def __init__(self, raw_image, mask=None, filename='my_mask', fmt='pypad'):
"""
Instantiate an interactive masking session.
Parameters
----------
raw_image : np.ndarray
A shape (4, 8, 185, 388) array containing a reference image that
the user will use to guide their masking.
mask : padmask.PadMask
A PadMask object to modify. If `None` (default), generate a new
mask.
filename : str
The name of the file to generate at the end of the session.
fmt : str
The file format of `filename` to write.
"""
self.print_gui_help()
self.filename = filename
self.file_fmt = fmt
if not raw_image.shape == (4, 16, 185, 194):
raise ValueError("`raw_image` must have shape: (4, 16, 185, 194)")
if mask == None:
self.mask = PadMask()
elif isinstance(mask, PadMask):
self.mask = mask
else:
raise TypeError(
'`mask` argument must be a pypad.mask.PadMask object')
# inject a new mask type into our PadMask obj
m = self.mask._blank_mask()
if not 'manual' in self.mask._masks.keys():
self.mask._inject_mask('manual', m)
# deal with negative values
if not 'negatives' in self.mask._masks.keys():
self.mask._inject_mask('negatives', m.copy())
self.mask._masks['negatives'][raw_image <= 0.0] = 0
print "Masked: %d negative pixels" % np.sum(
np.logical_not(self.mask._masks['negatives']))
# we're going to plot the log of the image, so do that up front
self.raw_image_4d = raw_image
self.raw_image = utils.flatten_2x1s(raw_image)
self.log_image = self.raw_image.copy()
self.log_image[self.log_image < 0.0] = 0.0
self.log_image = np.log10(self.log_image + 1.0)
# populate an array containing the indices of all pixels in the image
mg = np.meshgrid(np.arange(self.raw_image.shape[0]),
np.arange(self.raw_image.shape[1]))
self.points = np.vstack((mg[0].flatten(), mg[1].flatten())).T
# create a colormap with masked pixels clearly highlighted
self.palette = plt.cm.PuOr_r # reversed purple-orange -- base cm
self.palette.set_under(color='green')
# draw the main GUI, which is an image that can be interactively masked
plt.figure(figsize=(9, 6))
self.ax = plt.subplot(111)
self.im = self.ax.imshow(
(self.log_image * self.mask.mask2d) - 1e-10,
cmap=self.palette,
origin='lower',
interpolation='nearest',
vmin=1e-10,
aspect=1,
extent=[0, self.log_image.shape[0], 0, self.log_image.shape[1]])
self.lc, = self.ax.plot((0, 0), (0, 0),
'-+m',
linewidth=1,
markersize=8,
markeredgewidth=1)
self.lm, = self.ax.plot((0, 0), (0, 0),
'-+m',
linewidth=1,
markersize=8,
markeredgewidth=1)
self.line_corner = (0, 0)
self.xy = None
self.lines_xy = None
self.single_px = None # for masking single pixels
self.colorbar = plt.colorbar(self.im, pad=0.01)
self.colorbar.set_label(r'$\log_{10}$ Intensity')
cidb = plt.connect('button_press_event', self.on_click)
cidk = plt.connect('key_press_event', self.on_keypress)
cidm = plt.connect('motion_notify_event', self.on_move)
plt.xlim([0, self.log_image.shape[0]])
plt.ylim([0, self.log_image.shape[1]])
self.ax.get_xaxis().set_ticks([])
self.ax.get_yaxis().set_ticks([])
# add toggle buttons that allow the user to turn on and off std masks
# I used to have this in its own nice function, but MPL didn't like
# that for some reason... there is probably a better way, I just dont
# know the innerds of MPL enough --TJL
axcolor = 'lightgoldenrodyellow'
ax1 = plt.axes([0.04, 0.7, 0.12, 0.08])
self.b1 = ToggleButton(ax1,
'nonbonded',
color=axcolor,
hovercolor='0.975')
self.b1.on_turned_on(self.mask.mask_nonbonded)
self.b1.on_turned_off(self.mask.remove_mask, 'nonbonded')
self.b1.on_turned_on(self.update_image)
self.b1.on_turned_off(self.update_image)
ax2 = plt.axes([0.04, 0.6, 0.12, 0.08])
self.b2 = ToggleButton(ax2,
'row 13',
color=axcolor,
hovercolor='0.975')
self.b2.on_turned_on(self.mask.mask_row13)
self.b2.on_turned_off(self.mask.remove_mask, 'row13')
self.b2.on_turned_on(self.update_image)
self.b2.on_turned_off(self.update_image)
ax3 = plt.axes([0.04, 0.5, 0.12, 0.08])
self.b3 = ToggleButton(ax3,
'borders',
color=axcolor,
hovercolor='0.975')
self.b3.on_turned_on(self._set_borderwidth)
self.mask_border_cid = self.b3.on_turned_on(self.mask.mask_borders)
self.b3.on_turned_off(self.mask.remove_mask, 'border')
self.b3.on_turned_on(self.update_image)
self.b3.on_turned_off(self.update_image)
ax4 = plt.axes([0.04, 0.4, 0.12, 0.08])
self.b4 = ToggleButton(ax4,
'threshold',
color=axcolor,
hovercolor='0.975')
self.b4.on_turned_on(self._set_threshold)
self.mask_threshold_cid = self.b4.on_turned_on(
self.mask.mask_threshold, self.raw_image_4d, None, None)
self.b4.on_turned_off(self.mask.remove_mask, 'threshold')
self.b4.on_turned_on(self.update_image)
self.b4.on_turned_off(self.update_image)
plt.show()
return
def __init__(self, raw_image, mask=None, filename='my_mask', fmt='pypad'):
"""
Instantiate an interactive masking session.
