def edit_with_default_desc(self, unmixed_track): selected_tracks = [unmixed_track[i] for i in self.targets_index] linear_sum = np.sum(unmixed_track, axis=0) manipulated_linear_sum = np.sum(selected_tracks, axis=0) linear_sum, manipulated_linear_sum = normalize(linear_sum, manipulated_linear_sum) return self.gen_desc_default(), linear_sum, manipulated_linear_sum
def __edit__(self, unmixed_track: np.ndarray): manipulated_track = np.copy(unmixed_track) for idx in self.targets_index: manipulated_track[idx] = self.snd_fx(manipulated_track[idx]) linear_sum = np.sum(unmixed_track, axis=0) manipulated_linear_sum = np.sum(manipulated_track, axis=0) linear_sum, manipulated_linear_sum = normalize(linear_sum, manipulated_linear_sum) return linear_sum, manipulated_linear_sum
def edit_with_default_desc(self, unmixed_track): manipulated_track = np.copy(unmixed_track) for idx in self.targets_index: manipulated_track[idx] *= .5 linear_sum = np.sum(unmixed_track, axis=0) manipulated_linear_sum = np.sum(manipulated_track, axis=0) linear_sum, manipulated_linear_sum = normalize(linear_sum, manipulated_linear_sum) return self.gen_desc_default(), linear_sum, manipulated_linear_sum
def edit_with_default_desc(self, unmixed_track): manipulated_track = np.copy(unmixed_track) for idx in self.targets_index: mean = manipulated_track[idx].mean(axis=-1) manipulated_track[idx, :, 0] = mean * 1.0 manipulated_track[idx, :, 1] = mean * 0.0 linear_sum = np.sum(unmixed_track, axis=0) manipulated_linear_sum = np.sum(manipulated_track, axis=0) linear_sum, manipulated_linear_sum = normalize(linear_sum, manipulated_linear_sum) return self.gen_desc_default(), linear_sum, manipulated_linear_sum
def edit_with_default_desc(self, unmixed_track): manipulated_track = np.copy(unmixed_track) for idx in range(3): if idx in self.targets_index: # unmixed_track[idx] = self.snd_fx(unmixed_track[idx]) # else: manipulated_track[idx] = self.snd_fx(manipulated_track[idx]) # unmixed_track[idx] = self.snd_fx(unmixed_track[idx]) linear_sum = np.sum(unmixed_track, axis=0) manipulated_linear_sum = np.sum(manipulated_track, axis=0) linear_sum, manipulated_linear_sum = normalize(linear_sum, manipulated_linear_sum) return self.gen_desc_default(), manipulated_linear_sum, linear_sum