Utilities
Conversions
- topaz.utils.conversions.boxes_to_coordinates(boxes, shape=None, invert_y=False, image_name=None)
- topaz.utils.conversions.coordinates_to_boxes(coords, box_width, box_height, shape=None, invert_y=False, tag='manual')
- topaz.utils.conversions.coordinates_to_eman2_json(coords, shape=None, invert_y=False, tag='manual')
- topaz.utils.conversions.coordinates_to_star(table, image_ext='')
- topaz.utils.conversions.mirror_y_axis(coords, n)
File Utilities
- topaz.utils.conversions.boxes_to_coordinates(boxes, shape=None, invert_y=False, image_name=None)
- topaz.utils.conversions.coordinates_to_boxes(coords, box_width, box_height, shape=None, invert_y=False, tag='manual')
- topaz.utils.conversions.coordinates_to_eman2_json(coords, shape=None, invert_y=False, tag='manual')
- topaz.utils.conversions.coordinates_to_star(table, image_ext='')
- topaz.utils.conversions.mirror_y_axis(coords, n)
- class topaz.mrc.MRCHeader(nx, ny, nz, mode, nxstart, nystart, nzstart, mx, my, mz, xlen, ylen, zlen, alpha, beta, gamma, mapc, mapr, maps, amin, amax, amean, ispg, next, creatid, nint, nreal, imodStamp, imodFlags, idtype, lens, nd1, nd2, vd1, vd2, tilt_ox, tilt_oy, tilt_oz, tilt_cx, tilt_cy, tilt_cz, xorg, yorg, zorg, cmap, stamp, rms, nlabl, labels)
- alpha
Alias for field number 13
- amax
Alias for field number 20
- amean
Alias for field number 21
- amin
Alias for field number 19
- beta
Alias for field number 14
- cmap
Alias for field number 44
- creatid
Alias for field number 24
- gamma
Alias for field number 15
- idtype
Alias for field number 29
- imodFlags
Alias for field number 28
- imodStamp
Alias for field number 27
- ispg
Alias for field number 22
- labels
Alias for field number 48
- lens
Alias for field number 30
- mapc
Alias for field number 16
- mapr
Alias for field number 17
- maps
Alias for field number 18
- mode
Alias for field number 3
- mx
Alias for field number 7
- my
Alias for field number 8
- mz
Alias for field number 9
- nd1
Alias for field number 31
- nd2
Alias for field number 32
- next
Alias for field number 23
- nint
Alias for field number 25
- nlabl
Alias for field number 47
- nreal
Alias for field number 26
- nx
Alias for field number 0
- nxstart
Alias for field number 4
- ny
Alias for field number 1
- nystart
Alias for field number 5
- nz
Alias for field number 2
- nzstart
Alias for field number 6
- rms
Alias for field number 46
- stamp
Alias for field number 45
- tilt_cx
Alias for field number 38
- tilt_cy
Alias for field number 39
- tilt_cz
Alias for field number 40
- tilt_ox
Alias for field number 35
- tilt_oy
Alias for field number 36
- tilt_oz
Alias for field number 37
- vd1
Alias for field number 33
- vd2
Alias for field number 34
- xlen
Alias for field number 10
- xorg
Alias for field number 41
- ylen
Alias for field number 11
- yorg
Alias for field number 42
- zlen
Alias for field number 12
- zorg
Alias for field number 43
- topaz.mrc.get_mode(dtype)
- topaz.mrc.make_header(shape, cella, cellb, mz=1, dtype=<class 'numpy.float32'>, order=(1, 2, 3), dmin=0, dmax=-1, dmean=-2, rms=-1, exthd_size=0, ispg=0)
- topaz.mrc.parse(content)
- topaz.mrc.write(f, array, header=None, extended_header=b'', ax=1, ay=1, az=1, alpha=0, beta=0, gamma=0)
Image Manipulations
- topaz.utils.image.downsample(x, factor=1, shape=None)
Downsample 2d array using fourier transform
- topaz.utils.image.quantize(x, mi=-3, ma=3, dtype=<class 'numpy.uint8'>)
