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Function masked_outside

numpy/ma/core.py:2152–2189  ·  view source on GitHub ↗

Mask an array outside a given interval. Shortcut to ``masked_where``, where `condition` is True for `x` outside the interval [v1,v2] (x < v1)|(x > v2). The boundaries `v1` and `v2` can be given in either order. See Also -------- masked_where : Mask where a condition is

(x, v1, v2, copy=True)

Source from the content-addressed store, hash-verified

2150
2151
2152def masked_outside(x, v1, v2, copy=True):
2153 """
2154 Mask an array outside a given interval.
2155
2156 Shortcut to ``masked_where``, where `condition` is True for `x` outside
2157 the interval [v1,v2] (x < v1)|(x > v2).
2158 The boundaries `v1` and `v2` can be given in either order.
2159
2160 See Also
2161 --------
2162 masked_where : Mask where a condition is met.
2163
2164 Notes
2165 -----
2166 The array `x` is prefilled with its filling value.
2167
2168 Examples
2169 --------
2170 >>> import numpy.ma as ma
2171 >>> x = [0.31, 1.2, 0.01, 0.2, -0.4, -1.1]
2172 >>> ma.masked_outside(x, -0.3, 0.3)
2173 masked_array(data=[--, --, 0.01, 0.2, --, --],
2174 mask=[ True, True, False, False, True, True],
2175 fill_value=1e+20)
2176
2177 The order of `v1` and `v2` doesn&#x27;t matter.
2178
2179 >>> ma.masked_outside(x, 0.3, -0.3)
2180 masked_array(data=[--, --, 0.01, 0.2, --, --],
2181 mask=[ True, True, False, False, True, True],
2182 fill_value=1e+20)
2183
2184 """
2185 if v2 < v1:
2186 (v1, v2) = (v2, v1)
2187 xf = filled(x)
2188 condition = (xf < v1) | (xf > v2)
2189 return masked_where(condition, x, copy=copy)
2190
2191
2192def masked_object(x, value, copy=True, shrink=True):

Callers 2

test_testOddFeaturesMethod · 0.90

Calls 2

filledFunction · 0.85
masked_whereFunction · 0.85

Tested by 2

test_testOddFeaturesMethod · 0.72