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numba用户手册

5.1.@cfunc                                             # 创建C/C++回调函数;还公开了ctypes指向该回调的回调对象-------------------------------------------------------------------------------------------------------------- #实例1.1：from numba import cfunc@cfunc("float64(float64, float64)")def add(x, y):    return x + yprint(add.ctypes(4.0, 5.0))                      # prints "9.0"--------------------------------------------------------------------------------------------------------------  #实例1.2：import numpy as npfrom numba import cfuncdef fun(t):                                                # 纯Python函数    return np.exp(-t) / t**2nb_fun = cfunc("float64(float64)")(fun)# 将其编译为C回调# 将nb_fun对象的ctypes回调传递给scipy.integrate.quad并检查结果是否与纯Python函数相同import scipy.integrate as sidef run_fun(func):    return si.quad(func, 1, np.inf)             # 接受常规Python回调或包装在ctypes回调对象中的C回调run_fun(fun)                                            # (0.14849550677592208, 3.8736750296130505e-10)run_fun(nb_fun.ctypes)                           # (0.14849550677592208, 3.8736750296130505e-10)-------------------------------------------------------------------------------------------------------------- 5.2.指针和阵列存储器处理# 实例2.1：实现回调：void(double *input, double *output, int m, int n)调用传递C数组from numba import cfunc, types, carrayc_sig = types.void(types.CPointer(types.double),types.CPointer(types.double),types.intc, types.intc)@cfunc(c_sig)def my_callback(in_, out_, m, n):    in_array = carray(in_, (m, n))    out_array = carray(out_, (m, n))        for i in range(m):        for j in range(n):            out_array[i, j] = 2 * in_array[i, j]--------------------------------------------------------------------------------------------------------------  # 实例2.2：处理C结构# numba可将cffi类型转换为numba Record类型 numba.cffi_support.map_type：from numba import cffi_supportfrom cffi import FFIsrc = """/* Define the C struct */typedef struct my_struct {   int    i1;   float  f2;   double d3;   float  af4[7];                                         // arrays are supported} my_struct;/* Define a callback function */typedef double (*my_func)(my_struct*, size_t);"""ffi = FFI()ffi.cdef(src)# Get the function signature from *my_func*sig = cffi_support.map_type(ffi.typeof('my_func'),                        use_record_dtype=True)#True是必需否则返回指向C结构的指针作为void指针# Make the cfuncfrom numba import cfunc, carray@cfunc(sig)def foo(ptr, n):    base = carray(ptr, n)                          # view pointer as an array of my_struct    tmp = 0    for i in range(n):        tmp += base[i].i1 * base[i].f2 / base[i].d3        tmp += base[i].af4.sum()              # nested arrays are like normal numpy array    return tmp--------------------------------------------------------------------------------------------------------------  # 实例2.3：                                             # 用nb.types.Record.make_c_struct可手动创建遵循C-结构的布局my_struct = types.Record.make_c_struct([    # Provides a sequence of 2-tuples i.e. (name:str, type:Type)    ('i1', types.int32),    ('f2', types.float32),    ('d3', types.float64),    ('af4', types.NestedArray(dtype=types.float32, shape=(7,))),])--------------------------------------------------------------------------------------------------------------

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