how numpy.transpose implementation

The numpy.transpose() function is implemented in C language. Here is the basic algorithm:

1. Check the input array’s dimensionality, and raise an error if it is not a 1D or 2D array.
2. If the input array is a 1D array, return the same array (no transpose required).
3. If the input array is a 2D array, create a new empty 2D array with the shape (n, m), where n and m are the number of rows and columns of the input array, respectively.
4. Loop through the input array’s rows and columns, and copy the corresponding elements to the new array in transposed positions.
5. Return the transposed array.

Here is an example C code that implements the numpy.transpose() function:

#include <stdlib.h>
#include <stdio.h>

void transpose(double *in_array, double *out_array, int rows, int cols) {
    int i, j;
    for (i=0; i<rows; i++) {
        for (j=0; j<cols; j++) {
            out_array[j*rows+i] = in_array[i*cols+j];
        }
    }
}

int main() {
    double in_array[3][2] = {{1, 2}, {3, 4}, {5, 6}};
    double out_array[2][3];
    transpose(&in_array[0][0], &out_array[0][0], 3, 2);
    int i, j;
    for (i=0; i<2; i++) {
        for (j=0; j<3; j++) {
            printf("%f ", out_array[i][j]);
        }
        printf("\n");
    }
    return 0;
}

In this example, the input array is a 3x2 matrix, and the output array is a 2x3 matrix. The transpose() function takes the input array, the output array, the number of rows, and the number of columns as arguments, and returns the transposed array in the output array. The function uses two nested loops to copy the elements of the input array to the output array in transposed positions.