1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290
|
#!/usr/bin/env python
# coding: utf-8
#
# Project: X-ray image reader
# https://github.com/silx-kit/fabio
#
#
# Copyright (C) European Synchrotron Radiation Facility, Grenoble, France
#
# Principal author: Jérôme Kieffer (Jerome.Kieffer@ESRF.eu)
#
# Permission is hereby granted, free of charge, to any person
# obtaining a copy of this software and associated documentation files
# (the "Software"), to deal in the Software without restriction,
# including without limitation the rights to use, copy, modify, merge,
# publish, distribute, sublicense, and/or sell copies of the Software,
# and to permit persons to whom the Software is furnished to do so,
# subject to the following conditions:
#
# The above copyright notice and this permission notice shall be
# included in all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
# EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
# OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
# NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
# HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
# WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
# FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
# OTHER DEALINGS IN THE SOFTWARE.
"""Convert a sparse fileformat (Generated by sparsify-Bragg from pyFAI) to a dense
stack of frames in Eiger, Lima ... images.
"""
__author__ = "Jerome Kieffer"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
__licence__ = "MIT"
__date__ = "05/11/2021"
__status__ = "production"
FOOTER = """
"""
import logging
logging.basicConfig()
logger = logging.getLogger("densify")
import sys
import argparse
import os
import time
import multiprocessing.pool
import json
import numpy
from .. import eigerimage, limaimage, sparseimage
from ..openimage import openimage as fabio_open
from .._version import version as fabio_version
from ..utils.cli import ProgressBar, expand_args
from ..nexus import Nexus
try:
import hdf5plugin
import h5py
except ImportError:
pass
EXIT_SUCCESS = 0
EXIT_FAILURE = 1
EXIT_ARGUMENT_FAILURE = 2
def parse_args():
"""Parse command line arguments and returns those arguments"""
epilog = """return codes: 0 means a success. 1 means the conversion
contains a failure, 2 means there was an error in the
arguments"""
parser = argparse.ArgumentParser(prog="densify",
description=__doc__,
epilog=epilog)
parser.add_argument("IMAGE", nargs="*",
help="File with input images")
parser.add_argument("-V", "--version", action='version', version=fabio_version,
help="output version and exit")
parser.add_argument("-v", "--verbose", action='store_true', dest="verbose", default=False,
help="show information for each conversions")
parser.add_argument("--debug", action='store_true', dest="debug", default=False,
help="show debug information")
group = parser.add_argument_group("main arguments")
group.add_argument("-l", "--list", action="store_true", dest="list", default=None,
help="show the list of available output formats and exit")
group.add_argument("-o", "--output", default=None, type=str,
help="output filename, by default {baseame}_densify.h5")
group.add_argument("-O", "--output-format", dest="format", default='lima', type=str,
help="output format among 'lima', 'eiger' ...")
group.add_argument("-D", "--dummy", type=int, default=None,
help="Set masked values to this dummy value")
group = parser.add_argument_group("optional behaviour arguments")
# group.add_argument("-f", "--force", dest="force", action="store_true", default=False,
# help="if an existing destination file cannot be" +
# " opened, remove it and try again (this option" +
# " is ignored when the -n option is also used)")
# group.add_argument("-n", "--no-clobber", dest="no_clobber", action="store_true", default=False,
# help="do not overwrite an existing file (this option" +
# " is ignored when the -i option is also used)")
# group.add_argument("--remove-destination", dest="remove_destination", action="store_true", default=False,
# help="remove each existing destination file before" +
# " attempting to open it (contrast with --force)")
# group.add_argument("-u", "--update", dest="update", action="store_true", default=False,
# help="copy only when the SOURCE file is newer" +
# " than the destination file or when the" +
# " destination file is missing")
# group.add_argument("-i", "--interactive", dest="interactive", action="store_true", default=False,
# help="prompt before overwrite (overrides a previous -n" +
# " option)")
group.add_argument("--dry-run", dest="dry_run", action="store_true", default=False,
help="do everything except modifying the file system")
group.add_argument("-N", "--noise", type=float, dest="noisy", default=1.0,
help="Noise scaling factor, from 0 to 1, set to 0 to disable the noise reconstruction")
# group = parser.add_argument_group("Image preprocessing (Important: applied in this order!)")
# group.add_argument("--rotation", type=int, default=180,
# help="Rotate the initial image by this value in degrees. Must be a multiple of 90°. By default 180 deg (flip_up with origin=lower and flip_lr because the image is seen from the sample).")
# group.add_argument("--transpose", default=False, action="store_true",
# help="Flip the x/y axis")
# group.add_argument("--flip-ud", dest="flip_ud", default=False, action="store_true",
# help="Flip the image upside-down")
# group.add_argument("--flip-lr", dest="flip_lr", default=False, action="store_true",
# help="Flip the image left-right")
try:
args = parser.parse_args()
if args.debug:
logger.setLevel(logging.DEBUG)
if args.list:
print("Supported output formats: LimaImage, EigerImage, soon NxMx")
return EXIT_SUCCESS
if len(args.IMAGE) == 0:
raise argparse.ArgumentError(None, "No input file specified.")
