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test_fancy_indexing.nim
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test_fancy_indexing.nim
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# Copyright 2017-2020 Mamy André-Ratsimbazafy
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import ../../src/arraymancer
import unittest
suite "Fancy indexing":
# x = np.array([[ 4, 99, 2],
# [ 3, 4, 99],
# [ 1, 8, 7],
# [ 8, 6, 8]])
let x = [[ 4, 99, 2],
[ 3, 4, 99],
[ 1, 8, 7],
[ 8, 6, 8]].toTensor()
test "Index selection via fancy indexing":
block: # print(x[:, [0, 2]])
let r = x[_, [0, 2]]
let exp = [[ 4, 2],
[ 3, 99],
[ 1, 7],
[ 8, 8]].toTensor()
check: r == exp
block: # print(x[[1, 3], :])
let r = x[[1, 3], _]
let exp = [[3, 4, 99],
[8, 6, 8]].toTensor()
check: r == exp
test "Masked selection via fancy indexing":
block:
let r = x[x >. 50]
let exp = [99, 99].toTensor()
check: r == exp
block:
let r = x[x <. 50]
let exp = [4, 2, 3, 4, 1, 8, 7, 8, 6, 8].toTensor()
check: r == exp
test "Masked axis selection via fancy indexing":
block: # print('x[:, np.sum(x, axis = 0) > 50]')
let r = x[_, x.sum(axis = 0) >. 50]
let exp = [[99, 2],
[ 4, 99],
[ 8, 7],
[ 6, 8]].toTensor()
check: r == exp
block: # print('x[np.sum(x, axis = 1) > 50, :]')
let r = x[x.sum(axis = 1) >. 50, _]
let exp = [[4, 99, 2],
[3, 4, 99]].toTensor()
check: r == exp