def show(scan_id, step=0, frame=None, logscale=True, cmap='jet'):
"""Plot light, dark and subtracted image arrays for the given scan.
scan_id -- integer index or any other scan specification accepted
by data broker.
step -- index of the scan step that should be plotted.
frame -- optional selection of frames for steps that contain multiple
exposures. This is used as an index for a 3D image array,
which is then summed along its first axis.
logscale -- flag for plotting logarithm of intensities.
cmap -- colormap to be used in the array plots.
No return value.
"""
from uiophyd.brokerutils import blank_events, fill_event
from uiophyd.pylab_utilities import reportzcoord
header = db[scan_id]
events = blank_events(header)
ev = events[step]
fill_event(ev)
light = ev.data['pe1_image_lightfield']
dark = (ev.data['pe1_image_darkfield']
if 'pe1_image_darkfield' in ev.data else np.zeros_like(light))
signal = light - dark
selectedframes = [0]
if 3 == signal.ndim:
if frame is None: frame = slice(None)
frameindices = np.arange(len(light))
selectedframes = frameindices[frame].reshape(-1)
shp = (-1, ) + signal.shape[1:]
light = light[frame].reshape(shp).sum(axis=0)
dark = dark[frame].reshape(shp).sum(axis=0)
signal = signal[frame].reshape(shp).sum(axis=0)
if logscale:
# low-threshold all arrays at 1.
light = np.log10(np.where(light > 1, light, 1))
dark = np.log10(np.where(dark > 1, dark, 1))
signal = np.log10(np.where(signal > 1, signal, 1))
# create the figure and axes
fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(15, 5))
sctp = 'logarithmic' if logscale else 'linear'
fig.text(0.5,
.95,
'scan {}, step {}, summed frames {} in {} color scale.'.format(
scan_id, step, selectedframes, sctp),
horizontalalignment='center')
ax1.imshow(light, cmap=cmap)
ax1.set_title('Light')
ax2.imshow(dark, cmap=cmap)
ax2.set_title('Dark')
ax3.imshow(signal, cmap=cmap)
ax3.set_title('(Light - Dark)')
reportzcoord([ax1, ax2, ax3])
fig.canvas.show()
return
def show(scan_id, step=0, frame=None, logscale=True, cmap='jet'):
"""Plot light, dark and subtracted image arrays for the given scan.
scan_id -- integer index or any other scan specification accepted
by data broker.
step -- index of the scan step that should be plotted.
frame -- optional selection of frames for steps that contain multiple
exposures. This is used as an index for a 3D image array,
which is then summed along its first axis.
logscale -- flag for plotting logarithm of intensities.
cmap -- colormap to be used in the array plots.
No return value.
"""
from uiophyd.brokerutils import blank_events, fill_event
from uiophyd.pylab_utilities import reportzcoord
header = db[scan_id]
events = blank_events(header)
ev = events[step]
fill_event(ev)
light = ev.data['pe1_image_lightfield']
dark = (ev.data['pe1_image_darkfield']
if 'pe1_image_darkfield' in ev.data else np.zeros_like(light))
signal = light - dark
selectedframes = [0]
if 3 == signal.ndim:
if frame is None: frame = slice(None)
frameindices = np.arange(len(light))
selectedframes = frameindices[frame].reshape(-1)
shp = (-1,) + signal.shape[1:]
light = light[frame].reshape(shp).sum(axis=0)
dark = dark[frame].reshape(shp).sum(axis=0)
signal = signal[frame].reshape(shp).sum(axis=0)
if logscale:
# low-threshold all arrays at 1.
light = np.log10(np.where(light > 1, light, 1))
dark = np.log10(np.where(dark > 1, dark, 1))
signal = np.log10(np.where(signal > 1, signal, 1))
# create the figure and axes
fig, (ax1, ax2, ax3) = plt.subplots(ncols=3, figsize=(15, 5))
sctp = 'logarithmic' if logscale else 'linear'
fig.text(0.5, .95,
'scan {}, step {}, summed frames {} in {} color scale.'.format(
scan_id, step, selectedframes, sctp),
horizontalalignment='center')
ax1.imshow(light, cmap=cmap)
ax1.set_title('Light')
ax2.imshow(dark, cmap=cmap)
ax2.set_title('Dark')
ax3.imshow(signal, cmap=cmap)
ax3.set_title('(Light - Dark)')
reportzcoord([ax1, ax2, ax3])
fig.canvas.show()
return
def writeEvent(self, filename, event, overwrite):
from uiophyd.brokerutils import fill_event
savedfile = self.findSavedEvent(event)
if savedfile:
msgrm = "remove existing file {}".format(savedfile)
msgskip = "skip {}, already saved as {}".format(filename, savedfile)
if overwrite:
self._dryordo(msgrm, os.remove, savedfile)
else:
self._dryordo(msgskip, lambda: None)
return
dd = event.data
nlight = [k for k in dd if k.endswith("image_lightfield")][0]
Alight = dd[nlight]
if isinstance(Alight, str):
fill_event(event)
Alight = event.data[nlight]
ndark = nlight.replace("lightfield", "darkfield")
Adark = event.data.get(ndark, 0)
A = Alight - Adark
if 3 == A.ndim:
A = A.sum(axis=-1)
if 0 == A.size:
return
if self.dtype is not None:
A = A.astype(self.dtype)
def _writetiff():
tifffile.imsave(filename, A)
stinfo = os.stat(filename)
os.utime(filename, (stinfo.st_atime, event.time))
msg = "write {} using {}, adjust mtime".format(filename, A.dtype)
self._dryordo(msg, _writetiff)
return
def writeEvent(self, filename, event, overwrite):
from uiophyd.brokerutils import fill_event
savedfile = self.findSavedEvent(event)
if savedfile:
msgrm = 'remove existing file {}'.format(savedfile)
msgskip = 'skip {}, already saved as {}'.format(
filename, savedfile)
if overwrite:
self._dryordo(msgrm, os.remove, savedfile)
else:
self._dryordo(msgskip, lambda: None)
return
dd = event.data
nlight = [k for k in dd if k.endswith('image_lightfield')][0]
Alight = dd[nlight]
if isinstance(Alight, str):
fill_event(event)
Alight = event.data[nlight]
ndark = nlight.replace('lightfield', 'darkfield')
Adark = event.data.get(ndark, 0)
A = Alight - Adark
if 3 == A.ndim:
A = A.sum(axis=-1)
if 0 == A.size:
return
if self.dtype is not None:
A = A.astype(self.dtype)
def _writetiff():
tifffile.imsave(filename, A)
stinfo = os.stat(filename)
os.utime(filename, (stinfo.st_atime, event.time))
msg = 'write {} using {}, adjust mtime'.format(filename, A.dtype)
self._dryordo(msg, _writetiff)
return