- topaz.utils.image.save_image(x, path, mi=- 3, ma=3, f=None, verbose=False)
- topaz.utils.image.save_jpeg(x, path, mi=- 3, ma=3)
- topaz.utils.image.save_mrc(x, path)
- topaz.utils.image.save_png(x, path, mi=- 3, ma=3)
- topaz.utils.image.save_tiff(x, path)
- topaz.utils.image.unquantize(x, mi=-3, ma=3, dtype=<class 'numpy.float32'>)
convert quantized image array back to approximate unquantized values
Pick Masking
- topaz.utils.picks.as_mask(shape, x_coord, y_coord, radii)
Printing
- topaz.utils.printing.report(*args)
STAR File Manipulations
- topaz.utils.star.parse(f)
- topaz.utils.star.parse_star(f)
- topaz.utils.star.parse_star_body(lines)
- topaz.utils.star.parse_star_loop(lines)
- topaz.utils.star.write(table, f)
Data Utilities
Coordinate Manipulations
- topaz.utils.data.coordinates.coordinates_table_to_dict(coords)
- topaz.utils.data.coordinates.match_coordinates_to_images(coords, images, radius=- 1)
If radius >= 0, then convert the coordinates to an image mask
Image Loading
- class topaz.utils.data.loader.ImageDirectoryLoader(rootdir, pathspec='{source}/{image_name}', format='tiff', standardize=False)
- get(*args, **kwargs)
- class topaz.utils.data.loader.LabeledImageCropDataset(images, labels, crop)
- class topaz.utils.data.loader.LabeledRegionsDataset(images, labels, crop)
- class topaz.utils.data.loader.SegmentedImageDataset(images, labels, to_tensor=False)
- topaz.utils.data.loader.load_image(path, standardize=False)
- topaz.utils.data.loader.load_images_from_directory(names, rootdir, sources=None, standardize=False)
- topaz.utils.data.loader.load_images_from_list(names, paths, sources=None, standardize=False)
- topaz.utils.data.loader.load_jpeg(path, standardize=False)
- topaz.utils.data.loader.load_mrc(path, standardize=False)
- topaz.utils.data.loader.load_pil(path, standardize=False)
- topaz.utils.data.loader.load_png(path, standardize=False)
- topaz.utils.data.loader.load_tiff(path, standardize=False)
Dataset Partitioning
- topaz.utils.data.partition.kfold(k, labels, nbins=5, random=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/topaz-em/envs/latest/lib/python3.9/site-packages/numpy/random/__init__.py'>)
Split the labels in k train/test partitions by image. Labels should contain columns of source, image_name, and count, where count is the number of objects in the image.
- topaz.utils.data.partition.stratify(labels, nbins=5)
Dataset Sampling
- class topaz.utils.data.sampler.RandomImageTransforms(data, rotate=True, flip=True, crop=None, resample=2, to_tensor=False)
- class topaz.utils.data.sampler.ShuffledSampler(x, random=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/topaz-em/envs/latest/lib/python3.9/site-packages/numpy/random/__init__.py'>)
- next()
- class topaz.utils.data.sampler.StratifiedCoordinateSampler(labels, balance=0.5, size=None, random=<module 'numpy.random' from '/home/docs/checkouts/readthedocs.org/user_builds/topaz-em/envs/latest/lib/python3.9/site-packages/numpy/random/__init__.py'>, split='pn')
- next()
- topaz.utils.data.sampler.enumerate_pn_coordinates(Y)
Given a list of 2d arrays containing labels, enumerate the positive and negative coordinates as (image,coordinate) pairs.
- topaz.utils.data.sampler.enumerate_pu_coordinates(Y)
Given a list of 2d arrays containing labels, enumerate the positive and unlabeled(all) coordinates as (image,coordinate) pairs.