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.enhancer.clear() for channel, color in zip(channels, colors): self.enhancer.addChannel(cn.display(channel), color, no_auto_button=True)