{"id":27530,"date":"2022-08-14T14:27:20","date_gmt":"2022-08-14T08:57:20","guid":{"rendered":"https:\/\/python-programs.com\/?p=27530"},"modified":"2022-08-14T14:27:20","modified_gmt":"2022-08-14T08:57:20","slug":"python-numpy-matrix-diagonal-function","status":"publish","type":"post","link":"https:\/\/python-programs.com\/python-numpy-matrix-diagonal-function\/","title":{"rendered":"Python Numpy matrix.diagonal() Function"},"content":{"rendered":"
NumPy Library\u00a0<\/strong><\/p>\n NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import it into our program and then we can easily use the functionality of NumPy in our program.<\/p>\n NumPy is a Python library that is frequently used for scientific and statistical analysis. NumPy arrays are grids of the same datatype\u2019s values.<\/p>\n Numpy matrix.diagonal() Function:<\/strong><\/p>\n We can find a diagonal element from a given matrix using the Numpy matrix.diagonal() method, which returns a one-dimensional matrix as output.<\/p>\n Syntax:<\/strong><\/p>\n Return Value:<\/strong><\/p>\n The diagonal element of a given matrix is returned by the diagonal() function.<\/p>\n For 2-Dimensional (2D) Matrix<\/strong><\/p>\n Approach:<\/strong><\/p>\n Below is the implementation:<\/strong><\/p>\n Output:<\/strong><\/p>\n For 3-Dimensional (3D) Matrix<\/strong><\/p>\n Approach:<\/strong><\/p>\n Below is the implementation:<\/strong><\/p>\n Output:<\/strong><\/p>\n NumPy Library\u00a0 NumPy is a library in python that is created to work efficiently with arrays in python. It is fast, easy to learn, and provides efficient storage. It also provides a better way of handling data for the process. We can create an n-dimensional array in NumPy. To use NumPy simply have to import …<\/p>\n matrix.diagonal()<\/pre>\n
Numpy matrix.diagonal() Function in Python<\/h2>\n
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# Import numpy module using the import keyword\r\nimport numpy as np\r\n \r\n# Create a matrix(2-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 2D matrix as an argument to it and store it in a variable\r\ngvn_matrx = np.matrix('[2, 1; 6, 3]')\r\n \r\n# Apply diagonal() function on the given matrix to get all the diagonal elements of a given matrix.\r\n# Store it in another variable\r\nrslt = gvn_matrx.diagonal()\r\n# Print all the diagonal elements of a given matrix.\r\nprint(\"The diagonal elements of a given matrix:\")\r\nprint(rslt)<\/pre>\n
The diagonal elements of a given matrix:\r\n[[2 3]]<\/pre>\n
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# Import numpy module using the import keyword\r\nimport numpy as np\r\n \r\n# Create a matrix(3-Dimensional) using the matrix() function of numpy module by passing \r\n# some random 3D matrix as an argument to it and store it in a variable\r\ngvn_matrx = np.matrix('[2, 4, 1; 8, 7, 3; 10, 9, 5]')\r\n \r\n# Apply diagonal() function on the given matrix to get all the diagonal elements of a given matrix.\r\n# Store it in another variable\r\nrslt = gvn_matrx.diagonal()\r\n# Print all the diagonal elements of a given matrix.\r\nprint(\"The diagonal elements of a given matrix:\")\r\nprint(rslt)<\/pre>\n
The diagonal elements of a given matrix:\r\n[[2 7 5]]<\/pre>\n","protected":false},"excerpt":{"rendered":"