Numpy属性错误pymc

Question

我试图实现一个使用pymc和numpy的状态空间模型。

因此，我用dtype对象使用numpy数组来避免设置一个具有序列错误的数组元素。作为证明here

然后我用一个列表作为pymc节点的“容器”建议here和实施here

我的问题是当我尝试使用numpy的的指数函数，这将不与阵列上运行对象的类型。

当我尝试将dtype更改为浮点数时，我得到一个具有序列错误的数组。

下面是一些复制问题的代码。

import pandas as pd 
import pymc as pm 
import numpy as np 
from datetime import datetime 
import pylab 

df = pd.read_csv('http://www.football-data.co.uk/mmz4281/1314/E0.csv') 

results = df[['HomeTeam','AwayTeam','FTHG','FTAG']] 

teams = sorted(results['HomeTeam'].unique()) 

y1 = np.array(results['FTHG']) 

y2 = np.array(results['FTAG']) 

home_team = pd.Series(np.arange(20),index=teams)[results['HomeTeam']].values 

away_team = pd.Series(np.arange(20),index=teams)[results['AwayTeam']].values 

game = range(df.shape[0]) 

nteams = len(teams) 
ngames = len(game) 



df.Date = df.Date.apply(lambda x: datetime.strptime(x, '%d/%m/%y')) 

df.Date = df.Date.apply(lambda x: (x - df.Date.ix[0]).days//7) 


week = pd.factorize(df.Date)[0] 

nweeks = max(week)+1 

nweeks 

home = pm.Normal('home', 0, .0001, value=[0]*nteams,size=(nteams,)) 
away = pm.Normal('away', 0, .0001, value=0) 
mu_att = pm.Normal('mu_att', 0, .0001) 
mu_def = pm.Normal('mu_def', 0, .0001, value=0) 
tau_att = pm.Gamma('tau_att', .1, .1) 
tau_def = pm.Gamma('tau_def', .1, .1) 
sigma = pm.Gamma('sigma', .1, .1) 


atts_0 = pm.Normal("atts_0", 
       mu=mu_att, 
       tau=tau_att, 
       size=(nteams,1)) 

defs_0 = pm.Normal("atts_0", 
       mu=mu_def, 
       tau=tau_def, 
       size=(nteams,1)) 

atts = [atts_0] 
defs = [defs_0] 

for i in range(1,nweeks+1): 
    a = pm.Normal('a_%i'%i, mu = atts[i-1],tau=sigma) 
    attsi = pm.Lambda('atts_%i' % i, lambda a=a: np.eye(nteams).dot(a) - np.ones(nteams).dot(np.ones(nteams).T)) 
    atts.append(attsi) 

for i in range(1,nweeks+1): 
    d = pm.Normal('d_%i'%i, mu = defs[i-1],tau=sigma) 
    defsi = pm.Lambda('defs_%i' % i, lambda d=d: np.eye(nteams).dot(d) - np.ones(nteams).dot(np.ones(nteams).T)) 
    defs.append(defsi) 

atts = np.array(atts[1:]) 
defs = np.array(defs[1:]) 


@pm.deterministic 
def home_theta(home=home, 
      atts=atts, 
      defs=defs, 
      week=week, 
      home_team=home_team, 
      away_team=away_team): 
    return np.exp((home[home_team] + atts[week][home_team] + defs[week][away_team]))  


LazyFunction.pyx in pymc.LazyFunction.LazyFunction.force_compute (pymc/LazyFunction.c:2409)() 

<ipython-input-35-9977366624a3> in home_theta(home, atts, defs, week, home_team, away_team) 
    6    home_team=home_team, 
    7    away_team=away_team): 
----> 8  return np.exp((home[home_team] + atts[week][home_team] + defs[week][away_team])) 

AttributeError: 'numpy.ndarray' object has no attribute 'exp' 

Answer 1

从错误

----> 8  return np.exp((home[home_team] + atts[week][home_team] + defs[week][away_team])) 
AttributeError: 'numpy.ndarray' object has no attribute 'exp' 

我猜测的numpy模块（名为np）已被替换为一个阵列，np.ndarray对象。换句话说，事情是做这样的事情：

np = np.array(...) # or 
np = x + 3 # where x=np.array... 

也许它是@pm.deterministic装饰。

不知道任何关于pymc你可以尝试使用numpy作为导入名称，而不是np。换句话说，试着绕过这个重命名。

import numpy 
.... 
numpy.exp(...)