```#!/usr/bin/env python
# vim: set fileencoding=utf-8 :
# Pavel Korshunov <pavel.korshunov@idiap.ch>
# Tue 17 May 15:43:22 CEST 2016

import numpy
import bob.io.base

from bob.bio.base_legacy.extractor import Extractor
import math

import logging

class Ratios(Extractor):
def __init__(self,
features_processor,  # another extractor that provides features for LBP computation
n_bands=5,
**kwargs
):
Extractor.__init__(self,
requires_training=False, split_training_data_by_client=False,
**kwargs)
self.n_bands = n_bands

assert isinstance(features_processor, bob.bio.base_legacy.extractor.Extractor), \
"Only feature processors derived from bob.bio.base_legacy.extractor.Extractor are supported in this class. "

self.features_processor = features_processor

[docs]    def compute_ratios(self, data):
# find the size of each band (a stip of features, for which we compute ratio)
band_length = int(math.floor(self.features_processor.n_filters / self.n_bands))
# compute ratio between the highest and the lowest band
lower_band = data[:, 0:band_length]
higher_band = data[:, -band_length:]
ratios = [numpy.mean(higher_band) / numpy.mean(lower_band)]
# compute ratio between the rest of the bands
if self.n_bands > 2:
for i in range(1, self.n_bands):
higher_band = data[:, i * band_length:(i + 1) * band_length]
ratios.append(numpy.mean(higher_band) / numpy.mean(lower_band))
lower_band = higher_band

ratios = numpy.asarray(ratios, dtype=numpy.float64)
return ratios

def __call__(self, input_data, annotations):
"""Use VAD to filter out useless energy bands"""

if self.features_processor is not None:
feature_bands = self.features_processor(input_data, annotations)
if feature_bands.any():
ratios = self.compute_ratios(feature_bands)
logger.info("- Extractions: computed ratios of size: %s ", str(ratios.shape))
return ratios

from .spectrogram_extended import SpectrogramExtended
extractor = Ratios(features_processor=SpectrogramExtended())
```