259 lines
8.1 KiB
Python
259 lines
8.1 KiB
Python
from ijutils import *
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from ch.psi.pshell.imaging.Overlays import *
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from ch.psi.pshell.imaging.Utils import *
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import ch.psi.pshell.imaging.Pen as Pen
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import java.awt.Rectangle as Rectangle
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import ch.psi.pshell.imaging.Data as Data
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import ch.psi.pshell.device.Camera.DataType as DataType
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eiger.setDataType(DataType.Float32)
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eiger.getDataArray().monitored=True
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###############################################################################
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# ROI Integration
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###############################################################################
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def integrate_roi(source, x,y, w, h):
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if source.data is None:
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source.update()
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roi = source.data.getRoi(Rectangle(x,y, w, h))
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return roi.integrate(False)
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class RoiIntensitySourceListener (ImageListener):
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def __init__(self, parent):
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self.parent = parent
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def onImage(self, origin, image, data):
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self.parent.update()
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def onError(self, origin, ex):
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pass
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class RoiIntensity(ReadonlyRegisterBase):
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def __init__(self, name, source, x,y, w, h):
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ReadonlyRegisterBase.__init__(self, name)
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self.source=source
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self.roi = x,y, w, h
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self.source_listener = RoiIntensitySourceListener(self)
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def doRead(self):
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x,y, w, h = self.roi
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return integrate_roi(self.source, x,y, w, h)
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def doSetMonitored(self, value):
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if value:
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self.source.addListener(self.source_listener)
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else:
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self.source.removeListener(self.source_listener)
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def doClose(self):
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self.source.removeListener(self.source_listener)
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def create_roi_devices(roi_list, add = True):
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rois = []
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for r in roi_list:
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roi = RoiIntensity(r, image, roi_list[r][0], roi_list[r][1], roi_list[r][2], roi_list[r][3])
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if add:
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add_device(roi, True)
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rois.append(roi)
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return rois
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###############################################################################
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# Frame integration
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###############################################################################
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"""
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def get_image(source, roi=None, wait_next=False):
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if wait_next:
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source.waitNext(-1)
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elif wait_next:
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if str(source.camera)=="Single":
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eiger.start()
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eiger.waitCacheChange(20000)
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ret = load_image(Utils.grayscale(source.output, Rectangle(roi[0], roi[1], roi[2], roi[3]) if (roi is not None) else None))
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return ret
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def grab_frames(source, samples, roi=None, wait_next=False, sleep=0):
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frames = []
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for i in range(samples):
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if sleep>0:
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time.sleep(sleep)
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aux = get_image(source, roi, wait_next)
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frames.append(aux)
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return frames
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def average_frames(source, samples=1, roi=None, wait_next=False, sleep=0, as_float=True):
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return average_ips(grab_frames(source, samples, roi, wait_next, sleep), as_float)
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def integrate_frames(source, samples=1, roi=None, wait_next=False, sleep=0, as_float=True):
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return integrate_ips(grab_frames(source, samples, roi, wait_next, sleep), as_float)
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"""
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def grab_frame(source, roi=None, wait_next=False, outliers_threshold=None, outliers_mask=None):
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if outliers_threshold is None:
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outliers_threshold = get_outliers_threshold()
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if outliers_mask is None:
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outliers_mask = get_outliers_mask()
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if wait_next:
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if str(eiger.grabMode)=="Single":
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eiger.start()
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#eiger.getDataArray().waitCacheChange(2000)
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source.waitNext(20000 + int(eiger.exposure * 1000))
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#ret = load_image(Utils.grayscale(source.output, Rectangle(roi[0], roi[1], roi[2], roi[3]) if (roi is not None) else None))
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time.sleep(0.01)
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data=source.data
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if roi is not None:
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data = data.getRoi(Rectangle(roi[0], roi[1], roi[2], roi[3]))
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#ret = load_image(img)
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if outliers_mask is not None:
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data.mult(outliers_mask)
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if outliers_threshold>0:
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data.threshold(outliers_threshold, False, None)
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return data
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def grab_frames(source, samples, roi=None, wait_next=False, sleep=0, outliers_threshold=None, outliers_mask=None):
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frames = []
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for i in range(samples):
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if (i>0) and (sleep>0):
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time.sleep(sleep)
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aux = grab_frame(source, roi, wait_next, outliers_threshold, outliers_mask)
