def event_page(self, doc):
'''Add event page document information to a ".tiff" file.
This method adds event_page document information to a ".tiff" file,
creating it if nesecary.
.. warning::
All non 2D 'image like' data is explicitly ignored.
.. note::
The data in Events might be structured as an Event, an EventPage,
or a "bulk event" (deprecated). The DocumentRouter base class takes
care of first transforming the other representations into an
EventPage and then routing them through here, so no further action
is required in this class. We can assume we will always receive an
EventPage.
Parameters:
-----------
doc : dict
EventPage document
'''
event_model.verify_filled(doc)
descriptor = self._descriptors[doc['descriptor']]
stream_name = descriptor.get('name')
for field in doc['data']:
for img in doc['data'][field]:
# Check that the data is 2D or 3D; if not ignore it.
data_key = descriptor['data_keys'][field]
ndim = len(data_key['shape'] or [])
if data_key['dtype'] == 'array' and 1 < ndim < 4:
# there is data to be written so
# create a file for this stream and field
# if one does not exist yet
if not self._tiff_writers.get(stream_name, {}).get(field):
filename = get_prefixed_filename(
file_prefix=self._file_prefix,
start_doc=self._start,
stream_name=stream_name,
field=field)
file = self._manager.open('stream_data', filename,
'xb')
tw = TiffWriter(file, **self._init_kwargs)
self._tiff_writers[stream_name][field] = tw
# write the data
img_asarray = numpy.asarray(img, dtype=self._astype)
if ndim == 2:
# handle 2D data just like 3D data
# by adding a 3rd dimension
img_asarray = numpy.expand_dims(img_asarray, axis=0)
for i in range(img_asarray.shape[0]):
img_asarray_2d = img_asarray[i, :]
# append the image to the file
tw = self._tiff_writers[stream_name][field]
tw.save(img_asarray_2d, *self._kwargs)
def plot_image(data, **kwargs):
p = functools.partial(plt.imshow, cmap='gray', clim=(0, 500)) # noqa
p(data, **kwargs)
from tifffile import TiffWriter
##File saving needs to be done properly via suite-case
with open('/nsls2/xf07bm/data/pe1_data/2019/05/23/Diffraction_Image.tiff', 'xb') as f:
tw = TiffWriter(f)
tw.save(data)
def event(self, doc):
'''Add event document information to a ".tiff" file.
This method adds event document information to a ".tiff" file,
creating it if necessary.
.. warning::
All non 2D 'image-like' data is explicitly ignored.
.. note::
The data in Events might be structured as an Event, an EventPage,
or a "bulk event" (deprecated). The DocumentRouter base class takes
care of first transforming the other representations into an
EventPage and then routing them through here, as we require Event
documents _in this case_ we overwrite both the `event` method and
the `event_page` method so we can assume we will always receive an
Event.
Parameters:
-----------
doc : dict
Event document
'''
event_model.verify_filled(event_model.pack_event_page(*[doc]))
descriptor = self._descriptors[doc['descriptor']]
stream_name = descriptor.get('name')
for field in doc['data']:
img = doc['data'][field]
# Check that the data is 2D or 3D; if not ignore it.
data_key = descriptor['data_keys'][field]
ndim = len(data_key['shape'] or [])
if data_key['dtype'] == 'array' and 1 < ndim < 4:
img_asarray = numpy.asarray(img, dtype=self._astype)
if ndim == 2:
# handle 2D data just like 3D data
# by adding a 3rd dimension
img_asarray = numpy.expand_dims(img_asarray, axis=0)
for i in range(img_asarray.shape[0]):
img_asarray_2d = img_asarray[i, :]
num = next(self._counter[stream_name][field])
filename = get_prefixed_filename(
file_prefix=self._file_prefix,
start_doc=self._start,
descriptor_doc=descriptor,
event_doc=doc,
num=num,
stream_name=stream_name,
field=field)
file = self._manager.open('stream_data', filename, 'xb')
tw = TiffWriter(file, **self._init_kwargs)
self._tiff_writers[stream_name][field + f'-{num}'] = tw
tw.save(img_asarray_2d, *self._kwargs)
def event_page(self, doc):
'''Add event page document information to a ".tiff" file.
This method adds event_page document information to a ".tiff" file,
creating it if nesecary.
.. warning::
All non 2D 'image like' data is explicitly ignored.
.. note::
The data in Events might be structured as an Event, an EventPage,
or a "bulk event" (deprecated). The DocumentRouter base class takes
care of first transforming the other repsentations into an
EventPage and then routing them through here, so no further action
is required in this class. We can assume we will always receive an
EventPage.
Parameters:
-----------
doc : dict
EventPage document
'''
event_model.verify_filled(doc)
streamname = self._descriptors[doc['descriptor']].get('name')
self._templated_file_prefix = self._file_prefix.format(
start=self._start)
for field in doc['data']:
for img in doc['data'][field]:
# check that the data is 2D, if not ignore it
img_asarray = numpy.asarray(img,
dtype=numpy.dtype(self._astype))
if img_asarray.ndim == 2:
# create a file for this stream and field if required
if not self._tiff_writers.get(streamname, {}).get(field):
filename = (f'{self._templated_file_prefix}'
f'{streamname}-{field}.tiff')
file = self._manager.open('stream_data', filename,
'xb')
tw = TiffWriter(file, **self._init_kwargs)
self._tiff_writers[streamname][field] = tw
# append the image to the file
tw = self._tiff_writers[streamname][field]
tw.save(img_asarray, *self._kwargs)
def event(self, doc):
'''Add event document information to a ".tiff" file.
This method adds event document information to a ".tiff" file,
creating it if necessary.
