def _updateViewRotable(self):
simg = self.img
if simg.ndim == 2:
simg = [simg]
for img, plot, vplot, rplot in zip(simg, self.plots,
self.stdPlots, self.rmsPlots):
data, coords = self.getArrayRegion(img.view(np.ndarray),
self.master.imageItem, axes=(
0, 1),
returnMappedCoords=True)
dataorig = data # np.copy(data)
if data is not None:
while data.ndim > 1:
# average rectangle to line
data = data.mean(axis=1)
while coords.ndim > 2:
coords = coords[:, :, 0]
coords = coords - coords[:, 0, np.newaxis]
xvals = (coords**2).sum(axis=0) ** 0.5
plot.setData(y=data, x=xvals)
if vplot:
vplot.setData(y=dataorig.var(axis=1),
x=xvals,
symbol=self.getSymbol())
if rplot:
rplot.setData(y=RMS(dataorig, axis=1),
x=xvals,
symbol=self.getSymbol())
p = self.boundingRect().bottomLeft() + self.pos()
self.text.setPos(p)
def updateView(self):
x_vals = self.tool.display.stack.values
data = []
# DATA
def getData(img):
d = self.getArrayRegion(img.view(np.ndarray),
self.master.imageItem, axes=(0, 1))
if d is not None:
data.append(d)
if self.img.ndim > 2:
for layer in self.img:
getData(layer)
else:
getData(self.img)
# MEAN
mean = [d.mean() for d in data]
self.plot.setData(y=mean,
x=x_vals,
symbol=self.getSymbol())
# STD
if self.stdPlot:
self.stdPlot.setData(y=[d.std() for d in data],
x=x_vals,
symbol=self.getSymbol())
# RMS
if self.rmsPlot:
self.rmsPlot.setData(y=[RMS(d) - m for d, m in zip(data, mean)],
x=x_vals,
symbol=self.getSymbol())
def _updateViewStatic(self):
# COORDS
px, py = self.pos().x(), self.pos().y()
r = self.boundingRect()
x0, y0, x1, y1 = r.getCoords()
x0 = max(0, int(round(x0 + px)))
x1 = int(round(x1 + px))
y0 = max(0, int(round(y0 + py)))
y1 = int(round(y1 + py))
# TEXT
#self.text.setText('%s (%s,%s)-(%s,%s)' %(self.name(), x0,y0,x1,y1) )
self.text.setPos(px, py)
simg = self.img
if simg.ndim == 2:
simg = [simg]
for img, plot, vplot, rplot in zip(simg, self.plots,
self.stdPlots, self.rmsPlots):
# DATA
try:
dataorig = img[y0:y1, x0:x1]
if dataorig.dtype.kind == 'f' and np.any(np.sum(dataorig)):
mean = np.nanmean
else:
mean = np.mean
if dataorig.ndim == 3: # color
data = mean(dataorig, axis=(self.av_dir, 2))
else:
data = mean(dataorig,axis=self.av_dir)
if self.av_dir == 1:
xvals = np.linspace(x0, x1, len(data))
else:
xvals = np.linspace(y0, y1, len(data))
plot.setData(y=data, x=xvals)
if vplot:
vplot.setData(y=dataorig.var(axis=self.av_dir),
x=xvals,
symbol=self.getSymbol())
if rplot:
rplot.setData(y=RMS(dataorig, axis=self.av_dir),
x=xvals,
symbol=self.getSymbol())
except (IndexError, ValueError): # out out bounds
pass
def activate(self):
img = self.display.widget.image
if self.pLimitRange.value():
mn, mx = self.pMin.value(), self.pMax.value()
else:
mn, mx = np.min(img[0]), np.max(img[0])
bins = np.linspace(mn, mx, self.pNPlots.value() + 1)
plots = []
var_plots = []
rms_plots = []
names = []
xvals = self.display.stack.values
for start, stop in zip(bins[:-1], bins[1:]):
# get positions from first image:
indexes = np.logical_and(img[0] >= start, img[0] <= stop)
nPx = np.sum(indexes)
if not nPx:
# no values found in given range / one one element is True
continue
yvals = []
var_yvals = []
rms_yvals = []
names.append(
'(%s) %s - %s' %
(nPx, round(
start, 2), round(
stop, 2)))
# prevent stack overflow with float16 (with returns inf):
#dtype = np.float32 if img[0].dtype==np.float16 else None
for layer in img:
# CALCULATE PLOT VALUES:
mean = np.mean(layer[indexes])
yvals.append(mean)
if self.pVar.value():
var_yvals.append(np.var(layer[indexes]))
if self.pRMS.value():
rms_yvals.append(RMS(layer[indexes]) - mean)
# APPEND PLOT VALUES:
plots.append((xvals, yvals))
var_plots.append((xvals, var_yvals))
rms_plots.append((xvals, rms_yvals))
# CREATE DISPLAYS:
self.display.workspace.addDisplay(
origin=self.display,
axes=self.display.axes.copy(('stack', 0)),
names=names,
data=plots,
title='Averaged trend')
if self.pVar.value():
self.display.workspace.addDisplay(
origin=self.display,
axes=self.display.axes.copy(('stack', 0)),
names=names,
data=var_plots,
title='Variance trend ')
if self.pRMS.value():
self.display.workspace.addDisplay(
origin=self.display,
axes=self.display.axes.copy(('stack', 0)),
names=names,
data=rms_plots,
title='RMS trend - %s')