extrapolating with predict?

[cascadianaturalist]

I have a set of 30 plots of species presence-absence data that have spatial coordinates and i want to extrapolate to the grid the plots are embedded in (255 plots), when i run predict on the new data frame of 255 I get the following warning and do not know how to proceed.

Thanks!

Error in py_call_impl(callable, call_args$unnamed, call_args$named) :
IndexError: tuple index out of range
Run reticulate::py_last_error() for details.
8.
stop(structure(list(message = "IndexError: tuple index out of range\n\033[90mRun \033]8;;rstudio:run:reticulate::py_last_error()\areticulate::py_last_error()\033]8;;\a for details.\033[39m",
call = py_call_impl(callable, call_args$unnamed, call_args$named)), class = c("python.builtin.IndexError",
"python.builtin.LookupError", "python.builtin.Exception", "python.builtin.BaseException",
"python.builtin.object", "error", "condition"), py_object = ))
7.
MVP_logLik at dist_mvp.py#155
6.
pkg.env$fa$MVP_logLik(cbind(1, Y[, focal]), predictions[, c(K,
focal)], reticulate::py_to_r(object$model$get_sigma)[c(K,
focal), ], device = object$model$device, individual = TRUE,
dtype = object$model$dtype, batch_size = as.integer(object$settings$step_size), ...
5.
py_to_r_cpp(x)
4.
is_py_object(x <- py_to_r_cpp(x))
3.
reticulate::py_to_r(pkg.env$fa$MVP_logLik(cbind(1, Y[, focal]),
predictions[, c(K, focal)], reticulate::py_to_r(object$model$get_sigma)[c(K,
focal), ], device = object$model$device, individual = TRUE,
dtype = object$model$dtype, batch_size = as.integer(object$settings$step_size), ...
2.
predict.sjSDM(model, newdata = NewEnv, SP = NewCoords, Y = NewPA)
1.
predict(model, newdata = NewEnv, SP = NewCoords, Y = NewPA)

[MaximilianPi]

Hi @cascadianaturalist,

could you please show your code?