numpy >= 1.20 incompatibilities

[ghylander]

Didn't find any issue related to this

Starting in numpy 1.20 (release notes), "using the aliases of builtin types like np.int is deprecated". This results in the following warning:

guiqwt\image.py:2233: FutureWarning: In the future 'np.bool' will be defined as the corresponding NumPy scalar. (This may have returned Python scalars in past versions.

However, in numpy 1.24, the following exception is raised:

AttributeError: module 'numpy' has no attribute 'bool'. Did you mean: 'bool_'?

This behaviour can be observed in the guiqwt test "image_masked.py", when applying a "mask (outside)", then selecting "apply".

[ghylander]

As the exception suggests, simply changing image.py line 2233 from:

indexes = np.ones(self.data.shape, dtype=np.bool)

to:

indexes = np.ones(self.data.shape, dtype=np.bool_)

Supresses the warning and the exception

[ghylander]

I found additional incompatibilities. In the 'mandelbrot' test, the following warning is raised:

guiqwt\tests\mandelbrot.py:60: DeprecationWarning: NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays.  The conversion of -1 to uint8 will fail in the future.
For the old behavior, usually:
    np.array(value).astype(dtype)`
will give the desired result (the cast overflows).

Then, in the 'pcolor' test, the following exception is reaised. Could be related to the warning raised in the 'mandelbrot' tetst:

Traceback (most recent call last):
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 306, in selection_changed
    curve.set_hist_source(item)
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 140, in set_hist_source
    self.update_histogram()
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 183, in update_histogram
    hist, bin_edges = self.compute_histogram()
                      ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 178, in compute_histogram
    return self.get_hist_source().get_histogram(self.bins)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\image.py", line 746, in get_histogram
    res = np.histogram(self.data, nbins)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<__array_function__ internals>", line 200, in histogram
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 780, in histogram
    bin_edges, uniform_bins = _get_bin_edges(a, bins, range, weights)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 426, in _get_bin_edges
    first_edge, last_edge = _get_outer_edges(a, range)
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 323, in _get_outer_edges
    raise ValueError(
ValueError: autodetected range of [nan, nan] is not finite

[PierreRaybaut]

Hi,
Thanks for the feedback.

Didn't find any issue related to this

Starting in numpy 1.20 (release notes), "using the aliases of builtin types like np.int is deprecated". This results in the following warning:

guiqwt\image.py:2233: FutureWarning: In the future 'np.bool' will be defined as the corresponding NumPy scalar. (This may have returned Python scalars in past versions.

However, in numpy 1.24, the following exception is raised:

AttributeError: module 'numpy' has no attribute 'bool'. Did you mean: 'bool_'?

This behaviour can be observed in the guiqwt test "image_masked.py", when applying a "mask (outside)", then selecting "apply".

This is fixed by: 56ae061

I found additional incompatibilities. In the 'mandelbrot' test, the following warning is raised:

guiqwt\tests\mandelbrot.py:60: DeprecationWarning: NumPy will stop allowing conversion of out-of-bound Python integers to integer arrays.  The conversion of -1 to uint8 will fail in the future.
For the old behavior, usually:
    np.array(value).astype(dtype)`
will give the desired result (the cast overflows).

This one is probably due to the fact that the mandelbrot extension (Cython) somehow returns negative values that where until now casted without warning by NumPy.
I will treat this separetely: #106

Then, in the 'pcolor' test, the following exception is reaised. Could be related to the warning raised in the 'mandelbrot' tetst:

Traceback (most recent call last):
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 306, in selection_changed
    curve.set_hist_source(item)
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 140, in set_hist_source
    self.update_histogram()
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 183, in update_histogram
    hist, bin_edges = self.compute_histogram()
                      ^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\histogram.py", line 178, in compute_histogram
    return self.get_hist_source().get_histogram(self.bins)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\guiqwt\image.py", line 746, in get_histogram
    res = np.histogram(self.data, nbins)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "<__array_function__ internals>", line 200, in histogram
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 780, in histogram
    bin_edges, uniform_bins = _get_bin_edges(a, bins, range, weights)
                              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 426, in _get_bin_edges
    first_edge, last_edge = _get_outer_edges(a, range)
                            ^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "C:\Users\user\miniconda3\envs\env_name\Lib\site-packages\numpy\lib\histograms.py", line 323, in _get_outer_edges
    raise ValueError(
ValueError: autodetected range of [nan, nan] is not finite

This should be fixed by 6d815e1