Index: pcyl_Kfun.cpp
===================================================================
--- Capcyl_Kfun.cpp	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,15 +1,0 @@
-real ConvLens_kernel(real len, real rad, real endRad, real x, real tt, real theta)
-{
-    real be = 0;
-	real hDist = -1.0*sqrt(fabs(endRad*endRad-rad*rad));
-	real arg1 = x*cos(theta)*(endRad*tt+hDist+len/2.0);
-	real arg2 = x*endRad*sin(theta)*sqrt(1.0-tt*tt);
-
-	if(arg2 == 0) {be = 0.5;}
-	else {
-		be = NR_BessJ1(arg2)/arg2;
-	}
-	real val = cos(arg1)*(1.0-tt*tt)*be;
-
-	return(val);
-}
Index: C07084.DAT
===================================================================
--- DEC07084.DAT	(revision 79fcc4062b8d89e414a4ff08dded369f28b31be4)
+++ 	(revision )
@@ -1,16403 +1,0 @@
-FILE: Dec07084.SA2_LP _P375   CREATED: Wed, Jul 16, 2014 11:17:56 AM
-LABEL: Tan scatt sample 3011-1 0Hz                                 
-MON CNT   LAMBDA (A)  DET_OFF(cm)   DET_DIST(m)   TRANS   THICK(cm)
-1e+08  6       15     14.547     0.21545     0.1
-BCENT(X,Y)   A1(mm)   A2(mm)   A1A2DIST(m)   DL/L   BSTOP(mm)   DET_TYP  
-94.7  63.04  38    12.7    15.727    0.124    76.2    ORNL  
-SAM: Dec07084.SA2_LP _P375
-BGD: DEC07039.SA2_LP_P330,
-EMP: DEC07135.SA2_LP_P426,
-DIV: PLEX_02NOV2007_NG7.DIV,
-MASK: DEFAULT_NOV2007.MASK,
-ABS Parameters (3-6): TSTAND=1;DSTAND=1;IZERO=66.639;XSECT=1;SDEV=0.38591
-Average Choices: AVTYPE=QxQy_ASCII;SAVE=Yes;NAME=Auto;PLOT=Yes;
-
-*** Data written from ABS folder and may not be a fully corrected data file ***
-Data columns are Qx - Qy - I(Qx,Qy) - err(I) - Qz - SigmaQ_parall - SigmaQ_perp - fSubS(beam stop shadow)
-Error wave is properly propagated through all reduction steps 8/2011
-ASCII data created Wed, Jul 16, 2014 11:17:56 AM
-
--0.033700895	-0.022313805	20.455286	12.023424	0.00078030414	0.0022246654	0.00078542141	1
--0.033341594	-0.022314051	11.612531	9.4682322	0.00076879945	0.0022108171	0.00078544591	1
--0.032982279	-0.022314293	19.243776	12.059004	0.00075741782	0.0021970314	0.00078547018	1
--0.032622956	-0.022314534	15.173979	11.020971	0.00074615929	0.0021833098	0.00078549405	1
--0.032263618	-0.022314772	14.433326	10.764729	0.00073502387	0.0021696531	0.00078551762	1
--0.031904269	-0.022315007	16.30975	11.114478	0.00072401151	0.0021560628	0.00078554085	1
--0.031544913	-0.022315238	14.578104	10.602077	0.00071312231	0.0021425399	0.00078556361	1
--0.031185541	-0.022315469	7.3731956	8.4802599	0.00070235622	0.0021290858	0.00078558596	1
--0.030826161	-0.022315696	17.891489	11.359548	0.00069171324	0.002115702	0.00078560784	1
--0.030466767	-0.022315919	10.409319	9.4676542	0.00068119343	0.0021023897	0.00078562927	1
--0.030107364	-0.022316141	17.569141	11.35936	0.00067079678	0.00208915	0.0007856501	1
--0.029747952	-0.022316361	21.389107	12.058284	0.00066052331	0.0020759846	0.00078567042	1
--0.029388526	-0.022316577	18.662199	11.359227	0.00065037305	0.0020628949	0.00078569015	1
--0.029029092	-0.022316791	18.488319	11.597904	0.00064034591	0.002049882	0.00078570918	1
--0.028669648	-0.022317002	11.7249	9.7671185	0.00063044205	0.0020369478	0.00078572758	1
--0.028310193	-0.02231721	7.1453853	8.5440969	0.00062066136	0.0020240934	0.00078574521	1
--0.027950728	-0.022317417	10.055431	9.4671268	0.0006110039	0.0020113206	0.00078576209	1
--0.027591253	-0.02231762	13.728639	10.697477	0.00060146966	0.0019986306	0.00078577816	1
--0.027231768	-0.022317819	15.259146	10.861038	0.0005920587	0.0019860254	0.00078579335	1
--0.026872274	-0.022318019	21.629978	12.420154	0.00058277097	0.0019735065	0.00078580761	1
--0.02651277	-0.022318214	12.884902	10.551178	0.00057360652	0.0019610752	0.00078582094	1
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--0.025793735	-0.022318596	12.288017	10.054572	0.00055564742	0.0019364831	0.00078584446	1
--0.025434203	-0.022318784	20.799929	12.362379	0.00054685283	0.0019243255	0.00078585453	1
--0.025074663	-0.022318969	16.508194	10.86052	0.00053818151	0.0019122625	0.00078586338	1
--0.024715113	-0.022319151	14.585339	11.155746	0.00052963349	0.001900296	0.000785871	1
--0.024355555	-0.022319332	18.395147	11.745345	0.00052120886	0.0018884277	0.00078587729	1
--0.023995988	-0.022319509	11.896608	9.7660379	0.00051290751	0.0018766593	0.00078588218	1
--0.023636412	-0.022319682	11.921181	9.7659492	0.00050472951	0.001864993	0.00078588561	1
--0.023276828	-0.022319853	10.595659	9.4660721	0.00049667485	0.0018534305	0.00078588753	1
--0.022917237	-0.022320023	15.796764	10.859891	0.00048874354	0.0018419739	0.00078588782	1
--0.022557637	-0.02232019	13.962336	10.384347	0.00048093559	0.0018306248	0.00078588643	1
--0.022198029	-0.022320354	14.476873	10.59973	0.00047325104	0.0018193854	0.00078588323	1
--0.021838414	-0.022320515	13.33726	10.331252	0.00046568984	0.0018082578	0.00078587822	1
--0.021478789	-0.022320673	17.106207	11.556253	0.00045825206	0.0017972437	0.00078587123	1
--0.021119159	-0.022320829	9.9872398	9.5231924	0.00045093766	0.0017863456	0.00078586221	1
--0.020759519	-0.022320982	8.9472027	9.2638111	0.00044374666	0.0017755653	0.00078585115	1
--0.020399874	-0.022321133	12.43563	10.053162	0.00043667908	0.0017649051	0.00078583782	1
--0.020040222	-0.022321282	9.6123085	9.1522465	0.00042973494	0.0017543669	0.00078582222	1
--0.01968056	-0.022321427	16.457386	10.858951	0.00042291419	0.0017439531	0.00078580418	1
--0.019320892	-0.022321569	12.608366	10.107185	0.00041621688	0.0017336657	0.00078578369	1
--0.018961219	-0.02232171	10.238747	9.6465912	0.00040964302	0.0017235072	0.00078576058	1
--0.018601539	-0.022321848	10.751271	9.4648628	0.00040319262	0.0017134796	0.0007857348	1
--0.018241851	-0.022321982	15.159501	10.598575	0.00039686568	0.0017035853	0.00078570622	1
--0.017882157	-0.022322115	13.829176	10.382981	0.00039066217	0.0016938264	0.00078567473	1
--0.017522456	-0.022322245	17.774021	11.35567	0.00038458215	0.0016842055	0.00078564021	1
--0.01716275	-0.022322372	10.92201	9.4644661	0.00037862561	0.0016747246	0.00078560255	1
--0.016803037	-0.022322496	8.5517073	9.3975306	0.00037279254	0.0016653863	0.00078556169	1
--0.01644332	-0.022322617	11.536099	9.7639608	0.00036708295	0.0016561928	0.00078551751	1
--0.016083594	-0.022322737	11.051029	9.464159	0.00036149687	0.0016471467	0.00078546983	1
--0.015723865	-0.022322852	15.559906	11.016315	0.00035603429	0.0016382501	0.00078541867	1
--0.01536413	-0.022322968	7.0893722	8.6791582	0.00035069519	0.0016295054	0.00078536384	1
--0.015004389	-0.022323078	13.067456	10.051567	0.00034547964	0.0016209153	0.00078530516	1
--0.014644642	-0.022323187	14.043894	10.329087	0.00034038757	0.001612482	0.00078524271	1
--0.014284891	-0.022323292	11.930279	9.7633123	0.00033541906	0.001604208	0.00078517623	1
--0.013925134	-0.022323396	14.483725	10.328864	0.00033057405	0.0015960956	0.00078510569	1
--0.013565373	-0.022323497	10.962592	9.4634018	0.00032585257	0.0015881475	0.00078503095	1
--0.013205606	-0.022323595	7.6466212	8.4762678	0.00032125463	0.0015803658	0.00078495196	1
--0.012845836	-0.02232369	10.835062	9.4631739	0.00031678024	0.0015727532	0.00078486861	1
--0.01248606	-0.022323783	6.910121	8.6783628	0.00031242939	0.001565312	0.00078478077	1
--0.012126281	-0.022323873	8.8942318	8.8218803	0.00030820211	0.0015580446	0.00078468845	1
--0.011766496	-0.02232396	18.648195	11.353612	0.00030409836	0.0015509535	0.00078459154	1
--0.011406708	-0.022324046	8.9809561	8.8216686	0.00030011818	0.001544041	0.00078448997	1
--0.011046915	-0.022324128	9.3702755	9.2093086	0.00029626157	0.0015373094	0.00078438368	1
--0.010687119	-0.022324206	12.260316	9.7621527	0.00029252854	0.0015307612	0.00078427256	1
--0.010327319	-0.022324285	11.094871	9.4623747	0.00028891905	0.0015243988	0.00078415667	1
--0.0099675152	-0.022324359	9.978241	9.1493549	0.00028543317	0.0015182245	0.00078403589	1
--0.0096077081	-0.02232443	9.2988892	9.3369284	0.00028207086	0.0015122404	0.00078391028	1
--0.0092478972	-0.022324499	6.7790489	8.108161	0.00027883213	0.001506449	0.00078377977	1
--0.0088880835	-0.022324566	2.8816853	6.9032531	0.00027571697	0.0015008523	0.00078364438	1
--0.0085282661	-0.022324629	6.6408968	8.7400246	0.00027272542	0.0014954527	0.00078350416	1
--0.0081684459	-0.022324691	6.5597486	8.1078434	0.00026985747	0.0014902523	0.00078335905	1
--0.0078086234	-0.022324748	9.0842514	8.8205538	0.00026711309	0.0014852531	0.00078320917	1
--0.0074487976	-0.022324804	11.52507	9.9371357	0.00026449235	0.0014804574	0.00078305451	1
--0.007088969	-0.022324858	10.131307	9.1484108	0.00026199518	0.001475867	0.00078289525	1
--0.0067291381	-0.022324909	7.5817194	8.47435	0.00025962162	0.001471484	0.00078273134	1
--0.0063693048	-0.022324957	8.3525753	8.4742556	0.00025737169	0.0014673101	0.00078256294	1
--0.0060094693	-0.022325002	13.863226	10.048455	0.00025524534	0.0014633475	0.00078239024	1
--0.0056496314	-0.022325044	8.8814049	8.8198395	0.00025324262	0.0014595978	0.00078221329	1
--0.0052897916	-0.022325085	6.0130758	7.7144136	0.0002513635	0.0014560627	0.00078203221	1
--0.00492995	-0.022325123	9.8178225	9.1476555	0.00024960801	0.0014527439	0.00078184722	1
--0.004570107	-0.022325158	10.718953	10.087296	0.00024797613	0.0014496431	0.00078165851	1
--0.0042102616	-0.02232519	3.990171	8.0638132	0.00024646788	0.0014467615	0.00078146625	1
--0.0038504153	-0.02232522	5.4061699	7.7139726	0.00024508324	0.0014441008	0.00078127062	1
--0.0034905677	-0.022325246	10.126167	9.6981039	0.00024382224	0.0014416623	0.00078107195	1
