Create a grid of all unique combinations of half-window widths to evaluate. The result can be passed to winsrch_grid.
numeric vector of half-window widths for months, a value of one indicates twelve months
numeric vector of half-window widths for years, a value of one indicates one-year
numeric vector of half-window widths for salinity or flow, a value of one indicates the full range of values (100 percent)
A matrix with number of rows equal to the product of the lengths of each input vector, where each row is a unique combination for the selected half-window widths.
The weighting function uses a tri-cube weighting scheme such that weights diminish with distance from the center of the window. For example, a value of one for the month window does not mean that all months are weighted equally even though the window covers an entire calendar year.
createsrch()
#> mos yrs flo
#> 1 0.50 5 0.5
#> 2 0.75 5 0.5
#> 3 1.00 5 0.5
#> 4 2.00 5 0.5
#> 5 10.00 5 0.5
#> 6 0.50 8 0.5
#> 7 0.75 8 0.5
#> 8 1.00 8 0.5
#> 9 2.00 8 0.5
#> 10 10.00 8 0.5
#> 11 0.50 11 0.5
#> 12 0.75 11 0.5
#> 13 1.00 11 0.5
#> 14 2.00 11 0.5
#> 15 10.00 11 0.5
#> 16 0.50 14 0.5
#> 17 0.75 14 0.5
#> 18 1.00 14 0.5
#> 19 2.00 14 0.5
#> 20 10.00 14 0.5
#> 21 0.50 50 0.5
#> 22 0.75 50 0.5
#> 23 1.00 50 0.5
#> 24 2.00 50 0.5
#> 25 10.00 50 0.5
#> 26 0.50 5 0.6
#> 27 0.75 5 0.6
#> 28 1.00 5 0.6
#> 29 2.00 5 0.6
#> 30 10.00 5 0.6
#> 31 0.50 8 0.6
#> 32 0.75 8 0.6
#> 33 1.00 8 0.6
#> 34 2.00 8 0.6
#> 35 10.00 8 0.6
#> 36 0.50 11 0.6
#> 37 0.75 11 0.6
#> 38 1.00 11 0.6
#> 39 2.00 11 0.6
#> 40 10.00 11 0.6
#> 41 0.50 14 0.6
#> 42 0.75 14 0.6
#> 43 1.00 14 0.6
#> 44 2.00 14 0.6
#> 45 10.00 14 0.6
#> 46 0.50 50 0.6
#> 47 0.75 50 0.6
#> 48 1.00 50 0.6
#> 49 2.00 50 0.6
#> 50 10.00 50 0.6
#> 51 0.50 5 0.7
#> 52 0.75 5 0.7
#> 53 1.00 5 0.7
#> 54 2.00 5 0.7
#> 55 10.00 5 0.7
#> 56 0.50 8 0.7
#> 57 0.75 8 0.7
#> 58 1.00 8 0.7
#> 59 2.00 8 0.7
#> 60 10.00 8 0.7
#> 61 0.50 11 0.7
#> 62 0.75 11 0.7
#> 63 1.00 11 0.7
#> 64 2.00 11 0.7
#> 65 10.00 11 0.7
#> 66 0.50 14 0.7
#> 67 0.75 14 0.7
#> 68 1.00 14 0.7
#> 69 2.00 14 0.7
#> 70 10.00 14 0.7
#> 71 0.50 50 0.7
#> 72 0.75 50 0.7
#> 73 1.00 50 0.7
#> 74 2.00 50 0.7
#> 75 10.00 50 0.7
#> 76 0.50 5 0.8
#> 77 0.75 5 0.8
#> 78 1.00 5 0.8
#> 79 2.00 5 0.8
#> 80 10.00 5 0.8
#> 81 0.50 8 0.8
#> 82 0.75 8 0.8
#> 83 1.00 8 0.8
#> 84 2.00 8 0.8
#> 85 10.00 8 0.8
#> 86 0.50 11 0.8
#> 87 0.75 11 0.8
#> 88 1.00 11 0.8
#> 89 2.00 11 0.8
#> 90 10.00 11 0.8
#> 91 0.50 14 0.8
#> 92 0.75 14 0.8
#> 93 1.00 14 0.8
#> 94 2.00 14 0.8
#> 95 10.00 14 0.8
#> 96 0.50 50 0.8
#> 97 0.75 50 0.8
#> 98 1.00 50 0.8
#> 99 2.00 50 0.8
#> 100 10.00 50 0.8
#> 101 0.50 5 0.9
#> 102 0.75 5 0.9
#> 103 1.00 5 0.9
#> 104 2.00 5 0.9
#> 105 10.00 5 0.9
#> 106 0.50 8 0.9
#> 107 0.75 8 0.9
#> 108 1.00 8 0.9
#> 109 2.00 8 0.9
#> 110 10.00 8 0.9
#> 111 0.50 11 0.9
#> 112 0.75 11 0.9
#> 113 1.00 11 0.9
#> 114 2.00 11 0.9
#> 115 10.00 11 0.9
#> 116 0.50 14 0.9
#> 117 0.75 14 0.9
#> 118 1.00 14 0.9
#> 119 2.00 14 0.9
#> 120 10.00 14 0.9
#> 121 0.50 50 0.9
#> 122 0.75 50 0.9
#> 123 1.00 50 0.9
#> 124 2.00 50 0.9
#> 125 10.00 50 0.9
#> 126 0.50 5 1.0
#> 127 0.75 5 1.0
#> 128 1.00 5 1.0
#> 129 2.00 5 1.0
#> 130 10.00 5 1.0
#> 131 0.50 8 1.0
#> 132 0.75 8 1.0
#> 133 1.00 8 1.0
#> 134 2.00 8 1.0
#> 135 10.00 8 1.0
#> 136 0.50 11 1.0
#> 137 0.75 11 1.0
#> 138 1.00 11 1.0
#> 139 2.00 11 1.0
#> 140 10.00 11 1.0
#> 141 0.50 14 1.0
#> 142 0.75 14 1.0
#> 143 1.00 14 1.0
#> 144 2.00 14 1.0
#> 145 10.00 14 1.0
#> 146 0.50 50 1.0
#> 147 0.75 50 1.0
#> 148 1.00 50 1.0
#> 149 2.00 50 1.0
#> 150 10.00 50 1.0
#> 151 0.50 5 5.0
#> 152 0.75 5 5.0
#> 153 1.00 5 5.0
#> 154 2.00 5 5.0
#> 155 10.00 5 5.0
#> 156 0.50 8 5.0
#> 157 0.75 8 5.0
#> 158 1.00 8 5.0
#> 159 2.00 8 5.0
#> 160 10.00 8 5.0
#> 161 0.50 11 5.0
#> 162 0.75 11 5.0
#> 163 1.00 11 5.0
#> 164 2.00 11 5.0
#> 165 10.00 11 5.0
#> 166 0.50 14 5.0
#> 167 0.75 14 5.0
#> 168 1.00 14 5.0
#> 169 2.00 14 5.0
#> 170 10.00 14 5.0
#> 171 0.50 50 5.0
#> 172 0.75 50 5.0
#> 173 1.00 50 5.0
#> 174 2.00 50 5.0
#> 175 10.00 50 5.0
createsrch(1, 1, 1)
#> mos yrs flo
#> 1 1 1 1