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NA	'T'
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NA	'H'
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NA	'T'
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NA	'M'
NA	'M'
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NA	'S'
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9,692766521	'H'
11,57803882	'E'
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NA	'M'
11,90017908	'M'
NA	'T'
9,210340372	'M'
11,62500337	'E'
12,32436222	'M'
10,24558679	'T'
12,59351295	'T'
12,38640055	'E'
10,81977828	'H'
10,49127422	'H'
9,913437883	'H'
10,58405595	'H'
9,846070282	'M'
12,90917016	'H'
10,81679384	'H'
NA	'T'
10,30011371	'T'
11,84730265	'M'
11,53517607	'T'
10,06556388	'S'
9,510444964	'H'
NA	'T'
10,51254635	'T'
10,20032756	'T'
9,910959567	'M'
12,89798907	'T'
14,03302148	'T'
9,210340372	'M'
NA	'M'
9,259130536	'H'
12,46914051	'E'
9,975808214	'E'
9,620859354	'H'
10,37464676	'M'
9,36777138	'E'
NA	'E'
9,98681716	'E'
NA	'E'
11,29009436	'S'
9,630759772	'M'
11,08374127	'H'
9,903487553	'H'
NA	'H'
9,68427377	'M'
NA	'M'
9,210340372	'M'
9,49912184	'T'
10,93310697	'H'
9,249561085	'T'
9,883284845	'H'
10,62132735	'T'
12,68585951	'T'
11,83632694	'H'
NA	'T'
11,01246263	'T'
NA	'T'
9,948317504	'H'
NA	'H'
9,417354541	'H'
12,72121096	'H'
12,96195986	'M'
9,568014816	'T'
9,928180165	'T'
9,563669726	'T'
10,59663473	'M'
10,57041909	'E'
11,6022633	'H'
10,31015194	'T'
10,20359214	'T'
9,398975291	'T'
11,78504964	'E'
10,73203937	'H'
10,98359637	'M'
13,12498993	'E'
11,75978554	'H'
NA	'H'
9,313708905	'M'
11,93034549	'T'
11,17557684	'T'
10,96888771	'M'
12,14718745	'E'
10,80413659	'T'
9,562475024	'M'
10,81977828	'H'
10,67398922	'H'
11,8874639	'H'
10,00595388	'H'
11,8257342	'M'
NA	'M'
11,20854474	'M'
9,618867454	'H'
11,05830688	'T'
11,87059991	'T'
NA	'T'
9,210340372	'T'
10,04324949	'S'
NA	'S'
11,16574813	'H'
NA	'H'
11,39928633	'E'
11,34651663	'T'
10,74926998	'H'
12,05314871	'E'
10,5118935	'T'
NA	'H'
9,742085646	'H'
11,34030866	'M'
10,54534144	'M'
11,88325378	'M'
11,47553508	'H'
11,7905572	'H'
NA	'H'
14,25974756	'T'
11,22524339	'M'
10,70539945	'T'
10,39830574	'T'
12,61271706	'T'
10,00333289	'M'
9,433483923	'T'
NA	'T'
12,54650133	'H'
11,14759892	'H'
NA	'H'
10,1266311	'H'
10,20905866	'H'
9,775654181	'T'
12,10625231	'E'
12,86490526	'T'
9,384629757	'T'
9,733232897	'M'
9,392078425	'M'
11,46163217	'H'
9,928180165	'H'
NA	'H'
10,59663473	'T'
NA	'H'
10,30985226	'T'
11,34918226	'E'
10,51737505	'E'
10,06598898	'H'
9,279213236	'E'
11,00209984	'H'
9,287301413	'M'
11,75665565	'M'
10,4487146	'T'
10,61189274	'H'
10,30895266	'H'
10,81977828	'M'
9,29679326	'T'
10,96950778	'H'
9,82978719	'M'
10,46310334	'M'
NA	'M'
10,98796711	'T'
9,604407435	'T'
11,23321156	'T'
11,47221805	'T'
9,546669741	'E'
NA	'E'
