amps, FWHMs, means Dimensions is different

[sunmingke]

---

ValueError Traceback (most recent call last)
Cell In[3], line 24
20 train.training()
23 if name == "main":
---> 24 main()

Cell In[3], line 20, in main()
18 train.alpha2_initial = 6.
19 # 开始训练
---> 20 train.training()

File ~/.local/lib/python3.8/site-packages/gausspyplus-0.2.dev0-py3.8.egg/gausspyplus/training.py:73, in GaussPyTraining.training(self)
71 self.initialize()
72 self.getting_ready()
---> 73 self.gausspy_train_alpha()

File ~/.local/lib/python3.8/site-packages/gausspyplus-0.2.dev0-py3.8.egg/gausspyplus/training.py:90, in GaussPyTraining.gausspy_train_alpha(self)
88 g.set('phase', 'two') # Set GaussPy parameters
89 # Train AGD starting with initial guess for alpha
---> 90 g.train(alpha1_initial=self.alpha1_initial, alpha2_initial=self.alpha2_initial,
91 logger=self.logger)
92 else:
93 g.set('phase', 'one')

File ~/.local/lib/python3.8/site-packages/gausspyplus-0.2.dev0-py3.8.egg/gausspyplus/gausspy_py3/gp.py:50, in GaussianDecomposer.train(self, alpha1_initial, alpha2_initial, plot, verbose, mode, learning_rate, eps, MAD, logger)
46 return
47 print('Training...')
49 self.p['alpha1'], self.p['alpha2'], self.p['training_results'] =
---> 50 gradient_descent.train(alpha1_initial=alpha1_initial,
51 alpha2_initial=alpha2_initial,
52 training_data=self.p['training_data'],
53 phase=self.p['phase'],
54 SNR_thresh=self.p['SNR_thresh'],
55 SNR2_thresh=self.p['SNR2_thresh'],
56 plot=plot, eps=eps,
57 verbose=verbose, mode=mode,
58 learning_rate=learning_rate, MAD=MAD,
59 logger=logger)

File ~/.local/lib/python3.8/site-packages/gausspyplus-0.2.dev0-py3.8.egg/gausspyplus/gausspy_py3/gradient_descent.py:221, in train(objective_function, training_data, alpha1_initial, alpha2_initial, iterations, MAD, eps, learning_rate, p, window_size, iterations_for_convergence, plot, phase, SNR2_thresh, SNR_thresh, verbose, mode, improve_fitting_dict, logger)
219 FWHMs = training_data['fwhms']
220 amps = training_data['amplitudes']
--> 221 true_params = np.append(amps, np.append(FWHMs, means))
223 # Initialize book-keeping object
224 gd = gradient_descent(iterations)

File <array_function internals>:200, in append(*args, **kwargs)

File ~/.local/lib/python3.8/site-packages/numpy/lib/function_base.py:5493, in append(arr, values, axis)
5444 @array_function_dispatch(_append_dispatcher)
5445 def append(arr, values, axis=None):
5446 """
5447 Append values to the end of an array.
5448
(...)
5491
5492 """
-> 5493 arr = asanyarray(arr)
5494 if axis is None:
5495 if arr.ndim != 1:

ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (73,) + inhomogeneous part.
my python is 3.8.10, lmfit 12.2. ,numpy 1.24.4, scipy 1.10.1

[sunmingke]

There was a problem in the second step, I just gave it 432 spectrum training samples, it is not clear if it is my python package version of the problem

[y-angarita]

It is indeed new Numpy versions. I had the same problem with Numpy > v1.24, then downgrade to v1.23.5 and it worked.