python/pycubool/matrix.py
def transpose(self, time_check=False):
        """
        Creates new transposed `self` matrix.

        >>> a = Matrix.from_lists((4, 4), [0, 1, 2, 3], [0, 1, 2, 0], is_sorted=True, no_duplicates=True)
        >>> b = a.transpose()
        >>> print(a, b, sep="")
        '
                0   1   2   3
          0 |   1   .   .   . |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   1   .   .   . |   3
                0   1   2   3
                0   1   2   3
          0 |   1   .   .   1 |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   .   .   .   . |   3
                0   1   2   3
        '

        :param time_check: Pass True to measure and log elapsed time of the operation
        :return: New matrix instance with `self` transposed data
        """

        shape = (self.ncols, self.nrows)
        out = Matrix.empty(shape)

        status = wrapper.loaded_dll.cuBool_Matrix_Transpose(
            out.hnd,
            self.hnd,
            ctypes.c_uint(bridge.get_transpose_hints(time_check=time_check))
        )

        bridge.check(status)
        return out

        Creates new transposed `self` matrix.

        >>> a = Matrix.from_lists((4, 4), [0, 1, 2, 3], [0, 1, 2, 0], is_sorted=True, no_duplicates=True)
        >>> b = a.transpose()
        >>> print(a, b, sep="")
        '
                0   1   2   3
          0 |   1   .   .   . |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   1   .   .   . |   3
                0   1   2   3
                0   1   2   3
          0 |   1   .   .   1 |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   .   .   .   . |   3
                0   1   2   3
        '

        :param time_check: Pass True to measure and log elapsed time of the operation
        :return: New matrix instance with `self` transposed data
        
Creates new transposed `self` matrix.
Creates new transposed ` self ` matrix .
def transpose(self, time_check=False):
        shape = (self.ncols, self.nrows)
        out = Matrix.empty(shape)
        status = wrapper.loaded_dll.cuBool_Matrix_Transpose(
            out.hnd,
            self.hnd,
            ctypes.c_uint(bridge.get_transpose_hints(time_check=time_check))
        )
        bridge.check(status)
        return out
def transpose ( self , time_check = False ) : shape = ( self . ncols , self . nrows ) out = Matrix . empty ( shape ) status = wrapper . loaded_dll . cuBool_Matrix_Transpose ( out . hnd , self . hnd , ctypes . c_uint ( bridge . get_transpose_hints ( time_check = time_check ) ) ) bridge . check ( status ) return out
Creates new transposed `self` matrix.
Creates new transposed ` self ` matrix .
"""
        Creates new transposed `self` matrix.

        >>> a = Matrix.from_lists((4, 4), [0, 1, 2, 3], [0, 1, 2, 0], is_sorted=True, no_duplicates=True)
        >>> b = a.transpose()
        >>> print(a, b, sep="")
        '
                0   1   2   3
          0 |   1   .   .   . |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   1   .   .   . |   3
                0   1   2   3
                0   1   2   3
          0 |   1   .   .   1 |   0
          1 |   .   1   .   . |   1
          2 |   .   .   1   . |   2
          3 |   .   .   .   . |   3
                0   1   2   3
        '

        :param time_check: Pass True to measure and log elapsed time of the operation
        :return: New matrix instance with `self` transposed data
        """
New matrix instance with `self` transposed data
New matrix instance with ` self ` transposed data
self
time_check
Pass True to measure and log elapsed time of the operation
Pass True to measure and log elapsed time of the operation