def run(self, workspace):
'''Run the imageJ command'''
import imagej.ijbridge as ijbridge
J.attach()
ijb = None
try:
ijb = ijbridge.get_ij_bridge()
image_set = workspace.image_set
assert isinstance(image_set, cpi.ImageSet)
d = self.get_dictionary(workspace.image_set_list)
if self.wants_to_set_current_image:
input_image_name = self.current_input_image_name.value
img = image_set.get_image(input_image_name,
must_be_grayscale=True)
else:
img = None
#
# Run a command or macro on the first image of the set
#
if d[D_FIRST_IMAGE_SET] == image_set.number + 1:
self.do_imagej(ijb, workspace, D_FIRST_IMAGE_SET)
#
# Install the input image as the current image
#
if img is not None:
ijb.inject_image(img.pixel_data, input_image_name)
self.do_imagej(ijb, workspace)
#
# Get the output image
#
if self.wants_to_get_current_image:
output_image_name = self.current_output_image_name.value
pixel_data = ijb.get_current_image()
image = cpi.Image(pixel_data)
image_set.add(output_image_name, image)
#
# Execute the post-group macro or command
#
if d[D_LAST_IMAGE_SET] == image_set.number + 1:
self.do_imagej(ijb, workspace, D_LAST_IMAGE_SET)
#
# Save the current ImageJ image after executing the post-group
# command or macro
#
if (self.post_group_choice != CM_NOTHING
and self.wants_post_group_image):
output_image_name = self.post_group_output_image.value
pixel_data = ijb.get_current_image()
image = cpi.Image(pixel_data)
image_set.add(output_image_name, image)
if self.is_interactive():
self.display(workspace)
finally:
if ijb is not None:
del (ijb)
J.detach()
def run(self, workspace):
'''Run the imageJ command'''
import imagej.ijbridge as ijbridge
J.attach()
ijb = None
try:
ijb = ijbridge.get_ij_bridge()
image_set = workspace.image_set
assert isinstance(image_set, cpi.ImageSet)
d = self.get_dictionary(workspace.image_set_list)
if self.wants_to_set_current_image:
input_image_name = self.current_input_image_name.value
img = image_set.get_image(input_image_name,
must_be_grayscale = True)
else:
img = None
#
# Run a command or macro on the first image of the set
#
if d[D_FIRST_IMAGE_SET] == image_set.number + 1:
self.do_imagej(ijb, workspace, D_FIRST_IMAGE_SET)
#
# Install the input image as the current image
#
if img is not None:
ijb.inject_image(img.pixel_data, input_image_name)
self.do_imagej(ijb, workspace)
#
# Get the output image
#
if self.wants_to_get_current_image:
output_image_name = self.current_output_image_name.value
pixel_data = ijb.get_current_image()
image = cpi.Image(pixel_data)
image_set.add(output_image_name, image)
#
# Execute the post-group macro or command
#
if d[D_LAST_IMAGE_SET] == image_set.number + 1:
self.do_imagej(ijb, workspace, D_LAST_IMAGE_SET)
#
# Save the current ImageJ image after executing the post-group
# command or macro
#
if (self.post_group_choice != CM_NOTHING and
self.wants_post_group_image):
output_image_name = self.post_group_output_image.value
pixel_data = ijb.get_current_image()
image = cpi.Image(pixel_data)
image_set.add(output_image_name, image)
if self.is_interactive():
self.display(workspace)
finally:
if ijb is not None:
del(ijb)
J.detach()
def exit_thread(self):
from bioformats.formatreader import clear_image_reader_cache
self.notify_socket.close()
clear_image_reader_cache()
J.deactivate_awt()
J.detach()
if self.with_stop_run_loop:
stop_run_loop()
def exit_thread(self):
from bioformats.formatreader import clear_image_reader_cache
self.notify_socket.close()
clear_image_reader_cache()
J.deactivate_awt()
J.detach()
if self.with_stop_run_loop:
stop_run_loop()
def run(self, workspace):
jb.attach()#initialize JVM
input_image_name = self.input_image_name.value
output_image_name = self.output_image_name.value
self.gsize = self.input_gaussian_filter.value
