我正在通过RPy与nlme和lme4 R函数接口(interface)，我想从我的python控制台访问输出摘要。
我运行以下代码:
test1=nlme.lme(r.formula('Pupil~CoI*Time'), random=r.formula('~1|ID'),data=dfr)
test2=nlme.lme(r.formula('Pupil~CoI*measurement'),random=r.formula('~1|ID'),data=dfr)
test1_sum= r.summary(test1)
test2_sum= r.summary(test2)
print test1_sum
print test2_sum
对于nlme，对于lme4:
test1=lme4.lmer(r.formula('Pupil~CoI*Time+(1|ID)'),data=dfr)
test2=lme4.lmer(r.formula('Pupil~CoI*measurement+(1|ID)'),data=dfr)
test1_sum= r.summary(test1)
test2_sum= r.summary(test2)
print test1_sum
print test2_sum
要获取包含数据和显式导入的代码段，请引用此IPython notebook。
在所有情况下，我都会得到大量的打印输出，其中包括一个长得很长的部分，如下所示:
Data: structure(list(CoI = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L ......
我想获得以下方面的摘要:
Random effects:
Formula: ~1 | ID
(Intercept) Residual
StdDev: 0.2201214 0.1199874
Fixed effects: Pupil ~ CoI * measurement
Value Std.Error DF t-value p-value
(Intercept) 1.2068660 0.06369911 5769 18.946357 0
CoIhard -0.0394413 0.00629117 5769 -6.269306 0
measurement -0.0002743 0.00003207 5769 -8.554287 0
CoIhard:measurement 0.0005227 0.00004536 5769 11.524511 0
Correlation:
(Intr) CoIhrd msrmnt
CoIhard -0.049
measurement -0.060 0.612
CoIhard:measurement 0.043 -0.865 -0.707
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-9.86773055 -0.37638950 0.02085029 0.43203795 4.97364143
Number of Observations: 5784
Number of Groups: 12
(这包括在我得到的内容中，但在上述内容之后仅包含成千上万的条目)
我该如何实现？
最佳答案
正确的方法是使用.rx2()方法，有多种使用方法:
In [43]:
print test2_sum.names
Unable to unlink tempfile c:\docume~1\x60t\locals~1\temp\tmpnhw4n4
[1] "methTitle" "objClass" "devcomp" "isLmer" "useScale"
[6] "logLik" "family" "link" "ngrps" "coefficients"
[11] "sigma" "vcov" "varcor" "AICtab" "call"
[16] "residuals"
In [44]:
print test2_sum.rx2('vcov') # to access R type print out
Unable to unlink tempfile c:\docume~1\x60t\locals~1\temp\tmpebn3f1
4 x 4 Matrix of class "dpoMatrix"
(Intercept) CoIhard measurement CoIhard:measurement
(Intercept) 93253.4275120 -80.6588422 -0.503069702 0.503069702
CoIhard -80.6588422 161.3176844 0.503069702 -1.006139404
measurement -0.5030697 0.5030697 0.004192248 -0.004192248
CoIhard:measurement 0.5030697 -1.0061394 -0.004192248 0.008384495
In [45]:
print test2_sum.rx2('varcor') # to access R type print out
Unable to unlink tempfile c:\docume~1\x60t\locals~1\temp\tmpcad6ld
Groups Name Std.Dev.
ID (Intercept) 1057.39
Residual 242.24
In [46]:
list(test2_sum.rx2('varcor')) # to get the values
Out[46]:
[<Matrix - Python:0x0782CEB8 / R:0x0E97FB28>
[1118073.223847]]
In [47]:
list(test2_sum.rx2('varcor')[0]) # to get the values
Out[47]:
[1118073.2238471208]
通过跳过
calls和residuals，您将摆脱大多数事情，请尝试:for i, v in enumerate(list(test2_sum.names)):
if v not in ['call', 'residuals']:
print '%s========================================================='%i, v
print test2_sum.rx2(v)
附加编辑:
我认为访问
tTable结果的lme4(使用rpy2)的最佳方法是将其转换为pandas DataFrame:In [73]:
print com.convert_robj(test2_sum.rx2('tTable'))
Value Std.Error DF t-value p-value
(Intercept) 2480.515542 305.374210 5769 8.122872 5.521357e-16
CoIhard -90.840336 12.701090 5769 -7.152169 9.602962e-13
measurement -0.288709 0.064748 5769 -4.458998 8.390496e-06
CoIhard:measurement 1.049136 0.091567 5769 11.457595 4.546122e-30
[4 rows x 5 columns]
print输出与R输出不完全匹配，但是很容易完成:In [87]:
print test2_sum.rx2('tTable').__str__().replace('\r\n\r\n', '\n')
Value Std.Error DF t-value p-value
(Intercept) 2480.5155423 305.37420990 5769 8.122872 5.521357e-16
CoIhard -90.8403359 12.70108989 5769 -7.152169 9.602962e-13
measurement -0.2887093 0.06474757 5769 -4.458998 8.390496e-06
CoIhard:measurement 1.0491363 0.09156689 5769 11.457595 4.546122e-30