Parameters
----------
raw_image : np.ndarray
A shape (4, 8, 185, 388) array containing a reference image that
the user will use to guide their masking.
mask : padmask.PadMask
A PadMask object to modify. If `None` (default), generate a new
mask.
filename : str
The name of the file to generate at the end of the session.
fmt : str
The file format of `filename` to write.
"""
self.print_gui_help()
self.filename = filename
self.file_fmt = fmt
if not raw_image.shape == (4, 16, 185, 194):
raise ValueError("`raw_image` must have shape: (4, 16, 185, 194)")
if mask == None:
self.mask = PadMask()
elif isinstance(mask, PadMask):
self.mask = mask
else:
raise TypeError('`mask` argument must be a pypad.mask.PadMask object')
# inject a new mask type into our PadMask obj
m = self.mask._blank_mask()
if not 'manual' in self.mask._masks.keys():
self.mask._inject_mask('manual', m)
# deal with negative values
if not 'negatives' in self.mask._masks.keys():
self.mask._inject_mask('negatives', m.copy())
self.mask._masks['negatives'][raw_image <= 0.0] = 0
print "Masked: %d negative pixels" % np.sum(np.logical_not(self.mask._masks['negatives']))
# we're going to plot the log of the image, so do that up front
self.raw_image_4d = raw_image
self.raw_image = utils.flatten_2x1s(raw_image)
self.log_image = self.raw_image.copy()
self.log_image[self.log_image < 0.0] = 0.0
self.log_image = np.log10(self.log_image + 1.0)
# populate an array containing the indices of all pixels in the image
mg = np.meshgrid( np.arange(self.raw_image.shape[0]),
np.arange(self.raw_image.shape[1]) )
self.points = np.vstack((mg[0].flatten(), mg[1].flatten())).T
# create a colormap with masked pixels clearly highlighted
self.palette = plt.cm.PuOr_r # reversed purple-orange -- base cm
self.palette.set_under(color='green')
# draw the main GUI, which is an image that can be interactively masked
plt.figure(figsize=(9,6))
self.ax = plt.subplot(111)
self.im = self.ax.imshow( (self.log_image * self.mask.mask2d) - 1e-10, cmap=self.palette,
origin='lower', interpolation='nearest', vmin=1e-10, aspect=1,
extent=[0, self.log_image.shape[0], 0, self.log_image.shape[1]] )
self.lc, = self.ax.plot((0,0),(0,0),'-+m', linewidth=1, markersize=8, markeredgewidth=1)
self.lm, = self.ax.plot((0,0),(0,0),'-+m', linewidth=1, markersize=8, markeredgewidth=1)
self.line_corner = (0,0)
self.xy = None
self.lines_xy = None
self.single_px = None # for masking single pixels
self.colorbar = plt.colorbar(self.im, pad=0.01)
self.colorbar.set_label(r'$\log_{10}$ Intensity')
cidb = plt.connect('button_press_event', self.on_click)
cidk = plt.connect('key_press_event', self.on_keypress)
cidm = plt.connect('motion_notify_event', self.on_move)
plt.xlim([0, self.log_image.shape[0]])
plt.ylim([0, self.log_image.shape[1]])
self.ax.get_xaxis().set_ticks([])
self.ax.get_yaxis().set_ticks([])
# add toggle buttons that allow the user to turn on and off std masks
# I used to have this in its own nice function, but MPL didn't like
# that for some reason... there is probably a better way, I just dont
# know the innerds of MPL enough --TJL
axcolor = 'lightgoldenrodyellow'
ax1 = plt.axes([0.04, 0.7, 0.12, 0.08])
self.b1 = ToggleButton(ax1, 'nonbonded', color=axcolor, hovercolor='0.975')
self.b1.on_turned_on(self.mask.mask_nonbonded)
self.b1.on_turned_off(self.mask.remove_mask, 'nonbonded')
self.b1.on_turned_on(self.update_image)
self.b1.on_turned_off(self.update_image)
ax2 = plt.axes([0.04, 0.6, 0.12, 0.08])
self.b2 = ToggleButton(ax2, 'row 13', color=axcolor, hovercolor='0.975')
self.b2.on_turned_on(self.mask.mask_row13)
self.b2.on_turned_off(self.mask.remove_mask, 'row13')
self.b2.on_turned_on(self.update_image)
self.b2.on_turned_off(self.update_image)
