Full-Stack Web Integration of KNN-based Cancer Detection Model with Django and Sklearn library

This data science project combines full-stack web development and data analysis to create a predictive model for cancer detection using the K-Nearest Neighbors (KNN) algorithm using Python's scikit-learn library. The project's primary objective is to seamlessly integrate this predictive model into a Django web application, enabling users to perform cancer diagnosis predictions with ease and accuracy.

In this project, combining the capabilities of Python, sci-kit-learn, and Django, the objective is to create a cancer detection model, ensuring a seamless process of preparing data and splitting it into train and test datasets. The generated model can assist in the early diagnosis of cancer, improving the accuracy of healthcare professionals' decisions.

Step By Step data processing

Data Collections

Gather and preprocess datasets containing cancer detection information. These datasets may include features such as tumor size, shape, and texture, along with the corresponding cancer diagnosis labels.

                        
# Install in the virtual environment scikit-learn and import these methods.
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
from sklearn.model_selection import cross_val_score

file_path = parent_directory + '/mparraf/static/datasets/database_cancer.csv'
df = pd.read_csv(file_path, usecols=lambda column: column != "Unnamed: 0")

Data Preparation, and Exploration

Converting the dataset to a Pandas DataFrame is a critical step that facilitates data analysis, preprocessing, and modeling. It harnesses the power of Pandas, making data-related tasks more efficient and enabling the seamless integration of the dataset with machine learning libraries like scikit-learn. This step ensures that the data is well-prepared to work with it and develop a classifier to help diagnose patients effectively. Data cleaning, and data normalization to prepare for modeling.

                        
Index = ['benign', 'malignant']
types_count = df['target'].value_counts()
types_count.index = Index