--0.0031307186	-0.02232527	6.9641652	8.6754246	0.00024268485	0.0014394472	0.00078087032	1
--0.0027708684	-0.022325292	4.5232043	7.2889123	0.00024167109	0.0014374567	0.00078066613	1
--0.0024110172	-0.022325311	2.1938665	7.1484151	0.00024078097	0.0014356918	0.00078045961	1
--0.0020511653	-0.022325328	5.5990143	7.7134233	0.00024001446	0.0014341536	0.00078025094	1
--0.0016913125	-0.022325341	9.4555807	9.3341341	0.00023937158	0.001432843	0.00078004051	1
--0.0013314593	-0.022325352	8.8101921	8.8183327	0.00023885234	0.0014317607	0.00077982852	1
--0.00097160548	-0.022325361	8.0532999	8.4724474	0.00023845672	0.0014309074	0.00077961537	1
--0.00061175134	-0.022325367	4.1488552	7.3629298	0.00023818473	0.0014302838	0.00077940134	1
--0.000251897	-0.022325369	3.2997091	6.8212457	0.00023803637	0.00142989	0.00077918667	1
-0.00010795743	-0.02232537	8.9115925	8.8178091	0.00023801165	0.0014297268	0.00077897176	1
-0.00046781183	-0.022325367	7.4556713	8.6741571	0.00023811056	0.0014297942	0.00077875686	1
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-0.0015473735	-0.022325346	3.1349006	6.8207226	0.00023914906	0.0014313813	0.00077811547	1
-0.0019072265	-0.022325333	6.1334162	8.1717854	0.00023974248	0.0014323718	0.00077790383	1
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--0.03370114	-0.021954298	20.527962	9.4687614	0.00077270763	0.0022149193	0.00078538444	1
--0.033341836	-0.021954538	20.740318	9.5263891	0.00076120271	0.00220101	0.00078540976	1
--0.032982521	-0.021954777	12.354168	8.5451126	0.00074982084	0.0021871629	0.00078543479	1
--0.03262319	-0.021955013	4.6496873	7.0775704	0.00073856203	0.0021733793	0.00078545953	1
--0.032263853	-0.021955248	16.0387	8.8268919	0.00072742638	0.0021596602	0.00078548398	1
--0.031904504	-0.021955479	13.58455	8.4806395	0.00071641378	0.0021460068	0.00078550808	1
--0.03154514	-0.021955706	12.50801	8.6828442	0.00070552435	0.0021324207	0.00078553177	1
--0.031185769	-0.021955933	24.25058	10.056432	0.00069475803	0.0021189027	0.00078555511	1
--0.030826384	-0.021956155	25.906961	10.334181	0.00068411481	0.0021054544	0.00078557798	1
--0.030466989	-0.021956377	19.436811	9.5257759	0.00067359477	0.0020920772	0.00078560039	1
--0.030107584	-0.021956595	14.400239	9.0209885	0.00066319789	0.0020787723	0.00078562228	1
--0.029748168	-0.021956811	13.08728	8.6825657	0.00065292424	0.0020655412	0.0007856437	1
--0.029388741	-0.021957023	18.38509	9.1547785	0.0006427737	0.0020523851	0.00078566448	1
--0.029029302	-0.021957234	24.329075	10.500342	0.00063274638	0.0020393059	0.00078568468	1
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--0.0060093375	0.023375247	3.110811	6.2970905	0.00027816705	0.0013854898	0.00077561854	1
--0.0056495075	0.023375291	5.7746582	7.2902989	0.00027616447	0.0013817302	0.00077579886	1
--0.0052896757	0.023375334	9.9498072	8.1076813	0.00027428547	0.001378202	0.00077598338	1
--0.004929842	0.023375373	3.7205572	6.9027748	0.0002725301	0.0013749069	0.00077617192	1
--0.0045700069	0.023375411	8.8936977	8.1074238	0.00027089834	0.0013718465	0.00077636435	1
--0.0042101694	0.023375444	5.5780978	7.2898927	0.00026939018	0.0013690222	0.0007765604	1
--0.0038503311	0.023375474	11.381567	8.819972	0.00026800562	0.0013664353	0.00077675987	1
--0.0034904911	0.023375502	10.119536	8.4740105	0.0002667447	0.0013640872	0.00077696249	1
--0.0031306499	0.023375528	5.8189816	7.2895885	0.00026560738	0.0013619788	0.00077716808	1
--0.0027708078	0.02337555	8.5864563	8.1068411	0.00026459369	0.0013601112	0.00077737629	1
--0.0024109646	0.023375571	4.8508992	7.5235305	0.00026370364	0.0013584851	0.00077758689	1
--0.0020511204	0.023375588	11.626168	8.8193483	0.00026293716	0.0013571013	0.00077779952	1
--0.0016912755	0.023375602	5.9394627	7.2891693	0.00026229434	0.0013559603	0.00077801401	1
--0.0013314302	0.023375614	8.3634291	8.1063623	0.00026177513	0.0013550625	0.00077822991	1
--0.00097158417	0.023375623	16.063766	9.7594461	0.00026137952	0.0013544083	0.00077844696	1
--0.00061173795	0.023375629	4.4777045	6.8218756	0.00026110758	0.001353998	0.00077866483	1
--0.0002518915	0.023375632	7.1397276	7.7134676	0.0002609592	0.0013538313	0.00077888323	1
-0.00010795506	0.023375632	5.24265	7.3632793	0.0002609345	0.0013539083	0.0007791018	1
-0.00046780158	0.02337563	3.0452051	6.295465	0.00026103339	0.0013542288	0.00077932019	1
-0.00082764792	0.023375625	9.2535782	8.4724827	0.00026125592	0.0013547924	0.00077953812	1
-0.001187494	0.023375617	18.57835	10.376803	0.00026160205	0.0013555986	0.00077975518	1
-0.0015473396	0.023375606	8.1064568	8.6744232	0.00026207182	0.0013566467	0.00077997113	1
-0.0019071847	0.023375593	4.3704395	6.8211446	0.00026266521	0.0013579361	0.00078018563	1
-0.0022670291	0.023375578	5.5869865	7.2879453	0.00026338222	0.0013594658	0.00078039838	1
-0.0026268726	0.02337556	5.5631886	7.2878299	0.00026422285	0.0013612349	0.00078060903	1
-0.0029867154	0.023375537	6.1315022	7.7829566	0.00026518709	0.0013632423	0.0007808173	1
-0.003346557	0.023375513	6.9490252	7.7122674	0.00026627496	0.0013654868	0.00078102294	1
-0.0037063975	0.023375485	6.7077365	7.7121382	0.00026748644	0.001367967	0.00078122574	1
-0.0040662368	0.023375455	10.079783	8.4713097	0.00026882152	0.0013706814	0.00078142533	1
-0.0044260742	0.023375424	4.0513806	6.8203773	0.00027028023	0.0013736289	0.00078162149	1
-0.0047859102	0.023375388	4.2365561	6.8202691	0.00027186258	0.0013768073	0.00078181404	1
-0.0051457449	0.023375351	5.5528603	7.2870073	0.0002735685	0.0013802153	0.00078200281	1
-0.0055055772	0.02337531	8.2454758	8.1039515	0.00027539805	0.0013838508	0.0007821875	1
-0.0058654081	0.023375265	5.4347262	7.2867637	0.00027735118	0.0013877122	0.00078236801	1
-0.0062252367	0.023375219	2.9180565	7.1462641	0.00027942794	0.0013917973	0.00078254414	1
-0.0065850629	0.02337517	4.4323592	7.520575	0.00028162831	0.0013961042	0.0007827158	1
-0.0069448869	0.023375118	12.074215	9.2033796	0.00028395228	0.0014006308	0.00078288285	1
-0.0073047085	0.023375064	4.4691048	7.5203195	0.00028639982	0.0014053747	0.00078304514	1
-0.0076645277	0.023375006	3.7221291	7.71874	0.00028897097	0.0014103339	0.00078320259	1
-0.0080243442	0.023374947	8.0490246	8.1029902	0.00029166572	0.0014155059	0.00078335515	1
-0.008384157	0.023374883	6.6602435	7.7104654	0.00029448405	0.0014208885	0.00078350276	1
-0.0087439679	0.023374818	10.98882	8.8151083	0.00029742598	0.0014264792	0.00078364537	1
-0.009103775	0.023374749	7.1786232	8.3136225	0.00030049149	0.0014322756	0.00078378298	1
-0.0094635794	0.023374679	2.6482594	6.2928677	0.00030368057	0.0014382751	0.00078391552	1
-0.00982338	0.023374604	9.6548567	8.4690104	0.00030699326	0.0014444754	0.00078404299	1
-0.010183177	0.023374528	8.8254347	8.5331211	0.00031042949	0.0014508736	0.0007841654	1
-0.010542971	0.023374448	8.3678589	8.1020069	0.00031398929	0.0014574673	0.00078428286	1
-0.010902761	0.023374366	5.9716291	7.9309983	0.00031767268	0.0014642539	0.00078439532	1
-0.011262547	0.02337428	13.017301	9.454524	0.0003214796	0.0014712308	0.00078450289	1
-0.011622329	0.023374192	5.195888	7.3593526	0.0003254101	0.0014783951	0.00078460551	1
-0.011982108	0.023374103	8.4105606	7.284677	0.00032946415	0.0014857443	0.00078470336	1
Index: rnel-CapCyl.cpp
===================================================================
--- Kernel-CapCyl.cpp	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,55 +1,0 @@
-__kernel void CapCylinderKernel(__global const real *qx, __global const real *qy, __global real *_ptvalue, __global real *vol_i,
-const real rad_cyl, const real rad_cap, const real length, const real thet, const real ph, const real sub,
-const real scale, const real phi_weight, const real theta_float, const real rad_cap_weight, const real rad_cyl_weight,
-const real length_weight, const int total, const int size, __const real Gauss76Wt, __const real Gauss76Z)
-//ph is phi, sub is sldc-slds, thet is theta
-{
-    int i = get_global_id(0);
-    if(i < total)
-    {
-        real q = sqrt(qx[i]*qx[i] + qy[i]*qy[i]);
-        real pi = 4.0*atan(1.0);
-        real theta = thet*pi/180.0;
-        real phi = ph*pi/180.0;
-        real cyl_x = cos(theta)*cos(phi);
-        real cyl_y = sin(theta);
-        real cos_val = cyl_x*qx[i]/q + cyl_y*qy[i]/q;
-        real alpha = acos(cos_val);
-        real ans1=0; real ans2=0; real y=0; real xx=0; real ans=0; real zij=0; real be=0; real summj=0;
-
-        real hDist = -1.0*sqrt(fabs(rad_cap*rad_cap-rad_cyl*rad_cyl));
-        vol_i[i] = pi*rad_cyl*rad_cyl*length+2.0*pi/3.0*((rad_cap-hDist)*(rad_cap-hDist)*(2*rad_cap+hDist));
-        real vaj = -1.0*hDist/rad_cap;
-
-        for(int j=0;j<76;j++) //the 76 corresponds to the Gauss constants
-        {
-            zij = (Gauss76Z[j]*(1.0-vaj)+vaj+1.0)/2.0;
-            summj += Gauss76Wt[j]*ConvLens_kernel(length,rad_cyl,rad_cap,q,zij,alpha);
-        }
-        real yyy = (1.0-vaj)/2.0*summj*4.0*pi*rad_cap*rad_cap*rad_cap;
-        real arg1 = q*length/2.0*cos(alpha);
-        real arg2 = q*rad_cyl*sin(alpha);
-
-        if(arg2 == 0) {be = 0.5;}
-        else {
-            be = NR_BessJ1(arg2)/arg2;
-        }
-
-        if(arg1 == 0.0) {
-            yyy += pi*rad_cyl*rad_cyl*length*2.0*be;
-        } 
-        else {
-            yyy += pi*rad_cyl*rad_cyl*length*sin(arg1)/arg1*2.0*be;
-        }
-        real answer=yyy*yyy*1.0e8*sub*sub*scale/pi*rad_cyl*rad_cyl*length+2.0*pi*(2.0*rad_cap*rad_cap*rad_cap/3.0+rad_cap*rad_cap*hDist-hDist*hDist*hDist/3.0);
-        answer/=sin(alpha);
