This is a major update. Feature names, arguments and outputs have changed, so please read "Breaking changes" before upgrading from version 0.99.x.
axDistmap(): the argument allFeatures is replaced by featureSet = "standard" or "all".s.perimeter is Per, h.ent.s1 is ENT, s.area is Area). See "Feature names" in ?axDistmap. Text files written by version 0.99.6 (original EBImage names) are converted automatically by axSvm() and axQnt().axDistmap(): the standard output now has 11 columns (Area, Per, Ras, Ran, ecc, mjx, ENT, SVA, SV2, CON, cir) instead of 7. Feature tables exported with the earlier default settings lack features required by the built-in models; please re-run axDistmap() on the images.svm_example_model.svm is discontinued and replaced by two built-in models, g0.1_APA (recommended) and g0.2_ACC. AII and DI therefore differ from those of version 0.99.x.axSvm(): the default features and hyperparameters have changed (previously six fixed features, C = 3, gamma = 0.1). With model = "custom" and without nCst / nGmm, C = 1 and gamma = 0.1 are used.axSvm() now samples the training data by default: up to 12 images per group and up to 1000 objects per image, randomly selected with seed = 1. Training results therefore differ from version 0.99.6. To use all data, set maxNumImg = NULL and maxNumObj = NULL.axSvm(): degenerate_path and intact_path accept one folder or a character vector of .txt files. Several folders, or folders mixed with files, now stop with an error.axQnt(): the output is written to one subfolder per input folder (<folder>_<date>_output_files), and FileName in the summary is the path relative to the input folder.axDistmap() and axQnt(): new arguments pixelSize, targetPixelSize, autoParam and colorMode.
pixelSize argument (recommended) or from the file metadata (OME-XML, TIFF resolution tags, ImageJ calibration).autoParam = TRUE.colorMode = "rgb" averages the three channels of color-camera images.axDistmap() writes <folder>_<date>_Parameters.csv (one row per image). When analyzing images, axQnt() writes the same kind of file for each input folder.axSvm(): new arguments model ("g0.1_APA", "g0.2_ACC" or "custom"), features, targetPixelSize, maxNumImg, maxNumObj and seed. The random number state of the R session is restored on exit. The scale of the training data is recorded with the model when *_Parameters.csv is found next to the input data.axSvm(): columns that are not present in every input file are reported and not used.axQnt(): new arguments model and distMapImg. A model produced by axSvm() is selected with svm_model_path, and the required predictors are read from the model itself. Models trained with version 0.99.x can still be used.axQnt(): when images were analyzed at a scale different from that of the model, one warning at the end of the run reports the number of images and the scale ratio.?AiES describing supported, not recommended and unsupported images.axQnt(): fixed a missing binarization inversion in the image processing for images (imprtImg = TRUE), which made the segmentation differ from that of axDistmap().axQnt(): the default of svm_model_path is now NULL (it was tempdir()).axQnt(): objects stored in the model file (e.g. a saved workspace) could silently overwrite the arguments of the function. The file is now loaded into a separate environment.axQnt(): a folder, a missing file or several paths given as svm_model_path now stop with a clear message. The model selection dialog accepts one file only.axQnt(): no summary file is written when no file could be processed.axDistmap(): imgType = "jpg" now works (converted to the "jpeg" accepted by EBImage::writeImage()).axSvm(): fixed errors when the folder selection dialog was canceled (R >= 4.3), when a vector of file paths was given (R >= 4.2), and in the save dialog of tcltk.axSvm(): input files with different columns (e.g. exported with different featureSet settings) no longer cause an rbind() error or silently dropped rows.tiff, rstudioapi and utils are now in Imports.Introduction_to_AiES.