diff --git a/ai/data/SC-index.csv b/ai/data/SC-index.csv
new file mode 100644
index 00000000..f6d5ee51
--- /dev/null
+++ b/ai/data/SC-index.csv
@@ -0,0 +1,307 @@
+subject,night,record type,sha,fname
+0,1,PSG,adabd3b01fc7bb75c523a974f38ee3ae4e57b40f,SC4001E0-PSG.edf
+0,1,Hypnogram,21c998eadc8b1e3ea6727d3585186b8f76e7e70b,SC4001EC-Hypnogram.edf
+0,2,PSG,c6b6d7a8605cc7e7602b6028ee77f6fbf5f7581d,SC4002E0-PSG.edf
+0,2,Hypnogram,386230188a3552b1fc90bba0fb7476ceaca174b6,SC4002EC-Hypnogram.edf
+1,1,PSG,4d17451f7847355bcab17584de05e7e1df58c660,SC4011E0-PSG.edf
+1,1,Hypnogram,d582a3cbe2db481a362af890bc5a2f5ca7c878dc,SC4011EH-Hypnogram.edf
+1,2,PSG,a47d525f5147904b6890231e2ad338359c7ab94c,SC4012E0-PSG.edf
+1,2,Hypnogram,fa99f60d7f54617cdd1128aff4f21c4daed763c7,SC4012EC-Hypnogram.edf
+2,1,PSG,8b135afa7fb93bb5f1998fda50355944777c245e,SC4021E0-PSG.edf
+2,1,Hypnogram,91043cfe46695088b17b6a02937b25efd674c3fb,SC4021EH-Hypnogram.edf
+2,2,PSG,d739e142b3b328c71b4752149901805dcd6d7e19,SC4022E0-PSG.edf
+2,2,Hypnogram,0c46a03699dd00e8f92a7edff99ebc4642cb3d48,SC4022EJ-Hypnogram.edf
+3,1,PSG,85e58dc1e3303537dade8c5827ab58328239c384,SC4031E0-PSG.edf
+3,1,Hypnogram,6363d8b0fdc48cf396c9abf054bb4a9696d38bdb,SC4031EC-Hypnogram.edf
+3,2,PSG,43963d300642b3aa840e8c468f321b8162601772,SC4032E0-PSG.edf
+3,2,Hypnogram,7925514bc8d2ef3f1103130f08f7b3afd2136b88,SC4032EP-Hypnogram.edf
+4,1,PSG,04d2b88d25f2ae4a65ba44cd9145bd12800a0e20,SC4041E0-PSG.edf
+4,1,Hypnogram,f148821669bd3588187b3b430bd79adf569f86d1,SC4041EC-Hypnogram.edf
+4,2,PSG,76253d964d7797540ffd791e6e136023ed67a485,SC4042E0-PSG.edf
+4,2,Hypnogram,9873df429f971f8a4b720a454f6c0472b8a25ebb,SC4042EC-Hypnogram.edf
+5,1,PSG,ea073451b65ce8a6f1a02a8cc2b89d1a162ca0ae,SC4051E0-PSG.edf
+5,1,Hypnogram,4159ef8a3e119d6dcc1bede806f6fbc017b27a0f,SC4051EC-Hypnogram.edf
+5,2,PSG,5a2efbd21be9b745fd534394eb2503caca7dc53f,SC4052E0-PSG.edf
+5,2,Hypnogram,0e96482d44762df4da65dc4fdb970b342264d22a,SC4052EC-Hypnogram.edf
+6,1,PSG,1736736e585807c14f1ae8bc87a94cae222c5170,SC4061E0-PSG.edf
+6,1,Hypnogram,4bf99622c67c281b25ceccd35e7050328a2946e8,SC4061EC-Hypnogram.edf
+6,2,PSG,763c7ac059f1771a0165e5cb351b176afb1cfe15,SC4062E0-PSG.edf
+6,2,Hypnogram,14f07411cd04d3b4b522d37c129334955287ff5f,SC4062EC-Hypnogram.edf
+7,1,PSG,1374b34f6139b6ff7e865d8243eef39ba334ef50,SC4071E0-PSG.edf
+7,1,Hypnogram,608024fd19a140ad233a4680e07c2495a74b69c2,SC4071EC-Hypnogram.edf
+7,2,PSG,1c570644243d79396df612fa2b9bc027b24430e4,SC4072E0-PSG.edf
+7,2,Hypnogram,a8da6c20b9b48189f05ab537886b59dd141374d2,SC4072EH-Hypnogram.edf
+8,1,PSG,0e1cc2c4e1da14ab94515e3e7e75e8ad30ec99cb,SC4081E0-PSG.edf
+8,1,Hypnogram,9ec663ffa5c17afcaca59d7829d77b9165102237,SC4081EC-Hypnogram.edf
+8,2,PSG,d57d4aa7cbc5045f611a3a3e342b501e086ea426,SC4082E0-PSG.edf
+8,2,Hypnogram,d43c785dba43063d7baa332671c6bac9c832b5b7,SC4082EP-Hypnogram.edf
+9,1,PSG,b3502e0bd54683e973182c791aa962b804e79633,SC4091E0-PSG.edf
+9,1,Hypnogram,7aa63b408c769a4a983a908b6ba41d87dd743c6e,SC4091EC-Hypnogram.edf
+9,2,PSG,246e35852119b33d197db2f7bcfb1b46a5270a03,SC4092E0-PSG.edf
+9,2,Hypnogram,9d85766a83231b1c6076cb293367ccc354c57eeb,SC4092EC-Hypnogram.edf
+10,1,PSG,3ae168ff2c9c0c56f51205fdb10f05a4c6b2064e,SC4101E0-PSG.edf
+10,1,Hypnogram,60d9c3913881e11b06ad99e9870bd1ca4d93c952,SC4101EC-Hypnogram.edf
+10,2,PSG,86f307190961eaab0214fdc0213f8fe05812c7a5,SC4102E0-PSG.edf
+10,2,Hypnogram,8072e2d52bc6c19b45fbd921550e5243bc5a1de7,SC4102EC-Hypnogram.edf
+11,1,PSG,e490956b4dce01c46ba88a2b847f091bb54ea16e,SC4111E0-PSG.edf
+11,1,Hypnogram,12db1920e2f6083c8ab1f2c24fe35dfa03715e4a,SC4111EC-Hypnogram.edf
+11,2,PSG,ca24dc464df61144627588b29d35a85fcc7ac984,SC4112E0-PSG.edf
+11,2,Hypnogram,54dbc39015b0a445b51189987a00e08cc27d8f0c,SC4112EC-Hypnogram.edf
+12,1,PSG,33c72025a7a215ea5e255f4254cb0f93b1313369,SC4121E0-PSG.edf
+12,1,Hypnogram,daa57ece807cb5325c6d1ce059f0e8a8d1c85391,SC4121EC-Hypnogram.edf
+12,2,PSG,34f5145ab62dcc5a53ba18735519e5bb2b13841a,SC4122E0-PSG.edf
+12,2,Hypnogram,b7af1a32d8ca15e8185e4c94213ffc18ad7f6e8a,SC4122EV-Hypnogram.edf
+13,1,PSG,42ff97035aae6dd34ca9437857c48ac6f2ab97df,SC4131E0-PSG.edf
+13,1,Hypnogram,5beef85170bdbb5cf2eea24a79f0f5c2c3975c4b,SC4131EC-Hypnogram.edf
+14,1,PSG,83493e1c32d441c9e5ee3de6a024bfb5e7ab9f5f,SC4141E0-PSG.edf
+14,1,Hypnogram,511d398f22b9b2b304de27c40740a41584ff6af2,SC4141EU-Hypnogram.edf
+14,2,PSG,63d13828b7ebe0d2ed7f491d2b5520e928b9b55d,SC4142E0-PSG.edf