	mean radius	mean texture	mean perimeter	mean area	mean smoothness	mean compactness	mean concavity	mean concave points	mean symmetry	mean fractal dimension	radius error	texture error	perimeter error	area error	smoothness error	compactness error	concavity error	concave points error	symmetry error	fractal dimension error	worst radius	worst texture	worst perimeter	worst area	worst smoothness	worst compactness	worst concavity	worst concave points	worst symmetry	worst fractal dimension	target
0	17.990	10.38	122.80	1001.0	0.11840	0.27760	0.300100	0.147100	0.2419	0.07871	1.0950	0.9053	8.5890	153.400	0.006399	0.049040	0.053730	0.015870	0.030030	0.006193	25.380	17.33	184.60	2019.0	0.16220	0.66560	0.711900	0.265400	0.4601	0.11890	0.0
1	20.570	17.77	132.90	1326.0	0.08474	0.07864	0.086900	0.070170	0.1812	0.05667	0.5435	0.7339	3.3980	74.080	0.005225	0.013080	0.018600	0.013400	0.013890	0.003532	24.990	23.41	158.80	1956.0	0.12380	0.18660	0.241600	0.186000	0.2750	0.08902	0.0
2	19.690	21.25	130.00	1203.0	0.10960	0.15990	0.197400	0.127900	0.2069	0.05999	0.7456	0.7869	4.5850	94.030	0.006150	0.040060	0.038320	0.020580	0.022500	0.004571	23.570	25.53	152.50	1709.0	0.14440	0.42450	0.450400	0.243000	0.3613	0.08758	0.0
3	11.420	20.38	77.58	386.1	0.14250	0.28390	0.241400	0.105200	0.2597	0.09744	0.4956	1.1560	3.4450	27.230	0.009110	0.074580	0.056610	0.018670	0.059630	0.009208	14.910	26.50	98.87	567.7	0.20980	0.86630	0.686900	0.257500	0.6638	0.17300	0.0
4	20.290	14.34	135.10	1297.0	0.10030	0.13280	0.198000	0.104300	0.1809	0.05883	0.7572	0.7813	5.4380	94.440	0.011490	0.024610	0.056880	0.018850	0.017560	0.005115	22.540	16.67	152.20	1575.0	0.13740	0.20500	0.400000	0.162500	0.2364	0.07678	0.0
5	12.450	15.70	82.57	477.1	0.12780	0.17000	0.157800	0.080890	0.2087	0.07613	0.3345	0.8902	2.2170	27.190	0.007510	0.033450	0.036720	0.011370	0.021650	0.005082	15.470	23.75	103.40	741.6	0.17910	0.52490	0.535500	0.174100	0.3985	0.12440	0.0
6	18.250	19.98	119.60	1040.0	0.09463	0.10900	0.112700	0.074000	0.1794	0.05742	0.4467	0.7732	3.1800	53.910	0.004314	0.013820	0.022540	0.010390	0.013690	0.002179	22.880	27.66	153.20	1606.0	0.14420	0.25760	0.378400	0.193200	0.3063	0.08368	0.0
7	13.710	20.83	90.20	577.9	0.11890	0.16450	0.093660	0.059850	0.2196	0.07451	0.5835	1.3770	3.8560	50.960	0.008805	0.030290	0.024880	0.014480	0.014860	0.005412	17.060	28.14	110.60	897.0	0.16540	0.36820	0.267800	0.155600	0.3196	0.11510	0.0
8	13.000	21.82	87.50	519.8	0.12730	0.19320	0.185900	0.093530	0.2350	0.07389	0.3063	1.0020	2.4060	24.320	0.005731	0.035020	0.035530	0.012260	0.021430	0.003749	15.490	30.73	106.20	739.3	0.17030	0.54010	0.539000	0.206000	0.4378	0.10720	0.0
9	12.460	24.04	83.97	475.9	0.11860	0.23960	0.227300	0.085430	0.2030	0.08243	0.2976	1.5990	2.0390	23.940	0.007149	0.072170	0.077430	0.014320	0.017890	0.010080	15.090	40.68	97.65	711.4	0.18530	1.05800	1.105000	0.221000	0.4366	0.20750	0.0
10	16.020	23.24	102.70	797.8	0.08206	0.06669	0.032990	0.033230	0.1528	0.05697	0.3795	1.1870	2.4660	40.510	0.004029	0.009269	0.011010	0.007591	0.014600	0.003042	19.190	33.88	123.80	1150.0	0.11810	0.15510	0.145900	0.099750	0.2948	0.08452	0.0
11	15.780	17.89	103.60	781.0	0.09710	0.12920	0.099540	0.066060	0.1842	0.06082	0.5058	0.9849	3.5640	54.160	0.005771	0.040610	0.027910	0.012820	0.020080	0.004144	20.420	27.28	136.50	1299.0	0.13960	0.56090	0.396500	0.181000	0.3792	0.10480	0.0
12	19.170	24.80	132.40	1123.0	0.09740	0.24580	0.206500	0.111800	0.2397	0.07800	0.9555	3.5680	11.0700	116.200	0.003139	0.082970	0.088900	0.040900	0.044840	0.012840	20.960	29.94	151.70	1332.0	0.10370	0.39030	0.363900	0.176700	0.3176	0.10230	0.0
13	15.850	23.95	103.70	782.7	0.08401	0.10020	0.099380	0.053640	0.1847	0.05338	0.4033	1.0780	2.9030	36.580	0.009769	0.031260	0.050510	0.019920	0.029810	0.003002	16.840	27.66	112.00	876.5	0.11310	0.19240	0.232200	0.111900	0.2809	0.06287	0.0
14	13.730	22.61	93.60	578.3	0.11310	0.22930	0.212800	0.080250	0.2069	0.07682	0.2121	1.1690	2.0610	19.210	0.006429	0.059360	0.055010	0.016280	0.019610	0.008093	15.030	32.01	108.80	697.7	0.16510	0.77250	0.694300	0.220800	0.3596	0.14310	0.0
15	14.540	27.54	96.73	658.8	0.11390	0.15950	0.163900	0.073640	0.2303	0.07077	0.3700	1.0330	2.8790	32.550	0.005607	0.042400	0.047410	0.010900	0.018570	0.005466	17.460	37.13	124.10	943.2	0.16780	0.65770	0.702600	0.171200	0.4218	0.13410	0.0
16	14.680	20.13	94.74	684.5	0.09867	0.07200	0.073950	0.052590	0.1586	0.05922	0.4727	1.2400	3.1950	45.400	0.005718	0.011620	0.019980	0.011090	0.014100	0.002085	19.070	30.88	123.40	1138.0	0.14640	0.18710	0.291400	0.160900	0.3029	0.08216	0.0
17	16.130	20.68	108.10	798.8	0.11700	0.20220	0.172200	0.102800	0.2164	0.07356	0.5692	1.0730	3.8540	54.180	0.007026	0.025010	0.031880	0.012970	0.016890	0.004142	20.960	31.48	136.80	1315.0	0.17890	0.42330	0.478400	0.207300	0.3706	0.11420	0.0
18	19.810	22.15	130.00	1260.0	0.09831	0.10270	0.147900	0.094980	0.1582	0.05395	0.7582	1.0170	5.8650	112.400	0.006494	0.018930	0.033910	0.015210	0.013560	0.001997	27.320	30.88	186.80	2398.0	0.15120	0.31500	0.537200	0.238800	0.2768	0.07615	0.0
19	13.540	14.36	87.46	566.3	0.09779	0.08129	0.066640	0.047810	0.1885	0.05766	0.2699	0.7886	2.0580	23.560	0.008462	0.014600	0.023870	0.013150	0.019800	0.002300	15.110	19.26	99.70	711.2	0.14400	0.17730	0.239000	0.128800	0.2977	0.07259	1.0
20	13.080	15.71	85.63	520.0	0.10750	0.12700	0.045680	0.031100	0.1967	0.06811	0.1852	0.7477	1.3830	14.670	0.004097	0.018980	0.016980	0.006490	0.016780	0.002425	14.500	20.49	96.09	630.5	0.13120	0.27760	0.189000	0.072830	0.3184	0.08183	1.0
21	9.504	12.44	60.34	273.9	0.10240	0.06492	0.029560	0.020760	0.1815	0.06905	0.2773	0.9768	1.9090	15.700	0.009606	0.014320	0.019850	0.014210	0.020270	0.002968	10.230	15.66	65.13	314.9	0.13240	0.11480	0.088670	0.062270	0.2450	0.07773	1.0
22	15.340	14.26	102.50	704.4	0.10730	0.21350	0.207700	0.097560	0.2521	0.07032	0.4388	0.7096	3.3840	44.910	0.006789	0.053280	0.064460	0.022520	0.036720	0.004394	18.070	19.08	125.10	980.9	0.13900	0.59540	0.630500	0.239300	0.4667	0.09946	0.0
23	21.160	23.04	137.20	1404.0	0.09428	0.10220	0.109700	0.086320	0.1769	0.05278	0.6917	1.1270	4.3030	93.990	0.004728	0.012590	0.017150	0.010380	0.010830	0.001987	29.170	35.59	188.00	2615.0	0.14010	0.26000	0.315500	0.200900	0.2822	0.07526	0.0
24	16.650	21.38	110.00	904.6	0.11210	0.14570	0.152500	0.091700	0.1995	0.06330	0.8068	0.9017	5.4550	102.600	0.006048	0.018820	0.027410	0.011300	0.014680	0.002801	26.460	31.56	177.00	2215.0	0.18050	0.35780	0.469500	0.209500	0.3613	0.09564	0.0
25	17.140	16.40	116.00	912.7	0.11860	0.22760	0.222900	0.140100	0.3040	0.07413	1.0460	0.9760	7.2760	111.400	0.008029	0.037990	0.037320	0.023970	0.023080	0.007444	22.250	21.40	152.40	1461.0	0.15450	0.39490	0.385300	0.255000	0.4066	0.10590	0.0
26	14.580	21.53	97.41	644.8	0.10540	0.18680	0.142500	0.087830	0.2252	0.06924	0.2545	0.9832	2.1100	21.050	0.004452	0.030550	0.026810	0.013520	0.014540	0.003711	17.620	33.21	122.40	896.9	0.15250	0.66430	0.553900	0.270100	0.4264	0.12750	0.0
27	18.610	20.25	122.10	1094.0	0.09440	0.10660	0.149000	0.077310	0.1697	0.05699	0.8529	1.8490	5.6320	93.540	0.010750	0.027220	0.050810	0.019110	0.022930	0.004217	21.310	27.26	139.90	1403.0	0.13380	0.21170	0.344600	0.149000	0.2341	0.07421	0.0
28	15.300	25.27	102.40	732.4	0.10820	0.16970	0.168300	0.087510	0.1926	0.06540	0.4390	1.0120	3.4980	43.500	0.005233	0.030570	0.035760	0.010830	0.017680	0.002967	20.270	36.71	149.30	1269.0	0.16410	0.61100	0.633500	0.202400	0.4027	0.09876	0.0
29	17.570	15.05	115.00	955.1	0.09847	0.11570	0.098750	0.079530	0.1739	0.06149	0.6003	0.8225	4.6550	61.100	0.005627	0.030330	0.034070	0.013540	0.019250	0.003742	20.010	19.52	134.90	1227.0	0.12550	0.28120	0.248900	0.145600	0.2756	0.07919	0.0
30	18.630	25.11	124.80	1088.0	0.10640	0.18870	0.231900	0.124400	0.2183	0.06197	0.8307	1.4660	5.5740	105.000	0.006248	0.033740	0.051960	0.011580	0.020070	0.004560	23.150	34.01	160.50	1670.0	0.14910	0.42570	0.613300	0.184800	0.3444	0.09782	0.0
31	11.840	18.70	77.93	440.6	0.11090	0.15160	0.121800	0.051820	0.2301	0.07799	0.4825	1.0300	3.4750	41.000	0.005551	0.034140	0.042050	0.010440	0.022730	0.005667	16.820	28.12	119.40	888.7	0.16370	0.57750	0.695600	0.154600	0.4761	0.14020	0.0
32	17.020	23.98	112.80	899.3	0.11970	0.14960	0.241700	0.120300	0.2248	0.06382	0.6009	1.3980	3.9990	67.780	0.008268	0.030820	0.050420	0.011120	0.021020	0.003854	20.880	32.09	136.10	1344.0	0.16340	0.35590	0.558800	0.184700	0.3530	0.08482	0.0
33	19.270	26.47	127.90	1162.0	0.09401	0.17190	0.165700	0.075930	0.1853	0.06261	0.5558	0.6062	3.5280	68.170	0.005015	0.033180	0.034970	0.009643	0.015430	0.003896	24.150	30.90	161.40	1813.0	0.15090	0.65900	0.609100	0.178500	0.3672	0.11230	0.0
34	16.130	17.88	107.00	807.2	0.10400	0.15590	0.135400	0.077520	0.1998	0.06515	0.3340	0.6857	2.1830	35.030	0.004185	0.028680	0.026640	0.009067	0.017030	0.003817	20.210	27.26	132.70	1261.0	0.14460	0.58040	0.527400	0.186400	0.4270	0.12330	0.0
35	16.740	21.59	110.10	869.5	0.09610	0.13360	0.134800	0.060180	0.1896	0.05656	0.4615	0.9197	3.0080	45.190	0.005776	0.024990	0.036950	0.011950	0.027890	0.002665	20.010	29.02	133.50	1229.0	0.15630	0.38350	0.540900	0.181300	0.4863	0.08633	0.0
36	14.250	21.72	93.63	633.0	0.09823	0.10980	0.131900	0.055980	0.1885	0.06125	0.2860	1.0190	2.6570	24.910	0.005878	0.029950	0.048150	0.011610	0.020280	0.004022	15.890	30.36	116.20	799.6	0.14460	0.42380	0.518600	0.144700	0.3591	0.10140	0.0
37	13.030	18.42	82.61	523.8	0.08983	0.03766	0.025620	0.029230	0.1467	0.05863	0.1839	2.3420	1.1700	14.160	0.004352	0.004899	0.013430	0.011640	0.026710	0.001777	13.300	22.81	84.46	545.9	0.09701	0.04619	0.048330	0.050130	0.1987	0.06169	1.0
38	14.990	25.20	95.54	698.8	0.09387	0.05131	0.023980	0.028990	0.1565	0.05504	1.2140	2.1880	8.0770	106.000	0.006883	0.010940	0.018180	0.019170	0.007882	0.001754	14.990	25.20	95.54	698.8	0.09387	0.05131	0.023980	0.028990	0.1565	0.05504	0.0
39	13.480	20.82	88.40	559.2	0.10160	0.12550	0.106300	0.054390	0.1720	0.06419	0.2130	0.5914	1.5450	18.520	0.005367	0.022390	0.030490	0.012620	0.013770	0.003187	15.530	26.02	107.30	740.4	0.16100	0.42250	0.503000	0.225800	0.2807	0.10710	0.0
40	13.440	21.58	86.18	563.0	0.08162	0.06031	0.031100	0.020310	0.1784	0.05587	0.2385	0.8265	1.5720	20.530	0.003280	0.011020	0.013900	0.006881	0.013800	0.001286	15.930	30.25	102.50	787.9	0.10940	0.20430	0.208500	0.111200	0.2994	0.07146	0.0
41	10.950	21.35	71.90	371.1	0.12270	0.12180	0.104400	0.056690	0.1895	0.06870	0.2366	1.4280	1.8220	16.970	0.008064	0.017640	0.025950	0.010370	0.013570	0.003040	12.840	35.34	87.22	514.0	0.19090	0.26980	0.402300	0.142400	0.2964	0.09606	0.0
42	19.070	24.81	128.30	1104.0	0.09081	0.21900	0.210700	0.099610	0.2310	0.06343	0.9811	1.6660	8.8300	104.900	0.006548	0.100600	0.097230	0.026380	0.053330	0.007646	24.090	33.17	177.40	1651.0	0.12470	0.74440	0.724200	0.249300	0.4670	0.10380	0.0
43	13.280	20.28	87.32	545.2	0.10410	0.14360	0.098470	0.061580	0.1974	0.06782	0.3704	0.8249	2.4270	31.330	0.005072	0.021470	0.021850	0.009560	0.017190	0.003317	17.380	28.00	113.10	907.2	0.15300	0.37240	0.366400	0.149200	0.3739	0.10270	0.0
44	13.170	21.81	85.42	531.5	0.09714	0.10470	0.082590	0.052520	0.1746	0.06177	0.1938	0.6123	1.3340	14.490	0.003350	0.013840	0.014520	0.006853	0.011130	0.001720	16.230	29.89	105.50	740.7	0.15030	0.39040	0.372800	0.160700	0.3693	0.09618	0.0
45	18.650	17.60	123.70	1076.0	0.10990	0.16860	0.197400	0.100900	0.1907	0.06049	0.6289	0.6633	4.2930	71.560	0.006294	0.039940	0.055540	0.016950	0.024280	0.003535	22.820	21.32	150.60	1567.0	0.16790	0.50900	0.734500	0.237800	0.3799	0.09185	0.0
46	8.196	16.84	51.71	201.9	0.08600	0.05943	0.015880	0.005917	0.1769	0.06503	0.1563	0.9567	1.0940	8.205	0.008968	0.016460	0.015880	0.005917	0.025740	0.002582	8.964	21.96	57.26	242.2	0.12970	0.13570	0.068800	0.025640	0.3105	0.07409	1.0
47	13.170	18.66	85.98	534.6	0.11580	0.12310	0.122600	0.073400	0.2128	0.06777	0.2871	0.8937	1.8970	24.250	0.006532	0.023360	0.029050	0.012150	0.017430	0.003643	15.670	27.95	102.80	759.4	0.17860	0.41660	0.500600	0.208800	0.3900	0.11790	0.0
48	12.050	14.63	78.04	449.3	0.10310	0.09092	0.065920	0.027490	0.1675	0.06043	0.2636	0.7294	1.8480	19.870	0.005488	0.014270	0.023220	0.005660	0.014280	0.002422	13.760	20.70	89.88	582.6	0.14940	0.21560	0.305000	0.065480	0.2747	0.08301	1.0
49	13.490	22.30	86.91	561.0	0.08752	0.07698	0.047510	0.033840	0.1809	0.05718	0.2338	1.3530	1.7350	20.200	0.004455	0.013820	0.020950	0.011840	0.016410	0.001956	15.150	31.82	99.00	698.8	0.11620	0.17110	0.228200	0.128200	0.2871	0.06917	1.0
50	11.760	21.60	74.72	427.9	0.08637	0.04966	0.016570	0.011150	0.1495	0.05888	0.4062	1.2100	2.6350	28.470	0.005857	0.009758	0.011680	0.007445	0.024060	0.001769	12.980	25.72	82.98	516.5	0.10850	0.08615	0.055230	0.037150	0.2433	0.06563	1.0
51	13.640	16.34	87.21	571.8	0.07685	0.06059	0.018570	0.017230	0.1353	0.05953	0.1872	0.9234	1.4490	14.550	0.004477	0.011770	0.010790	0.007956	0.013250	0.002551	14.670	23.19	96.08	656.7	0.10890	0.15820	0.105000	0.085860	0.2346	0.08025	1.0
52	11.940	18.24	75.71	437.6	0.08261	0.04751	0.019720	0.013490	0.1868	0.06110	0.2273	0.6329	1.5200	17.470	0.007210	0.008380	0.013110	0.008000	0.019960	0.002635	13.100	21.33	83.67	527.2	0.11440	0.08906	0.092030	0.062960	0.2785	0.07408	1.0
53	18.220	18.70	120.30	1033.0	0.11480	0.14850	0.177200	0.106000	0.2092	0.06310	0.8337	1.5930	4.8770	98.810	0.003899	0.029610	0.028170	0.009222	0.026740	0.005126	20.600	24.13	135.10	1321.0	0.12800	0.22970	0.262300	0.132500	0.3021	0.07987	0.0
54	15.100	22.02	97.26	712.8	0.09056	0.07081	0.052530	0.033340	0.1616	0.05684	0.3105	0.8339	2.0970	29.910	0.004675	0.010300	0.016030	0.009222	0.010950	0.001629	18.100	31.69	117.70	1030.0	0.13890	0.20570	0.271200	0.153000	0.2675	0.07873	0.0
55	11.520	18.75	73.34	409.0	0.09524	0.05473	0.030360	0.022780	0.1920	0.05907	0.3249	0.9591	2.1830	23.470	0.008328	0.008722	0.013490	0.008670	0.032180	0.002386	12.840	22.47	81.81	506.2	0.12490	0.08720	0.090760	0.063160	0.3306	0.07036	1.0
56	19.210	18.57	125.50	1152.0	0.10530	0.12670	0.132300	0.089940	0.1917	0.05961	0.7275	1.1930	4.8370	102.500	0.006458	0.023060	0.029450	0.015380	0.018520	0.002608	26.140	28.14	170.10	2145.0	0.16240	0.35110	0.387900	0.209100	0.3537	0.08294	0.0
57	14.710	21.59	95.55	656.9	0.11370	0.13650	0.129300	0.081230	0.2027	0.06758	0.4226	1.1500	2.7350	40.090	0.003659	0.028550	0.025720	0.012720	0.018170	0.004108	17.870	30.70	115.70	985.5	0.13680	0.42900	0.358700	0.183400	0.3698	0.10940	0.0
58	13.050	19.31	82.61	527.2	0.08060	0.03789	0.000692	0.004167	0.1819	0.05501	0.4040	1.2140	2.5950	32.960	0.007491	0.008593	0.000692	0.004167	0.021900	0.002990	14.230	22.25	90.24	624.1	0.10210	0.06191	0.001845	0.011110	0.2439	0.06289	1.0
59	8.618	11.79	54.34	224.5	0.09752	0.05272	0.020610	0.007799	0.1683	0.07187	0.1559	0.5796	1.0460	8.322	0.010110	0.010550	0.019810	0.005742	0.020900	0.002788	9.507	15.40	59.90	274.9	0.17330	0.12390	0.116800	0.044190	0.3220	0.09026	1.0
60	10.170	14.88	64.55	311.9	0.11340	0.08061	0.010840	0.012900	0.2743	0.06960	0.5158	1.4410	3.3120	34.620	0.007514	0.010990	0.007665	0.008193	0.041830	0.005953	11.020	17.45	69.86	368.6	0.12750	0.09866	0.021680	0.025790	0.3557	0.08020	1.0
61	8.598	20.98	54.66	221.8	0.12430	0.08963	0.030000	0.009259	0.1828	0.06757	0.3582	2.0670	2.4930	18.390	0.011930	0.031620	0.030000	0.009259	0.033570	0.003048	9.565	27.04	62.06	273.9	0.16390	0.16980	0.090010	0.027780	0.2972	0.07712	1.0
62	14.250	22.15	96.42	645.7	0.10490	0.20080	0.213500	0.086530	0.1949	0.07292	0.7036	1.2680	5.3730	60.780	0.009407	0.070560	0.068990	0.018480	0.017000	0.006113	17.670	29.51	119.10	959.5	0.16400	0.62470	0.692200	0.178500	0.2844	0.11320	0.0
63	9.173	13.86	59.20	260.9	0.07721	0.08751	0.059880	0.021800	0.2341	0.06963	0.4098	2.2650	2.6080	23.520	0.008738	0.039380	0.043120	0.015600	0.041920	0.005822	10.010	19.23	65.59	310.1	0.09836	0.16780	0.139700	0.050870	0.3282	0.08490	1.0
64	12.680	23.84	82.69	499.0	0.11220	0.12620	0.112800	0.068730	0.1905	0.06590	0.4255	1.1780	2.9270	36.460	0.007781	0.026480	0.029730	0.012900	0.016350	0.003601	17.090	33.47	111.80	888.3	0.18510	0.40610	0.402400	0.171600	0.3383	0.10310	0.0
65	14.780	23.94	97.40	668.3	0.11720	0.14790	0.126700	0.090290	0.1953	0.06654	0.3577	1.2810	2.4500	35.240	0.006703	0.023100	0.023150	0.011840	0.019000	0.003224	17.310	33.39	114.60	925.1	0.16480	0.34160	0.302400	0.161400	0.3321	0.08911	0.0
66	9.465	21.01	60.11	269.4	0.10440	0.07773	0.021720	0.015040	0.1717	0.06899	0.2351	2.0110	1.6600	14.200	0.010520	0.017550	0.017140	0.009333	0.022790	0.004237	10.410	31.56	67.03	330.7	0.15480	0.16640	0.094120	0.065170	0.2878	0.09211	1.0
67	11.310	19.04	71.80	394.1	0.08139	0.04701	0.037090	0.022300	0.1516	0.05667	0.2727	0.9429	1.8310	18.150	0.009282	0.009216	0.020630	0.008965	0.021830	0.002146	12.330	23.84	78.00	466.7	0.12900	0.09148	0.144400	0.069610	0.2400	0.06641	1.0
68	9.029	17.33	58.79	250.5	0.10660	0.14130	0.313000	0.043750	0.2111	0.08046	0.3274	1.1940	1.8850	17.670	0.009549	0.086060	0.303800	0.033220	0.041970	0.009559	10.310	22.65	65.50	324.7	0.14820	0.43650	1.252000	0.175000	0.4228	0.11750	1.0
69	12.780	16.49	81.37	502.5	0.09831	0.05234	0.036530	0.028640	0.1590	0.05653	0.2368	0.8732	1.4710	18.330	0.007962	0.005612	0.015850	0.008662	0.022540	0.001906	13.460	19.76	85.67	554.9	0.12960	0.07061	0.103900	0.058820	0.2383	0.06410	1.0
70	18.940	21.31	123.60	1130.0	0.09009	0.10290	0.108000	0.079510	0.1582	0.05461	0.7888	0.7975	5.4860	96.050	0.004444	0.016520	0.022690	0.013700	0.013860	0.001698	24.860	26.58	165.90	1866.0	0.11930	0.23360	0.268700	0.178900	0.2551	0.06589	0.0
71	8.888	14.64	58.79	244.0	0.09783	0.15310	0.086060	0.028720	0.1902	0.08980	0.5262	0.8522	3.1680	25.440	0.017210	0.093680	0.056710	0.017660	0.025410	0.021930	9.733	15.67	62.56	284.4	0.12070	0.24360	0.143400	0.047860	0.2254	0.10840	1.0
72	17.200	24.52	114.20	929.4	0.10710	0.18300	0.169200	0.079440	0.1927	0.06487	0.5907	1.0410	3.7050	69.470	0.005820	0.056160	0.042520	0.011270	0.015270	0.006299	23.320	33.82	151.60	1681.0	0.15850	0.73940	0.656600	0.189900	0.3313	0.13390	0.0
73	13.800	15.79	90.43	584.1	0.10070	0.12800	0.077890	0.050690	0.1662	0.06566	0.2787	0.6205	1.9570	23.350	0.004717	0.020650	0.017590	0.009206	0.012200	0.003130	16.570	20.86	110.30	812.4	0.14110	0.35420	0.277900	0.138300	0.2589	0.10300	0.0
74	12.310	16.52	79.19	470.9	0.09172	0.06829	0.033720	0.022720	0.1720	0.05914	0.2505	1.0250	1.7400	19.680	0.004854	0.018190	0.018260	0.007965	0.013860	0.002304	14.110	23.21	89.71	611.1	0.11760	0.18430	0.170300	0.086600	0.2618	0.07609	1.0
75	16.070	19.65	104.10	817.7	0.09168	0.08424	0.097690	0.066380	0.1798	0.05391	0.7474	1.0160	5.0290	79.250	0.010820	0.022030	0.035000	0.018090	0.015500	0.001948	19.770	24.56	128.80	1223.0	0.15000	0.20450	0.282900	0.152000	0.2650	0.06387	0.0
76	13.530	10.94	87.91	559.2	0.12910	0.10470	0.068770	0.065560	0.2403	0.06641	0.4101	1.0140	2.6520	32.650	0.013400	0.028390	0.011620	0.008239	0.025720	0.006164	14.080	12.49	91.36	605.5	0.14510	0.13790	0.085390	0.074070	0.2710	0.07191	1.0
77	18.050	16.15	120.20	1006.0	0.10650	0.21460	0.168400	0.108000	0.2152	0.06673	0.9806	0.5505	6.3110	134.800	0.007940	0.058390	0.046580	0.020700	0.025910	0.007054	22.390	18.91	150.10	1610.0	0.14780	0.56340	0.378600	0.210200	0.3751	0.11080	0.0
78	20.180	23.97	143.70	1245.0	0.12860	0.34540	0.375400	0.160400	0.2906	0.08142	0.9317	1.8850	8.6490	116.400	0.010380	0.068350	0.109100	0.025930	0.078950	0.005987	23.370	31.72	170.30	1623.0	0.16390	0.61640	0.768100	0.250800	0.5440	0.09964	0.0
79	12.860	18.00	83.19	506.3	0.09934	0.09546	0.038890	0.023150	0.1718	0.05997	0.2655	1.0950	1.7780	20.350	0.005293	0.016610	0.020710	0.008179	0.017480	0.002848	14.240	24.82	91.88	622.1	0.12890	0.21410	0.173100	0.079260	0.2779	0.07918	1.0
80	11.450	20.97	73.81	401.5	0.11020	0.09362	0.045910	0.022330	0.1842	0.07005	0.3251	2.1740	2.0770	24.620	0.010370	0.017060	0.025860	0.007506	0.018160	0.003976	13.110	32.16	84.53	525.1	0.15570	0.16760	0.175500	0.061270	0.2762	0.08851	1.0
81	13.340	15.86	86.49	520.0	0.10780	0.15350	0.116900	0.069870	0.1942	0.06902	0.2860	1.0160	1.5350	12.960	0.006794	0.035750	0.039800	0.013830	0.021340	0.004603	15.530	23.19	96.66	614.9	0.15360	0.47910	0.485800	0.170800	0.3527	0.10160	1.0
