RecursionError for executing sensitivities_from_surrogate() function

[FariborzDaneshvar-NOAA]

Here is the full message for executing sensitivities_from_surrogate() for an ensemble of 5 perturbed tracks for florence 2018:

---------------------------------------------------------------------------
RecursionError                            Traceback (most recent call last)
Cell In[11], line 2
      1 if make_sensitivities_plot:
----> 2     sensitivities = sensitivities_from_surrogate(
      3         surrogate_model=surrogate_model,
      4         distribution=distribution,
      5         variables=perturbations['variable'],
      6         nodes=subset,
      7         element_table=elements if point_spacing is None else None,
      8         filename=sensitivities_filename,
      9     )
     10     plot_sensitivities(
     11         sensitivities=sensitivities,
     12         storm=storm_name,
     13         output_filename=output_directory / 'sensitivities.png' if save_plots else None,
     14     )
     16 if make_validation_plot:

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/ensembleperturbation/uncertainty_quantification/surrogate.py:239, in sensitivities_from_surrogate(surrogate_model, distribution, variables, nodes, element_table, filename)
    234 if filename is None or not filename.exists():
    235     LOGGER.info(f'extracting sensitivities from surrogate model and distribution')
    237     sensitivities = [
    238         chaospy.Sens_m(surrogate_model, distribution),
--> 239         chaospy.Sens_t(surrogate_model, distribution),
    240     ]
    242     sensitivities = numpy.stack(sensitivities)
    244     sensitivities = xarray.DataArray(
    245         sensitivities,
    246         coords={
   (...)
    254         dims=('order', 'variable', 'node'),
    255     ).T

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/chaospy/descriptives/sensitivity/total.py:43, in Sens_t(poly, dist, **kws)
     41 valids = variance != 0
     42 if not numpy.all(valids):
---> 43     out[:, valids] = Sens_t(poly[valids], dist, **kws)
     44     return out
     46 out[:] = variance

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/chaospy/descriptives/sensitivity/total.py:43, in Sens_t(poly, dist, **kws)
     41 valids = variance != 0
     42 if not numpy.all(valids):
---> 43     out[:, valids] = Sens_t(poly[valids], dist, **kws)
     44     return out
     46 out[:] = variance

    [... skipping similar frames: Sens_t at line 43 (2956 times)]

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/chaospy/descriptives/sensitivity/total.py:43, in Sens_t(poly, dist, **kws)
     41 valids = variance != 0
     42 if not numpy.all(valids):
---> 43     out[:, valids] = Sens_t(poly[valids], dist, **kws)
     44     return out
     46 out[:] = variance

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/chaospy/descriptives/sensitivity/total.py:36, in Sens_t(poly, dist, **kws)
     10 """
     11 Variance-based decomposition
     12 AKA Sobol' indices
   (...)
     33            [0.        , 0.        , 1.        , 0.57142857]])
     34 """
     35 dim = len(dist)
---> 36 poly = numpoly.set_dimensions(poly, dim)
     38 out = numpy.zeros((dim,) + poly.shape, dtype=float)
     39 variance = Var(poly, dist, **kws)

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpoly/poly_function/set_dimensions.py:67, in set_dimensions(poly, dimensions)
     64 else:
     65     return poly
---> 67 return numpoly.polynomial_from_attributes(
     68     exponents=exponents,
     69     coefficients=coefficients,
     70     names=names,
     71     dtype=poly.dtype,
     72     allocation=poly.allocation,
     73     retain_names=True,
     74 )

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpoly/construct/from_attributes.py:72, in polynomial_from_attributes(exponents, coefficients, names, dtype, allocation, retain_coefficients, retain_names)
     13 def polynomial_from_attributes(
     14     exponents: numpy.typing.ArrayLike,
     15     coefficients: Sequence[numpy.typing.ArrayLike],
   (...)
     20     retain_names: Optional[bool] = None,
     21 ) -> ndpoly:
     22     """
     23     Construct polynomial from polynomial attributes.
     24 
   (...)
     70 
     71     """
---> 72     exponents, coefficients, names = clean.postprocess_attributes(
     73         exponents=exponents,
     74         coefficients=coefficients,
     75         names=names,
     76         retain_coefficients=retain_coefficients,
     77         retain_names=retain_names,
     78     )
     79     if coefficients:
     80         dtype = coefficients[0].dtype if dtype is None else dtype

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpoly/construct/clean.py:139, in postprocess_attributes(exponents, coefficients, names, retain_coefficients, retain_names)
    136 if not retain_names:
    137     exponents, names = remove_redundant_names(exponents, names)
--> 139 exponents_, count = numpy.unique(exponents, return_counts=True, axis=0)
    140 if numpy.any(count > 1):
    141     raise PolynomialConstructionError(
    142         f"Duplicate exponent keys found: {exponents_[count > 1][0]}"
    143     )

File <__array_function__ internals>:200, in unique(*args, **kwargs)

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpy/lib/arraysetops.py:319, in unique(ar, return_index, return_inverse, return_counts, axis, equal_nan)
    315     return uniq
    317 output = _unique1d(consolidated, return_index,
    318                    return_inverse, return_counts, equal_nan=equal_nan)
--> 319 output = (reshape_uniq(output[0]),) + output[1:]
    320 return _unpack_tuple(output)

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpy/lib/arraysetops.py:314, in unique.<locals>.reshape_uniq(uniq)
    312 uniq = uniq.view(orig_dtype)
    313 uniq = uniq.reshape(n, *orig_shape[1:])
--> 314 uniq = np.moveaxis(uniq, 0, axis)
    315 return uniq

File <__array_function__ internals>:200, in moveaxis(*args, **kwargs)

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpy/core/numeric.py:1467, in moveaxis(a, source, destination)
   1464     a = asarray(a)
   1465     transpose = a.transpose
-> 1467 source = normalize_axis_tuple(source, a.ndim, 'source')
   1468 destination = normalize_axis_tuple(destination, a.ndim, 'destination')
   1469 if len(source) != len(destination):

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpy/core/numeric.py:1398, in normalize_axis_tuple(axis, ndim, argname, allow_duplicate)
   1396         pass
   1397 # Going via an iterator directly is slower than via list comprehension.
-> 1398 axis = tuple([normalize_axis_index(ax, ndim, argname) for ax in axis])
   1399 if not allow_duplicate and len(set(axis)) != len(axis):
   1400     if argname:

File ~/miniconda3/envs/perturbation/lib/python3.10/site-packages/numpy/core/numeric.py:1398, in <listcomp>(.0)
   1396         pass
   1397 # Going via an iterator directly is slower than via list comprehension.
-> 1398 axis = tuple([normalize_axis_index(ax, ndim, argname) for ax in axis])
   1399 if not allow_duplicate and len(set(axis)) != len(axis):
   1400     if argname:

RecursionError: maximum recursion depth exceeded while calling a Python object