R，Python，网状和Limmbo：将数组'float64'转换为'int64'错误

Question

I am trying to use the python module limmbo ( https://github.com/HannahVMeyer/limmbo ) with R via the reticulate R package. I have successfully installed limmbo with Anaconda2. I'm now trying to use the function limmbo$core$vdbootstrap$LiMMBo$runBootstrapCovarianceEstimation , as in my code below. When I run the code below, I get an error about converting a float64 to an integer64.

```{r}
library(reticulate)
import("limmbo") -> limmbo
```

I then run the python code:

```{python}
import numpy
from numpy.random import RandomState
from numpy.linalg import cholesky as chol
from limmbo.core.vdsimple import vd_reml
from limmbo.io.input import InputData
random = RandomState(15)
N = 100
S = 1000
P = 3
snps = (random.rand(N, S) < 0.2).astype(float)
kinship = numpy.dot(snps, snps.T) / float(10)
y  = random.randn(N, P)
pheno = numpy.dot(chol(kinship), y)
pheno_ID = [ 'PID{}'.format(x+1) for x in range(P)]
samples = [ 'SID{}'.format(x+1) for x in range(N)]
datainput = InputData()
datainput.addPhenotypes(phenotypes = pheno,
phenotype_ID = pheno_ID, pheno_samples = samples)
datainput.addRelatedness(relatedness = kinship,
relatedness_samples = samples)
```

The problem arises when I try to run the R function limmbo$core$vdbootstrap$LiMMBo$runBootstrapCovarianceEstimation :

```{r}
(limmbo$core$vdbootstrap$LiMMBo(py$datainput, timing = TRUE, iterations = 100, S = 2) -> foo)
limmbo$core$vdbootstrap$LiMMBo$runBootstrapCovarianceEstimation(foo, cpus = 1, seed = 12345)
```



Error in py_call_impl(callable, dots$args, dots$keywords) : 
  TypeError: Cannot cast array from dtype('float64') to dtype('int64') according to the rule 'safe'

Detailed traceback: 
  File "/Users/frederickboehm/anaconda2/lib/python2.7/site-packages/limmbo/core/vdbootstrap.py", line 96, in runBootstrapCovarianceEstimation
    minCooccurrence=minCooccurrence)
  File "/Users/frederickboehm/anaconda2/lib/python2.7/site-packages/limmbo/core/vdbootstrap.py", line 353, in __generateBootstrapMatrix
    rand_state = np.random.RandomState(seed)
  File "mtrand.pyx", line 644, in mtrand.RandomState.__init__
  File "mtrand.pyx", line 687, in mtrand.RandomState.seed
Calls: <Anonymous> ... eval -> eval -> <Anonymous> -> py_call_impl ->     .Call
Execution halted

Answer 1

First of all, import you numpy module via np <- import("numpy", convert = FALSE) .

And then you can re-create your numpy array with explicit type int64 by using reticulate::np_array(datainput, dtype = np$int64) .

You can learn more about how to manipulate and create your arrays in this tutorial .

Hope this helps.

Answer 2

Yuan's tutorial (link in the answer above) contains suggestions that allowed me to answer the question. Here is my revised R code that, as of now, works:

np <- import("numpy", convert = FALSE)
(limmbo$core$vdbootstrap$LiMMBo(datainput, timing = TRUE, iterations = np_array(10, dtype = "int64"), S = np_array(2, dtype = "int64")) -> foo)
limmbo$core$vdbootstrap$LiMMBo$runBootstrapCovarianceEstimation(foo, cpus = np$int(1), seed = np_array(1232, dtype = "int64"))