class InteractiveImagePlot(ImageView):
""" Allows to draw 2d numpy array in an interactive plot using a colormap"""
def __init__(self,
model,
video_model=None,
parent=None,
colormap="inferno"):
""" Sets the datamodel and optionally a videomodel that is used to print a time indicator according to its current frameself.
Args:
model: DataModel wrapping either 1d or 2d data
video_model: VideoModel wrapping a video file
parent: Parent QtWidget
colormap: String describing matplotlib colormap
"""
self.view = PlotItem()
super().__init__(view=self.view)
self.model = model
self.video_model = video_model
self.print_indicator = False
self.indicator = None
# Get a colormap
colormap = plt.cm.get_cmap(
colormap) # cm.get_cmap("CMRmap")nipy_spectral
colormap._init()
self.lut = (colormap._lut * 255).view(
np.ndarray
) # Convert matplotlib colormap from 0-1 to 0 -255 for Qt
self.ui.histogram.hide()
self.ui.roiBtn.hide()
self.ui.menuBtn.hide()
initial_data = self.model.get_data()
if not isinstance(initial_data,
type(None)): #Draw imagedata if possible
try:
self.print_data(initial_data)
except: #It might be that the model contains data that is not displayable e.g. 1d
pass
def print_data(self, data):
""" Prints data to dataplot
Args:
data: 2d float.64 numpy arrays containing values between 0 and 1
"""
self.print_indicator = True
self.imagedata = data
self.setImage(self.imagedata)
self.indicator_min = -200
self.indicator_max = 200
if self.video_model != None:
pos = int(self.video_model.get_pos(datatype="motion"))
self.indicator = self.view.plot(
[pos, pos], [self.indicator_min, self.indicator_max],
pen=pyqtgraph.mkPen(color=pyqtgraph.hsvColor(2), width=1))
def update(self, pos):
""" Updates indicator position
Args:
pos: Int describing the current position of the indicator
"""
if self.print_indicator and self.indicator and not self.video_model == None:
C = pyqtgraph.hsvColor(1)
pen = pyqtgraph.mkPen(color=C, width=1)
pos = int(
self.video_model.get_pos(datatype=self.model.get_datatype()))
self.indicator.setData([pos, pos],
[self.indicator_min, self.indicator_max])
def updateImage(self, autoHistogramRange=True):
""" Updates the image, setting the colormap"""
super().updateImage(autoHistogramRange=autoHistogramRange)
self.getImageItem().setLookupTable(self.lut)
def setImage(self, *args, **kwargs):
""" Sets the image and adjusts the initial view/zoom in the plot"""
super().setImage(*args, **kwargs)
self.view.disableAutoRange(axis=0)
self.view.enableAutoRange(axis=1)
