def test_focus_metric_default(data_dir):
data = fits.getdata(os.path.join(data_dir, 'unsolved.fits'))
data = focus_utils.mask_saturated(data)
assert focus_utils.focus_metric(data) == pytest.approx(14667.207897717599)
assert focus_utils.focus_metric(
data, axis='Y') == pytest.approx(14380.343807477504)
assert focus_utils.focus_metric(
data, axis='X') == pytest.approx(14954.071987957694)
with pytest.raises(ValueError):
focus_utils.focus_metric(data, axis='Z')
def test_focus_metric_bad_string(data_dir):
data = fits.getdata(os.path.join(data_dir, 'unsolved.fits'))
data = focus_utils.mask_saturated(data)
with pytest.raises(KeyError):
focus_utils.focus_metric(data, merit_function='NOTAMERITFUNCTION')
def _autofocus(self, seconds, focus_range, focus_step, cutout_size,
keep_files, take_dark, merit_function,
merit_function_kwargs, mask_dilations, make_plots, coarse,
focus_event, *args, **kwargs):
"""Private helper method for calling autofocus in a Thread.
See public `autofocus` for information about the parameters.
"""
focus_type = 'fine'
if coarse:
focus_type = 'coarse'
initial_focus = self.position
self.logger.debug(
f"Beginning {focus_type} autofocus of {self._camera} - "
f"initial position: {initial_focus}")
# Set up paths for temporary focus files, and plots if requested.
image_dir = self.get_config('directories.images')
start_time = current_time(flatten=True)
file_path_root = os.path.join(image_dir, 'focus', self._camera.uid,
start_time)
self._autofocus_error = None
dark_cutout = None
if take_dark:
dark_path = os.path.join(file_path_root,
f'dark.{self._camera.file_extension}')
self.logger.debug(
f'Taking dark frame {dark_path} on camera {self._camera}')
try:
dark_cutout = self._camera.get_cutout(seconds,
dark_path,
cutout_size,
keep_file=True,
dark=True)
# Mask 'saturated' with a low threshold to remove hot pixels
dark_cutout = mask_saturated(dark_cutout,
threshold=0.3,
bit_depth=self.camera.bit_depth)
except Exception as err:
self.logger.error(f"Error taking dark frame: {err!r}")
self._autofocus_error = repr(err)
focus_event.set()
raise err
# Take an image before focusing, grab a cutout from the centre and add it to the plot
initial_fn = f"{initial_focus}-{focus_type}-initial.{self._camera.file_extension}"
initial_path = os.path.join(file_path_root, initial_fn)
try:
initial_cutout = self._camera.get_cutout(seconds,
initial_path,
cutout_size,
keep_file=True)
initial_cutout = mask_saturated(initial_cutout,
bit_depth=self.camera.bit_depth)
if dark_cutout is not None:
initial_cutout = initial_cutout.astype(np.int32) - dark_cutout
except Exception as err:
self.logger.error(f"Error taking initial image: {err!r}")
self._autofocus_error = repr(err)
focus_event.set()
raise err
# Set up encoder positions for autofocus sweep, truncating at focus travel
# limits if required.
if coarse:
focus_range = focus_range[1]
focus_step = focus_step[1]
else:
focus_range = focus_range[0]
focus_step = focus_step[0]
# Get focus steps.
focus_positions = np.arange(
max(initial_focus - focus_range / 2, self.min_position),
min(initial_focus + focus_range / 2, self.max_position) + 1,
focus_step,
dtype=np.int)
n_positions = len(focus_positions)
# Set up empty array holders
cutouts = np.zeros((n_positions, cutout_size, cutout_size),
dtype=initial_cutout.dtype)
masks = np.empty((n_positions, cutout_size, cutout_size),
dtype=np.bool)
metrics = np.empty(n_positions)
# Take and store an exposure for each focus position.
for i, position in enumerate(focus_positions):
# Move focus, updating focus_positions with actual encoder position after move.
focus_positions[i] = self.move_to(position)
focus_fn = f"{focus_positions[i]}-{i:02d}.{self._camera.file_extension}"
file_path = os.path.join(file_path_root, focus_fn)
# Take exposure.
try:
cutouts[i] = self._camera.get_cutout(seconds,
file_path,
cutout_size,
keep_file=keep_files)
except Exception as err:
self.logger.error(f"Error taking image {i + 1}: {err!r}")
self._autofocus_error = repr(err)
focus_event.set()
raise err
masks[i] = mask_saturated(cutouts[i],
bit_depth=self.camera.bit_depth).mask
self.logger.debug(
f'Making master mask with binary dilation for {self._camera}')
master_mask = masks.any(axis=0)
master_mask = binary_dilation(master_mask, iterations=mask_dilations)
