我正在使用一个名为 emcee 的 Python 模块来对分发进行采样。我需要将一个 (37,100)(我分别命名为 Ntrig 和 Nsamp)数组events
传递给下面的函数。
def mp(SNR2, *events):
events = np.asarray(events).reshape((Ntrig,Nsamp))
bessel = special.iv(0,np.sqrt(x*SNR2(event)))
exp = np.exp(-0.5*(x+SNR2(event)))
I = integrate.quad(lambda x: exp*bessel,0,SNRth**2)[0]
return np.asarray([np.array[I for event in events[i]] for i in range(len(events))]).reshape(events.shape)
我不断收到错误:
ValueError: total size of new array must be unchanged
据我了解,*events
会将events
数组分解为 37*100 个单独的参数。不应该在我重塑数组的下一行将其放回 37 x 100 数组吗?
PS 在你问我为什么还要费心分解events
成单独的参数之前 PS——模块需要这个才能工作,它不能接受一个数组。
完整回溯错误:
ValueError Traceback (most recent call last)
<ipython-input-17-c8e815326a69> in <module>()
----> 1 mp(SNR2,events)
<ipython-input-16-9f73f234c628> in mp(SNR2, *events)
5 def mp(SNR2, *events):
6 events = np.asarray(events).reshape((Ntrig,Nsamp))
----> 7 return np.asarray([np.array([integrate.quad(lambda x: np.exp(-0.5*(x+SNR2(event)))*special.iv(0,np.sqrt(x*SNR2(event))),0,SNRth**2)[0] for event in events[i]]) for i in range(len(events))]).reshape(events.shape)
8 # return integrate.quad(lambda x: 0.5*np.exp(-0.5*(x+SNR2(event)))*special.iv(0,np.sqrt(x*SNR2(event))),0,SNRth**2)[0]
9 def pp(SNR2, *events):
/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/integrate/quadpack.pyc in quad(func, a, b, args, full_output, epsabs, epsrel, limit, points, weight, wvar, wopts, maxp1, limlst)
279 args = (args,)
280 if (weight is None):
--> 281 retval = _quad(func,a,b,args,full_output,epsabs,epsrel,limit,points)
282 else:
283 retval = _quad_weight(func,a,b,args,full_output,epsabs,epsrel,limlst,limit,maxp1,weight,wvar,wopts)
/opt/local/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/scipy/integrate/quadpack.pyc in _quad(func, a, b, args, full_output, epsabs, epsrel, limit, points)
343 if points is None:
344 if infbounds == 0:
--> 345 return _quadpack._qagse(func,a,b,args,full_output,epsabs,epsrel,limit)
346 else:
347 return _quadpack._qagie(func,bound,infbounds,args,full_output,epsabs,epsrel,limit)
<ipython-input-16-9f73f234c628> in <lambda>(x)
5 def mp(SNR2, *events):
6 events = np.asarray(events).reshape((Ntrig,Nsamp))
----> 7 return np.asarray([np.array([integrate.quad(lambda x: np.exp(-0.5*(x+SNR2(event)))*special.iv(0,np.sqrt(x*SNR2(event))),0,SNRth**2)[0] for event in events[i]]) for i in range(len(events))]).reshape(events.shape)
8 # return integrate.quad(lambda x: 0.5*np.exp(-0.5*(x+SNR2(event)))*special.iv(0,np.sqrt(x*SNR2(event))),0,SNRth**2)[0]
9 def pp(SNR2, *events):
<ipython-input-16-9f73f234c628> in SNR2(*events)
1 def SNR2(*events):
----> 2 events = np.asarray(events).reshape((Ntrig,Nsamp))
3 C = 5*np.pi**(-1.33333)*events**(1.66667)/(96*d**2)
4 return C*integrate.quad(lambda f: f**(-2.3333)/S(f), 20, 1500, limit=1000)[0]
5 def mp(SNR2, *events):
ValueError: total size of new array must be unchanged