+14,2,Hypnogram,6f123e6fdc90a01b83e694d9744a6d27f3c87b25,SC4142EU-Hypnogram.edf
+15,1,PSG,5a92d49699d4de369d66d9462e91b0dcb3312649,SC4151E0-PSG.edf
+15,1,Hypnogram,37dcbd339c95322d028b3a5466812697041cc373,SC4151EC-Hypnogram.edf
+15,2,PSG,778626489bc4fe2c9137d2d361876d97dce97e5e,SC4152E0-PSG.edf
+15,2,Hypnogram,294cdc47cd3d165031f7041c17f18dd013d216cb,SC4152EC-Hypnogram.edf
+16,1,PSG,e56ff3aa366fe9a04a0fdfdd4cd862e77e8ac807,SC4161E0-PSG.edf
+16,1,Hypnogram,56711b1bfed292032491f5cce57494629286a131,SC4161EC-Hypnogram.edf
+16,2,PSG,722692f9940f3a1bccb9b4488c4477edf7fb128f,SC4162E0-PSG.edf
+16,2,Hypnogram,c85647fb4bc1f382fe46bf9aaf579dc483115885,SC4162EC-Hypnogram.edf
+17,1,PSG,f1a65522cb7d6c71ac47742535a12c88e2019dad,SC4171E0-PSG.edf
+17,1,Hypnogram,dd257c8d922f08c2c8ca5236c9bf54da887c68e5,SC4171EU-Hypnogram.edf
+17,2,PSG,572b81bc24c2c9482e6fc7ba9202a7bf253655e1,SC4172E0-PSG.edf
+17,2,Hypnogram,c9a3b590748d7d6c7ad97c62222bd53d8ebaf630,SC4172EC-Hypnogram.edf
+18,1,PSG,23674d20572853eb6d988d24378c52123f66500c,SC4181E0-PSG.edf
+18,1,Hypnogram,51fc3df2df7d4da654f3e18ed1b233d0c60cfa80,SC4181EC-Hypnogram.edf
+18,2,PSG,83e8cbe882ba863da9fd3c11393c95b6fec5b7a5,SC4182E0-PSG.edf
+18,2,Hypnogram,43c487955edddb4ee2f60193a097c68c25c5dd4d,SC4182EC-Hypnogram.edf
+19,1,PSG,d6da621dbb20dec3494a38c7d2a0363793ac5ebe,SC4191E0-PSG.edf
+19,1,Hypnogram,defc7b9368c2d3c4ab4a294757843825a83cdb5d,SC4191EP-Hypnogram.edf
+19,2,PSG,941353118732321d0246a1d58d72e903bd2f0d8f,SC4192E0-PSG.edf
+19,2,Hypnogram,97b91b3067c5ecde766042fc2cff9e22f8023371,SC4192EV-Hypnogram.edf
+20,1,PSG,38a0be6e45ddd9b1f17d09964a32e005dc5a6519,SC4201E0-PSG.edf
+20,1,Hypnogram,83822f9970d3959ad2e0613492ae39bd0fae6068,SC4201EC-Hypnogram.edf
+20,2,PSG,aa69f5bd47c2ae03c9d38bfe6d0e58408744b885,SC4202E0-PSG.edf
+20,2,Hypnogram,5c5c63016b43421a523d1efcb34247e90aa6318b,SC4202EC-Hypnogram.edf
+21,1,PSG,c106ad072dbc975a3742f7eff151219870f0c794,SC4211E0-PSG.edf
+21,1,Hypnogram,9126937ea8a414d6ae9bc4a4194d841a891fa8a8,SC4211EC-Hypnogram.edf
+21,2,PSG,a06ecb3f0a7b2c306f5ae4dbd83685f877cd945b,SC4212E0-PSG.edf
+21,2,Hypnogram,a85f178b69a1cda47d11dd1e5394dfdcb58de1d4,SC4212EC-Hypnogram.edf
+22,1,PSG,8733ea022d3778259a436507156cf3360ad8be06,SC4221E0-PSG.edf
+22,1,Hypnogram,b158eda4f81772095c129be77f8e60ec9d81b884,SC4221EJ-Hypnogram.edf
+22,2,PSG,211410fab6381da0dfaef4134d5a05eec935a4ec,SC4222E0-PSG.edf
+22,2,Hypnogram,1488fbfbc149499dafa8dafff4f7504053af429f,SC4222EC-Hypnogram.edf
+23,1,PSG,d96f1f35b2f77c7de706036c6e4114139e07b307,SC4231E0-PSG.edf
+23,1,Hypnogram,9f6df70676d6cddcf069ceb7f408a7989af99ce2,SC4231EJ-Hypnogram.edf
+23,2,PSG,6b493fa424c1329ea1c13543d08ba82a9f1e85b6,SC4232E0-PSG.edf
+23,2,Hypnogram,d8ca7d694b3c48ab9d983b9cf67e17744c6b50fb,SC4232EV-Hypnogram.edf
+24,1,PSG,58719e53fe18d2fc4cb1776ab5d43306beb1325d,SC4241E0-PSG.edf
+24,1,Hypnogram,fb1432e303a8f99a2256ce682db95d88772c479f,SC4241EC-Hypnogram.edf
+24,2,PSG,5a6277972c5f03572ed99d9ff63fb637945be778,SC4242E0-PSG.edf
+24,2,Hypnogram,bbbf097f4cc6560fc20c903fba2c7055e1549f85,SC4242EA-Hypnogram.edf
+25,1,PSG,7dbc0289707ff70662d367d65de7bec188484d1b,SC4251E0-PSG.edf
+25,1,Hypnogram,e38be8134e4a36eb418ca1f06a1fe02b52d0ebf1,SC4251EP-Hypnogram.edf
+25,2,PSG,cb3922910ea03d06c1fc5c8f15b71339dc26bc9d,SC4252E0-PSG.edf
+25,2,Hypnogram,4cb7a383736e09125a82ef7e4f17b41130c7ac00,SC4252EU-Hypnogram.edf
+26,1,PSG,b81c9bd1875b33713b5eb56b58f1e120841b507f,SC4261F0-PSG.edf
+26,1,Hypnogram,501eda59557bb99d530d01bdad3579f1e1158991,SC4261FM-Hypnogram.edf
+26,2,PSG,c9f9ad7cd751d5be91396886a2b64a7c1de564ee,SC4262F0-PSG.edf
+26,2,Hypnogram,7ccd12803c5fc602ac1929ff3afd914b894b9143,SC4262FC-Hypnogram.edf
+27,1,PSG,20994715d34edb26113180ee330ce287dbf57b60,SC4271F0-PSG.edf
+27,1,Hypnogram,26c5c7f3a5c350d3505af2857835ce81252c5990,SC4271FC-Hypnogram.edf
+27,2,PSG,9e79eb465e34b7eb6fe27ae3ce35d28d6693d44b,SC4272F0-PSG.edf
+27,2,Hypnogram,956fe4b45d29a8999faf280a6168e332afab6abc,SC4272FM-Hypnogram.edf
+28,1,PSG,51811913d7854f95c319076e670d988687ca667c,SC4281G0-PSG.edf
+28,1,Hypnogram,d188150831e912081dbeda2695231177200c39f9,SC4281GC-Hypnogram.edf
+28,2,PSG,e9f080a766a9b7a247f228e44e9c4ec67e571c95,SC4282G0-PSG.edf
+28,2,Hypnogram,12d777787dd1975eef9015329fd774b2bfa1d53a,SC4282GC-Hypnogram.edf
+29,1,PSG,f81c7574a5e5829e006d0b705bf5208a3349c9c7,SC4291G0-PSG.edf
+29,1,Hypnogram,577c1345f6d070d975db5016048722f78b1b414e,SC4291GA-Hypnogram.edf