9,46109909	'M'
13,03276466	'H'
10,77726736	'H'
10,81500692	'S'
11,66650455	'H'
NA	'E'
10,9511749	'H'
11,91664238	'H'
9,588708312	'E'
11,25508694	'H'
13,9887981	'T'
10,45036541	'H'
12,29733373	'H'
10,30895266	'M'
9,431241411	'M'
9,519000851	'H'
12,00941278	'H'
9,957028319	'M'
11,62973024	'E'
9,69879768	'H'
9,693877016	'H'
9,585827257	'H'
10,00278975	'E'
11,00209984	'H'
12,46843691	'T'
10,42942836	'T'
NA	'H'
NA	'H'
9,215327913	'M'
9,878169745	'T'
NA	'T'
10,36407196	'H'
12,5021469	'T'
10,30895266	'T'
10,08647555	'M'
9,223552703	'H'
NA	'H'
NA	'E'
11,65054599	'H'
11,44862158	'T'
9,305650552	'H'
NA	'H'
10,08580911	'T'
9,903487553	'H'
NA	'H'
11,09843979	'M'
10,70398577	'H'
9,651301316	'H'
10,0647557	'E'
11,19862559	'T'
10,2065138	'T'
NA	'T'
10,0895521	'T'
12,06870533	'H'
11,05515076	'H'
9,590487672	'E'
9,416541203	'T'
10,59663473	'M'
11,65572626	'S'
9,449357272	'H'
NA	'H'
10,98063784	'M'
10,5971596	'M'
NA	'M'
11,18163976	'E'
11,51292546	'M'
9,463508636	'M'
10,46310334	'T'
9,25598273	'E'
11,31491345	'T'
9,971379819	'M'
NA	'M'
9,853456619	'H'
NA	'H'
NA	'H'
12,41963848	'H'
12,91770786	'M'
9,409191231	'T'
10,58405595	'E'
13,16443579	'T'
9,904487053	'E'
11,46163217	'T'
9,492507264	'M'
10,86666187	'T'
10,04450957	'T'
11,21187442	'E'
11,33881014	'E'
10,33624352	'T'
NA	'T'
11,80312935	'H'
NA	'H'
11,16083997	'H'
10,00784757	'E'
10,41631118	'E'
NA	'T'
NA	'T'
9,702961291	'M'
9,210340372	'M'
9,453286551	'H'
12,60480178	'T'
9,986126886	'T'
12,20607265	'T'
10,66082945	'H'
9,807196892	'E'
9,451716692	'T'
11,93979323	'M'
9,798127037	'M'
9,774687805	'E'
10,28236909	'H'
NA	'H'
9,945684601	'T'
11,13657246	'T'
9,305650552	'E'
9,84686429	'T'
9,717157974	'H'
9,305650552	'H'
NA	'H'
NA	'T'
13,06727341	'H'
10,98529272	'E'
10,73072847	'T'
9,667765219	'T'
12,57374935	'T'
10,4115995	'M'
10,66807128	'M'
10,00802773	'T'
10,55059079	'H'
10,57681461	'H'
10,21603295	'H'
12,20753657	'E'
9,216819338	'M'
12,74256602	'H'
9,338293736	'T'
11,23425599	'M'
10,77895629	'M'
10,39249692	'H'
11,83353687	'H'
10,23995979	'H'
9,210340372	'M'
11,49740565	'H'
10,40426284	'H'
NA	'H'
9,594036922	'H'
NA	'H'
NA	'T'
9,509333236	'T'
9,314880551	'T'
9,541512876	'S'
10,30169304	'T'
9,694308542	'H'
NA	'H'
9,68059397	'T'
NA	'E'
NA	'E'
12,22283143	'E'
11,7486456	'H'
9,275191344	'S'
10,33064892	'T'
13,61598343	'T'
13,54002053	'T'
9,546812609	'E'
11,46163217	'M'
11,00209984	'H'
9,58342002	'H'
11,22524339	'T'
11,54659232	'T'
NA	'T'
12,85723048	'T'
NA	'H'
NA	'H'
9,755045547	'M'
NA	'H'
9,61580548	'T'
10,19046938	'T'
NA	'H'
10,16819522	'H'
10,08776553	'M'
NA	'M'
9,652651581	'M'
9,305650552	'H'
10,30895266	'H'
9,900783901	'M'
11,60423675	'T'
9,61580548	'T'
NA	'T'
11,01287491	'E'
11,56264853	'H'
9,37160852	'T'
NA	'S'
NA	'S'
9,496946866	'H'
10,29214554	'T'
NA	'E'
11,22984612	'T'
12,45980748	'T'
