async def coro_preprocess_selected_signal(self) -> List[ndarray]:
sig = self.get_selected_signal()
if not self.preproc_mp_handler:
self.preproc_mp_handler = MPHandler()
return await self.preproc_mp_handler.coro_preprocess(sig, None, None)
async def coro_preprocess_selected_signal(self) -> List[ndarray]:
"""
Coroutine to preprocess the currently selected signal.
:return: the preprocessed signal as a 1D array
"""
sig = self.get_selected_signal()
fmin = self.view.get_fmin()
fmax = self.view.get_fmax()
if not self.preproc_mp_handler:
self.preproc_mp_handler = MPHandler()
return await self.preproc_mp_handler.coro_preprocess(sig, fmin, fmax)
async def coro_plot_preprocessed_signal(self) -> None:
"""
Coroutine to preprocess the signal and plot the result.
"""
sig = self.get_selected_signal()
fmin = self.view.get_fmin()
fmax = self.view.get_fmax()
if not self.preproc_mp_handler:
self.preproc_mp_handler = MPHandler()
result = await self.preproc_mp_handler.coro_preprocess(sig, fmin, fmax)
if result and result[0] is not None:
self.view.plot_preprocessed_signal(sig.times, sig.signal, result[0])
async def coro_preprocess_all_signals(self) -> List[ndarray]:
"""
Coroutine to preprocess all signals.
:return: a list containing the preprocessed signals as a 1D array each
"""
signals = self.signals
try:
fmin = self.view.get_fmin()
fmax = self.view.get_fmax()
except AttributeError:
fmin, fmax = None, None
if not self.preproc_mp_handler:
self.preproc_mp_handler = MPHandler()
return await self.preproc_mp_handler.coro_preprocess(signals, fmin, fmax)
async def coro_calculate(self, calculate_all: bool) -> None:
self.view.enable_save_data(False)
self.is_calculating_all = calculate_all
if self.mp_handler:
self.mp_handler.stop()
self.is_plotted = False
self.invalidate_data()
self.view.main_plot().clear()
self.view.main_plot().set_in_progress(True)
self.view.amplitude_plot().clear()
self.view.amplitude_plot().set_in_progress(True)
params = self.get_params(all_signals=calculate_all)
self.params = params
self.surrogate_count = self.view.get_surr_count()
self.surrogates_enabled = self.view.get_surr_enabled()
self.mp_handler = MPHandler()
self.view.main_plot().set_log_scale(logarithmic=True)
self.view.amplitude_plot().set_log_scale(logarithmic=True)
self.view.on_calculate_started()
data = await self.mp_handler.coro_transform(
params=params, on_progress=self.on_progress_updated)
for d in data:
self.on_transform_completed(*d)
all_data = await self.coro_phase_coherence(self.signals_calc, params,
self.on_progress_updated)
for d in all_data:
self.on_phase_coherence_completed(*d)
self.plot_phase_coherence()
self.view.on_calculate_stopped()
self.on_all_tasks_completed()
print("Finished calculating phase coherence.")
async def coro_calculate(self):
if self.mp_handler:
self.mp_handler.stop()
self.mp_handler = MPHandler()
data = await self.mp_handler.coro_bayesian(self.signals,
self.get_paramsets(),
self.on_progress_updated)
for d in data:
self.on_bayesian_inference_completed(*d)
if data:
self.plot_bayesian()
else:
print("No data returned; are any parameter sets added?")
print("Dynamical Bayesian inference completed.")
self.view.on_calculate_stopped()
async def coro_calculate(self, calculate_all: bool) -> None:
"""
Coroutine to perform the calculation.
:param calculate_all: whether to calculate for all signals, or just the current signal
"""
self.is_calculating_all = calculate_all
self.view.enable_save_data(False)
for s in self.signals:
s.data = None
if self.mp_handler:
self.mp_handler.stop()
self.mp_handler = MPHandler()
params = self.get_params(all_signals=calculate_all)
self.params = params
self.params.preprocess = self.view.get_preprocess()
self.is_plotted = False
self.view.main_plot().clear()
self.invalidate_data()
self.view.main_plot().set_log_scale(logarithmic=True)
self.view.on_calculate_started()
all_data = await self.mp_handler.coro_harmonics(
self.signals_calc, params, self.params.preprocess,
self.on_progress_updated)
if not isinstance(all_data, List):
all_data = [all_data]
for signal, data in zip(self.signals_calc, all_data):
signal.data = data
self.view.enable_save_data(bool(all_data))
self.view.on_calculate_stopped()
self.update_plots()