def minimize_window():
'''
Minimize foreground Window
'''
global lasthandle
lasthandle = Window.get_foreground()
Window.get_foreground().minimize()
def restore_window():
'''
Restores last minimized window triggered minimize_window.
'''
global lasthandle
if lasthandle is None:
printer.out("No previous window minimized by voice")
else:
Window.restore(lasthandle)
def get_active_explorer(self):
handle = Window.get_foreground().handle
for window in collection_iter(self.application.Windows()):
if window.HWND == handle:
return window
self._log.warning("%s: no active explorer." % self)
return None
def value(self, node):
if node.has_child_with_name("win_names"):
window = node.get_child_by_name("win_names").value()
if not isinstance(window, Window):
window = get_default_window(window)
return window
return Window.get_foreground()
def focus_mousegrid(gridtitle):
'''
Loops over active windows for MouseGrid window titles. Issue #171
When MouseGrid window titles found focuses MouseGrid overly.
'''
if sys.platform.startswith('win'):
# May not be needed for Linux/Mac OS - testing required
try:
for i in range(9):
matches = Window.get_matching_windows(title=gridtitle,
executable="python")
if not matches:
Pause("50").execute()
else:
break
if matches:
for handle in matches:
handle.set_foreground()
break
else:
printer.out(
"`Title: `{}` no matching windows found".format(gridtitle))
except Exception as e:
printer.out("Error focusing MouseGrid: {}".format(e))
else:
pass
def mimic(self, words):
""" Mimic a recognition of the given *words*. """
# Handle string input.
if isinstance(words, string_types):
words = words.split()
# Don't allow non-iterable objects.
if not iter(words):
raise TypeError("%r is not a string or other iterable object" %
words)
# Notify observers that a recognition has begun.
self._recognition_observer_manager.notify_begin()
# Generate the input for process_words.
words_rules = self.generate_words_rules(words)
# Call process_begin and process_words for all grammar wrappers,
# stopping early if processing occurred.
fg_window = Window.get_foreground()
processing_occurred = False
for wrapper in self._grammar_wrappers.values():
wrapper.process_begin(fg_window)
processing_occurred = wrapper.process_words(words_rules)
if processing_occurred:
break
# If no processing occurred, then the mimic failed.
if not processing_occurred:
self._recognition_observer_manager.notify_failure()
raise MimicFailure("No matching rule found for words %r." %
(words, ))
def _speech_start_callback(self, mimicking):
# Get context info.
fg_window = Window.get_foreground()
window_info = {
"executable": fg_window.executable,
"title": fg_window.title,
"handle": fg_window.handle,
}
# Call process_begin for all grammars so that any out of context
# grammar will not be used.
for wrapper in self._grammar_wrappers.copy().values():
wrapper.process_begin(**window_info)
if not mimicking:
# Trim excess audio buffers from the start of the list. Keep a maximum 1
# second of silence before speech start was detected. This should help
# increase the performance of batch reprocessing later.
chunk = self.config.FRAMES_PER_BUFFER
rate = self.config.RATE
seconds = 1
n_buffers = int(rate / chunk * seconds)
self._audio_buffers = self._audio_buffers[-1 * n_buffers:]
# Notify observers
self._recognition_observer_manager.notify_begin()
def get_window_by_title(title=None):
# returns 0 if nothing found
Matches = Window.get_matching_windows(title=title)
if Matches:
return Matches[0].handle
else:
return 0
def _process_recognition(self, node, extras):
name = str(extras["name"])
window = Window.get_foreground()
window.name = name
window_names[name] = window
self._log.debug("%s: named foreground window '%s'." %
(self, window))
def disconnect(self):
""" Disconnect from natlink. """
# Unload all grammars from the engine so that Dragon doesn't keep
# recognizing them.
for grammar in self.grammars:
grammar.unload()
# Close the the waitForSpeech() dialog box if it is active.
from dragonfly import Window
target_title = "Natlink / Python Subsystem"
for window in Window.get_matching_windows(title=target_title):
if window.is_visible:
try:
window.close()
except pywintypes.error:
pass
break
# Stop the special timer thread if it is running.
if self._timer_thread:
self._timer_thread.stop()
self._timer_thread = None
# Finally disconnect from natlink.
self.natlink.natDisconnect()
def value(self, node):
if node.has_child_with_name("win_names"):
window = node.get_child_by_name("win_names").value()
if not isinstance(window, Window):
window = get_default_window(window)
return window
return Window.get_foreground()
def get_active_explorer(self):
handle = Window.get_foreground().handle
for window in collection_iter(self.application.Windows()):
if window.HWND == handle:
return window
self._log.warning("%s: no active explorer." % self)
return None
def mimic(self, words):
""" Mimic a recognition of the given *words*. """
# Handle string input.
if isinstance(words, string_types):
words = words.split()
# Don't allow non-iterable objects.
if not iter(words):
raise TypeError("%r is not a string or other iterable object"
% words)
# Notify observers that a recognition has begun.
self._recognition_observer_manager.notify_begin()
# Generate the input for process_words.
words_rules = self.generate_words_rules(words)
# Call process_begin and process_words for all grammar wrappers,
# stopping early if processing occurred.
fg_window = Window.get_foreground()
processing_occurred = False
for wrapper in self._grammar_wrappers.values():
wrapper.process_begin(fg_window)
processing_occurred = wrapper.process_words(words_rules)
if processing_occurred:
break
# If no processing occurred, then the mimic failed.
if not processing_occurred:
self._recognition_observer_manager.notify_failure()
raise MimicFailure("No matching rule found for words %r."