82	25.220	24.91	171.50	1878.0	0.10630	0.26650	0.333900	0.184500	0.1829	0.06782	0.8973	1.4740	7.3820	120.000	0.008166	0.056930	0.057300	0.020300	0.010650	0.005893	30.000	33.62	211.70	2562.0	0.15730	0.60760	0.647600	0.286700	0.2355	0.10510	0.0
83	19.100	26.29	129.10	1132.0	0.12150	0.17910	0.193700	0.146900	0.1634	0.07224	0.5190	2.9100	5.8010	67.100	0.007545	0.060500	0.021340	0.018430	0.030560	0.010390	20.330	32.72	141.30	1298.0	0.13920	0.28170	0.243200	0.184100	0.2311	0.09203	0.0
84	12.000	15.65	76.95	443.3	0.09723	0.07165	0.041510	0.018630	0.2079	0.05968	0.2271	1.2550	1.4410	16.160	0.005969	0.018120	0.020070	0.007027	0.019720	0.002607	13.670	24.90	87.78	567.9	0.13770	0.20030	0.226700	0.076320	0.3379	0.07924	1.0
85	18.460	18.52	121.10	1075.0	0.09874	0.10530	0.133500	0.087950	0.2132	0.06022	0.6997	1.4750	4.7820	80.600	0.006471	0.016490	0.028060	0.014200	0.023700	0.003755	22.930	27.68	152.20	1603.0	0.13980	0.20890	0.315700	0.164200	0.3695	0.08579	0.0
86	14.480	21.46	94.25	648.2	0.09444	0.09947	0.120400	0.049380	0.2075	0.05636	0.4204	2.2200	3.3010	38.870	0.009369	0.029830	0.053710	0.017610	0.024180	0.003249	16.210	29.25	108.40	808.9	0.13060	0.19760	0.334900	0.122500	0.3020	0.06846	0.0
87	19.020	24.59	122.00	1076.0	0.09029	0.12060	0.146800	0.082710	0.1953	0.05629	0.5495	0.6636	3.0550	57.650	0.003872	0.018420	0.037100	0.012000	0.019640	0.003337	24.560	30.41	152.90	1623.0	0.12490	0.32060	0.575500	0.195600	0.3956	0.09288	0.0
88	12.360	21.80	79.78	466.1	0.08772	0.09445	0.060150	0.037450	0.1930	0.06404	0.2978	1.5020	2.2030	20.950	0.007112	0.024930	0.027030	0.012930	0.019580	0.004463	13.830	30.50	91.46	574.7	0.13040	0.24630	0.243400	0.120500	0.2972	0.09261	1.0
89	14.640	15.24	95.77	651.9	0.11320	0.13390	0.099660	0.070640	0.2116	0.06346	0.5115	0.7372	3.8140	42.760	0.005508	0.044120	0.044360	0.016230	0.024270	0.004841	16.340	18.24	109.40	803.6	0.12770	0.30890	0.260400	0.139700	0.3151	0.08473	1.0
90	14.620	24.02	94.57	662.7	0.08974	0.08606	0.031020	0.029570	0.1685	0.05866	0.3721	1.1110	2.2790	33.760	0.004868	0.018180	0.011210	0.008606	0.020850	0.002893	16.110	29.11	102.90	803.7	0.11150	0.17660	0.091890	0.069460	0.2522	0.07246	1.0
91	15.370	22.76	100.20	728.2	0.09200	0.10360	0.112200	0.074830	0.1717	0.06097	0.3129	0.8413	2.0750	29.440	0.009882	0.024440	0.045310	0.017630	0.024710	0.002142	16.430	25.84	107.50	830.9	0.12570	0.19970	0.284600	0.147600	0.2556	0.06828	0.0
92	13.270	14.76	84.74	551.7	0.07355	0.05055	0.032610	0.026480	0.1386	0.05318	0.4057	1.1530	2.7010	36.350	0.004481	0.010380	0.013580	0.010820	0.010690	0.001435	16.360	22.35	104.50	830.6	0.10060	0.12380	0.135000	0.100100	0.2027	0.06206	1.0
93	13.450	18.30	86.60	555.1	0.10220	0.08165	0.039740	0.027800	0.1638	0.05710	0.2950	1.3730	2.0990	25.220	0.005884	0.014910	0.018720	0.009366	0.018840	0.001817	15.100	25.94	97.59	699.4	0.13390	0.17510	0.138100	0.079110	0.2678	0.06603	1.0
94	15.060	19.83	100.30	705.6	0.10390	0.15530	0.170000	0.088150	0.1855	0.06284	0.4768	0.9644	3.7060	47.140	0.009250	0.037150	0.048670	0.018510	0.014980	0.003520	18.230	24.23	123.50	1025.0	0.15510	0.42030	0.520300	0.211500	0.2834	0.08234	0.0
95	20.260	23.03	132.40	1264.0	0.09078	0.13130	0.146500	0.086830	0.2095	0.05649	0.7576	1.5090	4.5540	87.870	0.006016	0.034820	0.042320	0.012690	0.026570	0.004411	24.220	31.59	156.10	1750.0	0.11900	0.35390	0.409800	0.157300	0.3689	0.08368	0.0
96	12.180	17.84	77.79	451.1	0.10450	0.07057	0.024900	0.029410	0.1900	0.06635	0.3661	1.5110	2.4100	24.440	0.005433	0.011790	0.011310	0.015190	0.022200	0.003408	12.830	20.92	82.14	495.2	0.11400	0.09358	0.049800	0.058820	0.2227	0.07376	1.0
97	9.787	19.94	62.11	294.5	0.10240	0.05301	0.006829	0.007937	0.1350	0.06890	0.3350	2.0430	2.1320	20.050	0.011130	0.014630	0.005308	0.005250	0.018010	0.005667	10.920	26.29	68.81	366.1	0.13160	0.09473	0.020490	0.023810	0.1934	0.08988	1.0
98	11.600	12.84	74.34	412.6	0.08983	0.07525	0.041960	0.033500	0.1620	0.06582	0.2315	0.5391	1.4750	15.750	0.006153	0.013300	0.016930	0.006884	0.016510	0.002551	13.060	17.16	82.96	512.5	0.14310	0.18510	0.192200	0.084490	0.2772	0.08756	1.0
99	14.420	19.77	94.48	642.5	0.09752	0.11410	0.093880	0.058390	0.1879	0.06390	0.2895	1.8510	2.3760	26.850	0.008005	0.028950	0.033210	0.014240	0.014620	0.004452	16.330	30.86	109.50	826.4	0.14310	0.30260	0.319400	0.156500	0.2718	0.09353	0.0
100	13.610	24.98	88.05	582.7	0.09488	0.08511	0.086250	0.044890	0.1609	0.05871	0.4565	1.2900	2.8610	43.140	0.005872	0.014880	0.026470	0.009921	0.014650	0.002355	16.990	35.27	108.60	906.5	0.12650	0.19430	0.316900	0.118400	0.2651	0.07397	0.0
101	6.981	13.43	43.79	143.5	0.11700	0.07568	0.000000	0.000000	0.1930	0.07818	0.2241	1.5080	1.5530	9.833	0.010190	0.010840	0.000000	0.000000	0.026590	0.004100	7.930	19.54	50.41	185.2	0.15840	0.12020	0.000000	0.000000	0.2932	0.09382	1.0
102	12.180	20.52	77.22	458.7	0.08013	0.04038	0.023830	0.017700	0.1739	0.05677	0.1924	1.5710	1.1830	14.680	0.005080	0.006098	0.010690	0.006797	0.014470	0.001532	13.340	32.84	84.58	547.8	0.11230	0.08862	0.114500	0.074310	0.2694	0.06878	1.0
103	9.876	19.40	63.95	298.3	0.10050	0.09697	0.061540	0.030290	0.1945	0.06322	0.1803	1.2220	1.5280	11.770	0.009058	0.021960	0.030290	0.011120	0.016090	0.003570	10.760	26.83	72.22	361.2	0.15590	0.23020	0.264400	0.097490	0.2622	0.08490	1.0
104	10.490	19.29	67.41	336.1	0.09989	0.08578	0.029950	0.012010	0.2217	0.06481	0.3550	1.5340	2.3020	23.130	0.007595	0.022190	0.028800	0.008614	0.027100	0.003451	11.540	23.31	74.22	402.8	0.12190	0.14860	0.079870	0.032030	0.2826	0.07552	1.0
105	13.110	15.56	87.21	530.2	0.13980	0.17650	0.207100	0.096010	0.1925	0.07692	0.3908	0.9238	2.4100	34.660	0.007162	0.029120	0.054730	0.013880	0.015470	0.007098	16.310	22.40	106.40	827.2	0.18620	0.40990	0.637600	0.198600	0.3147	0.14050	0.0
106	11.640	18.33	75.17	412.5	0.11420	0.10170	0.070700	0.034850	0.1801	0.06520	0.3060	1.6570	2.1550	20.620	0.008540	0.023100	0.029450	0.013980	0.015650	0.003840	13.140	29.26	85.51	521.7	0.16880	0.26600	0.287300	0.121800	0.2806	0.09097	1.0
107	12.360	18.54	79.01	466.7	0.08477	0.06815	0.026430	0.019210	0.1602	0.06066	0.1199	0.8944	0.8484	9.227	0.003457	0.010470	0.011670	0.005558	0.012510	0.001356	13.290	27.49	85.56	544.1	0.11840	0.19630	0.193700	0.084420	0.2983	0.07185	1.0
108	22.270	19.67	152.80	1509.0	0.13260	0.27680	0.426400	0.182300	0.2556	0.07039	1.2150	1.5450	10.0500	170.000	0.006515	0.086680	0.104000	0.024800	0.031120	0.005037	28.400	28.01	206.80	2360.0	0.17010	0.69970	0.960800	0.291000	0.4055	0.09789	0.0
109	11.340	21.26	72.48	396.5	0.08759	0.06575	0.051330	0.018990	0.1487	0.06529	0.2344	0.9861	1.5970	16.410	0.009113	0.015570	0.024430	0.006435	0.015680	0.002477	13.010	29.15	83.99	518.1	0.16990	0.21960	0.312000	0.082780	0.2829	0.08832	1.0
110	9.777	16.99	62.50	290.2	0.10370	0.08404	0.043340	0.017780	0.1584	0.07065	0.4030	1.4240	2.7470	22.870	0.013850	0.029320	0.027220	0.010230	0.032810	0.004638	11.050	21.47	71.68	367.0	0.14670	0.17650	0.130000	0.053340	0.2533	0.08468	1.0
111	12.630	20.76	82.15	480.4	0.09933	0.12090	0.106500	0.060210	0.1735	0.07070	0.3424	1.8030	2.7110	20.480	0.012910	0.040420	0.051010	0.022950	0.021440	0.005891	13.330	25.47	89.00	527.4	0.12870	0.22500	0.221600	0.110500	0.2226	0.08486	1.0
112	14.260	19.65	97.83	629.9	0.07837	0.22330	0.300300	0.077980	0.1704	0.07769	0.3628	1.4900	3.3990	29.250	0.005298	0.074460	0.143500	0.022920	0.025660	0.012980	15.300	23.73	107.00	709.0	0.08949	0.41930	0.678300	0.150500	0.2398	0.10820	1.0
113	10.510	20.19	68.64	334.2	0.11220	0.13030	0.064760	0.030680	0.1922	0.07782	0.3336	1.8600	2.0410	19.910	0.011880	0.037470	0.045910	0.015440	0.022870	0.006792	11.160	22.75	72.62	374.4	0.13000	0.20490	0.129500	0.061360	0.2383	0.09026	1.0
114	8.726	15.83	55.84	230.9	0.11500	0.08201	0.041320	0.019240	0.1649	0.07633	0.1665	0.5864	1.3540	8.966	0.008261	0.022130	0.032590	0.010400	0.017080	0.003806	9.628	19.62	64.48	284.4	0.17240	0.23640	0.245600	0.105000	0.2926	0.10170	1.0
115	11.930	21.53	76.53	438.6	0.09768	0.07849	0.033280	0.020080	0.1688	0.06194	0.3118	0.9227	2.0000	24.790	0.007803	0.025070	0.018350	0.007711	0.012780	0.003856	13.670	26.15	87.54	583.0	0.15000	0.23990	0.150300	0.072470	0.2438	0.08541	1.0
116	8.950	15.76	58.74	245.2	0.09462	0.12430	0.092630	0.023080	0.1305	0.07163	0.3132	0.9789	3.2800	16.940	0.018350	0.067600	0.092630	0.023080	0.023840	0.005601	9.414	17.07	63.34	270.0	0.11790	0.18790	0.154400	0.038460	0.1652	0.07722	1.0
117	14.870	16.67	98.64	682.5	0.11620	0.16490	0.169000	0.089230	0.2157	0.06768	0.4266	0.9489	2.9890	41.180	0.006985	0.025630	0.030110	0.012710	0.016020	0.003884	18.810	27.37	127.10	1095.0	0.18780	0.44800	0.470400	0.202700	0.3585	0.10650	0.0
118	15.780	22.91	105.70	782.6	0.11550	0.17520	0.213300	0.094790	0.2096	0.07331	0.5520	1.0720	3.5980	58.630	0.008699	0.039760	0.059500	0.013900	0.014950	0.005984	20.190	30.50	130.30	1272.0	0.18550	0.49250	0.735600	0.203400	0.3274	0.12520	0.0
119	17.950	20.01	114.20	982.0	0.08402	0.06722	0.072930	0.055960	0.2129	0.05025	0.5506	1.2140	3.3570	54.040	0.004024	0.008422	0.022910	0.009863	0.050140	0.001902	20.580	27.83	129.20	1261.0	0.10720	0.12020	0.224900	0.118500	0.4882	0.06111	0.0
120	11.410	10.82	73.34	403.3	0.09373	0.06685	0.035120	0.026230	0.1667	0.06113	0.1408	0.4607	1.1030	10.500	0.006040	0.015290	0.015140	0.006460	0.013440	0.002206	12.820	15.97	83.74	510.5	0.15480	0.23900	0.210200	0.089580	0.3016	0.08523	1.0
121	18.660	17.12	121.40	1077.0	0.10540	0.11000	0.145700	0.086650	0.1966	0.06213	0.7128	1.5810	4.8950	90.470	0.008102	0.021010	0.033420	0.016010	0.020450	0.004570	22.250	24.90	145.40	1549.0	0.15030	0.22910	0.327200	0.167400	0.2894	0.08456	0.0
122	24.250	20.20	166.20	1761.0	0.14470	0.28670	0.426800	0.201200	0.2655	0.06877	1.5090	3.1200	9.8070	233.000	0.023330	0.098060	0.127800	0.018220	0.045470	0.009875	26.020	23.99	180.90	2073.0	0.16960	0.42440	0.580300	0.224800	0.3222	0.08009	0.0
123	14.500	10.89	94.28	640.7	0.11010	0.10990	0.088420	0.057780	0.1856	0.06402	0.2929	0.8570	1.9280	24.190	0.003818	0.012760	0.028820	0.012000	0.019100	0.002808	15.700	15.98	102.80	745.5	0.13130	0.17880	0.256000	0.122100	0.2889	0.08006	1.0
124	13.370	16.39	86.10	553.5	0.07115	0.07325	0.080920	0.028000	0.1422	0.05823	0.1639	1.1400	1.2230	14.660	0.005919	0.032700	0.049570	0.010380	0.012080	0.004076	14.260	22.75	91.99	632.1	0.10250	0.25310	0.330800	0.089780	0.2048	0.07628	1.0
125	13.850	17.21	88.44	588.7	0.08785	0.06136	0.014200	0.011410	0.1614	0.05890	0.2185	0.8561	1.4950	17.910	0.004599	0.009169	0.009127	0.004814	0.012470	0.001708	15.490	23.58	100.30	725.9	0.11570	0.13500	0.081150	0.051040	0.2364	0.07182	1.0
126	13.610	24.69	87.76	572.6	0.09258	0.07862	0.052850	0.030850	0.1761	0.06130	0.2310	1.0050	1.7520	19.830	0.004088	0.011740	0.017960	0.006880	0.013230	0.001465	16.890	35.64	113.20	848.7	0.14710	0.28840	0.379600	0.132900	0.3470	0.07900	0.0
127	19.000	18.91	123.40	1138.0	0.08217	0.08028	0.092710	0.056270	0.1946	0.05044	0.6896	1.3420	5.2160	81.230	0.004428	0.027310	0.040400	0.013610	0.020300	0.002686	22.320	25.73	148.20	1538.0	0.10210	0.22640	0.320700	0.121800	0.2841	0.06541	0.0
128	15.100	16.39	99.58	674.5	0.11500	0.18070	0.113800	0.085340	0.2001	0.06467	0.4309	1.0680	2.7960	39.840	0.009006	0.041850	0.032040	0.022580	0.023530	0.004984	16.110	18.33	105.90	762.6	0.13860	0.28830	0.196000	0.142300	0.2590	0.07779	1.0
129	19.790	25.12	130.40	1192.0	0.10150	0.15890	0.254500	0.114900	0.2202	0.06113	0.4953	1.1990	2.7650	63.330	0.005033	0.031790	0.047550	0.010430	0.015780	0.003224	22.630	33.58	148.70	1589.0	0.12750	0.38610	0.567300	0.173200	0.3305	0.08465	0.0
130	12.190	13.29	79.08	455.8	0.10660	0.09509	0.028550	0.028820	0.1880	0.06471	0.2005	0.8163	1.9730	15.240	0.006773	0.024560	0.010180	0.008094	0.026620	0.004143	13.340	17.81	91.38	545.2	0.14270	0.25850	0.099150	0.081870	0.3469	0.09241	1.0
131	15.460	19.48	101.70	748.9	0.10920	0.12230	0.146600	0.080870	0.1931	0.05796	0.4743	0.7859	3.0940	48.310	0.006240	0.014840	0.028130	0.010930	0.013970	0.002461	19.260	26.00	124.90	1156.0	0.15460	0.23940	0.379100	0.151400	0.2837	0.08019	0.0
132	16.160	21.54	106.20	809.8	0.10080	0.12840	0.104300	0.056130	0.2160	0.05891	0.4332	1.2650	2.8440	43.680	0.004877	0.019520	0.022190	0.009231	0.015350	0.002373	19.470	31.68	129.70	1175.0	0.13950	0.30550	0.299200	0.131200	0.3480	0.07619	0.0
133	15.710	13.93	102.00	761.7	0.09462	0.09462	0.071350	0.059330	0.1816	0.05723	0.3117	0.8155	1.9720	27.940	0.005217	0.015150	0.016780	0.012680	0.016690	0.002330	17.500	19.25	114.30	922.8	0.12230	0.19490	0.170900	0.137400	0.2723	0.07071	1.0
134	18.450	21.91	120.20	1075.0	0.09430	0.09709	0.115300	0.068470	0.1692	0.05727	0.5959	1.2020	3.7660	68.350	0.006001	0.014220	0.028550	0.009148	0.014920	0.002205	22.520	31.39	145.60	1590.0	0.14650	0.22750	0.396500	0.137900	0.3109	0.07610	0.0
135	12.770	22.47	81.72	506.3	0.09055	0.05761	0.047110	0.027040	0.1585	0.06065	0.2367	1.3800	1.4570	19.870	0.007499	0.012020	0.023320	0.008920	0.016470	0.002629	14.490	33.37	92.04	653.6	0.14190	0.15230	0.217700	0.093310	0.2829	0.08067	0.0
136	11.710	16.67	74.72	423.6	0.10510	0.06095	0.035920	0.026000	0.1339	0.05945	0.4489	2.5080	3.2580	34.370	0.006578	0.013800	0.026620	0.013070	0.013590	0.003707	13.330	25.48	86.16	546.7	0.12710	0.10280	0.104600	0.069680	0.1712	0.07343	1.0
137	11.430	15.39	73.06	399.8	0.09639	0.06889	0.035030	0.028750	0.1734	0.05865	0.1759	0.9938	1.1430	12.670	0.005133	0.015210	0.014340	0.008602	0.015010	0.001588	12.320	22.02	79.93	462.0	0.11900	0.16480	0.139900	0.084760	0.2676	0.06765	1.0
138	14.950	17.57	96.85	678.1	0.11670	0.13050	0.153900	0.086240	0.1957	0.06216	1.2960	1.4520	8.4190	101.900	0.010000	0.034800	0.065770	0.028010	0.051680	0.002887	18.550	21.43	121.40	971.4	0.14110	0.21640	0.335500	0.166700	0.3414	0.07147	0.0
139	11.280	13.39	73.00	384.8	0.11640	0.11360	0.046350	0.047960	0.1771	0.06072	0.3384	1.3430	1.8510	26.330	0.011270	0.034980	0.021870	0.019650	0.015800	0.003442	11.920	15.77	76.53	434.0	0.13670	0.18220	0.086690	0.086110	0.2102	0.06784	1.0
140	9.738	11.97	61.24	288.5	0.09250	0.04102	0.000000	0.000000	0.1903	0.06422	0.1988	0.4960	1.2180	12.260	0.006040	0.005656	0.000000	0.000000	0.022770	0.003220	10.620	14.10	66.53	342.9	0.12340	0.07204	0.000000	0.000000	0.3105	0.08151	1.0
141	16.110	18.05	105.10	813.0	0.09721	0.11370	0.094470	0.059430	0.1861	0.06248	0.7049	1.3320	4.5330	74.080	0.006770	0.019380	0.030670	0.011670	0.018750	0.003434	19.920	25.27	129.00	1233.0	0.13140	0.22360	0.280200	0.121600	0.2792	0.08158	0.0
142	11.430	17.31	73.66	398.0	0.10920	0.09486	0.020310	0.018610	0.1645	0.06562	0.2843	1.9080	1.9370	21.380	0.006664	0.017350	0.011580	0.009520	0.022820	0.003526	12.780	26.76	82.66	503.0	0.14130	0.17920	0.077080	0.064020	0.2584	0.08096	1.0
143	12.900	15.92	83.74	512.2	0.08677	0.09509	0.048940	0.030880	0.1778	0.06235	0.2143	0.7712	1.6890	16.640	0.005324	0.015630	0.015100	0.007584	0.021040	0.001887	14.480	21.82	97.17	643.8	0.13120	0.25480	0.209000	0.101200	0.3549	0.08118	1.0
144	10.750	14.97	68.26	355.3	0.07793	0.05139	0.022510	0.007875	0.1399	0.05688	0.2525	1.2390	1.8060	17.740	0.006547	0.017810	0.020180	0.005612	0.016710	0.002360	11.950	20.72	77.79	441.2	0.10760	0.12230	0.097550	0.034130	0.2300	0.06769	1.0
145	11.900	14.65	78.11	432.8	0.11520	0.12960	0.037100	0.030030	0.1995	0.07839	0.3962	0.6538	3.0210	25.030	0.010170	0.047410	0.027890	0.011100	0.031270	0.009423	13.150	16.51	86.26	509.6	0.14240	0.25170	0.094200	0.060420	0.2727	0.10360	1.0
146	11.800	16.58	78.99	432.0	0.10910	0.17000	0.165900	0.074150	0.2678	0.07371	0.3197	1.4260	2.2810	24.720	0.005427	0.036330	0.046490	0.018430	0.056280	0.004635	13.740	26.38	91.93	591.7	0.13850	0.40920	0.450400	0.186500	0.5774	0.10300	0.0
147	14.950	18.77	97.84	689.5	0.08138	0.11670	0.090500	0.035620	0.1744	0.06493	0.4220	1.9090	3.2710	39.430	0.005790	0.048770	0.053030	0.015270	0.033560	0.009368	16.250	25.47	107.10	809.7	0.09970	0.25210	0.250000	0.084050	0.2852	0.09218	1.0
148	14.440	15.18	93.97	640.1	0.09970	0.10210	0.084870	0.055320	0.1724	0.06081	0.2406	0.7394	2.1200	21.200	0.005706	0.022970	0.031140	0.014930	0.014540	0.002528	15.850	19.85	108.60	766.9	0.13160	0.27350	0.310300	0.159900	0.2691	0.07683	1.0
149	13.740	17.91	88.12	585.0	0.07944	0.06376	0.028810	0.013290	0.1473	0.05580	0.2500	0.7574	1.5730	21.470	0.002838	0.015920	0.017800	0.005828	0.013290	0.001976	15.340	22.46	97.19	725.9	0.09711	0.18240	0.156400	0.060190	0.2350	0.07014	1.0
150	13.000	20.78	83.51	519.4	0.11350	0.07589	0.031360	0.026450	0.2540	0.06087	0.4202	1.3220	2.8730	34.780	0.007017	0.011420	0.019490	0.011530	0.029510	0.001533	14.160	24.11	90.82	616.7	0.12970	0.11050	0.081120	0.062960	0.3196	0.06435	1.0
151	8.219	20.70	53.27	203.9	0.09405	0.13050	0.132100	0.021680	0.2222	0.08261	0.1935	1.9620	1.2430	10.210	0.012430	0.054160	0.077530	0.010220	0.023090	0.011780	9.092	29.72	58.08	249.8	0.16300	0.43100	0.538100	0.078790	0.3322	0.14860	1.0
152	9.731	15.34	63.78	300.2	0.10720	0.15990	0.410800	0.078570	0.2548	0.09296	0.8245	2.6640	4.0730	49.850	0.010970	0.095860	0.396000	0.052790	0.035460	0.029840	11.020	19.49	71.04	380.5	0.12920	0.27720	0.821600	0.157100	0.3108	0.12590	1.0
153	11.150	13.08	70.87	381.9	0.09754	0.05113	0.019820	0.017860	0.1830	0.06105	0.2251	0.7815	1.4290	15.480	0.009019	0.008985	0.011960	0.008232	0.023880	0.001619	11.990	16.30	76.25	440.8	0.13410	0.08971	0.071160	0.055060	0.2859	0.06772	1.0
154	13.150	15.34	85.31	538.9	0.09384	0.08498	0.092930	0.034830	0.1822	0.06207	0.2710	0.7927	1.8190	22.790	0.008584	0.020170	0.030470	0.009536	0.027690	0.003479	14.770	20.50	97.67	677.3	0.14780	0.22560	0.300900	0.097220	0.3849	0.08633	1.0
155	12.250	17.94	78.27	460.3	0.08654	0.06679	0.038850	0.023310	0.1970	0.06228	0.2200	0.9823	1.4840	16.510	0.005518	0.015620	0.019940	0.007924	0.017990	0.002484	13.590	25.22	86.60	564.2	0.12170	0.17880	0.194300	0.082110	0.3113	0.08132	1.0
156	17.680	20.74	117.40	963.7	0.11150	0.16650	0.185500	0.105400	0.1971	0.06166	0.8113	1.4000	5.5400	93.910	0.009037	0.049540	0.052060	0.018410	0.017780	0.004968	20.470	25.11	132.90	1302.0	0.14180	0.34980	0.358300	0.151500	0.2463	0.07738	0.0
157	16.840	19.46	108.40	880.2	0.07445	0.07223	0.051500	0.027710	0.1844	0.05268	0.4789	2.0600	3.4790	46.610	0.003443	0.026610	0.030560	0.011100	0.015200	0.001519	18.220	28.07	120.30	1032.0	0.08774	0.17100	0.188200	0.084360	0.2527	0.05972	1.0
158	12.060	12.74	76.84	448.6	0.09311	0.05241	0.019720	0.019630	0.1590	0.05907	0.1822	0.7285	1.1710	13.250	0.005528	0.009789	0.008342	0.006273	0.014650	0.002530	13.140	18.41	84.08	532.8	0.12750	0.12320	0.086360	0.070250	0.2514	0.07898	1.0
159	10.900	12.96	68.69	366.8	0.07515	0.03718	0.003090	0.006588	0.1442	0.05743	0.2818	0.7614	1.8080	18.540	0.006142	0.006134	0.001835	0.003576	0.016370	0.002665	12.360	18.20	78.07	470.0	0.11710	0.08294	0.018540	0.039530	0.2738	0.07685	1.0
160	11.750	20.18	76.10	419.8	0.10890	0.11410	0.068430	0.037380	0.1993	0.06453	0.5018	1.6930	3.9260	38.340	0.009433	0.024050	0.041670	0.011520	0.033970	0.005061	13.320	26.21	88.91	543.9	0.13580	0.18920	0.195600	0.079090	0.3168	0.07987	1.0
161	19.190	15.94	126.30	1157.0	0.08694	0.11850	0.119300	0.096670	0.1741	0.05176	1.0000	0.6336	6.9710	119.300	0.009406	0.030550	0.043440	0.027940	0.031560	0.003362	22.030	17.81	146.60	1495.0	0.11240	0.20160	0.226400	0.177700	0.2443	0.06251	0.0
162	19.590	18.15	130.70	1214.0	0.11200	0.16660	0.250800	0.128600	0.2027	0.06082	0.7364	1.0480	4.7920	97.070	0.004057	0.022770	0.040290	0.013030	0.016860	0.003318	26.730	26.39	174.90	2232.0	0.14380	0.38460	0.681000	0.224700	0.3643	0.09223	0.0
163	12.340	22.22	79.85	464.5	0.10120	0.10150	0.053700	0.028220	0.1551	0.06761	0.2949	1.6560	1.9550	21.550	0.011340	0.031750	0.031250	0.011350	0.018790	0.005348	13.580	28.68	87.36	553.0	0.14520	0.23380	0.168800	0.081940	0.2268	0.09082	1.0
164	23.270	22.04	152.10	1686.0	0.08439	0.11450	0.132400	0.097020	0.1801	0.05553	0.6642	0.8561	4.6030	97.850	0.004910	0.025440	0.028220	0.016230	0.019560	0.003740	28.010	28.22	184.20	2403.0	0.12280	0.35830	0.394800	0.234600	0.3589	0.09187	0.0