+29,2,PSG,7416f44a3b149b4ca1fc3e53d546a093a7333bb5,SC4292G0-PSG.edf
+29,2,Hypnogram,6e111a15160a31609761f742315df800b1311b3b,SC4292GC-Hypnogram.edf
+30,1,PSG,7818e5a02afa89e913111d91ecd651aa3e786e5d,SC4301E0-PSG.edf
+30,1,Hypnogram,d49df84bfea28bb241c09b922cd2dc64f57c5ae5,SC4301EC-Hypnogram.edf
+30,2,PSG,d52859ba6a7ded3364b0d8ef2b722e1d3edda060,SC4302E0-PSG.edf
+30,2,Hypnogram,b3d6f687831ee32f6df1da59f2d568c13f9c09d0,SC4302EV-Hypnogram.edf
+31,1,PSG,b62f5104bddf452f4700c85997e51bec17f0243b,SC4311E0-PSG.edf
+31,1,Hypnogram,812c34844e834b97949019741fa7f835d973725d,SC4311EC-Hypnogram.edf
+31,2,PSG,b0a9b4922665734773abbaba06e7aab32010b862,SC4312E0-PSG.edf
+31,2,Hypnogram,fca1935a8974eac27803e3125cea177995deca11,SC4312EM-Hypnogram.edf
+32,1,PSG,335381ae310e9f1f053c37763eeee74d7d873471,SC4321E0-PSG.edf
+32,1,Hypnogram,67ba7d3b97354deb31db095e748ea3a4014fae2c,SC4321EC-Hypnogram.edf
+32,2,PSG,c9fdcfcce7e603b3289b7417891987fd67f6d921,SC4322E0-PSG.edf
+32,2,Hypnogram,40cf9a6397a52c7deda693ca596e928cc2b9f4e9,SC4322EC-Hypnogram.edf
+33,1,PSG,f37cb4df27286e38c604cae943169ff29b1473fc,SC4331F0-PSG.edf
+33,1,Hypnogram,ca943e2b73c6404f929c372ebd817b7b3b71b4dd,SC4331FV-Hypnogram.edf
+33,2,PSG,5bce6ea9b2d6c9bfb41065e92bf9cc05a11b5b75,SC4332F0-PSG.edf
+33,2,Hypnogram,e4595b0313d5320b0bffefa43260485e19977e3c,SC4332FC-Hypnogram.edf
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+34,1,Hypnogram,81ba3c0d8320c9ee306f678b4bc9e6e266165886,SC4341FA-Hypnogram.edf
+34,2,PSG,b659037447a1871f4ba72bbe496cfbe507330530,SC4342F0-PSG.edf
+34,2,Hypnogram,e8e74c0905e89a59022ce0814ca9a050748ec9ae,SC4342FA-Hypnogram.edf
+35,1,PSG,631900bef36d359a0f5807a7e1b202f80b0427ac,SC4351F0-PSG.edf
+35,1,Hypnogram,a15cdf3973b77198d8276dc505dbb35cb39a9b4a,SC4351FA-Hypnogram.edf
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+37,1,PSG,0dc56fce13b6317f197d0b17c04f5be4af1c964f,SC4371F0-PSG.edf
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+38,1,PSG,6098d2b501b82ca0ddc8893547c6990e204e8ba6,SC4381F0-PSG.edf
+38,1,Hypnogram,fdbf653a4a675843c97d0a76ef5e4cebf5d2dbcb,SC4381FC-Hypnogram.edf
+38,2,PSG,40ce0168d5f546fcd445996ab614f43823a7c2b1,SC4382F0-PSG.edf
+38,2,Hypnogram,796f8507254c2d8d345171c077dbd855e112eb47,SC4382FW-Hypnogram.edf
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+40,1,Hypnogram,65b5671a89871351ee3da7ea800aad276a445b2a,SC4401EC-Hypnogram.edf
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+40,2,Hypnogram,037efea0fc8a6dfa8f85fa1f2fa6fd9a19f2c830,SC4402EW-Hypnogram.edf
+41,1,PSG,30a533b67fdb2adac6a4e83088a07fe1bbaddb6c,SC4411E0-PSG.edf
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+41,2,Hypnogram,f46b1dcfe4f4e3c9d4d4c8516dab9759f9c1224e,SC4412EM-Hypnogram.edf
+42,1,PSG,e8a5d9e0f160ae7bd0b35d75d77b4c872daa30f8,SC4421E0-PSG.edf
+42,1,Hypnogram,d2e34f9bcaac7af23da4448f742ac6ea3c895ed9,SC4421EA-Hypnogram.edf
+42,2,PSG,80f246adffb92a3785f91368a77b0250aa040462,SC4422E0-PSG.edf
+42,2,Hypnogram,709251cc7ae6556544c153caf9dac7f82bba113b,SC4422EA-Hypnogram.edf
+43,1,PSG,194ae942cf80764e81b4cdabeed9e5a57916aab3,SC4431E0-PSG.edf
+43,1,Hypnogram,497ad7e671edab6e7adc9d35a6aa45b7fd9a706b,SC4431EM-Hypnogram.edf
+43,2,PSG,c45a66d27ea03bf448903fe30f17838e9a0fa0de,SC4432E0-PSG.edf
+43,2,Hypnogram,10fe276e215f9406c0ddedaa48651cf480892476,SC4432EM-Hypnogram.edf
+44,1,PSG,e3a09d832cb79b0095d7a311ef1b6ed7c569b79d,SC4441E0-PSG.edf
+44,1,Hypnogram,68d4e44ad54069701972df66d8a81b4ca434bf2f,SC4441EC-Hypnogram.edf
+44,2,PSG,fe51d45e9f3e64a61fa8a5e5274b2e4951a9de43,SC4442E0-PSG.edf
+44,2,Hypnogram,efc2b86bb796b0143f61667402612dfbb85cbb78,SC4442EV-Hypnogram.edf
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diff --git a/ai/data/SC-subjects.csv b/ai/data/SC-subjects.csv
new file mode 100644
index 00000000..a26bd2ae
--- /dev/null
+++ b/ai/data/SC-subjects.csv
@@ -0,0 +1,154 @@
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+71;1;88;2;21:15
+71;2;88;2;23:18
+72;1;88;2;23:04
+72;2;88;2;23:09
+73;1;97;2;22:30
+73;2;97;2;22:00
+74;1;92;2;23:14
+74;2;92;2;23:06
+75;1;96;2;22:58
+75;2;96;2;23:00
+76;1;90;2;23:28
+76;2;90;2;1:29
+77;1;85;2;23:23
+77;2;85;2;0:10
+80;1;54;1;23:05
+80;2;54;1;23:18
+81;1;57;1;22:00
+81;2;57;1;21:56
+82;1;56;1;23:59
+82;2;56;1;0:05
diff --git a/ai/data/recordings-info.csv b/ai/data/recordings-info.csv
new file mode 100644
index 00000000..79ff50e6
--- /dev/null
+++ b/ai/data/recordings-info.csv
