def calculate(self, pcm_data): sample_pack_size = 1024 pcm_mono = pcm.into_mono(pcm_data) pcm_sample_packs = pcm.to_sample_packs(pcm_mono, sample_pack_size) centroids = [] for sample_pack in pcm_sample_packs: centroids.append(pcm.centroid(sample_pack)) centroid_avg = stats.average(centroids) return centroid_avg
def calculate(self, pcm_data): sample_pack_size = 1024 pcm_mono = pcm.into_mono(pcm_data) pcm_sample_packs = pcm.to_sample_packs(pcm_mono, sample_pack_size) rolloffs = [] for sample_pack in pcm_sample_packs: rolloffs.append(pcm.roll_off(sample_pack)) rolloff = stats.average(rolloffs) return rolloff
def calculate(self, pcm_data): sample_pack_size = 1024 pcm_mono = pcm.into_mono(pcm_data) pcm_sample_packs = pcm.to_sample_packs(pcm_mono, sample_pack_size) fluxes = [] for i in range(1, len(pcm_sample_packs)): fluxes.append(pcm.spectral_flux(pcm_sample_packs[i - 1], pcm_sample_packs[i])) fluxes_sd = stats.average(fluxes) return fluxes_sd