9,70454869	'H'
11,23630202	'T'
NA	'T'
9,210340372	'T'
NA	'H'
NA	'H'
11,72310535	'H'
NA	'H'
10,43429226	'M'
12,28303369	'T'
9,433483923	'H'
NA	'H'
10,31201463	'T'
NA	'H'
NA	'H'
9,521861034	'H'
9,49912184	'T'
10,75930615	'T'
9,502114062	'H'
11,51782345	'M'
10,07314594	'T'
9,850877602	'T'
9,217812387	'M'
9,296518068	'E'
9,477156252	'H'
NA	'H'
NA	'H'
10,05212305	'T'
13,62714034	'H'
11,8244681	'T'
10,64823048	'T'
NA	'T'
9,375346207	'H'
NA	'H'
NA	'H'
NA	'H'
9,573315428	'T'
9,210340372	'T'
NA	'H'
NA	'H'
10,75864728	'E'
11,51292546	'E'
12,0404076	'T'
13,43188424	'E'
10,47956707	'T'
10,01023211	'H'
NA	'H'
10,30895266	'H'
10,29741974	'H'
10,21533771	'H'
NA	'H'
9,461799234	'E'
9,668714136	'H'
NA	'T'
11,78725631	'T'
10,30895266	'M'
10,68230771	'H'
9,392661929	'H'
10,66592756	'H'
9,510444964	'H'
10,02428825	'H'
11,73039696	'H'
10,71014197	'H'
NA	'T'
NA	'T'
10,97671365	'T'
9,449357272	'T'
13,1263554	'T'
10,47294051	'T'
NA	'H'
NA	'H'
10,34174248	'T'
9,643420647	'T'
10,6038834	'M'
NA	'M'
10,40976284	'M'
9,940012327	'M'
10,3609124	'H'
12,10735667	'S'
9,52434787	'E'
11,23733005	'H'
9,521494801	'H'
9,263312257	'S'
NA	'H'
NA	'H'
13,20633681	'E'
10,66024313	'H'
9,969696553	'H'
9,903487553	'T'
9,679093219	'H'
11,5972758	'T'
9,622450023	'M'
12,42592278	'E'
12,24899324	'E'
9,76995616	'T'
11,04404121	'H'
10,0961719	'M'
12,34962739	'H'
10,95778216	'H'
9,903487553	'H'
NA	'H'
9,903487553	'E'
11,14764215	'E'
9,82119231	'T'
9,350015354	'M'
9,98994044	'H'
11,53092254	'M'
NA	'M'
14,02449839	'H'
13,02747011	'H'
9,226705726	'H'
NA	'H'
NA	'M'
11,62029895	'M'
9,588845299	'E'
9,45273738	'E'
11,27754485	'T'
10,35271433	'T'
10,66634735	'T'
10,88177608	'T'
9,964441532	'H'
10,95168336	'H'
NA	'M'
11,27357631	'M'
9,659056522	'M'
10,13277221	'T'
11,50720916	'T'
9,789870826	'T'
9,61580548	'T'
13,20492905	'T'
9,627799925	'T'
11,57105285	'T'
11,76056649	'H'
11,58907136	'T'
9,778151061	'T'
10,37648669	'E'
12,20607265	'T'
9,825526011	'M'
11,04368954	'E'
11,44398259	'T'
10,49562585	'M'
9,903487553	'H'
NA	'H'
9,512369038	'H'
10,1266311	'H'
NA	'H'
9,546812609	'M'
9,908873025	'T'
9,820920829	'M'
10,46310334	'M'
10,40728856	'T'
11,08214255	'M'
NA	'M'
NA	'M'
11,16261593	'T'
9,61580548	'M'
10,7831143	'T'
10,67148707	'E'
11,78291443	'H'
10,98569942	'H'
11,04775812	'H'
10,28636616	'H'
11,68435458	'H'
9,903487553	'H'
11,15988676	'M'
NA	'M'
10,54402478	'M'
11,34864027	'H'
11,62789566	'E'
14,21563141	'T'
9,468851067	'H'
9,46498259	'H'
10,30895266	'T'
NA	'T'
9,715711145	'E'
9,752664663	'H'
10,35894845	'H'
13,23730683	'T'
10,55968544	'E'
11,06352414	'H'
9,322418275	'H'
9,61580548	'M'
NA	'M'
10,80012645	'E'
9,210340372	'H'
10,79133766	'H'
12,5287719	'H'
10,17473532	'M'
NA	'T'
9,504873919	'T'
9,71111566	'T'
10,45042329	'T'
NA	'E'
10,98529272	'E'
10,56134429	'T'
NA	'H'
NA	'H'