-
-        _ptvalue[i] = rad_cyl_weight*length_weight*rad_cap_weight*theta_weight*phi_weight*vol_i[i]*answer
-        if (_ptvalue[i] == INFINITY || _ptvalue == NAN){
-            _ptvalue[i] = 0.0;
-        }
-     //   if (size>1) {
-   //         _ptvalue[i] *= fabs(cos(thet*pi/180.0));
-     //   }
-    }
-}
Index: rnel-CoreShellCylinder.cpp
===================================================================
--- Kernel-CoreShellCylinder.cpp	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,55 +1,0 @@
-__kernel void CoreShellCylinderKernel(__global const real *qx, __global const real *qy, __global real *_ptvalue,
-const real axis_theta, const real axis_phi, const real thickness, const real length, const real radius,
-const real scale, const real radius_weight, const real length_weight, const real thickness_weight,
-const real theta_weight, const real phi_weight, const real core_sld, const real shell_sld, const real solvent_sld,
-const int size, const int total)
-{
-    int i = get_global_id(0);
-    if(i < total)
-    {
-        real q = sqrt(qx[i]*qx[i]+qy[i]*qy[i]);
-        real pi = 4.0*atan(1.0);
-        real theta = axis_theta*pi/180.0;
-        real alpha = acos(cos(theta)*cos(axis_phi*pi/180.0)*qx[i]/q + sin(theta)*qy[i]/q);
-
-        if (alpha == 0.0){
-        alpha = 1.0e-26;
-        }
-
-        real si1=0; real si2=0; real be1=0; real be2=0;
-
-        real vol2 = pi*(radius+thickness)*(radius+thickness)*(length+2.0*thickness);
-
-        real besarg1 = q*radius*sin(alpha);
-        real besarg2 = q*(radius+thickness)*sin(alpha);
-        real sinarg1 = q*length/2.0*cos(alpha);
-        real sinarg2 = q*(length/2.0+thickness)*cos(alpha);
-
-
-        if (besarg1 == 0.0){be1 = 0.5;}
-        else{be1 = NR_BessJ1(besarg1)/besarg1;}
-
-        if (besarg2 == 0.0){be2 = 0.5;}
-        else{be2 = NR_BessJ1(besarg2)/besarg2;}
-
-        if (sinarg1 == 0.0){si1 = 1.0;}
-        else{si1 = sin(sinarg1)/sinarg1;}
-
-        if (sinarg2 == 0.0){si2 = 1.0;}
-        else{si2 = sin(sinarg2)/sinarg2;}
-
-        real tt = 2.0*vol2*(shell_sld-solvent_sld)*si2*be2+2.0*(pi*radius*radius*(length))*(core_sld-shell_sld)*si1*be1;
-
-        real answer = (tt*tt)*sin(alpha)/fabs(sin(alpha));
-        answer *= answer/(pi*(radius+thickness)*(radius+thickness)*(length+2.0*thickness))*1.0e8*scale;
-
-        _ptvalue[i] = radius_weight*length_weight*thickness_weight*theta_weight*phi_weight*answer*pow(radius+thickness,2)*(length+2.0*thickness);
-     //   if (size>1) {
-       // _ptvalue[i] *= fabs(cos(axis_theta*pi/180.0));
-        //}
-
-    }
-}
-
-
-
Index: rnel-Cylinder.cpp
===================================================================
--- Kernel-Cylinder.cpp	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,78 +1,0 @@
-__kernel void CylinderKernel(__global const real *qx, global const real *qy, __global real *_ptvalue, const real sub,
-const real rr, const real h, const real scale, const real radius_weight, const real length_weight,
-const real theta_weight, const real phi_weight, const real cyl_theta,
-const real cyl_phi, const int count, const int size)
-{
-	// qq is the q-value for the calculation (1/A)
-	// rr is the radius of the cylinder (A)
-	// h is the -LENGTH of the cylinder = L (A)
-    int i = get_global_id(0);
-
-    if(i < count)
-    {
-        real be=0.0; real si=0.0;
-        real qq = sqrt(qx[i]*qx[i]+qy[i]*qy[i]);
-
-        real pi = 4.0*atan(1.0);
-        real theta = cyl_theta*pi/180.0;
-        real cos_val = cos(theta)*cos(cyl_phi*pi/180.0)*(qx[i]/qq) + sin(theta)*(qy[i]/qq);
-
-        real alpha = acos(cos_val);
-        if(alpha == 0.0){
-            alpha = 1.0e-26;
-        }
-        real besarg = qq*rr*sin(alpha);
-        real siarg = qq*h/2*cos(alpha);
-
-        real bj = NR_BessJ1(besarg);
-        real d1 = qq*rr*sin(alpha);
-
-        if (besarg == 0.0){
-            be = sin(alpha);
-        }
-        else{
-            be = bj*bj*4.0*sin(alpha)/(d1*d1);
-        }
-        if(siarg == 0.0){
-            si = 1.0;
-        }else{
-            si = sin(siarg)*sin(siarg)/(siarg*siarg);
-        }
-        real form = be*si/sin(alpha);
-        real answer = sub*sub*form*acos(-1.0)*rr*rr*h*1.0e8*scale;
-
-        _ptvalue[i] = radius_weight*length_weight*theta_weight*phi_weight*answer*pow(rr,2)*h;
-       // if (size>1) {
-         //   _ptvalue[i] *= fabs(cos(cyl_theta*pi/180.0));
-      //  }
-    }
-}
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Index: rnel-Ellipse.cpp
===================================================================
--- Kernel-Ellipse.cpp	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,27 +1,0 @@
-__kernel void EllipsoidKernel(const real radius_a_weight, const real radius_b_weight, const real axis_theta_weight,
-const real axis_phi_weight, const real scale, const real radius_a, const real radius_b, const real sub, const real axis_theta, const real axis_phi, __global const real *qx,
-__global const real *qy, __global real *_ptvalue, const int length, const int size)
-{
-     int i = get_global_id(0);
-     if(i < length){
-         real ret = 0;
-         real q = sqrt(qx[i]*qx[i] + qy[i]*qy[i]);
-         real pi = 4.0*atan(1.0);
-         real theta = axis_theta*pi/180.0;
-         real cos_val = cos(theta)*cos(axis_phi*pi/180.0)*(qx[i]/q) + sin(theta)*(qy[i]/q);
-
-         real arg = q*radius_b*sqrt(1.0+(cos_val*cos_val*(((radius_a*radius_a/(radius_b*radius_b))-1.0))));
-         if(arg == 0.0){
-             ret = 1.0/3.0;
-         }
-         else{
-             ret = (sin(arg)-arg*cos(arg))/(arg*arg*arg);
-         }
-         ret*=ret*9.0*sub*sub*4.0/3.0*acos(-1.0)*radius_b*radius_b*radius_a*scale*(1.0e8);
-
-         _ptvalue[i] = radius_a_weight*radius_b_weight*axis_theta_weight*radius_a*axis_phi_weight*ret*pow(radius_b, 2);
-         //if(size > 1){
-          //  _ptvalue[i] *= fabs(cos(axis_theta*pi/180.0));
-         //}
-     }
-}
Index: rnel-Lamellar.cpp
===================================================================
--- Kernel-Lamellar.cpp	(revision 496b2528aace8ce941bc0fda35e188e39e778443)
+++ 	(revision )
@@ -1,11 +1,0 @@
-
-__kernel void LamellarKernel(__global const real *qx, global const real *qy, __global real *ret, const real bi_thick,
- const real scale, const real sub, const int length)
-{
-    int i = get_global_id(0);
-    if(i < length)
-    {
-        real q = sqrt(qx[i]*qx[i]+qy[i]*qy[i]);
-        ret[i] = 2.0*4.0*atan(1.0)*scale*2.0*sub*(sub/q)/q*(1.0-cos(q*bi_thick))/(q*q)/bi_thick*1.0e8 ;
-    }
-}
Index: rnel-OneDCylinder.cpp
===================================================================
--- Kernel-OneDCylinder.cpp	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,25 +1,0 @@
-__kernel void OneDCylKernel(__global const real *q, __global real *answer, const real sub, const real length,
-const real radius, const real scale, const real size, const real uplim, const real lolim)
-{
-    int k = get_global_id(0);
-    if(k < size)
-    {
-        real Pi = 4.0*atan(1.0);
-        real up = uplim*Pi/180;
-        real low = lolim*Pi/180;
-
-        real summ = 0.0; real zi = 0;
-        real halfheight = length/2.0;
-
-        for(int i=0; i<76; i++)
-        {
-            zi = (Gauss76Z(i)*(up-low) + up + low )/2.0;
-            summ += Gauss76Wt(i)*CylKernel(q[k], radius, halfheight, zi);
-        }
-
-        answer[k] = (up-low)/2.0*summ*sub*sub*1.0e8*scale*Pi*radius*radius*length;
-
-    }
-}
-
-
Index: rnel-TriaxialEllipse.cpp
===================================================================
--- Kernel-TriaxialEllipse.cpp	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,43 +1,0 @@
-__kernel void TriaxialEllipseKernel(__global const real *qx, __global const real *qy, __global real *_ptvalue,
-const real sub, const real scale, const real axisA, const real axisB, const real axisC, const real axis_phi,
-const real axis_theta, const real axis_psi, const real axisA_weight, const real axisB_weight, const real axisC_weight,
-const real psi_weight, const real phi_weight, const real theta_weight, const int total, const int size)
-{
-    int i = get_global_id(0);
-    if(i < total)
-    {
-        real q = sqrt(qx[i]*qx[i]+qy[i]*qy[i]);
-        real q_x = qx[i]/q;
-        real q_y = qy[i]/q;
-        real pi = 4.0*atan(1.0);
-        real answer=0;
-        
-        //convert angle degree to radian
-        real theta = axis_theta*pi/180.0;
-        real phi = axis_phi*pi/180.0;
-        real psi = axis_psi*pi/180.0;
-        real cos_val = cos(theta)*cos(phi)*q_x + sin(theta)*q_y;
-        
-        // calculate the axis of the ellipse wrt q-coord.
-        real cos_nu = (-cos(phi)*sin(psi)*sin(theta)+sin(phi)*cos(psi))*q_x + sin(psi)*cos(theta)*q_y;
-        real cos_mu = (-sin(theta)*cos(psi)*cos(phi)-sin(psi)*sin(phi))*q_x + cos(theta)*cos(psi)*q_y;
-        real t = q*sqrt(axisA*axisA*cos_nu*cos_nu+axisB*axisB*cos_mu*cos_mu+axisC*axisC*cos_val*cos_val);
-
-        if (t==0.0){
-            answer = 1.0;
-        }
-        else{
-            answer  = 3.0*(sin(t)-t*cos(t))/(t*t*t);
-        }
-        answer*=answer*sub*sub*4.0*pi/3.0*axisA*axisB*axisC*1.0e8*scale;
-
-        _ptvalue[i] = axisA_weight*axisB_weight*axisC_weight*theta_weight*phi_weight*psi_weight*answer*axisA*axisB*axisC;
-       // if (size>1)
