test_that("data-decomposition.R works on ATHABASCA RIVER (07BE001)", { df <- data_local("CAN-07BE001.csv") decomposed <- data_decomposition(df$max, df$year, S00) expect_equal(decomposed, df$max) decomposed <- data_decomposition(df$max, df$year, S10) expect_equal(decomposed, c( 1654.8837, 3073.7209, 2742.5581, 2061.3953, 2470.2326, 1449.0698, 1007.9070, 2476.7442, 1455.5814, 897.4186, 1843.2558, 1522.0930, 1870.9302, 1439.7674, 2198.6047, 2167.4419, 1116.2791, 1745.1163, 291.9535, 1015.8140, 1204.6512, 1593.4884, 1932.3256, 1651.1628, 2030.0000, 4758.8372, 898.6744, 1576.5116, 1945.3488, 3594.1860, 973.0233, 1511.8605, 1740.6977, 2369.5349, 1768.3721, 5377.2093, 2166.0465, 1654.8837, 1093.7209, 2202.5581, 1651.3953, 2740.2326, 1019.0698, 1477.9070, 1516.7442, 1525.5814, 3434.4186, 1663.2558, 1552.0930, 1210.9302, 2919.7674, 1448.6047, 4387.4419, 3286.2791, 1755.1163, 2433.9535, 1702.7907, 1541.6279, 2250.4651, 2199.3023, 2138.1395, 4096.9767, 1145.8140, 3324.6512, 1453.4884, 1292.3256, 1351.1628, 4300.0000, 1938.8372, 1477.6744, 2216.5116, 2585.3488, 1764.1860, 913.0233, 810.8605, 1530.6977, 2049.5349, 2458.3721, 2767.2093, 1496.0465, 1984.8837, 1393.7209, 2462.5581, 1011.3953, 1250.2326, 1679.0698, 1887.9070, 1036.7442, 2165.5814, 1374.4186, 1333.2558, 778.0930, 3680.9302, 2999.7674, 2048.6047, 1237.4419, 886.2791, 1085.1163, 2163.9535, 1722.7907, 2571.6279, 3760.4651 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S01) expect_equal(decomposed, c( 1674.9205, 3074.9329, 2748.9377, 2079.3326, 2482.1749, 1480.4503, 1049.5381, 2490.6185, 1491.9412, 947.9455, 1873.9490, 1561.9025, 1903.5241, 1484.9727, 2224.7928, 2195.4535, 1176.0103, 1787.8352, 381.3997, 1097.1945, 1280.7355, 1655.9294, 1982.4184, 1714.1835, 2078.2544, 4688.8584, 999.6091, 1648.6659, 2001.8246, 3573.4761, 1078.8932, 1593.1722, 1812.0373, 2409.9660, 1840.9188, 5259.3176, 2219.6846, 1737.5516, 1209.1604, 2256.8803, 1738.4376, 2764.7640, 1146.5770, 1579.6074, 1617.5980, 1627.3852, 3416.9459, 1759.2012, 1656.6327, 1339.4421, 2935.7216, 1564.5248, 4302.9888, 3277.3671, 1854.0436, 2485.6691, 1808.0154, 1659.9484, 2317.7152, 2271.1960, 2215.5249, 4024.9322, 1302.0420, 3311.5858, 1588.8395, 1442.1140, 1497.8149, 4206.3413, 2039.9325, 1618.4699, 2296.2292, 2634.3427, 1884.6156, 1108.9283, 1017.7097, 1675.5205, 2149.1456, 2521.8532, 2803.0134, 1649.6649, 2094.3277, 1559.8109, 2528.6339, 1217.1268, 1434.6957, 1823.3267, 2012.8711, 1247.2282, 2264.9043, 1554.4027, 1518.9246, 1022.2361, 3626.8790, 3016.2880, 2165.2036, 1440.8732, 1128.7873, 1308.1180, 2271.7292, 1879.5707, 2636.1813, 3693.6996 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S11) expect_equal(decomposed, c( 1658.8103, 3058.2798, 2730.9435, 2059.7872, 2461.6651, 1458.1330, 1025.7219, 2466.5664, 1465.9896, 