ó ‡ˆ\c@sîdZddlmZmZmZddlmZmZddlZ ddl m Z ddl m Z ddl mZdd l mZdd l mZd d lmZd d lmZmZeddddddƒZdeded„ZdS(sModified Olivetti faces dataset. The original database was available from (now defunct) https://www.cl.cam.ac.uk/research/dtg/attarchive/facedatabase.html The version retrieved here comes in MATLAB format from the personal web page of Sam Roweis: https://cs.nyu.edu/~roweis/ iÿÿÿÿ(tdirnametexiststjoin(tmakedirstremoveN(tloadmati(t get_data_home(t _fetch_remote(tRemoteFileMetadata(t _pkl_filepathi(t_joblib(tcheck_random_statetBunchtfilenamesolivettifaces.matturls.https://ndownloader.figshare.com/files/5976027tchecksumt@b612fb967f2dc77c9c62d3e1266e0c73d5fca46a4b8906c18e454d41af987794ic Csôtd|ƒ}t|ƒs(t|ƒnt|dƒ}t|ƒsÄ|sXtdƒ‚ndtj|fGHttd|ƒ}td|ƒ}t |ƒ|dj j ƒ}t j ||dd ƒ~nt j|ƒ}tj|ƒ}||jƒ}||jƒ:}|jdƒjd d dƒ}tjgtd ƒD]}|d^q3ƒ} |rŠt|ƒ}|jt|ƒƒ} || }| | } nttƒ} tt| ddƒƒ} | jƒ} WdQXtd|jt|ƒdƒd|d| d| ƒS(sELoad the Olivetti faces data-set from AT&T (classification). Download it if necessary. ================= ===================== Classes 40 Samples total 400 Dimensionality 4096 Features real, between 0 and 1 ================= ===================== Read more in the :ref:`User Guide `. Parameters ---------- data_home : optional, default: None Specify another download and cache folder for the datasets. By default all scikit-learn data is stored in '~/scikit_learn_data' subfolders. shuffle : boolean, optional If True the order of the dataset is shuffled to avoid having images of the same person grouped. random_state : int, RandomState instance or None (default=0) Determines random number generation for dataset shuffling. Pass an int for reproducible output across multiple function calls. See :term:`Glossary `. download_if_missing : optional, True by default If False, raise a IOError if the data is not locally available instead of trying to download the data from the source site. Returns ------- An object with the following attributes: data : numpy array of shape (400, 4096) Each row corresponds to a ravelled face image of original size 64 x 64 pixels. images : numpy array of shape (400, 64, 64) Each row is a face image corresponding to one of the 40 subjects of the dataset. target : numpy array of shape (400, ) Labels associated to each face image. Those labels are ranging from 0-39 and correspond to the Subject IDs. DESCR : string Description of the modified Olivetti Faces Dataset. t data_homes olivetti.pkzs1Data not found and `download_if_missing` is Falses(downloading Olivetti faces from %s to %sRt file_nametfacestcompressiii@iiii tdescrsolivetti_faces.rstNtdataiÿÿÿÿtimagesttargettDESCR(ii@i@( RRRR tIOErrortFACESRRRRtTtcopyR tdumptloadtnptfloat32tmintmaxtreshapet transposetarraytrangeR t permutationtlenRt__file__topenRtreadR (Rtshufflet random_statetdownload_if_missingtfilepathtmat_pathtmfileRtiRtordert module_pathtrst_filetfdescr((s>lib/python2.7/site-packages/sklearn/datasets/olivetti_faces.pytfetch_olivetti_faces&sB5    ,    (t__doc__tos.pathRRRtosRRtnumpyR tscipy.io.matlabRtbaseRRRR tutilsR R R RtNonetFalsetTrueR8(((s>lib/python2.7/site-packages/sklearn/datasets/olivetti_faces.pyt s