For example, a 1D array: /// /// ```c /// double_complex data[5]; /// ``` /// /// would be represented in the file with two dimensions (when not /// using a compound datatype!), and so if we use the standard netCDF /// API we would need to use `{5, 2}` for ...
# TODO: configure numpy to output scalar arrays as regular Python scalars # once possible to improve readability of the tests docstrings. # https://numpy.org/neps/nep-0051-scalar-representation.html#implementation reason = "Due to NEP 51 numpy scalar repr has changed in numpy 2" skip_doctest...
/* Input */ $map: ( 'one': ( 'key': 'value', ), 'two': ( 'key': 'value', ), ) /* Prettier 2.8.1 */ $map: ( 'one': ( 'key': 'value', ), 'two': ( 'key': 'value', ), ) /* Prettier 2.8.2 */ $map: ( 'one': ( 'key': 'value', ), 'two': ( '...
As the data has been flattened into a 1D # is a preprocessed subset of the MNIST dataset, containing digit images. # The data is already a NumPy array. As the data has been flattened into a 1D # vector of pixels, we need to reshape the arrays to their original 8x8 shape. # Then ...
We can define these two functions # in Python as follows (remember than the input and output are both NumPy # arrays). def f(t): return np.sin(6 * t) def g(t): return t**2 # %% # Lets now define the functional basis. We create a subclass of # :class:`~skfda.representation...
`test_structural.py` * Set dtype on numpy arrays used in test_structural.py * Remove dictionary merge with pipe Tweak tolerances for test in `test_structural.py` * Disable all PSD tests for univariate filter when floatX=float32 * Remove `variable_by_shape` helper, use `pt.tensor` ...
scikit-learn: the outputs of transformers are numpy arrays, even when the input is a data frame. However, to inspect a model it is essential to keep track of the feature names. dev_url: https://github.com/BCG-Gamma/sklearndf doc_url: https://bcg-gamma.github.io/sklearndf/ doc_sour...