SCMeTA

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Save Function ​

Introduction ​

save function is designed to save processed single-cell mass spectrometry data to files. It is part of the SCMeTA class. The function allows users to save processed data in various formats, including cell_mat, mat, process, and raw, file type details can be seen in SCData. Users can choose to save all files at once or specify a single file to save. The function also provides the flexibility to save files in a custom directory path or the default directory.

Usage ​

To use the save method of the SCMeTA class, you need to have an instance of the class that contains processed MS data.

Save Method Arguments ​

  • file_name (str | None, optional): The name of the specific file to save. If None, all files will be processed.
  • data_type (str, optional): The type of data to save. Default is "cell_mat". Other supported types include "mat", "process", and "raw".
  • path (str | None, optional): The directory path where the file should be saved. If None, the file will save in the subdirectory "Process" of the directory where the data were loaded from.

Examples ​

  • To save all data of type "cell_mat" in the default path:

    python
    scmeta.save(path="/path/to/directory")

  • To save a specific file of type “process” in a specified path:

    python
    scmeta.save(file_name="sample1", data_type="process", path="/path/to/directory")

Features ​

  • Flexible file saving: Save either all files at once or specify a single file.
  • Multiple data types: Can save data in various formats including cell_mat, mat, process, and raw.
  • Custom paths: Choose where to save your output files - either in the default directory or a path of your choice.
  • Intuitive logging: Provides informational logs to confirm successful saves.

Support ​

If you encounter issues or have questions regarding the save function, please refer to the documentation of MSProcess class for further details or contact the support team/maintainer of the module.

In case of requiring additional help about Python standard libraries such as os or logging, consult the official Python documentation or communities like Stack Overflow.