ax3 = plt.axes([0.04, 0.5, 0.12, 0.08])
self.b3 = ToggleButton(ax3, 'borders', color=axcolor, hovercolor='0.975')
self.b3.on_turned_on(self._set_borderwidth)
self.mask_border_cid = self.b3.on_turned_on(self.mask.mask_borders)
self.b3.on_turned_off(self.mask.remove_mask, 'border')
self.b3.on_turned_on(self.update_image)
self.b3.on_turned_off(self.update_image)
ax4 = plt.axes([0.04, 0.4, 0.12, 0.08])
self.b4 = ToggleButton(ax4, 'threshold', color=axcolor, hovercolor='0.975')
self.b4.on_turned_on(self._set_threshold)
self.mask_threshold_cid = self.b4.on_turned_on(self.mask.mask_threshold, self.raw_image_4d, None, None)
self.b4.on_turned_off(self.mask.remove_mask, 'threshold')
self.b4.on_turned_on(self.update_image)
self.b4.on_turned_off(self.update_image)
plt.show()
return
class MaskGUI(object):
def __init__(self, raw_image, mask=None, filename='my_mask', fmt='pypad'):
"""
Instantiate an interactive masking session.
Parameters
----------
raw_image : np.ndarray
A shape (4, 8, 185, 388) array containing a reference image that
the user will use to guide their masking.
mask : padmask.PadMask
A PadMask object to modify. If `None` (default), generate a new
mask.
filename : str
The name of the file to generate at the end of the session.
fmt : str
The file format of `filename` to write.
"""
self.print_gui_help()
self.filename = filename
self.file_fmt = fmt
if not raw_image.shape == (4, 16, 185, 194):
raise ValueError("`raw_image` must have shape: (4, 16, 185, 194)")
if mask == None:
self.mask = PadMask()
elif isinstance(mask, PadMask):
self.mask = mask
else:
raise TypeError(
'`mask` argument must be a pypad.mask.PadMask object')
# inject a new mask type into our PadMask obj
m = self.mask._blank_mask()
if not 'manual' in self.mask._masks.keys():
self.mask._inject_mask('manual', m)
# deal with negative values
if not 'negatives' in self.mask._masks.keys():
self.mask._inject_mask('negatives', m.copy())
self.mask._masks['negatives'][raw_image <= 0.0] = 0
print "Masked: %d negative pixels" % np.sum(
np.logical_not(self.mask._masks['negatives']))
# we're going to plot the log of the image, so do that up front
self.raw_image_4d = raw_image
self.raw_image = utils.flatten_2x1s(raw_image)
self.log_image = self.raw_image.copy()
self.log_image[self.log_image < 0.0] = 0.0
self.log_image = np.log10(self.log_image + 1.0)
# populate an array containing the indices of all pixels in the image
mg = np.meshgrid(np.arange(self.raw_image.shape[0]),
np.arange(self.raw_image.shape[1]))
self.points = np.vstack((mg[0].flatten(), mg[1].flatten())).T
# create a colormap with masked pixels clearly highlighted
self.palette = plt.cm.PuOr_r # reversed purple-orange -- base cm
self.palette.set_under(color='green')
# draw the main GUI, which is an image that can be interactively masked
plt.figure(figsize=(9, 6))
self.ax = plt.subplot(111)
self.im = self.ax.imshow(
(self.log_image * self.mask.mask2d) - 1e-10,
cmap=self.palette,
origin='lower',
interpolation='nearest',
vmin=1e-10,
aspect=1,
extent=[0, self.log_image.shape[0], 0, self.log_image.shape[1]])
self.lc, = self.ax.plot((0, 0), (0, 0),
'-+m',
linewidth=1,
markersize=8,
markeredgewidth=1)
self.lm, = self.ax.plot((0, 0), (0, 0),
'-+m',
linewidth=1,
markersize=8,
markeredgewidth=1)
self.line_corner = (0, 0)
self.xy = None
self.lines_xy = None
self.single_px = None # for masking single pixels
self.colorbar = plt.colorbar(self.im, pad=0.01)
self.colorbar.set_label(r'$\log_{10}$ Intensity')
cidb = plt.connect('button_press_event', self.on_click)
cidk = plt.connect('key_press_event', self.on_keypress)
cidm = plt.connect('motion_notify_event', self.on_move)
plt.xlim([0, self.log_image.shape[0]])
plt.ylim([0, self.log_image.shape[1]])
self.ax.get_xaxis().set_ticks([])