-         //   _ptvalue[i] *= fabs(cos(theta*pi/180.0));
-
-    }
-}
-
-
-
-
Index: Kernel/__init__.py
===================================================================
--- Kernel/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
+++ Kernel/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -0,0 +1,1 @@
+__author__ = 'HMP1'
Index: Models/__init__.py
===================================================================
--- Models/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
+++ Models/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -0,0 +1,1 @@
+__author__ = 'HMP1'
Index: Models/code_capcyl.py
===================================================================
--- Models/code_capcyl.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_capcyl.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -5,6 +5,8 @@
 from math import asin, sqrt, fabs, atan
 import pyopencl as cl
+
 from weights import GaussianDispersion
-from sasmodel import card
+from Models.sasmodel import card
+
 
 def set_precision(src, qx, qy, dtype):
Index: Models/code_coreshellcyl.py
===================================================================
--- Models/code_coreshellcyl.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_coreshellcyl.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -3,8 +3,9 @@
 
 import numpy as np
-import math
 import pyopencl as cl
+
 from weights import GaussianDispersion
-from sasmodel import card
+from Models.sasmodel import card
+
 
 def set_precision(src, qx, qy, dtype):
Index: Models/code_cylinder.py
===================================================================
--- Models/code_cylinder.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_cylinder.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -4,6 +4,8 @@
 import numpy as np
 import pyopencl as cl
+
 from weights import GaussianDispersion
-from sasmodel import card
+from Models.sasmodel import card
+
 
 def set_precision(src, qx, qy, dtype):
Index: Models/code_ellipse.py
===================================================================
--- Models/code_ellipse.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_ellipse.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -3,8 +3,9 @@
 
 import numpy as np
-import math
 import pyopencl as cl
+
 from weights import GaussianDispersion
-from sasmodel import card
+from Models.sasmodel import card
+
 
 def set_precision(src, qx, qy, dtype):
Index: Models/code_lamellar.py
===================================================================
--- Models/code_lamellar.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_lamellar.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -61,41 +61,4 @@
         return sum/norm + pars['background']
 
-def demo():
-
-    from time import time
-    import matplotlib.pyplot as plt
-
-    #create qx and qy evenly spaces
-    qx = np.linspace(-.01, .01, 128)
-    qy = np.linspace(-.01, .01, 128)
-    qx, qy = np.meshgrid(qx, qy)
-
-    #saved shape of qx
-    r_shape = qx.shape
-
-    #reshape for calculation; resize as float32
-    qx = qx.flatten()
-    qy = qy.flatten()
-
-    pars = LamellarParameters(scale=1, bi_thick=100, sld_bi=.291e-6, sld_sol=5.77e-6, background=0)
-    t = time()
-    result = GpuLamellar(qx, qy)
-    result.x = result.lamellar_fit(pars, b_n=35, b_w=.1, sigma=3)
-    result.x = np.reshape(result.x, r_shape)
-    tt = time()
-
-    print("Time taken: %f" % (tt - t))
-
-    f = open("r.txt", "w")
-    for x in xrange(len(r_shape)):
-        f.write(str(result.x[x]))
-        f.write("\n")
-
-    plt.pcolormesh(np.log10(result.x))
-    plt.show()
-
-
-if __name__ == "__main__":
-    demo()
 
 
@@ -126,6 +89,2 @@
 
 
-
-
-
-
Index: Models/code_triaxialellipse.py
===================================================================
--- Models/code_triaxialellipse.py	(revision dbb0048466f8b528c1953a0eb5a496b6c1c25e32)
+++ Models/code_triaxialellipse.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -3,8 +3,9 @@
 
 import numpy as np
-from math import asin
 import pyopencl as cl
+
 from weights import GaussianDispersion
-from sasmodel import card
+from Models.sasmodel import card
+
 
 def set_precision(src, qx, qy, dtype):
Index: _BessJ1.cpp
===================================================================
--- NR_BessJ1.cpp	(revision 8faffcd2c614126a3e6035d58f1f258f3271103e)
+++ 	(revision )
@@ -1,22 +1,0 @@
-real NR_BessJ1(real x)
-{
-    real xx=0; real y=0; real ans=0; real ans1=0; real ans2=0;
-    real ax = fabs(x);
-	if (ax < 8.0)
-	{
-		y=x*x;
-		ans1=x*(72362614232.0+y*(-7895059235.0+y*(242396853.1+y*(-2972611.439+y*(15704.48260+y*(-30.16036606))))));
-		ans2=144725228442.0+y*(2300535178.0+y*(18583304.74+y*(99447.43394+y*(376.9991397+y*1.0))));
-		ans=ans1/ans2;
-	}
-	else
-	{
-		y=64.0/(ax*ax);
-		xx= ax-2.356194491;
-		ans1=1.0+y*(0.183105e-2+y*(-0.3516396496e-4+y*(0.2457520174e-5+y*(-0.240337019e-6))));
-		ans2=0.04687499995+y*(-0.2002690873e-3+y*(0.8449199096e-5+y*(-0.88228987e-6+y*0.105787412e-6)));
-		ans=sqrt(0.636619772/ax)*(cos(xx)*ans1-(8.0/ax)*sin(xx)*ans2);
-		if (x < 0.0) {ans*=-1;}
-	}
-	return(ans);
-}
Index: eDCyl_Kfun.cpp
===================================================================
--- OneDCyl_Kfun.cpp	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,73 +1,0 @@
-real CylKernel(real qq, real rr, real h, real theta)
-{
-    // qq is the q-value for the calculation (1/A)
-    // rr is the radius of the cylinder (A)
-    // h is the HALF-LENGTH of the cylinder = L/2 (A)
-    real be=0; real si=0;
-    real besarg = qq*rr*sin(theta);
-    real siarg = qq*h*cos(theta);
-    real bj = NR_BessJ1(besarg);
-
-    real d1 = qq*rr*sin(theta);
-
-    if (besarg == 0.0){
-        be = sin(theta);
-    }else{
-        be = bj*bj*4.0*sin(theta) / (d1*d1);
-    }
-
-    if (siarg == 0.0){
-        si = 1.0;
-    }else{
-        si = sin(siarg)*sin(siarg)/(siarg*siarg);
-    }
-    return be*si;
-}
-real Gauss76Z(int i)
-{
-real array[76] = {.999505948362153*(-1.0),.997397786355355*(-1.0),.993608772723527*(-1.0),.988144453359837*(-1.0),
-.981013938975656*(-1.0),.972229228520377*(-1.0),.961805126758768*(-1.0),.949759207710896*(-1.0),
-.936111781934811*(-1.0),.92088586125215*(-1.0),.904107119545567*(-1.0),.885803849292083*(-1.0),
-.866006913771982*(-1.0),.844749694983342*(-1.0),.822068037328975*(-1.0),.7980001871612*(-1.0),
-.77258672828181*(-1.0),.74587051350361*(-1.0),.717896592387704*(-1.0),.688712135277641*(-1.0),
-.658366353758143*(-1.0),.626910417672267*(-1.0),.594397368836793*(-1.0),.560882031601237*(-1.0),
-.526420920401243*(-1.0),.491072144462194*(-1.0),.454895309813726*(-1.0),.417951418780327*(-1.0),
-.380302767117504*(-1.0),.342012838966962*(-1.0),.303146199807908*(-1.0),.263768387584994*(-1.0),
-.223945802196474*(-1.0),.183745593528914*(-1.0),.143235548227268*(-1.0),.102483975391227*(-1.0),
-.0615595913906112*(-1.0),.0205314039939986*(-1.0),-.0205314039939986*(-1.0),-.0615595913906112*(-1.0),
--.102483975391227*(-1.0),-.143235548227268*(-1.0),-.183745593528914*(-1.0),-.223945802196474*(-1.0),
--.263768387584994*(-1.0),-.303146199807908*(-1.0),-.342012838966962*(-1.0),-.380302767117504*(-1.0),
--.417951418780327*(-1.0),-.454895309813726*(-1.0),-.491072144462194*(-1.0),-.526420920401243*(-1.0),
--.560882031601237*(-1.0),-.594397368836793*(-1.0),-.626910417672267*(-1.0),-.658366353758143*(-1.0),
--.688712135277641*(-1.0),-.717896592387704*(-1.0),-.74587051350361*(-1.0),-.77258672828181*(-1.0),
--.7980001871612*(-1.0),	-.822068037328975*(-1.0),-.844749694983342*(-1.0),-.866006913771982*(-1.0),
--.885803849292083*(-1.0),-.904107119545567*(-1.0),-.92088586125215*(-1.0),-.936111781934811*(-1.0),
--.949759207710896*(-1.0),-.961805126758768*(-1.0),-.972229228520377*(-1.0),-.981013938975656*(-1.0),
--.988144453359837*(-1.0),-.993608772723527*(-1.0),-.997397786355355*(-1.0),-.999505948362153*(-1.0) };
-
-return array[i];
-}
-real Gauss76Wt(int i)
-{
-real array[76] = {.00126779163408536,.00294910295364247,.00462793522803742,.00629918049732845,
-.00795984747723973,.00960710541471375,.0112381685696677,.0128502838475101,
-.0144407317482767,.0160068299122486,.0175459372914742,.0190554584671906,
-.020532847967908,.0219756145344162,.0233813253070112,.0247476099206597,
-.026072164497986,.0273527555318275,.028587223650054,.029773487255905,
-.0309095460374916,.0319934843404216,.0330234743977917,.0339977794120564,
-.0349147564835508,.0357728593807139,.0365706411473296,.0373067565423816,
-.0379799643084053,.0385891292645067,.0391332242205184,.0396113317090621,
-.0400226455325968,.040366472122844,.0406422317102947,.0408494593018285,
-.040987805464794,.0410570369162294,.0410570369162294,.040987805464794,
-.0408494593018285,.0406422317102947,.040366472122844,.0400226455325968,
-.0396113317090621,.0391332242205184,.0385891292645067,.0379799643084053,
-.0373067565423816,.0365706411473296,.0357728593807139,.0349147564835508,
-.0339977794120564,.0330234743977917,.0319934843404216,.0309095460374916,
-.029773487255905,.028587223650054,.0273527555318275,.026072164497986,
-.0247476099206597,.0233813253070112,.0219756145344162,.020532847967908,
-.0190554584671906,.0175459372914742,.0160068299122486,.0144407317482767,
-.0128502838475101,.0112381685696677,.00960710541471375,.00795984747723973,
-.00629918049732845,.00462793522803742,.00294910295364247,.00126779163408536 };
-
-return array[i];
-}
Index: ST-Kernel-Ellipse.cpp