self.rsize = self.input_rolling_ball.value
self.lowseed = self.input_low_seed.value
self.highseed = self.input_high_seed.value
image_set = workspace.image_set
assert isinstance(image_set, cpi.ImageSet)
#prepare input image
input_image = image_set.get_image(input_image_name, must_be_grayscale = True)
input_pixels = input_image.pixel_data
ij_processor = ijiproc.make_image_processor((input_pixels*255.0).astype('float32'))
#JavaScript API
script = """
var img=Packages.ij.ImagePlus(name,ij_processor);
Packages.ij.IJ.run(img, "8-bit", "");
var macro="g_size="+gsize+" r_size="+rsize+" low_edge="+lowseed+" high_edge="+highseed+" noise=-1";
java.lang.System.out.println(macro);
Packages.ij.IJ.run(img, "Hysteresis Segment", macro);
var output_proc=img.getProcessor();
"""
#img.show();
#Packages.ij.WindowManager.setCurrentWindow(img.getWindow());
#"""
in_params={
"name":output_image_name,
"ij_processor": ij_processor,
"gsize":self.gsize,
"rsize":self.rsize,
"lowseed":self.lowseed,
"highseed":self.highseed}
out_params={"output_proc":None}
r = jb.run_script(script, bindings_in = in_params,bindings_out = out_params)
#prepare output image
output_pixels = ijiproc.get_image(out_params["output_proc"], False)
output_image = cpi.Image(output_pixels, parent_image = input_image)
#write output
image_set.add(output_image_name, output_image)
if workspace.frame is not None:
workspace.display_data.input_pixels = input_pixels
workspace.display_data.output_pixels = output_pixels
jb.detach()#close JVM
if ((get_headless() and not os.environ.has_key("CELLPROFILER_USE_XVFB"))
or sys.platform=="darwin"):
__args += [ r"-Djava.awt.headless=true" ]
logger.debug("JVM arguments: " + " ".join(__args))
jutil.start_vm(__args)
logger.debug("Java virtual machine started.")
jutil.attach()
try:
jutil.static_call("loci/common/Location",
"cacheDirectoryListings",
"(Z)V", True)
except:
logger.warning("Bioformats version does not support directory cacheing")
finally:
jutil.detach()
# if get_headless() or sys.platform=="darwin":
# jutil.attach()
# jutil.static_call("java/lang/System", "setProperty", '(Ljava/lang/String;Ljava/lang/String;)Ljava/lang/String;', "java.awt.headless", "true")
# jutil.detach()
#
# Start the log4j logger to avoid error messages.
#
if __init_logger:
jutil.attach()
try:
jutil.static_call("org/apache/log4j/BasicConfigurator",
"configure", "()V")
log4j_logger = jutil.static_call("org/apache/log4j/Logger",
def run(my_integer=my_integer):
env = J.attach()
self.assertEqual(my_integer.intValue(), my_value)
del my_integer
J.detach()
def __del__(self):
'''call del on this object to detach from javabridge. If the object is
declared locally the javabridge will be detached once the program leaves
it's scope'''
J.detach()
def tearDown(self):
J.detach()
def tearDown(self):
J.detach()
def exit_thread(self):
self.notify_socket.close()
J.deactivate_awt()
J.detach()
if self.with_stop_run_loop:
stop_run_loop()
def interface(self,
start_signal,
image_set_start=1,
image_set_end=None,
overwrite=True):
'''Top-half thread for running an analysis. Sets up grouping for jobs,
deals with returned measurements, reports status periodically.
start_signal- signal this semaphore when jobs are ready.
image_set_start - beginning image set number to process
image_set_end - last image set number to process
overwrite - whether to recompute imagesets that already have data in initial_measurements.
'''
from cellprofiler.utilities.jutil import attach, detach
posted_analysis_started = False
acknowledged_thread_start = False
measurements = None
workspace = None
attach()
try:
# listen for pipeline events, and pass them upstream
self.pipeline.add_listener(lambda pipe, evt: self.post_event(evt))
initial_measurements = None
if self.output_path is None:
