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- numpy.record.ndim
...numpy.record.ndim...
- numpy.record.ndim (Python attribute, in numpy.record.ndim)
- NumPy 1.10.2 Release Notes
...treated as C contiguous which breaks some code that depended the two being mutually exclusive for non-scalar arrays of ndim > 1. This deprecation prepares the way to always enable relaxed stride checking. Issues Fixed gh-6019 Masked ar...
- NumPy 1.13.0 Release Notes
...tch the behavior of np.conjugate, which throws an error). Calling expand_dims when the axis keyword does not satisfy -a.ndim - 1 <= axis <= a.ndim, where a is the array being reshaped, is deprecated. Future Changes Assignment between st...
- NumPy 1.13.1 Release Notes
...DOC: update f2py front page and some doc build metadata. #9299 BUG: Fix Intel compilation on Unix. #9317 BUG: fix wrong ndim used in empty where check #9319 BUG: Make extensions compilable with MinGW on Py2.7 #9339 BUG: Prevent crash if ufu...
- numpy.recarray
...ay element in bytes. mTView of the matrix transposed array. nbytesTotal bytes consumed by the elements of the array. ndimNumber of array dimensions. newbyteorder ptp realThe real part of the array. shapeTuple of array dimensions. size...
- numpy.record
...view of the scalar. imagThe imaginary part of the scalar. itemset itemsizeThe length of one element in bytes. nbytes ndimThe number of array dimensions. newbyteorder ptp realThe real part of the scalar. shapeTuple of array dimensions....
- numpy.record.ndim
...numpy.record.ndim...
- NumPy: the absolute basics for beginners
...ese names (e.g. the fundamental data structure of PyTorch is the “tensor”). Array attributes This section covers the ndim, shape, size, and dtype attributes of an array. The number of dimensions of an array is contained in the ndim attr...
- Glossary
...sis. This is useful in distinguishing, say, a (1,2,3) shape from a (2,3) shape: >>> a = np.arange(6).reshape(2,3) >>> a.ndim 2 >>> a array([[0, 1, 2], [3, 4, 5]]) >>> a = np.arange(6).reshape(1,2,3) >>> a.ndim 3 >>> a array([[[0, 1...
- Indexing on
ndarrays...selection tuple to index all dimensions. In most cases, this means that the length of the expanded selection tuple is x.ndim. There may only be a single ellipsis present. From the above example: >>> x[..., 0] array([[1, 2, 3], [4, 5,...