# Apply the master mask and then get metrics for each frame.
for i, cutout in enumerate(cutouts):
self.logger.debug(f'Applying focus metric to cutout {i:02d}')
if dark_cutout is not None:
cutout = cutout.astype(np.float32) - dark_cutout
cutout = np.ma.array(cutout,
mask=np.ma.mask_or(master_mask,
np.ma.getmask(cutout)))
metrics[i] = focus_utils.focus_metric(cutout, merit_function,
**merit_function_kwargs)
self.logger.debug(f'Focus metric for cutout {i:02d}: {metrics[i]}')
# Only fit a fine focus.
fitted = False
fitting_indices = [None, None]
# Find maximum metric values.
imax = metrics.argmax()
if imax == 0 or imax == (n_positions - 1):
# TODO: have this automatically switch to coarse focus mode if this happens
self.logger.warning(
f"Best focus outside sweep range, stopping focus and using"
f" {focus_positions[imax]}")
best_focus = focus_positions[imax]
elif not coarse:
# Fit data around the maximum value to determine best focus position.
# Initialise models
shift = models.Shift(offset=-focus_positions[imax])
# Small initial coeffs with expected sign. Helps fitting start in the right direction.
poly = models.Polynomial1D(degree=4,
c0=1,
c1=0,
c2=-1e-2,
c3=0,
c4=-1e-4,
fixed={
'c0': True,
'c1': True,
'c3': True
})
scale = models.Scale(factor=metrics[imax])
# https://docs.astropy.org/en/stable/modeling/compound-models.html?#model-composition
reparameterised_polynomial = shift | poly | scale
# Initialise fitter
fitter = fitting.LevMarLSQFitter()
# Select data range for fitting. Tries to use 2 points either side of max, if in range.
fitting_indices = (max(imax - 2, 0), min(imax + 2,
n_positions - 1))
# Fit models to data
fit = fitter(
reparameterised_polynomial,
focus_positions[fitting_indices[0]:fitting_indices[1] + 1],
metrics[fitting_indices[0]:fitting_indices[1] + 1])
# Get the encoder position of the best focus.
best_focus = np.abs(fit.offset_0)
fitted = True
# Guard against fitting failures, force best focus to stay within sweep range.
min_focus = focus_positions[0]
max_focus = focus_positions[-1]
if best_focus < min_focus:
self.logger.warning(
f"Fitting failure: best focus {best_focus} below sweep limit"
f" {min_focus}")
best_focus = focus_positions[1]
if best_focus > max_focus:
self.logger.warning(
f"Fitting failure: best focus {best_focus} above sweep limit"
f" {max_focus}")
best_focus = focus_positions[-2]
else:
# Coarse focus, just use max value.
best_focus = focus_positions[imax]
# Move the focuser to best focus position.
final_focus = self.move_to(best_focus)
# Get final cutout.
final_fn = f"{final_focus}-{focus_type}-final.{self._camera.file_extension}"
file_path = os.path.join(file_path_root, final_fn)
try:
final_cutout = self._camera.get_cutout(seconds,
file_path,
cutout_size,
keep_file=True)
final_cutout = mask_saturated(final_cutout,
bit_depth=self.camera.bit_depth)
if dark_cutout is not None:
final_cutout = final_cutout.astype(np.int32) - dark_cutout
except Exception as err:
self.logger.error(f"Error taking final image: {err!r}")
self._autofocus_error = repr(err)
focus_event.set()
raise err
if make_plots:
line_fit = None
if fitted:
focus_range = np.arange(
focus_positions[fitting_indices[0]],
focus_positions[fitting_indices[1]] + 1)
fit_line = fit(focus_range)
line_fit = [focus_range, fit_line]
plot_title = f'{self._camera} {focus_type} focus at {start_time}'
# Make the plots
plot_path = os.path.join(file_path_root, f'{focus_type}-focus.png')
plot_path = make_autofocus_plot(plot_path,
initial_cutout,
final_cutout,
initial_focus,
final_focus,
focus_positions,
metrics,
merit_function,
plot_title=plot_title,
line_fit=line_fit)
self.logger.info(
f"{focus_type.capitalize()} focus plot for {self._camera} written to "
f" {plot_path}")
self.logger.debug(f"Autofocus of {self._camera} complete - final focus"
f" position: {final_focus}")
if focus_event:
focus_event.set()
return initial_focus, final_focus