scipy.stats.rv_continuous.fit - 优化器参数

如何解决scipy.stats.rv_continuous.fit - 优化器参数

当使用 /shops/*path/*path e.i. 时，可以操纵 //partial output of the command 'rake routes' GET /shops/login(.:format) POST /shops/login(.:format) DELETE /shops/logout(.:format) GET /shops/password_reset/error(.:format) GET /shops/password_reset/finish(.:format) POST /shops/password_reset(.:format) GET /shops/password_reset/new(.:format) GET /shops/password_reset/edit(.:format) //routes get '/shops/',to: redirect('www.xxx.com/shops/information/1') get '/shops/login' to: redirect('www.xxx.com/shops/information/1') get '/shops/logout' to: redirect('www.xxx.com/shops/information/1') get '/shops/password_reset/*path' to: redirect('www.xxx.com/shops/information/1') get '/shops/password_reset to: redirect('www.xxx.com/shops/information/1') 的参数。相对容差？

在 R 中，我们可以使用 optimizer。 Python呢？

scipy.stats.rv_continuous.fit

解决方法

optimizer 方法的 fit 参数允许您覆盖默认优化函数（即 scipy.optimize.fmin）并提供您自己的优化函数。您作为 optimizer 参数提供的可调用对象必须具有签名 optimize(func,x0,args=(),disp=False)。

要更改默认控制参数，您可以使用自定义 optimizer，该 fmin 调用带有附加 xtol 和/或 ftol 参数的 fmin。 （注意：您可以使用不同的优化器来代替 from scipy.optimize import fmin def optimizer(func,disp=False): return fmin(func,args=args,disp=disp,xtol=1e-13,ftol=1e-12) 。）我经常使用的是

from scipy.stats import weibull_min
from scipy.optimize import fmin


def optimizer(func,ftol=1e-12)


data = [2457.145,878.081,855.118,1157.135,1099.82]

shape,loc,scale = weibull_min.fit(data,floc=0,optimizer=optimizer)
print(f"shape = {shape:9.7f},scale={scale:9.7f}")

例如

shape = 2.3078998,scale=1463.7713354

输出：

SELECT library.name,(SELECT ARRAY (select book.title 
                      from books 
                      where book.library_id = 1 and book.is_free = false) as book_lists) 
from library 
where id = 1;