def _process_recognition(self, node, extras): # Callback when command is spoken. windows = Window.get_all_windows() #windows.sort(key=lambda x: x.executable) for window in windows: if utils.windowIsValid(window): executable = unicode(window.executable, errors='ignore').lower() title = unicode(window.title, errors='ignore').lower() print "{:7} : {:75} : {}".format(window.handle, executable, title)
def _process_recognition(self, node, extras): # Callback when command is spoken. windows = Window.get_all_windows() #windows.sort(key=lambda x: x.executable) for window in windows: if utils.windowIsValid(window): print "{:7} : {:75} : {}".format( window.handle, window.executable.encode("utf-8"), window.title.encode("utf-8"))
def script(): X = in_data.X y = in_data.Y feat_names = [x.name for x in in_data.domain.attributes] new_feat_names = [x.split('=')[-1] for x in feat_names] print(feat_names) model_type = str(in_learners).split(',')[0].split('(')[0][1:] is_cont = in_data.domain.class_var.is_continuous class_type = 'regression' if is_cont else 'classification' class_names = in_data.domain.class_var.values if not is_cont else None shap_values = in_object biggest_val = np.amax(np.absolute(shap_values)) shap_values = shap_values / biggest_val xrange = (-1.1, 1.1) num_rows_2_sample = shap_values.shape[0] max_display = shap_values.shape[1] font_size = 13 idx = np.random.choice(list(range(shap_values.shape[0])), size=num_rows_2_sample, replace=False) shap_values = shap_values[idx, :] X = X[idx, :] if type(shap_values) == list: shap_values = shap_values[class_val] title = '{0} is {1}'.format(in_data.domain.class_var.name, class_names[class_val]) else: title = in_data.domain.class_var.name id = len(Window.get_all_windows()) summary_plot(shap_values, features=X, feature_names=feat_names, class_names=class_names, max_display=max_display, plot_type='bar', color='black', id=id, xrange=xrange) summary_plot(shap_values, features=X, feature_names=feat_names, class_names=class_names, max_display=max_display, plot_type='dot', title=title, id=id, xrange=xrange) return None, None, None, None
def get_default_window(name): executable, title = default_names[name] if executable: executable = executable.lower() if title: title = title.lower() windows = Window.get_all_windows() for window in windows: if not window.is_visible: continue elif executable and window.executable.lower().find(executable) == -1: continue elif title and window.title.lower().find(title) == -1: continue window.name = name win_names[name] = window return window return None
def clear_log(): # Function to clear natlink status window try: # pylint: disable=import-error import natlink windows = Window.get_all_windows() matching = [ w for w in windows if b"Messages from Python Macros" in w.title ] if matching: handle = (matching[0].handle) rt_handle = win32gui.FindWindowEx(handle, None, "RICHEDIT", None) win32gui.SetWindowText(rt_handle, "") return except Exception as e: print(e)
from dragonfly import Window print(Window.get_all_windows())
def move_desktop_to(n): for window in Window.get_all_windows(): if vda.IsWindowOnCurrentVirtualDesktop(window.handle): vda.MoveWindowToDesktopNumber(window.handle, n - 1)