matrix(data, dtype=None, copy=True) .. note:: It is no longer recommended to use this class, even for linear algebra. Instead use regular arrays. The class may be removed in the future. Returns a matrix from an array-like object, or from a string of data.
| 72 | |
| 73 | @set_module('numpy') |
| 74 | class matrix(N.ndarray): |
| 75 | """ |
| 76 | matrix(data, dtype=None, copy=True) |
| 77 | |
| 78 | .. note:: It is no longer recommended to use this class, even for linear |
| 79 | algebra. Instead use regular arrays. The class may be removed |
| 80 | in the future. |
| 81 | |
| 82 | Returns a matrix from an array-like object, or from a string of data. |
| 83 | A matrix is a specialized 2-D array that retains its 2-D nature |
| 84 | through operations. It has certain special operators, such as ``*`` |
| 85 | (matrix multiplication) and ``**`` (matrix power). |
| 86 | |
| 87 | Parameters |
| 88 | ---------- |
| 89 | data : array_like or string |
| 90 | If `data` is a string, it is interpreted as a matrix with commas |
| 91 | or spaces separating columns, and semicolons separating rows. |
| 92 | dtype : data-type |
| 93 | Data-type of the output matrix. |
| 94 | copy : bool |
| 95 | If `data` is already an `ndarray`, then this flag determines |
| 96 | whether the data is copied (the default), or whether a view is |
| 97 | constructed. |
| 98 | |
| 99 | See Also |
| 100 | -------- |
| 101 | array |
| 102 | |
| 103 | Examples |
| 104 | -------- |
| 105 | >>> a = np.matrix('1 2; 3 4') |
| 106 | >>> a |
| 107 | matrix([[1, 2], |
| 108 | [3, 4]]) |
| 109 | |
| 110 | >>> np.matrix([[1, 2], [3, 4]]) |
| 111 | matrix([[1, 2], |
| 112 | [3, 4]]) |
| 113 | |
| 114 | """ |
| 115 | __array_priority__ = 10.0 |
| 116 | def __new__(subtype, data, dtype=None, copy=True): |
| 117 | warnings.warn('the matrix subclass is not the recommended way to ' |
| 118 | 'represent matrices or deal with linear algebra (see ' |
| 119 | 'https://docs.scipy.org/doc/numpy/user/' |
| 120 | 'numpy-for-matlab-users.html). ' |
| 121 | 'Please adjust your code to use regular ndarray.', |
| 122 | PendingDeprecationWarning, stacklevel=2) |
| 123 | if isinstance(data, matrix): |
| 124 | dtype2 = data.dtype |
| 125 | if (dtype is None): |
| 126 | dtype = dtype2 |
| 127 | if (dtype2 == dtype) and (not copy): |
| 128 | return data |
| 129 | return data.astype(dtype) |
| 130 | |
| 131 | if isinstance(data, N.ndarray): |
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