negative axis 1 index

[NAThompson]

Code to reproduce:

#!/usr/bin/env python3
from math import pi as π
import random
import numpy as np
from smt.surrogate_models import RMTB, RMTC


dimension = 2

def generate_sine_surface_data(samples=20):
    training_points = np.full(shape=(samples, dimension), fill_value=np.nan)
    training_values = np.full(shape=samples, fill_value=np.nan)

    for i in range(samples):
        x = np.random.uniform(-1, 1, dimension)
        training_points[i, :] = x
        v = 1
        for j in range(dimension):
            v *= np.sin(π*x[j])
        training_values[i] = v
    return training_points, training_values


def rmtb_surrogate_model(training_points, training_values):
    limits = np.full(shape=(dimension, 2), fill_value=np.nan)
    limits[0, 0] = -1
    limits[0, 1] = 1

    model = RMTB(
        xlimits=limits,
    )
    model.set_training_values(training_points, training_values)
    model.train()
    return model


if __name__ == "__main__":
    training_points, training_values = generate_sine_surface_data()
    rmtb = rmtb_surrogate_model(training_points, training_values)

Error:

___________________________________________________________________________
   
                                   RMTB
___________________________________________________________________________
   
 Problem size
   
      # training points.        : 20
   
___________________________________________________________________________
   
 Training
   
   Training ...
      Pre-computing matrices ...
         Computing dof2coeff ...
         Computing dof2coeff - done. Time (sec):  0.0000010
         Initializing Hessian ...
         Initializing Hessian - done. Time (sec):  0.0001552
         Computing energy terms ...
Traceback (most recent call last):
  File "~/smt/./rmtb_negative_axis.py", line 39, in <module>
    rmtb = rmtb_surrogate_model(training_points, training_values)
           ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "~/smt/./rmtb_negative_axis.py", line 33, in rmtb_surrogate_model
    model.train()
  File "~/smt/smt/surrogate_models/surrogate_model.py", line 275, in train
    self._train()
  File "~/smt/smt/surrogate_models/rmts.py", line 443, in _train
    self._new_train()
  File "~/smt/smt/surrogate_models/rmts.py", line 406, in _new_train
    self._compute_energy_terms() * self.options["energy_weight"]
    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "~/smt/smt/surrogate_models/rmts.py", line 209, in _compute_energy_terms
    mtx = self._compute_jac(kx + 1, kx + 1, x)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "~/smt/smt/surrogate_models/rmts.py", line 142, in _compute_jac
    full_jac = scipy.sparse.csc_matrix(
               ^^^^^^^^^^^^^^^^^^^^^^^^
  File "~/smt/venv_smt/lib/python3.12/site-packages/scipy/sparse/_compressed.py", line 55, in __init__
    coo = self._coo_container(arg1, shape=shape, dtype=dtype)
          ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "~/smt/venv_smt/lib/python3.12/site-packages/scipy/sparse/_coo.py", line 99, in __init__
    self._check()
  File "~/smt/venv_smt/lib/python3.12/site-packages/scipy/sparse/_coo.py", line 208, in _check
    raise ValueError(f'negative axis {i} index: {idx.min()}')
ValueError: negative axis 1 index: -1

Additional information:

$ pip show scipy
Name: scipy
Version: 1.13.1
$ python3 -V
Python 3.12.3
$ uname -a
Darwin  23.4.0 Darwin Kernel Version 23.4.0: Fri Mar 15 00:12:49 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T6020 arm64

Reproduces on scipy==1.12 as well, albeit with a different error message.