通过rpy2将Python Lambda函数传递给R

Question

我想围绕R库Rdtq （https://github.com/cran/Rdtq）编写一个Python包装器。 该库（或更确切地说，类实例）将主要输入作为两个函数：漂移f（x）和扩散g（x）。例如，

my_drift = function(x) { -x } 
my_diff = function(x) { rep(1,length(x)) } 

因为我写周围的Rdtq类的包装，我想直接从Python中通过漂移和扩散功能，通过lambda函数

my_python_drift(x) = lambda x: -x 
my_python_diff(x) = lambda x: np.ones(len(x)) 

等理想。所以更一般地说，我的问题是： 我可以通过rpy2将Python lambda（或全局）函数作为参数传递给R吗？

Answer 1

考虑使用rpy2的SignatureTranslatedAnonymousPackage (STAP)在Python环境中导入任意R代码作为可用包。为了演示，写入中的R到Python的Rdtq github使用rpy2以下转换：

ř

# Loading required package: Rdtq 
require(Rdtq) 

# Assigning drift and diff functions 
mydrift = function(x) { -x } 
mydiff = function(x) { rep(1,length(x)) } 

# Running rdtq() 
test = rdtq(h=0.1, k=0.01, bigm=250, init=0, fT=1, 
      drift=mydrift, diffusion=mydiff, method="sparse") 

# Plotting output 
plot(test$xvec, test$pdf, type='l') 

的Python

from rpy2 import robjects 
from rpy2.robjects.packages import STAP 
from rpy2.robjects.packages import importr 

# Loading required package: Rdtq 
Rdtq = importr('Rdtq') 

fct_string = """ 
my_drift <- function(x) { -x } 
my_diff <- function(x) { rep(1,length(x)) } 
""" 

# Creating package with above drift and diff methods 
my_fcts = STAP(fct_string, "my_fcts") 

# Running rdtq() --notice per Python's model: all methods are period qualified 
test = Rdtq.rdtq(h=0.1, k=0.01, bigm=250, init=0, fT=1, 
       drift=my_fcts.my_drift(), diffusion=my_fcts.my_diff(), method="sparse") 

# Load plot function 
plot = robjects.r.plot 

# Plotting by name index 
plot(test[test.names.index('xvec')], test[test.names.index('pdf')], type='l')