self.ax.get_yaxis().set_ticks([])
# add toggle buttons that allow the user to turn on and off std masks
# I used to have this in its own nice function, but MPL didn't like
# that for some reason... there is probably a better way, I just dont
# know the innerds of MPL enough --TJL
axcolor = 'lightgoldenrodyellow'
ax1 = plt.axes([0.04, 0.7, 0.12, 0.08])
self.b1 = ToggleButton(ax1,
'nonbonded',
color=axcolor,
hovercolor='0.975')
self.b1.on_turned_on(self.mask.mask_nonbonded)
self.b1.on_turned_off(self.mask.remove_mask, 'nonbonded')
self.b1.on_turned_on(self.update_image)
self.b1.on_turned_off(self.update_image)
ax2 = plt.axes([0.04, 0.6, 0.12, 0.08])
self.b2 = ToggleButton(ax2,
'row 13',
color=axcolor,
hovercolor='0.975')
self.b2.on_turned_on(self.mask.mask_row13)
self.b2.on_turned_off(self.mask.remove_mask, 'row13')
self.b2.on_turned_on(self.update_image)
self.b2.on_turned_off(self.update_image)
ax3 = plt.axes([0.04, 0.5, 0.12, 0.08])
self.b3 = ToggleButton(ax3,
'borders',
color=axcolor,
hovercolor='0.975')
self.b3.on_turned_on(self._set_borderwidth)
self.mask_border_cid = self.b3.on_turned_on(self.mask.mask_borders)
self.b3.on_turned_off(self.mask.remove_mask, 'border')
self.b3.on_turned_on(self.update_image)
self.b3.on_turned_off(self.update_image)
ax4 = plt.axes([0.04, 0.4, 0.12, 0.08])
self.b4 = ToggleButton(ax4,
'threshold',
color=axcolor,
hovercolor='0.975')
self.b4.on_turned_on(self._set_threshold)
self.mask_threshold_cid = self.b4.on_turned_on(
self.mask.mask_threshold, self.raw_image_4d, None, None)
self.b4.on_turned_off(self.mask.remove_mask, 'threshold')
self.b4.on_turned_on(self.update_image)
self.b4.on_turned_off(self.update_image)
plt.show()
return
def _set_threshold(self):
print "\n --- Enter threshold values --- "
self.lower_thld = float(raw_input('Enter lower threshold: '))
self.upper_thld = float(raw_input('Enter upper threshold: '))
self.b4.onstate_exargs[self.mask_threshold_cid] = (self.raw_image_4d,
self.upper_thld,
self.lower_thld)
return
def _set_borderwidth(self):
print "\n --- Enter the desired border width --- "
raw_in = raw_input('Size of border (in pixels) [1]: ')
if raw_in == '':
self.borderwidth = 1
else:
self.borderwidth = int(raw_in)
self.b3.onstate_exargs[self.mask_border_cid] = (self.borderwidth, )
return
def update_image(self):
self.im.set_data((self.log_image * self.mask.mask2d) - 1e-10)
return
def on_click(self, event):
# for WHATEVER reason, the imshow drawing is stretched incorrectly
# such that pixel positions for x/y are off by the ratio used below
# ... this is likely due to me not understanding MPL, hence this hack
# -- TJL
ratio = float(self.log_image.shape[0]) / float(self.log_image.shape[1])
x_coord = event.xdata / ratio
y_coord = event.ydata * ratio
# if a button that is *not* the left click is pressed
if event.inaxes and (event.button is not 1):
# save the points for masking in pixel coordinates
if self.xy != None:
self.xy = np.vstack(
(self.xy, np.array([int(x_coord),
int(y_coord)])))
else:
self.xy = np.array([int(x_coord), int(y_coord)])
# save the points for drawing the lines in MPL coordinates
if self.lines_xy != None:
self.lines_xy = np.vstack(
(self.lines_xy,
np.array([int(event.xdata),
int(event.ydata)])))
else:
self.lines_xy = np.array([int(event.xdata), int(event.ydata)])
self.lc.set_data(self.lines_xy.T) # draws lines
self.line_corner = (int(event.xdata), int(event.ydata))
# if the left button is pressed
elif event.inaxes and (event.button is 1):
self.single_px = (int(x_coord), int(y_coord))
print "Selected: (%s, %s)" % self.single_px
return
def on_keypress(self, event):
# mask or unmask
if event.key in ['m', 'u']:
if self.xy == None:
print "No area selected, mask not changed."
