Core

AnalyzerResult

class timeside.core.analyzer.AnalyzerResult(data_mode='value', time_mode='framewise')

Bases: timeside.core.analyzer.MetadataObject

Object that contains the metadata and parameters of an analyzer process

Parameters

data_modestr

data_mode describes the type of data :

• ‘value’ for values

• ‘label’ for label data see LabelMetadata

time_modestr

time_mode describes the correspondance between data values and time

• ‘framewise’

• ‘global’

• ‘segment’

• ‘event’

Returns

A new MetadataObject with the following attributes :

• data_object : DataObject

• id_metadata : IdMetadata

• audio_metadata : AudioMetadata

• frame_metadata : FrameMetadata

• label_metadata : LabelMetadata

• parameters : Parameters Object

Construct an Metadata object Abstract Class _default_value must be specified by

Metadata()

Returns

Metadata

as_dict(self)

property data

property data_mode

property duration

static from_hdf5(h5group)

static from_xml(xml_string)

property id

property name

render(self)

Render a matplotlib figure from the analyzer result

Return the figure, use fig.show() to display if neeeded

property time

property time_mode

to_hdf5(self, h5_file)

to_json(self, output_file=None)

to_xml(self)

property unit

AnalyzerResultContainer

class timeside.core.analyzer.AnalyzerResultContainer(analyzer_results=None)

Bases: dict

>>> import timeside
>>> from timeside.core.analyzer import Analyzer
>>> from timeside.core.tools.test_samples import samples
>>> wav_file = samples['sweep.mp3']
>>> d = timeside.core.get_processor('file_decoder')(wav_file)
>>> a = Analyzer()
>>> (d|a).run()
>>> a.new_result() 
AnalyzerResult(id_metadata=IdMetadata(id='analyzer', name='Generic analyzer', unit='', description='...', date='...', version='...', author='TimeSide', proc_uuid='...'), data_object=FrameValueObject(value=array([], dtype=float64), y_value=array([], dtype=float64), frame_metadata=FrameMetadata(samplerate=44100, blocksize=8192, stepsize=8192)), audio_metadata=AudioMetadata(uri='.../sweep.mp3', start=0.0, duration=8.0..., is_segment=False, sha1='...', channels=2, channelsManagement=''), parameters={})
>>> resContainer = timeside.core.analyzer.AnalyzerResultContainer()

add(self, analyzer_result, overwrite=False)

from_hdf5(self, input_file)

from_json(self, json_str)

from_numpy(self, input_file)

from_xml(self, xml_string)

from_yaml(self, yaml_str)

get_result_by_id(self, result_id)

list_id(self)

to_hdf5(self, output_file)

to_json(self, output_file=None)

to_numpy(self, output_file=None)

to_xml(self, output_file=None)

to_yaml(self, output_file=None)