165	14.970	19.76	95.50	690.2	0.08421	0.05352	0.019470	0.019390	0.1515	0.05266	0.1840	1.0650	1.2860	16.640	0.003634	0.007983	0.008268	0.006432	0.019240	0.001520	15.980	25.82	102.30	782.1	0.10450	0.09995	0.077500	0.057540	0.2646	0.06085	1.0
166	10.800	9.71	68.77	357.6	0.09594	0.05736	0.025310	0.016980	0.1381	0.06400	0.1728	0.4064	1.1260	11.480	0.007809	0.009816	0.010990	0.005344	0.012540	0.002120	11.600	12.02	73.66	414.0	0.14360	0.12570	0.104700	0.046030	0.2090	0.07699	1.0
167	16.780	18.80	109.30	886.3	0.08865	0.09182	0.084220	0.065760	0.1893	0.05534	0.5990	1.3910	4.1290	67.340	0.006123	0.024700	0.026260	0.016040	0.020910	0.003493	20.050	26.30	130.70	1260.0	0.11680	0.21190	0.231800	0.147400	0.2810	0.07228	0.0
168	17.470	24.68	116.10	984.6	0.10490	0.16030	0.215900	0.104300	0.1538	0.06365	1.0880	1.4100	7.3370	122.300	0.006174	0.036340	0.046440	0.015690	0.011450	0.005120	23.140	32.33	155.30	1660.0	0.13760	0.38300	0.489000	0.172100	0.2160	0.09300	0.0
169	14.970	16.95	96.22	685.9	0.09855	0.07885	0.026020	0.037810	0.1780	0.05650	0.2713	1.2170	1.8930	24.280	0.005080	0.013700	0.007276	0.009073	0.013500	0.001706	16.110	23.00	104.60	793.7	0.12160	0.16370	0.066480	0.084850	0.2404	0.06428	1.0
170	12.320	12.39	78.85	464.1	0.10280	0.06981	0.039870	0.037000	0.1959	0.05955	0.2360	0.6656	1.6700	17.430	0.008045	0.011800	0.016830	0.012410	0.019240	0.002248	13.500	15.64	86.97	549.1	0.13850	0.12660	0.124200	0.093910	0.2827	0.06771	1.0
171	13.430	19.63	85.84	565.4	0.09048	0.06288	0.058580	0.034380	0.1598	0.05671	0.4697	1.1470	3.1420	43.400	0.006003	0.010630	0.021510	0.009443	0.015200	0.001868	17.980	29.87	116.60	993.6	0.14010	0.15460	0.264400	0.116000	0.2884	0.07371	0.0
172	15.460	11.89	102.50	736.9	0.12570	0.15550	0.203200	0.109700	0.1966	0.07069	0.4209	0.6583	2.8050	44.640	0.005393	0.023210	0.043030	0.013200	0.017920	0.004168	18.790	17.04	125.00	1102.0	0.15310	0.35830	0.583000	0.182700	0.3216	0.10100	0.0
173	11.080	14.71	70.21	372.7	0.10060	0.05743	0.023630	0.025830	0.1566	0.06669	0.2073	1.8050	1.3770	19.080	0.014960	0.021210	0.014530	0.015830	0.030820	0.004785	11.350	16.82	72.01	396.5	0.12160	0.08240	0.039380	0.043060	0.1902	0.07313	1.0
174	10.660	15.15	67.49	349.6	0.08792	0.04302	0.000000	0.000000	0.1928	0.05975	0.3309	1.9250	2.1550	21.980	0.008713	0.010170	0.000000	0.000000	0.032650	0.001002	11.540	19.20	73.20	408.3	0.10760	0.06791	0.000000	0.000000	0.2710	0.06164	1.0
175	8.671	14.45	54.42	227.2	0.09138	0.04276	0.000000	0.000000	0.1722	0.06724	0.2204	0.7873	1.4350	11.360	0.009172	0.008007	0.000000	0.000000	0.027110	0.003399	9.262	17.04	58.36	259.2	0.11620	0.07057	0.000000	0.000000	0.2592	0.07848	1.0
176	9.904	18.06	64.60	302.4	0.09699	0.12940	0.130700	0.037160	0.1669	0.08116	0.4311	2.2610	3.1320	27.480	0.012860	0.088080	0.119700	0.024600	0.038800	0.017920	11.260	24.39	73.07	390.2	0.13010	0.29500	0.348600	0.099100	0.2614	0.11620	1.0
177	16.460	20.11	109.30	832.9	0.09831	0.15560	0.179300	0.088660	0.1794	0.06323	0.3037	1.2840	2.4820	31.590	0.006627	0.040940	0.053710	0.018130	0.016820	0.004584	17.790	28.45	123.50	981.2	0.14150	0.46670	0.586200	0.203500	0.3054	0.09519	0.0
178	13.010	22.22	82.01	526.4	0.06251	0.01938	0.001595	0.001852	0.1395	0.05234	0.1731	1.1420	1.1010	14.340	0.003418	0.002252	0.001595	0.001852	0.016130	0.000968	14.000	29.02	88.18	608.8	0.08125	0.03432	0.007977	0.009259	0.2295	0.05843	1.0
179	12.810	13.06	81.29	508.8	0.08739	0.03774	0.009193	0.013300	0.1466	0.06133	0.2889	0.9899	1.7780	21.790	0.008534	0.006364	0.006180	0.007408	0.010650	0.003351	13.630	16.15	86.70	570.7	0.11620	0.05445	0.027580	0.039900	0.1783	0.07319	1.0
180	27.220	21.87	182.10	2250.0	0.10940	0.19140	0.287100	0.187800	0.1800	0.05770	0.8361	1.4810	5.8200	128.700	0.004631	0.025370	0.031090	0.012410	0.015750	0.002747	33.120	32.85	220.80	3216.0	0.14720	0.40340	0.534000	0.268800	0.2856	0.08082	0.0
181	21.090	26.57	142.70	1311.0	0.11410	0.28320	0.248700	0.149600	0.2395	0.07398	0.6298	0.7629	4.4140	81.460	0.004253	0.047590	0.038720	0.015670	0.017980	0.005295	26.680	33.48	176.50	2089.0	0.14910	0.75840	0.678000	0.290300	0.4098	0.12840	0.0
182	15.700	20.31	101.20	766.6	0.09597	0.08799	0.065930	0.051890	0.1618	0.05549	0.3699	1.1500	2.4060	40.980	0.004626	0.022630	0.019540	0.009767	0.015470	0.002430	20.110	32.82	129.30	1269.0	0.14140	0.35470	0.290200	0.154100	0.3437	0.08631	0.0
183	11.410	14.92	73.53	402.0	0.09059	0.08155	0.061810	0.023610	0.1167	0.06217	0.3344	1.1080	1.9020	22.770	0.007356	0.037280	0.059150	0.017120	0.021650	0.004784	12.370	17.70	79.12	467.2	0.11210	0.16100	0.164800	0.062960	0.1811	0.07427	1.0
184	15.280	22.41	98.92	710.6	0.09057	0.10520	0.053750	0.032630	0.1727	0.06317	0.2054	0.4956	1.3440	19.530	0.003290	0.013950	0.017740	0.006009	0.011720	0.002575	17.800	28.03	113.80	973.1	0.13010	0.32990	0.363000	0.122600	0.3175	0.09772	0.0
185	10.080	15.11	63.76	317.5	0.09267	0.04695	0.001597	0.002404	0.1703	0.06048	0.4245	1.2680	2.6800	26.430	0.014390	0.012000	0.001597	0.002404	0.025380	0.003470	11.870	21.18	75.39	437.0	0.15210	0.10190	0.006920	0.010420	0.2933	0.07697	1.0
186	18.310	18.58	118.60	1041.0	0.08588	0.08468	0.081690	0.058140	0.1621	0.05425	0.2577	0.4757	1.8170	28.920	0.002866	0.009181	0.014120	0.006719	0.010690	0.001087	21.310	26.36	139.20	1410.0	0.12340	0.24450	0.353800	0.157100	0.3206	0.06938	0.0
187	11.710	17.19	74.68	420.3	0.09774	0.06141	0.038090	0.032390	0.1516	0.06095	0.2451	0.7655	1.7420	17.860	0.006905	0.008704	0.019780	0.011850	0.018970	0.001671	13.010	21.39	84.42	521.5	0.13230	0.10400	0.152100	0.109900	0.2572	0.07097	1.0
188	11.810	17.39	75.27	428.9	0.10070	0.05562	0.023530	0.015530	0.1718	0.05780	0.1859	1.9260	1.0110	14.470	0.007831	0.008776	0.015560	0.006240	0.031390	0.001988	12.570	26.48	79.57	489.5	0.13560	0.10000	0.088030	0.043060	0.3200	0.06576	1.0
189	12.300	15.90	78.83	463.7	0.08080	0.07253	0.038440	0.016540	0.1667	0.05474	0.2382	0.8355	1.6870	18.320	0.005996	0.022120	0.021170	0.006433	0.020250	0.001725	13.350	19.59	86.65	546.7	0.10960	0.16500	0.142300	0.048150	0.2482	0.06306	1.0
190	14.220	23.12	94.37	609.9	0.10750	0.24130	0.198100	0.066180	0.2384	0.07542	0.2860	2.1100	2.1120	31.720	0.007970	0.135400	0.116600	0.016660	0.051130	0.011720	15.740	37.18	106.40	762.4	0.15330	0.93270	0.848800	0.177200	0.5166	0.14460	0.0
191	12.770	21.41	82.02	507.4	0.08749	0.06601	0.031120	0.028640	0.1694	0.06287	0.7311	1.7480	5.1180	53.650	0.004571	0.017900	0.021760	0.017570	0.033730	0.005875	13.750	23.50	89.04	579.5	0.09388	0.08978	0.051860	0.047730	0.2179	0.06871	1.0
192	9.720	18.22	60.73	288.1	0.06950	0.02344	0.000000	0.000000	0.1653	0.06447	0.3539	4.8850	2.2300	21.690	0.001713	0.006736	0.000000	0.000000	0.037990	0.001688	9.968	20.83	62.25	303.8	0.07117	0.02729	0.000000	0.000000	0.1909	0.06559	1.0
193	12.340	26.86	81.15	477.4	0.10340	0.13530	0.108500	0.045620	0.1943	0.06937	0.4053	1.8090	2.6420	34.440	0.009098	0.038450	0.037630	0.013210	0.018780	0.005672	15.650	39.34	101.70	768.9	0.17850	0.47060	0.442500	0.145900	0.3215	0.12050	0.0
194	14.860	23.21	100.40	671.4	0.10440	0.19800	0.169700	0.088780	0.1737	0.06672	0.2796	0.9622	3.5910	25.200	0.008081	0.051220	0.055510	0.018830	0.025450	0.004312	16.080	27.78	118.60	784.7	0.13160	0.46480	0.458900	0.172700	0.3000	0.08701	0.0
195	12.910	16.33	82.53	516.4	0.07941	0.05366	0.038730	0.023770	0.1829	0.05667	0.1942	0.9086	1.4930	15.750	0.005298	0.015870	0.023210	0.008420	0.018530	0.002152	13.880	22.00	90.81	600.6	0.10970	0.15060	0.176400	0.082350	0.3024	0.06949	1.0
196	13.770	22.29	90.63	588.9	0.12000	0.12670	0.138500	0.065260	0.1834	0.06877	0.6191	2.1120	4.9060	49.700	0.013800	0.033480	0.046650	0.020600	0.026890	0.004306	16.390	34.01	111.60	806.9	0.17370	0.31220	0.380900	0.167300	0.3080	0.09333	0.0
197	18.080	21.84	117.40	1024.0	0.07371	0.08642	0.110300	0.057780	0.1770	0.05340	0.6362	1.3050	4.3120	76.360	0.005530	0.052960	0.061100	0.014440	0.021400	0.005036	19.760	24.70	129.10	1228.0	0.08822	0.19630	0.253500	0.091810	0.2369	0.06558	0.0
198	19.180	22.49	127.50	1148.0	0.08523	0.14280	0.111400	0.067720	0.1767	0.05529	0.4357	1.0730	3.8330	54.220	0.005524	0.036980	0.027060	0.012210	0.014150	0.003397	23.360	32.06	166.40	1688.0	0.13220	0.56010	0.386500	0.170800	0.3193	0.09221	0.0
199	14.450	20.22	94.49	642.7	0.09872	0.12060	0.118000	0.059800	0.1950	0.06466	0.2092	0.6509	1.4460	19.420	0.004044	0.015970	0.020000	0.007303	0.015220	0.001976	18.330	30.12	117.90	1044.0	0.15520	0.40560	0.496700	0.183800	0.4753	0.10130	0.0
200	12.230	19.56	78.54	461.0	0.09586	0.08087	0.041870	0.041070	0.1979	0.06013	0.3534	1.3260	2.3080	27.240	0.007514	0.017790	0.014010	0.011400	0.015030	0.003338	14.440	28.36	92.15	638.4	0.14290	0.20420	0.137700	0.108000	0.2668	0.08174	1.0
201	17.540	19.32	115.10	951.6	0.08968	0.11980	0.103600	0.074880	0.1506	0.05491	0.3971	0.8282	3.0880	40.730	0.006090	0.025690	0.027130	0.013450	0.015940	0.002658	20.420	25.84	139.50	1239.0	0.13810	0.34200	0.350800	0.193900	0.2928	0.07867	0.0
202	23.290	26.67	158.90	1685.0	0.11410	0.20840	0.352300	0.162000	0.2200	0.06229	0.5539	1.5600	4.6670	83.160	0.009327	0.051210	0.089580	0.024650	0.021750	0.005195	25.120	32.68	177.00	1986.0	0.15360	0.41670	0.789200	0.273300	0.3198	0.08762	0.0
203	13.810	23.75	91.56	597.8	0.13230	0.17680	0.155800	0.091760	0.2251	0.07421	0.5648	1.9300	3.9090	52.720	0.008824	0.031080	0.031120	0.012910	0.019980	0.004506	19.200	41.85	128.50	1153.0	0.22260	0.52090	0.464600	0.201300	0.4432	0.10860	0.0
204	12.470	18.60	81.09	481.9	0.09965	0.10580	0.080050	0.038210	0.1925	0.06373	0.3961	1.0440	2.4970	30.290	0.006953	0.019110	0.027010	0.010370	0.017820	0.003586	14.970	24.64	96.05	677.9	0.14260	0.23780	0.267100	0.101500	0.3014	0.08750	1.0
205	15.120	16.68	98.78	716.6	0.08876	0.09588	0.075500	0.040790	0.1594	0.05986	0.2711	0.3621	1.9740	26.440	0.005472	0.019190	0.020390	0.008260	0.015230	0.002881	17.770	20.24	117.70	989.5	0.14910	0.33310	0.332700	0.125200	0.3415	0.09740	0.0
206	9.876	17.27	62.92	295.4	0.10890	0.07232	0.017560	0.019520	0.1934	0.06285	0.2137	1.3420	1.5170	12.330	0.009719	0.012490	0.007975	0.007527	0.022100	0.002472	10.420	23.22	67.08	331.6	0.14150	0.12470	0.062130	0.055880	0.2989	0.07380	1.0
207	17.010	20.26	109.70	904.3	0.08772	0.07304	0.069500	0.053900	0.2026	0.05223	0.5858	0.8554	4.1060	68.460	0.005038	0.015030	0.019460	0.011230	0.022940	0.002581	19.800	25.05	130.00	1210.0	0.11110	0.14860	0.193200	0.109600	0.3275	0.06469	0.0
208	13.110	22.54	87.02	529.4	0.10020	0.14830	0.087050	0.051020	0.1850	0.07310	0.1931	0.9223	1.4910	15.090	0.005251	0.030410	0.025260	0.008304	0.025140	0.004198	14.550	29.16	99.48	639.3	0.13490	0.44020	0.316200	0.112600	0.4128	0.10760	1.0
209	15.270	12.91	98.17	725.5	0.08182	0.06230	0.058920	0.031570	0.1359	0.05526	0.2134	0.3628	1.5250	20.000	0.004291	0.012360	0.018410	0.007373	0.009539	0.001656	17.380	15.92	113.70	932.7	0.12220	0.21860	0.296200	0.103500	0.2320	0.07474	1.0
210	20.580	22.14	134.70	1290.0	0.09090	0.13480	0.164000	0.095610	0.1765	0.05024	0.8601	1.4800	7.0290	111.700	0.008124	0.036110	0.054890	0.027650	0.031760	0.002365	23.240	27.84	158.30	1656.0	0.11780	0.29200	0.386100	0.192000	0.2909	0.05865	0.0
211	11.840	18.94	75.51	428.0	0.08871	0.06900	0.026690	0.013930	0.1533	0.06057	0.2222	0.8652	1.4440	17.120	0.005517	0.017270	0.020450	0.006747	0.016160	0.002922	13.300	24.99	85.22	546.3	0.12800	0.18800	0.147100	0.069130	0.2535	0.07993	1.0
212	28.110	18.47	188.50	2499.0	0.11420	0.15160	0.320100	0.159500	0.1648	0.05525	2.8730	1.4760	21.9800	525.600	0.013450	0.027720	0.063890	0.014070	0.047830	0.004476	28.110	18.47	188.50	2499.0	0.11420	0.15160	0.320100	0.159500	0.1648	0.05525	0.0
213	17.420	25.56	114.50	948.0	0.10060	0.11460	0.168200	0.065970	0.1308	0.05866	0.5296	1.6670	3.7670	58.530	0.031130	0.085550	0.143800	0.039270	0.021750	0.012560	18.070	28.07	120.40	1021.0	0.12430	0.17930	0.280300	0.109900	0.1603	0.06818	0.0
214	14.190	23.81	92.87	610.7	0.09463	0.13060	0.111500	0.064620	0.2235	0.06433	0.4207	1.8450	3.5340	31.000	0.010880	0.037100	0.036880	0.016270	0.044990	0.004768	16.860	34.85	115.00	811.3	0.15590	0.40590	0.374400	0.177200	0.4724	0.10260	0.0
215	13.860	16.93	90.96	578.9	0.10260	0.15170	0.099010	0.056020	0.2106	0.06916	0.2563	1.1940	1.9330	22.690	0.005960	0.034380	0.039090	0.014350	0.019390	0.004560	15.750	26.93	104.40	750.1	0.14600	0.43700	0.463600	0.165400	0.3630	0.10590	0.0
216	11.890	18.35	77.32	432.2	0.09363	0.11540	0.066360	0.031420	0.1967	0.06314	0.2963	1.5630	2.0870	21.460	0.008872	0.041920	0.059460	0.017850	0.027930	0.004775	13.250	27.10	86.20	531.2	0.14050	0.30460	0.280600	0.113800	0.3397	0.08365	1.0
217	10.200	17.48	65.05	321.2	0.08054	0.05907	0.057740	0.010710	0.1964	0.06315	0.3567	1.9220	2.7470	22.790	0.004680	0.031200	0.057740	0.010710	0.025600	0.004613	11.480	24.47	75.40	403.7	0.09527	0.13970	0.192500	0.035710	0.2868	0.07809	1.0
218	19.800	21.56	129.70	1230.0	0.09383	0.13060	0.127200	0.086910	0.2094	0.05581	0.9553	1.1860	6.4870	124.400	0.006804	0.031690	0.034460	0.017120	0.018970	0.004045	25.730	28.64	170.30	2009.0	0.13530	0.32350	0.361700	0.182000	0.3070	0.08255	0.0
219	19.530	32.47	128.00	1223.0	0.08420	0.11300	0.114500	0.066370	0.1428	0.05313	0.7392	1.3210	4.7220	109.900	0.005539	0.026440	0.026640	0.010780	0.013320	0.002256	27.900	45.41	180.20	2477.0	0.14080	0.40970	0.399500	0.162500	0.2713	0.07568	0.0
220	13.650	13.16	87.88	568.9	0.09646	0.08711	0.038880	0.025630	0.1360	0.06344	0.2102	0.4336	1.3910	17.400	0.004133	0.016950	0.016520	0.006659	0.013710	0.002735	15.340	16.35	99.71	706.2	0.13110	0.24740	0.175900	0.080560	0.2380	0.08718	1.0
221	13.560	13.90	88.59	561.3	0.10510	0.11920	0.078600	0.044510	0.1962	0.06303	0.2569	0.4981	2.0110	21.030	0.005851	0.023140	0.025440	0.008360	0.018420	0.002918	14.980	17.13	101.10	686.6	0.13760	0.26980	0.257700	0.090900	0.3065	0.08177	1.0
222	10.180	17.53	65.12	313.1	0.10610	0.08502	0.017680	0.019150	0.1910	0.06908	0.2467	1.2170	1.6410	15.050	0.007899	0.014000	0.008534	0.007624	0.026370	0.003761	11.170	22.84	71.94	375.6	0.14060	0.14400	0.065720	0.055750	0.3055	0.08797	1.0
223	15.750	20.25	102.60	761.3	0.10250	0.12040	0.114700	0.064620	0.1935	0.06303	0.3473	0.9209	2.2440	32.190	0.004766	0.023740	0.023840	0.008637	0.017720	0.003131	19.560	30.29	125.90	1088.0	0.15520	0.44800	0.397600	0.147900	0.3993	0.10640	0.0
224	13.270	17.02	84.55	546.4	0.08445	0.04994	0.035540	0.024560	0.1496	0.05674	0.2927	0.8907	2.0440	24.680	0.006032	0.011040	0.022590	0.009057	0.014820	0.002496	15.140	23.60	98.84	708.8	0.12760	0.13110	0.178600	0.096780	0.2506	0.07623	1.0
225	14.340	13.47	92.51	641.2	0.09906	0.07624	0.057240	0.046030	0.2075	0.05448	0.5220	0.8121	3.7630	48.290	0.007089	0.014280	0.023600	0.012860	0.022660	0.001463	16.770	16.90	110.40	873.2	0.12970	0.15250	0.163200	0.108700	0.3062	0.06072	1.0
226	10.440	15.46	66.62	329.6	0.10530	0.07722	0.006643	0.012160	0.1788	0.06450	0.1913	0.9027	1.2080	11.860	0.006513	0.008061	0.002817	0.004972	0.015020	0.002821	11.520	19.80	73.47	395.4	0.13410	0.11530	0.026390	0.044640	0.2615	0.08269	1.0
227	15.000	15.51	97.45	684.5	0.08371	0.10960	0.065050	0.037800	0.1881	0.05907	0.2318	0.4966	2.2760	19.880	0.004119	0.032070	0.036440	0.011550	0.013910	0.003204	16.410	19.31	114.20	808.2	0.11360	0.36270	0.340200	0.137900	0.2954	0.08362	1.0
228	12.620	23.97	81.35	496.4	0.07903	0.07529	0.054380	0.020360	0.1514	0.06019	0.2449	1.0660	1.4450	18.510	0.005169	0.022940	0.030160	0.008691	0.013650	0.003407	14.200	31.31	90.67	624.0	0.12270	0.34540	0.391100	0.118000	0.2826	0.09585	1.0
229	12.830	22.33	85.26	503.2	0.10880	0.17990	0.169500	0.068610	0.2123	0.07254	0.3061	1.0690	2.2570	25.130	0.006983	0.038580	0.046830	0.014990	0.016800	0.005617	15.200	30.15	105.30	706.0	0.17770	0.53430	0.628200	0.197700	0.3407	0.12430	0.0
230	17.050	19.08	113.40	895.0	0.11410	0.15720	0.191000	0.109000	0.2131	0.06325	0.2959	0.6790	2.1530	31.980	0.005532	0.020080	0.030550	0.013840	0.011770	0.002336	19.590	24.89	133.50	1189.0	0.17030	0.39340	0.501800	0.254300	0.3109	0.09061	0.0
231	11.320	27.08	71.76	395.7	0.06883	0.03813	0.016330	0.003125	0.1869	0.05628	0.1210	0.8927	1.0590	8.605	0.003653	0.016470	0.016330	0.003125	0.015370	0.002052	12.080	33.75	79.82	452.3	0.09203	0.14320	0.108900	0.020830	0.2849	0.07087	1.0
232	11.220	33.81	70.79	386.8	0.07780	0.03574	0.004967	0.006434	0.1845	0.05828	0.2239	1.6470	1.4890	15.460	0.004359	0.006813	0.003223	0.003419	0.019160	0.002534	12.360	41.78	78.44	470.9	0.09994	0.06885	0.023180	0.030020	0.2911	0.07307	1.0
233	20.510	27.81	134.40	1319.0	0.09159	0.10740	0.155400	0.083400	0.1448	0.05592	0.5240	1.1890	3.7670	70.010	0.005020	0.020620	0.034570	0.010910	0.012980	0.002887	24.470	37.38	162.70	1872.0	0.12230	0.27610	0.414600	0.156300	0.2437	0.08328	0.0
234	9.567	15.91	60.21	279.6	0.08464	0.04087	0.016520	0.016670	0.1551	0.06403	0.2152	0.8301	1.2150	12.640	0.011640	0.010400	0.011860	0.009623	0.023830	0.003540	10.510	19.16	65.74	335.9	0.15040	0.09515	0.071610	0.072220	0.2757	0.08178	1.0
235	14.030	21.25	89.79	603.4	0.09070	0.06945	0.014620	0.018960	0.1517	0.05835	0.2589	1.5030	1.6670	22.070	0.007389	0.013830	0.007302	0.010040	0.012630	0.002925	15.330	30.28	98.27	715.5	0.12870	0.15130	0.062310	0.079630	0.2226	0.07617	1.0
236	23.210	26.97	153.50	1670.0	0.09509	0.16820	0.195000	0.123700	0.1909	0.06309	1.0580	0.9635	7.2470	155.800	0.006428	0.028630	0.044970	0.017160	0.015900	0.003053	31.010	34.51	206.00	2944.0	0.14810	0.41260	0.582000	0.259300	0.3103	0.08677	0.0
237	20.480	21.46	132.50	1306.0	0.08355	0.08348	0.090420	0.060220	0.1467	0.05177	0.6874	1.0410	5.1440	83.500	0.007959	0.031330	0.042570	0.016710	0.013410	0.003933	24.220	26.17	161.70	1750.0	0.12280	0.23110	0.315800	0.144500	0.2238	0.07127	0.0
238	14.220	27.85	92.55	623.9	0.08223	0.10390	0.110300	0.044080	0.1342	0.06129	0.3354	2.3240	2.1050	29.960	0.006307	0.028450	0.038500	0.010110	0.011850	0.003589	15.750	40.54	102.50	764.0	0.10810	0.24260	0.306400	0.082190	0.1890	0.07796	1.0
239	17.460	39.28	113.40	920.6	0.09812	0.12980	0.141700	0.088110	0.1809	0.05966	0.5366	0.8561	3.0020	49.000	0.004860	0.027850	0.026020	0.013740	0.012260	0.002759	22.510	44.87	141.20	1408.0	0.13650	0.37350	0.324100	0.206600	0.2853	0.08496	0.0
240	13.640	15.60	87.38	575.3	0.09423	0.06630	0.047050	0.037310	0.1717	0.05660	0.3242	0.6612	1.9960	27.190	0.006470	0.012480	0.018100	0.011030	0.018980	0.001794	14.850	19.05	94.11	683.4	0.12780	0.12910	0.153300	0.092220	0.2530	0.06510	1.0
241	12.420	15.04	78.61	476.5	0.07926	0.03393	0.010530	0.011080	0.1546	0.05754	0.1153	0.6745	0.7570	9.006	0.003265	0.004930	0.006493	0.003762	0.017200	0.001360	13.200	20.37	83.85	543.4	0.10370	0.07776	0.062430	0.040520	0.2901	0.06783	1.0
242	11.300	18.19	73.93	389.4	0.09592	0.13250	0.154800	0.028540	0.2054	0.07669	0.2428	1.6420	2.3690	16.390	0.006663	0.059140	0.088800	0.013140	0.019950	0.008675	12.580	27.96	87.16	472.9	0.13470	0.48480	0.743600	0.121800	0.3308	0.12970	1.0
243	13.750	23.77	88.54	590.0	0.08043	0.06807	0.046970	0.023440	0.1773	0.05429	0.4347	1.0570	2.8290	39.930	0.004351	0.026670	0.033710	0.010070	0.025980	0.003087	15.010	26.34	98.00	706.0	0.09368	0.14420	0.135900	0.061060	0.2663	0.06321	1.0
244	19.400	23.50	129.10	1155.0	0.10270	0.15580	0.204900	0.088860	0.1978	0.06000	0.5243	1.8020	4.0370	60.410	0.010610	0.032520	0.039150	0.015590	0.021860	0.003949	21.650	30.53	144.90	1417.0	0.14630	0.29680	0.345800	0.156400	0.2920	0.07614	0.0
245	10.480	19.86	66.72	337.7	0.10700	0.05971	0.048310	0.030700	0.1737	0.06440	0.3719	2.6120	2.5170	23.220	0.016040	0.013860	0.018650	0.011330	0.034760	0.003560	11.480	29.46	73.68	402.8	0.15150	0.10260	0.118100	0.067360	0.2883	0.07748	1.0
246	13.200	17.43	84.13	541.6	0.07215	0.04524	0.043360	0.011050	0.1487	0.05635	0.1630	1.6010	0.8730	13.560	0.006261	0.015690	0.030790	0.005383	0.019620	0.002250	13.940	27.82	88.28	602.0	0.11010	0.15080	0.229800	0.049700	0.2767	0.07198	1.0
247	12.890	14.11	84.95	512.2	0.08760	0.13460	0.137400	0.039800	0.1596	0.06409	0.2025	0.4402	2.3930	16.350	0.005501	0.055920	0.081580	0.013700	0.012660	0.007555	14.390	17.70	105.00	639.1	0.12540	0.58490	0.772700	0.156100	0.2639	0.11780	1.0
248	10.650	25.22	68.01	347.0	0.09657	0.07234	0.023790	0.016150	0.1897	0.06329	0.2497	1.4930	1.4970	16.640	0.007189	0.010350	0.010810	0.006245	0.021580	0.002619	12.250	35.19	77.98	455.7	0.14990	0.13980	0.112500	0.061360	0.3409	0.08147	1.0