920.3733, 1845.8833, 1532.3882, 1873.1030, 1452.9930, 2192.2990, 2161.7611, 1140.1392, 1751.3894, 342.2899, 1050.4986, 1233.0991, 1607.6257, 1933.4067, 1663.6449, 2027.0896, 4640.4196, 944.5355, 1593.4253, 1945.9942, 3519.0414, 1019.2838, 1533.2648, 1751.3633, 2349.1996, 1778.0367, 5201.4629, 2155.2475, 1671.1070, 1140.5924, 2189.1934, 1668.6342, 2695.8857, 1073.3485, 1506.1369, 1543.0921, 1551.7888, 3344.0777, 1681.6758, 1577.7805, 1258.7787, 2857.5685, 1482.1620, 4225.9054, 3196.8512, 1769.0840, 2401.1550, 1720.7783, 1571.2633, 2229.5989, 2181.9002, 2125.0252, 3938.0805, 1207.0190, 3220.8289, 1492.4228, 1344.2267, 1399.0071, 4113.9980, 1940.5108, 1516.8006, 2195.4451, 2533.5008, 1780.5503, 1001.5205, 908.9615, 1567.6892, 2041.7105, 2414.5334, 2695.5481, 1537.5750, 1982.6045, 1445.3552, 2416.2610, 1099.4805, 1316.7177, 1705.5976, 1894.7506, 1125.5133, 2145.6079, 1431.6677, 1395.0428, 895.6019, 3508.3497, 2894.6386, 2039.5436, 1311.6118, 997.3788, 1176.3407, 2142.4806, 1747.8805, 2506.3204, 3566.8446 ), tol = 1e-4) }) test_that("data-decomposition.R works on KOOTENAI RIVER (08NH021)", { df <- data_local("CAN-08NH021.csv") decomposed <- data_decomposition(df$max, df$year, S10) expect_equal(decomposed, c( 2738.0000, 2081.8571, 2145.7143, 1899.5714, 2633.4286, 3097.2857, 3001.1429, 2455.0000, 2188.8571, 2052.7143, 3106.5714, 1990.4286, 2104.2857, 1668.1429, 2902.0000, 2525.8571, 1552.7143, 2383.5714, 2997.4286, 3231.2857, 4205.1429, 3139.0000, 3282.8571, 3216.7143, 2740.5714, 2974.4286, 3638.2857, 3272.1429, 4006.0000, 3119.8571, 3103.7143, 3457.5714, 3021.4286, 4155.2857, 2659.1429, 2683.0000, 3526.8571, 3040.7143, 3384.5714, 3708.4286, 3072.2857, 3546.1429, 2830.0000, 3533.8571, 2697.7143, 1821.5714, 2585.4286, 2169.2857, 2313.1429, 1758.0000, 1910.8571, 1856.7143, 2158.5714, 2382.4286, 2416.2857, 2067.1429, 1875.0000, 2207.8571, 2185.7143, 2114.5714, 1967.4286, 2187.2857, 2347.1429, 2781.0000, 2067.8571, 2092.7143, 2041.5714, 2556.4286, 2920.2857, 3084.1429, 2688.0000, 2771.8571, 2415.7143, 1872.5714, 2833.4286, 2415.2857, 2313.1429, 2401.0000, 3248.8571, 2522.7143, 3116.5714, 2550.4286, 2874.2857, 2998.1429, 3262.0000, 3125.8571, 2959.7143, 2733.5714, 2817.4286, 2951.2857, 2975.1429 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S01) expect_equal(decomposed, c( 3285.4744, 2503.0477, 2562.1839, 2253.3776, 3113.3915, 3658.9715, 3532.9385, 2856.7756, 2515.5683, 2330.5160, 3621.4723, 2215.8483, 2339.8680, 1768.8937, 3319.4387, 2824.3895, 1551.5993, 2607.6926, 3393.9021, 3689.9212, 4971.9132, 3545.9539, 3728.0809, 3628.2690, 2967.7733, 3273.3118, 4178.0894, 3660.6259, 4679.4691, 3423.0601, 3387.1087, 3881.3635, 3241.3528, 4877.4762, 2680.4970, 2696.6664, 3934.2662, 3194.9758, 3699.4743, 4181.3830, 3196.1186, 3913.9522, 2785.8902, 