Runif, генерирующий значения NaN

Question

У меня есть матрица базовых значений для разных параметров, которая представляет собой матрицу строк 1 столбца x 305, и я хочу использовать runif для генерации матрицы случайных чисел (100 для каждого значения параметра) между + - 10% от исходного значения параметра. Проблема заключается в том, что существуют NaN термины случайным образом перемежаются в выходной, когда не должно быть, и я получаю следующее предупреждение:

Warning message: 
In runif(n = 30500, min = lower, max = upper) : NAs produced 

Это мой код до сих пор:

baseline <- scan("baseline.txt") 
baseline <- as.matrix(baseline) 
base <- t(baseline) 
upper <- 1.1 * base 
lower <- 0.9 * base 
matrice2 <- matrix(runif(n=30500, min = lower, max = upper), nrow=305) 

(I должен был принять t(baseline), чтобы получившийся matrice2 был в правильной форме передан другой функции, которую я использую позже). Числа в исходном диапазоне от -0,281 до 800.

У кого-нибудь есть идеи относительно того, почему он генерирует NaN? Я использовал этот точный код, прежде чем уделил время праздникам, и тогда он работал.

EDIT: это данные baseline.txt, A 305 строка х 1 колонка текстовый файл

baseline 
       [,1] 
    [1,] 0.400000000 
    [2,] 0.800000000 
    [3,] 0.200000000 
    [4,] 0.800000000 
    [5,] 0.600000000 
    [6,] 0.800000000 
    [7,] 0.150000000 
    [8,] 0.900000000 
    [9,] 0.500000000 
[10,] 0.600000000 
[11,] 0.500000000 
[12,] 0.500000000 
[13,] 0.600000000 
[14,] 0.500000000 
[15,] 0.500000000 
[16,] 0.600000000 
[17,] 0.200000000 
[18,] 0.700000000 
[19,] 0.800000000 
[20,] 0.300000000 
[21,] 0.700000000 
[22,] 0.800000000 
[23,] 0.300000000 
[24,] 0.700000000 
[25,] 0.800000000 
[26,] 0.200000000 
[27,] 0.002000000 
[28,] 0.400000000 
[29,] 0.001000000 
[30,] 0.001300000 
[31,] 0.800000000 
[32,] 0.526000000 
[33,] 0.526000000 
[34,] 0.714000000 
[35,] 0.306000000 
[36,] 0.306000000 
[37,] 0.711000000 
[38,] 0.711000000 
[39,] 0.847000000 
[40,] 0.300000000 
[41,] 0.300000000 
[42,] 0.300000000 
[43,] 0.300000000 
[44,] 0.300000000 
[45,] 0.300000000 
[46,] 0.050000000 
[47,] 0.400000000 
[48,] 0.450000000 
[49,] 0.300000000 
[50,] 0.400000000 
[51,] 0.700000000 
[52,] 0.400000000 
[53,] 0.600000000 
[54,] 0.306000000 
[55,] 0.885000000 
[56,] 0.008610000 
[57,] 0.008610000 
[58,] 0.008610000 
[59,] 0.008610000 
[60,] 0.016500000 
[61,] 6.450000000 
[62,] 6.450000000 
[63,] 6.450000000 
[64,] 6.450000000 
[65,] 0.014650000 
[66,] 0.014650000 
[67,] 0.014650000 
[68,] 0.014650000 
[69,] 0.200000000 
[70,] 0.400000000 
[71,] 0.400000000 
[72,] 3.000000000 
[73,] 3.000000000 
[74,] 3.000000000 
[75,] 3.000000000 
[76,] 3.000000000 
[77,] 3.000000000 
[78,] 3.000000000 
[79,] 3.000000000 
[80,] 3.000000000 
[81,] 0.338000000 
[82,] 0.013200000 
[83,] 0.001350000 
[84,] 0.001350000 
[85,] 0.001350000 
[86,] 0.338000000 
[87,] 34.694000000 
[88,] 0.002710000 
[89,] 0.000420000 
[90,] 0.015900000 
[91,] 0.037000000 
[92,] 0.024500000 
[93,] 0.075000000 
[94,] 0.045000000 
[95,] 0.024800000 
[96,] 0.015900000 
[97,] 0.045000000 
[98,] 0.045000000 
[99,] 2.800000000 
[100,] 0.001590000 
[101,] 0.004500000 
[102,] 0.001000000 
[103,] 0.020000000 
[104,] 0.004800000 
[105,] 7.500000000 
[106,] 34.694000000 
[107,] 0.338000000 
[108,] 0.028900000 
[109,] 0.022400000 
[110,] 0.022400000 
[111,] 0.040000000 
[112,] 0.008000000 
[113,] 0.338000000 
[114,] 0.026400000 
[115,] 0.046080000 
[116,] 0.057600000 
[117,] 0.700000000 
[118,] 0.400000000 
[119,] 0.200000000 
[120,] 0.700000000 
[121,] 0.300000000 
[122,] 0.750000000 
[123,] 4.000000000 
[124,] 0.500000000 
[125,] 8.000000000 
[126,] 800.000000000 
[127,] 3.000000000 
[128,] 3.000000000 
[129,] 6.480000000 
[130,] 1.150000000 
[131,] 0.700000000 
[132,] 0.100000000 
[133,] 1.793000000 
[134,] 1.291000000 
[135,] 1.793000000 
[136,] 1.291000000 
[137,] 1.793000000 