9,897268253	'H'
9,488199355	'H'
9,29118276	'H'
11,78699784	'M'
9,703388916	'E'
11,65268741	'H'
9,798127037	'T'
9,546812609	'T'
NA	'T'
9,392661929	'H'
NA	'H'
NA	'H'
9,328123408	'E'
9,579003174	'M'
9,396819939	'T'
14,48285109	'M'
NA	'T'
9,779736745	'T'
9,221577004	'H'
10,89094479	'H'
NA	'H'
10,56359488	'H'
11,23056255	'T'
9,772125234	'H'
NA	'H'
9,392661929	'M'
NA	'M'
11,66514857	'S'
9,280052984	'E'
11,15806316	'T'
12,20899338	'T'
9,37585481	'H'
9,210340372	'H'
9,680344001	'M'
9,951467865	'T'
NA	'T'
10,40728856	'S'
11,23848862	'T'
10,23458825	'T'
10,14435314	'M'
9,823578169	'H'
9,736369829	'H'
9,297251744	'H'
9,86526634	'H'
9,809176873	'T'
9,380336279	'E'
10,59663473	'H'
NA	'H'
10,56553099	'M'
NA	'M'
NA	'M'
9,656947423	'H'
13,17718295	'M'
10,81977828	'H'
10,59663473	'H'
9,740968623	'H'
12,06976025	'T'
10,25878154	'M'
9,392661929	'M'
12,86416502	'T'
NA	'M'
9,37160852	'M'
NA	'M'
9,433483923	'M'
NA	'M'
11,08572075	'H'
9,574636203	'M'
9,585277542	'E'
9,520395295	'S'
NA	'S'
10,49819466	'M'
10,01873404	'T'
9,60238246	'M'
12,37123957	'E'
11,96146283	'T'
10,3205518	'H'
NA	'H'
NA	'E'
NA	'T'
NA	'T'
11,2185544	'T'
NA	'T'
NA	'H'
11,08214255	'H'
NA	'H'
12,03486905	'T'
11,41254143	'M'
9,369734424	'E'
NA	'E'
11,28978191	'E'
11,76756768	'T'
9,729134165	'T'
9,875448096	'T'
12,21602298	'M'
11,81303006	'M'
9,903487553	'T'
NA	'T'
9,739673667	'H'
9,758692968	'M'
9,414504957	'T'
10,22918769	'M'
9,860057995	'H'
12,07537153	'H'
NA	'H'
10,02127059	'H'
10,62132735	'H'
12,2932086	'M'
10,18338944	'T'
10,858999	'E'
9,553930076	'M'
9,909071931	'S'
9,5965547	'S'
NA	'S'
9,903487553	'T'
9,825526011	'H'
9,215327913	'H'
9,238247325	'M'
NA	'M'
11,49786259	'T'
10,76983145	'T'
9,480367509	'T'
10,71007502	'T'
NA	'T'
11,17234882	'H'
10,69686461	'H'
10,81452451	'H'
9,76995616	'M'
10,30209587	'T'
10,74656222	'E'
11,09331072	'H'
9,487972109	'T'
9,472704636	'T'
11,81303006	'T'
9,80642584	'H'
10,08580911	'H'
10,89942091	'T'
10,14643373	'E'
11,52936952	'T'
NA	'T'
12,53148393	'H'
9,339436945	'T'
11,00209984	'M'
11,95413088	'S'
14,33705829	'T'
10,45558947	'M'
9,771212513	'H'
9,251866119	'H'
9,409191231	'M'
9,210340372	'H'
NA	'H'
10,03889219	'H'
10,6454249	'T'
NA	'H'
NA	'H'
9,991544216	'T'
10,00056889	'E'
9,277064004	'H'
9,277064004	'H'
NA	'M'
11,53607542	'T'
10,65242415	'M'
11,22524339	'E'
10,46310334	'H'
NA	'H'
NA	'H'
NA	'H'
9,409191231	'E'
11,52832626	'T'
NA	'T'
9,210340372	'M'
11,19747472	'H'
12,80856181	'H'
10,83958091	'H'
13,25685406	'T'
9,494616651	'T'
9,848450417	'T'
9,704426672	'T'
9,794174793	'T'
11,51292546	'H'
9,586376669	'T'
11,03438954	'H'
9,653614941	'H'
9,937599082	'H'
NA	'H'
10,50386133	'T'
NA	'T'
10,09481014	'H'
NA	'H'
10,69507637	'H'
NA	'H'
13,37721333	'T'
10,50916871	'E'
9,396902923	'H'
10,05190756	'M'
12,76568843	'H'
12,62303474	'H'
9,798127037	'H'