@@ -0,0 +1,154 @@
+subject,night,age,sex,LightsOff,NightDuration,LightsOffSecond,StartRecord,StartRecordTimestamp
+0,1,33,1,1989-04-25 00:38:00,21810.0,30300.0,1989-04-24 16:13:00,609437580.0
+0,2,33,1,1989-04-25 21:57:00,30330.0,25620.0,1989-04-25 14:50:00,609519000.0
+1,1,33,1,1989-03-29 22:44:00,29250.0,21300.0,1989-03-29 16:49:00,607193340.0
+1,2,33,1,1989-03-30 22:15:00,31260.0,18900.0,1989-03-30 17:00:00,607280400.0
+2,1,26,1,1989-04-05 22:50:00,27150.0,21720.0,1989-04-05 16:48:00,607798080.0
+2,2,26,1,1989-04-06 22:57:00,26880.0,22500.0,1989-04-06 16:42:00,607884120.0
+3,1,26,1,1989-04-11 00:02:00,25110.0,25920.0,1989-04-10 16:50:00,608230200.0
+3,2,26,1,1989-04-12 00:24:00,23790.0,27300.0,1989-04-11 16:49:00,608316540.0
+4,1,34,1,1989-04-24 23:12:00,34890.0,22920.0,1989-04-24 16:50:00,609439800.0
+4,2,34,1,1989-04-25 23:35:00,34020.0,30660.0,1989-04-25 15:04:00,609519840.0
+5,1,28,1,1989-04-27 01:22:00,22950.0,32220.0,1989-04-26 16:25:00,609611100.0
+5,2,28,1,1989-04-28 00:35:00,34260.0,31980.0,1989-04-27 15:42:00,609694920.0
+6,1,31,1,1989-05-09 00:16:00,21600.0,27660.0,1989-05-08 16:35:00,610648500.0
+6,2,31,1,1989-05-09 22:44:00,27630.0,24540.0,1989-05-09 15:55:00,610732500.0
+7,1,30,1,1989-05-18 00:36:00,26400.0,27060.0,1989-05-17 17:05:00,611427900.0
+7,2,30,1,1989-02-19 00:41:00,26370.0,27360.0,1989-02-18 17:05:00,603824700.0
+8,1,25,1,1989-05-24 23:35:00,29220.0,25080.0,1989-05-24 16:37:00,612031020.0
+8,2,25,1,1989-05-25 23:37:00,28500.0,24840.0,1989-05-25 16:43:00,612117780.0
+9,1,25,1,1989-06-05 23:02:00,30900.0,23880.0,1989-06-05 16:24:00,613067040.0
+9,2,25,1,1989-06-06 23:01:00,29880.0,26880.0,1989-06-06 15:33:00,613150380.0
+10,1,26,2,1989-04-17 22:59:00,30060.0,22140.0,1989-04-17 16:50:00,608835000.0
+10,2,26,2,1989-04-18 23:07:00,29580.0,25860.0,1989-04-18 15:56:00,608918160.0
+11,1,26,2,1989-05-01 23:00:00,28740.0,23460.0,1989-05-01 16:29:00,610043340.0
+11,2,26,2,1989-05-03 01:14:00,20250.0,35640.0,1989-05-02 15:20:00,610125600.0
+12,1,26,2,1989-05-23 00:50:00,25050.0,31680.0,1989-05-22 16:02:00,611856120.0
+12,2,26,2,1989-05-24 01:03:00,26520.0,32460.0,1989-05-23 16:02:00,611942520.0
+13,1,27,2,1989-06-15 00:14:00,27480.0,28500.0,1989-06-14 16:19:00,613844340.0
+14,1,27,2,1989-06-19 22:55:00,27030.0,24600.0,1989-06-19 16:05:00,614275500.0
+14,2,27,2,1989-06-20 23:22:00,25290.0,28140.0,1989-06-20 15:33:00,614359980.0
+15,1,31,2,1989-06-21 23:56:00,25380.0,26160.0,1989-06-21 16:40:00,614450400.0
+15,2,31,2,1989-06-22 23:38:00,27960.0,31500.0,1989-06-22 14:53:00,614530380.0
+16,1,32,2,1989-07-10 22:16:00,32310.0,20700.0,1989-07-10 16:31:00,616091460.0
+16,2,32,2,1989-07-11 23:16:00,27900.0,30120.0,1989-07-11 14:54:00,616172040.0
+17,1,31,2,1989-07-12 23:58:00,25830.0,28140.0,1989-07-12 16:09:00,616262940.0
+17,2,31,2,1989-07-06 00:37:00,27480.0,32400.0,1989-07-05 15:37:00,615656220.0
+18,1,28,2,1989-07-19 23:25:00,24810.0,26700.0,1989-07-19 16:00:00,616867200.0
+18,2,28,2,1989-07-20 23:45:00,23940.0,30360.0,1989-07-20 15:19:00,616951140.0
+19,1,28,2,1989-07-20 01:50:00,42930.0,34380.0,1989-07-19 16:17:00,616868220.0
+19,2,28,2,1989-07-21 00:57:00,40620.0,32520.0,1989-07-20 15:55:00,616953300.0
+20,1,51,1,1989-05-08 23:10:00,27210.0,24720.0,1989-05-08 16:18:00,610647480.0
+20,2,51,1,1989-05-09 23:15:00,27030.0,25560.0,1989-05-09 16:09:00,610733340.0
+21,1,51,1,1989-06-14 23:28:00,26400.0,25380.0,1989-06-14 16:25:00,613844700.0
+21,2,51,1,1989-06-15 23:59:00,23100.0,27360.0,1989-06-15 16:23:00,613930980.0
+22,1,56,1,1989-05-24 23:47:00,29370.0,24720.0,1989-05-24 16:55:00,612032100.0
+22,2,56,1,1989-05-25 23:14:00,29910.0,24240.0,1989-05-25 16:30:00,612117000.0
+23,1,50,1,1989-06-29 00:51:00,23820.0,31440.0,1989-06-28 16:07:00,615053220.0
+23,2,50,1,1989-06-30 00:32:00,48690.0,28620.0,1989-06-29 16:35:00,615141300.0
+24,1,54,1,1989-07-05 23:22:00,27000.0,26280.0,1989-07-05 16:04:00,615657840.0
+24,2,54,1,1989-07-06 22:50:00,29460.0,27300.0,1989-07-06 15:15:00,615741300.0
+25,1,56,1,1989-07-18 00:32:00,24930.0,30420.0,1989-07-17 16:05:00,616694700.0
+25,2,56,1,1989-07-18 23:49:00,27000.0,29640.0,1989-07-18 15:35:00,616779300.0
+26,1,51,1,1990-03-05 23:39:00,31440.0,26940.0,1990-03-05 16:10:00,636653400.0
+26,2,51,1,1990-03-07 00:20:00,26760.0,29400.0,1990-03-06 16:10:00,636739800.0
+27,1,54,1,1990-04-03 23:41:00,27900.0,29460.0,1990-04-03 15:30:00,639156600.0