else:
# print "Masking region inside:"
# print self.xy
# wrap around to close polygon
self.xy = np.vstack((self.xy, self.xy[0, :]))
path = Path(self.xy)
in_area = path.contains_points(self.points + 0.5)
inds = self.points[in_area]
#print self.xy
#print inds
# if we're going to mask, mask
if event.key == 'm':
print 'Masking convex area...'
x = self._conv_2dinds_to_4d(inds)
self.mask._masks['manual'][x[:, 0], x[:, 1], x[:, 2],
x[:, 3]] = 0
# if we're unmasking, unmask
elif event.key == 'u':
print 'Unmasking convex area...'
x = self._conv_2dinds_to_4d(inds)
self.mask._masks['manual'][x[:, 0], x[:, 1], x[:, 2],
x[:, 3]] = 1
# draw and reset
self.update_image()
self._reset()
plt.draw()
# reset all masks
elif event.key == 'r':
print 'Unmasking all'
self.mask._masks['manual'] = self.mask._blank_mask()
self.update_image()
self._reset()
#self.im.autoscale()
plt.draw()
# toggle selection
elif event.key == 't':
if self.single_px != None:
x = self._conv_2dinds_to_4d(np.array(self.single_px)[None, :])
x = x.flatten()
if self.mask.mask[x[0], x[1], x[2], x[3]] == 0:
print "Unmasking single pixel:", self.single_px
self.mask._masks['manual'][x[0], x[1], x[2], x[3]] = 1
else:
print "Masking single pixel:", self.single_px
self.mask._masks['manual'][x[0], x[1], x[2], x[3]] = 0
else:
print "No single pixel selected to toggle. Click a pixel and"
print " press `t` to toggle the mask on that pixel."
self.update_image()
self._reset()
#self.im.autoscale()
plt.draw()
# clear mouse selection
elif event.key == 'x':
print "Reset selections"
self._reset()
# save and exit
elif event.key == 'w':
self.mask.save(self.filename, fmt=self.file_fmt)
plt.close()
return
# exit w/o saving
elif event.key == 'q':
print 'Exiting without saving...'
plt.close()
return
# else:
# print "Could not understand key: %s" % event.key
# print "Valid options: {m, u, r, k, q}"
return
def on_move(self, event):
if not event.inaxes: return
xm, ym = int(event.xdata), int(event.ydata)
# update the line positions
if self.line_corner != (0, 0):
self.lm.set_data((self.line_corner[0], xm),
(self.line_corner[1], ym))
plt.draw()
return
def _reset(self):
self.single_pixel = None
self.xy = None
self.lines_xy = None
self.lc.set_data([], [])
self.lm.set_data([], [])
self.line_corner = (0, 0)
return
def _conv_2dinds_to_4d(self, inds):
"""
Convert indices in a 2d Cheetah array to (4,16,185,194).
Parameters
----------
inds : np.ndarray, int
An N x 2 array, where the first column indexes x on the 2d image,
and the second column indexes y.
Returns
-------
inds_4d : np.ndarray, int
An N x 4 array, with each column indexing quads/asics/y/x,
"""
inds_4d = np.zeros((inds.shape[0], 4), dtype=np.int32)
# index each asic, in the correct order
of64 = (inds[:, 1] / 185) * 2 + (inds[:, 0] / 388) * 16 + (inds[:, 0] /
194) % 2
assert np.all(of64 < 64)
# quads / asics
# print 'masking in ASICs:', inds, of64
inds_4d[:, 0] = of64 / 16
inds_4d[:, 1] = of64 % 16
# x / y : note the image is displayed transposed
inds_4d[:, 2] = (inds[:, 1] % 185)
inds_4d[:, 3] = (inds[:, 0] % 194)
return inds_4d
def print_gui_help(self):
print
print
print " --- WELCOME TO PYPAD's INTERACTIVE MASKING ENVIRONMENT --- "
print
print " Green pixels are masked."
