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_mode : str

data_mode describes the type of data :

• ‘value’ for values
• ‘label’ for label data see LabelMetadata

time_mode : str

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

as_dict()

data

data_mode

duration

static from_hdf5(h5group)

static from_xml(xml_string)

id

name

render()

Render a matplotlib figure from the analyzer result

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

time

time_mode

to_hdf5(h5_file)

to_json(output_file=None)

to_xml()

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(analyzer_result, overwrite=False)

from_hdf5(input_file)

from_json(json_str)

from_numpy(input_file)

from_xml(xml_string)

from_yaml(yaml_str)

get_result_by_id(result_id)

list_id()

to_hdf5(output_file)

to_json(output_file=None)

to_numpy(output_file=None)

to_xml(output_file=None)

to_yaml(output_file=None)