% (words,))
def mimic(self, words, **kwargs):
""" Mimic a recognition of the given *words*. """
# Handle string input.
if isinstance(words, string_types):
words = words.split()
# Don't allow non-iterable objects.
if not iter(words):
raise TypeError("%r is not a string or other iterable object" %
words)
# Notify observers that a recognition has begun.
self._recognition_observer_manager.notify_begin()
# Generate the input for process_words.
words_rules = self.generate_words_rules(words)
w = Window.get_foreground()
process_args = {
"executable": w.executable,
"title": w.title,
"handle": w.handle,
}
# Allows optional passing of window attributes to mimic
process_args.update(kwargs)
# Call process_begin() for each grammar wrapper. Use a copy of
# _grammar_wrappers in case it changes.
for wrapper in self._grammar_wrappers.copy().values():
wrapper.process_begin(**process_args)
# Take another copy of _grammar_wrappers to use for processing.
grammar_wrappers = self._grammar_wrappers.copy().values()
# Count exclusive grammars.
exclusive_count = 0
for wrapper in grammar_wrappers:
if wrapper.exclusive:
exclusive_count += 1
# Call process_words() for each grammar wrapper, stopping early if
# processing occurred.
processing_occurred = False
for wrapper in grammar_wrappers:
# Skip non-exclusive grammars if there are one or more exclusive
# grammars.
if exclusive_count > 0 and not wrapper.exclusive:
continue
# Process the grammar.
processing_occurred = wrapper.process_words(words_rules)
if processing_occurred:
break
# If no processing occurred, then the mimic failed.
if not processing_occurred:
self._recognition_observer_manager.notify_failure()
raise MimicFailure("No matching rule found for words %r." %
(words, ))
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 paste_command():
# Add Command Prompt, putty, ...?
context = AppContext(executable="console")
window = Window.get_foreground()
if context.matches(window.executable, window.title, window.handle):
return
release.execute()
Key("c-v/3").execute()
def move_current_to_new(follow=False):
wndh = Window.get_foreground().handle
current = vda.GetCurrentDesktopNumber()
total = vda.GetDesktopCount()
Key("wc-d").execute()
vda.MoveWindowToDesktopNumber(wndh, total)
if not follow:
vda.GoToDesktopNumber(current)
def get_application():
window = Window.get_foreground()
# Check all contexts. Return the name of the first one that matches or
# "standard" if none matched.
for name, context in contexts.items():
if context.matches(window.executable, window.title, window.handle):
return name
return "standard"
def paste_command():
# Add Command Prompt, putty, ...?
context = AppContext(executable="console")
window = Window.get_foreground()
if context.matches(window.executable, window.title, window.handle):
return
release.execute()
Key("c-v/3").execute()
def reload_natlink():
"""Reloads Natlink and custom Python modules."""
win = Window.get_foreground()
FocusWindow(executable="natspeak",
title="Messages from Python Macros").execute()
Pause("10").execute()
Key("a-f, r").execute()
Pause("10").execute()
win.set_foreground()
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 reload_natlink():
"""Reloads Natlink and custom Python modules."""
win = Window.get_foreground()
FocusWindow(executable="natspeak",
title="Messages from Python Macros").execute()
Pause("10").execute()
Key("a-f, r").execute()
Pause("10").execute()
win.set_foreground()
def get_active_window_info():
'''Returns foreground window executable_file, executable_path, title, handle, classname'''
FILENAME_PATTERN = re.compile(r"[/\\]([\w_ ]+\.[\w]+)")
window = Window.get_foreground()
executable_path = str(Path(get_active_window_path()))
match_object = FILENAME_PATTERN.findall(window.executable)
executable_file = None
if len(match_object) > 0:
executable_file = match_object[0]
return [executable_file, executable_path, window.title, window.handle, window.classname]
def check_context(self):
if natlink.getMicState() == "on":
w = Window.get_foreground()
should_be_command = self.command_contexts.matches(w.executable, w.title, w.handle)
if should_be_command and self.mode == "normal":
self.switch_mode("command")
elif not should_be_command and self.mode == "command":
self.switch_mode("normal")
else:
pass
def callback(hWinEventHook, event, hwnd, idObject, idChild, dwEventThread,
dwmsEventTime):
window = Window.get_foreground()
if hwnd == window.handle:
for grammar in engine.grammars:
# Prevent 'notify_begin()' from being called.
if grammar.name == "_recobs_grammar":
continue
grammar.process_begin(window.executable, window.title,
window.handle)
def _process_recognition(self, node, extras):
# Find a notepad window, set it as the target window and move it.
# Display a warning if no notepad window was found.
notepad_windows = Window.get_matching_windows(executable="notepad",
title="notepad")
if not notepad_windows:
print("Could not find a notepad window to move.")