print
print " Keystrokes"
print " ----------"
print " m : mask u : unmask r : reset "
print " x : clear selection w : save & exit t : toggle pixel"
print " q : exit w/o saving"
print
print " Mouse"
print " -----"
print " Right click on three or more points to draw a polygon around a"
print " set of pixels. Then press `m` or `u` to mask or unmask that area."
print
print " You can also mask/unmask single pixels by clicking on them with"
print " the mouse and pressing `t` to toggle the mask state."
print
print " Toggle Buttons (left)"
print " ---------------------"
print " nonbonded : Mask nonbonded pixels, and their nearest neighbours."
print " These pixels aren't even connected to the detector."
print
print " row 13 : In some old experiments, row 13 on one ASIC was "
print " busted -- mask that (will be clear if this is needed)"
print
print " threshold : You will be prompted for an upper and lower limit --"
print " pixels outside that range are masked. Units are ADUs"
print " and you can set only a lower/upper limit by passing"
print " 'None' for one option."
print
print " borders : Mask the borders of each ASIC. These often give"
print " anomoulous responses. Recommended to mask one pixel"
print " borders at least."
print ""
print " ----- // -----"
print
class MaskGUI(object):
def __init__(self, raw_image, mask=None, filename='my_mask', fmt='pypad'):
"""
Instantiate an interactive masking session.
Parameters
----------
raw_image : np.ndarray
A shape (4, 8, 185, 388) array containing a reference image that
the user will use to guide their masking.
mask : padmask.PadMask
A PadMask object to modify. If `None` (default), generate a new
mask.
filename : str
The name of the file to generate at the end of the session.
fmt : str
The file format of `filename` to write.
"""
self.print_gui_help()
self.filename = filename
self.file_fmt = fmt
if not raw_image.shape == (4, 16, 185, 194):
raise ValueError("`raw_image` must have shape: (4, 16, 185, 194)")
if mask == None:
self.mask = PadMask()
elif isinstance(mask, PadMask):
self.mask = mask
else:
raise TypeError('`mask` argument must be a pypad.mask.PadMask object')
# inject a new mask type into our PadMask obj
m = self.mask._blank_mask()
if not 'manual' in self.mask._masks.keys():
self.mask._inject_mask('manual', m)
# deal with negative values
if not 'negatives' in self.mask._masks.keys():
self.mask._inject_mask('negatives', m.copy())
self.mask._masks['negatives'][raw_image <= 0.0] = 0
print "Masked: %d negative pixels" % np.sum(np.logical_not(self.mask._masks['negatives']))
# we're going to plot the log of the image, so do that up front
self.raw_image_4d = raw_image
self.raw_image = utils.flatten_2x1s(raw_image)
self.log_image = self.raw_image.copy()
self.log_image[self.log_image < 0.0] = 0.0
self.log_image = np.log10(self.log_image + 1.0)
# populate an array containing the indices of all pixels in the image
mg = np.meshgrid( np.arange(self.raw_image.shape[0]),
np.arange(self.raw_image.shape[1]) )
self.points = np.vstack((mg[0].flatten(), mg[1].flatten())).T
# create a colormap with masked pixels clearly highlighted
self.palette = plt.cm.PuOr_r # reversed purple-orange -- base cm
self.palette.set_under(color='green')
# draw the main GUI, which is an image that can be interactively masked
plt.figure(figsize=(9,6))
self.ax = plt.subplot(111)
self.im = self.ax.imshow( (self.log_image * self.mask.mask2d) - 1e-10, cmap=self.palette,
origin='lower', interpolation='nearest', vmin=1e-10, aspect=1,
extent=[0, self.log_image.shape[0], 0, self.log_image.shape[1]] )
self.lc, = self.ax.plot((0,0),(0,0),'-+m', linewidth=1, markersize=8, markeredgewidth=1)
self.lm, = self.ax.plot((0,0),(0,0),'-+m', linewidth=1, markersize=8, markeredgewidth=1)
self.line_corner = (0,0)
self.xy = None
self.lines_xy = None
self.single_px = None # for masking single pixels
self.colorbar = plt.colorbar(self.im, pad=0.01)
self.colorbar.set_label(r'$\log_{10}$ Intensity')
cidb = plt.connect('button_press_event', self.on_click)
cidk = plt.connect('key_press_event', self.on_keypress)
cidm = plt.connect('motion_notify_event', self.on_move)
plt.xlim([0, self.log_image.shape[0]])
