\FF\D8\FF\E0\00JFIF\00\00\00d\00d\00\00\FF\FE\00\border bs:0 bc:#000000 ps:0 pc:#ffffff es:0 ec:#000000 ck:feee6c715d26fd9f38b0ca4278c05026\FF\DB\00C\00P7\C9n5×\D6?\BDê\9Ds\EBp\9F[`8m\B7)o\B5\E8\E6I\99\FE3]]A2\BA\8Cw\D6E\93\\DEv\C8\009\F2\F1NI?uc\\F5\EA\96k\xN<~buv\EA\C8\D7 \8B\84\CEcxI\BBg\AE\9E=\D6+n\EC\80\C8A\8C\AE\EB\CF\D5\DA\E9"2\A4\B9j5\EB\F3W\B63\96\B30Yu\DA\FC8\ED\DF\E7Ms\FB\F1\8E\B3\FA\EA\E8\E6(\883zs\F2_\8DFk\8Bh \00\8C\DCw\D3R\B5+6X\BA\B2\C4j\AB0\B4\FCMw\C2I\8E\9B\E3\A9~9u\FA\D3l\80\C8%p\EE\FDn2€ \00 $\FEj\C4e\A9\DB\~\95\A7\A5\80EK\BB\8DDsP\00@@AD'k\CF\E8\DB\D2(\80\9AK\D3\85\D6lb\F2\BA\8C*\80\00)\95 59\A3R:\F3\CE"\B6\80\88\00\00i1u4ê\E9\F2á\A6\A2\FACM\93WMb*\E0*\00\00\00\00\00(\A8\80\00\00\80\00\00\00\00\00\00\00\00\00\FF\D9 C/// import sys import numpy as np f2: np.float16 f8: np.float64 c8: np.complex64 # Construction np.float32(3j) # E: incompatible type # Technically the following examples are valid NumPy code. But they # are not considered a best practice, and people who wish to use the # stubs should instead do # # np.array([1.0, 0.0, 0.0], dtype=np.float32) # np.array([], dtype=np.complex64) # # See e.g. the discussion on the mailing list # # https://mail.python.org/pipermail/numpy-discussion/2020-April/080566.html # # and the issue # # https://github.com/numpy/numpy-stubs/issues/41 # # for more context. np.float32([1.0, 0.0, 0.0]) # E: incompatible type np.complex64([]) # E: incompatible type np.complex64(1, 2) # E: Too many arguments # TODO: protocols (can't check for non-existent protocols w/ __getattr__) np.datetime64(0) # E: No overload variant class A: def __float__(self): return 1.0 np.int8(A()) # E: incompatible type np.int16(A()) # E: incompatible type np.int32(A()) # E: incompatible type np.int64(A()) # E: incompatible type np.uint8(A()) # E: incompatible type np.uint16(A()) # E: incompatible type np.uint32(A()) # E: incompatible type np.uint64(A())