I am using this as an example auto_arima use case but getting segmentation fault error on Mac M1 Max, can somebody guide me what I am doing wrong. The same code is running on Mac M1 Pro.
To Reproduce
I am using latest Mac M1 Max (64 gb) bought a week ago.
Install python3
pip install pmdarima # along with its dependencies
And use with the following code
import numpy as np
import pmdarima as pm
from pmdarima.datasets import load_wineind
wineind = load_wineind().astype(np.float64)
stepwise_fit = pm.auto_arima(wineind, start_p=1, start_q=1,
max_p=3, max_q=3, m=12,
start_P=0, seasonal=True,
d=1, D=1, trace=True,
error_action='trace', # don't want to know if an order does not work
suppress_warnings=False, # don't want convergence warnings
stepwise=False) # set to stepwise
Versions
Python: 3.10.8
macOS: 13.0.1 (22A400)
Expected Behavior
segmentation fault # when running directly in terminal
finished with exit code 139 (interrupted by signal 11: SIGSEGV) # when running in django using debugger
Describe the bug
I am using this as an example auto_arima use case but getting segmentation fault error on Mac M1 Max, can somebody guide me what I am doing wrong. The same code is running on Mac M1 Pro.
To Reproduce
I am using latest Mac M1 Max (64 gb) bought a week ago.
Install python3 pip install pmdarima # along with its dependencies
And use with the following code
Versions
Expected Behavior
Actual Behavior
It should return results in stepwise_fit
Additional Context
No response