249	11.520	14.93	73.87	406.3	0.10130	0.07808	0.043280	0.029290	0.1883	0.06168	0.2562	1.0380	1.6860	18.620	0.006662	0.012280	0.021050	0.010060	0.016770	0.002784	12.650	21.19	80.88	491.8	0.13890	0.15820	0.180400	0.096080	0.2664	0.07809	1.0
250	20.940	23.56	138.90	1364.0	0.10070	0.16060	0.271200	0.131000	0.2205	0.05898	1.0040	0.8208	6.3720	137.900	0.005283	0.039080	0.095180	0.018640	0.024010	0.005002	25.580	27.00	165.30	2010.0	0.12110	0.31720	0.699100	0.210500	0.3126	0.07849	0.0
251	11.500	18.45	73.28	407.4	0.09345	0.05991	0.026380	0.020690	0.1834	0.05934	0.3927	0.8429	2.6840	26.990	0.006380	0.010650	0.012450	0.009175	0.022920	0.001461	12.970	22.46	83.12	508.9	0.11830	0.10490	0.081050	0.065440	0.2740	0.06487	1.0
252	19.730	19.82	130.70	1206.0	0.10620	0.18490	0.241700	0.097400	0.1733	0.06697	0.7661	0.7800	4.1150	92.810	0.008482	0.050570	0.068000	0.019710	0.014670	0.007259	25.280	25.59	159.80	1933.0	0.17100	0.59550	0.848900	0.250700	0.2749	0.12970	0.0
253	17.300	17.08	113.00	928.2	0.10080	0.10410	0.126600	0.083530	0.1813	0.05613	0.3093	0.8568	2.1930	33.630	0.004757	0.015030	0.023320	0.012620	0.013940	0.002362	19.850	25.09	130.90	1222.0	0.14160	0.24050	0.337800	0.185700	0.3138	0.08113	0.0
254	19.450	19.33	126.50	1169.0	0.10350	0.11880	0.137900	0.085910	0.1776	0.05647	0.5959	0.6342	3.7970	71.000	0.004649	0.018000	0.027490	0.012670	0.013650	0.002550	25.700	24.57	163.10	1972.0	0.14970	0.31610	0.431700	0.199900	0.3379	0.08950	0.0
255	13.960	17.05	91.43	602.4	0.10960	0.12790	0.097890	0.052460	0.1908	0.06130	0.4250	0.8098	2.5630	35.740	0.006351	0.026790	0.031190	0.013420	0.020620	0.002695	16.390	22.07	108.10	826.0	0.15120	0.32620	0.320900	0.137400	0.3068	0.07957	0.0
256	19.550	28.77	133.60	1207.0	0.09260	0.20630	0.178400	0.114400	0.1893	0.06232	0.8426	1.1990	7.1580	106.400	0.006356	0.047650	0.038630	0.015190	0.019360	0.005252	25.050	36.27	178.60	1926.0	0.12810	0.53290	0.425100	0.194100	0.2818	0.10050	0.0
257	15.320	17.27	103.20	713.3	0.13350	0.22840	0.244800	0.124200	0.2398	0.07596	0.6592	1.0590	4.0610	59.460	0.010150	0.045880	0.049830	0.021270	0.018840	0.008660	17.730	22.66	119.80	928.8	0.17650	0.45030	0.442900	0.222900	0.3258	0.11910	0.0
258	15.660	23.20	110.20	773.5	0.11090	0.31140	0.317600	0.137700	0.2495	0.08104	1.2920	2.4540	10.1200	138.500	0.012360	0.059950	0.082320	0.030240	0.023370	0.006042	19.850	31.64	143.70	1226.0	0.15040	0.51720	0.618100	0.246200	0.3277	0.10190	0.0
259	15.530	33.56	103.70	744.9	0.10630	0.16390	0.175100	0.083990	0.2091	0.06650	0.2419	1.2780	1.9030	23.020	0.005345	0.025560	0.028890	0.010220	0.009947	0.003359	18.490	49.54	126.30	1035.0	0.18830	0.55640	0.570300	0.201400	0.3512	0.12040	0.0
260	20.310	27.06	132.90	1288.0	0.10000	0.10880	0.151900	0.093330	0.1814	0.05572	0.3977	1.0330	2.5870	52.340	0.005043	0.015780	0.021170	0.008185	0.012820	0.001892	24.330	39.16	162.30	1844.0	0.15220	0.29450	0.378800	0.169700	0.3151	0.07999	0.0
261	17.350	23.06	111.00	933.1	0.08662	0.06290	0.028910	0.028370	0.1564	0.05307	0.4007	1.3170	2.5770	44.410	0.005726	0.011060	0.012460	0.007671	0.014110	0.001578	19.850	31.47	128.20	1218.0	0.12400	0.14860	0.121100	0.082350	0.2452	0.06515	0.0
262	17.290	22.13	114.40	947.8	0.08999	0.12730	0.096970	0.075070	0.2108	0.05464	0.8348	1.6330	6.1460	90.940	0.006717	0.059810	0.046380	0.021490	0.027470	0.005838	20.390	27.24	137.90	1295.0	0.11340	0.28670	0.229800	0.152800	0.3067	0.07484	0.0
263	15.610	19.38	100.00	758.6	0.07840	0.05616	0.042090	0.028470	0.1547	0.05443	0.2298	0.9988	1.5340	22.180	0.002826	0.009105	0.013110	0.005174	0.010130	0.001345	17.910	31.67	115.90	988.6	0.10840	0.18070	0.226000	0.085680	0.2683	0.06829	0.0
264	17.190	22.07	111.60	928.3	0.09726	0.08995	0.090610	0.065270	0.1867	0.05580	0.4203	0.7383	2.8190	45.420	0.004493	0.012060	0.020480	0.009875	0.011440	0.001575	21.580	29.33	140.50	1436.0	0.15580	0.25670	0.388900	0.198400	0.3216	0.07570	0.0
265	20.730	31.12	135.70	1419.0	0.09469	0.11430	0.136700	0.086460	0.1769	0.05674	1.1720	1.6170	7.7490	199.700	0.004551	0.014780	0.021430	0.009280	0.013670	0.002299	32.490	47.16	214.00	3432.0	0.14010	0.26440	0.344200	0.165900	0.2868	0.08218	0.0
266	10.600	18.95	69.28	346.4	0.09688	0.11470	0.063870	0.026420	0.1922	0.06491	0.4505	1.1970	3.4300	27.100	0.007470	0.035810	0.033540	0.013650	0.035040	0.003318	11.880	22.94	78.28	424.8	0.12130	0.25150	0.191600	0.079260	0.2940	0.07587	1.0
267	13.590	21.84	87.16	561.0	0.07956	0.08259	0.040720	0.021420	0.1635	0.05859	0.3380	1.9160	2.5910	26.760	0.005436	0.024060	0.030990	0.009919	0.020300	0.003009	14.800	30.04	97.66	661.5	0.10050	0.17300	0.145300	0.061890	0.2446	0.07024	1.0
268	12.870	16.21	82.38	512.2	0.09425	0.06219	0.039000	0.016150	0.2010	0.05769	0.2345	1.2190	1.5460	18.240	0.005518	0.021780	0.025890	0.006330	0.025930	0.002157	13.900	23.64	89.27	597.5	0.12560	0.18080	0.199200	0.057800	0.3604	0.07062	1.0
269	10.710	20.39	69.50	344.9	0.10820	0.12890	0.084480	0.028670	0.1668	0.06862	0.3198	1.4890	2.2300	20.740	0.008902	0.047850	0.073390	0.017450	0.027280	0.007610	11.690	25.21	76.51	410.4	0.13350	0.25500	0.253400	0.086000	0.2605	0.08701	1.0
270	14.290	16.82	90.30	632.6	0.06429	0.02675	0.007250	0.006250	0.1508	0.05376	0.1302	0.7198	0.8439	10.770	0.003492	0.003710	0.004826	0.003608	0.015360	0.001381	14.910	20.65	94.44	684.6	0.08567	0.05036	0.038660	0.033330	0.2458	0.06120	1.0
271	11.290	13.04	72.23	388.0	0.09834	0.07608	0.032650	0.027550	0.1769	0.06270	0.1904	0.5293	1.1640	13.170	0.006472	0.011220	0.012820	0.008849	0.016920	0.002817	12.320	16.18	78.27	457.5	0.13580	0.15070	0.127500	0.087500	0.2733	0.08022	1.0
272	21.750	20.99	147.30	1491.0	0.09401	0.19610	0.219500	0.108800	0.1721	0.06194	1.1670	1.3520	8.8670	156.800	0.005687	0.049600	0.063290	0.015610	0.019240	0.004614	28.190	28.18	195.90	2384.0	0.12720	0.47250	0.580700	0.184100	0.2833	0.08858	0.0
273	9.742	15.67	61.50	289.9	0.09037	0.04689	0.011030	0.014070	0.2081	0.06312	0.2684	1.4090	1.7500	16.390	0.013800	0.010670	0.008347	0.009472	0.017980	0.004261	10.750	20.88	68.09	355.2	0.14670	0.09370	0.040430	0.051590	0.2841	0.08175	1.0
274	17.930	24.48	115.20	998.9	0.08855	0.07027	0.056990	0.047440	0.1538	0.05510	0.4212	1.4330	2.7650	45.810	0.005444	0.011690	0.016220	0.008522	0.014190	0.002751	20.920	34.69	135.10	1320.0	0.13150	0.18060	0.208000	0.113600	0.2504	0.07948	0.0
275	11.890	17.36	76.20	435.6	0.12250	0.07210	0.059290	0.074040	0.2015	0.05875	0.6412	2.2930	4.0210	48.840	0.014180	0.014890	0.012670	0.019100	0.026780	0.003002	12.400	18.99	79.46	472.4	0.13590	0.08368	0.071530	0.089460	0.2220	0.06033	1.0
276	11.330	14.16	71.79	396.6	0.09379	0.03872	0.001487	0.003333	0.1954	0.05821	0.2375	1.2800	1.5650	17.090	0.008426	0.008998	0.001487	0.003333	0.023580	0.001627	12.200	18.99	77.37	458.0	0.12590	0.07348	0.004955	0.011110	0.2758	0.06386	1.0
277	18.810	19.98	120.90	1102.0	0.08923	0.05884	0.080200	0.058430	0.1550	0.04996	0.3283	0.8280	2.3630	36.740	0.007571	0.011140	0.026230	0.014630	0.019300	0.001676	19.960	24.30	129.00	1236.0	0.12430	0.11600	0.221000	0.129400	0.2567	0.05737	0.0
278	13.590	17.84	86.24	572.3	0.07948	0.04052	0.019970	0.012380	0.1573	0.05520	0.2580	1.1660	1.6830	22.220	0.003741	0.005274	0.010650	0.005044	0.013440	0.001126	15.500	26.10	98.91	739.1	0.10500	0.07622	0.106000	0.051850	0.2335	0.06263	1.0
279	13.850	15.18	88.99	587.4	0.09516	0.07688	0.044790	0.037110	0.2110	0.05853	0.2479	0.9195	1.8300	19.410	0.004235	0.015410	0.014570	0.010430	0.015280	0.001593	14.980	21.74	98.37	670.0	0.11850	0.17240	0.145600	0.099930	0.2955	0.06912	1.0
280	19.160	26.60	126.20	1138.0	0.10200	0.14530	0.192100	0.096640	0.1902	0.06220	0.6361	1.0010	4.3210	69.650	0.007392	0.024490	0.039880	0.012930	0.014350	0.003446	23.720	35.90	159.80	1724.0	0.17820	0.38410	0.575400	0.187200	0.3258	0.09720	0.0
281	11.740	14.02	74.24	427.3	0.07813	0.04340	0.022450	0.027630	0.2101	0.06113	0.5619	1.2680	3.7170	37.830	0.008034	0.014420	0.015140	0.018460	0.029210	0.002005	13.310	18.26	84.70	533.7	0.10360	0.08500	0.067350	0.082900	0.3101	0.06688	1.0
282	19.400	18.18	127.20	1145.0	0.10370	0.14420	0.162600	0.094640	0.1893	0.05892	0.4709	0.9951	2.9030	53.160	0.005654	0.021990	0.030590	0.014990	0.016230	0.001965	23.790	28.65	152.40	1628.0	0.15180	0.37490	0.431600	0.225200	0.3590	0.07787	0.0
283	16.240	18.77	108.80	805.1	0.10660	0.18020	0.194800	0.090520	0.1876	0.06684	0.2873	0.9173	2.4640	28.090	0.004563	0.034810	0.038720	0.012090	0.013880	0.004081	18.550	25.09	126.90	1031.0	0.13650	0.47060	0.502600	0.173200	0.2770	0.10630	0.0
284	12.890	15.70	84.08	516.6	0.07818	0.09580	0.111500	0.033900	0.1432	0.05935	0.2913	1.3890	2.3470	23.290	0.006418	0.039610	0.079270	0.017740	0.018780	0.003696	13.900	19.69	92.12	595.6	0.09926	0.23170	0.334400	0.101700	0.1999	0.07127	1.0
285	12.580	18.40	79.83	489.0	0.08393	0.04216	0.001860	0.002924	0.1697	0.05855	0.2719	1.3500	1.7210	22.450	0.006383	0.008008	0.001860	0.002924	0.025710	0.002015	13.500	23.08	85.56	564.1	0.10380	0.06624	0.005579	0.008772	0.2505	0.06431	1.0
286	11.940	20.76	77.87	441.0	0.08605	0.10110	0.065740	0.037910	0.1588	0.06766	0.2742	1.3900	3.1980	21.910	0.006719	0.051560	0.043870	0.016330	0.018720	0.008015	13.240	27.29	92.20	546.1	0.11160	0.28130	0.236500	0.115500	0.2465	0.09981	1.0
287	12.890	13.12	81.89	515.9	0.06955	0.03729	0.022600	0.011710	0.1337	0.05581	0.1532	0.4690	1.1150	12.680	0.004731	0.013450	0.016520	0.005905	0.016190	0.002081	13.620	15.54	87.40	577.0	0.09616	0.11470	0.118600	0.053660	0.2309	0.06915	1.0
288	11.260	19.96	73.72	394.1	0.08020	0.11810	0.092740	0.055880	0.2595	0.06233	0.4866	1.9050	2.8770	34.680	0.015740	0.082620	0.080990	0.034870	0.034180	0.006517	11.860	22.33	78.27	437.6	0.10280	0.18430	0.154600	0.093140	0.2955	0.07009	1.0
289	11.370	18.89	72.17	396.0	0.08713	0.05008	0.023990	0.021730	0.2013	0.05955	0.2656	1.9740	1.9540	17.490	0.006538	0.013950	0.013760	0.009924	0.034160	0.002928	12.360	26.14	79.29	459.3	0.11180	0.09708	0.075290	0.062030	0.3267	0.06994	1.0
290	14.410	19.73	96.03	651.0	0.08757	0.16760	0.136200	0.066020	0.1714	0.07192	0.8811	1.7700	4.3600	77.110	0.007762	0.106400	0.099600	0.027710	0.040770	0.022860	15.770	22.13	101.70	767.3	0.09983	0.24720	0.222000	0.102100	0.2272	0.08799	1.0
291	14.960	19.10	97.03	687.3	0.08992	0.09823	0.059400	0.048190	0.1879	0.05852	0.2877	0.9480	2.1710	24.870	0.005332	0.021150	0.015360	0.011870	0.015220	0.002815	16.250	26.19	109.10	809.8	0.13130	0.30300	0.180400	0.148900	0.2962	0.08472	1.0
292	12.950	16.02	83.14	513.7	0.10050	0.07943	0.061550	0.033700	0.1730	0.06470	0.2094	0.7636	1.2310	17.670	0.008725	0.020030	0.023350	0.011320	0.026250	0.004726	13.740	19.93	88.81	585.4	0.14830	0.20680	0.224100	0.105600	0.3380	0.09584	1.0
293	11.850	17.46	75.54	432.7	0.08372	0.05642	0.026880	0.022800	0.1875	0.05715	0.2070	1.2380	1.2340	13.880	0.007595	0.015000	0.014120	0.008578	0.017920	0.001784	13.060	25.75	84.35	517.8	0.13690	0.17580	0.131600	0.091400	0.3101	0.07007	1.0
294	12.720	13.78	81.78	492.1	0.09667	0.08393	0.012880	0.019240	0.1638	0.06100	0.1807	0.6931	1.3400	13.380	0.006064	0.011800	0.006564	0.007978	0.013740	0.001392	13.500	17.48	88.54	553.7	0.12980	0.14720	0.052330	0.063430	0.2369	0.06922	1.0
295	13.770	13.27	88.06	582.7	0.09198	0.06221	0.010630	0.019170	0.1592	0.05912	0.2191	0.6946	1.4790	17.740	0.004348	0.008153	0.004272	0.006829	0.021540	0.001802	14.670	16.93	94.17	661.1	0.11700	0.10720	0.037320	0.058020	0.2823	0.06794	1.0
296	10.910	12.35	69.14	363.7	0.08518	0.04721	0.012360	0.013690	0.1449	0.06031	0.1753	1.0270	1.2670	11.090	0.003478	0.012210	0.010720	0.009393	0.029410	0.003428	11.370	14.82	72.42	392.2	0.09312	0.07506	0.028840	0.031940	0.2143	0.06643	1.0
297	11.760	18.14	75.00	431.1	0.09968	0.05914	0.026850	0.035150	0.1619	0.06287	0.6450	2.1050	4.1380	49.110	0.005596	0.010050	0.012720	0.014320	0.015750	0.002758	13.360	23.39	85.10	553.6	0.11370	0.07974	0.061200	0.071600	0.1978	0.06915	0.0
298	14.260	18.17	91.22	633.1	0.06576	0.05220	0.024750	0.013740	0.1635	0.05586	0.2300	0.6690	1.6610	20.560	0.003169	0.013770	0.010790	0.005243	0.011030	0.001957	16.220	25.26	105.80	819.7	0.09445	0.21670	0.156500	0.075300	0.2636	0.07676	1.0
299	10.510	23.09	66.85	334.2	0.10150	0.06797	0.024950	0.018750	0.1695	0.06556	0.2868	1.1430	2.2890	20.560	0.010170	0.014430	0.018610	0.012500	0.034640	0.001971	10.930	24.22	70.10	362.7	0.11430	0.08614	0.041580	0.031250	0.2227	0.06777	1.0
300	19.530	18.90	129.50	1217.0	0.11500	0.16420	0.219700	0.106200	0.1792	0.06552	1.1110	1.1610	7.2370	133.000	0.006056	0.032030	0.056380	0.017330	0.018840	0.004787	25.930	26.24	171.10	2053.0	0.14950	0.41160	0.612100	0.198000	0.2968	0.09929	0.0
301	12.460	19.89	80.43	471.3	0.08451	0.10140	0.068300	0.030990	0.1781	0.06249	0.3642	1.0400	2.5790	28.320	0.006530	0.033690	0.047120	0.014030	0.027400	0.004651	13.460	23.07	88.13	551.3	0.10500	0.21580	0.190400	0.076250	0.2685	0.07764	1.0
302	20.090	23.86	134.70	1247.0	0.10800	0.18380	0.228300	0.128000	0.2249	0.07469	1.0720	1.7430	7.8040	130.800	0.007964	0.047320	0.076490	0.019360	0.027360	0.005928	23.680	29.43	158.80	1696.0	0.13470	0.33910	0.493200	0.192300	0.3294	0.09469	0.0
303	10.490	18.61	66.86	334.3	0.10680	0.06678	0.022970	0.017800	0.1482	0.06600	0.1485	1.5630	1.0350	10.080	0.008875	0.009362	0.018080	0.009199	0.017910	0.003317	11.060	24.54	70.76	375.4	0.14130	0.10440	0.084230	0.065280	0.2213	0.07842	1.0
304	11.460	18.16	73.59	403.1	0.08853	0.07694	0.033440	0.015020	0.1411	0.06243	0.3278	1.0590	2.4750	22.930	0.006652	0.026520	0.022210	0.007807	0.018940	0.003411	12.680	21.61	82.69	489.8	0.11440	0.17890	0.122600	0.055090	0.2208	0.07638	1.0
305	11.600	24.49	74.23	417.2	0.07474	0.05688	0.019740	0.013130	0.1935	0.05878	0.2512	1.7860	1.9610	18.210	0.006122	0.023370	0.015960	0.006998	0.031940	0.002211	12.440	31.62	81.39	476.5	0.09545	0.13610	0.072390	0.048150	0.3244	0.06745	1.0
306	13.200	15.82	84.07	537.3	0.08511	0.05251	0.001461	0.003261	0.1632	0.05894	0.1903	0.5735	1.2040	15.500	0.003632	0.007861	0.001128	0.002386	0.013440	0.002585	14.410	20.45	92.00	636.9	0.11280	0.13460	0.011200	0.025000	0.2651	0.08385	1.0
307	9.000	14.40	56.36	246.3	0.07005	0.03116	0.003681	0.003472	0.1788	0.06833	0.1746	1.3050	1.1440	9.789	0.007389	0.004883	0.003681	0.003472	0.027010	0.002153	9.699	20.07	60.90	285.5	0.09861	0.05232	0.014720	0.013890	0.2991	0.07804	1.0
308	13.500	12.71	85.69	566.2	0.07376	0.03614	0.002758	0.004419	0.1365	0.05335	0.2244	0.6864	1.5090	20.390	0.003338	0.003746	0.002030	0.003242	0.014800	0.001566	14.970	16.94	95.48	698.7	0.09023	0.05836	0.013790	0.022100	0.2267	0.06192	1.0
309	13.050	13.84	82.71	530.6	0.08352	0.03735	0.004559	0.008829	0.1453	0.05518	0.3975	0.8285	2.5670	33.010	0.004148	0.004711	0.002831	0.004821	0.014220	0.002273	14.730	17.40	93.96	672.4	0.10160	0.05847	0.018240	0.035320	0.2107	0.06580	1.0
310	11.700	19.11	74.33	418.7	0.08814	0.05253	0.015830	0.011480	0.1936	0.06128	0.1601	1.4300	1.1090	11.280	0.006064	0.009110	0.010420	0.007638	0.023490	0.001661	12.610	26.55	80.92	483.1	0.12230	0.10870	0.079150	0.057410	0.3487	0.06958	1.0
311	14.610	15.69	92.68	664.9	0.07618	0.03515	0.014470	0.018770	0.1632	0.05255	0.3160	0.9115	1.9540	28.900	0.005031	0.006021	0.005325	0.006324	0.014940	0.000895	16.460	21.75	103.70	840.8	0.10110	0.07087	0.047460	0.058130	0.2530	0.05695	1.0
312	12.760	13.37	82.29	504.1	0.08794	0.07948	0.040520	0.025480	0.1601	0.06140	0.3265	0.6594	2.3460	25.180	0.006494	0.027680	0.031370	0.010690	0.017310	0.004392	14.190	16.40	92.04	618.8	0.11940	0.22080	0.176900	0.084110	0.2564	0.08253	1.0
313	11.540	10.72	73.73	409.1	0.08597	0.05969	0.013670	0.008907	0.1833	0.06100	0.1312	0.3602	1.1070	9.438	0.004124	0.013400	0.010030	0.004667	0.020320	0.001952	12.340	12.87	81.23	467.8	0.10920	0.16260	0.083240	0.047150	0.3390	0.07434	1.0
314	8.597	18.60	54.09	221.2	0.10740	0.05847	0.000000	0.000000	0.2163	0.07359	0.3368	2.7770	2.2220	17.810	0.020750	0.014030	0.000000	0.000000	0.061460	0.006820	8.952	22.44	56.65	240.1	0.13470	0.07767	0.000000	0.000000	0.3142	0.08116	1.0
315	12.490	16.85	79.19	481.6	0.08511	0.03834	0.004473	0.006423	0.1215	0.05673	0.1716	0.7151	1.0470	12.690	0.004928	0.003012	0.002620	0.003390	0.013930	0.001344	13.340	19.71	84.48	544.2	0.11040	0.04953	0.019380	0.027840	0.1917	0.06174	1.0
316	12.180	14.08	77.25	461.4	0.07734	0.03212	0.011230	0.005051	0.1673	0.05649	0.2113	0.5996	1.4380	15.820	0.005343	0.005767	0.011230	0.005051	0.019770	0.000950	12.850	16.47	81.60	513.1	0.10010	0.05332	0.041160	0.018520	0.2293	0.06037	1.0
317	18.220	18.87	118.70	1027.0	0.09746	0.11170	0.113000	0.079500	0.1807	0.05664	0.4041	0.5503	2.5470	48.900	0.004821	0.016590	0.024080	0.011430	0.012750	0.002451	21.840	25.00	140.90	1485.0	0.14340	0.27630	0.385300	0.177600	0.2812	0.08198	0.0
318	9.042	18.90	60.07	244.5	0.09968	0.19720	0.197500	0.049080	0.2330	0.08743	0.4653	1.9110	3.7690	24.200	0.009845	0.065900	0.102700	0.025270	0.034910	0.007877	10.060	23.40	68.62	297.1	0.12210	0.37480	0.460900	0.114500	0.3135	0.10550	1.0
319	12.430	17.00	78.60	477.3	0.07557	0.03454	0.013420	0.016990	0.1472	0.05561	0.3778	2.2000	2.4870	31.160	0.007357	0.010790	0.009959	0.011200	0.034330	0.002961	12.900	20.21	81.76	515.9	0.08409	0.04712	0.022370	0.028320	0.1901	0.05932	1.0
320	10.250	16.18	66.52	324.2	0.10610	0.11110	0.067260	0.039650	0.1743	0.07279	0.3677	1.4710	1.5970	22.680	0.010490	0.042650	0.040040	0.015440	0.027190	0.007596	11.280	20.61	71.53	390.4	0.14020	0.23600	0.189800	0.097440	0.2608	0.09702	1.0
321	20.160	19.66	131.10	1274.0	0.08020	0.08564	0.115500	0.077260	0.1928	0.05096	0.5925	0.6863	3.8680	74.850	0.004536	0.013760	0.026450	0.012470	0.021930	0.001589	23.060	23.03	150.20	1657.0	0.10540	0.15370	0.260600	0.142500	0.3055	0.05933	0.0
322	12.860	13.32	82.82	504.8	0.11340	0.08834	0.038000	0.034000	0.1543	0.06476	0.2212	1.0420	1.6140	16.570	0.005910	0.020160	0.019020	0.010110	0.012020	0.003107	14.040	21.08	92.80	599.5	0.15470	0.22310	0.179100	0.115500	0.2382	0.08553	1.0
323	20.340	21.51	135.90	1264.0	0.11700	0.18750	0.256500	0.150400	0.2569	0.06670	0.5702	1.0230	4.0120	69.060	0.005485	0.024310	0.031900	0.013690	0.027680	0.003345	25.300	31.86	171.10	1938.0	0.15920	0.44920	0.534400	0.268500	0.5558	0.10240	0.0
324	12.200	15.21	78.01	457.9	0.08673	0.06545	0.019940	0.016920	0.1638	0.06129	0.2575	0.8073	1.9590	19.010	0.005403	0.014180	0.010510	0.005142	0.013330	0.002065	13.750	21.38	91.11	583.1	0.12560	0.19280	0.116700	0.055560	0.2661	0.07961	1.0
325	12.670	17.30	81.25	489.9	0.10280	0.07664	0.031930	0.021070	0.1707	0.05984	0.2100	0.9505	1.5660	17.610	0.006809	0.009514	0.013290	0.006474	0.020570	0.001784	13.710	21.10	88.70	574.4	0.13840	0.12120	0.102000	0.056020	0.2688	0.06888	1.0
326	14.110	12.88	90.03	616.5	0.09309	0.05306	0.017650	0.027330	0.1373	0.05700	0.2571	1.0810	1.5580	23.920	0.006692	0.011320	0.005717	0.006627	0.014160	0.002476	15.530	18.00	98.40	749.9	0.12810	0.11090	0.053070	0.058900	0.2100	0.07083	1.0
327	12.030	17.93	76.09	446.0	0.07683	0.03892	0.001546	0.005592	0.1382	0.06070	0.2335	0.9097	1.4660	16.970	0.004729	0.006887	0.001184	0.003951	0.014660	0.001755	13.070	22.25	82.74	523.4	0.10130	0.07390	0.007732	0.027960	0.2171	0.07037	1.0
328	16.270	20.71	106.90	813.7	0.11690	0.13190	0.147800	0.084880	0.1948	0.06277	0.4375	1.2320	3.2700	44.410	0.006697	0.020830	0.032480	0.013920	0.015360	0.002789	19.280	30.38	129.80	1121.0	0.15900	0.29470	0.359700	0.158300	0.3103	0.08200	0.0
329	16.260	21.88	107.50	826.8	0.11650	0.12830	0.179900	0.079810	0.1869	0.06532	0.5706	1.4570	2.9610	57.720	0.010560	0.037560	0.058390	0.011860	0.040220	0.006187	17.730	25.21	113.70	975.2	0.14260	0.21160	0.334400	0.104700	0.2736	0.07953	0.0
330	16.030	15.51	105.80	793.2	0.09491	0.13710	0.120400	0.070410	0.1782	0.05976	0.3371	0.7476	2.6290	33.270	0.005839	0.032450	0.037150	0.014590	0.014670	0.003121	18.760	21.98	124.30	1070.0	0.14350	0.44780	0.495600	0.198100	0.3019	0.09124	0.0
331	12.980	19.35	84.52	514.0	0.09579	0.11250	0.071070	0.029500	0.1761	0.06540	0.2684	0.5664	2.4650	20.650	0.005727	0.032550	0.043930	0.009811	0.027510	0.004572	14.420	21.95	99.21	634.3	0.12880	0.32530	0.343900	0.098580	0.3596	0.09166	1.0
332	11.220	19.86	71.94	387.3	0.10540	0.06779	0.005006	0.007583	0.1940	0.06028	0.2976	1.9660	1.9590	19.620	0.012890	0.011040	0.003297	0.004967	0.042430	0.001963	11.980	25.78	76.91	436.1	0.14240	0.09669	0.013350	0.020220	0.3292	0.06522	1.0