plt.ylim([0, self.log_image.shape[1]])
self.ax.get_xaxis().set_ticks([])
self.ax.get_yaxis().set_ticks([])
# add toggle buttons that allow the user to turn on and off std masks
# I used to have this in its own nice function, but MPL didn't like
# that for some reason... there is probably a better way, I just dont
# know the innerds of MPL enough --TJL
axcolor = 'lightgoldenrodyellow'
ax1 = plt.axes([0.04, 0.7, 0.12, 0.08])
self.b1 = ToggleButton(ax1, 'nonbonded', color=axcolor, hovercolor='0.975')
self.b1.on_turned_on(self.mask.mask_nonbonded)
self.b1.on_turned_off(self.mask.remove_mask, 'nonbonded')
self.b1.on_turned_on(self.update_image)
self.b1.on_turned_off(self.update_image)
ax2 = plt.axes([0.04, 0.6, 0.12, 0.08])
self.b2 = ToggleButton(ax2, 'row 13', color=axcolor, hovercolor='0.975')
self.b2.on_turned_on(self.mask.mask_row13)
self.b2.on_turned_off(self.mask.remove_mask, 'row13')
self.b2.on_turned_on(self.update_image)
self.b2.on_turned_off(self.update_image)
ax3 = plt.axes([0.04, 0.5, 0.12, 0.08])
self.b3 = ToggleButton(ax3, 'borders', color=axcolor, hovercolor='0.975')
self.b3.on_turned_on(self._set_borderwidth)
self.mask_border_cid = self.b3.on_turned_on(self.mask.mask_borders)
self.b3.on_turned_off(self.mask.remove_mask, 'border')
self.b3.on_turned_on(self.update_image)
self.b3.on_turned_off(self.update_image)
ax4 = plt.axes([0.04, 0.4, 0.12, 0.08])
self.b4 = ToggleButton(ax4, 'threshold', color=axcolor, hovercolor='0.975')
self.b4.on_turned_on(self._set_threshold)
self.mask_threshold_cid = self.b4.on_turned_on(self.mask.mask_threshold, self.raw_image_4d, None, None)
self.b4.on_turned_off(self.mask.remove_mask, 'threshold')
self.b4.on_turned_on(self.update_image)
self.b4.on_turned_off(self.update_image)
plt.show()
return
def _set_threshold(self):
print "\n --- Enter threshold values --- "
self.lower_thld = float( raw_input('Enter lower threshold: ') )
self.upper_thld = float( raw_input('Enter upper threshold: ') )
self.b4.onstate_exargs[ self.mask_threshold_cid ] = (self.raw_image_4d, self.upper_thld, self.lower_thld)
return
def _set_borderwidth(self):
print "\n --- Enter the desired border width --- "
raw_in = raw_input('Size of border (in pixels) [1]: ')
if raw_in == '':
self.borderwidth = 1
else:
self.borderwidth = int( raw_in )
self.b3.onstate_exargs[ self.mask_border_cid ] = (self.borderwidth,)
return
def update_image(self):
self.im.set_data( (self.log_image * self.mask.mask2d) - 1e-10 )
return
def on_click(self, event):
# for WHATEVER reason, the imshow drawing is stretched incorrectly
# such that pixel positions for x/y are off by the ratio used below
# ... this is likely due to me not understanding MPL, hence this hack
# -- TJL
ratio = float(self.log_image.shape[0]) / float(self.log_image.shape[1])
x_coord = event.xdata / ratio
y_coord = event.ydata * ratio
# if a button that is *not* the left click is pressed
if event.inaxes and (event.button is not 1):
# save the points for masking in pixel coordinates
if self.xy != None:
self.xy = np.vstack(( self.xy, np.array([int(x_coord),
int(y_coord)]) ))
else:
self.xy = np.array([int(x_coord), int(y_coord)])
# save the points for drawing the lines in MPL coordinates
if self.lines_xy != None:
self.lines_xy = np.vstack(( self.lines_xy, np.array([int(event.xdata),
int(event.ydata)]) ))
else:
self.lines_xy = np.array([int(event.xdata), int(event.ydata)])
self.lc.set_data(self.lines_xy.T) # draws lines
self.line_corner = (int(event.xdata), int(event.ydata))
# if the left button is pressed
elif event.inaxes and (event.button is 1):
self.single_px = (int(x_coord), int(y_coord))
print "Selected: (%s, %s)" % self.single_px
return
def on_keypress(self, event):
# mask or unmask
if event.key in ['m', 'u']:
if self.xy == None:
print "No area selected, mask not changed."
else:
# print "Masking region inside:"
# print self.xy
# wrap around to close polygon
self.xy = np.vstack(( self.xy, self.xy[0,:] ))
path = Path(self.xy)
in_area = path.contains_points(self.points+0.5)
inds = self.points[in_area]
#print self.xy
#print inds
# if we're going to mask, mask
if event.key == 'm':
print 'Masking convex area...'