NA	'H'
11,97736364	'T'
11,31447453	'T'
9,210340372	'M'
NA	'T'
10,13197679	'H'
11,00209984	'M'
9,309914177	'H'
10,73639668	'T'
9,994241916	'E'
NA	'E'
10,46310334	'T'
10,38899537	'T'
9,210340372	'E'
NA	'E'
10,21950195	'H'
NA	'H'
10,46027076	'E'
9,660013735	'T'
10,3829773	'H'
10,24288408	'H'
9,59096619	'S'
NA	'S'
9,722025626	'H'
NA	'H'
NA	'H'
NA	'H'
9,358760377	'E'
10,81404186	'E'
10,04706828	'H'
10,60164715	'T'
10,59663473	'H'
NA	'H'
10,36407196	'T'
9,798127037	'T'
NA	'T'
9,225031921	'H'
9,323669057	'T'
NA	'T'
10,1266311	'H'
NA	'H'
NA	'M'
NA	'M'
11,4870947	'T'
NA	'T'
NA	'T'
9,328834266	'H'
9,70320567	'H'
NA	'H'
10,85185818	'H'
11,01862914	'H'
9,466763949	'T'
11,61728548	'T'
12,13951609	'E'
11,30116686	'T'
11,21188794	'T'
9,732817848	'H'
9,410092464	'M'
12,02694598	'T'
11,50967017	'H'
9,220290703	'H'
10,66352206	'T'
9,667765219	'H'
9,210340372	'H'
13,30867364	'T'
10,29194213	'H'
NA	'H'
10,9252188	'T'
10,57339169	'H'
9,975808214	'T'
10,30895266	'H'
9,710751957	'T'
9,358760377	'M'
9,83397669	'T'
9,643939319	'M'
11,26735735	'T'
NA	'T'
10,50089446	'M'
10,6454249	'M'
NA	'E'
9,502636782	'M'
11,6324847	'H'
11,29266525	'T'
10,48570317	'H'
NA	'H'
12,8346813	'T'
11,07168809	'T'
9,628392596	'H'
10,92649588	'M'
10,1266311	'H'
10,54428825	'E'
NA	'T'
9,463586267	'M'
NA	'M'
10,86856845	'T'
NA	'T'
11,35040654	'T'
10,85166447	'M'
13,56061831	'T'
9,917143879	'H'
11,33377488	'T'
13,65308457	'E'
12,92070241	'T'
11,58603651	'T'
10,858999	'T'
9,210340372	'M'
13,05978134	'M'
10,23995979	'H'
9,648595303	'H'
10,81142348	'T'
9,726034127	'H'
11,55469101	'M'
10,05625156	'H'
NA	'H'
12,21602298	'T'
NA	'H'
NA	'H'
NA	'H'
NA	'E'
10,63103616	'T'
9,28126471	'T'
9,893437217	'E'
10,1064284	'H'
10,1064284	'H'
9,27799902	'E'
11,31630212	'T'
10,94876939	'H'
9,517236663	'T'
12,02972322	'H'
10,1266311	'T'
12,56374709	'H'
9,827685839	'T'
NA	'T'
NA	'T'
10,32744724	'E'
NA	'E'
10,60539624	'T'
NA	'T'
9,210340372	'T'
NA	'T'
10,30895266	'T'
NA	'T'
11,48408351	'E'
13,38472764	'E'
9,392661929	'M'
NA	'M'
9,635608107	'E'
10,46021345	'T'
11,02100337	'T'
12,64863763	'E'
9,581903928	'M'
10,80567936	'T'
NA	'T'
9,46498259	'T'
9,753594463	'T'
9,717398909	'T'
9,61580548	'M'
9,694431801	'M'
9,210340372	'M'
NA	'M'
9,230142999	'M'
NA	'M'
9,436997743	'E'
NA	'T'
9,61580548	'H'
9,392661929	'H'
10,49548755	'E'
11,47525475	'S'
10,20894815	'T'
10,1266311	'H'
NA	'H'
9,667765219	'M'
10,27832162	'M'
NA	'M'
11,81175517	'M'
10,49703537	'T'
9,66516691	'E'
NA	'E'
12,05054101	'M'
10,73761333	'M'
11,38625051	'M'
9,540938245	'H'
NA	'H'
9,29468152	'H'
10,04324949	'T'
10,76553327	'H'
10,25590344	'S'
10,19854238	'H'
9,715711145	'H'
9,784140795	'M'
10,6454249	'T'
9,903487553	'T'
NA	'H'
9,61580548	'H'
12,84345867	'E'
12,87798342	'E'
9,798127037	'M'
9,852194258	'E'
NA	'E'
10,63648025	'E'
9,392661929	'M'
