Python EMApp.show_specific方法代码示例

# 需要导入模块: from emapplication import EMApp [as 别名]
# 或者: from emapplication.EMApp import show_specific [as 别名]
def main():
	progname = os.path.basename(sys.argv[0])
	usage = """prog

	Presents a graphical representation of the orientation distribution of the particles in a single particle
	reconstruction. This is displayed as a single asymmetric unit on a sphere, with cylinders of varying height
	representing the number of particles found in each orientation. Middle-click will produce a control-panel
	as usual, and clicking on a single peak will permit viewing the class-average and related projection
	(and particles).

	Normally launched without arguments from a e2workflow project directory.

"""

	parser = EMArgumentParser(usage=usage,version=EMANVERSION)
	parser.add_header(name="e2eulerxplorheader", help="Click Launch to Run e2eulerxplor.py", title="### Click Launch to Run e2eulerxplor.py ###", row=0, col=0, rowspan=1, colspan=3)
	parser.add_argument("--eulerdata", "-e", type=str,help="File for Eulerdata, Ryan style, if none is given, data is read from the DB.",default=None)
	parser.add_argument("--ppid", type=int, help="Set the PID of the parent process, used for cross platform PPID",default=-1)
	parser.add_argument("--verbose", "-v", dest="verbose", action="store", metavar="n", type=int, default=0, help="verbose level [0-9], higner number means higher level of verboseness")

	global options
	(options, args) = parser.parse_args()


	logid=E2init(sys.argv,options.ppid)

	em_app = EMApp()
	window = EMEulerWidget(file_name = options.eulerdata)
	em_app.show_specific(window)
	em_app.execute()

	E2end(logid)

# 需要导入模块: from emapplication import EMApp [as 别名]
# 或者: from emapplication.EMApp import show_specific [as 别名]
def main():
	
	usage="[prog] <2D image file> "
	parser = EMArgumentParser(usage=usage,version=EMANVERSION)
	(options, args) = parser.parse_args()
	logid=E2init(sys.argv)


	
	filename=args[0]
	
	app = EMApp()
	img=EMData(filename)
	
	
	#print img[0]["mean"]
	w=EMBreakBrick(img,app)
	#w.set_data(img,filename)
	
	app.show_specific(w)
	app.exec_()
	
	
	
	
	
	E2end(logid)

# 需要导入模块: from emapplication import EMApp [as 别名]
# 或者: from emapplication.EMApp import show_specific [as 别名]
def main():
	progname = os.path.basename(sys.argv[0])
	usage = progname + """ [options] <xml>
	Convert xml to txt and optionally display them.
	"""
	
	args_def = {'display':1}	
	parser = argparse.ArgumentParser()
	parser.add_argument("xml", nargs='*', help="specify xml files to be processed")
	parser.add_argument("-d", "--display", type=int, help="disply (1) or not (0), by default {}".format(args_def['display']))
	args = parser.parse_args()
	
	if len(sys.argv) == 1:
		print "usage: " + usage
		print "Please run '" + progname + " -h' for detailed options."
		sys.exit(1)
	# get default values
	for i in args_def:
		if args.__dict__[i] == None:
			args.__dict__[i] = args_def[i]
	#		
	for xml in args.xml:
		with open(xml+'.txt', 'w') as w_txt:
			for coord in XE.parse(xml).getroot():
				for xy in coord:
					if xy.tag == 'x':
						w_txt.write(xy.text + '\t')
					else:
						w_txt.write(xy.text + '\n')
	# display
	if args.display == 1:
		app = EMApp()
		for xml in args.xml:
			filename = xml+'.txt'
			w = EMWidgetFromFile(filename,application=app,force_2d=False)
			w.setWindowTitle(base_name(filename))
			app.show_specific(w)
		app.exec_()			

# 需要导入模块: from emapplication import EMApp [as 别名]
# 或者: from emapplication.EMApp import show_specific [as 别名]
def main():
	
	usage="Generate training set for tomogram segmentation. This program is still experimental. Please consult the developers before using. "
	print usage
	parser = EMArgumentParser(usage=usage,version=EMANVERSION)
	parser.add_header(name="tmpheader", help='temp label', title="### This program is NOT avaliable yet... ###", row=0, col=0, rowspan=1, colspan=2, mode="box,seg,set")
	#### boxing ####
	parser.add_argument("--boxing",action="store_true",help="Boxing particles.",default=False, guitype='boolbox', row=4, col=0, rowspan=1, colspan=1, mode='box[True]')
	parser.add_pos_argument(name="micrographs",help="List the file to process with e2boxer here.", default="", guitype='filebox', browser="EMRawDataTable(withmodal=True,startpath=\"rawtomograms\")",  row=1, col=0,rowspan=1, colspan=3, mode="box")
	parser.add_argument("--boxsize","-B",type=int,help="Box size in pixels",default=-1, guitype='intbox', row=3, col=0, rowspan=1, colspan=3, mode="box")
	
