def render(self):
# Convert data to QImage for display.
profile = debug.Profiler()
if self.image is None or self.image.size == 0:
return
if isinstance(self.lut, collections.Callable):
lut = self.lut(self.image)
else:
lut = self.lut
if self.logScale:
image = self.image + 1
with np.errstate(invalid="ignore"):
image = image.astype(np.float)
np.log(image, where=image >= 0, out=image) # map to 0-255
else:
image = self.image
if self.autoDownsample:
# reduce dimensions of image based on screen resolution
o = self.mapToDevice(QPointF(0, 0))
x = self.mapToDevice(QPointF(1, 0))
y = self.mapToDevice(QPointF(0, 1))
w = Point(x - o).length()
h = Point(y - o).length()
if w == 0 or h == 0:
self.qimage = None
return
xds = max(1, int(1.0 / w))
yds = max(1, int(1.0 / h))
axes = [1, 0] if self.axisOrder == "row-major" else [0, 1]
image = fn.downsample(image, xds, axis=axes[0])
image = fn.downsample(image, yds, axis=axes[1])
self._lastDownsample = (xds, yds)
else:
pass
# if the image data is a small int, then we can combine levels + lut
# into a single lut for better performance
levels = self.levels
if levels is not None and levels.ndim == 1 and image.dtype in (
np.ubyte, np.uint16):
if self._effectiveLut is None:
eflsize = 2**(image.itemsize * 8)
ind = np.arange(eflsize)
minlev, maxlev = levels
levdiff = maxlev - minlev
levdiff = 1 if levdiff == 0 else levdiff # don't allow division by 0
if lut is None:
efflut = fn.rescaleData(ind,
scale=255.0 / levdiff,
offset=minlev,
dtype=np.ubyte)
else:
lutdtype = np.min_scalar_type(lut.shape[0] - 1)
efflut = fn.rescaleData(ind,
scale=(lut.shape[0] - 1) / levdiff,
offset=minlev,
dtype=lutdtype,
clip=(0, lut.shape[0] - 1))
efflut = lut[efflut]
self._effectiveLut = efflut
lut = self._effectiveLut
levels = None
# Assume images are in column-major order for backward compatibility
# (most images are in row-major order)
if self.axisOrder == "col-major":
image = image.transpose((1, 0, 2)[:image.ndim])
if self.logScale:
with np.errstate(invalid="ignore"):
levels = np.log(np.add(levels, 1))
levels[0] = np.nanmax([levels[0], 0])
argb, alpha = fn.makeARGB(image, lut=lut, levels=levels)
self.qimage = fn.makeQImage(argb, alpha, transpose=False)
def makeARGBwithNaNs(data, lut=None, levels=None, scale=None, useRGBA=False):
"""
This is the same as pyqtgraph.makeARGB, except that all NaN's in the data are set to transparent pixels
"""
nanlocations = np.isnan(data)
profile = debug.Profiler()
if data.ndim not in (2, 3):
raise TypeError("data must be 2D or 3D")
if data.ndim == 3 and data.shape[2] > 4:
raise TypeError("data.shape[2] must be <= 4")
if lut is not None and not isinstance(lut, np.ndarray):
lut = np.array(lut)
if levels is None:
# automatically decide levels based on data dtype
if data.dtype.kind == 'u':
levels = np.array([0, 2**(data.itemsize * 8) - 1])
elif data.dtype.kind == 'i':
s = 2**(data.itemsize * 8 - 1)
levels = np.array([-s, s - 1])
elif data.dtype.kind == 'b':
levels = np.array([0, 1])
else:
raise Exception(
'levels argument is required for float input types')
if not isinstance(levels, np.ndarray):
levels = np.array(levels)
if levels.ndim == 1:
if levels.shape[0] != 2:
raise Exception('levels argument must have length 2')
elif levels.ndim == 2:
if lut is not None and lut.ndim > 1:
raise Exception(
'Cannot make ARGB data when both levels and lut have ndim > 2')
if levels.shape != (data.shape[-1], 2):
raise Exception('levels must have shape (data.shape[-1], 2)')
else:
raise Exception("levels argument must be 1D or 2D (got shape=%s)." %
repr(levels.shape))
profile()
# Decide on maximum scaled value
if scale is None:
if lut is not None:
scale = lut.shape[0] - 1
else:
scale = 255.