9,687195476	'H'
NA	'H'
11,00589264	'H'
9,210340372	'H'
9,372033961	'T'
9,546812609	'T'
NA	'T'
9,305650552	'T'
NA	'T'
9,851615143	'M'
10,46626975	'E'
NA	'T'
9,935325309	'S'
NA	'S'
12,77379548	'T'
10,29458325	'E'
10,54534144	'M'
10,66888562	'S'
9,61580548	'S'
10,77128108	'M'
9,621456152	'H'
NA	'H'
11,1861976	'M'
9,239899174	'M'
11,46268425	'H'
14,06544949	'E'
NA	'M'
12,82233878	'H'
9,38890488	'E'
9,665674427	'H'
13,00792848	'T'
11,51292546	'H'
9,514879561	'E'
NA	'E'
10,82637647	'T'
9,998706819	'T'
9,510444964	'T'
11,58742979	'T'
10,37349118	'M'
10,80035079	'T'
NA	'T'
12,09514108	'T'
10,13400386	'T'
NA	'T'
13,13429195	'M'
NA	'E'
9,323669057	'T'
13,48882705	'E'
9,354094336	'H'
NA	'H'
9,435721418	'H'
9,732402628	'E'
NA	'M'
NA	'M'
10,91412436	'T'
9,862665558	'H'
9,639326675	'M'
NA	'M'
11,06866755	'M'
9,724001971	'H'
11,32653564	'H'
NA	'H'
13,29719193	'H'
10,01663765	'H'
NA	'H'
11,30936393	'H'
NA	'H'
9,86526634	'H'
NA	'H'
10,13559085	'H'
9,648595303	'H'
11,67717639	'T'
11,00209984	'H'
10,06734808	'T'
13,26057978	'T'
11,20638672	'T'
10,30895266	'T'
9,259130536	'E'
11,66540618	'H'
10,29231502	'S'
NA	'S'
10,37349118	'H'
NA	'H'
10,6454249	'T'
12,04920244	'H'
NA	'H'
9,629182277	'S'
NA	'S'
9,312535884	'M'
9,910860307	'S'
9,699472382	'S'
11,62204889	'T'
10,49182962	'E'
9,798127037	'H'
11,47626148	'M'
9,259130536	'H'
10,46310334	'E'
9,220290703	'E'
10,16761948	'E'
13,27206876	'E'
9,778547718	'H'
10,43373338	'E'
10,90595598	'T'
13,80984956	'M'
11,77608172	'M'
9,236008119	'M'
9,343033914	'T'
NA	'M'
NA	'M'
NA	'T'
NA	'H'
12,70015895	'T'
NA	'T'
11,53105021	'H'
9,942323576	'H'
11,75665565	'T'
9,72853875	'M'
11,01039864	'T'
10,04102964	'M'
9,358070484	'H'
9,258368341	'M'
12,27839331	'M'
10,24835304	'H'
NA	'H'
NA	'H'
11,30913101	'T'
9,835529859	'S'
11,60823564	'M'
9,385889044	'S'
9,61580548	'H'
NA	'H'
11,28978191	'H'
11,08214255	'T'
12,0179342	'T'
11,13377117	'T'
10,85849887	'S'
9,96697865	'T'
9,754813515	'H'
NA	'H'
10,22201401	'H'
10,04324949	'M'
11,39196614	'H'
10,22012145	'H'
NA	'H'
10,8406	'H'
9,211939093	'M'
13,35679814	'E'
11,68813848	'M'

par3 <- 'TRUE'
par2 <- '2'
par1 <- '1'
cat1 <- as.numeric(par1) #
cat2<- as.numeric(par2) #
intercept<-as.logical(par3)
x <- t(x)
x1<-as.numeric(x[,cat1])
f1<-as.character(x[,cat2])
xdf<-data.frame(x1,f1)
(V1<-dimnames(y)[[1]][cat1])
(V2<-dimnames(y)[[1]][cat2])
names(xdf)<-c('Response', 'Treatment')
if(intercept == FALSE) (lmxdf<-lm(Response ~ Treatment - 1, data = xdf) ) else (lmxdf<-lm(Response ~ Treatment, data = xdf) )
(aov.xdf<-aov(lmxdf) )
(anova.xdf<-anova(lmxdf) )
load(file='createtable')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Model', length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, paste(V1, ' ~ ', V2), length(lmxdf$coefficients)+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'means',,TRUE)
