£Á°èZ¨Ä…–K§‚«“ô4“ÒÙ´dîfUÙÃÅ WKbyʦ•ꎅȮFÒ¿ÊÎóCozá¬S@6{Í:›œêZÌ:Š•_%:¢¾¾~;‘Ã~芩ÊǍí`ÔÑ©ú뙵'5I¿fš×WO%ø9¾«¾DK|€ùÍD”Ýs]nHÕ¶êםӼ㞪éUWŸÈË%DÒÕ¬ï‘]/Åcx ‰ï2ß]ä6G[]S£Ôϯrs{úëóµmÒï#UQxo·õÞCe]"±/aÙ&Eã4ú9Jé_ÞåëdãöKë)AÞ ¯¹ægƒÛowЍø^d™ý½ßB7áyMä9ÜÖUã !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! import numpy as np import numpy.typing as npt AR_f8: npt.NDArray[np.float64] # NOTE: Mypy bug presumably due to the special-casing of heterogeneous tuples; # xref numpy/numpy#20901 # # The expected output should be no different than, e.g., when using a # list instead of a tuple np.concatenate(([1], AR_f8)) # E: Argument 1 to "concatenate" has incompatible type