.. warning::
All non 2D 'image-like' data is explicitly ignored.
.. note::
The data in Events might be structured as an Event, an EventPage,
or a "bulk event" (deprecated). The DocumentRouter base class takes
care of first transforming the other repsentations into an
EventPage and then routing them through here, as we require Event
documents _in this case_ we overwrite both the `event` method and
the `event_page` method so we can assume we will always receive an
Event.
Parameters:
-----------
doc : dict
Event document
'''
event_model.verify_filled(event_model.pack_event_page(*[doc]))
descriptor = self._descriptors[doc['descriptor']]
streamname = descriptor.get('name')
for field in doc['data']:
img = doc['data'][field]
# check that the data is 2D, if not ignore it
img_asarray = numpy.asarray(img, dtype=self._astype)
if img_asarray.ndim == 2:
# template the file name.
self._templated_file_prefix = self._file_prefix.format(
start=self._start, descriptor=descriptor, event=doc)
num = next(self._counter[streamname][field])
filename = (f'{self._templated_file_prefix}'
f'{streamname}-{field}-{num}.tiff')
file = self._manager.open('stream_data', filename, 'xb')
tw = TiffWriter(file, **self._init_kwargs)
self._tiff_writers[streamname][field + f'-{num}'] = tw
tw.save(img_asarray, *self._kwargs)
class WriterHandler(BaseHandler):
def sync_name(self, member, filedir, filename):
path = ip1_datapath.joinpath(member, filedir)
if not path.is_dir():
os.makedirs(path.str)
self.tifpath = path.joinpath(filename).with_suffix('.tif')
self.csvpath = path.joinpath(filename).with_suffix('.csv')
return True # self.ready()
def check(self, filename):
pass
def ready(self):
if self.tifpath.is_file() or self.csvpath.is_file():
raise Exception(
'Filename already exists. Please provide new one...')
else:
return True
def register(self):
super(WriterHandler, self).register()
self.ready_at = time.time()
def enter(self):
print 'enter'
self.tif = TiffWriter(self.tifpath.str, bigtiff=True)
self.csv = self.csvpath.open('w')
def exposure_end(self, frame, _ts):
if self.svc.bypass:
return
ts = time.time() - self.ready_at
self.tif.save(frame)
# self.tif.save(frame, extratags=[(
# 306, 's', 0, str(ts), False
# )])
self.csv.write(u'{}\n'.format(ts))
def exit(self):
print 'exit'
self.tif.close()
self.csv.close()
def process(self, theSourceDir, theDestinationDir, **kwargs):
for key, value in kwargs.items():
setattr(self, key, value)
if theSourceDir == theDestinationDir:
self.log("Input and output directories cannot be the same.")
return False
fileList = glob.glob(theSourceDir+'/*.'+self.fileExtension)
if len(fileList) == 0:
self.log(" Zero files to process in source directory.")
return False
fileList = glob.glob(theSourceDir+'/*.'+self.fileExtension)
self.log('Processing %i images' % len(fileList))
progress = 0
for file in fileList:
#Load image
data = cv2.cvtColor(cv2.imread(file), cv2.COLOR_BGR2RGB)
data = data.astype('float')
self.currentMax = 0
#Load original EXIF data
inExif = pyexiv2.metadata.ImageMetadata(file)
inExif.read()
#Radiometric Calibration
if self.radiometricCalibrator != None and self.radiometricCalibration:
data = self.radiometricCalibrator.calibrate(data)
self.currentMax = 1
#compute index
if self.index == 'NDVI':
data = self.indexNdvi(data)
#Scale
if self.currentMax != 0:
percentOfRange = (data - self.currentMin) / (self.currentMax - self.currentMin)
data = (self.scaleFrom * (1 - percentOfRange)) + (self.scaleTo * percentOfRange)
#Set dtype
if self.scaleTo == 1:
if data.dtype.name != 'float32':
data = data.astype('float32')
elif self.scaleTo > 255:
#unsigned int (I:16)
data = data.astype('uint16')
elif self.index != 'None':
if self.lut == 'None':
#bit image (L)
data = data.astype('uint8')
pass
else:
#Paletted
pass
else:
#RGB (RGB)
data = data.astype('uint8')
#Save processed data to new file
path, baseName = os.path.split(file)
baseName = re.sub(r''+re.escape(self.fileExtension)+'$', 'tiff', baseName)
if self.index != 'None':
baseName = self.index+'-'+baseName
tif = TiffWriter(theDestinationDir+'/'+baseName)
tif.save(data, compress=6)
tif = None
#Transfer EXIF data to new file
outExif = pyexiv2.metadata.ImageMetadata(theDestinationDir+'/'+baseName)
outExif.read()
#inExif.copy(outExif, comment=False)
#outExif.write()
#Log and progress
progress += 1
self.log('%s created' % (baseName), progress=progress)
laser = TopticaiBeam(port="COM1")
# initialise buffer as a queue
image_buffer = Queue()
# configure camera, pass the buffer queue and enable.
camera.set_client(image_buffer)
camera.exposure_time = exposure_seconds
camera.set_trigger(TriggerType.SOFTWARE, TriggerMode.ONCE)
camera.enable()
# configure laser
laser.power = power_level
laser.set_trigger(TriggerType.HIGH, TriggerMode.BULB)
laser.enable()
# main loop to collect images.
for i in range(n_repeats):
camera.trigger()
time.sleep(interval_seconds)
# shutdown hardware devices
laser.shutdown()
camera.shutdown()
# write out image data to a file.
writer = TiffWriter("data.tif")
for i in range(n_repeats):
writer.save(image_buffer.get())
writer.close()