+27,2,54,1,1990-04-02 22:58:00,31020.0,38580.0,1990-04-02 12:15:00,639058500.0
+28,1,56,1,1991-08-28 23:55:00,31080.0,36540.0,1991-08-28 13:46:00,683387160.0
+28,2,56,1,1991-08-30 00:13:00,27870.0,38400.0,1991-08-29 13:33:00,683472780.0
+29,1,51,1,1991-09-16 22:38:00,30510.0,26160.0,1991-09-16 15:22:00,685034520.0
+29,2,51,1,1991-09-17 23:04:00,28500.0,29340.0,1991-09-17 14:55:00,685119300.0
+30,1,50,2,1989-06-20 00:09:00,24270.0,27900.0,1989-06-19 16:24:00,614276640.0
+30,2,50,2,1989-06-21 00:20:00,21240.0,33060.0,1989-06-20 15:09:00,614358540.0
+31,1,54,2,1989-07-10 23:44:00,29370.0,24840.0,1989-07-10 16:50:00,616092600.0
+31,2,54,2,1989-07-11 23:14:00,31980.0,27840.0,1989-07-11 15:30:00,616174200.0
+32,1,57,2,1989-07-13 00:48:00,24420.0,30180.0,1989-07-12 16:25:00,616263900.0
+32,2,57,2,1989-07-13 00:15:00,27030.0,29100.0,1989-07-12 16:10:00,616263000.0
+33,1,60,2,1990-03-19 22:58:00,53610.0,27780.0,1990-03-19 15:15:00,637859700.0
+33,2,60,2,1990-03-20 22:55:00,24660.0,27300.0,1990-03-20 15:20:00,637946400.0
+34,1,54,2,1990-04-02 23:03:00,26340.0,24180.0,1990-04-02 16:20:00,639073200.0
+34,2,54,2,1990-04-03 22:30:00,29340.0,24900.0,1990-04-03 15:35:00,639156900.0
+35,1,57,2,1990-05-29 00:02:00,25710.0,28920.0,1990-05-28 16:00:00,643910400.0
+35,2,57,2,1990-05-29 23:30:00,30360.0,27900.0,1990-05-29 15:45:00,643995900.0
+36,2,51,2,1990-06-07 23:59:00,21420.0,30720.0,1990-06-07 15:27:00,644772420.0
+37,1,52,2,1990-05-28 23:03:00,23610.0,26280.0,1990-05-28 15:45:00,643909500.0
+37,2,52,2,1990-05-28 23:05:00,24420.0,25500.0,1990-05-28 16:00:00,643910400.0
+38,1,51,2,1990-03-26 23:12:00,26820.0,27720.0,1990-03-26 15:30:00,638465400.0
+38,2,51,2,1990-03-27 23:47:00,25830.0,31920.0,1990-03-27 14:55:00,638549700.0
+40,1,67,1,1989-05-10 23:30:00,31860.0,23700.0,1989-05-10 16:55:00,610822500.0
+40,2,67,1,1989-05-11 23:55:00,29190.0,30000.0,1989-05-11 15:35:00,610904100.0
+41,1,66,1,1989-05-17 23:28:00,28950.0,24120.0,1989-05-17 16:46:00,611426760.0
+41,2,66,1,1989-05-18 23:30:00,25350.0,25200.0,1989-05-18 16:30:00,611512200.0
+42,1,69,1,1989-06-01 01:30:00,20340.0,32220.0,1989-05-31 16:33:00,612635580.0
+42,2,69,1,1989-06-02 00:22:00,23040.0,29280.0,1989-06-01 16:14:00,612720840.0
+43,1,73,1,1989-06-13 01:30:00,18750.0,34200.0,1989-06-12 16:00:00,613670400.0
+43,2,73,1,1989-06-14 00:47:00,25170.0,34920.0,1989-06-13 15:05:00,613753500.0
+44,1,74,1,1989-07-04 00:18:00,33840.0,27480.0,1989-07-03 16:40:00,615487200.0
+44,2,74,1,1989-07-04 23:55:00,29250.0,31320.0,1989-07-04 15:13:00,615568380.0
+45,1,66,1,1990-03-13 00:26:00,33960.0,31860.0,1990-03-12 15:35:00,637256100.0
+45,2,66,1,1990-03-14 00:34:00,32820.0,33900.0,1990-03-13 15:09:00,637340940.0
+46,1,66,1,1990-03-29 00:30:00,25950.0,32280.0,1990-03-28 15:32:00,638638320.0
+46,2,66,1,1990-03-30 00:38:00,26910.0,36180.0,1990-03-29 14:35:00,638721300.0
+47,1,73,1,1990-03-14 22:36:00,29670.0,25260.0,1990-03-14 15:35:00,637428900.0
+47,2,73,1,1990-03-15 22:25:00,54570.0,26400.0,1990-03-15 15:05:00,637513500.0
+48,1,67,1,1990-07-13 23:04:00,58590.0,26940.0,1990-07-13 15:35:00,647883300.0
+48,2,67,1,1990-07-14 23:57:00,53490.0,29220.0,1990-07-14 15:50:00,647970600.0
+49,1,67,1,1991-11-27 23:26:00,29670.0,29460.0,1991-11-27 15:15:00,691254900.0
+49,2,67,1,1991-11-29 00:13:00,28140.0,33180.0,1991-11-28 15:00:00,691340400.0
+50,1,71,2,1989-05-01 22:07:00,37470.0,20520.0,1989-05-01 16:25:00,610043100.0
+50,2,71,2,1989-05-02 23:40:00,30570.0,27600.0,1989-05-02 16:00:00,610128000.0
+51,1,70,2,1989-05-31 23:10:00,29370.0,24360.0,1989-05-31 16:24:00,612635040.0
+51,2,70,2,1989-06-02 00:03:00,25710.0,30180.0,1989-06-01 15:40:00,612718800.0
+52,2,69,2,1989-07-04 23:53:00,26700.0,31560.0,1989-07-04 15:07:00,615568020.0
+53,1,67,2,1989-07-10 23:49:00,29670.0,25500.0,1989-07-10 16:44:00,616092240.0
+53,2,67,2,1989-07-11 23:53:00,28140.0,32040.0,1989-07-11 14:59:00,616172340.0
+54,1,73,2,1990-03-12 23:00:00,37470.0,26400.0,1990-03-12 15:40:00,637256400.0
+54,2,73,2,1990-03-13 23:30:00,36570.0,30600.0,1990-03-13 15:00:00,637340400.0
+55,1,71,2,1990-03-14 22:40:00,29040.0,25980.0,1990-03-14 15:27:00,637428420.0
+55,2,71,2,1990-03-15 22:29:00,26730.0,27240.0,1990-03-15 14:55:00,637512900.0
+56,1,72,2,1990-06-06 23:14:00,33210.0,26760.0,1990-06-06 15:48:00,644687280.0
+56,2,72,2,1990-06-07 23:22:00,29940.0,30720.0,1990-06-07 14:50:00,644770200.0
