int_ = long intp = long int64 = long int0 = long class long(signedinteger): """ 64-bit integer. Character code 'l'. Python int compatible. """ pass 补充:复数的概念 我们把形如 z=a+bi(a, b均为实数)的数称为复数,其中 a 称为实部,b 称为虚部,i 称为虚数单位。当虚部 b=0 时,...
NumPy 提供numpy.iinfo并numpy.finfo分别验证 NumPy 整数和浮点值的最小值或最大值 >>> np.iinfo(int) # Bounds of the default integer on this system. iinfo(min=-9223372036854775808, max=9223372036854775807, dtype=int64) >>> np.iinfo(np.int32) # Bounds of a 32-bit integer iinfo(min=-214748364...
dtype的类型有: np.int64#Signed 64-bit integer typesnp.float32#Standard double-precision floating pointnp.complex#Complex numbers represented by 128 floatsnp.bool#Boolean type storing TRUE and FALSE valuesnp.object#Python object typenp.string_#Fixed-length string typenp.unicode_#Fixed-length unicode...
Integer large enough to hold a pointer np.float32 float np.float64 / np.float_ double Note that this matches the precision of the builtin python float. np.complex64 float complex Complex number, represented by two 32-bit floats (real and imaginary components) np.complex128 / np.complex_ ...
integer) True >>> np.issubdtype(d, np.floating) False 数据溢出 一般来说,如果超出了数据的范围是会报异常的。比如我们有一个非常长的int值: In [38]: a= 1000000000000000000000000000000000000000000000000000000000000000000000000000000 In [39]: a Out[39]: ...
>>>dt = np.dtype(np.int32)# 32-bit integer>>>dt = np.dtype(np.complex128)# 128-bit complex floating-point number 通用类型 通用层次类型对象根据关联转换为相应类型对象: 自版本 1.19 起已弃用:通用标量类型的此转换已弃用。这是因为在arr.astype(dtype=np.floating)这样的上下文中可能会出现意外情况...
PCG64makes a guarantee that a fixed seed will always produce the same random integer stream. PCG-64是O’Neill置换同余发生器的128位实现 。 PCG-64的周期为2的128次方,并支持任意步骤的推进以及2的127次方个流。 我们使用PCG家族的特定成员PCG XSL RR 128/64,如文献[2]中所述。
np.uintpuintptr_tInteger large enough to hold a pointer np.float32float np.float64/np.float_doubleNote that this matches the precision of the builtin pythonfloat. np.complex64float complexComplex number, represented by two 32-bit floats (real and imaginary components) ...
This is likely the one that I'll be using most often, personally. The main downside is that it uses 128-bit integer arithmetic, which is emulated in C if the compiler does not provide such an integer type. The two main platforms for which this is the case are 32-bit CPUs and 64-bi...
data-type for integer and boolean data-type input arrays. (gh-26766) The type annotations of numpy.float64 and numpy.complex128 now reflect that they are also subtypes of the built-in float and complex types, respectively. This update prevents static type-checkers from reporting errors in case...