333	11.250	14.78	71.38	390.0	0.08306	0.04458	0.000974	0.002941	0.1773	0.06081	0.2144	0.9961	1.5290	15.070	0.005617	0.007124	0.000974	0.002941	0.017000	0.002030	12.760	22.06	82.08	492.7	0.11660	0.09794	0.005518	0.016670	0.2815	0.07418	1.0
334	12.300	19.02	77.88	464.4	0.08313	0.04202	0.007756	0.008535	0.1539	0.05945	0.1840	1.5320	1.1990	13.240	0.007881	0.008432	0.007004	0.006522	0.019390	0.002222	13.350	28.46	84.53	544.3	0.12220	0.09052	0.036190	0.039830	0.2554	0.07207	1.0
335	17.060	21.00	111.80	918.6	0.11190	0.10560	0.150800	0.099340	0.1727	0.06071	0.8161	2.1290	6.0760	87.170	0.006455	0.017970	0.045020	0.017440	0.018290	0.003733	20.990	33.15	143.20	1362.0	0.14490	0.20530	0.392000	0.182700	0.2623	0.07599	0.0
336	12.990	14.23	84.08	514.3	0.09462	0.09965	0.037380	0.020980	0.1652	0.07238	0.1814	0.6412	0.9219	14.410	0.005231	0.023050	0.031130	0.007315	0.016390	0.005701	13.720	16.91	87.38	576.0	0.11420	0.19750	0.145000	0.058500	0.2432	0.10090	1.0
337	18.770	21.43	122.90	1092.0	0.09116	0.14020	0.106000	0.060900	0.1953	0.06083	0.6422	1.5300	4.3690	88.250	0.007548	0.038970	0.039140	0.018160	0.021680	0.004445	24.540	34.37	161.10	1873.0	0.14980	0.48270	0.463400	0.204800	0.3679	0.09870	0.0
338	10.050	17.53	64.41	310.8	0.10070	0.07326	0.025110	0.017750	0.1890	0.06331	0.2619	2.0150	1.7780	16.850	0.007803	0.014490	0.016900	0.008043	0.021000	0.002778	11.160	26.84	71.98	384.0	0.14020	0.14020	0.105500	0.064990	0.2894	0.07664	1.0
339	23.510	24.27	155.10	1747.0	0.10690	0.12830	0.230800	0.141000	0.1797	0.05506	1.0090	0.9245	6.4620	164.100	0.006292	0.019710	0.035820	0.013010	0.014790	0.003118	30.670	30.73	202.40	2906.0	0.15150	0.26780	0.481900	0.208900	0.2593	0.07738	0.0
340	14.420	16.54	94.15	641.2	0.09751	0.11390	0.080070	0.042230	0.1912	0.06412	0.3491	0.7706	2.6770	32.140	0.004577	0.030530	0.038400	0.012430	0.018730	0.003373	16.670	21.51	111.40	862.1	0.12940	0.33710	0.375500	0.141400	0.3053	0.08764	1.0
341	9.606	16.84	61.64	280.5	0.08481	0.09228	0.084220	0.022920	0.2036	0.07125	0.1844	0.9429	1.4290	12.070	0.005954	0.034710	0.050280	0.008510	0.017500	0.004031	10.750	23.07	71.25	353.6	0.12330	0.34160	0.434100	0.081200	0.2982	0.09825	1.0
342	11.060	14.96	71.49	373.9	0.10330	0.09097	0.053970	0.033410	0.1776	0.06907	0.1601	0.8225	1.3550	10.800	0.007416	0.018770	0.027580	0.010100	0.023480	0.002917	11.920	19.90	79.76	440.0	0.14180	0.22100	0.229900	0.107500	0.3301	0.09080	1.0
343	19.680	21.68	129.90	1194.0	0.09797	0.13390	0.186300	0.110300	0.2082	0.05715	0.6226	2.2840	5.1730	67.660	0.004756	0.033680	0.043450	0.018060	0.037560	0.003288	22.750	34.66	157.60	1540.0	0.12180	0.34580	0.473400	0.225500	0.4045	0.07918	0.0
344	11.710	15.45	75.03	420.3	0.11500	0.07281	0.040060	0.032500	0.2009	0.06506	0.3446	0.7395	2.3550	24.530	0.009536	0.010970	0.016510	0.011210	0.019530	0.003100	13.060	18.16	84.16	516.4	0.14600	0.11150	0.108700	0.078640	0.2765	0.07806	1.0
345	10.260	14.71	66.20	321.6	0.09882	0.09159	0.035810	0.020370	0.1633	0.07005	0.3380	2.5090	2.3940	19.330	0.017360	0.046710	0.026110	0.012960	0.036750	0.006758	10.880	19.48	70.89	357.1	0.13600	0.16360	0.071620	0.040740	0.2434	0.08488	1.0
346	12.060	18.90	76.66	445.3	0.08386	0.05794	0.007510	0.008488	0.1555	0.06048	0.2430	1.1520	1.5590	18.020	0.007180	0.010960	0.005832	0.005495	0.019820	0.002754	13.640	27.06	86.54	562.6	0.12890	0.13520	0.045060	0.050930	0.2880	0.08083	1.0
347	14.760	14.74	94.87	668.7	0.08875	0.07780	0.046080	0.035280	0.1521	0.05912	0.3428	0.3981	2.5370	29.060	0.004732	0.015060	0.018550	0.010670	0.021630	0.002783	17.270	17.93	114.20	880.8	0.12200	0.20090	0.215100	0.125100	0.3109	0.08187	1.0
348	11.470	16.03	73.02	402.7	0.09076	0.05886	0.025870	0.023220	0.1634	0.06372	0.1707	0.7615	1.0900	12.250	0.009191	0.008548	0.009400	0.006315	0.017550	0.003009	12.510	20.79	79.67	475.8	0.15310	0.11200	0.098230	0.065480	0.2851	0.08763	1.0
349	11.950	14.96	77.23	426.7	0.11580	0.12060	0.011710	0.017870	0.2459	0.06581	0.3610	1.0500	2.4550	26.650	0.005800	0.024170	0.007816	0.010520	0.027340	0.003114	12.810	17.72	83.09	496.2	0.12930	0.18850	0.031220	0.047660	0.3124	0.07590	1.0
350	11.660	17.07	73.70	421.0	0.07561	0.03630	0.008306	0.011620	0.1671	0.05731	0.3534	0.6724	2.2250	26.030	0.006583	0.006991	0.005949	0.006296	0.022160	0.002668	13.280	19.74	83.61	542.5	0.09958	0.06476	0.030460	0.042620	0.2731	0.06825	1.0
351	15.750	19.22	107.10	758.6	0.12430	0.23640	0.291400	0.124200	0.2375	0.07603	0.5204	1.3240	3.4770	51.220	0.009329	0.065590	0.099530	0.022830	0.055430	0.007330	17.360	24.17	119.40	915.3	0.15500	0.50460	0.687200	0.213500	0.4245	0.10500	0.0
352	25.730	17.46	174.20	2010.0	0.11490	0.23630	0.336800	0.191300	0.1956	0.06121	0.9948	0.8509	7.2220	153.100	0.006369	0.042430	0.042660	0.015080	0.023350	0.003385	33.130	23.58	229.30	3234.0	0.15300	0.59370	0.645100	0.275600	0.3690	0.08815	0.0
353	15.080	25.74	98.00	716.6	0.10240	0.09769	0.123500	0.065530	0.1647	0.06464	0.6534	1.5060	4.1740	63.370	0.010520	0.024310	0.049120	0.017460	0.021200	0.004867	18.510	33.22	121.20	1050.0	0.16600	0.23560	0.402900	0.152600	0.2654	0.09438	0.0
354	11.140	14.07	71.24	384.6	0.07274	0.06064	0.045050	0.014710	0.1690	0.06083	0.4222	0.8092	3.3300	28.840	0.005541	0.033870	0.045050	0.014710	0.031020	0.004831	12.120	15.82	79.62	453.5	0.08864	0.12560	0.120100	0.039220	0.2576	0.07018	1.0
355	12.560	19.07	81.92	485.8	0.08760	0.10380	0.103000	0.043910	0.1533	0.06184	0.3602	1.4780	3.2120	27.490	0.009853	0.042350	0.062710	0.019660	0.026390	0.004205	13.370	22.43	89.02	547.4	0.10960	0.20020	0.238800	0.092650	0.2121	0.07188	1.0
356	13.050	18.59	85.09	512.0	0.10820	0.13040	0.096030	0.056030	0.2035	0.06501	0.3106	1.5100	2.5900	21.570	0.007807	0.039320	0.051120	0.018760	0.028600	0.005715	14.190	24.85	94.22	591.2	0.13430	0.26580	0.257300	0.125800	0.3113	0.08317	1.0
357	13.870	16.21	88.52	593.7	0.08743	0.05492	0.015020	0.020880	0.1424	0.05883	0.2543	1.3630	1.7370	20.740	0.005638	0.007939	0.005254	0.006042	0.015440	0.002087	15.110	25.58	96.74	694.4	0.11530	0.10080	0.052850	0.055560	0.2362	0.07113	1.0
358	8.878	15.49	56.74	241.0	0.08293	0.07698	0.047210	0.023810	0.1930	0.06621	0.5381	1.2000	4.2770	30.180	0.010930	0.028990	0.032140	0.015060	0.028370	0.004174	9.981	17.70	65.27	302.0	0.10150	0.12480	0.094410	0.047620	0.2434	0.07431	1.0
359	9.436	18.32	59.82	278.6	0.10090	0.05956	0.027100	0.014060	0.1506	0.06959	0.5079	1.2470	3.2670	30.480	0.006836	0.008982	0.023480	0.006565	0.019420	0.002713	12.020	25.02	75.79	439.6	0.13330	0.10490	0.114400	0.050520	0.2454	0.08136	1.0
360	12.540	18.07	79.42	491.9	0.07436	0.02650	0.001194	0.005449	0.1528	0.05185	0.3511	0.9527	2.3290	28.300	0.005783	0.004693	0.000793	0.003617	0.020430	0.001058	13.720	20.98	86.82	585.7	0.09293	0.04327	0.003581	0.016350	0.2233	0.05521	1.0
361	13.300	21.57	85.24	546.1	0.08582	0.06373	0.033440	0.024240	0.1815	0.05696	0.2621	1.5390	2.0280	20.980	0.005498	0.020450	0.017950	0.006399	0.018290	0.001956	14.200	29.20	92.94	621.2	0.11400	0.16670	0.121200	0.056140	0.2637	0.06658	1.0
362	12.760	18.84	81.87	496.6	0.09676	0.07952	0.026880	0.017810	0.1759	0.06183	0.2213	1.2850	1.5350	17.260	0.005608	0.016460	0.015290	0.009997	0.019090	0.002133	13.750	25.99	87.82	579.7	0.12980	0.18390	0.125500	0.083120	0.2744	0.07238	1.0
363	16.500	18.29	106.60	838.1	0.09686	0.08468	0.058620	0.048350	0.1495	0.05593	0.3389	1.4390	2.3440	33.580	0.007257	0.018050	0.018320	0.010330	0.016940	0.002001	18.130	25.45	117.20	1009.0	0.13380	0.16790	0.166300	0.091230	0.2394	0.06469	1.0
364	13.400	16.95	85.48	552.4	0.07937	0.05696	0.021810	0.014730	0.1650	0.05701	0.1584	0.6124	1.0360	13.220	0.004394	0.012500	0.014510	0.005484	0.012910	0.002074	14.730	21.70	93.76	663.5	0.12130	0.16760	0.136400	0.069870	0.2741	0.07582	1.0
365	20.440	21.78	133.80	1293.0	0.09150	0.11310	0.097990	0.077850	0.1618	0.05557	0.5781	0.9168	4.2180	72.440	0.006208	0.019060	0.023750	0.014610	0.014450	0.001906	24.310	26.37	161.20	1780.0	0.13270	0.23760	0.270200	0.176500	0.2609	0.06735	0.0
366	20.200	26.83	133.70	1234.0	0.09905	0.16690	0.164100	0.126500	0.1875	0.06020	0.9761	1.8920	7.1280	103.600	0.008439	0.046740	0.059040	0.025360	0.037100	0.004286	24.190	33.81	160.00	1671.0	0.12780	0.34160	0.370300	0.215200	0.3271	0.07632	0.0
367	12.210	18.02	78.31	458.4	0.09231	0.07175	0.043920	0.020270	0.1695	0.05916	0.2527	0.7786	1.8740	18.570	0.005833	0.013880	0.020000	0.007087	0.019380	0.001960	14.290	24.04	93.85	624.6	0.13680	0.21700	0.241300	0.088290	0.3218	0.07470	1.0
368	21.710	17.25	140.90	1546.0	0.09384	0.08562	0.116800	0.084650	0.1717	0.05054	1.2070	1.0510	7.7330	224.100	0.005568	0.011120	0.020960	0.011970	0.012630	0.001803	30.750	26.44	199.50	3143.0	0.13630	0.16280	0.286100	0.182000	0.2510	0.06494	0.0
369	22.010	21.90	147.20	1482.0	0.10630	0.19540	0.244800	0.150100	0.1824	0.06140	1.0080	0.6999	7.5610	130.200	0.003978	0.028210	0.035760	0.014710	0.015180	0.003796	27.660	25.80	195.00	2227.0	0.12940	0.38850	0.475600	0.243200	0.2741	0.08574	0.0
370	16.350	23.29	109.00	840.4	0.09742	0.14970	0.181100	0.087730	0.2175	0.06218	0.4312	1.0220	2.9720	45.500	0.005635	0.039170	0.060720	0.016560	0.031970	0.004085	19.380	31.03	129.30	1165.0	0.14150	0.46650	0.708700	0.224800	0.4824	0.09614	0.0
371	15.190	13.21	97.65	711.8	0.07963	0.06934	0.033930	0.026570	0.1721	0.05544	0.1783	0.4125	1.3380	17.720	0.005012	0.014850	0.015510	0.009155	0.016470	0.001767	16.200	15.73	104.50	819.1	0.11260	0.17370	0.136200	0.081780	0.2487	0.06766	1.0
372	21.370	15.10	141.30	1386.0	0.10010	0.15150	0.193200	0.125500	0.1973	0.06183	0.3414	1.3090	2.4070	39.060	0.004426	0.026750	0.034370	0.013430	0.016750	0.004367	22.690	21.84	152.10	1535.0	0.11920	0.28400	0.402400	0.196600	0.2730	0.08666	0.0
373	20.640	17.35	134.80	1335.0	0.09446	0.10760	0.152700	0.089410	0.1571	0.05478	0.6137	0.6575	4.1190	77.020	0.006211	0.018950	0.026810	0.012320	0.012760	0.001711	25.370	23.17	166.80	1946.0	0.15620	0.30550	0.415900	0.211200	0.2689	0.07055	0.0
374	13.690	16.07	87.84	579.1	0.08302	0.06374	0.025560	0.020310	0.1872	0.05669	0.1705	0.5066	1.3720	14.000	0.004230	0.015870	0.011690	0.006335	0.019430	0.002177	14.840	20.21	99.16	670.6	0.11050	0.20960	0.134600	0.069870	0.3323	0.07701	1.0
375	16.170	16.07	106.30	788.5	0.09880	0.14380	0.066510	0.053970	0.1990	0.06572	0.1745	0.4890	1.3490	14.910	0.004510	0.018120	0.019510	0.011960	0.019340	0.003696	16.970	19.14	113.10	861.5	0.12350	0.25500	0.211400	0.125100	0.3153	0.08960	1.0
376	10.570	20.22	70.15	338.3	0.09073	0.16600	0.228000	0.059410	0.2188	0.08450	0.1115	1.2310	2.3630	7.228	0.008499	0.076430	0.153500	0.029190	0.016170	0.012200	10.850	22.82	76.51	351.9	0.11430	0.36190	0.603000	0.146500	0.2597	0.12000	1.0
377	13.460	28.21	85.89	562.1	0.07517	0.04726	0.012710	0.011170	0.1421	0.05763	0.1689	1.1500	1.4000	14.910	0.004942	0.012030	0.007508	0.005179	0.014420	0.001684	14.690	35.63	97.11	680.6	0.11080	0.14570	0.079340	0.057810	0.2694	0.07061	1.0
378	13.660	15.15	88.27	580.6	0.08268	0.07548	0.042490	0.024710	0.1792	0.05897	0.1402	0.5417	1.1010	11.350	0.005212	0.029840	0.024430	0.008356	0.018180	0.004868	14.540	19.64	97.96	657.0	0.12750	0.31040	0.256900	0.105400	0.3387	0.09638	1.0
379	11.080	18.83	73.30	361.6	0.12160	0.21540	0.168900	0.063670	0.2196	0.07950	0.2114	1.0270	1.7190	13.990	0.007405	0.045490	0.045880	0.013390	0.017380	0.004435	13.240	32.82	91.76	508.1	0.21840	0.93790	0.840200	0.252400	0.4154	0.14030	0.0
380	11.270	12.96	73.16	386.3	0.12370	0.11110	0.079000	0.055500	0.2018	0.06914	0.2562	0.9858	1.8090	16.040	0.006635	0.017770	0.021010	0.011640	0.021080	0.003721	12.840	20.53	84.93	476.1	0.16100	0.24290	0.224700	0.131800	0.3343	0.09215	1.0
381	11.040	14.93	70.67	372.7	0.07987	0.07079	0.035460	0.020740	0.2003	0.06246	0.1642	1.0310	1.2810	11.680	0.005296	0.019030	0.017230	0.006960	0.018800	0.001941	12.090	20.83	79.73	447.1	0.10950	0.19820	0.155300	0.067540	0.3202	0.07287	1.0
382	12.050	22.72	78.75	447.8	0.06935	0.10730	0.079430	0.029780	0.1203	0.06659	0.1194	1.4340	1.7780	9.549	0.005042	0.045600	0.043050	0.016670	0.024700	0.007358	12.570	28.71	87.36	488.4	0.08799	0.32140	0.291200	0.109200	0.2191	0.09349	1.0
383	12.390	17.48	80.64	462.9	0.10420	0.12970	0.058920	0.028800	0.1779	0.06588	0.2608	0.8730	2.1170	19.200	0.006715	0.037050	0.047570	0.010510	0.018380	0.006884	14.180	23.13	95.23	600.5	0.14270	0.35930	0.320600	0.098040	0.2819	0.11180	1.0
384	13.280	13.72	85.79	541.8	0.08363	0.08575	0.050770	0.028640	0.1617	0.05594	0.1833	0.5308	1.5920	15.260	0.004271	0.020730	0.028280	0.008468	0.014610	0.002613	14.240	17.37	96.59	623.7	0.11660	0.26850	0.286600	0.091730	0.2736	0.07320	1.0
385	14.600	23.29	93.97	664.7	0.08682	0.06636	0.083900	0.052710	0.1627	0.05416	0.4157	1.6270	2.9140	33.010	0.008312	0.017420	0.033890	0.015760	0.017400	0.002871	15.790	31.71	102.20	758.2	0.13120	0.15810	0.267500	0.135900	0.2477	0.06836	0.0
386	12.210	14.09	78.78	462.0	0.08108	0.07823	0.068390	0.025340	0.1646	0.06154	0.2666	0.8309	2.0970	19.960	0.004405	0.030260	0.043440	0.010870	0.019210	0.004622	13.130	19.29	87.65	529.9	0.10260	0.24310	0.307600	0.091400	0.2677	0.08824	1.0
387	13.880	16.16	88.37	596.6	0.07026	0.04831	0.020450	0.008507	0.1607	0.05474	0.2541	0.6218	1.7090	23.120	0.003728	0.014150	0.019880	0.007016	0.016470	0.001970	15.510	19.97	99.66	745.3	0.08484	0.12330	0.109100	0.045370	0.2542	0.06623	1.0
388	11.270	15.50	73.38	392.0	0.08365	0.11140	0.100700	0.027570	0.1810	0.07252	0.3305	1.0670	2.5690	22.970	0.010380	0.066690	0.094720	0.020470	0.012190	0.012330	12.040	18.93	79.73	450.0	0.11020	0.28090	0.302100	0.082720	0.2157	0.10430	1.0
389	19.550	23.21	128.90	1174.0	0.10100	0.13180	0.185600	0.102100	0.1989	0.05884	0.6107	2.8360	5.3830	70.100	0.011240	0.040970	0.074690	0.034410	0.027680	0.006240	20.820	30.44	142.00	1313.0	0.12510	0.24140	0.382900	0.182500	0.2576	0.07602	0.0
390	10.260	12.22	65.75	321.6	0.09996	0.07542	0.019230	0.019680	0.1800	0.06569	0.1911	0.5477	1.3480	11.880	0.005682	0.013650	0.008496	0.006929	0.019380	0.002371	11.380	15.65	73.23	394.5	0.13430	0.16500	0.086150	0.066960	0.2937	0.07722	1.0
391	8.734	16.84	55.27	234.3	0.10390	0.07428	0.000000	0.000000	0.1985	0.07098	0.5169	2.0790	3.1670	28.850	0.015820	0.019660	0.000000	0.000000	0.018650	0.006736	10.170	22.80	64.01	317.0	0.14600	0.13100	0.000000	0.000000	0.2445	0.08865	1.0
392	15.490	19.97	102.40	744.7	0.11600	0.15620	0.189100	0.091130	0.1929	0.06744	0.6470	1.3310	4.6750	66.910	0.007269	0.029280	0.049720	0.016390	0.018520	0.004232	21.200	29.41	142.10	1359.0	0.16810	0.39130	0.555300	0.212100	0.3187	0.10190	0.0
393	21.610	22.28	144.40	1407.0	0.11670	0.20870	0.281000	0.156200	0.2162	0.06606	0.6242	0.9209	4.1580	80.990	0.005215	0.037260	0.047180	0.012880	0.020450	0.004028	26.230	28.74	172.00	2081.0	0.15020	0.57170	0.705300	0.242200	0.3828	0.10070	0.0
394	12.100	17.72	78.07	446.2	0.10290	0.09758	0.047830	0.033260	0.1937	0.06161	0.2841	1.6520	1.8690	22.220	0.008146	0.016310	0.018430	0.007513	0.020150	0.001798	13.560	25.80	88.33	559.5	0.14320	0.17730	0.160300	0.062660	0.3049	0.07081	1.0
395	14.060	17.18	89.75	609.1	0.08045	0.05361	0.026810	0.032510	0.1641	0.05764	0.1504	1.6850	1.2370	12.670	0.005371	0.012730	0.011320	0.009155	0.017190	0.001444	14.920	25.34	96.42	684.5	0.10660	0.12310	0.084600	0.079110	0.2523	0.06609	1.0
396	13.510	18.89	88.10	558.1	0.10590	0.11470	0.085800	0.053810	0.1806	0.06079	0.2136	1.3320	1.5130	19.290	0.005442	0.019570	0.033040	0.013670	0.013150	0.002464	14.800	27.20	97.33	675.2	0.14280	0.25700	0.343800	0.145300	0.2666	0.07686	1.0
397	12.800	17.46	83.05	508.3	0.08044	0.08895	0.073900	0.040830	0.1574	0.05750	0.3639	1.2650	2.6680	30.570	0.005421	0.034770	0.045450	0.013840	0.018690	0.004067	13.740	21.06	90.72	591.0	0.09534	0.18120	0.190100	0.082960	0.1988	0.07053	1.0
398	11.060	14.83	70.31	378.2	0.07741	0.04768	0.027120	0.007246	0.1535	0.06214	0.1855	0.6881	1.2630	12.980	0.004259	0.014690	0.019400	0.004168	0.011910	0.003537	12.680	20.35	80.79	496.7	0.11200	0.18790	0.207900	0.055560	0.2590	0.09158	1.0
399	11.800	17.26	75.26	431.9	0.09087	0.06232	0.028530	0.016380	0.1847	0.06019	0.3438	1.1400	2.2250	25.060	0.005463	0.019640	0.020790	0.005398	0.014770	0.003071	13.450	24.49	86.00	562.0	0.12440	0.17260	0.144900	0.053560	0.2779	0.08121	1.0
400	17.910	21.02	124.40	994.0	0.12300	0.25760	0.318900	0.119800	0.2113	0.07115	0.4030	0.7747	3.1230	41.510	0.007159	0.037180	0.061650	0.010510	0.015910	0.005099	20.800	27.78	149.60	1304.0	0.18730	0.59170	0.903400	0.196400	0.3245	0.11980	0.0
401	11.930	10.91	76.14	442.7	0.08872	0.05242	0.026060	0.017960	0.1601	0.05541	0.2522	1.0450	1.6490	18.950	0.006175	0.012040	0.013760	0.005832	0.010960	0.001857	13.800	20.14	87.64	589.5	0.13740	0.15750	0.151400	0.068760	0.2460	0.07262	1.0
402	12.960	18.29	84.18	525.2	0.07351	0.07899	0.040570	0.018830	0.1874	0.05899	0.2357	1.2990	2.3970	20.210	0.003629	0.037130	0.034520	0.010650	0.026320	0.003705	14.130	24.61	96.31	621.9	0.09329	0.23180	0.160400	0.066080	0.3207	0.07247	1.0
403	12.940	16.17	83.18	507.6	0.09879	0.08836	0.032960	0.023900	0.1735	0.06200	0.1458	0.9050	0.9975	11.360	0.002887	0.012850	0.016130	0.007308	0.018700	0.001972	13.860	23.02	89.69	580.9	0.11720	0.19580	0.181000	0.083880	0.3297	0.07834	1.0
404	12.340	14.95	78.29	469.1	0.08682	0.04571	0.021090	0.020540	0.1571	0.05708	0.3833	0.9078	2.6020	30.150	0.007702	0.008491	0.013070	0.010300	0.029700	0.001432	13.180	16.85	84.11	533.1	0.10480	0.06744	0.049210	0.047930	0.2298	0.05974	1.0
405	10.940	18.59	70.39	370.0	0.10040	0.07460	0.049440	0.029320	0.1486	0.06615	0.3796	1.7430	3.0180	25.780	0.009519	0.021340	0.019900	0.011550	0.020790	0.002701	12.400	25.58	82.76	472.4	0.13630	0.16440	0.141200	0.078870	0.2251	0.07732	1.0
406	16.140	14.86	104.30	800.0	0.09495	0.08501	0.055000	0.045280	0.1735	0.05875	0.2387	0.6372	1.7290	21.830	0.003958	0.012460	0.018310	0.008747	0.015000	0.001621	17.710	19.58	115.90	947.9	0.12060	0.17220	0.231000	0.112900	0.2778	0.07012	1.0
407	12.850	21.37	82.63	514.5	0.07551	0.08316	0.061260	0.018670	0.1580	0.06114	0.4993	1.7980	2.5520	41.240	0.006011	0.044800	0.051750	0.013410	0.026690	0.007731	14.400	27.01	91.63	645.8	0.09402	0.19360	0.183800	0.056010	0.2488	0.08151	1.0
408	17.990	20.66	117.80	991.7	0.10360	0.13040	0.120100	0.088240	0.1992	0.06069	0.4537	0.8733	3.0610	49.810	0.007231	0.027720	0.025090	0.014800	0.014140	0.003336	21.080	25.41	138.10	1349.0	0.14820	0.37350	0.330100	0.197400	0.3060	0.08503	0.0
409	12.270	17.92	78.41	466.1	0.08685	0.06526	0.032110	0.026530	0.1966	0.05597	0.3342	1.7810	2.0790	25.790	0.005888	0.023100	0.020590	0.010750	0.025780	0.002267	14.100	28.88	89.00	610.2	0.12400	0.17950	0.137700	0.095320	0.3455	0.06896	1.0
410	11.360	17.57	72.49	399.8	0.08858	0.05313	0.027830	0.021000	0.1601	0.05913	0.1916	1.5550	1.3590	13.660	0.005391	0.009947	0.011630	0.005872	0.013410	0.001659	13.050	36.32	85.07	521.3	0.14530	0.16220	0.181100	0.086980	0.2973	0.07745	1.0
411	11.040	16.83	70.92	373.2	0.10770	0.07804	0.030460	0.024800	0.1714	0.06340	0.1967	1.3870	1.3420	13.540	0.005158	0.009355	0.010560	0.007483	0.017180	0.002198	12.410	26.44	79.93	471.4	0.13690	0.14820	0.106700	0.074310	0.2998	0.07881	1.0
412	9.397	21.68	59.75	268.8	0.07969	0.06053	0.037350	0.005128	0.1274	0.06724	0.1186	1.1820	1.1740	6.802	0.005515	0.026740	0.037350	0.005128	0.019510	0.004583	9.965	27.99	66.61	301.0	0.10860	0.18870	0.186800	0.025640	0.2376	0.09206	1.0
413	14.990	22.11	97.53	693.7	0.08515	0.10250	0.068590	0.038760	0.1944	0.05913	0.3186	1.3360	2.3100	28.510	0.004449	0.028080	0.033120	0.011960	0.019060	0.004015	16.760	31.55	110.20	867.1	0.10770	0.33450	0.311400	0.130800	0.3163	0.09251	1.0
414	15.130	29.81	96.71	719.5	0.08320	0.04605	0.046860	0.027390	0.1852	0.05294	0.4681	1.6270	3.0430	45.380	0.006831	0.014270	0.024890	0.009087	0.031510	0.001750	17.260	36.91	110.10	931.4	0.11480	0.09866	0.154700	0.065750	0.3233	0.06165	0.0
415	11.890	21.17	76.39	433.8	0.09773	0.08120	0.025550	0.021790	0.2019	0.06290	0.2747	1.2030	1.9300	19.530	0.009895	0.030530	0.016300	0.009276	0.022580	0.002272	13.050	27.21	85.09	522.9	0.14260	0.21870	0.116400	0.082630	0.3075	0.07351	1.0
