def blend_bg(self, bg, weight=0.5):
if weight > 1 or weight < 0:
raise GridError("weight must be between 0 and 1")
if bg.ndim == 3:
bg = rgb2uint(bg)
logger.warn('3-channel image convert to 8-bit uint')
if bg.shape != self.shape:
xf, yf = self.shape
try:
bg = crop(bg, 0, 0, xf, yf)
except Exception as E:
raise GridError('bg shape %s did not match grid shape %s and '
'cropping failed with: %s' %
(bg.shape, self.shape, E.message))
else:
logger.warn("bg image cropped to grid dimensions %s" %
self.shape)
# Normalize the values to balance weight sum
scale = bg.max() / self.zz.max()
zzout = self.zz * scale
alpha = 1 - weight
return (weight * zzout + (alpha * bg)) #/ scale
def multi_mask(img, *names, **kwargs):
""" Return a list/tuple/generator of masks of an image, one for each unique
label found in a colored img. EVERYTHING DOWN-CONVERTED TO UINT: NECESSARY
FOR MORPHOLOGY.LABELS ANYWAY, ALTHOUGH POSSIBLY SHOULD DO RGB2GRAY OR 255
LABELS IS MAX"""
astype = kwargs.pop('astype', tuple)
ignore = kwargs.pop('ignore', 'black')
names = list(names)
# THIS WILL DRASTICALLY REDUCE NUMBER OF UNIQUE LABELS ALLOWED RIGHT?
# SINCE IT ONLY HAS 255 POSSIBLE VALUES?!
if img.ndim == 3:
img = putil.rgb2uint(img, warnmsg=True)
# Labels requires on grayscale; npunique also doesn't play nice w/ rgb
if ignore == 'black' or ignore == (0,0,0):
ignore = 0
elif ignore == 'white' or ignore == (1,1,1):
ignore = 255
unique = ptools.unique(img)
if ignore not in unique:
logger.warn("Ignore set to %s but was not found on image." % ignore)
else:
unique = [v for v in unique if v != ignore]
names = _parse_names(names, unique)
# Make the mask dict as generator
out = ((str(names[idx]), (img==v)) for idx, v in enumerate(unique))
return putil._parse_generator(out, astype)
def blend_bg(self, bg, weight=0.5):
if weight > 1 or weight < 0:
raise GridError("weight must be between 0 and 1")
if bg.ndim == 3:
bg = rgb2uint(bg)
logger.warn('3-channel image convert to 8-bit uint')
if bg.shape != self.shape:
xf, yf = self.shape
try:
bg = crop(bg, 0, 0, xf, yf)
except Exception as E:
raise GridError('bg shape %s did not match grid shape %s and '
'cropping failed with: %s' % (bg.shape, self.shape, E.message))
else:
logger.warn("bg image cropped to grid dimensions %s" % self.shape)
# Normalize the values to balance weight sum
scale = bg.max() / self.zz.max()
zzout = self.zz * scale
alpha = 1-weight
return (weight * zzout + ( alpha * bg) ) #/ scale
def graybackground(self):
return rgb2uint(self.background)
def grayimage(self):
""" Collapse multi-channel, scale to 255 (via ubyte) """
return rgb2uint(self.image)
def show(self, *args, **kwargs):
""" Wrapper to imshow. Converts to gray to allow color maps.
Notes
-----
Differs from patchshow in that the collective image (bg, grid, particles)
is a series of masks, so they have to be drawn onto a single ndarray and
then plotted. Sicne patchshow is writing patchs, it can plot the background
separate from the grid and particles, which is slightly easier"""
# This will pull out "ax", leaving remaing args/kwargs
axes, kwargs = _parse_ax(*args, **kwargs)
title = kwargs.pop('title', None)
save = kwargs.pop('save', None)
bgonly = kwargs.pop('bgonly', False)
annotate = kwargs.pop('annotate', False)
grid = kwargs.pop('grid', False)
gcolor = kwargs.pop('gcolor', None)
gunder = kwargs.pop('gunder', False)
gstyle = kwargs.pop('gstyle', None) #NOT USED
nolabel = kwargs.pop('nolabel', False)
zoom = kwargs.pop('zoom', None)
if gstyle:
raise CanvasPlotError('"gstyle" only valid for patchshow()')
if 'pmap' in kwargs:
raise CanvasPlotError('"pmap" is only valid for patchshow() method')
PBINARY = False
if 'cmap' in kwargs:
if kwargs['cmap'] == 'pbinary' or kwargs['cmap'] == 'pbinary_r':
PBINARY = kwargs['cmap']
del kwargs['cmap']
# Get the background
if bgonly:
if 'cmap' not in kwargs:
raise CanvasPlotError('"bgonly" is only valid when a colormap is'
' passed.')
bg = kwargs['cmap'](self.graybackground)[... , :3]
del kwargs['cmap']
else:
bg = self.background
if PBINARY:
if PBINARY == 'pbinary_r':
bg = np.ones(bg.shape).astype(bool)
else:
bg = np.zeros(bg.shape).astype(bool)
# grid overlay
if gcolor or gunder and not grid:
grid = True
# If user enters gcolor, assume default grid
if grid and not gcolor:
gcolor = GCOLOR
# Map attributes from grid (centers, corners, grid)
gattr = np.zeros(bg.shape).astype(bool) #IE pass
if grid:
if not gcolor:
gcolor = GCOLOR
if grid == True:
grid = 'grid'
# Validate grid keyword
try:
gattr=getattr( self.grid, grid.lower() )
except Exception:
raise CanvasPlotError('Invalid grid argument, "%s". Choose from: '
'True, "grid", "centers", "corners", "hlines", "vlines"'
% grid)
gcolor = to_normrgb(gcolor)
#Draw grid over or under?
if gunder:
bg[gattr] = gcolor
image = self._draw_particles(bg, force_binary=PBINARY)
else:
image = self._draw_particles(bg, force_binary=PBINARY)
image[gattr] = gcolor
# GRAY CONVERT
if 'cmap' in kwargs:
image = rgb2uint(image)
# Matplotlib
if axes:
axes.imshow(image, **kwargs)
else:
axes = plt.imshow(image, **kwargs).axes
axes = self._annotate_plot(axes, annotate, title)
# SHOW DOESNT ACTUALLY CROP ANYTHING WHEN ZOOMING
if zoom:
xi, yi, xf, yf = zoom
axes.set_xlim(xi, xf)
axes.set_ylim(yf, yi)
if nolabel:
axes.xaxis.set_visible(False)
axes.yaxis.set_visible(False)
if nolabel == 'x':
axes.yaxis.set_visible(True)
elif nolabel == 'y':
axes.xaxis.set_visible(True)
if save:
path = _parse_path(save)
skimage.io.imsave(path, image)
return axes