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Function argmax

numpy/core/fromnumeric.py:1141–1229  ·  view source on GitHub ↗

Returns the indices of the maximum values along an axis. Parameters ---------- a : array_like Input array. axis : int, optional By default, the index is into the flattened array, otherwise along the specified axis. out : array, optional If pr

(a, axis=None, out=None, *, keepdims=np._NoValue)

Source from the content-addressed store, hash-verified

1139
1140@array_function_dispatch(_argmax_dispatcher)
1141def argmax(a, axis=None, out=None, *, keepdims=np._NoValue):
1142 """
1143 Returns the indices of the maximum values along an axis.
1144
1145 Parameters
1146 ----------
1147 a : array_like
1148 Input array.
1149 axis : int, optional
1150 By default, the index is into the flattened array, otherwise
1151 along the specified axis.
1152 out : array, optional
1153 If provided, the result will be inserted into this array. It should
1154 be of the appropriate shape and dtype.
1155 keepdims : bool, optional
1156 If this is set to True, the axes which are reduced are left
1157 in the result as dimensions with size one. With this option,
1158 the result will broadcast correctly against the array.
1159
1160 .. versionadded:: 1.22.0
1161
1162 Returns
1163 -------
1164 index_array : ndarray of ints
1165 Array of indices into the array. It has the same shape as `a.shape`
1166 with the dimension along `axis` removed. If `keepdims` is set to True,
1167 then the size of `axis` will be 1 with the resulting array having same
1168 shape as `a.shape`.
1169
1170 See Also
1171 --------
1172 ndarray.argmax, argmin
1173 amax : The maximum value along a given axis.
1174 unravel_index : Convert a flat index into an index tuple.
1175 take_along_axis : Apply ``np.expand_dims(index_array, axis)``
1176 from argmax to an array as if by calling max.
1177
1178 Notes
1179 -----
1180 In case of multiple occurrences of the maximum values, the indices
1181 corresponding to the first occurrence are returned.
1182
1183 Examples
1184 --------
1185 >>> a = np.arange(6).reshape(2,3) + 10
1186 >>> a
1187 array([[10, 11, 12],
1188 [13, 14, 15]])
1189 >>> np.argmax(a)
1190 5
1191 >>> np.argmax(a, axis=0)
1192 array([1, 1, 1])
1193 >>> np.argmax(a, axis=1)
1194 array([2, 2])
1195
1196 Indexes of the maximal elements of a N-dimensional array:
1197
1198 >>> ind = np.unravel_index(np.argmax(a, axis=None), a.shape)

Callers

nothing calls this directly

Calls 1

_wrapfuncFunction · 0.85

Tested by

no test coverage detected