[138,] 1.291000000 
[139,] 5.944000000 
[140,] 4.877000000 
[141,] 0.000210000 
[142,] 0.006700000 
[143,] 2.000000000 
[144,] 0.080000000 
[145,] 0.110000000 
[146,] 0.008500000 
[147,] 120.000000000 
[148,] 60.000000000 
[149,] 3.200000000 
[150,] 0.800000000 
[151,] 1.300000000 
[152,] 1.300000000 
[153,] 1.300000000 
[154,] 2.690000000 
[155,] 0.024500000 
[156,] 7.850000000 
[157,] 1.500000000 
[158,] 10.000000000 
[159,] 10.000000000 
[160,] 4.300000000 
[161,] 0.050000000 
[162,] 0.400000000 
[163,] 7.860000000 
[164,] 3.000000000 
[165,] 0.052800000 
[166,] 0.052800000 
[167,] 15.439000000 
[168,] 7.860000000 
[169,] 15.439000000 
[170,] 0.200000000 
[171,] 0.053000000 
[172,] 0.022000000 
[173,] 0.164600000 
[174,] 0.164600000 
[175,] 0.164600000 
[176,] 0.164600000 
[177,] 4.100000000 
[178,] 15.439000000 
[179,] 7.860000000 
[180,] 0.160000000 
[181,] 0.040000000 
[182,] 0.014400000 
[183,] 7.860000000 
[184,] 6.000000000 
[185,] 0.300000000 
[186,] 0.300000000 
[187,] 33.500000000 
[188,] 0.020000000 
[189,] 1.277000000 
[190,] 0.981700000 
[191,] 1.000000000 
[192,] 1.000000000 
[193,] 1.000000000 
[194,] 0.016666667 
[195,] 0.271000000 
[196,] 0.504000000 
[197,] 0.504000000 
[198,] 0.504000000 
[199,] 0.713000000 
[200,] 0.742000000 
[201,] 0.713000000 
[202,] 0.981700000 
[203,] 0.058800000 
[204,] 1.257000000 
[205,] 1.257000000 
[206,] 2.723000000 
[207,] 3.969000000 
[208,] 2.462000000 
[209,] 2.492000000 
[210,] 3.000000000 
[211,] 0.815000000 
[212,] 1.191000000 
[213,] 1.191000000 
[214,] 1.191000000 
[215,] 2.241000000 
[216,] 3.969000000 
[217,] 2.241000000 
[218,] 3.969000000 
[219,] 152.000000000 
[220,] 0.085000000 
[221,] 0.493900000 
[222,] 0.231000000 
[223,] 0.246000000 
[224,] 0.500000000 
[225,] 0.011363636 
[226,] 0.133000000 
[227,] 0.133000000 
[228,] 0.133000000 
[229,] 0.198000000 
[230,] 0.493900000 
[231,] 0.198000000 
[232,] 0.493900000 
[233,] 1.447000000 
[234,] 1.970000000 
[235,] 0.995000000 
[236,] 0.995000000 
[237,] 1.000000000 
[238,] 0.271000000 
[239,] 0.623000000 
[240,] 0.623000000 
[241,] 0.623000000 
[242,] 1.128000000 
[243,] 1.970000000 
[244,] 1.128000000 
[245,] 1.970000000 
[246,] 2.256000000 
[247,] 2.951000000 
[248,] 3.000000000 
[249,] 3.000000000 
[250,] 3.000000000 
[251,] -0.281000000 
[252,] 1.065000000 
[253,] 1.065000000 
[254,] 1.065000000 
[255,] 0.949000000 
[256,] 2.951000000 
[257,] 0.949000000 
[258,] 2.951000000 
[259,] 0.000840000 
[260,] 0.000120000 
[261,] 0.006200000 
[262,] 0.006200000 
[263,] 0.006200000 
[264,] 0.085000000 
[265,] 0.030500000 
[266,] 0.459000000 
[267,] 0.030500000 
[268,] 0.459000000 
[269,] 0.030500000 
[270,] 0.011100000 
[271,] 0.001481000 
[272,] 0.000210000 
[273,] 0.000210000 
[274,] 0.000210000 
[275,] 0.000210000 
[276,] 142.050000000 
[277,] 0.468000000 
[278,] 0.355000000 
[279,] 0.335000000 
[280,] 0.013513514 
[281,] 0.729000000 
[282,] 0.154000000 
[283,] 0.154000000 
[284,] 0.154000000 
[285,] 0.396000000 
[286,] 0.396000000 
[287,] 0.009100000 
[288,] 0.006700000 
[289,] 0.006700000 
[290,] 0.006700000 
[291,] 0.006700000 
[292,] 112.500000000 
[293,] 112.500000000 
[294,] 112.500000000 
[295,] 0.009803922 
[296,] 0.237000000 
[297,] 0.237000000 
[298,] 0.237000000 
[299,] 0.017900000 
[300,] 0.017900000 
[301,] 0.000120000 
[302,] 0.000120000 
[303,] 0.000120000 
[304,] 0.006200000 
[305,] 0.006200000 

Answer 1

Как было отмечено в комментариях, в runifmin должно быть меньше, чем max. Ваш метод вычисления min и max перемещает max дальше от 0 и mins ближе к 0, который работает только тогда, когда числа положительны.

Как указывается в комментариях, есть несколько способов, вы можете сделать это, например pmin и pmax:

upper = pmax(0.9 * base, 1.1 * base) 
lower = pmin(0.9 * base, 1.1 * base) 

другой способ, вероятно, более эффективным, было бы:

offset = 0.1 * abs(base) 
upper = base + offset 
lower = base - offset