Mercurial > repos > iuc > spyboat
view spyboat_cli.py @ 0:76733d05d8ef draft
"planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/packages/spyboat commit 5c60a414c785246371beac23ce52d8bbab3602d1"
author | iuc |
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date | Sat, 28 Nov 2020 13:45:34 +0000 |
parents | |
children | 639d2031d998 |
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#!/usr/bin/env python # Gets interfaced by Galaxy or can be used for bash scripting import argparse import logging import os import sys import output_report import spyboat from numpy import float32 from skimage import io logging.basicConfig(level=logging.INFO, stream=sys.stdout, force=True) logger = logging.getLogger('spyboat-cli') # ----------command line parameters --------------- parser = argparse.ArgumentParser(description='Process some arguments.') # I/O parser.add_argument('--input_path', help="Input movie location", required=True) parser.add_argument('--phase_out', help='Phase output file name', required=False) parser.add_argument('--period_out', help='Period output file name', required=False) parser.add_argument('--power_out', help='Power output file name', required=False) parser.add_argument('--amplitude_out', help='Amplitude output file name', required=False) parser.add_argument('--preprocessed_out', help="Preprocessed-input output file name", required=False) # (Optional) Multiprocessing parser.add_argument('--ncpu', help='Number of processors to use', required=False, type=int, default=1) # Optional spatial downsampling parser.add_argument('--rescale_factor', help='Rescale the image by a factor given in %%, None means no rescaling', required=False, type=int) # Optional Gaussian smoothing parser.add_argument('--gauss_sigma', help='Gaussian smoothing parameter, None means no smoothing', required=False, type=float) # Wavelet Analysis Parameters parser.add_argument('--dt', help='Sampling interval', required=True, type=float) parser.add_argument('--Tmin', help='Smallest period', required=True, type=float) parser.add_argument('--Tmax', help='Biggest period', required=True, type=float) parser.add_argument('--nT', help='Number of periods to scan for', required=True, type=int) parser.add_argument('--Tcutoff', help='Sinc cut-off period, disables detrending if not set', required=False, type=float) parser.add_argument('--win_size', help='Sliding window size for amplitude normalization, None means no normalization', required=False, type=float) # Optional masking parser.add_argument('--masking', help="Set to either 'dynamic', 'static' or 'None' which is the default", default='None', required=False, type=str) parser.add_argument('--mask_frame', help="The frame of the input movie to create a static mask from, needs masking set to 'static'", required=False, type=int) parser.add_argument('--mask_thresh', help='The threshold of the mask, all pixels with less than this value get masked (if masking enabled).', required=False, type=float, default=0) # output html report/snapshots parser.add_argument('--html_fname', help="Name of the html report.", default='OutputReport.html', required=False, type=str) parser.add_argument('--report_img_path', help="For the html report, to be set in Galaxy. Without galaxy leave at cwd!", default='.', required=False, type=str) parser.add_argument('--version', action='version', version='0.1.0') arguments = parser.parse_args() logger.info("Received following arguments:") for arg in vars(arguments): logger.info(f'{arg} -> {getattr(arguments, arg)}') # ------------Read the input---------------------------------------- try: movie = spyboat.open_tif(arguments.input_path) except FileNotFoundError: logger.critical(f"Couldn't open {arguments.input_path}, check movie storage directory!") sys.exit(1) # problems get logged in 'open_tif' if movie is None: sys.exit(1) # -------- Do (optional) spatial downsampling --------------------------- scale_factor = arguments.rescale_factor # defaults to None if not scale_factor: logger.info('No downsampling requested..') elif 0 < scale_factor < 100: logger.info(f'Downsampling the movie to {scale_factor:d}% of its original size..') movie = spyboat.down_sample(movie, scale_factor / 100) else: raise ValueError('Scale factor must be between 0 and 100!') # -------- Do (optional) pre-smoothing ------------------------- # note that downsampling already is a smoothing operation.. # check if pre-smoothing requested if not arguments.gauss_sigma: logger.info('No pre-smoothing requested..') else: logger.info(f'Pre-smoothing the movie with Gaussians, sigma = {arguments.gauss_sigma:.2f}..') movie = spyboat.gaussian_blur(movie, arguments.gauss_sigma) # ----- Set up Masking before processing ---- mask = None if arguments.masking == 'static': if not arguments.mask_frame: logger.critical("Frame number for static masking is missing!") sys.exit(1) if (arguments.mask_frame > movie.shape[0]) or (arguments.mask_frame < 0): logger.critical(f'Requested frame does not exist, input only has {movie.shape[0]} frames.. exiting') sys.exit(1) else: logger.info(f'Creating static mask from frame {arguments.mask_frame} with threshold {arguments.mask_thresh}') mask = spyboat.create_static_mask(movie, arguments.mask_frame, arguments.mask_thresh) elif arguments.masking == 'dynamic': logger.info(f'Creating dynamic mask with threshold {arguments.mask_thresh}') mask = spyboat.create_dynamic_mask(movie, arguments.mask_thresh) else: logger.info('No masking requested..') # ------ Retrieve wavelet parameters --------------------------- Wkwargs = {'dt': arguments.dt, 'Tmin': arguments.Tmin, 'Tmax': arguments.Tmax, 'nT': arguments.nT, 'T_c': arguments.Tcutoff, # defaults to None 'win_size': arguments.win_size # defaults to None } # --- start parallel processing --- results = spyboat.run_parallel(movie, arguments.ncpu, **Wkwargs) # --- masking? --- if mask is not None: # mask all output movies (in place!) for key in results: logger.info(f'Masking {key}') spyboat.apply_mask(results[key], mask, fill_value=-1) # --- Produce Output HTML Report Figures/png's --- # create the directory, yes we have to do that ourselves :) # galaxy then magically renders the html from that directory try: if arguments.report_img_path != '.': logger.info(f'Creating report directory {arguments.report_img_path}') os.mkdir(arguments.report_img_path) # 4 snapshots each Nsnap = 7 NFrames = movie.shape[0] # show only frames at least one Tmin # away from the edge (-effects) start_frame = int(Wkwargs['Tmin'] / Wkwargs['dt']) if (start_frame > NFrames // 2): logger.warning("Smallest period already is larger than half the observation time!") # set to 0 in this case start_frame = 0 frame_increment = int((NFrames - 2 * start_frame) / Nsnap) snapshot_frames = range(start_frame, NFrames - start_frame, frame_increment) for snapshot_frame in snapshot_frames: output_report.produce_snapshots(movie, results, snapshot_frame, Wkwargs, img_path=arguments.report_img_path) output_report.produce_distr_plots(results, Wkwargs, img_path=arguments.report_img_path) output_report.create_html(snapshot_frames, arguments.html_fname) except FileExistsError as e: logger.critical(f"Could not create html report directory: {repr(e)}") # --- save out result movies --- # None means output is filtered from galaxy settings if arguments.phase_out is not None: # save phase movie io.imsave(arguments.phase_out, results['phase'], plugin="tifffile") logger.info(f'Written phase to {arguments.phase_out}') if arguments.period_out is not None: # save period movie io.imsave(arguments.period_out, results['period'], plugin="tifffile") logger.info(f'Written period to {arguments.period_out}') if arguments.power_out is not None: # save power movie io.imsave(arguments.power_out, results['power'], plugin="tifffile") logger.info(f'Written power to {arguments.power_out}') if arguments.amplitude_out is not None: # save amplitude movie io.imsave(arguments.amplitude_out, results['amplitude'], plugin="tifffile") logger.info(f'Written amplitude to {arguments.amplitude_out}') # save out the probably pre-processed (scaled and blurred) input movie for # direct comparison to results and coordinate mapping etc. if arguments.preprocessed_out is not None: io.imsave(arguments.preprocessed_out, movie.astype(float32), plugin='tifffile') logger.info(f'Written preprocessed to {arguments.preprocessed_out}')