# Caller wants a temporary measurements file.
fd, filename = tempfile.mkstemp(".h5")
try:
fd = os.fdopen(fd, "wb")
fd.write(self.initial_measurements_buf)
fd.close()
initial_measurements = cpmeas.Measurements(
filename=filename, mode="r")
measurements = cpmeas.Measurements(
image_set_start=None,
copy=initial_measurements,
mode="a")
finally:
if initial_measurements is not None:
initial_measurements.close()
os.unlink(filename)
else:
with open(self.output_path, "wb") as fd:
fd.write(self.initial_measurements_buf)
measurements = cpmeas.Measurements(image_set_start=None,
filename=self.output_path,
mode="a")
# The shared dicts are needed in jobserver()
self.shared_dicts = [
m.get_dictionary() for m in self.pipeline.modules()
]
workspace = cpw.Workspace(self.pipeline, None, None, None,
measurements, cpimage.ImageSetList())
if image_set_end is None:
image_set_end = measurements.get_image_numbers()[-1]
image_sets_to_process = filter(
lambda x: x >= image_set_start and x <= image_set_end,
measurements.get_image_numbers())
self.post_event(AnalysisStarted())
posted_analysis_started = True
# reset the status of every image set that needs to be processed
has_groups = measurements.has_groups()
if self.pipeline.requires_aggregation():
overwrite = True
if has_groups and not overwrite:
if not measurements.has_feature(cpmeas.IMAGE, self.STATUS):
overwrite = True
else:
group_status = {}
for image_number in measurements.get_image_numbers():
group_number = measurements[cpmeas.IMAGE,
cpmeas.GROUP_NUMBER,
image_number]
status = measurements[cpmeas.IMAGE, self.STATUS,
image_number]
if status != self.STATUS_DONE:
group_status[
group_number] = self.STATUS_UNPROCESSED
elif group_number not in group_status:
group_status[group_number] = self.STATUS_DONE
new_image_sets_to_process = []
for image_set_number in image_sets_to_process:
needs_reset = False
if (overwrite or (not measurements.has_measurements(
cpmeas.IMAGE, self.STATUS, image_set_number)) or
(measurements[cpmeas.IMAGE, self.STATUS, image_set_number]
!= self.STATUS_DONE)):
needs_reset = True
elif has_groups:
group_number = measurements[cpmeas.IMAGE,
cpmeas.GROUP_NUMBER,
image_set_number]
if group_status[group_number] != self.STATUS_DONE:
needs_reset = True
if needs_reset:
measurements[cpmeas.IMAGE, self.STATUS, image_set_number] =\
self.STATUS_UNPROCESSED
new_image_sets_to_process.append(image_set_number)
image_sets_to_process = new_image_sets_to_process
# Find image groups. These are written into measurements prior to
# analysis. Groups are processed as a single job.
if has_groups or self.pipeline.requires_aggregation():
worker_runs_post_group = True
job_groups = {}
for image_set_number in image_sets_to_process:
group_number = measurements[cpmeas.IMAGE,
cpmeas.GROUP_NUMBER,
image_set_number]
group_index = measurements[cpmeas.IMAGE,
cpmeas.GROUP_INDEX,
image_set_number]
job_groups[group_number] = job_groups.get(
group_number, []) + [(group_index, image_set_number)]
job_groups = [[
isn for _, isn in sorted(job_groups[group_number])
] for group_number in sorted(job_groups)]
else:
worker_runs_post_group = False # prepare_group will be run in worker, but post_group is below.
job_groups = [[image_set_number]
for image_set_number in image_sets_to_process]
# XXX - check that any constructed groups are complete, i.e.,
# image_set_start and image_set_end shouldn't carve them up.
if not worker_runs_post_group:
# put the first job in the queue, then wait for the first image to
# finish (see the check of self.finish_queue below) to post the rest.
# This ensures that any shared data from the first imageset is
# available to later imagesets.
self.work_queue.put(
(job_groups[0], worker_runs_post_group, True))
waiting_for_first_imageset = True
del job_groups[0]
else:
waiting_for_first_imageset = False
for job in job_groups:
self.work_queue.put((job, worker_runs_post_group, False))
job_groups = []
start_signal.release()
acknowledged_thread_start = True
# We loop until every image is completed, or an outside event breaks the loop.
while not self.cancelled:
# gather measurements
while not self.received_measurements_queue.empty():
image_numbers, buf = self.received_measurements_queue.get()
image_numbers = [int(i) for i in image_numbers]
recd_measurements = cpmeas.load_measurements_from_buffer(
buf)
self.copy_recieved_measurements(recd_measurements,
measurements,
image_numbers)
recd_measurements.close()
del recd_measurements
# check for jobs in progress
while not self.in_process_queue.empty():
image_set_numbers = self.in_process_queue.get()
for image_set_number in image_set_numbers:
measurements[
cpmeas.IMAGE, self.STATUS,
int(image_set_number)] = self.STATUS_IN_PROCESS
# check for finished jobs that haven't returned measurements, yet
while not self.finished_queue.empty():
finished_req = self.finished_queue.get()
measurements[cpmeas.IMAGE, self.STATUS,
int(finished_req.image_set_number
)] = self.STATUS_FINISHED_WAITING
if waiting_for_first_imageset:
assert isinstance(finished_req,
ImageSetSuccessWithDictionary)
self.shared_dicts = finished_req.shared_dicts
waiting_for_first_imageset = False
assert len(self.shared_dicts) == len(
self.pipeline.modules())