# Decide on the dtype we want after scaling
if lut is None:
dtype = np.ubyte
else:
dtype = np.min_scalar_type(lut.shape[0] - 1)
# Apply levels if given
if levels is not None:
if isinstance(levels, np.ndarray) and levels.ndim == 2:
# we are going to rescale each channel independently
if levels.shape[0] != data.shape[-1]:
raise Exception(
"When rescaling multi-channel data, there must be the same number of levels as channels (data.shape[-1] == levels.shape[0])"
)
newData = np.empty(data.shape, dtype=int)
for i in range(data.shape[-1]):
minVal, maxVal = levels[i]
if minVal == maxVal:
maxVal += 1e-16
newData[..., i] = fn.rescaleData(data[..., i],
scale / (maxVal - minVal),
minVal,
dtype=dtype)
data = newData
else:
# Apply level scaling unless it would have no effect on the data
minVal, maxVal = levels
if minVal != 0 or maxVal != scale:
if minVal == maxVal:
maxVal += 1e-16
data = fn.rescaleData(data,
scale / (maxVal - minVal),
minVal,
dtype=dtype)
profile()
# apply LUT if given
if lut is not None:
data = fn.applyLookupTable(data, lut)
else:
if data.dtype is not np.ubyte:
data = np.clip(data, 0, 255).astype(np.ubyte)
#Set NaNs to transparent
data[nanlocations] = [0, 0, 0, 0]
profile()
# this will be the final image array
imgData = np.empty(data.shape[:2] + (4, ), dtype=np.ubyte)
profile()
# decide channel order
if useRGBA:
order = [0, 1, 2, 3] # array comes out RGBA
else:
order = [
2, 1, 0, 3
] # for some reason, the colors line up as BGR in the final image.
# copy data into image array
if data.ndim == 2:
# This is tempting:
# imgData[..., :3] = data[..., np.newaxis]
# ..but it turns out this is faster:
for i in range(3):
imgData[..., i] = data
elif data.shape[2] == 1:
for i in range(3):
imgData[..., i] = data[..., 0]
else:
for i in range(0, data.shape[2]):
imgData[..., i] = data[..., order[i]]
profile()
# add opaque alpha channel if needed
if data.ndim == 2 or data.shape[2] == 3:
alpha = False
imgData[..., 3] = 255
else:
alpha = True
profile()
return imgData, alpha
def render(self):
# Convert data to QImage for display.
profile = debug.Profiler()
if self.image is None or self.image.size == 0:
return
# Request a lookup table if this image has only one channel
if self.image.ndim == 2 or self.image.shape[2] == 1:
if isinstance(self.lut, Callable):
lut = self.lut(self.image)
else:
lut = self.lut
else:
lut = None
if self.autoDownsample:
# reduce dimensions of image based on screen resolution
o = self.mapToDevice(QtCore.QPointF(0, 0))
x = self.mapToDevice(QtCore.QPointF(1, 0))
y = self.mapToDevice(QtCore.QPointF(0, 1))
# Check if graphics view is too small to render anything
if o is None or x is None or y is None:
return
w = Point(x - o).length()
h = Point(y - o).length()
if w == 0 or h == 0:
self.qimage = None
return
xds = max(1, int(1.0 / w))
yds = max(1, int(1.0 / h))
axes = [1, 0] if self.axisOrder == 'row-major' else [0, 1]
image = fn.downsample(self.image, xds, axis=axes[0])
image = fn.downsample(image, yds, axis=axes[1])
self._lastDownsample = (xds, yds)
# Check if downsampling reduced the image size to zero due to inf values.
if image.size == 0:
return
else:
image = self.image
# if the image data is a small int, then we can combine levels + lut
# into a single lut for better performance
levels = self.levels
if levels is not None and levels.ndim == 1 and image.dtype in (
np.ubyte, np.uint16):
if self._effectiveLut is None:
eflsize = 2**(image.itemsize * 8)
ind = np.arange(eflsize)
minlev, maxlev = levels
levdiff = maxlev - minlev
levdiff = 1 if levdiff == 0 else levdiff # don't allow division by 0
if lut is None:
efflut = fn.rescaleData(ind,
scale=255. / levdiff,
offset=minlev,
dtype=np.ubyte)
else:
lutdtype = np.min_scalar_type(lut.shape[0] - 1)
efflut = fn.rescaleData(ind,
scale=(lut.shape[0] - 1) / levdiff,
offset=minlev,
dtype=lutdtype,
clip=(0, lut.shape[0] - 1))
efflut = lut[efflut]
self._effectiveLut = efflut
lut = self._effectiveLut
levels = None
# Convert single-channel image to 2D array
if image.ndim == 3 and image.shape[-1] == 1:
image = image[..., 0]
# Assume images are in column-major order for backward compatibility
# (most images are in row-major order)
if self.axisOrder == 'col-major':
image = image.transpose((1, 0, 2)[:image.ndim])
# Get bounds of view box
viewBounds = np.array(self.getViewBox().viewRange())
viewBounds[0][0] = max(viewBounds[0][0] - 1, 0)
viewBounds[0][1] = min(viewBounds[0][1] + 1, image.shape[1])