===================================================================
--- TEST-Kernel-Ellipse.cpp	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,81 +1,0 @@
-__kernel void EllipsoidKernel(__global const real *qx, __global const real *qy, __global const int *place, __global const real *array,
-__global real *final, const real scale, const real sub, const int length, const int size)//, __local real *poly)
-{
-    //__local real rada, radaw, radb, radbw, th, thw, ph, phw;
-
-    __local real rada;
-    int uno=0; int dos=1; int count = 0;
-    int l = get_local_id(0);
-    for(int j = 0; j < 4; j++)
-    {
-        for(int i = place[uno]; i < place[dos]; i++)
-        {
-            rada[count] = array[i]
-            radaw[count] = array[]
-        }
-    uno+=2;
-    dos+=2;
-    count = 0;
-    }
-
-
-    int i = get_global_id(0);
-    if(i < length){
-    //do local mem?
-    real sum=0.0; real vol=0.0; real norm_vol=0.0; real norm=0.0;
-
-    for(int a = 0; a < place[0]; a++) //radius_a values
-    {
-        real radius_a = array[a];
-        real radius_a_weight = array[a+place[0]];
-        for(int b = place[1]; b < place[2]; b++) //radius_b values
-        {
-            real radius_b = array[b];
-            real radius_b_weight = array[b+place[2]];
-            for(int t = place[3]; t < place[4]; t++) //Axis_theta values
-            {
-                real axis_theta = array[t];
-                real axis_theta_weight = array[t+place[4]];
-                for(int p = place[5]; p < place[6]; p++) //axis_phi values
-                {
-                    real axis_phi = array[p];
-                    real axis_phi_weight = array[p+place[6]];
-
-                    real ret = 0;
-                    real q = sqrt(qx[i]*qx[i] + qy[i]*qy[i]);
-                    real pi = 4.0*atan(1.0);
-                    real theta = axis_theta*pi/180.0;
-                    real cos_val = cos(theta)*cos(axis_phi*pi/180.0)*(qx[i]/q) + sin(theta)*(qy[i]/q);
-
-                    real arg = q*radius_b*sqrt(1.0+(cos_val*cos_val*(((radius_a*radius_a/(radius_b*radius_b))-1.0))));
-                    if(arg == 0.0){
-                     ret = 1.0/3.0;
-                    }
-                    else{
-                        ret = (sin(arg)-arg*cos(arg))/(arg*arg*arg);
-                    }
-                    ret*=ret*9.0*sub*sub*4.0/3.0*acos(-1.0)*radius_b*radius_b*radius_a*scale*(1.0e8);
-                    real _ptvalue = radius_a_weight*radius_b_weight*axis_theta_weight*radius_a*axis_phi_weight*ret*pow(radius_b, 2);
-                    if(size > 1){
-                        _ptvalue *= fabs(cos(axis_theta*pi/180.0));
-                    }
-
-                    sum += _ptvalue;
-                    vol += radius_a_weight*radius_b_weight*pow(radius_b, 2)*radius_a;
-                    norm_vol += radius_a_weight*radius_b_weight;
-                    norm += radius_a_weight*radius_b_weight*axis_theta_weight*axis_phi_weight;
-                }
-            }
-        }
-    }
-
-    if(size > 1){
-        norm /= asin(1.0);
-    }
-    if(vol != 0.0 && norm_vol != 0.0){
-        sum *= norm_vol/vol;
-    }
-
-    final[i] = sum/norm;
-}
-}
Index: Testers/__init__.py
===================================================================
--- Testers/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
+++ Testers/__init__.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -0,0 +1,1 @@
+__author__ = 'HMP1'
Index: Testers/load.py
===================================================================
--- Testers/load.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
+++ Testers/load.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -0,0 +1,70 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+from sans.dataloader.loader import Loader
+from sans.dataloader.manipulations import Ringcut
+from Kernel import fit
+
+
+def cylinder(data): ##################################################################################
+    from sans.models.CylinderModel import CylinderModel
+    model1 = CylinderModel()
+    model1.setParam("scale", 10.0)
+    model1.setParam("radius",18)
+    model1.setParam("length", 397)
+    model1.setParam("sldCyl",3e-006 )
+    model1.setParam("sldSolv",0.0 )
+    model1.setParam("background", 0.0)
+
+    # Dispersion parameters
+    model1.dispersion['radius']['width'] = 0.25
+    model1.dispersion['radius']['npts'] = 50
+
+    theory = model1.evalDistribution([data.qx_data, data.qy_data])
+    return theory
+
+def load_data(filename):
+    loader = Loader()
+    f = loader.load(filename)
+    return f
+
+def set_beam_stop(data, radius):
+    data.mask = Ringcut(0, radius)(data)
+
+def plot_data(data):
+    from numpy.ma import masked_array
+    import matplotlib.pyplot as plt
+    img = masked_array(data.data, data.mask)
+    xmin, xmax = min(data.qx_data), max(data.qx_data)
+    ymin, ymax = min(data.qy_data), max(data.qy_data)
+    plt.imshow(img.reshape(128,128),
+               interpolation='nearest', aspect=1, origin='upper',
+               extent=[xmin, xmax, ymin, ymax])
+
+def demo():
+
+    data = load_data('NOV07090.DAT')
+    """
+    print data
+    print type(data)
+    set_beam_stop(data, 0.004)
+    plot_data(data)
+    import matplotlib.pyplot as plt; plt.show()
+    """
+    import matplotlib.pyplot as plt
+    import numpy as np
+    sasviewcyl = cylinder(data)
+    gpucyl = fit.Fit(data)
+    diff = gpucyl - sasviewcyl
+    np.linalg.norm(diff, order=None)
+    np.linalg.norm(diff, order=np.inf)
+
+    plot_data(data, diff)
+    plt.show()
+
+
+
+
+if __name__ == "__main__":
+    demo()
+
Index: de_capcyl.py
===================================================================
--- code_capcyl.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,139 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-from math import asin
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-from Gauss import Gauss76Wt, Gauss76Z
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-class GpuCapCylinder(object):
-    PARS = {'scale':1, 'rad_cyl':1, 'rad_cap':1, 'length':1, 'sld_capcyl':1e-6, 'sld_solv':0, 'background':0,
-             'theta':0, 'phi':0}
-
-    PD_PARS = ['rad_cyl', 'length', 'rad_cap', 'theta', 'phi']
-
-    def __init__(self, qx, qy, dtype='float32'):
-
-        #create context, queue, and build program
-        ctx,_queue = card()
-        trala = open('NR_BessJ1.cpp').read()+"\n"+open('Capcyl_Kfun.cpp').read()+"\n"+open('Kernel-Cylinder.cpp').read()
-        src, qx, qy = set_precision(trala, qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        G = np.ascontiguousarray(Gauss76Wt, dtype=dtype)
-        Z = np.ascontiguousarray(Gauss76Z, dtype=dtype)
-        self.Gauss76W_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=G)
-        self.Gauss76Z_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=Z)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-        self.vol_i = float(0.0)
-        self.vol_b = cl.Buffer(ctx, mf.WRITE_ONLY, self.vol_i.nbytes)
-
-    def eval(self, pars):
-
-        _ctx,queue = card()
-        rad_cyl,length,rad_cap,theta,phi = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in GpuCapCylinder.PD_PARS]
-
-        rad_cyl.value, rad_cyl.weight = rad_cyl.get_weights(pars['rad_cyl'], 0, 1000, True)
-        rad_cap.value, rad_cap.weight = rad_cap.get_weights(pars['rad_cap'], 0, 1000, True)
-        length.value, length.weight = length.get_weights(pars['length'], 0, 1000, True)
-        theta.value, theta.weight = theta.get_weights(pars['theta'], -90, 180, False)
-        phi.value, phi.weight = phi.get_weights(pars['phi'], -90, 180, False)
-
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-        size = len(theta.weight)
-        sub = pars['sld_capcyl']-pars['sld_solv']
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-
-        for i in xrange(len(rad_cyl.weight)):
-            for m in xrange(len(rad_cap.weight)):
-                for j in xrange(len(length.weight)):
-                    for k in xrange(len(theta.weight)):
-                        for l in xrange(len(phi.weight)):
-
-                            self.prg.CapCylinderKernel(queue, self.qx.shape, None, self.qx_b, self.qy_b, self.res_b,
-                                        self.vol_b, real(rad_cyl.value[i]), real(rad_cap.value[m]), real(length.value[j]),
-                                        real(theta.value[k]), real(phi.value[l]), real(sub), real(pars['scale']),
-                                        real(phi.weight[l]), real(theta.weight[k]), real(rad_cap.weight[m]),
-                                        real(rad_cyl.weight[i]), real(length.weight[j]), np.uint32(self.qx.size), np.uint32(size),
-                                        self.Gauss76W_b, self.Gauss76Z_b)
-
-                            cl.enqueue_copy(queue, self.res, self.res_b)
-                            cl.enqueue_copy(queue, self.vol_i, self.vol_b)
-
-                            sum += self.res
-                            vol += rad_cyl.weight[i]*length.weight[j]*rad_cap.weight[m]*self.vol_i
-                            norm_vol += rad_cyl.weight[i]*length.weight[j]*rad_cap.weight[m]
-                            norm += rad_cyl.weight[i]*length.weight[j]*rad_cap.weight[m]*theta.weight[k]*phi.weight[l]
-
-        if size > 1:
