Application
Luminosity simplifies the process of reading and writing Luminex IS100/200 system CSV files, streamlining data management for labs.
Contributors
Developed by the open-source community to enhance laboratory data handling capabilities.
Contact
Free Download
Access the Luminosity module from the GitHub repository.
Progress
Luminosity is actively maintained and supports a range of functionalities for laboratory data management.
Resources
Luminosity is a Python module designed for reading and writing CSV files generated by the Luminex IS100/200 system. This module simplifies data handling for researchers and professionals using Luminex technology, allowing for easy manipulation of exported data. The module is particularly useful for laboratories that require efficient data management and analysis capabilities.
Key Features
- CSV File Compatibility: Supports Luminex IS100/200 exported CSV files, regardless of whether all additional features are enabled.
- Easy Metadata Access: Retrieve essential information, such as machine serial numbers and sample data, with simple commands.
- Data Manipulation: Edit, update, and merge CSV files effortlessly, making it easy to manage your data sets.
- Comprehensive Data Structures: Utilizes
pandasdata frames for robust data handling and analysis. - Flexible Installation: While not available on PyPI yet, the module can be easily installed from the source.
Installation
To install Luminosity, you need to clone the repository or download the ZIP file. Run the following command in your terminal or command prompt:
bashCopy codepython setup.py install
To uninstall, use:
bashCopy codepip uninstall luminosity
Properties
| Property | Data Type |
|---|---|
| Luminosity.beads | pandas.indexes.base.Index |
| Luminosity.cal_info | pandas.core.frame.DataFrame |
| Luminosity.con_info | pandas.core.frame.DataFrame |
| Luminosity.data | pandas.core.frame.DataFrame |
| Luminosity.datatypes | pandas.indexes.base.Index |
| Luminosity.meta | dict |
| Luminosity.sample_num | int |
| Luminosity.samples | pandas.core.series.Series |
Methods
- Luminosity.get_meta(): Retrieve metadata from the CSV file.
- Luminosity.output(): Save modified data to a new CSV file.
- Luminosity.update_from(): Replace sample data in one file with data from another.
- Luminosity.merge_with(): Combine two CSV files into one.
Quick Start Examples
- Get Metadata:pythonCopy code
from luminosity import Luminosity c = Luminosity('path_to_your_csv_file') print('Machine Serial Number is: {}.'.format(c.get_meta('SN'))) - Get Trimmed Mean Values:pythonCopy code
tmean = c.data.loc[('Trimmed Mean', '5 (A12)'), :] print(tmean) - Edit CSV File:pythonCopy code
c.meta['Operator'] = 'New Operator' c.output('newfile.csv') - Update Sample Data:pythonCopy code
c1 = Luminosity('path_to_your_csv_file1') c2 = Luminosity('path_to_your_csv_file2') c1.update_from(from_obj=c2, from_loc=['1 (C2)', '2 (D2)', '3 (E2)'], to_loc=['1 (E11)', '3 (G11)', '5 (A12)']) c1.output() - Merge Two CSV Files:pythonCopy code
c1.merge_with(c2) c1.output()
License
This project is licensed under the Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0).
