API

I/O

io.read_img(path[, colors, z_slices, ...])	Read image file.
io.read_fov(path, fov[, series, colors, ...])	Read FOV from MERFISH experiment.
io.read_mosaic(path, series[, colors, fovs, ...])	Read FOV images as a mosaic.
io.list_fovs(path[, file_pattern])	List FOV files.
io.read_dax(path[, frames, shape, dtype])	Read a MERFISH formatted dax file.
io.read_xml(path[, parse, parse_colors])	Read MERFISH formatted xml file.
io.read_color_usage(path)	Read MERFISH color usage file.

Plotting

pl.imshow(X[, colors, norm, vmin, vmax, ...])

Display image with specified colors

Correction

correct.illumination(img, colors, corr_path)	Correct image illumination.
correct.color_normalization(intensities, colors)	Normalize channel intensities by color.
correct.spot_alignment(spots, alignment[, ...])	Adjust spot coordinates based on alignment.

Filters

filters.deconwolf(img, colors[, z_step, ...])	Deconwolf deconvolution.
filters.unsharp_mask(img[, sigma, truncate, ...])	Gaussian unsharp mask.

Decode

decode.spot_intensities(img, x, y[, z, ...])	Get spot intensities.
decode.expectation_maximization(intensities, ...)	Decode intensities using expectation maximization.
decode.logistic_regression(intensities, weights)	Decode intensities using logistic regression.

Segmentation

seg.masks_to_polygons(masks[, tolerance, id, z])	Covert segmentation masks to polygons.
seg.polygons_to_masks(polygons, bounds, shape)	Convert polygons to segmentation masks.
seg.fix_overlaps(polygons[, min_ioa, cell, ...])	Fix overlapping polygons from adjacent FOVs.
seg.polygon_properties(polygons[, cell, z])	Calculate geometric properties of polygons.
seg.assign_spots(spots, polygons[, ...])	Assigns spots to the nearest polygon

Utilities

utils.tile_polygons(polygons[, tile_shape, ...])	Split polygons into tiles.
utils.tile_image(image[, tile_shape])	Split image into tiles.
utils.create_mosaic(imgs, positions[, ...])	Create mosaic from images.
utils.determine_fov_format(path, series[, ...])	Determine FOV format.