to quit):
Enter the starting file number here.
Enter end number (or 'q' to quit):
Enter the ending file number here.
Generate PPT for files 1 to 1? (y/n):
Enter 'y' to generate the PowerPoint file.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file nanonis_reader-0.1.3.tar.gz.
File metadata
- Download URL: nanonis_reader-0.1.3.tar.gz
- Upload date:
- Size: 22.3 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
8a52a0477ae3b9eacf6bf5a9fb4fee7364154f61a87e0f2179eba47aea5b2135
|
|
| MD5 |
37770f41bc1d423e96abc34b58f70910
|
|
| BLAKE2b-256 |
60ce0ba2f8e090ae3e22369c0e3029a900b71319c1cd0ed69ba0eaaf8fe3b710
|
File details
Details for the file nanonis_reader-0.1.3-py3-none-any.whl.
File metadata
- Download URL: nanonis_reader-0.1.3-py3-none-any.whl
- Upload date:
- Size: 25.1 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.0.1 CPython/3.12.7
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
4b8cee968b40ec7c98e5b8a81240b1ebcadfbd8f3212e1198d365cb8fff0a889
|
|
| MD5 |
924fa7a4fa0fb1412c2cc0c91208b8b4
|
|
| BLAKE2b-256 |
4a378cb976f5d22fac29dbd24bd680f3701428ef156868ee1d2c8ca4c7fcd6b0
|