binary_io.py

################################################################################
#           The Neural Network (NN) based Speech Synthesis System
#                https://svn.ecdf.ed.ac.uk/repo/inf/dnn_tts/
#                
#                Centre for Speech Technology Research                 
#                     University of Edinburgh, UK                       
#                      Copyright (c) 2014-2015
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################################################################################



import numpy

class   BinaryIOCollection(object):

    def load_binary_file(self, file_name, dimension):
        fid_lab = open(file_name, 'rb')
        features = numpy.fromfile(fid_lab, dtype=numpy.float32)
        fid_lab.close()
        assert features.size % float(dimension) == 0.0,'specified dimension %s not compatible with data'%(dimension)
        features = features[:(dimension * (features.size / dimension))]
        features = features.reshape((-1, dimension))
            
        return  features

    def array_to_binary_file(self, data, output_file_name):
        data = numpy.array(data, 'float32')
               
        fid = open(output_file_name, 'wb')
        data.tofile(fid)
        fid.close()

    def load_binary_file_frame(self, file_name, dimension):
        fid_lab = open(file_name, 'rb')
        features = numpy.fromfile(fid_lab, dtype=numpy.float32)
        fid_lab.close()
        assert features.size % float(dimension) == 0.0,'specified dimension %s not compatible with data'%(dimension)
        frame_number = features.size / dimension
        features = features[:(dimension * frame_number)]
        features = features.reshape((-1, dimension))
            
        return  features, frame_number