+57,1,66,2,1990-07-13 23:02:00,34200.0,26820.0,1990-07-13 15:35:00,647883300.0
+57,2,66,2,1990-07-14 23:51:00,29940.0,29760.0,1990-07-14 15:35:00,647969700.0
+58,1,67,2,1991-09-09 22:36:00,29940.0,25740.0,1991-09-09 15:27:00,684430020.0
+58,2,67,2,1991-09-10 23:04:00,32610.0,28860.0,1991-09-10 15:03:00,684514980.0
+59,1,67,2,1991-11-27 23:25:00,51420.0,28500.0,1991-11-27 15:30:00,691255800.0
+59,2,67,2,1991-11-29 00:14:00,29220.0,31140.0,1991-11-28 15:35:00,691342500.0
+60,1,89,1,1989-09-04 21:35:00,38820.0,19800.0,1989-09-04 16:05:00,620928300.0
+60,2,89,1,1989-09-15 23:00:00,31770.0,28800.0,1989-09-15 15:00:00,621874800.0
+61,1,101,1,1989-09-07 00:20:00,30270.0,28200.0,1989-09-06 16:30:00,621102600.0
+61,2,101,1,1989-09-08 01:00:00,24810.0,36000.0,1989-09-07 15:00:00,621183600.0
+62,1,95,1,1989-11-21 21:00:00,38580.0,16440.0,1989-11-21 16:26:00,627668760.0
+62,2,95,1,1989-11-23 21:00:00,51060.0,23160.0,1989-11-23 14:34:00,627834840.0
+63,1,91,1,1989-11-21 00:15:00,26670.0,32340.0,1989-11-20 15:16:00,627578160.0
+63,2,91,1,1989-11-21 23:39:00,28350.0,32640.0,1989-11-21 14:35:00,627662100.0
+64,1,85,1,1989-10-23 22:30:00,35310.0,24000.0,1989-10-23 15:50:00,625161000.0
+64,2,85,1,1989-10-24 22:17:00,34530.0,27720.0,1989-10-24 14:35:00,625242900.0
+65,1,88,1,1989-11-06 23:10:00,45600.0,31500.0,1989-11-06 14:25:00,626365500.0
+65,2,88,1,1989-11-07 23:00:00,34440.0,30000.0,1989-11-07 14:40:00,626452800.0
+66,1,88,1,1989-11-27 21:52:00,59220.0,18900.0,1989-11-27 16:37:00,628187820.0
+66,2,88,1,1989-11-28 21:56:00,57450.0,24660.0,1989-11-28 15:05:00,628268700.0
+67,1,87,1,1991-08-07 22:49:00,56820.0,24540.0,1991-08-07 16:00:00,681580800.0
+67,2,87,1,1991-08-08 23:52:00,29160.0,29820.0,1991-08-08 15:35:00,681665700.0
+70,1,89,2,1989-09-20 21:40:00,34170.0,20700.0,1989-09-20 15:55:00,622310100.0
+70,2,89,2,1989-09-21 21:39:00,27180.0,25260.0,1989-09-21 14:38:00,622391880.0
+71,1,88,2,1989-09-26 21:15:00,37590.0,20400.0,1989-09-26 15:35:00,622827300.0
+71,2,88,2,1989-09-27 23:18:00,25410.0,31080.0,1989-09-27 14:40:00,622910400.0
+72,1,88,2,1989-10-05 23:04:00,28140.0,28860.0,1989-10-05 15:03:00,623602980.0
+72,2,88,2,1989-10-04 23:09:00,31530.0,26700.0,1989-10-04 15:44:00,623519040.0
+73,1,97,2,1989-10-11 22:30:00,56040.0,27300.0,1989-10-11 14:55:00,624120900.0
+73,2,97,2,1989-10-12 22:00:00,48360.0,27000.0,1989-10-12 14:30:00,624205800.0
+74,1,92,2,1989-10-09 23:14:00,51990.0,26640.0,1989-10-09 15:50:00,623951400.0
+74,2,92,2,1989-10-10 23:06:00,28440.0,30360.0,1989-10-10 14:40:00,624033600.0
+75,1,96,2,1989-10-25 22:58:00,53670.0,25380.0,1989-10-25 15:55:00,625334100.0
+75,2,96,2,1989-10-26 23:00:00,28020.0,29700.0,1989-10-26 14:45:00,625416300.0
+76,1,90,2,1989-11-13 23:28:00,38970.0,24780.0,1989-11-13 16:35:00,626978100.0
+76,2,90,2,1989-11-15 01:29:00,45120.0,38640.0,1989-11-14 14:45:00,627057900.0
+77,1,85,2,1991-10-21 23:23:00,37620.0,28560.0,1991-10-21 15:27:00,688058820.0
+77,2,85,2,1991-10-23 00:10:00,29220.0,32640.0,1991-10-22 15:06:00,688143960.0
+80,1,54,1,1991-09-16 23:05:00,36480.0,27900.0,1991-09-16 15:20:00,685034400.0
+80,2,54,1,1991-09-17 23:18:00,35250.0,30180.0,1991-09-17 14:55:00,685119300.0
+81,1,57,1,1991-09-23 22:00:00,28740.0,24180.0,1991-09-23 15:17:00,685639020.0
+81,2,57,1,1991-09-24 21:56:00,29850.0,34500.0,1991-09-24 12:21:00,685714860.0
+82,1,56,1,1991-09-25 23:59:00,27330.0,31200.0,1991-09-25 15:19:00,685811940.0
+82,2,56,1,1991-09-27 00:05:00,28650.0,32700.0,1991-09-26 15:00:00,685897200.0
diff --git a/ai/data/subject44-night1/SC4441EC-Hypnogram.edf b/ai/data/subject44-night1/SC4441EC-Hypnogram.edf
new file mode 100644
index 00000000..5b8c497f
Binary files /dev/null and b/ai/data/subject44-night1/SC4441EC-Hypnogram.edf differ
diff --git a/ai/data/subject44-night1/electrophysiologist_Hypnogram.edf b/ai/data/subject44-night1/electrophysiologist_Hypnogram.edf
new file mode 100644
index 00000000..06a2fa20
Binary files /dev/null and b/ai/data/subject44-night1/electrophysiologist_Hypnogram.edf differ
diff --git a/ai/data/williamharvey-night1/william-hypnogram.edf b/ai/data/williamharvey-night1/william-hypnogram.edf
new file mode 100644
index 00000000..052c39fd
Binary files /dev/null and b/ai/data/williamharvey-night1/william-hypnogram.edf differ
diff --git a/ai/data/williamharvey-night1/william-recording.edf b/ai/data/williamharvey-night1/william-recording.edf
new file mode 100644