416	9.405	21.70	59.60	271.2	0.10440	0.06159	0.020470	0.012570	0.2025	0.06601	0.4302	2.8780	2.7590	25.170	0.014740	0.016740	0.013670	0.008674	0.030440	0.004590	10.850	31.24	68.73	359.4	0.15260	0.11930	0.061410	0.037700	0.2872	0.08304	1.0
417	15.500	21.08	102.90	803.1	0.11200	0.15710	0.152200	0.084810	0.2085	0.06864	1.3700	1.2130	9.4240	176.500	0.008198	0.038890	0.044930	0.021390	0.020180	0.005815	23.170	27.65	157.10	1748.0	0.15170	0.40020	0.421100	0.213400	0.3003	0.10480	0.0
418	12.700	12.17	80.88	495.0	0.08785	0.05794	0.023600	0.024020	0.1583	0.06275	0.2253	0.6457	1.5270	17.370	0.006131	0.012630	0.009075	0.008231	0.017130	0.004414	13.650	16.92	88.12	566.9	0.13140	0.16070	0.093850	0.082240	0.2775	0.09464	1.0
419	11.160	21.41	70.95	380.3	0.10180	0.05978	0.008955	0.010760	0.1615	0.06144	0.2865	1.6780	1.9680	18.990	0.006908	0.009442	0.006972	0.006159	0.026940	0.002060	12.360	28.92	79.26	458.0	0.12820	0.11080	0.035820	0.043060	0.2976	0.07123	1.0
420	11.570	19.04	74.20	409.7	0.08546	0.07722	0.054850	0.014280	0.2031	0.06267	0.2864	1.4400	2.2060	20.300	0.007278	0.020470	0.044470	0.008799	0.018680	0.003339	13.070	26.98	86.43	520.5	0.12490	0.19370	0.256000	0.066640	0.3035	0.08284	1.0
421	14.690	13.98	98.22	656.1	0.10310	0.18360	0.145000	0.063000	0.2086	0.07406	0.5462	1.5110	4.7950	49.450	0.009976	0.052440	0.052780	0.015800	0.026530	0.005444	16.460	18.34	114.10	809.2	0.13120	0.36350	0.321900	0.110800	0.2827	0.09208	1.0
422	11.610	16.02	75.46	408.2	0.10880	0.11680	0.070970	0.044970	0.1886	0.06320	0.2456	0.7339	1.6670	15.890	0.005884	0.020050	0.026310	0.013040	0.018480	0.001982	12.640	19.67	81.93	475.7	0.14150	0.21700	0.230200	0.110500	0.2787	0.07427	1.0
423	13.660	19.13	89.46	575.3	0.09057	0.11470	0.096570	0.048120	0.1848	0.06181	0.2244	0.8950	1.8040	19.360	0.003980	0.028090	0.036690	0.012740	0.015810	0.003956	15.140	25.50	101.40	708.8	0.11470	0.31670	0.366000	0.140700	0.2744	0.08839	1.0
424	9.742	19.12	61.93	289.7	0.10750	0.08333	0.008934	0.019670	0.2538	0.07029	0.6965	1.7470	4.6070	43.520	0.013070	0.018850	0.006021	0.010520	0.031000	0.004225	11.210	23.17	71.79	380.9	0.13980	0.13520	0.020850	0.045890	0.3196	0.08009	1.0
425	10.030	21.28	63.19	307.3	0.08117	0.03912	0.002470	0.005159	0.1630	0.06439	0.1851	1.3410	1.1840	11.600	0.005724	0.005697	0.002074	0.003527	0.014450	0.002411	11.110	28.94	69.92	376.3	0.11260	0.07094	0.012350	0.025790	0.2349	0.08061	1.0
426	10.480	14.98	67.49	333.6	0.09816	0.10130	0.063350	0.022180	0.1925	0.06915	0.3276	1.1270	2.5640	20.770	0.007364	0.038670	0.052630	0.012640	0.021610	0.004830	12.130	21.57	81.41	440.4	0.13270	0.29960	0.293900	0.093100	0.3020	0.09646	1.0
427	10.800	21.98	68.79	359.9	0.08801	0.05743	0.036140	0.014040	0.2016	0.05977	0.3077	1.6210	2.2400	20.200	0.006543	0.021480	0.029910	0.010450	0.018440	0.002690	12.760	32.04	83.69	489.5	0.13030	0.16960	0.192700	0.074850	0.2965	0.07662	1.0
428	11.130	16.62	70.47	381.1	0.08151	0.03834	0.013690	0.013700	0.1511	0.06148	0.1415	0.9671	0.9680	9.704	0.005883	0.006263	0.009398	0.006189	0.020090	0.002377	11.680	20.29	74.35	421.1	0.10300	0.06219	0.045800	0.040440	0.2383	0.07083	1.0
429	12.720	17.67	80.98	501.3	0.07896	0.04522	0.014020	0.018350	0.1459	0.05544	0.2954	0.8836	2.1090	23.240	0.007337	0.011740	0.005383	0.005623	0.019400	0.001180	13.820	20.96	88.87	586.8	0.10680	0.09605	0.034690	0.036120	0.2165	0.06025	1.0
430	14.900	22.53	102.10	685.0	0.09947	0.22250	0.273300	0.097110	0.2041	0.06898	0.2530	0.8749	3.4660	24.190	0.006965	0.062130	0.079260	0.022340	0.014990	0.005784	16.350	27.57	125.40	832.7	0.14190	0.70900	0.901900	0.247500	0.2866	0.11550	0.0
431	12.400	17.68	81.47	467.8	0.10540	0.13160	0.077410	0.027990	0.1811	0.07102	0.1767	1.4600	2.2040	15.430	0.010000	0.032950	0.048610	0.011670	0.021870	0.006005	12.880	22.91	89.61	515.8	0.14500	0.26290	0.240300	0.073700	0.2556	0.09359	1.0
432	20.180	19.54	133.80	1250.0	0.11330	0.14890	0.213300	0.125900	0.1724	0.06053	0.4331	1.0010	3.0080	52.490	0.009087	0.027150	0.055460	0.019100	0.024510	0.004005	22.030	25.07	146.00	1479.0	0.16650	0.29420	0.530800	0.217300	0.3032	0.08075	0.0
433	18.820	21.97	123.70	1110.0	0.10180	0.13890	0.159400	0.087440	0.1943	0.06132	0.8191	1.9310	4.4930	103.900	0.008074	0.040880	0.053210	0.018340	0.023830	0.004515	22.660	30.93	145.30	1603.0	0.13900	0.34630	0.391200	0.170800	0.3007	0.08314	0.0
434	14.860	16.94	94.89	673.7	0.08924	0.07074	0.033460	0.028770	0.1573	0.05703	0.3028	0.6683	1.6120	23.920	0.005756	0.016650	0.014610	0.008281	0.015510	0.002168	16.310	20.54	102.30	777.5	0.12180	0.15500	0.122000	0.079710	0.2525	0.06827	1.0
435	13.980	19.62	91.12	599.5	0.10600	0.11330	0.112600	0.064630	0.1669	0.06544	0.2208	0.9533	1.6020	18.850	0.005314	0.017910	0.021850	0.009567	0.012230	0.002846	17.040	30.80	113.90	869.3	0.16130	0.35680	0.406900	0.182700	0.3179	0.10550	0.0
436	12.870	19.54	82.67	509.2	0.09136	0.07883	0.017970	0.020900	0.1861	0.06347	0.3665	0.7693	2.5970	26.500	0.005910	0.013620	0.007066	0.006502	0.022230	0.002378	14.450	24.38	95.14	626.9	0.12140	0.16520	0.071270	0.063840	0.3313	0.07735	1.0
437	14.040	15.98	89.78	611.2	0.08458	0.05895	0.035340	0.029440	0.1714	0.05898	0.3892	1.0460	2.6440	32.740	0.007976	0.012950	0.016080	0.009046	0.020050	0.002830	15.660	21.58	101.20	750.0	0.11950	0.12520	0.111700	0.074530	0.2725	0.07234	1.0
438	13.850	19.60	88.68	592.6	0.08684	0.06330	0.013420	0.022930	0.1555	0.05673	0.3419	1.6780	2.3310	29.630	0.005836	0.010950	0.005812	0.007039	0.020140	0.002326	15.630	28.01	100.90	749.1	0.11180	0.11410	0.047530	0.058900	0.2513	0.06911	1.0
439	14.020	15.66	89.59	606.5	0.07966	0.05581	0.020870	0.026520	0.1589	0.05586	0.2142	0.6549	1.6060	19.250	0.004837	0.009238	0.009213	0.010760	0.011710	0.002104	14.910	19.31	96.53	688.9	0.10340	0.10170	0.062600	0.082160	0.2136	0.06710	1.0
440	10.970	17.20	71.73	371.5	0.08915	0.11130	0.094570	0.036130	0.1489	0.06640	0.2574	1.3760	2.8060	18.150	0.008565	0.046380	0.064300	0.017680	0.015160	0.004976	12.360	26.87	90.14	476.4	0.13910	0.40820	0.477900	0.155500	0.2540	0.09532	1.0
441	17.270	25.42	112.40	928.8	0.08331	0.11090	0.120400	0.057360	0.1467	0.05407	0.5100	1.6790	3.2830	58.380	0.008109	0.043080	0.049420	0.017420	0.015940	0.003739	20.380	35.46	132.80	1284.0	0.14360	0.41220	0.503600	0.173900	0.2500	0.07944	0.0
442	13.780	15.79	88.37	585.9	0.08817	0.06718	0.010550	0.009937	0.1405	0.05848	0.3563	0.4833	2.2350	29.340	0.006432	0.011560	0.007741	0.005657	0.012270	0.002564	15.270	17.50	97.90	706.6	0.10720	0.10710	0.035170	0.033120	0.1859	0.06810	1.0
443	10.570	18.32	66.82	340.9	0.08142	0.04462	0.019930	0.011110	0.2372	0.05768	0.1818	2.5420	1.2770	13.120	0.010720	0.013310	0.019930	0.011110	0.017170	0.004492	10.940	23.31	69.35	366.3	0.09794	0.06542	0.039860	0.022220	0.2699	0.06736	1.0
444	18.030	16.85	117.50	990.0	0.08947	0.12320	0.109000	0.062540	0.1720	0.05780	0.2986	0.5906	1.9210	35.770	0.004117	0.015600	0.029750	0.009753	0.012950	0.002436	20.380	22.02	133.30	1292.0	0.12630	0.26660	0.429000	0.153500	0.2842	0.08225	0.0
445	11.990	24.89	77.61	441.3	0.10300	0.09218	0.054410	0.042740	0.1820	0.06850	0.2623	1.2040	1.8650	19.390	0.008320	0.020250	0.023340	0.016650	0.020940	0.003674	12.980	30.36	84.48	513.9	0.13110	0.18220	0.160900	0.120200	0.2599	0.08251	1.0
446	17.750	28.03	117.30	981.6	0.09997	0.13140	0.169800	0.082930	0.1713	0.05916	0.3897	1.0770	2.8730	43.950	0.004714	0.020150	0.036970	0.011100	0.012370	0.002556	21.530	38.54	145.40	1437.0	0.14010	0.37620	0.639900	0.197000	0.2972	0.09075	0.0
447	14.800	17.66	95.88	674.8	0.09179	0.08890	0.040690	0.022600	0.1893	0.05886	0.2204	0.6221	1.4820	19.750	0.004796	0.011710	0.017580	0.006897	0.022540	0.001971	16.430	22.74	105.90	829.5	0.12260	0.18810	0.206000	0.083080	0.3600	0.07285	1.0
448	14.530	19.34	94.25	659.7	0.08388	0.07800	0.088170	0.029250	0.1473	0.05746	0.2535	1.3540	1.9940	23.040	0.004147	0.020480	0.033790	0.008848	0.013940	0.002327	16.300	28.39	108.10	830.5	0.10890	0.26490	0.377900	0.095940	0.2471	0.07463	1.0
449	21.100	20.52	138.10	1384.0	0.09684	0.11750	0.157200	0.115500	0.1554	0.05661	0.6643	1.3610	4.5420	81.890	0.005467	0.020750	0.031850	0.014660	0.010290	0.002205	25.680	32.07	168.20	2022.0	0.13680	0.31010	0.439900	0.228000	0.2268	0.07425	0.0
450	11.870	21.54	76.83	432.0	0.06613	0.10640	0.087770	0.023860	0.1349	0.06612	0.2560	1.5540	1.9550	20.240	0.006854	0.060630	0.066630	0.015530	0.023540	0.008925	12.790	28.18	83.51	507.2	0.09457	0.33990	0.321800	0.087500	0.2305	0.09952	1.0
451	19.590	25.00	127.70	1191.0	0.10320	0.09871	0.165500	0.090630	0.1663	0.05391	0.4674	1.3750	2.9160	56.180	0.011900	0.019290	0.049070	0.014990	0.016410	0.001807	21.440	30.96	139.80	1421.0	0.15280	0.18450	0.397700	0.146600	0.2293	0.06091	0.0
452	12.000	28.23	76.77	442.5	0.08437	0.06450	0.040550	0.019450	0.1615	0.06104	0.1912	1.7050	1.5160	13.860	0.007334	0.025890	0.029410	0.009166	0.017450	0.004302	13.090	37.88	85.07	523.7	0.12080	0.18560	0.181100	0.071160	0.2447	0.08194	1.0
453	14.530	13.98	93.86	644.2	0.10990	0.09242	0.068950	0.064950	0.1650	0.06121	0.3060	0.7213	2.1430	25.700	0.006133	0.012510	0.016150	0.011360	0.022070	0.003563	15.800	16.93	103.10	749.9	0.13470	0.14780	0.137300	0.106900	0.2606	0.07810	1.0
454	12.620	17.15	80.62	492.9	0.08583	0.05430	0.029660	0.022720	0.1799	0.05826	0.1692	0.6674	1.1160	13.320	0.003888	0.008539	0.012560	0.006888	0.016080	0.001638	14.340	22.15	91.62	633.5	0.12250	0.15170	0.188700	0.098510	0.3270	0.07330	1.0
455	13.380	30.72	86.34	557.2	0.09245	0.07426	0.028190	0.032640	0.1375	0.06016	0.3408	1.9240	2.2870	28.930	0.005841	0.012460	0.007936	0.009128	0.015640	0.002985	15.050	41.61	96.69	705.6	0.11720	0.14210	0.070030	0.077630	0.2196	0.07675	1.0
456	11.630	29.29	74.87	415.1	0.09357	0.08574	0.071600	0.020170	0.1799	0.06166	0.3135	2.4260	2.1500	23.130	0.009861	0.024180	0.042750	0.009215	0.024750	0.002128	13.120	38.81	86.04	527.8	0.14060	0.20310	0.292300	0.068350	0.2884	0.07220	1.0
457	13.210	25.25	84.10	537.9	0.08791	0.05205	0.027720	0.020680	0.1619	0.05584	0.2084	1.3500	1.3140	17.580	0.005768	0.008082	0.015100	0.006451	0.013470	0.001828	14.350	34.23	91.29	632.9	0.12890	0.10630	0.139000	0.060050	0.2444	0.06788	1.0
458	13.000	25.13	82.61	520.2	0.08369	0.05073	0.012060	0.017620	0.1667	0.05449	0.2621	1.2320	1.6570	21.190	0.006054	0.008974	0.005681	0.006336	0.012150	0.001514	14.340	31.88	91.06	628.5	0.12180	0.10930	0.044620	0.059210	0.2306	0.06291	1.0
459	9.755	28.20	61.68	290.9	0.07984	0.04626	0.015410	0.010430	0.1621	0.05952	0.1781	1.6870	1.2430	11.280	0.006588	0.012700	0.014500	0.006104	0.015740	0.002268	10.670	36.92	68.03	349.9	0.11100	0.11090	0.071900	0.048660	0.2321	0.07211	1.0
460	17.080	27.15	111.20	930.9	0.09898	0.11100	0.100700	0.064310	0.1793	0.06281	0.9291	1.1520	6.0510	115.200	0.008740	0.022190	0.027210	0.014580	0.020450	0.004417	22.960	34.49	152.10	1648.0	0.16000	0.24440	0.263900	0.155500	0.3010	0.09060	0.0
461	27.420	26.27	186.90	2501.0	0.10840	0.19880	0.363500	0.168900	0.2061	0.05623	2.5470	1.3060	18.6500	542.200	0.007650	0.053740	0.080550	0.025980	0.016970	0.004558	36.040	31.37	251.20	4254.0	0.13570	0.42560	0.683300	0.262500	0.2641	0.07427	0.0
462	14.400	26.99	92.25	646.1	0.06995	0.05223	0.034760	0.017370	0.1707	0.05433	0.2315	0.9112	1.7270	20.520	0.005356	0.016790	0.019710	0.006370	0.014140	0.001892	15.400	31.98	100.40	734.6	0.10170	0.14600	0.147200	0.055630	0.2345	0.06464	1.0
463	11.600	18.36	73.88	412.7	0.08508	0.05855	0.033670	0.017770	0.1516	0.05859	0.1816	0.7656	1.3030	12.890	0.006709	0.017010	0.020800	0.007497	0.021240	0.002768	12.770	24.02	82.68	495.1	0.13420	0.18080	0.186000	0.082880	0.3210	0.07863	1.0
464	13.170	18.22	84.28	537.3	0.07466	0.05994	0.048590	0.028700	0.1454	0.05549	0.2023	0.6850	1.2360	16.890	0.005969	0.014930	0.015640	0.008463	0.010930	0.001672	14.900	23.89	95.10	687.6	0.12820	0.19650	0.187600	0.104500	0.2235	0.06925	1.0
465	13.240	20.13	86.87	542.9	0.08284	0.12230	0.101000	0.028330	0.1601	0.06432	0.2810	0.8135	3.3690	23.810	0.004929	0.066570	0.076830	0.013680	0.015260	0.008133	15.440	25.50	115.00	733.5	0.12010	0.56460	0.655600	0.135700	0.2845	0.12490	1.0
466	13.140	20.74	85.98	536.9	0.08675	0.10890	0.108500	0.035100	0.1562	0.06020	0.3152	0.7884	2.3120	27.400	0.007295	0.031790	0.046150	0.012540	0.015610	0.003230	14.800	25.46	100.90	689.1	0.13510	0.35490	0.450400	0.118100	0.2563	0.08174	1.0
467	9.668	18.10	61.06	286.3	0.08311	0.05428	0.014790	0.005769	0.1680	0.06412	0.3416	1.3120	2.2750	20.980	0.010980	0.012570	0.010310	0.003934	0.026930	0.002979	11.150	24.62	71.11	380.2	0.13880	0.12550	0.064090	0.025000	0.3057	0.07875	1.0
468	17.600	23.33	119.00	980.5	0.09289	0.20040	0.213600	0.100200	0.1696	0.07369	0.9289	1.4650	5.8010	104.900	0.006766	0.070250	0.065910	0.023110	0.016730	0.011300	21.570	28.87	143.60	1437.0	0.12070	0.47850	0.516500	0.199600	0.2301	0.12240	0.0
469	11.620	18.18	76.38	408.8	0.11750	0.14830	0.102000	0.055640	0.1957	0.07255	0.4101	1.7400	3.0270	27.850	0.014590	0.032060	0.049610	0.018410	0.018070	0.005217	13.360	25.40	88.14	528.1	0.17800	0.28780	0.318600	0.141600	0.2660	0.09270	1.0
470	9.667	18.49	61.49	289.1	0.08946	0.06258	0.029480	0.015140	0.2238	0.06413	0.3776	1.3500	2.5690	22.730	0.007501	0.019890	0.027140	0.009883	0.019600	0.003913	11.140	25.62	70.88	385.2	0.12340	0.15420	0.127700	0.065600	0.3174	0.08524	1.0
471	12.040	28.14	76.85	449.9	0.08752	0.06000	0.023670	0.023770	0.1854	0.05698	0.6061	2.6430	4.0990	44.960	0.007517	0.015550	0.014650	0.011830	0.020470	0.003883	13.600	33.33	87.24	567.6	0.10410	0.09726	0.055240	0.055470	0.2404	0.06639	1.0
472	14.920	14.93	96.45	686.9	0.08098	0.08549	0.055390	0.032210	0.1687	0.05669	0.2446	0.4334	1.8260	23.310	0.003271	0.017700	0.023100	0.008399	0.011480	0.002379	17.180	18.22	112.00	906.6	0.10650	0.27910	0.315100	0.114700	0.2688	0.08273	1.0
473	12.270	29.97	77.42	465.4	0.07699	0.03398	0.000000	0.000000	0.1701	0.05960	0.4455	3.6470	2.8840	35.130	0.007339	0.008243	0.000000	0.000000	0.031410	0.003136	13.450	38.05	85.08	558.9	0.09422	0.05213	0.000000	0.000000	0.2409	0.06743	1.0
474	10.880	15.62	70.41	358.9	0.10070	0.10690	0.051150	0.015710	0.1861	0.06837	0.1482	0.5380	1.3010	9.597	0.004474	0.030930	0.027570	0.006691	0.012120	0.004672	11.940	19.35	80.78	433.1	0.13320	0.38980	0.336500	0.079660	0.2581	0.10800	1.0
475	12.830	15.73	82.89	506.9	0.09040	0.08269	0.058350	0.030780	0.1705	0.05913	0.1499	0.4875	1.1950	11.640	0.004873	0.017960	0.033180	0.008360	0.016010	0.002289	14.090	19.35	93.22	605.8	0.13260	0.26100	0.347600	0.097830	0.3006	0.07802	1.0
476	14.200	20.53	92.41	618.4	0.08931	0.11080	0.050630	0.030580	0.1506	0.06009	0.3478	1.0180	2.7490	31.010	0.004107	0.032880	0.028210	0.013500	0.016100	0.002744	16.450	27.26	112.10	828.5	0.11530	0.34290	0.251200	0.133900	0.2534	0.07858	1.0
477	13.900	16.62	88.97	599.4	0.06828	0.05319	0.022240	0.013390	0.1813	0.05536	0.1555	0.5762	1.3920	14.030	0.003308	0.013150	0.009904	0.004832	0.013160	0.002095	15.140	21.80	101.20	718.9	0.09384	0.20060	0.138400	0.062220	0.2679	0.07698	1.0
478	11.490	14.59	73.99	404.9	0.10460	0.08228	0.053080	0.019690	0.1779	0.06574	0.2034	1.1660	1.5670	14.340	0.004957	0.021140	0.041560	0.008038	0.018430	0.003614	12.400	21.90	82.04	467.6	0.13520	0.20100	0.259600	0.074310	0.2941	0.09180	1.0
479	16.250	19.51	109.80	815.8	0.10260	0.18930	0.223600	0.091940	0.2151	0.06578	0.3147	0.9857	3.0700	33.120	0.009197	0.054700	0.080790	0.022150	0.027730	0.006355	17.390	23.05	122.10	939.7	0.13770	0.44620	0.589700	0.177500	0.3318	0.09136	0.0
480	12.160	18.03	78.29	455.3	0.09087	0.07838	0.029160	0.015270	0.1464	0.06284	0.2194	1.1900	1.6780	16.260	0.004911	0.016660	0.013970	0.005161	0.014540	0.001858	13.340	27.87	88.83	547.4	0.12080	0.22790	0.162000	0.056900	0.2406	0.07729	1.0
481	13.900	19.24	88.73	602.9	0.07991	0.05326	0.029950	0.020700	0.1579	0.05594	0.3316	0.9264	2.0560	28.410	0.003704	0.010820	0.015300	0.006275	0.010620	0.002217	16.410	26.42	104.40	830.5	0.10640	0.14150	0.167300	0.081500	0.2356	0.07603	1.0
482	13.470	14.06	87.32	546.3	0.10710	0.11550	0.057860	0.052660	0.1779	0.06639	0.1588	0.5733	1.1020	12.840	0.004450	0.014520	0.013340	0.008791	0.016980	0.002787	14.830	18.32	94.94	660.2	0.13930	0.24990	0.184800	0.133500	0.3227	0.09326	1.0
483	13.700	17.64	87.76	571.1	0.09950	0.07957	0.045480	0.031600	0.1732	0.06088	0.2431	0.9462	1.5640	20.640	0.003245	0.008186	0.016980	0.009233	0.012850	0.001524	14.960	23.53	95.78	686.5	0.11990	0.13460	0.174200	0.090770	0.2518	0.06960	1.0
484	15.730	11.28	102.80	747.2	0.10430	0.12990	0.119100	0.062110	0.1784	0.06259	0.1630	0.3871	1.1430	13.870	0.006034	0.018200	0.033360	0.010670	0.011750	0.002256	17.010	14.20	112.50	854.3	0.15410	0.29790	0.400400	0.145200	0.2557	0.08181	1.0
485	12.450	16.41	82.85	476.7	0.09514	0.15110	0.154400	0.048460	0.2082	0.07325	0.3921	1.2070	5.0040	30.190	0.007234	0.074710	0.111400	0.027210	0.032320	0.009627	13.780	21.03	97.82	580.6	0.11750	0.40610	0.489600	0.134200	0.3231	0.10340	1.0
486	14.640	16.85	94.21	666.0	0.08641	0.06698	0.051920	0.027910	0.1409	0.05355	0.2204	1.0060	1.4710	19.980	0.003535	0.013930	0.018000	0.006144	0.012540	0.001219	16.460	25.44	106.00	831.0	0.11420	0.20700	0.243700	0.078280	0.2455	0.06596	1.0
487	19.440	18.82	128.10	1167.0	0.10890	0.14480	0.225600	0.119400	0.1823	0.06115	0.5659	1.4080	3.6310	67.740	0.005288	0.028330	0.042560	0.011760	0.017170	0.003211	23.960	30.39	153.90	1740.0	0.15140	0.37250	0.593600	0.206000	0.3266	0.09009	0.0
488	11.680	16.17	75.49	420.5	0.11280	0.09263	0.042790	0.031320	0.1853	0.06401	0.3713	1.1540	2.5540	27.570	0.008998	0.012920	0.018510	0.011670	0.021520	0.003213	13.320	21.59	86.57	549.8	0.15260	0.14770	0.149000	0.098150	0.2804	0.08024	1.0
489	16.690	20.20	107.10	857.6	0.07497	0.07112	0.036490	0.023070	0.1846	0.05325	0.2473	0.5679	1.7750	22.950	0.002667	0.014460	0.014230	0.005297	0.019610	0.001700	19.180	26.56	127.30	1084.0	0.10090	0.29200	0.247700	0.087370	0.4677	0.07623	0.0
490	12.250	22.44	78.18	466.5	0.08192	0.05200	0.017140	0.012610	0.1544	0.05976	0.2239	1.1390	1.5770	18.040	0.005096	0.012050	0.009410	0.004551	0.016080	0.002399	14.170	31.99	92.74	622.9	0.12560	0.18040	0.123000	0.063350	0.3100	0.08203	1.0
491	17.850	13.23	114.60	992.1	0.07838	0.06217	0.044450	0.041780	0.1220	0.05243	0.4834	1.0460	3.1630	50.950	0.004369	0.008274	0.011530	0.007437	0.013020	0.001309	19.820	18.42	127.10	1210.0	0.09862	0.09976	0.104800	0.083410	0.1783	0.05871	1.0
492	18.010	20.56	118.40	1007.0	0.10010	0.12890	0.117000	0.077620	0.2116	0.06077	0.7548	1.2880	5.3530	89.740	0.007997	0.027000	0.037370	0.016480	0.028970	0.003996	21.530	26.06	143.40	1426.0	0.13090	0.23270	0.254400	0.148900	0.3251	0.07625	0.0
493	12.460	12.83	78.83	477.3	0.07372	0.04043	0.007173	0.011490	0.1613	0.06013	0.3276	1.4860	2.1080	24.600	0.010390	0.010030	0.006416	0.007895	0.028690	0.004821	13.190	16.36	83.24	534.0	0.09439	0.06477	0.016740	0.026800	0.2280	0.07028	1.0
494	13.160	20.54	84.06	538.7	0.07335	0.05275	0.018000	0.012560	0.1713	0.05888	0.3237	1.4730	2.3260	26.070	0.007802	0.020520	0.013410	0.005564	0.020860	0.002701	14.500	28.46	95.29	648.3	0.11180	0.16460	0.076980	0.041950	0.2687	0.07429	1.0
495	14.870	20.21	96.12	680.9	0.09587	0.08345	0.068240	0.049510	0.1487	0.05748	0.2323	1.6360	1.5960	21.840	0.005415	0.013710	0.021530	0.011830	0.019590	0.001812	16.010	28.48	103.90	783.6	0.12160	0.13880	0.170000	0.101700	0.2369	0.06599	1.0
496	12.650	18.17	82.69	485.6	0.10760	0.13340	0.080170	0.050740	0.1641	0.06854	0.2324	0.6332	1.6960	18.400	0.005704	0.025020	0.026360	0.010320	0.017590	0.003563	14.380	22.15	95.29	633.7	0.15330	0.38420	0.358200	0.140700	0.3230	0.10330	1.0
497	12.470	17.31	80.45	480.1	0.08928	0.07630	0.036090	0.023690	0.1526	0.06046	0.1532	0.7810	1.2530	11.910	0.003796	0.013710	0.013460	0.007096	0.015360	0.001541	14.060	24.34	92.82	607.3	0.12760	0.25060	0.202800	0.105300	0.3035	0.07661	1.0
498	18.490	17.52	121.30	1068.0	0.10120	0.13170	0.149100	0.091830	0.1832	0.06697	0.7923	1.0450	4.8510	95.770	0.007974	0.032140	0.044350	0.015730	0.016170	0.005255	22.750	22.88	146.40	1600.0	0.14120	0.30890	0.353300	0.166300	0.2510	0.09445	0.0
499	20.590	21.24	137.80	1320.0	0.10850	0.16440	0.218800	0.112100	0.1848	0.06222	0.5904	1.2160	4.2060	75.090	0.006666	0.027910	0.040620	0.014790	0.011170	0.003727	23.860	30.76	163.20	1760.0	0.14640	0.35970	0.517900	0.211300	0.2480	0.08999	0.0