-            norm /= asin(1.0)
-
-        if vol != 0.0 and norm_vol != 0.0:
-            sum *= norm_vol/vol
-
-        return sum/norm + pars['background']
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Index: de_coreshellcyl.py
===================================================================
--- code_coreshellcyl.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,94 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import math
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-class GpuCoreShellCylinder(object):
-    PARS = {'scale':1, 'radius':1, 'thickness':1, 'length':1, 'core_sld':1e-6, 'shell_sld':-1e-6, 'solvent_sld':0,
-            'background':0, 'axis_theta':0, 'axis_phi':0}
-    PD_PARS = ['radius', 'length', 'thickness', 'axis_phi', 'axis_theta']
-
-    def __init__(self, qx, qy, dtype='float32'):
-        #create context, queue, and build program
-        ctx,_queue = card()
-        src, qx, qy = set_precision(open('NR_BessJ1.cpp').read()+"\n"+open('Kernel-CoreShellCylinder.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(qx)
-
-    def eval(self, pars):
-
-        _ctx,queue = card()
-        radius, length, thickness, axis_phi, axis_theta = [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-                                     for base in GpuCoreShellCylinder.PD_PARS]
-
-        radius.value, radius.weight = radius.get_weights(pars['radius'], 0, 10000, True)
-        length.value, length.weight = length.get_weights(pars['length'], 0, 10000, True)
-        thickness.value, thickness.weight = thickness.get_weights(pars['thickness'], 0, 10000, True)
-        axis_phi.value, axis_phi.weight = axis_phi.get_weights(pars['axis_phi'], -90, 180, False)
-        axis_theta.value, axis_theta.weight = axis_theta.get_weights(pars['axis_theta'], -90, 180, False)
-
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-
-        print radius.value
-        print thickness.weight
-        print axis_phi.weight
-        print axis_theta.weight
-        print length.value
-
-        size = len(axis_theta.weight)
-
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-        for r in xrange(len(radius.weight)):
-            for l in xrange(len(length.weight)):
-                for at in xrange(len(axis_theta.weight)):
-                    for p in xrange(len(axis_phi.weight)):
-                        for th in xrange(len(thickness.weight)):
-
-                            self.prg.CoreShellCylinderKernel(queue, self.qx.shape, None, self.qx_b, self.qy_b, self.res_b,
-                                    real(axis_theta.value[at]), real(axis_phi.value[p]), real(thickness.value[th]),
-                                    real(length.value[l]), real(radius.value[r]), real(pars['scale']),
-                                    real(radius.weight[r]), real(length.weight[l]), real(thickness.weight[th]),
-                                    real(axis_theta.weight[at]), real(axis_phi.weight[p]), real(pars['core_sld']),
-                                    real(pars['shell_sld']), real(pars['solvent_sld']),np.uint32(size),
-                                    np.uint32(self.qx.size))
-                            cl.enqueue_copy(queue, self.res, self.res_b)
-
-                            sum += self.res
-                            vol += radius.weight[r]*length.weight[l]*thickness.weight[th]*pow(radius.value[r]+thickness.value[th],2)\
-                                   *(length.value[l]+2.0*thickness.value[th])
-                            norm_vol += radius.weight[r]*length.weight[l]*thickness.weight[th]
-                            norm += radius.weight[r]*length.weight[l]*thickness.weight[th]*axis_theta.weight[at]\
-                                    *axis_phi.weight[p]
-
-        #if size>1:
-         #   norm /= math.asin(1.0)
-        if vol != 0.0 and norm_vol != 0.0:
-            sum *= norm_vol/vol
-
-        return sum/norm + pars['background']
Index: de_cylinder.py
===================================================================
--- code_cylinder.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,183 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-def set_precision_1d(src, q, dtype):
-    q = np.ascontiguousarray(q, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, q
-
-class GpuCylinder(object):
-    PARS = {
-        'scale':1,'radius':1,'length':1,'sldCyl':1e-6,'sldSolv':0,'background':0,
-        'cyl_theta':0,'cyl_phi':0,
-    }
-    PD_PARS = ['radius', 'length', 'cyl_theta', 'cyl_phi']
-
-    def __init__(self, qx, qy, dtype='float32'):
-
-        #create context, queue, and build program
-        ctx,_queue = card()
-        src, qx, qy = set_precision(open('NR_BessJ1.cpp').read()+"\n"+open('Kernel-Cylinder.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-
-    def eval(self, pars):
-
-        _ctx,queue = card()
-        radius, length, cyl_theta, cyl_phi = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in GpuCylinder.PD_PARS]
-
-        #Get the weights for each
-        radius.value, radius.weight = radius.get_weights(pars['radius'], 0, 10000, True)
-        length.value, length.weight = length.get_weights(pars['length'], 0, 10000, True)
-        cyl_theta.value, cyl_theta.weight = cyl_theta.get_weights(pars['cyl_theta'], -90, 180, False)
-        cyl_phi.value, cyl_phi.weight = cyl_phi.get_weights(pars['cyl_phi'], -90, 180, False)
-
-        #Perform the computation, with all weight points
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-        size = len(cyl_theta.weight)
-        sub = pars['sldCyl'] - pars['sldSolv']
-
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-        #Loop over radius, length, theta, phi weight points
-        for i in xrange(len(radius.weight)):
-            for j in xrange(len(length.weight)):
-                for k in xrange(len(cyl_theta.weight)):
-                    for l in xrange(len(cyl_phi.weight)):
-                        self.prg.CylinderKernel(queue, self.qx.shape, None, self.qx_b, self.qy_b, self.res_b, real(sub),
-                                           real(radius.value[i]), real(length.value[j]), real(pars['scale']),
-                                           real(radius.weight[i]), real(length.weight[j]), real(cyl_theta.weight[k]),
-                                           real(cyl_phi.weight[l]), real(cyl_theta.value[k]), real(cyl_phi.value[l]),
-                                           np.uint32(self.qx.size), np.uint32(size))
-                        cl.enqueue_copy(queue, self.res, self.res_b)
-                        sum += self.res
-                        vol += radius.weight[i]*length.weight[j]*pow(radius.value[i], 2)*length.value[j]
-                        norm_vol += radius.weight[i]*length.weight[j]
-                        norm += radius.weight[i]*length.weight[j]*cyl_theta.weight[k]*cyl_phi.weight[l]
-
-       # if size > 1:
-        #    norm /= math.asin(1.0)
-        if vol != 0.0 and norm_vol != 0.0:
-            sum *= norm_vol/vol
-
-        return sum/norm+pars['background']
-
-class OneDGpuCylinder(object):
-    PARS = {
-        'scale':1,'radius':1,'length':1,'sldCyl':1e-6,'sldSolv':0,'background':0,
-        'bolim':0, 'uplim':90
-    }
-    PD_PARS = ['radius', 'length']
-
-    def __init__(self, q, dtype='float32'):
-
-        #create context, queue, and build program
-        ctx,_queue = card()
-        trala = open('NR_BessJ1.cpp').read()+"\n"+open('OneDCyl_Kfun.cpp').read()+"\n"+open('Kernel-OneDCylinder.cpp').read()
-        src, self.q = set_precision_1d(trala, q, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-
-        #buffers
-        mf = cl.mem_flags
-        self.q_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.q)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, q.nbytes)
-        self.res = np.empty_like(self.q)
-
-    def eval(self, pars):
-
-        _ctx,queue = card()
-        radius, length = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in OneDGpuCylinder.PD_PARS]
-
-        #Get the weights for each
-        radius.value, radius.weight = radius.get_weights(pars['radius'], 0, 10000, True)
-        length.value, length.weight = length.get_weights(pars['length'], 0, 10000, True)
-
-        #Perform the computation, with all weight points
-        sum, norm, vol = 0.0, 0.0, 0.0,
-        sub = pars['sldCyl'] - pars['sldSolv']
-
-        real = np.float32 if self.q.dtype == np.dtype('float32') else np.float64
-        #Loop over radius, length, theta, phi weight points
-        for r in xrange(len(radius.weight)):
-            for l in xrange(len(length.weight)):
-                        self.prg.OneDCylKernel(queue, self.q.shape, None, self.q_b, self.res_b, real(sub),
-                                           real(length.value[l]), real(radius.value[r]), real(pars['scale']),
-                                           np.uint32(self.q.size), real(pars['uplim']), real(pars['bolim']))
-                        cl.enqueue_copy(queue, self.res, self.res_b)
-                        sum += radius.weight[r]*length.weight[l]*self.res*pow(radius.value[r],2)*length.value[l]
-                        vol += radius.weight[r]*length.weight[l] *pow(radius.value[r],2)*length.value[l]
-                        norm += radius.weight[r]*length.weight[l]
-
-        if vol != 0.0 and norm != 0.0:
-            sum *= norm/vol
-
-        return sum/norm + pars['background']
-
-       
-
-        
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Index: de_ellipse.py
===================================================================
--- code_ellipse.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,129 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import math
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-class GpuEllipse(object):
-    PARS = {
-    'scale':1, 'radius_a':1, 'radius_b':1, 'sldEll':1e-6, 'sldSolv':0, 'background':0, 'axis_theta':0, 'axis_phi':0,
-    }
-    PD_PARS = ['radius_a', 'radius_b', 'axis_theta', 'axis_phi']
-
-    def __init__(self, qx, qy, dtype='float32'):
-
-        ctx,_queue = card()
-        src, qx, qy = set_precision(open('Kernel-Ellipse.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-
-    def eval(self, pars):
-    #b_n = radius_b # want, a_n = radius_a # want, etc
-        _ctx,queue = card()
-        radius_a, radius_b, axis_theta, axis_phi = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in GpuEllipse.PD_PARS]
-
-        radius_a.value, radius_a.weight = radius_a.get_weights(pars['radius_a'], 0, 10000, True)
-        radius_b.value, radius_b.weight = radius_b.get_weights(pars['radius_b'], 0, 10000, True)
-        axis_theta.value, axis_theta.weight = axis_theta.get_weights(pars['axis_theta'], -90, 180, False)
-        axis_phi.value, axis_phi.weight = axis_phi.get_weights(pars['axis_phi'], -90, 180, False)
-
-        #Perform the computation, with all weight points
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-        size = len(axis_theta.weight)
-        sub = pars['sldEll'] - pars['sldSolv']
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-
-        #Loop over radius weight points
-        for i in xrange(len(radius_a.weight)):
-            #Loop over length weight points
-            for j in xrange(len(radius_b.weight)):
-                #Average over theta distribution
-                for k in xrange(len(axis_theta.weight)):
-                    #Average over phi distribution
-                    for l in xrange(len(axis_phi.weight)):
-                        #call the kernel
-                        self.prg.EllipsoidKernel(queue, self.qx.shape, None, real(radius_a.weight[i]),
-                                        real(radius_b.weight[j]), real(axis_theta.weight[k]),
-                                        real(axis_phi.weight[l]), real(pars['scale']), real(radius_a.value[i]),
-                                        real(radius_b.value[j]), real(sub), real(axis_theta.value[k]),
-                                        real(axis_phi.value[l]), self.qx_b, self.qy_b, self.res_b,
-                                        np.uint32(self.qx.size), np.uint32(len(axis_theta.weight)))
-                        #copy result back from buffer
-                        cl.enqueue_copy(queue, self.res, self.res_b)
-                        sum += self.res
-                        vol += radius_a.weight[i]*radius_b.weight[j]*pow(radius_b.value[j], 2)*radius_a.value[i]
-                        norm_vol += radius_a.weight[i]*radius_b.weight[j]
-                        norm += radius_a.weight[i]*radius_b.weight[j]*axis_theta.weight[k]*axis_phi.weight[l]
-        # Averaging in theta needs an extra normalization
-        # factor to account for the sin(theta) term in the
-        # integration (see documentation).
-
-    #    if size > 1:
-     #       norm /= math.asin(1.0)
-        if vol != 0.0 and norm_vol != 0.0:
-            sum *= norm_vol/vol
-
-        return sum/norm+pars['background']
-
-
-def demo():
-    from time import time
-    import matplotlib.pyplot as plt
-
-    #create qx and qy evenly spaces
-    qx = np.linspace(-.02, .02, 128)
-    qy = np.linspace(-.02, .02, 128)
-    qx, qy = np.meshgrid(qx, qy)
-
-    #saved shape of qx
-    r_shape = qx.shape
-    #reshape for calculation; resize as float32
-    qx = qx.flatten()
-    qy = qy.flatten()
-
-    #int main
-    pars = EllipsoidParameters(.027, 60, 180, .297e-6, 5.773e-06, 4.9, 0, 90)
-
-    t = time()
-    result = GpuEllipse(qx, qy)
-    result.x = result.ellipsoid_fit(qx, qy, pars, b_n=35, t_n=35, a_n=1, p_n=1, sigma=3, b_w=.1, t_w=.1, a_w=.1, p_w=.1)
-    result.x = np.reshape(result.x, r_shape)
-    tt = time()
-    print("Time taken: %f" % (tt - t))
-
-    plt.pcolormesh(result.x)
-    plt.show()
-
-
-if __name__ == "__main__":
-    demo()
-
-
-
-
Index: de_lamellar.py
===================================================================
--- code_lamellar.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,131 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import pyopencl as cl
-from weights import GaussianDispersion
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if dtype == 'double':
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-
-class GpuLamellar(object):
-    PARS = {
-        'scale':1, 'bi_thick':1, 'sld_bi':1e-6, 'sld_sol':0, 'background':0,
-    }
-    PD_PARS = {'bi_thick'}
-    def __init__(self, qx, qy, dtype='float32'):
-
-        #create context, queue, and build program
-        self.ctx = cl.create_some_context()
-        self.queue = cl.CommandQueue(self.ctx)
-        src,qx,qy = set_precision(open('Kernel-Lamellar.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(self.ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(self.ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(self.ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.res_b = cl.Buffer(self.ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-
-    def eval(self, pars):
-
-        bi_thick = GaussianDispersion(int(pars['bi_thick_pd_n']), pars['bi_thick_pd'], pars['bi_thick_pd_nsigma'])
-        bi_thick.value, bi_thick.weight = bi_thick.get_weights(pars['bi_thick'], 0, 10000, True)
-
-        sum, norm = 0.0, 0.0
-        sub = pars['sld_bi'] - pars['sld_sol']
-
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-        for i in xrange(len(bi_thick.weight)):
-            self.prg.LamellarKernel(self.queue, self.qx.shape, None, self.qx_b, self.qy_b, self.res_b, real(bi_thick.value[i]),
-                                    real(pars['scale']), real(sub), np.uint32(self.qx.size))
-            cl.enqueue_copy(self.queue, self.res, self.res_b)
-
-            sum += bi_thick.weight[i]*self.res
-            norm += bi_thick.weight[i]
-
-        return sum/norm + pars['background']
-
-def demo():
-
-    from time import time
-    import matplotlib.pyplot as plt
-
-    #create qx and qy evenly spaces
-    qx = np.linspace(-.01, .01, 128)
-    qy = np.linspace(-.01, .01, 128)
-    qx, qy = np.meshgrid(qx, qy)
-
-    #saved shape of qx
-    r_shape = qx.shape
-
-    #reshape for calculation; resize as float32
-    qx = qx.flatten()
-    qy = qy.flatten()
-
-    pars = LamellarParameters(scale=1, bi_thick=100, sld_bi=.291e-6, sld_sol=5.77e-6, background=0)
-    t = time()
-    result = GpuLamellar(qx, qy)
-    result.x = result.lamellar_fit(pars, b_n=35, b_w=.1, sigma=3)
-    result.x = np.reshape(result.x, r_shape)
-    tt = time()
-
-    print("Time taken: %f" % (tt - t))
-
-    f = open("r.txt", "w")
-    for x in xrange(len(r_shape)):
-        f.write(str(result.x[x]))
-        f.write("\n")
-
-    plt.pcolormesh(np.log10(result.x))
-    plt.show()
-
-
-if __name__ == "__main__":
-    demo()
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Index: de_triaxialellipse.py
===================================================================
--- code_triaxialellipse.py	(revision d772f5d5cfc1cb59c225465b709386ac13da531b)
+++ 	(revision )
@@ -1,128 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-from math import asin
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-class GpuTriEllipse:
-    PARS = {'scale':1, 'axisA':35, 'axisB':100, 'axisC':400, 'sldEll':1e-6, 'sldSolv':6.3e-6, 'background':0,
-            'theta':0, 'phi':0, 'psi':0}
-
-    PD_PARS = ['axisA', 'axisB', 'axisC', 'theta', 'phi', 'psi']
-
-    def __init__(self, qx, qy, dtype='float32'):
-        ctx,_queue = card()
-        src, qx, qy = set_precision(open('Kernel-TriaxialEllipse.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-
-        #buffers
-        mf = cl.mem_flags
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-
-    def eval(self, pars):
-
-        _ctx,queue = card()
-        axisA, axisB, axisC, theta, phi, psi = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in GpuTriEllipse.PD_PARS]
-
-        axisA.value, axisA.weight = axisA.get_weights(pars['axisA'], 0, 10000, True)
-        axisB.value, axisB.weight = axisB.get_weights(pars['axisB'], 0, 10000, True)
-        axisC.value, axisC.weight = axisC.get_weights(pars['axisC'], 0, 10000, True)
-        theta.value, theta.weight = theta.get_weights(pars['theta'], -90, 180, False)
-        phi.value, phi.weight = phi.get_weights(pars['phi'], -90, 180, False)
-        psi.value, psi.weight = psi.get_weights(pars['psi'], -90, 180, False)
-
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-        size = len(theta.weight)
-        sub = pars['sldEll'] - pars['sldSolv']
-
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-        for a in xrange(len(axisA.weight)):
-            for b in xrange(len(axisB.weight)):
-                for c in xrange(len(axisC.weight)):