index 00000000..b0ed34f8
Binary files /dev/null and b/ai/data/williamharvey-night1/william-recording.edf differ
diff --git a/ai/prediction_anonymous.ipynb b/ai/prediction_anonymous.ipynb
index 7acd60c3..028b0bb1 100644
--- a/ai/prediction_anonymous.ipynb
+++ b/ai/prediction_anonymous.ipynb
@@ -18,9 +18,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The autoreload extension is already loaded. To reload it, use:\n",
+      "  %reload_ext autoreload\n"
+     ]
+    }
+   ],
    "source": [
     "%load_ext autoreload\n",
     "%autoreload 2"
@@ -28,7 +37,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -56,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -72,7 +81,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -146,13 +155,13 @@
        "1          25620.0  1989-04-25 14:50:00           609519000.0  "
       ]
      },
-     "execution_count": 4,
+     "execution_count": 9,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "df_records = pd.read_csv(\"data/recordings-info.csv\")\n",
+    "df_records = pd.read_csv(\"./data/recordings-info.csv\")\n",
     "df_records.head(2)"
    ]
   },
@@ -166,7 +175,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -222,7 +231,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -230,7 +239,7 @@
      "output_type": "stream",
      "text": [
       "Using default location ~/mne_data for PHYSIONET_SLEEP...\n",
-      "[['/home/william/mne_data/physionet-sleep-data/SC4441E0-PSG.edf', '/home/william/mne_data/physionet-sleep-data/SC4441EC-Hypnogram.edf']]\n",
+      "[['/Users/claudiaonorato/mne_data/physionet-sleep-data/SC4441E0-PSG.edf', '/Users/claudiaonorato/mne_data/physionet-sleep-data/SC4441EC-Hypnogram.edf']]\n",
       "    subject  night  age  sex            LightsOff  NightDuration  \\\n",
       "84       44      1   74    1  1989-07-04 00:18:00        33840.0   \n",
       "\n",
@@ -248,21 +257,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
-     "ename": "FileNotFoundError",
-     "evalue": "[Errno 2] No such file or directory: './data/subject44-night1/electrophysiologist_Hypnogram.edf'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
-      "\u001b[0;32m<ipython-input-7-ec25f6799142>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m y_electrophysiologist = get_hypnogram_from_filenames(\n\u001b[0m\u001b[1;32m      2\u001b[0m     \u001b[0mfile_names\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0;34mf\"{FOLDER_NAME}/electrophysiologist_Hypnogram.edf\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0mis_electrophysiologist\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m )\n",
-      "\u001b[0;32m<ipython-input-5-ba8305e4df87>\u001b[0m in \u001b[0;36mget_hypnogram_from_filenames\u001b[0;34m(signal_filename, hypnogram_filename, is_electrophysiologist)\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0mraw_data\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmne\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mio\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_raw_edf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msignal_filename\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mpreload\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstim_channel\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mverbose\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m     \u001b[0mannot\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmne\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_annotations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mhypnogram_filename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0mraw_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_annotations\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannot\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0memit_warning\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/Documents/PolyDossier/PolyCortex/polydodo/classification/.venv/lib/python3.8/site-packages/mne/annotations.py\u001b[0m in \u001b[0;36mread_annotations\u001b[0;34m(fname, sfreq, uint16_codec)\u001b[0m\n\u001b[1;32m    627\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    628\u001b[0m     \u001b[0;32melif\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mendswith\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'edf'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'bdf'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'gdf'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 