NumPy NumPy参考

• 数组对象
• 常数
• 通用功能（ufunc）
• 例行程序
•    数组创建例程
•    数组操作例程
•    Binary operations
•    String operations
•    C-Types Foreign Function Interface (numpy.ctypeslib)
•    Datetime Support Functions
•    Data type routines
•    Optionally Scipy-accelerated routines (numpy.dual)
•    Mathematical functions with automatic domain (numpy.emath)
•    Floating point error handling
•    Discrete Fourier Transform (numpy.fft)
•    Financial functions
•    Functional programming
•    NumPy-specific help functions
•    Indexing routines
•    输入输出
•    线性代数（numpy.linalg）
•    逻辑功能
•    Mathematical functions
•          numpy.sin
•          numpy.cos
•          numpy.tan
•          numpy.arcsin
•          numpy.arccos
•          numpy.arctan
•          numpy.hypot
•          numpy.arctan2
•          numpy.degrees
•          numpy.radians
•          numpy.unwrap
•          numpy.deg2rad
•          numpy.rad2deg
•          numpy.sinh
•          numpy.cosh
•          numpy.tanh
•          numpy.arcsinh
•          numpy.arccosh
•          numpy.arctanh
•          numpy.around
•          numpy.round_
•          numpy.rint
•          numpy.fix
•          numpy.floor
•          numpy.ceil
•          numpy.trunc
•          numpy.prod
•          numpy.sum
•          numpy.nanprod
•          numpy.nansum
•          numpy.cumprod
•          numpy.cumsum
•          numpy.nancumprod
•          numpy.nancumsum
•          numpy.diff
•          numpy.ediff1d
•          numpy.gradient
•          numpy.cross
•          numpy.trapz
•          numpy.exp
•          numpy.expm1
•          numpy.exp2
•          numpy.log
•          numpy.log10
•          numpy.log2
•          numpy.log1p
•          numpy.logaddexp
•          numpy.logaddexp2
•          numpy.i0
•          numpy.sinc
•          numpy.signbit
•          numpy.copysign
•          numpy.frexp
•          numpy.ldexp
•          numpy.nextafter
•          numpy.spacing
•          numpy.lcm
•          numpy.gcd
•          numpy.add
•          numpy.reciprocal
•          numpy.positive
•          numpy.negative
•          numpy.multiply
•          numpy.divide
•          numpy.power
•          numpy.subtract
•          numpy.true_divide
•          numpy.floor_divide
•          numpy.float_power
•          numpy.fmod
•          numpy.mod
•          numpy.modf
•          numpy.remainder
•          numpy.divmod
•          numpy.angle
•          numpy.real
•          numpy.imag
•          numpy.conj
•          numpy.conjugate
•          numpy.convolve
•          numpy.clip
•          numpy.sqrt
•          numpy.cbrt
•          numpy.square
•          numpy.absolute
•          numpy.fabs
•          numpy.sign
•          numpy.heaviside
•          numpy.maximum
•          numpy.minimum
•          numpy.fmax
•          numpy.fmin
•          numpy.nan_to_num
•          numpy.real_if_close
•          numpy.interp
•    Matrix library (numpy.matlib)
•    Miscellaneous routines
•    Padding Arrays
•    Polynomials
•    Random sampling (numpy.random)
•    Set routines
•    Sorting, searching, and counting
•    Statistics
•    Test Support (numpy.testing)
•    Window functions
• Packaging (numpy.distutils)
• NumPy Distutils - Users Guide
• NumPy C-API
• NumPy内部
• NumPy和SWIG

numpy.real（val ）[源代码] ¶

返回复杂参数的实部。

参量

val array_like

输入数组。

退货

输出ndarray或标量

复杂参数的实际组成部分。如果VAL是真实的类型，VAL用于输出。如果val具有复杂元素，则返回的类型为float。

也可以看看

real_if_close，imag，angle

例子

>>> a = np.array([1+2j, 3+4j, 5+6j])
>>> a.real
array([1.,  3.,  5.])
>>> a.real = 9
>>> a
array([9.+2.j,  9.+4.j,  9.+6.j])
>>> a.real = np.array([9, 8, 7])
>>> a
array([9.+2.j,  8.+4.j,  7.+6.j])
>>> np.real(1 + 1j)
1.0