loaders Package

base Module

An abstract loader class

class maidenhair.loaders.base.BaseLoader(using=None, parser=None)

Bases: object

A abstract loader class

Methods

glob(pathname[, using, unite, basecolumn, ...])	Load data from file matched with given glob pattern.
load(filename[, using, parser])	Load data from file using a specified parser.

glob(pathname, using=None, unite=False, basecolumn=0, parser=None, with_filename=False, recursive=False, natsort=True, **kwargs)

Load data from file matched with given glob pattern.

Return value will be a list of data unless unite is True. If unite is True, all dataset will be united into a single data.

Parameters:

pathname : string

A glob pattern

using : list of integer, slice instance, or None, optional

A list of index or slice instance used to slice data into column If it is not specified, using specified in constructor will be used instead.

unite : boolean, optional:

If it is True then dataset will be united into a single numpy array. See usage for more detail.

basecolumn : integer, optional

An index of base column. all data will be trimmed based on the order of this column when the number of samples are different among the dataset. It only affect when unite is specified as True.

parser : instance, optional

An instance or registered name of parser class. If it is not specified, parser specified in constructor will be used instead.

with_filename : boolean, optional

If it is True, returning dataset will contain filename in the first column. It is cannot be used with unite = True

recursive : boolean, optional

Recursively find pattern in the directory

natsort : boolean

Naturally sort found files.

Returns:

ndarray :

A list of numpy array

load(filename, using=None, parser=None, **kwargs)

Load data from file using a specified parser.

Return value will be separated or sliced into a column list

Parameters:

filename : string

A data file path

using : list of integer, slice instance, or None, optional

A list of index or slice instance used to slice data into column If it is not specified, using specified in constructor will be used instead.

parser : instance or None, optional

An instance or registered name of parser class. If it is not specified, parser specified in constructor will be used instead.

Returns:

ndarray :

A list of numpy array

maidenhair.loaders.base.slice_columns(x, using=None)

Slice a numpy array to make columns

Parameters:

x : ndarray

A numpy array instance

using : list of integer or slice instance or None, optional

A list of index or slice instance

Returns:

ndarray :

A list of numpy array columns sliced

maidenhair.loaders.base.unite_dataset(dataset, basecolumn=0)

Unite dataset into a single data

Parameters:

dataset : list of ndarray

A data list of a column list of a numpy arrays

basecolumn : integer, optional

An index of base column. All data will be trimmed based on the order of this column when the number of samples are different among the dataset

Returns:

list of numpy array :

A column list of a numpy array

plain Module

A plain text loader

class maidenhair.loaders.plain.PlainLoader(using=None, parser=None)

Bases: maidenhair.loaders.base.BaseLoader

A simple loader class

Methods

glob(pathname[, using, unite, basecolumn, ...])	Load data from file matched with given glob pattern.
load(filename[, using, parser])	Load data from file using a specified parser.