Preprocess

usage: preprocess [-h] [-s SCALE] [--affine] [--sample SAMPLE]
                  [--niters NITERS] [-a ALPHA] [-b BETA] [--metadata]
                  [-d DEVICE] [-t NUM_WORKERS] [-j NUM_THREADS] [-o DESTDIR]
                  [--format FORMAT_] [-v]
                  files [files ...]

Positional Arguments

files

Named Arguments

-s, --scale

downsample images by this factor (default: 1)

Default: 1

--affine

use standard normalization (x-mu)/std of whole image rather than GMM normalization

Default: False

--sample

pixel sampling factor for model fit. speeds up estimation of parameters but introduces sample error if set >1. (default: 10)

Default: 10

--niters

maximum number of EM iterations to run for model fit (default: 100)

Default: 100

-a, --alpha

alpha parameter of the beta distribution prior on the mixing proportion (default: 900)

Default: 900

-b, --beta

beta parameter of the beta distribution prior on the mixing proportion (default: 1)

Default: 1

--metadata

if set, save parameter metadata for each micrograph

Default: False

-d, --device

which device to use, set to -1 to force CPU. >=0 specifies GPU number (default: -1)

Default: -1

-t, --num-workers

number of parallel processes to use, 0 specifies main process only (default: 0)

Default: 0

-j, --num-threads

number of threads for pytorch, 0 uses pytorch defaults, <0 uses all cores (default: 0)

Default: 0

-o, --destdir

output directory

--format

image format(s) to write. choices are mrc, tiff, and png. images can be written in multiple formats by specifying each in a comma separated list, e.g. mrc,png would write mrc and png format images (default: mrc)

Default: “mrc”

-v, --verbose

verbose output

Default: False