# if we had jobs waiting for the first image set to finish,
# queue them now that the shared state is available.
for job in job_groups:
self.work_queue.put(
(job, worker_runs_post_group, False))
finished_req.reply(Ack())
# check progress and report
counts = collections.Counter(
measurements[cpmeas.IMAGE, self.STATUS, image_set_number]
for image_set_number in image_sets_to_process)
self.post_event(AnalysisProgress(counts))
# Are we finished?
if counts[self.STATUS_DONE] == len(image_sets_to_process):
last_image_number = measurements.get_image_numbers()[-1]
measurements.image_set_number = last_image_number
if not worker_runs_post_group:
self.pipeline.post_group(workspace, {})
workspace = cpw.Workspace(self.pipeline, None, None, None,
measurements, None, None)
workspace.post_run_display_handler = \
self.post_run_display_handler
self.pipeline.post_run(workspace)
break
measurements.flush()
# not done, wait for more work
with self.interface_work_cv:
while (self.paused
or ((not self.cancelled)
and self.in_process_queue.empty()
and self.finished_queue.empty()
and self.received_measurements_queue.empty())):
self.interface_work_cv.wait(
) # wait for a change of status or work to arrive
finally:
detach()
# Note - the measurements file is owned by the queue consumer
# after this post_event.
#
if not acknowledged_thread_start:
start_signal.release()
if posted_analysis_started:
was_cancelled = self.cancelled
self.post_event(AnalysisFinished(measurements, was_cancelled))
self.stop_workers()
self.analysis_id = False # this will cause the jobserver thread to exit
print 'big endian:', meta.getPixelsBigEndian(0, 0)
print 'dim order:', meta.getPixelsDimensionOrder(0, 0)
print 'pixel type:', meta.getPixelsPixelType(0, 0)
print 'size x:', meta.getPixelsSizeX(0, 0)
print 'size y:', meta.getPixelsSizeY(0, 0)
print 'size c:', meta.getPixelsSizeC(0, 0)
print 'size z:', meta.getPixelsSizeZ(0, 0)
print 'size t:', meta.getPixelsSizeT(0, 0)
print 'samples per pixel:', meta.getLogicalChannelSamplesPerPixel(0, 0)
writer.setMetadataRetrieve(meta)
writer.setId(out_file)
for image in images:
if len(image.shape)==3 and image.shape[2] == 3:
save_im = np.array([image[:,:,0], image[:,:,1], image[:,:,2]]).astype(np.uint8).flatten()
else:
save_im = image.astype(np.uint8).flatten()
writer.saveBytes(env.make_byte_array(save_im), (image is images[-1]))
writer.close()
print 'Done writing image :)'
# import PIL.Image as Image
# im = Image.open(out_file, 'r')
# im.show()
jutil.detach()
app.MainLoop()
def exit_thread(self):
self.notify_socket.close()
J.deactivate_awt()
J.detach()
if self.with_stop_run_loop:
stop_run_loop()
def interface(self,
start_signal,
image_set_start=1,
image_set_end=None,
overwrite=True):
'''Top-half thread for running an analysis. Sets up grouping for jobs,
deals with returned measurements, reports status periodically.
start_signal- signal this semaphore when jobs are ready.
image_set_start - beginning image set number to process
image_set_end - last image set number to process
overwrite - whether to recompute imagesets that already have data in initial_measurements.
