def __init__(self, items, indices, classes, title="", exclude_training_data=True, *args, **kw):
super(BoxPlot, self).__init__(*args, **kw)
loadUI(splitext(__file__)[0]+'.ui', self)
self.setWindowTitle(title)
self._exclude_td = exclude_training_data
self._tabs = dict()
self._items = items
values = lambda: defaultdict(list)
data = defaultdict(values)
for ch, idx in indices.iteritems():
for item in self._items:
if self._exclude_td and item.isTrainingSample():
continue
value = item.features[idx]
data[item.treatment][item.class_.name].append(value)
self._plot(cn.from_abreviation(ch), title, data, classes)
def setChannelNames(self, channels, colors):
self.colors = colors
self.enhancer.clear()
for channel in channels:
self.enhancer.addChannel(cn.display(channel), no_auto_button=True)
def setChannelNames(self, channels, colors):
self.colors = colors
self.enhancer.clear()
for channel in channels:
self.enhancer.addChannel(cn.display(channel), no_auto_button=True)
def setChannelNames(self, channels, colors):
self.enhancer.clear()
for channel, color in zip(channels, colors):
self.enhancer.addChannel(cn.display(channel), color,
no_auto_button=True)