3873.8983, 2536.7890, 1113.7550, 2311.6905, 1610.9722, 1816.6683, 870.0054, 1087.8897, 961.3350, 1436.6311, 1786.7674, 1815.0065, 1176.4459, 802.3714, 1352.8565, 1277.8866, 1112.9853, 806.3823, 1169.6700, 1428.3695, 2206.2346, 825.8639, 830.4951, 688.3543, 1648.0725, 2329.5143, 2626.5521, 1802.8607, 1937.9413, 1171.8003, 1.0000, 1961.8411, 1039.3723, 774.4740, 915.8048, 2727.3919, 1088.3242, 2373.6446, 1055.4862, 1750.5470, 1997.3188, 2579.3923, 2223.2162, 1785.9055, 1191.1843, 1347.6407, 1633.2986, 1647.4126 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S11) expect_equal(decomposed, c( 2745.7520, 1986.7403, 2057.2265, 1765.7994, 2624.0364, 3172.3982, 3060.7418, 2409.5491, 2087.8355, 1919.7419, 3197.5419, 1834.7326, 1969.9412, 1425.9181, 2954.7645, 2485.2764, 1258.1808, 2302.5772, 3082.8220, 3385.1131, 4645.8112, 3273.8182, 3465.2885, 3383.1687, 2757.9373, 3069.5106, 3960.6642, 3475.4315, 4475.3921, 3277.7318, 3259.3675, 3752.1509, 3152.3637, 4743.1162, 2647.8701, 2681.4626, 3886.7758, 3195.7871, 3697.0638, 4176.0355, 3252.6282, 3956.8318, 2899.9655, 3956.2598, 2703.3378, 1371.7703, 2531.6849, 1888.9117, 2106.5342, 1233.7518, 1463.9347, 1368.8692, 1841.8712, 2196.2992, 2247.5529, 1672.8126, 1348.1055, 1890.8865, 1847.5501, 1720.8018, 1462.6987, 1830.0098, 2099.5140, 2851.1305, 1598.9060, 1633.9288, 1533.7059, 2451.9274, 3111.3165, 3415.3691, 2689.1292, 2845.5763, 2176.7766, 1141.0432, 2967.8029, 2162.0924, 1958.0537, 2124.2906, 3803.7141, 2357.8341, 3557.0760, 2408.1842, 3073.8760, 3335.7732, 3897.4707, 3620.1595, 3272.8623, 2788.3845, 2973.1566, 3272.4465, 3331.9526 ), tol = 1e-4) }) test_that("data-decomposition.R works on BOW RIVER (05BB001)", { df <- data_local("CAN-05BB001.csv") decomposed <- data_decomposition(df$max, df$year, S10) expect_equal(decomposed, c( 318.3941, 234.8823, 269.3706, 179.8588, 238.3470, 220.8353, 243.3235, 316.8117, 182.3000, 353.7882, 194.2764, 257.7647, 181.2529, 219.7411, 388.2294, 178.7176, 224.2058, 142.6941, 234.1823, 302.6705, 229.1588, 277.6470, 202.1352, 294.6235, 327.1117, 285.5999, 214.0882, 236.5764, 166.0646, 238.5529, 197.0411, 223.5293, 146.0176, 186.5058, 229.9940, 179.4823, 147.9705, 226.4587, 189.9470, 315.4352, 144.9234, 310.4117, 267.8999, 180.3882, 285.8764, 312.3646, 272.8529, 284.3411, 179.8293, 219.3176, 240.8058, 211.2940, 295.7823, 214.2705, 213.7587, 277.2470, 320.7352, 257.2234, 307.7117, 224.1999, 236.6881, 189.1764, 233.6646, 346.1528, 250.6411, 353.1293, 180.6175, 228.1058, 244.5940, 227.0822, 188.5705, 229.0587, 266.5469, 232.0352, 195.5234, 261.0116, 201.4999, 354.9881, 188.4763, 286.9646, 251.4528, 282.9410, 286.4293, 175.9175, 173.4057, 192.8940, 309.3822, 277.8704, 260.3587, 180.8469, 253.3351, 201.8234, 214.3116, 275.7998, 214.2881, 212.7763, 218.2645, 219.7528, 