# the upper case IMAGE is used for the --help auto-documentation
args.images = expand_args(args.IMAGE)
args.images.sort()
args.format = args.format.lower()
except argparse.ArgumentError as e:
logger.error(e.message)
logger.debug("Backtrace", exc_info=True)
return EXIT_ARGUMENT_FAILURE
return args
def load_param(fn):
"Extract compression parameters from a sparse HDF5 file"
with Nexus(fn, "r") as nxs:
ndata = nxs.get_default_NXdata()
mask = numpy.uint32(1) - numpy.isfinite(ndata["mask"])
nframes = ndata["background_avg"].shape[0]
config = ndata.parent["sparsify/configuration/data"][()]
dico = json.loads(config)
dico["mask"] = mask
dico["nframes"] = nframes
return dico
def save_master(outfile, sparsefile):
"Save a master file in addition to the data file, ala Dectris"
s = os.path.splitext(outfile)[0][-1::-1].split("_", 1)
p = 1 if len(s) > 1 else 0
master = s[p][-1::-1] + "_master.h5"
if os.path.exists(master):
logger.warning("Master file exists, skipping")
else:
try:
import pyFAI
except ImportError:
logger.error("Master file generation requires pyFAI")
else:
logger.info("Create master file")
d = load_param(sparsefile)
ai = pyFAI.load(d["geometry"])
with Nexus(master, mode="w") as nxs:
entry = nxs.new_entry(program_name=None, force_name=True)
data = nxs.new_class(entry, "data", "NXdata")
data["data_000001"] = h5py.ExternalLink(outfile, "entry/data/data")
instrument = nxs.new_class(entry, "instrument", "NXinstrument")
beam = nxs.new_class(instrument, "beam", "NXbeam")
if ai.wavelength is not None:
beam["incident_wavelength"] = numpy.float32(1e10 * ai.wavelength)
beam["incident_wavelength"].attrs["units"] = "angstrom"
detector = nxs.new_class(instrument, "detector", "NXdetector")
detector["beam_center_x"] = numpy.float32(ai.getFit2D()["centerX"])
detector["beam_center_x"].attrs["unit"] = "pixel"
detector["beam_center_y"] = numpy.float32(ai.getFit2D()["centerY"])
detector["beam_center_y"].attrs["unit"] = "pixel"
detector["description"] = ai.detector.name
detector["distance"] = ai.dist
spec = nxs.new_class(detector, "detectorSpecific", "NXcollection")
spec["flatfield_correction_applied"] = numpy.int32(1)
detector["pixel_mask_applied"] = numpy.int32(1)
detector["x_pixel_size"] = numpy.float32(ai.detector.pixel2)
detector["y_pixel_size"] = numpy.float32(ai.detector.pixel2)
nxs.h5["/entry/instrument/detector/detectorSpecific/pixel_mask"] = d["mask"]
nxs.h5["/entry/instrument/detector/detectorSpecific/nimages"] = numpy.uint32(d["nframes"])
class Converter:
"Convert sparse format to dense HDF5 format"
def __init__(self, args):
self.args = args
self.pb = ProgressBar("Decompression", 50, 50)
sparseimage.SparseImage.NOISY = self.args.noisy
def decompress_one(self, filename):
"Decompress one input files"
self.pb.update(0, "Read input data")
t0 = time.perf_counter()
sparse = fabio_open(filename)
assert isinstance(sparse, sparseimage.SparseImage)
t1 = time.perf_counter()
if self.args.dummy is not None:
sparse.dummy = self.args.dummy
self.pb.max_value = sparse.nframes
if self.args.format.startswith("lima"):
dest = limaimage.LimaImage()
elif self.args.format.startswith("eiger"):
dest = eigerimage.EigerImage()
dest.dataset = [numpy.empty((sparse.nframes,) + sparse.shape, sparse.dtype)]
else:
raise RuntimeError(f"Unsupported output format {self.args.format}")
self.pb.update(1, "Create thread pool")
pool = multiprocessing.pool.ThreadPool(multiprocessing.cpu_count())
self.pb.update(1, "Populate thread pool")
future_frames = {idx: pool.apply_async(sparse._generate_data, (idx,))
for idx in range(sparse.nframes)}
pool.close()
for idx, future_frame in future_frames.items():
self.pb.update(idx, f"Decompress frame #{idx:04d}")
dest.set_data(future_frame.get(), idx)
pool.join()
# dest.set_data
t2 = time.perf_counter()
output = self.args.output
if self.args.output is None:
if self.args.format.startswith("lima"):
output = os.path.splitext(filename)[0] + "_dense.h5"
elif self.args.format.startswith("eiger"):
output = os.path.splitext(filename)[0] + "_000001.h5"
self.pb.update(self.pb.max_value, f"Save {output}")
dest.save(output)
if self.args.format.startswith("eiger"):
save_master(output, filename)
t3 = time.perf_counter()
self.pb.clear()
print(f"Densify of {filename} --> {output} took:")
print(f"Read input: {t1-t0:.3f}s")
print(f"Decompress: {t2-t1:.3f}s")
print(f"Write outp: {t3-t2:.3f}s")
def decompress(self):
"Decompress all input files"
for filename in self.args.images:
self.decompress_one(filename)
def main():
args = parse_args()
if args == EXIT_ARGUMENT_FAILURE:
raise
try:
c = Converter(args)
c.decompress()
except Exception as err:
logger.error(err.message)
logger.debug("Backtrace", exc_info=True)
return EXIT_FAILURE
else:
return EXIT_SUCCESS
if __name__ == "__main__":
sys.exit(main())
|