def _readout(self, filename, width, height, header):
exposure_status = Camera._driver.get_exposure_status(self._handle)
if exposure_status == 'SUCCESS':
try:
image_data = Camera._driver.get_exposure_data(
self._handle, width, height, self.image_type)
except RuntimeError as err:
raise error.PanError(
'Error getting image data from {}: {}'.format(self, err))
else:
# Fix 'raw' data scaling by changing from zero padding of LSBs
# to zero padding of MSBs.
if self.image_type == 'RAW16':
pad_bits = 16 - int(
get_quantity_value(self.bit_depth, u.bit))
image_data = np.right_shift(image_data, pad_bits)
fits_utils.write_fits(data=image_data,
header=header,
filename=filename)
elif exposure_status == 'FAILED':
raise error.PanError("Exposure failed on {}".format(self))
elif exposure_status == 'IDLE':
raise error.PanError("Exposure missing on {}".format(self))
else:
raise error.PanError(
"Unexpected exposure status on {}: '{}'".format(
self, exposure_status))
def _readout(self, filename=None, header=None):
self.logger.debug(f'Calling _readout for {self}')
timer = CountdownTimer(duration=self.readout_time)
# Get example FITS file from test data directory
file_path = os.path.join(os.environ['POCS'], 'tests', 'data', 'unsolved.fits')
fake_data = fits.getdata(file_path)
if header.get('IMAGETYP') == 'Dark Frame':
# Replace example data with a bunch of random numbers
fake_data = np.random.randint(low=975, high=1026,
size=fake_data.shape,
dtype=fake_data.dtype)
self.logger.debug(f'Writing filename={filename!r} for {self}')
fits_utils.write_fits(fake_data, header, filename)
# Sleep for the remainder of the readout time.
timer.sleep()
def _readout(self, filename, width, height, header):
# Use FLIGrabRow for now at least because I can't get FLIGrabFrame to work.
# image_data = self._FLIDriver.FLIGrabFrame(self._handle, width, height)
image_data = np.zeros((height, width), dtype=np.uint16)
rows_got = 0
try:
for i in range(image_data.shape[0]):
image_data[i] = self._driver.FLIGrabRow(
self._handle, image_data.shape[1])
rows_got += 1
except RuntimeError as err:
message = 'Readout error on {}, expected {} rows, got {}: {}'.format(
self, image_data.shape[0], rows_got, err)
raise error.PanError(message)
else:
fits_utils.write_fits(data=image_data,
header=header,
filename=filename)
def _video_readout(self, width, height, image_type, timeout, filename_root,
file_extension, max_frames, header):
start_time = time.monotonic()
good_frames = 0
bad_frames = 0
# Calculate number of bits that have been used to pad the raw data to RAW16 format.
if self.image_type == 'RAW16':
pad_bits = 16 - int(get_quantity_value(self.bit_depth, u.bit))
else:
pad_bits = 0
for frame_number in range(max_frames):
if self._video_event.is_set():
break
# This call will block for up to timeout milliseconds waiting for a frame
video_data = Camera._driver.get_video_data(self._handle, width,
height, image_type,
timeout)
if video_data is not None:
now = Time.now()
header.set('DATE-OBS', now.fits, 'End of exposure + readout')
filename = "{}_{:06d}.{}".format(filename_root, frame_number,
file_extension)
# Fix 'raw' data scaling by changing from zero padding of LSBs
# to zero padding of MSBs.
video_data = np.right_shift(video_data, pad_bits)
fits_utils.write_fits(video_data, header, filename)
good_frames += 1
else:
bad_frames += 1
if frame_number == max_frames - 1:
# No one callled stop_video() before max_frames so have to call it here
self.stop_video()
elapsed_time = (time.monotonic() - start_time) * u.second
self.logger.debug(
"Captured {} of {} frames in {:.2f} ({:.2f} fps), {} frames lost".
format(good_frames, max_frames, elapsed_time,
get_quantity_value(good_frames / elapsed_time), bad_frames))
def _readout(self, filename, readout_mode, top, left, height, width,
header):
exposure_status = Camera._driver.get_exposure_status(self._handle)
if exposure_status == 'CS_INTEGRATION_COMPLETE':
try:
image_data = Camera._driver.readout(self._handle, readout_mode,
top, left, height, width)
except RuntimeError as err:
raise error.PanError('Readout error on {}, {}'.format(
self, err))
else:
fits_utils.write_fits(data=image_data,
header=header,
filename=filename)
elif exposure_status == 'CS_IDLE':
raise error.PanError("Exposure missing on {}".format(self))
else:
raise error.PanError(
"Unexpected exposure status on {}: '{}'".format(
self, exposure_status))