def findPhase(signal: Signal, grid: Signal, period: int, toleranceWindow=0):
"""
find the phase of the signal based on it's amplitude at the grid positions and the number of peaks
- signal: works best with a discrete signal as no aglomeration is done
- grid: positions of the beats
- period: the periodicity to test
- tolerance window: if not at 0, returns the closest value in the signal to the grid, within the tolerance window
test:
# result = findPhase(Signal(np.ones(5), times=np.array([0, 4, 8, 9, 12])+1), Signal(np.ones(16), times=range(16)), period=4)
# print(result) = 1
"""
phases = []
for phase in range(period):
values = [signal.getValue(grid.times[i], toleranceWindow=0) for i in range(phase, len(grid), period)]
phases.append((np.sum([v for v in values if v is not None]) * len(values)))
bestPhase = np.argmax(phases)
return bestPhase
def findPhaseLocal(self,
period: int,
signal: Signal,
grid: Signal,
toleranceWindow=0.1):
"""
find the phase of the signal based on it's amplitude at the grid positions and the number of peaks
- signal: works best with a discrete signal as no aglomeration is done
- grid: positions of the beats
- period: the periodicity to test
- tolerance window: if not at 0, returns the closest value in the signal to the grid, within the tolerance window
test:
# result = findPhase(Signal(np.ones(5), times=np.array([0, 4, 8, 9, 12])+1), Signal(np.ones(16), times=range(16)),
period=4)
# print(result) = 1
"""
phases = []
for phase in range(period):
values = [
signal.getValue(grid.times[i], toleranceWindow=toleranceWindow)
for i in range(phase, len(grid), period)
]
values = [v for v in values if v is not None]
if self.parameters["distanceMetric"].value == "RMS":
value = np.sqrt(np.mean(np.array(values)**2))
elif self.parameters["distanceMetric"].value == "sum":
value = np.sum(values)
elif self.parameters["distanceMetric"].value == "Veire":
value = np.sum(values) * len(values)
else:
raise Exception("Bad distance metric parameter" +
self.parameters["distanceMetric"].value)
phases.append(value)
# bestPhase = np.argmax(phases)
return phases