'''
from cellprofiler.utilities.jutil import attach, detach
posted_analysis_started = False
acknowledged_thread_start = False
measurements = None
workspace = None
attach()
try:
# listen for pipeline events, and pass them upstream
self.pipeline.add_listener(lambda pipe, evt: self.post_event(evt))
initial_measurements = None
if self.output_path is None:
# Caller wants a temporary measurements file.
fd, filename = tempfile.mkstemp(".h5")
try:
fd = os.fdopen(fd, "wb")
fd.write(self.initial_measurements_buf)
fd.close()
initial_measurements = cpmeas.Measurements(
filename=filename, mode="r")
measurements = cpmeas.Measurements(
image_set_start = None,
copy = initial_measurements,
mode = "a")
finally:
if initial_measurements is not None:
initial_measurements.close()
os.unlink(filename)
else:
with open(self.output_path, "wb") as fd:
fd.write(self.initial_measurements_buf)
measurements = cpmeas.Measurements(image_set_start=None,
filename=self.output_path,
mode="a")
# The shared dicts are needed in jobserver()
self.shared_dicts = [m.get_dictionary() for m in self.pipeline.modules()]
workspace = cpw.Workspace(self.pipeline, None, None, None,
measurements, cpimage.ImageSetList())
if image_set_end is None:
image_set_end = measurements.get_image_numbers()[-1]
image_sets_to_process = filter(
lambda x: x >= image_set_start and x <= image_set_end,
measurements.get_image_numbers())
self.post_event(AnalysisStarted())
posted_analysis_started = True
# reset the status of every image set that needs to be processed
has_groups = measurements.has_groups()
if self.pipeline.requires_aggregation():
overwrite = True
if has_groups and not overwrite:
if not measurements.has_feature(cpmeas.IMAGE, self.STATUS):
overwrite = True
else:
group_status = {}
for image_number in measurements.get_image_numbers():
group_number = measurements[
cpmeas.IMAGE, cpmeas.GROUP_NUMBER, image_number]
status = measurements[cpmeas.IMAGE, self.STATUS,
image_number]
if status != self.STATUS_DONE:
group_status[group_number] = self.STATUS_UNPROCESSED
elif group_number not in group_status:
group_status[group_number] = self.STATUS_DONE
new_image_sets_to_process = []
for image_set_number in image_sets_to_process:
needs_reset = False
if (overwrite or
(not measurements.has_measurements(
cpmeas.IMAGE, self.STATUS, image_set_number)) or
(measurements[cpmeas.IMAGE, self.STATUS, image_set_number]
!= self.STATUS_DONE)):
needs_reset = True
elif has_groups:
group_number = measurements[
cpmeas.IMAGE, cpmeas.GROUP_NUMBER, image_set_number]
if group_status[group_number] != self.STATUS_DONE:
needs_reset = True
if needs_reset:
measurements[cpmeas.IMAGE, self.STATUS, image_set_number] =\
self.STATUS_UNPROCESSED
new_image_sets_to_process.append(image_set_number)
image_sets_to_process = new_image_sets_to_process
# Find image groups. These are written into measurements prior to
# analysis. Groups are processed as a single job.
if has_groups or self.pipeline.requires_aggregation():
worker_runs_post_group = True
job_groups = {}
for image_set_number in image_sets_to_process:
group_number = measurements[cpmeas.IMAGE,
cpmeas.GROUP_NUMBER,
image_set_number]
group_index = measurements[cpmeas.IMAGE,
cpmeas.GROUP_INDEX,
image_set_number]
job_groups[group_number] = job_groups.get(group_number, []) + [(group_index, image_set_number)]
job_groups = [[isn for _, isn in sorted(job_groups[group_number])]
for group_number in sorted(job_groups)]
else:
worker_runs_post_group = False # prepare_group will be run in worker, but post_group is below.
job_groups = [[image_set_number] for image_set_number in image_sets_to_process]
# XXX - check that any constructed groups are complete, i.e.,
# image_set_start and image_set_end shouldn't carve them up.
if not worker_runs_post_group:
# put the first job in the queue, then wait for the first image to
# finish (see the check of self.finish_queue below) to post the rest.
# This ensures that any shared data from the first imageset is
# available to later imagesets.
self.work_queue.put((job_groups[0],
worker_runs_post_group,
True))
waiting_for_first_imageset = True
del job_groups[0]
else:
waiting_for_first_imageset = False
for job in job_groups:
self.work_queue.put((job, worker_runs_post_group, False))
job_groups = []
start_signal.release()