350.2410, 215.7292, 196.2175, 191.7057, 233.1939, 386.6822, 521.1704, 233.6586, 207.1469, 163.6351, 256.6116 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S01) expect_equal(decomposed, c( 314.1597, 230.0312, 264.0995, 173.9204, 232.0451, 214.0047, 236.0626, 309.2704, 173.8871, 345.4173, 184.9103, 248.1254, 170.8495, 208.9882, 377.6622, 166.8111, 211.9997, 129.6273, 221.0421, 289.3763, 215.0148, 263.2670, 186.8641, 279.3744, 311.5709, 269.3385, 196.9077, 219.0436, 147.5851, 220.0527, 177.7674, 203.9435, 125.3820, 165.6611, 208.9768, 157.5831, 125.3212, 203.9349, 166.6286, 292.6727, 120.2174, 286.6483, 243.2767, 154.4793, 260.4458, 286.7007, 246.3276, 257.4417, 151.3987, 190.7853, 211.9992, 181.6830, 266.5781, 183.6941, 182.6780, 246.3818, 289.8793, 225.1501, 275.7417, 190.7479, 202.8898, 154.2968, 198.8366, 312.2541, 215.0376, 318.3676, 143.1006, 190.7178, 206.9312, 188.6828, 149.1355, 189.6886, 227.2132, 191.7097, 154.1643, 220.1175, 159.2189, 314.5320, 144.9852, 244.4961, 207.9360, 239.4280, 242.4811, 129.6821, 126.6182, 145.9188, 263.8553, 231.3213, 213.0159, 131.6293, 204.8761, 151.9547, 164.1586, 226.2514, 163.1234, 161.0779, 166.1618, 167.1725, 299.6289, 162.0609, 141.6657, 136.5557, 178.3491, 334.3817, 471.0889, 177.3110, 149.7539, 104.8372, 198.7262 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S11) expect_equal(decomposed, c( 318.6228, 234.8556, 269.4688, 179.6044, 238.3274, 220.7315, 243.3260, 317.2108, 181.9529, 354.4619, 193.9651, 257.8655, 180.8162, 219.5695, 389.3594, 178.1974, 224.0483, 141.8133, 234.1032, 303.2376, 229.0245, 278.0007, 201.7077, 295.1852, 328.0547, 286.0931, 213.7468, 236.4999, 165.1002, 238.4976, 196.4343, 223.2669, 144.6680, 185.7012, 229.8062, 178.5336, 146.5172, 226.2022, 189.1001, 316.6228, 143.2878, 311.5639, 268.3360, 179.2800, 286.6551, 313.6468, 273.4168, 285.1353, 178.6016, 218.8511, 240.7648, 210.6464, 296.8878, 213.6640, 213.1312, 278.0016, 322.4708, 257.5490, 309.2026, 223.7650, 236.5425, 187.8866, 233.4409, 348.7088, 250.8369, 355.9356, 179.0125, 227.7205, 244.6406, 226.6591, 187.0939, 228.6789, 267.2089, 231.7298, 194.1689, 261.5384, 200.2871, 358.3182, 186.8429, 288.3062, 251.7178, 284.1890, 287.8013, 173.7874, 171.1709, 191.2686, 311.5717, 279.0357, 260.9477, 178.7407, 253.6956, 200.4004, 213.3117, 276.9672, 213.2668, 211.6902, 217.3678, 218.9021, 354.2379, 214.7107, 194.4490, 189.7476, 232.8212, 392.2950, 532.1318, 233.2939, 205.7155, 160.4298, 257.1791 ), tol = 1e-4) }) test_that("data-decomposition.R works on CHILLIWACK RIVER (08MH016)", { df <- data_local("CAN-08MH016.csv") decomposed <- data_decomposition(df$max, df$year, S10) expect_equal(decomposed, c( 59.8854, 71.3484, 75.7114, 31.6744, 58.7373, 62.0003, 49.9633, 42.2263, 41.7892, 79.8522, 81.7152, 70.4782, 