Try "1i" -
y = randn(100, "like", 1i)
y =
Columns 1 through 10
1.0733 - 1.4141i -1.0336 - 0.1949i -0.8775 - 0.8478i 0.8356 + 0.7767i -0.6008 + 0.2024i -0.1514 - 0.0743i -0.2567 + 0.4227i 0.6336 + 1.1556i 0.8667 - 0.3602i -0.0557 + 0.1675i
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0.8905 + 0.3052i 1.4260 + 0.5499i -1.2288 - 0.5602i -1.0182 - 1.2177i 0.5471 - 0.0765i 0.1710 - 0.2722i 0.3659 - 0.8205i 0.6900 - 0.6191i -0.6429 - 0.5465i 0.1317 - 0.2566i
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0.6379 - 0.1877i 0.3414 + 0.4565i 1.6880 - 0.4068i -0.5710 - 1.6582i -0.1826 - 0.2503i 0.7691 - 1.3435i -0.7830 - 0.1392i 0.8096 - 0.2699i -1.3548 + 0.7242i 0.5474 - 1.9183i
0.3780 + 0.4836i -1.3521 + 0.6285i -1.0071 + 0.7769i 1.3005 + 0.7291i 0.6153 + 0.5437i 0.1457 + 0.5867i -0.1921 + 0.1376i 0.3061 + 0.3527i 0.2051 + 0.0071i 0.3127 + 0.7793i
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Columns 11 through 20
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Columns 31 through 40
-0.0023 + 1.7490i 0.2812 + 0.2990i -1.4350 - 0.6706i -0.2208 - 0.3708i -0.6512 - 0.6524i -0.6634 - 0.0213i 0.0117 - 0.2162i -0.6993 - 0.8206i -0.0552 - 0.3121i -0.2299 + 0.3355i
-0.1556 - 0.3251i -0.4916 + 0.1237i 0.4912 + 0.8545i -0.8544 + 1.0294i 0.5468 - 0.5134i -0.4351 - 0.7408i 0.0505 + 0.6684i 0.5833 + 1.3155i 0.6181 - 0.8611i 0.4289 + 0.2886i
-0.9622 - 1.3822i 0.6677 + 0.8978i 1.0151 + 1.0783i 0.4615 + 0.6798i 0.8790 - 0.0806i -0.9110 + 0.9729i 0.0263 + 0.4468i 0.5740 - 0.6270i 0.9680 - 0.0785i 0.3403 + 0.3169i
-0.1025 + 1.3711i 0.6768 - 0.6870i -0.7342 + 0.7119i 0.1069 - 0.4496i -1.0157 - 0.4890i -0.4223 - 0.0771i 0.5661 - 0.1322i 0.6479 + 0.4056i 0.8084 + 0.7242i -0.4771 - 0.7981i
0.5319 + 0.2473i 0.5066 + 0.3656i -0.0205 - 0.0009i 1.0371 - 0.3650i 0.9233 + 0.4095i -0.2398 + 1.0514i 0.5679 - 0.3576i 0.1902 - 1.0941i -0.6499 + 0.1064i -0.7455 - 0.8607i
0.2829 + 0.0878i 1.0871 + 0.2288i 1.2575 - 0.3444i 0.1804 + 0.4439i 0.6616 + 0.1234i 0.2652 - 0.3781i 0.2266 + 1.1256i 1.1907 - 0.4993i 0.4293 + 0.0001i 0.4026 - 0.9612i
0.4982 + 0.8677i -1.7185 - 0.2485i 0.0057 + 0.5742i 0.6947 - 1.1111i -1.0000 - 0.1284i 0.3623 - 1.2017i -0.0430 + 0.1113i 1.6230 - 1.5218i 2.0805 + 0.4117i 1.1924 + 0.7540i
-0.7078 + 0.5212i 0.7405 + 0.8593i -0.1637 + 0.0507i -1.0357 + 1.0083i -0.9693 - 0.2010i -0.0568 + 0.9119i 0.2590 - 0.6759i 1.2227 + 1.9600i -1.4554 - 0.0147i 0.6977 - 0.3534i
0.8763 - 0.4761i 0.6694 + 0.2827i -1.7575 + 0.3858i 0.1067 - 1.1505i -0.6653 + 0.0565i 0.2670 - 0.4363i 1.1289 - 1.4522i 0.1785 + 1.3165i -0.0086 + 0.4000i -0.3682 + 0.2435i
-0.0248 + 0.3247i 1.5708 + 0.8134i -0.4604 + 0.2687i 0.7200 - 0.1090i -0.0899 + 0.6769i 1.4576 + 0.0591i 0.1585 - 0.7068i -0.6248 - 0.3906i 0.2969 + 0.9088i 0.4230 - 0.9680i
-0.1318 - 1.0523i -0.9376 + 0.3466i -0.9577 - 0.0777i 0.4319 + 0.7599i 0.0332 + 0.6018i -1.0032 + 1.0795i -0.1179 + 0.8524i 0.0458 - 0.7234i 0.2247 - 0.1688i 0.3860 - 0.0316i
0.0233 - 0.4894i 0.6851 + 0.4854i 0.0416 + 2.3245i 0.6899 + 0.4911i -0.8680 + 0.1964i 0.7907 - 0.0567i 0.8257 + 1.4064i 0.2563 + 0.2285i -0.2525 + 0.0008i -1.8759 + 0.0429i
0.2480 - 0.4110i 0.2936 + 0.5493i 0.8553 - 0.1071i -0.1968 - 0.1427i -1.2295 - 0.7591i -1.0565 - 0.7473i -0.1557 + 1.7628i -1.1336 + 0.1594i 0.0679 + 0.0918i -1.5155 + 0.4116i