acknowledged_thread_start = True
# We loop until every image is completed, or an outside event breaks the loop.
while not self.cancelled:
# gather measurements
while not self.received_measurements_queue.empty():
image_numbers, buf = self.received_measurements_queue.get()
image_numbers = [int(i) for i in image_numbers]
recd_measurements = cpmeas.load_measurements_from_buffer(buf)
self.copy_recieved_measurements(recd_measurements, measurements, image_numbers)
recd_measurements.close()
del recd_measurements
# check for jobs in progress
while not self.in_process_queue.empty():
image_set_numbers = self.in_process_queue.get()
for image_set_number in image_set_numbers:
measurements[cpmeas.IMAGE, self.STATUS, int(image_set_number)] = self.STATUS_IN_PROCESS
# check for finished jobs that haven't returned measurements, yet
while not self.finished_queue.empty():
finished_req = self.finished_queue.get()
measurements[cpmeas.IMAGE, self.STATUS, int(finished_req.image_set_number)] = self.STATUS_FINISHED_WAITING
if waiting_for_first_imageset:
assert isinstance(finished_req,
ImageSetSuccessWithDictionary)
self.shared_dicts = finished_req.shared_dicts
waiting_for_first_imageset = False
assert len(self.shared_dicts) == len(self.pipeline.modules())
# if we had jobs waiting for the first image set to finish,
# queue them now that the shared state is available.
for job in job_groups:
self.work_queue.put((job, worker_runs_post_group, False))
finished_req.reply(Ack())
# check progress and report
counts = collections.Counter(measurements[cpmeas.IMAGE, self.STATUS, image_set_number]
for image_set_number in image_sets_to_process)
self.post_event(AnalysisProgress(counts))
# Are we finished?
if counts[self.STATUS_DONE] == len(image_sets_to_process):
last_image_number = measurements.get_image_numbers()[-1]
measurements.image_set_number = last_image_number
if not worker_runs_post_group:
self.pipeline.post_group(workspace, {})
workspace = cpw.Workspace(self.pipeline,
None, None, None,
measurements, None, None)
workspace.post_run_display_handler = \
self.post_run_display_handler
self.pipeline.post_run(workspace)
break
measurements.flush()
# not done, wait for more work
with self.interface_work_cv:
while (self.paused or
((not self.cancelled) and
self.in_process_queue.empty() and
self.finished_queue.empty() and
self.received_measurements_queue.empty())):
self.interface_work_cv.wait() # wait for a change of status or work to arrive
finally:
detach()
# Note - the measurements file is owned by the queue consumer
# after this post_event.
#
if not acknowledged_thread_start:
start_signal.release()
if posted_analysis_started:
was_cancelled = self.cancelled
self.post_event(AnalysisFinished(measurements, was_cancelled))
self.stop_workers()
self.analysis_id = False # this will cause the jobserver thread to exit
"()Ljava/lang/ClassLoader;")
def get_plugin(classname):
'''Return an instance of the named plugin'''
if classname.startswith("ij."):
cls = J.class_for_name(classname)
else:
cls = J.class_for_name(classname, get_user_loader())
cls = J.get_class_wrapper(cls, True)
constructor = J.get_constructor_wrapper(cls.getConstructor(None))
return constructor.newInstance(None)
if __name__ == "__main__":
import sys
J.attach()
try:
commands = get_commands()
print "Commands: "
for command in commands:
print "\t" + command
if len(sys.argv) == 2:
execute_command(sys.argv[1])
elif len(sys.argv) > 2:
execute_command(sys.argv[1], sys.argv[2])
finally:
J.detach()
J.kill_vm()
def __del__(self):
'''call del on this object to detach from javabridge. If the object is
declared locally the javabridge will be detached once the program leaves
it's scope'''
J.detach()
def run(my_integer = my_integer):
env = J.attach()
self.assertEqual(my_integer.intValue(),my_value)
del my_integer
J.detach()
def get_plugin(classname):
"""Return an instance of the named plugin"""
if classname.startswith("ij."):
cls = J.class_for_name(classname)
else:
cls = J.class_for_name(classname, get_user_loader())
cls = J.get_class_wrapper(cls, True)
constructor = J.get_constructor_wrapper(cls.getConstructor(None))
return constructor.newInstance(None)
if __name__ == "__main__":
import sys
J.attach()
try:
commands = get_commands()
print "Commands: "
for command in commands:
print "\t" + command
if len(sys.argv) == 2:
execute_command(sys.argv[1])
elif len(sys.argv) > 2:
execute_command(sys.argv[1], sys.argv[2])
finally:
J.detach()
J.kill_vm()
def __exit__(self, type, value, traceback):
self.notify_socket.close()
for m in self.initial_measurements.values():
m.close()
self.initial_measurements = {}
J.detach()
