CI: invalid value encountered in cast
return
self.assert_ready_to_execute()
> self.run()
/usr/local/lib/python3.9/site-packages/ewokscore/task.py:401:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
/usr/local/lib/python3.9/site-packages/ewoksxrpd/tasks/integrate.py:186: in run
result = worker.process(raw_data, normalization_factor=normalization_factor)
/usr/local/lib/python3.9/site-packages/pyFAI/worker.py:403: in process
raise err
/usr/local/lib/python3.9/site-packages/pyFAI/worker.py:388: in process
result = numpy.vstack(integrated_result).T
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tup = (array([1.46484392e-02, 4.39453177e-02, 7.32421962e-02, ...,
2.99267614e+01, 2.99560583e+01, 2.99853551e+01]), ...0e+00,
0.0000000e+00, 0.0000000e+00], dtype=float32), array([nan, 0., 0., ..., 0., 0., 0.], dtype=float32))
@array_function_dispatch(_vhstack_dispatcher)
def vstack(tup, *, dtype=None, casting="same_kind"):
"""
Stack arrays in sequence vertically (row wise).
This is equivalent to concatenation along the first axis after 1-D arrays
of shape `(N,)` have been reshaped to `(1,N)`. Rebuilds arrays divided by
`vsplit`.
This function makes most sense for arrays with up to 3 dimensions. For
instance, for pixel-data with a height (first axis), width (second axis),
and r/g/b channels (third axis). The functions `concatenate`, `stack` and
`block` provide more general stacking and concatenation operations.
``np.row_stack`` is an alias for `vstack`. They are the same function.
Parameters
----------
tup : sequence of ndarrays
The arrays must have the same shape along all but the first axis.
1-D arrays must have the same length.
dtype : str or dtype
If provided, the destination array will have this dtype. Cannot be
provided together with `out`.
.. versionadded:: 1.24
casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
Controls what kind of data casting may occur. Defaults to 'same_kind'.
.. versionadded:: 1.24
Returns
-------
stacked : ndarray
The array formed by stacking the given arrays, will be at least 2-D.
See Also
--------
concatenate : Join a sequence of arrays along an existing axis.
stack : Join a sequence of arrays along a new axis.
block : Assemble an nd-array from nested lists of blocks.
hstack : Stack arrays in sequence horizontally (column wise).
dstack : Stack arrays in sequence depth wise (along third axis).
column_stack : Stack 1-D arrays as columns into a 2-D array.
vsplit : Split an array into multiple sub-arrays vertically (row-wise).
Examples
--------
>>> a = np.array([1, 2, 3])
>>> b = np.array([4, 5, 6])
>>> np.vstack((a,b))
array([[1, 2, 3],
[4, 5, 6]])
>>> a = np.array([[1], [2], [3]])
>>> b = np.array([[4], [5], [6]])
>>> np.vstack((a,b))
array([[1],
[2],
[3],
[4],
[5],
[6]])
"""
arrs = atleast_2d(*tup)
if not isinstance(arrs, list):
arrs = [arrs]
> return _nx.concatenate(arrs, 0, dtype=dtype, casting=casting)
E RuntimeWarning: invalid value encountered in cast
/usr/local/lib/python3.9/site-packages/numpy/core/shape_base.py:289: RuntimeWarninghttps://gitlab.esrf.fr/workflow/ewoksapps/ewoksxrpd/-/jobs/1099404