我在将 numpy 矩阵转换为具有本机类型的 Julia 数组时遇到了一些困难。所以这是我的问题：我有一个代码，它返回一个 numpy 矩阵，前 73 列是 bool，表示特征数组，最后一列是与特征向量相关的概率。
B = np.ndarray((10,74),dtype = object)
B[:,0:73] = int(0)
B[:,-1] = float(0)
我有一个 Julia 代码可以调用和接收这个 numpy 矩阵
using PyCall
push!(pyimport("sys")["path"], pwd());
a = pyimport("main")
t = a.analyze()
但是我的变量 t 是一个 PyObject 数组，我想将整个数组转换为具有本机类型（bool 和 flop）。因为我将在 JuMP 模块中使用这些变量。
10×74 Array{PyObject,2}:
PyObject True PyObject False PyObject True PyObject False PyObject False … PyObject False PyObject False PyObject 0.4842317916002127
PyObject True PyObject False PyObject True PyObject False PyObject False PyObject False PyObject False PyObject 0.4077830940988835
PyObject True PyObject False PyObject True PyObject False PyObject False PyObject False PyObject False PyObject 0.4134680134680136
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.8565891472868217
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.4753872053872055
PyObject True PyObject False PyObject True PyObject True PyObject False … PyObject False PyObject False PyObject 0.5216037930323644
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.5216037930323644
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.4775252525252527
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.47481481481481497
PyObject True PyObject False PyObject True PyObject True PyObject False PyObject False PyObject False PyObject 0.5277056277056278