83.4411, 63.2041, 61.5671, 55.8300, 55.3930, 47.3560, 60.5190, 41.3819, 60.7449, 30.1079, 47.1709, 66.3338, 57.9968, 91.2598, 78.9228, 88.1857, 54.9266, 67.7895, 55.7525, 47.7155, 76.7785, 41.2414, 45.0044, 64.9674, 44.4304, 51.3933, 84.9563, 76.9193, 64.8823, 50.2452, 62.0082, 97.2712, 37.4341, 97.9971, 83.0601, 57.7231, 31.4860, 48.3490, 82.1120, 107.1750, 53.0379, 80.9009, 63.9639, 53.9269, 53.4898, 68.0528, 63.9158, 45.2788, 85.8417, 119.8047, 52.9677, 44.2307, 46.3936, 34.7566, 110.1196, 35.2826, 79.5455, 39.5085, 94.5715, 40.2345, 47.7974, 67.2604, 147.0234, 30.2864, 49.9493, 88.6123, 61.8753, 85.3382, 49.8012, 35.0642, 51.3272, 55.2901, 80.4531, 56.1161, 69.5791, 41.8420, 82.1050 ), tol = 1e-4) # NOTE: New implementation produces different results for trends 01 and 11. decomposed <- data_decomposition(df$max, df$year, S01) expect_equal(decomposed, c( 67.5444, 73.6057, 75.8476, 54.1693, 67.6624, 69.3686, 63.9093, 60.6130, 60.7010, 77.6823, 78.4552, 73.6528, 79.0888, 70.7547, 70.1827, 68.0063, 67.9643, 65.0101, 70.1484, 63.1265, 70.4073, 59.4441, 65.7484, 72.6059, 69.7764, 81.1832, 76.9701, 80.0237, 69.6225, 73.5394, 70.0207, 67.7516, 76.2135, 66.1034, 67.2758, 72.9233, 67.3155, 69.3043, 78.3954, 76.2334, 73.0669, 69.2923, 72.3895, 81.4037, 66.2737, 81.4732, 77.7311, 71.5238, 65.2226, 69.3671, 77.4380, 83.3095, 70.6481, 77.1176, 73.2419, 70.9984, 70.9465, 74.2247, 73.3308, 69.2929, 78.1142, 85.3668, 71.1003, 69.3046, 69.8132, 67.4594, 82.9842, 67.7094, 76.7030, 68.6909, 79.6715, 68.9521, 70.4846, 74.2962, 89.6280, 67.2777, 71.0630, 78.3539, 73.3586, 77.7130, 71.1847, 68.5392, 71.5318, 72.2752, 76.7803, 72.4751, 74.8617, 70.0402, 77.0432 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S11) expect_equal(decomposed, c( 61.4034, 67.2857, 69.3766, 47.7025, 60.9853, 62.5596, 57.0202, 53.6349, 53.6155, 70.3760, 71.0426, 66.1770, 71.4802, 63.1160, 62.4611, 60.2166, 60.0935, 57.0830, 62.1058, 55.0642, 62.2166, 51.2702, 57.4573, 64.1943, 61.3237, 72.5756, 68.3370, 71.3055, 60.6207, 64.4562, 60.9215, 58.6269, 66.9704, 56.9061, 58.0261, 63.5822, 57.9842, 59.9159, 68.8865, 66.7061, 63.5314, 59.7552, 62.7887, 71.6854, 56.6609, 71.6867, 67.9466, 61.7651, 55.4917, 59.5669, 67.5320, 73.3186, 60.7478, 67.1277, 63.2610, 61.0116, 60.9336, 64.1541, 63.2431, 59.2187, 67.9300, 75.0877, 60.9356, 59.1338, 59.6144, 57.2609, 72.6113, 57.4642, 66.3479, 58.3934, 69.2446, 58.6107, 60.1077, 63.8616, 79.0211, 56.8741, 60.6027, 67.8019, 62.8382, 67.1307, 60.6501, 58.0137, 60.9589, 61.6777, 66.1203, 61.8422, 64.1882, 59.3996, 66.3154 ), tol = 1e-4) }) test_that("data-decomposition.R works on OKANAGAN RIVER (08NM050)", { df <- data_local("CAN-08NM050.csv") decomposed <- data_decomposition(df$max, df$year, S10) expect_equal(decomposed, c( 45.2427, 47.9388, 