for(i in 1:length(lmxdf$coefficients)){
a<-table.element(a, round(lmxdf$coefficients[i], digits=3),,FALSE)
}
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'ANOVA Statistics', 5+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ',,TRUE)
a<-table.element(a, 'Df',,FALSE)
a<-table.element(a, 'Sum Sq',,FALSE)
a<-table.element(a, 'Mean Sq',,FALSE)
a<-table.element(a, 'F value',,FALSE)
a<-table.element(a, 'Pr(>F)',,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, V2,,TRUE)
a<-table.element(a, anova.xdf$Df[1],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'F value'[1], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Pr(>F)'[1], digits=3),,FALSE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, 'Residuals',,TRUE)
a<-table.element(a, anova.xdf$Df[2],,FALSE)
a<-table.element(a, round(anova.xdf$'Sum Sq'[2], digits=3),,FALSE)
a<-table.element(a, round(anova.xdf$'Mean Sq'[2], digits=3),,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.element(a, ' ',,FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable1.tab')
bitmap(file='anovaplot.png')
boxplot(Response ~ Treatment, data=xdf, xlab=V2, ylab=V1)
dev.off()
if(intercept==TRUE){
'Tukey Plot'
thsd<-TukeyHSD(aov.xdf)
bitmap(file='TukeyHSDPlot.png')
plot(thsd)
dev.off()
}
if(intercept==TRUE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Tukey Honest Significant Difference Comparisons', 5,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a, ' ', 1, TRUE)
for(i in 1:4){
a<-table.element(a,colnames(thsd[[1]])[i], 1, TRUE)
}
a<-table.row.end(a)
for(i in 1:length(rownames(thsd[[1]]))){
a<-table.row.start(a)
a<-table.element(a,rownames(thsd[[1]])[i], 1, TRUE)
for(j in 1:4){
a<-table.element(a,round(thsd[[1]][i,j], digits=3), 1, FALSE)
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
if(intercept==FALSE){
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'TukeyHSD Message', 1,TRUE)
a<-table.row.end(a)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Must Include Intercept to use Tukey Test ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable2.tab')
}
library(car)
lt.lmxdf<-leveneTest(lmxdf)
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Levenes Test for Homogeneity of Variance', 4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
for (i in 1:3){
a<-table.element(a,names(lt.lmxdf)[i], 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Group', 1, TRUE)
for (i in 1:3){
a<-table.element(a,round(lt.lmxdf[[i]][1], digits=3), 1, FALSE)
}
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ', 1, TRUE)
a<-table.element(a,lt.lmxdf[[1]][2], 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.element(a,' ', 1, FALSE)
a<-table.row.end(a)
a<-table.end(a)
table.save(a,file='mytable3.tab')