return
self.window_movement.target_window = notepad_windows[0]
self.move_target_window(extras)
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 on_begin(self):
window = Window.get_foreground()
if self.is_dynamic_active and not self.context.is_dynamic_active(
window.executable, window.title, window.handle):
self.is_dynamic_active = False
self.states_to_restore_on_window_focus = self.get_current_grammar_states(
)
self.set_current_grammar_states(self.static_grammar_states)
elif not self.is_dynamic_active and self.context.is_dynamic_active(
window.executable, window.title, window.handle):
self.is_dynamic_active = True
self.static_grammar_states = self.get_current_grammar_states()
self.set_current_grammar_states(
self.states_to_restore_on_window_focus)
def ensure_execution_context(data):
'''Populates the data field of execute with context information if not
present.'''
if data is None:
data = {}
if '_proxy' not in data:
data['_proxy'] = aenea.config.proxy_active()
if '_server_info' not in data:
data['_server_info'] = aenea.proxy_contexts._server_info()
if '_proxy_context' not in data:
data['_proxy_context'] = aenea.proxy_contexts._get_context()
if '_context' not in data:
data['_context'] = Window.get_foreground()
return data
def ensure_execution_context(data):
'''Populates the data field of execute with context information if not
present.'''
if data is None:
data = {}
if '_proxy' not in data:
data['_proxy'] = aenea.config.proxy_active()
if '_server_info' not in data:
data['_server_info'] = aenea.proxy_contexts._server_info()
if '_proxy_context' not in data:
data['_proxy_context'] = aenea.proxy_contexts._get_context()
if '_context' not in data:
data['_context'] = Window.get_foreground()
return data
def do_scratch_n_times(self, n):
for _ in range(n):
try:
# Get the number of characters to delete from the current
# window's stack. Discard the state flags.
scratch_number, _ = self._get_window_stack().pop()
Key("backspace:%d" % scratch_number).execute()
except IndexError:
handle = self._current_window_handle
window = Window.get_window(handle)
exe = os.path.basename(window.executable)
title = window.title
print("Nothing in scratch memory for %r window "
"(title=%r, id=%d)" % (exe, title, handle))
break
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 process_begin(self):
"""
Start the dragonfly grammar processing.
"""
# Get context info for the process_begin method. Dragonfly has a handy
# static method for this:
fg_window = Window.get_foreground()
if sys.platform.startswith("win"):
process_method = self.grammar.process_begin
else:
# Note: get_foreground() is mocked for non-Windows platforms
# TODO Change to process_begin once cross platform contexts are working
process_method = self.grammar._process_begin
# Call the process begin method
process_method(fg_window.executable, fg_window.title, fg_window.handle)
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)
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 _speech_start_callback(self, mimicking):
# Get context info. Dragonfly has a handy static method for this:
fg_window = Window.get_foreground()
# Call process_begin for all grammars so that any out of context
# grammar will not be used.
for wrapper in self._grammar_wrappers.values():
wrapper.process_begin(fg_window)
if not mimicking:
# Trim excess audio buffers from the start of the list. Keep a maximum 1
# second of silence before speech start was detected. This should help
# increase the performance of batch reprocessing later.
chunk = self.config.FRAMES_PER_BUFFER
rate = self.config.RATE
seconds = 1
n_buffers = int(rate / chunk * seconds)
self._audio_buffers = self._audio_buffers[-1 * n_buffers:]
# Notify observers
self._recognition_observer_manager.notify_begin()
def callback(hWinEventHook, event, hwnd, idObject, idChild, dwEventThread, dwmsEventTime):
window = Window.get_foreground()
if hwnd == window.handle:
engine.window_change(window.executable, window.title, window.handle)
def blitz_natlink_status():
win = Window.get_foreground()
FocusWindow(executable="natspeak", title="Messages from NatLink").execute()
Pause("100").execute()
win.set_foreground()
def minimize_window():
'''
Minimize foreground Window
'''
Window.get_foreground().minimize()
def maximize_window():
'''
Maximize foreground Window
'''
Window.get_foreground().maximize()
def _process_recognition(self, node, extras):
name = str(extras["name"])
window = Window.get_foreground()
window.name = name
win_names[name] = window
self._log.debug("%s: named foreground window '%s'." % (self, window))