ifcb_count_mat_annotations: Count IFCB Annotations from .mat Files

In iRfcb: Tools for Managing Imaging FlowCytobot (IFCB) Data

Count IFCB Annotations from .mat Files

Description

This function processes .mat files, generated by the code in the ifcb-analysis repository (Sosik and Olson 2007), to count and summarize the annotations for each class based on the class2use information provided in a file.

Usage

ifcb_count_mat_annotations(
  manual_files,
  class2use_file,
  skip_class = NULL,
  sum_level = "class",
  mat_recursive = FALSE,
  use_python = FALSE
)

Arguments

manual_files	A character string specifying the path to the .mat files or a folder containing .mat files.
class2use_file	A character string specifying the path to the file containing the class2use variable.
skip_class	A numeric vector of class IDs or a character vector of class names to be excluded from the count. Default is NULL.
sum_level	A character string specifying the level of summarization. Options: "sample", "roi" or "class" (default).
mat_recursive	Logical. If TRUE, the function will search for MATLAB files recursively when manual_files is a folder. Default is FALSE.
use_python	Logical. If TRUE, attempts to read the .mat file using a Python-based method. Default is FALSE.

Details

If use_python = TRUE, the function tries to read the .mat file using ifcb_read_mat(), which relies on SciPy. This approach may be faster than the default approach using R.matlab::readMat(), especially for large .mat files. To enable this functionality, ensure Python is properly configured with the required dependencies. You can initialize the Python environment and install necessary packages using ifcb_py_install().

If use_python = FALSE or if SciPy is not available, the function falls back to using R.matlab::readMat().

Value

A data frame with the total count of images per class, roi or per sample.

References

Sosik, H. M. and Olson, R. J. (2007), Automated taxonomic classification of phytoplankton sampled with imaging-in-flow cytometry. Limnol. Oceanogr: Methods 5, 204–216.

Examples

## Not run: 
# Count annotations excluding specific class IDs
result <- ifcb_count_mat_annotations("path/to/manual_folder",
                                     "path/to/class2use_file",
                                     skip_class = c(99, 100))
print(result)

# Count annotations excluding a specific class name
result <- ifcb_count_mat_annotations("path/to/manual_folder",
                                     "path/to/class2use_file",
                                     skip_class = "unclassified")
print(result)

## End(Not run)

iRfcb documentation built on April 16, 2025, 1:09 a.m.