	#### segment ####
	#parser.add_header(name="instruction", help='instruction', title="### Mark the target features white ###", row=0, col=0, rowspan=1, colspan=2, mode="seg")
	parser.add_argument("--segment",action="store_true",help="Segment particles.",default=False, guitype='boolbox', row=4, col=0, rowspan=1, colspan=1, mode='seg[True]')
	parser.add_pos_argument(name="particles",help="Particle file.", default="", guitype='filebox', browser="EMParticlesTable(withmodal=True)",  row=1, col=0,rowspan=1, colspan=3, mode="seg")
	parser.add_argument("--output", type=str,help="output file name. Default is the input particle file name plus _seg.hdf", default=None,guitype='strbox', row=3, col=0, rowspan=1, colspan=3, mode="seg")
	
	
	#### build set ####
	parser.add_argument("--buildset",action="store_true",help="Segment particles.",default=False, guitype='boolbox', row=7, col=0, rowspan=1, colspan=1, mode='set[True]')
	parser.add_argument("--particles_raw", type=str,help="Input raw particle file", default=None,guitype='filebox',browser="EMParticlesTable(withmodal=True)", row=1, col=0, rowspan=1, colspan=3, mode="set")
	parser.add_argument("--particles_label", type=str,help="Input labels for particle file", default=None,guitype='filebox',browser="EMParticlesTable(withmodal=True)", row=2, col=0, rowspan=1, colspan=3, mode="set")
	parser.add_argument("--boxes_negative", type=str,help="Input boxes of negative samples", default=None,guitype='filebox',browser="EMParticlesTable(withmodal=True)", row=3, col=0, rowspan=1, colspan=3, mode="set")
	parser.add_argument("--ncopy",type=int,help="Number of copies for NEGATIVE samples. (number of copies of particles is calculated accordingly) ",default=20, guitype='intbox', row=5, col=0, rowspan=1, colspan=1, mode="set")
	parser.add_argument("--trainset_output", type=str,help="output file name of the training set.Default is the input particle file name plus _trainset.hdf", default=None,guitype='strbox', row=4, col=0, rowspan=1, colspan=3, mode="set")

	##################
	parser.add_argument("--ppid", type=int, help="Set the PID of the parent process, used for cross platform PPID",default=-1)
	(options, args) = parser.parse_args()
	logid=E2init(sys.argv)
	
	#### boxing ###
	if options.boxing:
		db = js_open_dict(EMBOXERBASE_DB)
		cache_box_size = True
		if options.boxsize == -1:
			cache_box_size = False
			options.boxsize = db.setdefault("box_size",64)

		application = EMApp()
		module = EMBoxerModule(args,options.boxsize)
		module.show_interfaces()

		application.execute(logid)
	
	
	#### segment ###
	if options.segment:
		filename=args[0]
		if options.output==None:
			options.output=filename[:-4]+"_seg.hdf"
		app = EMApp()
		img=EMData.read_images(filename)
		#print img[0]["mean"]
		w=EMImageWidget(data=img,old=None,app=app,force_2d=True)
		#w = EMWidgetFromFile(filename,application=app,force_2d=True)
		w.setWindowTitle(base_name(filename))
		w.show_inspector(1)
		ins=w.get_inspector()
		ins.mmtab.setCurrentIndex(5)
		ins.dtpenv.setText('100')
		w.set_mouse_mode(5)
		app.show_specific(w)
		app.exec_()
		try: os.remove(options.output)
		except:pass
		for e in img:
			e.process_inplace("threshold.belowtozero", {"minval":99})
			e.process_inplace("threshold.binary", {"value":1})
			e.write_image(options.output,-1)
			
	#### build set ###
	
	if options.buildset:
		tomo_in=options.particles_raw
		seg_in=options.particles_label
		neg_in=options.boxes_negative
		if tomo_in and neg_in and seg_in:
			n_ptcl=EMUtil.get_image_count(tomo_in)
			n_neg=EMUtil.get_image_count(neg_in)
			if options.trainset_output==None:
				options.trainset_output=tomo_in[:-4]+"_trainset.hdf"
			p_copy=options.ncopy*n_neg/n_ptcl
		else:
			p_copy=options.ncopy
		try: os.remove(options.trainset_output)
		except: pass
		print "making {} copies for particles, and {} copies for negative samples".format(p_copy,options.ncopy)
		if tomo_in and seg_in:
			n_ptcl=EMUtil.get_image_count(tomo_in)
			for i in range(n_ptcl):
				t=EMData(tomo_in,i)
				s=EMData(seg_in,i)
				for c in range(p_copy):
					tr=Transform()
					rd=random.random()*360
					tr.set_rotation({"type":"2d","alpha":rd})
					e=t.process("xform",{"transform":tr})
					#e.process_inplace("normalize")
					e.write_image(options.trainset_output,-1)
#.........这里部分代码省略.........