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Count IFCB Annotations from .mat Files

Source: R/ifcb_count_mat_annotations.R
ifcb_count_mat_annotations.Rd

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.

Value

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

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().

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

if (FALSE) { # \dontrun{
# 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)
} # }