39.9348, 51.3309, 42.3270, 43.7230, 93.4191, 38.3152, 34.8112, 30.2773, 44.4033, 46.2994, 45.1955, 43.8915, 44.1876, 42.0836, 40.2797, 29.0758, 24.3218, 38.6679, 52.0639, 37.2600, 33.5561, 40.5521, 45.3482, 33.8442, 55.9403, 49.5364, 41.8324, 48.4285, 37.7245, 34.9206, 43.3167, 40.0127, 56.4088, 44.3048, 66.9009, 65.0970, 39.4930, 52.0891, 34.5852, 17.6812, 36.1773, 43.6733, 19.4694, 31.8655, 49.5615, 53.3576, 32.8536, 46.0497, 63.2458, 27.1418, 62.4379, 60.5339, 45.4300, 30.0261, 78.0221, 18.7182, 29.3142, 59.6103, 57.1064, 61.5024, 55.3985, 25.8945, 49.8906, 19.6867, 11.1827, 41.3788, 66.3748, 50.5709, 16.9670, 54.8630, 27.7591, 43.6552, 61.5512, 71.5473, 34.7433, 50.7394, 48.8355, 7.8315, 44.2276, 5.5236, 33.7197, 42.6158, 56.8118, 17.4079, 39.2039, 1.0000, 29.8961, 46.4921, 57.5882, 51.9842, 42.9803, 26.5764, 55.4724, 63.4685, 51.4645 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S01) expect_equal(decomposed, c( 26.8871, 29.1061, 24.3114, 32.0651, 26.7386, 28.0233, 58.8222, 25.5375, 23.8710, 21.6462, 30.2778, 31.6970, 31.3889, 30.9777, 31.4551, 30.6201, 29.9666, 24.3635, 22.2634, 30.0600, 37.1860, 29.9508, 28.4058, 32.1574, 34.7540, 29.4588, 40.2483, 37.4061, 34.0218, 37.2855, 32.6102, 31.5893, 35.5777, 34.3268, 41.6951, 36.6077, 46.4554, 45.7809, 35.1465, 40.5708, 33.5208, 26.8498, 34.5772, 37.7664, 28.3536, 33.4623, 40.5365, 42.1321, 34.4292, 39.6048, 46.1883, 32.8565, 46.0502, 45.4353, 40.0523, 34.6524, 51.9103, 31.0049, 34.9153, 45.6024, 44.8193, 46.4062, 44.4089, 34.5746, 42.7437, 32.8436, 30.2244, 40.2600, 48.4609, 43.4395, 32.8214, 44.9747, 36.5426, 41.6346, 47.2712, 50.4001, 39.2129, 44.1712, 43.6781, 31.5197, 42.4755, 31.1707, 39.5809, 42.2720, 46.4552, 35.2275, 41.5645, 30.8576, 39.1334, 43.8696, 47.0199, 45.5311, 43.1312, 38.7506, 46.6611, 48.8624, 45.7017 ), tol = 1e-4) decomposed <- data_decomposition(df$max, df$year, S11) expect_equal(decomposed, c( 17.3133, 19.2397, 13.4782, 21.5401, 15.1938, 16.1584, 49.9534, 12.5076, 10.2140, 7.2963, 16.5628, 17.7685, 17.0423, 16.2064, 16.3827, 15.0800, 13.9873, 7.2608, 4.5150, 13.0838, 20.9241, 12.3192, 10.2328, 14.2458, 16.9470, 10.5455, 22.7440, 19.1870, 14.9954, 18.5261, 12.8290, 11.3819, 15.7855, 14.0801, 22.4677, 16.2782, 27.6114, 26.6090, 13.8847, 20.0584, 11.5320, 3.4370, 12.3571, 15.9281, 4.5713, 10.4273, 18.6353, 20.3483, 10.9965, 16.9788, 24.6565, 8.5665, 24.1603, 23.2625, 16.6541, 10.0157, 30.5600, 5.3016, 9.8366, 22.5375, 21.4479, 23.2158, 20.6647, 8.6482, 18.3714, 6.2581, 2.9408, 14.9510, 24.7578, 18.5389, 5.5171, 20.1477, 9.7698, 15.8359, 22.5760, 26.2713, 12.5153, 18.4446, 17.7269, 2.7553, 16.0285, 2.0838, 12.2605, 15.4452, 20.4646, 6.5881, 14.2546, 1.0000, 11.0578, 16.7766, 20.5523, 18.6231, 15.5708, 10.0752, 19.7304, 22.3537, 18.3624 ), tol = 1e-4) })