dcase_util.processors.NormalizationProcessor

class dcase_util.processors.NormalizationProcessor(n=None, s1=None, s2=None, mean=None, std=None, normalizer=None, filename=None, **kwargs)

Data normalizer to accumulate data statistics

__init__ method.

Parameters

nint

Item count used to calculate statistics Default value None

s1numpy.array [shape=(vector_length,)]

Vector-wise sum of the data seen by the Normalizer Default value None

s2numpy.array [shape=(vector_length,)]

Vector-wise sum^2 of the data seen by the Normalizer Default value None

meannumpy.ndarray() [shape=(vector_length, 1)]

Mean of the data Default value None

stdnumpy.ndarray() [shape=(vector_length, 1)]

Standard deviation of the data Default value None

normalizerNormalizer

Normalizer object to initialize the processor Default value None

filenamestr

Filename to saved normalizer object to initialize the processor Default value None

__init__(n=None, s1=None, s2=None, mean=None, std=None, normalizer=None, filename=None, **kwargs)

__init__ method.

Parameters

nint

Item count used to calculate statistics Default value None

s1numpy.array [shape=(vector_length,)]

Vector-wise sum of the data seen by the Normalizer Default value None

s2numpy.array [shape=(vector_length,)]

Vector-wise sum^2 of the data seen by the Normalizer Default value None

meannumpy.ndarray() [shape=(vector_length, 1)]

Mean of the data Default value None

stdnumpy.ndarray() [shape=(vector_length, 1)]

Standard deviation of the data Default value None

normalizerNormalizer

Normalizer object to initialize the processor Default value None

filenamestr

Filename to saved normalizer object to initialize the processor Default value None

Methods

__init__([n, s1, s2, mean, std, normalizer, ...])	__init__ method.
delimiter([exclude_delimiters])	Use csv.sniffer to guess delimiter for CSV file
detect_file_format([filename])	Detect file format from extension
empty()	Check if file is empty
exists()	Checks that file exists
get_file_information()	Get file information, filename
get_processing_chain_item()	Get processing chain item with current Processor data.
is_package([filename])	Determine if the file is compressed package.
load([filename])	Load file
log([level])	Log container content
process([data, store_processing_chain])	Normalize feature matrix with internal statistics of the class
save([filename])	Save file
show([mode, indent, visualize])	Print container content
to_html([indent])	Get container information in a HTML formatted string
to_string([ui, indent])	Get container information in a string
validate_format()	Validate file format

Attributes

bytes	File size in bytes
input_type	Input data type
logger	Logger instance
md5	Checksum for file.
output_type	Output data type
valid_formats	Valid file formats