Проблема запуска PYMC3 с сеткой в ​​R

Question

В качестве принудительной функции, чтобы узнать больше о байесовском моделировании / научиться использовать сетчатый пакет, я пытался повторить упражнения «Байесовские методы для хакеров» в R (оригинал блокнот Jupyter ). Однако при попытке запустить MCM C я получаю ошибку TypeError, но я недостаточно знаком с PYMC3 или Reticulate, чтобы знать, где происходит ошибка. Ниже я включил репекс моего выпуска:

Представление

library(reticulate)
library(readr)

pm <- import("pymc3", convert = FALSE)
tt <- import("theano.tensor")
py <- import_builtins()
np <- import("numpy")
scipy <- import("scipy")

txtdata = read_csv("https://raw.githubusercontent.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers/master/Chapter1_Introduction/data/txtdata.csv", col_names = F)
#> Parsed with column specification:
#> cols(
#>   X1 = col_double()
#> )

count_data = np$array(txtdata$X1)
n_count_data = length(count_data)

model = pm$Model()

with(model, {
  alpha = 1.0 / np$mean(count_data)

  #Define the Two lambda parameters with hyperparameter alpha
  lambda_1 = pm$Exponential("lambda_1", alpha)
  lambda_2 = pm$Exponential("lambda_2", alpha)

  #Set Priors for Tau as a Uniform Variable
  tau = pm$DiscreteUniform("tau", lower=0, upper=n_count_data - 1)

  #Create an Array of Different Switch Point Varaibles
  idx = np$arange(n_count_data) # Index
  #Create new random variable lambda with our checkpoint

  lambda_ = pm$math$switch(tt$gt(tau, idx), lambda_1, lambda_2)

  #Observation combines the lambda variable with the actual data
  observation = pm$Poisson("obs", lambda_, observed=count_data)

  step = pm$Metropolis()
  trace = pm$sample(10000, tune=5000,step=step)

})
#> Error in py_call_impl(callable, dots$args, dots$keywords): TypeError: 'float' object cannot be interpreted as an integer
#> 
#> Detailed traceback: 
#>   File "C:\Users\Josh\miniconda3\lib\site-packages\pymc3\sampling.py", line 439, in sample
#>     trace = _mp_sample(**sample_args)
#>   File "C:\Users\Josh\miniconda3\lib\site-packages\pymc3\sampling.py", line 979, in _mp_sample
#>     strace.setup(draws + tune, idx + chain, step.stats_dtypes)
#>   File "C:\Users\Josh\miniconda3\lib\site-packages\pymc3\backends\ndarray.py", line 199, in setup
#>     dtype=self.var_dtypes[varname])

^{Создано в 2020-04-27 пакетом представ. (v0.3.0)}

sessionInfo()
#> R version 4.0.0 (2020-04-24)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows 10 x64 (build 18363)
#> 
#> Matrix products: default
#> 
#> locale:
#> [1] LC_COLLATE=English_United States.1252 
#> [2] LC_CTYPE=English_United States.1252   
#> [3] LC_MONETARY=English_United States.1252
#> [4] LC_NUMERIC=C                          
#> [5] LC_TIME=English_United States.1252    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] readr_1.3.1     reticulate_1.15
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.4.6     knitr_1.28       magrittr_1.5     hms_0.5.3       
#>  [5] lattice_0.20-41  R6_2.4.1         rlang_0.4.5      fansi_0.4.1     
#>  [9] stringr_1.4.0    highr_0.8        tools_4.0.0      grid_4.0.0      
#> [13] xfun_0.13        cli_2.0.2        htmltools_0.4.0  ellipsis_0.3.0  
#> [17] assertthat_0.2.1 yaml_2.2.1       digest_0.6.25    tibble_3.0.0    
#> [21] lifecycle_0.2.0  crayon_1.3.4     Matrix_1.2-18    vctrs_0.2.4     
#> [25] curl_4.3         glue_1.4.0       evaluate_0.14    rmarkdown_2.1   
#> [29] stringi_1.4.6    pillar_1.4.3     compiler_4.0.0   jsonlite_1.6.1  
#> [33] pkgconfig_2.0.3