x = self._conv_2dinds_to_4d(inds)
self.mask._masks['manual'][x[:,0],x[:,1],x[:,2],x[:,3]] = 0
# if we're unmasking, unmask
elif event.key == 'u':
print 'Unmasking convex area...'
x = self._conv_2dinds_to_4d(inds)
self.mask._masks['manual'][x[:,0],x[:,1],x[:,2],x[:,3]] = 1
# draw and reset
self.update_image()
self._reset()
plt.draw()
# reset all masks
elif event.key == 'r':
print 'Unmasking all'
self.mask._masks['manual'] = self.mask._blank_mask()
self.update_image()
self._reset()
#self.im.autoscale()
plt.draw()
# toggle selection
elif event.key == 't':
if self.single_px != None:
x = self._conv_2dinds_to_4d( np.array(self.single_px)[None,:] )
x = x.flatten()
if self.mask.mask[x[0],x[1],x[2],x[3]] == 0:
print "Unmasking single pixel:", self.single_px
self.mask._masks['manual'][x[0],x[1],x[2],x[3]] = 1
else:
print "Masking single pixel:", self.single_px
self.mask._masks['manual'][x[0],x[1],x[2],x[3]] = 0
else:
print "No single pixel selected to toggle. Click a pixel and"
print " press `t` to toggle the mask on that pixel."
self.update_image()
self._reset()
#self.im.autoscale()
plt.draw()
# clear mouse selection
elif event.key == 'x':
print "Reset selections"
self._reset()
# save and exit
elif event.key == 'w':
self.mask.save(self.filename, fmt=self.file_fmt)
plt.close()
return
# exit w/o saving
elif event.key == 'q':
print 'Exiting without saving...'
plt.close()
return
# else:
# print "Could not understand key: %s" % event.key
# print "Valid options: {m, u, r, k, q}"
return
def on_move(self, event):
if not event.inaxes: return
xm, ym = int(event.xdata), int(event.ydata)
# update the line positions
if self.line_corner != (0,0):
self.lm.set_data((self.line_corner[0],xm), (self.line_corner[1],ym))
plt.draw()
return
def _reset(self):
self.single_pixel = None
self.xy = None
self.lines_xy = None
self.lc.set_data([], [])
self.lm.set_data([], [])
self.line_corner = (0, 0)
return
def _conv_2dinds_to_4d(self, inds):
"""
Convert indices in a 2d Cheetah array to (4,16,185,194).
Parameters
----------
inds : np.ndarray, int
An N x 2 array, where the first column indexes x on the 2d image,
and the second column indexes y.
Returns
-------
inds_4d : np.ndarray, int
An N x 4 array, with each column indexing quads/asics/y/x,
"""
inds_4d = np.zeros((inds.shape[0], 4), dtype=np.int32)
# index each asic, in the correct order
of64 = (inds[:,1] / 185) * 2 + (inds[:,0] / 388) * 16 + (inds[:,0] / 194) % 2
assert np.all(of64 < 64)
# quads / asics
# print 'masking in ASICs:', inds, of64
inds_4d[:,0] = of64 / 16
inds_4d[:,1] = of64 % 16
# x / y : note the image is displayed transposed
inds_4d[:,2] = (inds[:,1] % 185)
inds_4d[:,3] = (inds[:,0] % 194)
return inds_4d
def print_gui_help(self):
print
print
print " --- WELCOME TO PYPAD's INTERACTIVE MASKING ENVIRONMENT --- "
print
print " Green pixels are masked."
print
print " Keystrokes"
print " ----------"
print " m : mask u : unmask r : reset "
print " x : clear selection w : save & exit t : toggle pixel"
print " q : exit w/o saving"
print
print " Mouse"
print " -----"
print " Right click on three or more points to draw a polygon around a"
print " set of pixels. Then press `m` or `u` to mask or unmask that area."
print
print " You can also mask/unmask single pixels by clicking on them with"
print " the mouse and pressing `t` to toggle the mask state."
print
print " Toggle Buttons (left)"
print " ---------------------"
print " nonbonded : Mask nonbonded pixels, and their nearest neighbours."
print " These pixels aren't even connected to the detector."
print
print " row 13 : In some old experiments, row 13 on one ASIC was "
print " busted -- mask that (will be clear if this is needed)"
print
print " threshold : You will be prompted for an upper and lower limit --"
print " pixels outside that range are masked. Units are ADUs"
print " and you can set only a lower/upper limit by passing"
print " 'None' for one option."
print
print " borders : Mask the borders of each ASIC. These often give"
print " anomoulous responses. Recommended to mask one pixel"
print " borders at least."
print ""
print " ----- // -----"
print
