def convert_before_saving_as_tiff( image_plus ):
# The bUnwarpJ plug-in produces TIFF image stacks consisting of 3
# slices which can be viewed in ImageJ. The 3 slices are: 1) the
# registered image, 2) the target image and 3) the black/white warp
# image. When running bUnwarpJ from the command line (as these
# Galaxy wrappers do) the initial call to IJ.openImage() (to open the
# registered source and target images produced by bUnwarpJ) in the
# tool's jython_script.py returns an ImagePlus object with a single
# slice which is the "generally undesired" slice 3 discussed above.
# However, a call to IJ.saveAs() will convert the single-slice TIFF
# into a 3-slice TIFF image stack (as described above) if the selected
# format for saving is TIFF. Galaxy supports only single-layered
# images, so to work around this behavior, we have to convert the
# image to something other than TIFF so that slices are eliminated.
# We can then convert back to TIFF for saving. There might be a way
# to do this without converting twice, but I spent a lot of time looking
# and I have yet to discover it.
tmp_dir = imagej2_base_utils.get_temp_dir()
tmp_out_png_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'png' )
IJ.saveAs( image_plus, 'png', tmp_out_png_path )
return IJ.openImage( tmp_out_png_path )
def convert_before_saving_as_tiff(image_plus):
# The bUnwarpJ plug-in produces TIFF image stacks consisting of 3
# slices which can be viewed in ImageJ. The 3 slices are: 1) the
# registered image, 2) the target image and 3) the black/white warp
# image. When running bUnwarpJ from the command line (as these
# Galaxy wrappers do) the initial call to IJ.openImage() (to open the
# registered source and target images produced by bUnwarpJ) in the
# tool's jython_script.py returns an ImagePlus object with a single
# slice which is the "generally undesired" slice 3 discussed above.
# However, a call to IJ.saveAs() will convert the single-slice TIFF
# into a 3-slice TIFF image stack (as described above) if the selected
# format for saving is TIFF. Galaxy supports only single-layered
# images, so to work around this behavior, we have to convert the
# image to something other than TIFF so that slices are eliminated.
# We can then convert back to TIFF for saving. There might be a way
# to do this without converting twice, but I spent a lot of time looking
# and I have yet to discover it.
tmp_dir = imagej2_base_utils.get_temp_dir()
tmp_out_png_path = imagej2_base_utils.get_temporary_image_path(
tmp_dir, 'png')
IJ.saveAs(image_plus, 'png', tmp_out_png_path)
return IJ.openImage(tmp_out_png_path)
parser.add_argument( '--threshold_max', dest='threshold_max', type=float, help='Maximum threshold value' )
parser.add_argument( '--method', dest='method', help='Threshold method' )
parser.add_argument( '--display', dest='display', help='Display mode' )
parser.add_argument( '--black_background', dest='black_background', help='Black background' )
parser.add_argument( '--stack_histogram', dest='stack_histogram', help='Stack histogram' )
parser.add_argument( '--jython_script', dest='jython_script', help='Path to the Jython script' )
parser.add_argument( '--output', dest='output', help='Path to the output file' )
parser.add_argument( '--output_datatype', dest='output_datatype', help='Datatype of the output image' )
args = parser.parse_args()
tmp_dir = imagej2_base_utils.get_temp_dir()
# ImageJ expects valid image file extensions, so the Galaxy .dat extension does not
# work for some features. The following creates a symlink with an appropriate file
# extension that points to the Galaxy dataset. This symlink is used by ImageJ.
tmp_input_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.input, args.input_datatype )
tmp_output_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.output_datatype )
# Define command response buffers.
tmp_out = tempfile.NamedTemporaryFile().name
tmp_stdout = open( tmp_out, 'wb' )
tmp_err = tempfile.NamedTemporaryFile().name
tmp_stderr = open( tmp_err, 'wb' )
# Java writes a lot of stuff to stderr, so we'll specify a file for handling actual errors.
error_log = tempfile.NamedTemporaryFile( delete=False ).name
# Build the command line.
cmd = imagej2_base_utils.get_base_command_imagej2( None, jython_script=args.jython_script )
if cmd is None:
imagej2_base_utils.stop_err( "ImageJ not found!" )
cmd += ' %s' % error_log
cmd += ' %s' % tmp_input_path
cmd += ' %.3f' % args.threshold_min
cmd += ' %.3f' % args.threshold_max
parser.add_argument( '--target_out', default=None, help='Output target image' )
parser.add_argument( '--target_out_datatype', default=None, help='Output registered target image format' )
parser.add_argument( '--jython_script', dest='jython_script', help='Path to the Jython script' )
parser.add_argument( '--max_heap_size_type', dest='max_heap_size_type', help='Type (default or megabytes) of max_heap_size value' )
parser.add_argument( '--max_heap_size', dest='max_heap_size', help='Maximum size of the memory allocation pool used by the JVM.' )
args = parser.parse_args()
if args.source_trans_out is not None and args.target_trans_out is not None:
save_transformation = True
else:
save_transformation = False
tmp_dir = imagej2_base_utils.get_temp_dir()
source_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.source_image, args.source_image_format )
tmp_source_out_tiff_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'tiff' )
tmp_source_out_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.source_out_datatype )
target_image_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.target_image, args.target_image_format )
if not args.mono:
tmp_target_out_tiff_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, 'tiff' )
tmp_target_out_path = imagej2_base_utils.get_temporary_image_path( tmp_dir, args.target_out_datatype )
if args.source_mask is not None and args.target_mask is not None:
tmp_source_mask_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.source_mask, args.source_mask_format )
tmp_target_mask_path = imagej2_base_utils.get_input_image_path( tmp_dir, args.target_mask, args.target_mask_format )
if save_transformation:
# bUnwarpJ automatically names the transformation files based on the names
# of the source and target image file names. We've defined symlinks to
# temporary files with valid image extensions since ImageJ does not handle
# the Galaxy "dataset.dat" file extensions.
source_file_name = imagej2_base_utils.get_file_name_without_extension( tmp_source_out_tiff_path )
tmp_source_out_transf_path = os.path.join( tmp_dir, '%s_transf.txt' % source_file_name )
parser.add_argument('--raw_transformation',
dest='raw_transformation',
help='Raw transformation as saved by bUnwarpJ')
parser.add_argument('--source_out', help='Output source image')
parser.add_argument('--source_out_datatype',
help='Output registered source image format')
parser.add_argument('--jython_script',
dest='jython_script',
help='Path to the Jython script')
args = parser.parse_args()
tmp_dir = imagej2_base_utils.get_temp_dir()
source_image_path = imagej2_base_utils.get_input_image_path(
tmp_dir, args.source_image, args.source_image_format)
tmp_source_out_tiff_path = imagej2_base_utils.get_temporary_image_path(
tmp_dir, 'tiff')
tmp_source_out_path = imagej2_base_utils.get_temporary_image_path(
tmp_dir, args.source_out_datatype)
target_image_path = imagej2_base_utils.get_input_image_path(
tmp_dir, args.target_image, args.target_image_format)
raw_transformation_path = imagej2_base_utils.get_input_image_path(
tmp_dir, args.raw_transformation, 'txt')
# Define command response buffers.
tmp_out = tempfile.NamedTemporaryFile().name
tmp_stdout = open(tmp_out, 'wb')
tmp_err = tempfile.NamedTemporaryFile().name
tmp_stderr = open(tmp_err, 'wb')
# Build the command line to apply the raw transformation.
cmd = imagej2_base_utils.get_base_cmd_bunwarpj(None)