-                    for t in xrange(len(theta.weight)):
-                        for i in xrange(len(phi.weight)):
-                            for s in xrange(len(psi.weight)):
-                                self.prg.TriaxialEllipseKernel(queue, self.qx.shape, None, self.qx_b, self.qy_b, self.res_b,
-                                            real(sub), real(pars['scale']), real(axisA.value[a]), real(axisB.value[b]),
-                                            real(axisC.value[c]), real(phi.value[i]), real(theta.value[t]), real(psi.value[s]),
-                                            real(axisA.weight[a]), real(axisB.weight[b]), real(axisC.weight[c]), real(psi.weight[s]),
-                                            real(phi.weight[i]), real(theta.weight[t]), np.uint32(self.qx.size), np.uint32(size))
-                                cl.enqueue_copy(queue, self.res, self.res_b)
-                                sum += self.res
-
-                                vol += axisA.weight[a]*axisB.weight[b]*axisC.weight[c]*axisA.value[a]*axisB.value[b]*axisC.value[c]
-                                norm_vol += axisA.weight[a]*axisB.weight[b]*axisC.weight[c]
-                                norm += axisA.weight[a]*axisB.weight[b]*axisC.weight[c]*theta.weight[t]*phi.weight[i]*psi.weight[s]
-
-      #  if size > 1:
-       #     norm /= asin(1.0)
-
-        if vol != 0.0 and norm_vol != 0.0:
-            sum *= norm_vol/vol
-
-        return sum/norm + pars['background']
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
Index: compare.py
===================================================================
--- compare.py	(revision 9a9f5b5060cd754295dd53d9583f6d410496af99)
+++ compare.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -3,5 +3,7 @@
 
 import datetime
-from sasmodel import SasModel, load_data, set_beam_stop, plot_data
+
+from Models.sasmodel import SasModel, load_data, set_beam_stop, plot_data
+
 
 TIC = None
Index: fit2.py
===================================================================
--- fit2.py	(revision 8faffcd2c614126a3e6035d58f1f258f3271103e)
+++ fit2.py	(revision 473183c753f3b44a54aab3a16e00e358edf72be6)
@@ -4,8 +4,5 @@
 from bumps.names import *
 from cylcode import GpuCylinder
-from lamellarcode import GpuLamellar
-from ellipsecode import GpuEllipse
-from coreshellcylcode import GpuCoreShellCylinder
-from sasmodel import SasModel, load_data, set_beam_stop
+from Models.sasmodel import SasModel, load_data, set_beam_stop
 
 
Index: ad.py
===================================================================
--- load.py	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,69 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-from sans.dataloader.loader import Loader
-from sans.dataloader.manipulations import Ringcut
-import fit
-
-def cylinder(data): ##################################################################################
-    from sans.models.CylinderModel import CylinderModel
-    model1 = CylinderModel()
-    model1.setParam("scale", 10.0)
-    model1.setParam("radius",18)
-    model1.setParam("length", 397)
-    model1.setParam("sldCyl",3e-006 )
-    model1.setParam("sldSolv",0.0 )
-    model1.setParam("background", 0.0)
-
-    # Dispersion parameters
-    model1.dispersion['radius']['width'] = 0.25
-    model1.dispersion['radius']['npts'] = 50
-
-    theory = model1.evalDistribution([data.qx_data, data.qy_data])
-    return theory
-
-def load_data(filename):
-    loader = Loader()
-    f = loader.load(filename)
-    return f
-
-def set_beam_stop(data, radius):
-    data.mask = Ringcut(0, radius)(data)
-
-def plot_data(data):
-    from numpy.ma import masked_array
-    import matplotlib.pyplot as plt
-    img = masked_array(data.data, data.mask)
-    xmin, xmax = min(data.qx_data), max(data.qx_data)
-    ymin, ymax = min(data.qy_data), max(data.qy_data)
-    plt.imshow(img.reshape(128,128),
-               interpolation='nearest', aspect=1, origin='upper',
-               extent=[xmin, xmax, ymin, ymax])
-
-def demo():
-
-    data = load_data('NOV07090.DAT')
-    """
-    print data
-    print type(data)
-    set_beam_stop(data, 0.004)
-    plot_data(data)
-    import matplotlib.pyplot as plt; plt.show()
-    """
-    import matplotlib.pyplot as plt
-    import numpy as np
-    sasviewcyl = cylinder(data)
-    gpucyl = fit.Fit(data)
-    diff = gpucyl - sasviewcyl
-    np.linalg.norm(diff, order=None)
-    np.linalg.norm(diff, order=np.inf)
-
-    plot_data(data, diff)
-    plt.show()
-
-
-
-
-if __name__ == "__main__":
-    demo()
-
Index: st_code_ellipse.py
===================================================================
--- test_code_ellipse.py	(revision 09e15be6501267fc2d7d3d325f9db88aa762c63c)
+++ 	(revision )
@@ -1,87 +1,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import numpy as np
-import pyopencl as cl
-from weights import GaussianDispersion
-from sasmodel import card
-import hi
-
-def set_precision(src, qx, qy, dtype):
-    qx = np.ascontiguousarray(qx, dtype=dtype)
-    qy = np.ascontiguousarray(qy, dtype=dtype)
-    if np.dtype(dtype) == np.dtype('float32'):
-        header = """\
-#define real float
-"""
-    else:
-        header = """\
-#pragma OPENCL EXTENSION cl_khr_fp64: enable
-#define real double
-"""
-    return header+src, qx, qy
-
-class GpuEllipse(object):
-    PARS = {
-    'scale':1, 'radius_a':1, 'radius_b':1, 'sldEll':1e-6, 'sldSolv':0, 'background':0, 'axis_theta':0, 'axis_phi':0,
-    }
-    PD_PARS = ['radius_a', 'radius_b', 'axis_theta', 'axis_phi']
-
-    def __init__(self, qx, qy, dtype='float32'):
-
-        ctx,_queue = card()
-        src, qx, qy = set_precision(open('TEST-Kernel-Ellipse.cpp').read(), qx, qy, dtype=dtype)
-        self.prg = cl.Program(ctx, src).build()
-        self.qx, self.qy = qx, qy
-        place = np.ascontiguousarray(hi.place, dtype=int)
-        #buffers
-        mf = cl.mem_flags
-        self.place_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=place)
-        self.qy_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qy)
-        self.qx_b = cl.Buffer(ctx, mf.READ_ONLY | mf.COPY_HOST_PTR, hostbuf=self.qx)
-        self.res_b = cl.Buffer(ctx, mf.WRITE_ONLY, qx.nbytes)
-        self.res = np.empty_like(self.qx)
-
-    def eval(self, pars):
-    #b_n = radius_b # want, a_n = radius_a # want, etc
-        ctx,queue = card()
-        radius_a, radius_b, axis_theta, axis_phi = \
-            [GaussianDispersion(int(pars[base+'_pd_n']), pars[base+'_pd'], pars[base+'_pd_nsigma'])
-             for base in GpuEllipse.PD_PARS]
-
-        radius_a.value, radius_a.weight = radius_a.get_weights(pars['radius_a'], 0, 1000, True)
-        radius_b.value, radius_b.weight = radius_b.get_weights(pars['radius_b'], 0, 1000, True)
-        axis_theta.value, axis_theta.weight = axis_theta.get_weights(pars['axis_theta'], -90, 180, False)
-        axis_phi.value, axis_phi.weight = axis_phi.get_weights(pars['axis_phi'], -90, 180, False)
-
-
-        #Perform the computation, with all weight points
-        sum, norm, norm_vol, vol = 0.0, 0.0, 0.0, 0.0
-        size = len(axis_theta.weight)
-        sub = pars['sldEll'] - pars['sldSolv']
-        real = np.float32 if self.qx.dtype == np.dtype('float32') else np.float64
-
-        x = [radius_a.value, radius_a.weight, radius_b.value, radius_b.weight, axis_theta.value,
-                 axis_theta.weight, axis_phi.value, axis_phi.weight]
-        array = np.hstack(x)
-
-        array_b = cl.Buffer(ctx, cl.mem_flags.READ_ONLY | cl.mem_flags.COPY_HOST_PTR, hostbuf=array)
-
-        self.prg.EllipsoidKernel(queue, self.qx.shape, None, self.qx_b, self.qy_b, self.place_b, array_b, self.res_b,
-                                 real(pars['scale']), real(sub), np.uint32(self.qx.size), np.uint32(len(axis_theta.weight)))
-        #copy result back from buffer
-        cl.enqueue_copy(queue, self.res, self.res_b)
-
-
-        a = open("answer.txt", "w")
-        for x in xrange(len(self.res)):
-            a.write(str(self.res))
-            a.write("\n")
-
-
-        return self.res+pars['background']
-
-
-
-
-
Index: ights.py
===================================================================
--- weights.py	(revision 5378e40a7fb092abdefdce6d59001232f68a74e2)
+++ 	(revision )
@@ -1,26 +1,0 @@
-import numpy as np
-
-class GaussianDispersion(object):
-    def __init__(self, npts=35, width=0, nsigmas=3): #number want, percent deviation, #standard deviations from mean
-        self.type = 'gaussian'
-        self.npts = npts
-        self.width = width
-        self.nsigmas = nsigmas
-
-    def get_pars(self):
-        return self.__dict__
-
-    def get_weights(self, center, min, max, relative):
-        """ *center* is the center of the distribution
-        *min*,*max* are the min, max allowed values
-        *relative* is True if the width is relative to the center instead of absolute
-        For polydispersity use relative.  For orientation parameters use absolute."""
-        npts, width, nsigmas = self.npts, self.width, self.nsigmas
-        sigma = width * center if relative else width
-        if sigma == 0:
-            return np.array([center, 1.], 'd')
-        x = center + np.linspace(-nsigmas * sigma, +nsigmas * sigma, npts)
-        x = x[(x >= min) & (x <= max)]
-        px = np.exp((x-center)**2 / (-2.0 * sigma * sigma))
-        return x, px
-
