[BUG] - AttributeError: module 'scipy.integrate' has no attribute 'simps

[BOBBEAR82]

I found an error when I am running the example of Fit_Everything, and I got the error as below

AttributeError: module 'scipy.integrate' has no attribute 'simps'

Looks like latest version of Scipy removed the method simps from integrate, and change to simpson

[clementfaisandier]

FYI: if you go to reliabilitydistributions.py and change integrate.simps to integrate.simpson this should work.

It appears the test functions ran just fine after that. I might try starting a branch and getting a pull request in for the authors to validate this week.

A safer solution:
You could also revert your scipy version to scipy<1.14.0. Here is the commit where simps was removed, which was released under version 1.14.0.

[lmotcho2001]

I found an error when I am running the example of Fit_Everything, and I got the error as below

AttributeError: module 'scipy.integrate' has no attribute 'simps'

Looks like latest version of Scipy removed the method simps from integrate, and change to simpson

I correct that but it's give this error :

: FutureWarning: The behavior of DataFrame concatenation with empty or all-NA entries is deprecated. In a future version, this will no longer exclude empty or all-NA columns when determining the result dtypes. To retain the old behavior, exclude the relevant entries before the concat operation.
df = pd.concat(
Traceback (most recent call last):

Cell In[9], line 1
Fit.Fit_Everything(np.array(V))

File ~\AppData\Local\spyder-6\envs\spyder-runtime\Lib\site-packages\reliability\Fitters.py:803 in init
self.__Weibull_Mixture_params = Fit_Weibull_Mixture(

File ~\AppData\Local\spyder-6\envs\spyder-runtime\Lib\site-packages\reliability\Fitters.py:3761 in init
self.distribution = Mixture_Model(

File ~\AppData\Local\spyder-6\envs\spyder-runtime\Lib\site-packages\reliability\Distributions.py:8662 in init
raise ValueError(

ValueError: distributions must be an array or list of probability distributions. Each distribution must be created using the reliability.Distributions module.