Mask an array inside a given interval. Shortcut to ``masked_where``, where `condition` is True for `x` inside the interval [v1,v2] (v1 <= x <= v2). The boundaries `v1` and `v2` can be given in either order. See Also -------- masked_where : Mask where a condition is me
(x, v1, v2, copy=True)
| 2110 | |
| 2111 | |
| 2112 | def masked_inside(x, v1, v2, copy=True): |
| 2113 | """ |
| 2114 | Mask an array inside a given interval. |
| 2115 | |
| 2116 | Shortcut to ``masked_where``, where `condition` is True for `x` inside |
| 2117 | the interval [v1,v2] (v1 <= x <= v2). The boundaries `v1` and `v2` |
| 2118 | can be given in either order. |
| 2119 | |
| 2120 | See Also |
| 2121 | -------- |
| 2122 | masked_where : Mask where a condition is met. |
| 2123 | |
| 2124 | Notes |
| 2125 | ----- |
| 2126 | The array `x` is prefilled with its filling value. |
| 2127 | |
| 2128 | Examples |
| 2129 | -------- |
| 2130 | >>> import numpy.ma as ma |
| 2131 | >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1] |
| 2132 | >>> ma.masked_inside(x, -0.3, 0.3) |
| 2133 | masked_array(data=[0.31, 1.2, --, --, -0.4, -1.1], |
| 2134 | mask=[False, False, True, True, False, False], |
| 2135 | fill_value=1e+20) |
| 2136 | |
| 2137 | The order of `v1` and `v2` doesn't matter. |
| 2138 | |
| 2139 | >>> ma.masked_inside(x, 0.3, -0.3) |
| 2140 | masked_array(data=[0.31, 1.2, --, --, -0.4, -1.1], |
| 2141 | mask=[False, False, True, True, False, False], |
| 2142 | fill_value=1e+20) |
| 2143 | |
| 2144 | """ |
| 2145 | if v2 < v1: |
| 2146 | (v1, v2) = (v2, v1) |
| 2147 | xf = filled(x) |
| 2148 | condition = (xf >= v1) & (xf <= v2) |
| 2149 | return masked_where(condition, x, copy=copy) |
| 2150 | |
| 2151 | |
| 2152 | def masked_outside(x, v1, v2, copy=True): |