Theoretical Concepts

In the realm of applied machine learning in Python, the k-Nearest Neighbors (k-NN) algorithm plays a vital role. This algorithm requires several critical specifications, including a distance metric, the number of nearest neighbors to consider, optional weighting functions, and a method for aggregating the classes of these neighbor points. Typically, a Euclidean distance metric is employed, and the choice of 'k,' the number of nearest neighbors, is a crucial factor in the model's performance. The k-NN algorithm operates on a simple majority vote principle, where the class with the most representatives among the nearest neighbors is assigned to the data point in question. To illustrate its behavior with different values of 'k.' Specifically, we observed the impact of 'k' set to 1, 5, and 10, showcasing the varying decision boundaries and classification outcomes. This exploration highlighted the importance of choosing an optimal 'k' value for the task at hand, as it directly influences the algorithm's accuracy. In an empirical test using a 75%/25% train-test split dataset, we further examined how sensitive the k-NN classifier's accuracy is to the choice of the 'k' parameter. This analysis underlines the critical role of parameter tuning and underscores the significance of finding the right balance between the number of neighbors considered and the model's predictive performance. In conclusion, the k-NN algorithm, with its versatility and sensitivity to the 'k' parameter, continues to be a valuable tool in the realm of applied machine learning, offering both an insightful visual understanding and practical predictive capabilities.

Efficient Graph Rendering and Integration for Dynamic Web Applications

                        
from io import BytesIO
import base64

def decode_graph(plt):
    # Save the plot to a BytesIO object
    buffer = BytesIO()
    plt.savefig(buffer, format='png')
    buffer.seek(0)
    image_png = buffer.getvalue()
    buffer.close()
    # Encode the image to base64
    graphic = base64.b64encode(image_png).decode()

    return  graphic

Data Splitting: Training and Testing KNN-Model"

In the context of KNN models, the separation of X and y is an essential step as it allows you to train a KNN classifier on the feature matrix (X) and then use the trained model to predict the class labels (y) for new or unseen data points. KNN relies on the features in X to find the k-nearest neighbors and determine the majority class among those neighbors, which is used to classify a data point.

                        
X = df.drop('target', axis=1)
y = df.get('target')
X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)

Creating a KNN-Model with Scipy-Learn

The next step is utilize K-nearest neighbors (KNN) classifier to predict a class label. The specific objective here is to make predictions based on the mean values of each feature, effectively gauging how our classifier responds to average feature values. To achieve this, we employ a useful technique: df.mean()[:-1].values.reshape(1, -1). Now, breaking down this code: df.mean(): This part calculates the mean value for each feature in the dataset, providing an insight into the central tendency of the data. [:-1]: The [:-1] notation is used to exclude the last column in the dataset. In our case, the last column typically represents the target variable, which is not used as a feature. .values: This function converts the resulting Pandas Series into a NumPy array. .reshape(1, -1): The reshaping operation is necessary to convert the array from one dimension to two, making it compatible with the predict method of the KNeighborsClassifier. This method expects a 2D array for prediction, even when there's only one data point to predict. By employing this technique, we generate a prediction based on the mean feature values, offering a simplified representation of our data's characteristics. This step helps us understand how the KNN classifier generalizes when faced with average feature values and provides insights into its overall performance. The result of this prediction is a NumPy array with a class label, which could be array([0.]) or array([1.]) depending on the predicted class.

Evaluating KNN Classifier Accuracy

Determine the mean accuracy score of your KNN classifier with X_test and y_test, yielding a float within the range of 0 to 1. Leveraging our K-nearest neighbors (KNN) classifier, we predict class labels for the test set, yielding a NumPy array with a shape of (143,) containing values of 0.0 or 1.

Evaluating KNN Classifier Accuracy with Cross-Validation

It is necessary to test various n_neighbors values for a K-nearest neighbors (KNN) classifier and select the most suitable parameter by assessing accuracy scores, ensuring a balance between overfitting and underfitting while considering the problem's nature and dataset size. In this project, we employ cross_val_score to conduct 5-fold cross-validation for varying n_neighbors values, enabling the calculation of mean accuracy across the cross-validation folds and the manual determination of the optimal n_neighbors parameter while ensuring robust assessment through cross-validation.

                        
for idx in range(1,20):
    knn_model = KNeighborsClassifier(n_neighbors=idx)
    knn = knn_model.fit(X_train, y_train)
    means = df.mean()[:-1].values.reshape(1,-1)
    knn_predict = knn.predict(means)
    test_data = knn.predict(X_test)
    score_knn = knn.score(X_test, y_test)
    cv_scores = cross_val_score(knn_model, X_train, y_train, cv=5)  # 5-fold cross-validation
    mean_accuracy = cv_scores.mean()
    results_dict[idx] = {
        'n_neighbors': idx,
        'cross_val_accuracy': mean_accuracy,
        'test_accuracy': score_knn
    }

Model Performance Evaluation and Hyperparameter Tuning

Evaluate the model's performance using appropriate metrics such as accuracy, precision, recall, and F1-score. This 5-fold cross-validation process helps assess the KNN model's performance and provides a more reliable estimate of its accuracy compared to a single train-test split. The mean of these accuracy scores is often used as a more robust measure of the model's performance. In conclusion, the analysis shows that n_neighbors = 7 provides the best combination of mean accuracy and test accuracy. This choice offers high generalization while maintaining a high test accuracy, making it the optimal configuration for the KNN classifier in this context.

                        
n_neighbors = [result['n_neighbors'] for result in results_dict.values()]
cross_val_accuracy = [result['cross_val_accuracy'] for result in results_dict.values()]
test_accuracy = [result['test_accuracy'] for result in results_dict.values()]

x_labels = np.arange(1, len(n_neighbors) + 1)
plt.figure(figsize=(10, 6))  # Set the figure size

plt.plot(x_labels, cross_val_accuracy, label='Cross-Validation Accuracy', marker='o', linestyle='-', color='blue')
plt.plot(x_labels, test_accuracy, label='Test Accuracy', marker='o', linestyle='-', color='green')

plt.xlabel('n_neighbors')
plt.ylabel('Accuracy')
plt.title('Accuracy vs. n_neighbors')

plt.xticks(x_labels)

plt.legend()

plt.grid(True)

# Save the plot to a BytesIO object
graphic2 = decode_graph(plt)

Show Code

views.py Code

def sklearn_knn(request):
    search_line = "def sklearn_knn(request):"
    pattern = "# end_knn"
    content_json = "/static/json/data-science/content.json"
    project_key = "knn-model"
    template_path = "portfolio/templates/data-science/data-visualization/index.html"

    # Path to import files
    file_path = os.path.join(static_dir, 'datasets/database_cancer.csv')

    answer = []  # Initialize list to store results

    try:
        # Call the get_views_code to retrieve code in the views file
        views_code = get_views_code(search_line, pattern, module_dir)
        content_json_data = get_content_json_data(content_json, project_key)
        template_code = get_template_code(template_path)

        # The dataset never changes, so training 19 classifiers with 5-fold cross-validation
        # on every visit (~6 s) is wasted work. The computed results and charts are cached
        # for 15 minutes; only the first visitor in each window pays for the training.
        cached = cache.get("knn_demo:results")
        if cached is not None:
            context = {'views': views_code, 'content': content_json_data, 'template': template_code, **cached}
            return render(request, 'data-science/machine-learning/sklearn_knn.html', context)

        # In this project, combining the capabilities of Python, sci-kit-learn, Pandas, and Django.
        df = pd.read_csv(file_path)
        # Specify the column indices to include, excluding the first column (index 0)
        df = pd.read_csv(file_path, usecols=lambda column: column != "Unnamed: 0")
        Index = ['benign', 'malignant']
        types_count = df['target'].value_counts()
        types_count.index = Index
        data_to_html = th_scope(df.head(500).to_html(classes='table table-bordered table-striped to_html', index=True))

        # Create a pie chart
        plt.figure(figsize=(6, 6))
        plt.pie(types_count, labels=types_count.index, autopct='%1.1f%%', colors=['green', 'red'], startangle=140)
        plt.title('Distribution of Cancer Types')
        plt.axis('equal')  # Ensures the pie chart is circular
        plt.legend(labels=types_count.index, loc='best', fontsize='x-large')  # Adjust the font size here
        # Save the plot to a BytesIO object
        graphic = decode_graph(plt)

        # In this project, combining the capabilities of Python, sci-kit-learn, and Django, the objective is to create a cancer detection model, ensuring a seamless process of preparing data and splitting it into train and test datasets.
        # The generated model can assist in the early diagnosis of cancer, improving the accuracy of healthcare professionals' decisions.
        # In the context of KNN models, the separation of X and y is an essential step as it allows you to train a KNN classifier on the feature matrix (X) and then use the trained model to predict the class labels (y) for new or unseen data points.
        # KNN relies on the features in X to find the k-nearest neighbors and determine the majority class among those neighbors, which is used to classify a data point.
        X = df.drop('target', axis=1)
        y = df.get('target')

        X_train, X_test, y_train, y_test = train_test_split(X, y, random_state=0)

        best_accuracy = 0
        best_n_neighboors = 0

        results_dict = {}

        # Creating an instance of the KNeighborsClassifier class with a specific configuration.
        # KNeighborsClassifier initializes a instance with a "k" value of 1, emphasizing the nearest neighbor's class as the primary factor in classification. This choice has implications for the model's precision and sensitivity, making it essential to carefully consider the appropriate value of n_neighbors based on the specific requirements of your task.
        for idx in range(1, 20):
            knn_model = KNeighborsClassifier(n_neighbors=idx)
            knn = knn_model.fit(X_train, y_train)

            # Creating dataframe to calculate the means to each column of original dataframe, exclude the target field.
            # Se pasa como DataFrame con los nombres de columna de X y no como ndarray: el modelo se
            # ajustó con nombres y sklearn avisaba ("X does not have valid feature names") 19 veces
            # por petición en los logs de producción.
            means = X.mean().to_frame().T

            # Creating a predict models
            knn_predict = knn.predict(means)

            # Leveraging our K-nearest neighbors (KNN) classifier, we predict class labels for the test set, yielding a NumPy array with a shape of (143,) containing values of 0.0 or 1.
            # Determine the mean accuracy score of your KNN classifier with X_test and y_test, yielding a float within the range of 0 to 1.
            test_data = knn.predict(X_test)
            score_knn = knn.score(X_test, y_test)

            # It is necessary to test various n_neighbors values for a K-nearest neighbors (KNN) classifier and select the most suitable parameter by assessing accuracy scores, ensuring a balance between overfitting and underfitting while considering the problem's nature and dataset size.
            # Perform cross-validation on the training data
            cv_scores = cross_val_score(knn_model, X_train, y_train, cv=5)  # 5-fold cross-validation
            # Calculate the mean accuracy across cross-validation folds
            mean_accuracy = cv_scores.mean()

            # Store the results in the dictionary
            results_dict[idx] = {
                'n_neighbors': idx,
                'cross_val_accuracy': mean_accuracy,
                'test_accuracy': score_knn
            }

        n_neighbors = [result['n_neighbors'] for result in results_dict.values()]
        cross_val_accuracy = [result['cross_val_accuracy'] for result in results_dict.values()]
        test_accuracy = [result['test_accuracy'] for result in results_dict.values()]

        # Generate x-axis labels as integers with a step of 1
        x_labels = np.arange(1, len(n_neighbors) + 1)
        plt.figure(figsize=(10, 6))  # Set the figure size

        # Plot cross-validation accuracy
        plt.plot(x_labels, cross_val_accuracy, label='Cross-Validation Accuracy', marker='o', linestyle='-',
                 color='blue')

        # Plot test accuracy
        plt.plot(x_labels, test_accuracy, label='Test Accuracy', marker='o', linestyle='-', color='green')

        # Add labels and title
        plt.xlabel('n_neighbors')
        plt.ylabel('Accuracy')
        plt.title('Accuracy vs. n_neighbors')

        # Set integer x-axis labels
        plt.xticks(x_labels)

        # Add a legend to differentiate between cross-validation and test accuracy
        plt.legend()

        # Display the plot
        plt.grid(True)

        # Save the plot to a BytesIO object
        graphic2 = decode_graph(plt)
        computed = {
            'answer': answer, 'graphic': graphic, 'results_dict': results_dict,
            'graphic2': graphic2, 'data_to_html': data_to_html
        }
        cache.set("knn_demo:results", computed, 60 * 15)
        context = {'views': views_code, 'content': content_json_data, 'template': template_code, **computed}
        return render(request, 'data-science/machine-learning/sklearn_knn.html', context)
    except FileNotFoundError:
        context = {'description': 'File not found. Please check the file path or create the file if it does not',
                   'reference': "Read & Process Excel files with Data Frame"}
        return render(request, 'data-science/retrieve_error.html', context)
    except TemplateDoesNotExist:
        context = {'description': 'Template not found. Please check the file path or create the file if it does not',
                   'reference': "Books Store connection from XML File"}
        return render(request, 'data-science/retrieve_error.html', context)
    else:
        context = {'description': 'Something is wrong to retrieve data.',
                   'reference': "Something wrong with retrieving Data with Pandas"}
        return render(request, 'data-science/retrieve_error.html', context)

Template

{% extends 'base.html' %}

{% load i18n %}
{% load static %}
{% load cached_pygments %}
{% block title %}{% trans "Daily Climate Charts (matplotlib)" %} | Marco A. Parra F.{% endblock %}
{% block meta_description %}{% trans "Daily climate series plotted with matplotlib and served as inline images from a Django view." %}{% endblock %}
{% block content %}
<br>
<br>

<section class="container-section mb-4">
    <div class="container-fluid">
        <div class="row g-0">
            <div class="portfolio-box-caption">
                <div class="card">
                {% for key, values in content.items %}
                {% for items in content.values %}
                {% for value in items %}
                    <h2 class="cart-title text-center">{{ value.title }}</h2>
                    <hr>
                    <div class="card-body mb-3">
                        <h5 class="card-subtitle mb-3">{{ value.description }}</h5>
                        <p class="card-text">{{ value.key_components }}</p>
                    </div>
                </div>
            </div>
        </div>
        <hr>
    </div>
</section>

<section class="container-section mb-4">
    <div class="container-fluid">
        <h1>Step By Step data processing</h1>
        <hr>
        <div class="row g-0 mb-3 ">
            <div class="portfolio-box-caption">
                <h3>Data Collections</h3>
                <div class="row">
                    <p>{{ value.data_collection }}</p>
                    <em>
                        To retrieve data from datasets using pandas and convert it into a DataFrame, using the pd.read_csv() used to read the data source format.<br>
                    </em>
                </div>
                <div class="row container-app" style="width: 100%; max-height: 50rem; /* Set the desired height here */
        overflow-y: scroll; /* Enable vertical scrolling */">
                    <pre>
                        <code class="python">
                            file_path = parent_directory + '/mparraf/static/datasets/agrometeorologia-chillan2013-2023.csv'
                            df = pd.read_csv(file_path, skiprows=5, header=0)
                        </code>
                    </pre>
                </div>
            </div>
        </div>
        <hr>
        <div class="row g-0 mb-3">
            <div class="portfolio-box-caption">
                <h3>Data Preparation, and Exploration</h3>
                <div class="row">
                    <p>{{ value.data_preparation_exploration }}</p>
                </div>
                <div class="row container-app">
                    <pre>
                        <code>
                            date_columns = ['Tiempo UTC-4']
                            integer_columns = ['Temperatura del Aire Mínima ºC', 'Temperatura del Aire Máxima ºC']
                            df_cleaned = df.dropna(subset=date_columns, how='all').reset_index(drop=True)
                            df_cleaned = df_cleaned.dropna(subset=integer_columns, how='all')
                            df_cleaned.rename(columns={integer_columns[0]:'TMIN', integer_columns[1]:'TMAX'}, inplace=True)
                        </code>
                    </pre>
                </div>
                <hr>
                <div class="row container-app" style="width: 100%; max-height: 50rem; /* Set the desired height here */
        overflow-y: scroll; /* Enable vertical scrolling */">
                   {{ merge_university_town|safe }}
                </div>
            </div>
        </div>
        <hr>
        <div class="row g-0 mb-3">
            <div class="portfolio-box-caption">
                <h3>Enhancing Data Insights: Leveraging Matplotlib for Interactive Visualizations in Your Django Project</h3>
                <div class="row">
                    <p>
                        {{ value.data_visualization }}
                    </p>
                    <em>In the virtual environment is necessary install the matplolib library and realize the importation in the views.py</em>
                </div>
                <div class="row container-app">
                    <pre>
                        <code>
                            import matplotlib.pyplot as plt

                            plt.figure(figsize=(16, 10))
                            plt.title('Record high and record low temperatures by day (period 2010-2023)', alpha=0.8)

                            plt.plot(df_cleaned['TMAX'], c='red', label='Record High')
                            plt.plot(df_cleaned['TMIN'], c='blue', label='Record Low')
                            plt.gca().fill_between(range(len(df_cleaned)), df_cleaned['TMAX'], df_cleaned['TMIN'], facecolor='black',
                                                   alpha=0.25)
                            plt.legend(['Record High T°', 'Record Low T°'])

                            plt.xlabel('Days')
                            plt.ylabel('Temperature, (tenths C°)')

                            for spine in plt.gca().spines.values():
                                spine.set_visible(False)

                            # Save the plot to a BytesIO object
                            graphic = decode_graph(plt)
                        </code>
                    </pre>
                </div>
                <div class="row container-app" style="width: 100%; max-height: 50rem; /* Set the desired height here */
        overflow-y: scroll; /* Enable vertical scrolling */">
                    <img src="data:image/png;base64,{{ plot }}" alt="Temperatures Plot graph">
                </div>
            </div>
        </div>
        <hr>
        <div class="row g-0 mb-3">
            <div class="portfolio-box-caption">
                <h3>Dynamically Generating and Serving Graphs in Your Django Application (Plot graph)</h3>
                <div class="row">
                    <p>
                        To generate a plot a function was created to save it in the 'BytesIO' buffer, convert it to a base64-encoded string, and then use this string to display the graph on a web page or include it in a downloadable report. This allows you to generate and serve graphs within your Django application dynamically.
                    </p>
                </div>
                <div class="row container-app">
                    <pre>
                        <code>
                            from io import BytesIO
                            import base64

                            def decode_graph(plt):
                                # Save the plot to a BytesIO object
                                buffer = BytesIO()
                                plt.savefig(buffer, format='png')
                                buffer.seek(0)
                                image_png = buffer.getvalue()
                                buffer.close()
                                # Encode the image to base64
                                graphic = base64.b64encode(image_png).decode()

                                return  graphic
                        </code>
                    </pre>
                </div>
            </div>
        </div>
        <hr>
        <div class="row g-0 mb-3">
            <div class="portfolio-box-caption">
                <h3>Chillán Climate Analysis: Unveiling Temperature Trends Through Data Visualization</h3>
                <div class="row">
                    <h6>Data Preparation</h6>
                    <p>
                    Highlighting Anomalies: Overlay a scatter plot with data from the year 2022. This scatter plot will emphasize any data points (representing temperature highs and lows) where the records set between 2010 and 2023 were surpassed in 2022. These points will provide valuable insights into notable climate anomalies.
                    </p>
                </div>
                <div class="row container-app">
                    <pre>
                        <code>
                        df_cleaned['Tiempo UTC-4'] = pd.to_datetime(df_cleaned['Tiempo UTC-4'], format='%d-%m-%Y')
                        df_2022 = df_cleaned[df_cleaned['Tiempo UTC-4'].dt.year == 2022]
                        max_tmax_2022 = df_2022['TMAX'].max()
                        min_tmax_2022 = df_2022['TMIN'].min()
                        </code>
                    </pre>
                </div>
            </div>
        </div>
        <hr>
        <div class="row g-0 mb-3">
            <div class="portfolio-box-caption">
                <h3>Dynamically Generating and Serving Graphs in Your Django Application (Scatter graph)</h3>
                <div class="row container-app">
                    <pre>
                        <code>
                            plt.figure(figsize=(16, 10))
                            plt.title('Record high and record low temperatures by day (year 2022)', alpha=0.8)
                            plt.scatter(df_cleaned['Tiempo UTC-4'], df_cleaned['TMAX'], c='red', label='Record High')
                            plt.scatter(df_cleaned['Tiempo UTC-4'], df_cleaned['TMIN'], c='blue', label='Record Low')
                            plt.legend(['Record High T (2015)°', 'Record Low T° (2015)', 'Record High (period 2005-2014)',
                                        'Record Low (period 2005-2014)'])
                            plt.xlabel('Date')
                            plt.ylabel('Temperature, (tenths C°)')
                            for spine in plt.gca().spines.values():
                                spine.set_visible(False)
                            x = plt.gca().xaxis
                            for item in x.get_ticklabels():
                                item.set_rotation(45)
                            xlim_start = pd.to_datetime('01-01-2010', format='%d-%m-%Y')
                            xlim_end = pd.to_datetime('01-10-2023', format='%d-%m-%Y')
                            plt.xlim([xlim_start, xlim_end])
                            plt.axhline(y=max_tmax_2022, color='r', linestyle='-', label='Record High (period 2010-2023)')
                            plt.axhline(y=min_tmax_2022, color='b', linestyle='-', label='Record Low (period 2010-2023)')

                            graphic2 = decode_graph(plt)
                        </code>
                    </pre>
                </div>
                <div class="row container-app" style="width: 100%; max-height: 50rem; /* Set the desired height here */
        overflow-y: scroll; /* Enable vertical scrolling */">
                    <img src="data:image/png;base64,{{ scatter }}" alt="Temperatures Scatter graph">
                </div>
            </div>
        </div>
        <hr>
        {% endfor %}
        {% endfor %}
        {% endfor %}
        <hr>
    </div>
</section>

<section class="container-section mb-4">
    <div class="container-fluid">
        <div class="row g-0">
            <div class="portfolio-box-caption">
                <div class="row">
                    <div class="col-12 col-sm-10">
                        <h3 class="portfolio-box-headers" style="text-align:center">
                            {% trans "Show Code" %}</h3>
                    </div>
                    <div class="col">
                        <button type="button" class="btn btn-light" onclick="$('#section-w').toggle();">
                            Show/Hide
                        </button>
                    </div>
                </div>
            </div>
            <hr>
            <div class="container" style="display:none;" id="section-w">
                <div class="row mb-4">
                    <div class="col">
                        <h4>views.py Code</h4>
                        <div class="sourcecode">
                            {% for item in views %}
                            {{ item|pygmentize:"python3" }}
                            {% endfor %}
                        </div>
                    </div>
                    <div class="col">
                        <h4>Template</h4>
                        <div class="sourcecode">
                            {{ template|pygmentize:"html" }}
                        </div>
                    </div>
                </div>
            </div>
        </div>
    </div>
</section>

{% endblock %}