View source: R/load_mask_data.R
cell.load.boundaries | R Documentation |
Load CellID boundary data to a dataframe
cell.load.boundaries(
data.source,
position_pattern = ".*Position(\\d+)$",
tsv_pattern = "^out_all_masks.tsv(?:\\.gz)?$",
cell_id_offset = -1,
interior_offset = NULL,
blank_bg = NULL,
arguments = NULL,
pixel.type = "b",
flags = NULL,
close.paths = FALSE,
cell.data = NULL,
tiff.channel = "BF.out"
)
data.source |
Either "out.tif" or "masks.tsv". |
position_pattern |
A regex pattern with one group for the integer position number, extracted from the directory name holding the TSV file. |
tsv_pattern |
A regex pattern matching the name of the TSV file ( |
cell_id_offset |
integer. The pixel intensity offset with respect to maximum pixel intensity, such
that |
interior_offset |
logical. If |
blank_bg |
logical. If |
arguments |
The arguments dataframe used to run cellid (prepared with |
pixel.type |
When |
flags |
Used to subset the input files by CellID's "flag" field. Each flag corresponds to an imaging channel, according to a "mapping" found in |
close.paths |
When TRUE and |
cell.data |
When |
tiff.channel |
When |
Using data_source = "out.tif"
will give **un** ordered boundary pixels.
See read_tiff_masks
for details and caveats.
CellID must have been run with the "encode_cellID_in_pixels" option enabled.
Using data_source = "masks.tsv"
will give ordered boundary pixels.
CellID must have been run with the "output_coords_to_tsv" option enabled.
However, in some cases, the pixel sequence may not be "manifold"
(see: https://github.com/darksideoftheshmoo/cellID-linux/issues/11).
Also, do not expect them to be consistent in their direction (clockwise or
anti-clockwise), and double check if the pixels are aligned to the output images
(see: https://github.com/darksideoftheshmoo/rcell2/issues/29).
A "cell.boundaries" data.frame.
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