コード例 #1
0
        /// <summary>
        /// An array with ones at and below the given diagonal and zeros elsewhere.
        /// </summary>
        /// <param name="N">Number of rows in the array.</param>
        /// <param name="M">Number of columns in the array.</param>
        /// <param name="k">The sub-diagonal at and below which the array is filled.'k' = 0 is the main diagonal, while 'k' LT 0 is below it, and 'k' GT 0 is above.The default is 0.</param>
        /// <param name="dtype">Data type of the returned array.  The default is float.</param>
        /// <returns></returns>
        public static ndarray tri(int N, int?M = null, int k = 0, dtype dtype = null)
        {
            /*
             * An array with ones at and below the given diagonal and zeros elsewhere.
             *
             * Parameters
             * ----------
             * N : int
             *  Number of rows in the array.
             * M : int, optional
             *  Number of columns in the array.
             *  By default, `M` is taken equal to `N`.
             * k : int, optional
             *  The sub-diagonal at and below which the array is filled.
             *  `k` = 0 is the main diagonal, while `k` < 0 is below it,
             *  and `k` > 0 is above.  The default is 0.
             * dtype : dtype, optional
             *  Data type of the returned array.  The default is float.
             *
             * Returns
             * -------
             * tri : ndarray of shape (N, M)
             *  Array with its lower triangle filled with ones and zero elsewhere;
             *  in other words ``T[i,j] == 1`` for ``i <= j + k``, 0 otherwise.
             *
             * Examples
             * --------
             * >>> np.tri(3, 5, 2, dtype=int)
             * array([[1, 1, 1, 0, 0],
             *     [1, 1, 1, 1, 0],
             *     [1, 1, 1, 1, 1]])
             *
             * >>> np.tri(3, 5, -1)
             * array([[ 0.,  0.,  0.,  0.,  0.],
             *     [ 1.,  0.,  0.,  0.,  0.],
             *     [ 1.,  1.,  0.,  0.,  0.]])
             */

            if (dtype == null)
            {
                dtype = np.Float32;
            }

            if (M == null)
            {
                M = N;
            }


            ndarray m = ufunc.outer(UFuncOperation.greater_equal, np.Bool, arange(N, dtype: _min_int(0, N)),
                                    arange(-k, M - k, dtype: _min_int(-k, (int)M - k)));

            // Avoid making a copy if the requested type is already bool
            m = m.astype(dtype, copy: false);

            return(m);
        }