N-D array operations
- Create
- Properties
- Get
- Aggregate to scalar
- Aggregate along axis
- Map
- Shrink
- Reshape
- Convert
Create
| What | How | Details |
| Ensure at least 1D array | np.atleast_1d(x) | |
| Ensure at least 2D array | np.atleast_2d(x) | |
| Ensure at least 3D array | np.atleast_3d(x) | |
Properties
| What | How | Details |
| Number of dimensions | x.ndim | |
| Dimension sizes | x.shape | |
| Size of the first dimension | len(x) | |
| Number of elements | x.size | |
Get
| What | How | Details | |—|—|—|
Aggregate to scalar
| What | How | Details |
| Sum of all elements | np.sum(a) | |
Aggregate along axis
| What | How | Details |
| Sum | np.sum(a, axis=ax) | |
Map
| What | How | Details |
| Cumulative sum along axis | np.cumsum(a, axis=ax) | |
Shrink
| What | How | Details |
| Drop singular dimensions | a.squeeze() | |
| Drop singular dimensions | np.squeeze(a) | |
| Difference along axis | np.diff(a, axis=ax) | |
| Difference along axis with lag | np.diff(a, n=lag, axis=ax) | |
Reshape
| What | How | Details |
| Reshape to dimensions d | x.reshape(d) | |
Convert
| What | How | Details |
| Bytes | x.tobytes() | Not sure what difference with data.tobytes() is |
| Hash | hash(x.data.tobytes()) | |