我们从Python开源项目中，提取了以下9个代码示例，用于说明如何使用ipywidgets.interact()。
def plot_grid_scores(self, x, hue=None, row=None, col=None, col_wrap=None, **kwargs): def none_if_none(x): return None if x == 'None' else x if has_widgets: choices = ['None'] + list(unpack_grid_scores(self.model) .columns.drop(['mean_', 'std_'])) @interact(x=choices, hue=choices, row=choices, col=choices) def wrapper(x=x, hue=None, row=None, col=None): return plot_grid_scores(self.model, none_if_none(x), 'mean_', hue=none_if_none(hue), row=none_if_none(row), col=none_if_none(col), col_wrap=none_if_none(col_wrap), **kwargs) return wrapper else: return plot_grid_scores(self.model, x, 'mean_', hue=hue, row=row, col=col, col_wrap=col_wrap, **kwargs)
def __init__(self, loopFunc, **kw): self.thread = None self.loopFunc = loopFunc ipywidgets.interact(self.toggler, x=ipywidgets.ToggleButton(**kw))
def __init__(self, gimbal): self.gimbal = gimbal ipywidgets.interact(self.fn, x=ipywidgets.ToggleButton(description='Motor Enable'))
def __init__(self, gimbal, number, axes=range(3), min=-0x8000, max=0x7fff, step=1): self.gimbal = gimbal self.number = number self.axes = axes self.widgets = [None] * 3 ThreadToggle(self._update, description='Refresh param %02x' % number) for t in self.axes: v = self.gimbal.getParam(number=number, target=t) self.widgets[t] = ipywidgets.IntSlider(description='Param %02x t=%d' % (self.number, t), value=v, min=min, max=max, step=step,layout=dict(width='100%')) ipywidgets.interact(self._set, x=self.widgets[t], target=ipywidgets.fixed(t))
def __init__(self, gimbal): self.gimbal = gimbal self.controlPacket = None xw = ipywidgets.IntSlider(value=0, min=-0x8000, max=0x7fff, step=1, layout=dict(width='100%')) yw = ipywidgets.IntSlider(value=0, min=-0x8000, max=0x7fff, step=1, layout=dict(width='100%')) zw = ipywidgets.IntSlider(value=0, min=-0x8000, max=0x7fff, step=1, layout=dict(width='100%')) mw = ipywidgets.IntSlider(value=1, min=0, max=255, step=1, layout=dict(width='100%')) ipywidgets.interact(self.setFn, x=xw, y=yw, z=zw, m=mw) ThreadToggle(self.loopFn, description='Controller thread') self.rate = ipywidgets.IntSlider(description='Update rate', value=25, min=1, max=400, step=1, layout=dict(width='100%')) display(self.rate)
def type_and_vis(self): def input_box(tweet, grads, activations, over_words, over_units): self.vis_activation([tweet], grads, activations, over_words, over_units) return interact(input_box, tweet='This is a great tool', grads=False, activations=True, over_words=True, over_units=False)
def plot(self, vis_func, img_path, label_list, figsize): img = utils.load_img(img_path, target_size=self.img_shape_) img = img[:,:,:3] predictions = self.model_.predict(img2tensor(img, self.img_shape_)) predictions = softmax(predictions) if not label_list: prediction_text = decode_predictions(predictions)[0] def _plot(label_id): label_id = int(label_id) text_label = get_pred_text_label(label_id) label_proba = np.round(predictions[0,label_id], 4) heatmap = vis_func(img, label_id) for p in prediction_text: print(p[1:]) plt.figure(figsize=figsize) plt.subplot(1,2,1) plt.title('label:%s\nscore:%s'%(text_label,label_proba)) plt.imshow(overlay(heatmap, img)) plt.subplot(1,2,2) plt.imshow(img) plt.show() else: def _plot(label_id): print(pd.DataFrame(predictions, columns=label_list)) label_id = int(label_id) text_label = label_list[label_id] label_proba = np.round(predictions[0,label_id], 4) heatmap = vis_func(img,label_id) plt.figure(figsize=figsize) plt.subplot(1,2,1) plt.title('label:%s\nscore:%s'%(text_label,label_proba)) plt.imshow(overlay(heatmap, img)) plt.subplot(1,2,2) plt.imshow(img) plt.show() return interact(_plot, label_id='1')
def browse(self, figsize=(16,10), labels=None): def plot(layer_id, filter_id): filepath = '{}/{}/{}/img.jpg'.format(self.save_dir_, layer_id, filter_id) img = plt.imread(filepath) plt.figure(figsize=figsize) if labels: plt.title('Label: {}'.format(labels[int(filter_id)])) plt.imshow(img) plt.show() return interact(plot, layer_id='1',filter_id='0')
def browse_layer(self, batch_size=25, cols=5): def plot(layer_id, batch_id): plt.figure(figsize=(14,20)) all_files = sorted(os.listdir('{}/{}'.format(self.save_dir_, layer_id))) batch_id = int(batch_id) img_list, label_list = [],[] for f in all_files[batch_id*batch_size:(batch_id+1)*batch_size]: img_path = os.path.join(self.save_dir_, layer_id, f, 'img.jpg') img = plt.imread(img_path) img_list.append(img) label_list.append(f) plot_list(img_list, label_list, cols_nr=cols) return interact(plot, layer_id='17',batch_id='6')