viewBounds[1][0] = max(viewBounds[1][0] - 1, 0)
viewBounds[1][1] = min(viewBounds[1][1] + 1, image.shape[0])
# Send image to ARGB worker
self.imageARGBWorker.prepareForNewImage(image, lut, levels, viewBounds,
self.onlyRenderVisible)
self.sigImageReadyForARGB.emit()
def render(self):
#The same as pyqtgraph's ImageItem.render, with the exception that the makeARGB function is slightly different
profile = debug.Profiler()
if self.image is None or self.image.size == 0:
return
if isinstance(self.lut, Callable):
lut = self.lut(self.image)
else:
lut = self.lut
if self.autoDownsample:
# reduce dimensions of image based on screen resolution
o = self.mapToDevice(QtCore.QPointF(0, 0))
x = self.mapToDevice(QtCore.QPointF(1, 0))
y = self.mapToDevice(QtCore.QPointF(0, 1))
w = Point(x - o).length()
h = Point(y - o).length()
if w == 0 or h == 0:
self.qimage = None
return
xds = max(1, int(1.0 / w))
yds = max(1, int(1.0 / h))
axes = [1, 0] if self.axisOrder == 'row-major' else [0, 1]
image = fn.downsample(self.image, xds, axis=axes[0])
image = fn.downsample(image, yds, axis=axes[1])
self._lastDownsample = (xds, yds)
else:
image = self.image
# if the image data is a small int, then we can combine levels + lut
# into a single lut for better performance
levels = self.levels
if levels is not None and levels.ndim == 1 and image.dtype in (
np.ubyte, np.uint16):
if self._effectiveLut is None:
eflsize = 2**(image.itemsize * 8)
ind = np.arange(eflsize)
minlev, maxlev = levels
levdiff = maxlev - minlev
levdiff = 1 if levdiff == 0 else levdiff # don't allow division by 0
if lut is None:
efflut = fn.rescaleData(ind,
scale=255. / levdiff,
offset=minlev,
dtype=np.ubyte)
else:
lutdtype = np.min_scalar_type(lut.shape[0] - 1)
efflut = fn.rescaleData(ind,
scale=(lut.shape[0] - 1) / levdiff,
offset=minlev,
dtype=lutdtype,
clip=(0, lut.shape[0] - 1))
efflut = lut[efflut]
self._effectiveLut = efflut
lut = self._effectiveLut
levels = None
# Assume images are in column-major order for backward compatibility
# (most images are in row-major order)
if self.axisOrder == 'col-major':
image = image.transpose((1, 0, 2)[:image.ndim])
argb, alpha = makeARGBwithNaNs(image, lut=lut, levels=levels)
self.qimage = fn.makeQImage(argb, alpha, transpose=False)
def render(self): # Convert data to QImage for display. profile = debug.Profiler() if self.image is None or self.image.size == 0: return # Request a lookup table if this image has only one channel if self.image.ndim == 2 or self.image.shape[2] == 1: if isinstance(self.lut, collections.Callable): lut = self.lut(self.image) else: lut = self.lut else: lut = None if self.autoDownsample: # reduce dimensions of image based on screen resolution o = self.mapToDevice(QtCore.QPointF(0,0)) x = self.mapToDevice(QtCore.QPointF(1,0)) y = self.mapToDevice(QtCore.QPointF(0,1)) w = Point(x-o).length() h = Point(y-o).length() if w == 0 or h == 0: self.qimage = None return xds = max(1, int(1.0 / w)) yds = max(1, int(1.0 / h)) axes = [1, 0] if self.axisOrder == 'row-major' else [0, 1] image = fn.downsample(self.image, xds, axis=axes[0]) image = fn.downsample(image, yds, axis=axes[1]) self._lastDownsample = (xds, yds) else: image = self.image # if the image data is a small int, then we can combine levels + lut # into a single lut for better performance levels = self.levels if levels is not None and levels.ndim == 1 and image.dtype in (np.ubyte, np.uint16): if self._effectiveLut is None: eflsize = 2**(image.itemsize*8) ind = np.arange(eflsize) minlev, maxlev = levels levdiff = maxlev - minlev levdiff = 1 if levdiff == 0 else levdiff # don't allow division by 0 if lut is None: efflut = fn.rescaleData(ind, scale=255./levdiff, offset=minlev, dtype=np.ubyte) else: lutdtype = np.min_scalar_type(lut.shape[0]-1) efflut = fn.rescaleData(ind, scale=(lut.shape[0]-1)/levdiff, offset=minlev, dtype=lutdtype, clip=(0, lut.shape[0]-1)) efflut = lut[efflut] self._effectiveLut = efflut lut = self._effectiveLut levels = None # Convert single-channel image to 2D array if image.ndim == 3 and image.shape[-1] == 1: image = image[..., 0] # Assume images are in column-major order for backward compatibility # (most images are in row-major order) if self.axisOrder == 'col-major': image = image.transpose((1, 0, 2)[:image.ndim]) argb, alpha = fn.makeARGB(image, lut=lut, levels=levels) if self.alpha is not None: argb[:,:,3] = self.alpha.T self.qimage = fn.makeQImage(argb, True, transpose=False)