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frames.append(aux)
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return frames
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def integrate_frames(frames):
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if frames is None or (len(frames)==0):
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return None
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ret = frames[0].copy()
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for data in frames[1:]:
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ret.sum(data)
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return ret
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def average_frames(frames):
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ret = integrate_frames(frames)
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if ret is not None:
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ret.div(len(frames))
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return ret
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def _timestamp(prec=0):
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t = time.time()
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s = time.strftime("%y/%m/%d %H:%M:%S", time.localtime(t))
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if prec > 0:
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s += ("%.9f" % (t % 1,))[1:2+prec]
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return s
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def _save_as_tiff(data, filename, check=False, show = False, metadata={}):
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if type(data) == Data:
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ip = load_array(data.matrix)
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else:
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ip = data
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#info = "Timestamp: " + _timestamp(3)
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#for key,val in metadata.items():
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# info = info + "\n" + str(key) + ": " + str(val)
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#print "Info:" ,info
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#ip.setProperty("Info", info)
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metadata["Timestamp"] = time.strftime("%y/%m/%d %H:%M:%S",time.localtime())
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if not os.path.exists(os.path.dirname(filename)):
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os.makedirs(os.path.dirname(filename))
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save_image(ip, filename,"tiff", metadata)
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#finfo = open(filename + ".info", "w")
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#for k, v in metadata.items():
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# finfo.write(str(k) + ': '+ str(v) + '\n')
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#info.close()
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if check:
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data = get_ip_array(ip)
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import java.util.Arrays as Arrays
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ip=open_image(filename)
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read = get_ip_array(ip)
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#print (" ------> Error reading array: " + str(filename))
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#TODO: Original checkcode was deleted!
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def save_as_tiff(data, filename, check=False, show = False, parallel=True, metadata={}):
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if parallel:
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return fork((_save_as_tiff,(data, filename, check, show, metadata)),)
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else:
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_save_as_tiff(data, filename, check, show, metadata)
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def trigger_eiger(wait=False):
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eiger.start()
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if wait:
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eiger.waitNewImage(20000)
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def set_exposure_time(exposure):
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if exposure == eiger.getExposure():
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return
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started = eiger.isStarted()
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if started:
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eiger.stop()
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time.sleep(0.2)
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eiger.setExposure(exposure)
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if started:
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if eiger.grabMode==eiger.GrabMode.Continuous:
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eiger.start()
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def restore_eiger():
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"""
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Set Eiger default mode
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"""
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if eiger.isStarted():
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eiger.stop()
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time.sleep(0.2)
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eiger.grabMode=eiger.GrabMode.Continuous
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eiger.setExposure(0.2)
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eiger.setNumImages(1)
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eiger.start()
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_outliers_mask_timestamp = 0
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_outliers_mask = None
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def get_outliers_mask(data_type='f'):
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global _outliers_mask_timestamp, _outliers_mask
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if get_exec_pars().start == _outliers_mask_timestamp:
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return _outliers_mask
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_outliers_mask_timestamp = get_exec_pars().start
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try:
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_outliers_mask = None
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filename = get_outliers_mask_file()
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if filename:
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ip=open_image(filename)
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#TRANSPOSE - ImageJ stores the data transposed
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ip.getProcessor().rotate(-90)
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ip.getProcessor().flipVertical()
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array = get_ip_array(ip)
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array = Convert.toPrimitiveArray(array, ScriptUtils.getType(data_type))
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_outliers_mask = Data(array)
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print "Generated outliers mask"
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except:
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pass
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return _outliers_mask
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if False:
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integrate_roi(image, 10, 5, 20, 10)
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add_device(RoiIntensity("Region1", image, 10, 5, 20, 10), True)
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add_device(RoiIntensity("Region2", image, 10, 5, 40, 20), True)
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import ch.psi.pshell.data.ProviderCSV as ProviderCSV
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ProviderCSV.setDefaultItemSeparator(" ")
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tscan((Region1, Region2), 10, 0.1, layout="table", provider = "csv")
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ret = grab_frames(image, 10, sleep=0.1)
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av = integrate_frames(ret)
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save_as_tiff(av,"{images}/data.tif", True)
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print "Success"
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