629\u001b[0;31m         \u001b[0monset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mduration\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdescription\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0m_read_annotations_edf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    630\u001b[0m         \u001b[0monset\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0monset\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    631\u001b[0m         \u001b[0mduration\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mduration\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mdtype\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;32m~/Documents/PolyDossier/PolyCortex/polydodo/classification/.venv/lib/python3.8/site-packages/mne/io/edf/edf.py\u001b[0m in \u001b[0;36m_read_annotations_edf\u001b[0;34m(annotations)\u001b[0m\n\u001b[1;32m   1333\u001b[0m     \u001b[0mpat\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'([+-]\\\\d+\\\\.?\\\\d*)(\\x15(\\\\d+\\\\.?\\\\d*))?(\\x14.*?)\\x14\\x00'\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1334\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1335\u001b[0;31m         \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mannotations\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m'latin-1'\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mannot_file\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1336\u001b[0m             \u001b[0mtriggers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mre\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfindall\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpat\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mannot_file\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1337\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
-      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: './data/subject44-night1/electrophysiologist_Hypnogram.edf'"
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "    subject  night  age  sex            LightsOff  NightDuration  \\\n",
+      "84       44      1   74    1  1989-07-04 00:18:00        33840.0   \n",
+      "\n",
+      "    LightsOffSecond          StartRecord  StartRecordTimestamp  \n",
+      "84          27480.0  1989-07-03 16:40:00           615487200.0  \n"
      ]
     }
    ],
@@ -276,9 +282,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 1440x360 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "plt.rcParams[\"figure.figsize\"] = (20,5)\n",
     "print_hypnogram(\n",
@@ -291,9 +310,45 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Matrice de confusion: \n",
+      " [[407   2   0   0   0]\n",
+      " [ 48  84  51   0   0]\n",
+      " [  9  74 285   0  37]\n",
+      " [  2   2  87   0   0]\n",
+      " [  0   0   0   0 100]]\n",
+      "\n",
+      "\n",
+      "               precision    recall  f1-score   support\n",
+      "\n",
+      "           W       0.87      1.00      0.93       409\n",
+      "          N1       0.52      0.46      0.49       183\n",
+      "          N2       0.67      0.70      0.69       405\n",
+      "          N3       0.00      0.00      0.00        91\n",
+      "         REM       0.73      1.00      0.84       100\n",
+      "\n",
+      "    accuracy                           0.74      1188\n",
+      "   macro avg       0.56      0.63      0.59      1188\n",
+      "weighted avg       0.67      0.74      0.70      1188\n",
+      "\n",
+      "Agreement score (Cohen Kappa):  0.631587265142547\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/claudiaonorato/miniconda3/envs/py3/lib/python3.6/site-packages/sklearn/metrics/_classification.py:1272: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
+      "  _warn_prf(average, modifier, msg_start, len(result))\n"
+     ]
+    }
+   ],
    "source": [
     "print(\"Matrice de confusion: \\n\", confusion_matrix(y_physionet, y_electrophysiologist))\n",
     "\n",
@@ -301,6 +356,13 @@
     "\n",
     "print(\"Agreement score (Cohen Kappa): \", cohen_kappa_score(y_physionet, y_electrophysiologist))"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -319,7 +381,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.2"
+   "version": "3.6.8"
   }
  },
  "nbformat": 4,