def calibrate_brightness_from_image_fn(fns):
"""
Calibrate pixel->brightness (size of beam) from a set of images
fns: `str`
Set of images to determine size of beam from
return:
instance of Calibration class with conversion methods
"""
values = []
for fn in fns:
print()
print("Image:", fn)
img, h = load_img(fn)
brightness = float(h["Brightness"])
binsize = float(h["ImageBinSize"])
img, scale = autoscale(img)
holes = find_holes(img, plot=False, fname=None, verbose=False, max_eccentricity=0.8)
size = max([hole.equivalent_diameter for hole in holes]) * binsize / scale
print(f"Brightness: {brightness:.0f}, equivalent diameter: {size:.1f}px")
values.append((brightness, size))
values = np.array(values)
c = CalibBrightness.from_data(*values.T)
c.plot()
return c
def calibrate_brightness_live(ctrl, step=1000, save_images=False, **kwargs):
"""
Calibrate pixel->brightness coordinates live on the microscope
ctrl: instance of `TEMController`
contains tem + cam interface
start: `float`
start value for calibration (0.0 - 1.0)
end: `float`
end value for calibration (0.0 - 1.0)
exposure: `float`
exposure time
binsize: `int`
return:
instance of CalibBrightness class with conversion methods
"""
raise NotImplementedError("calibrate_brightness_live function needs fixing...")
exposure = kwargs.get("exposure", ctrl.cam.default_exposure)
binsize = kwargs.get("binsize", ctrl.cam.default_binsize)
values = []
start = ctrl.brightness.value
for i in range(10):
target = start + i*step
ctrl.brightness.value = int(target)
outfile = f"calib_brightness_{i:04d}" if save_images else None
comment = f"Calib image {i}: brightness={target}"
img, h = ctrl.getImage(exposure=exposure, out=outfile, comment=comment, header_keys="Brightness")
img, scale = autoscale(img)
brightness = float(h["Brightness"])
holes = find_holes(img, plot=False, verbose=False, max_eccentricity=0.8)
if len(holes) == 0:
print(" >> No holes found, continuing...")
continue
size = max([hole.equivalent_diameter for hole in holes]) * binsize / scale
print("Brightness: {:.f}, equivalent diameter: {:.1f}".format(brightness, size))
values.append((brightness, size))
values = np.array(values)
c = CalibBrightness.from_data(*values.T)
# Calling c.plot with videostream crashes program
if not hasattr(ctrl.cam, "VideoLoop"):
c.plot()
return c
def calibrate_beamshift_from_image_fn(center_fn, other_fn):
"""
Calibrate pixel->beamshift coordinates from a set of images
center_fn: `str`
Reference image with the beam at the center of the image
other_fn: `tuple` of `str`
Set of images to cross correlate to the first reference image
return:
instance of Calibration class with conversion methods
"""
print()
print("Center:", center_fn)
img_cent, h_cent = load_img(center_fn)
beamshift_cent = np.array(h_cent["BeamShift"])
img_cent, scale = autoscale(img_cent, maxdim=512)
binsize = h_cent["ImageBinSize"]
holes = find_holes(img_cent,
plot=False,
verbose=False,
max_eccentricity=0.8)
pixel_cent = np.array(holes[0].centroid) * binsize / scale
print("Beamshift: x={} | y={}".format(*beamshift_cent))
print("Pixel: x={:.2f} | y={:.2f}".format(*pixel_cent))
shifts = []
beampos = []
for fn in other_fn:
img, h = load_img(fn)
img = imgscale(img, scale)
beamshift = np.array((h["BeamShift"]))
print()
print("Image:", fn)
print("Beamshift: x={} | y={}".format(*beamshift))
shift = cross_correlate(img_cent,
img,
upsample_factor=10,
verbose=False)
beampos.append(beamshift)
shifts.append(shift)
# correct for binsize, store as binsize=1
shifts = np.array(shifts) * binsize / scale
beampos = np.array(beampos) - beamshift_cent
c = CalibBeamShift.from_data(shifts,
beampos,
reference_shift=beamshift_cent,
reference_pixel=pixel_cent,
header=h_cent)
c.plot()
return c