Open ahucke opened 1 year ago
Looking around, it could be the MOFA2 version that I am using. My RStudio is locked with R 4.1.2, so I will try to find a workaround
Update: gave up on trying on R 4.1 and moved to R 4.2 locally. Did a fresh install of MOFA2 and mofapy2 and now the error moved from scipy to numpy as follows:
Error: AttributeError: module 'numpy' has no attribute 'float'.
np.float
was a deprecated alias for the builtin float
. To avoid this error in existing code, use float
by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.float64
here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
New session info:
Edit: spelling.
Edit: it seems to be an issue when saving the output file. The training was completed.
Another update: tried running with the most recent mofapy2 (version 0.7.0) and got this error:
Edit: previous comment error was with mofapy2 version 0.6.7
I am also having the same problem with R version 4.2.1 :(
i think the "AttributeError: Module 'scipy' has no attribute 'random'" is solved here already reticulate::py_install("scipy==1.7.0") https://github.com/bioFAM/MOFA2/issues/108
I am running into an issue when trying to follow the tutorial provided by the creator. It states that "AttributeError: Module 'scipy' has no attribute 'random'".
This are my python configurations: python: /miniconda3/envs/mofa/bin/python libpython: /miniconda3/envs/mofa/lib/libpython3.11.so pythonhome: /miniconda3/envs/mofa:/miniconda3/envs/mofa version: 3.11.0 | packaged by conda-forge | (main, Jan 14 2023, 12:27:40) [GCC 11.3.0] numpy: /miniconda3/envs/mofa/lib/python3.11/site-packages/numpy numpy_version: 1.24.2
And this is my code:
----message=FALSE------------------------------------------------------------
library(data.table) library(MOFA2) library(reticulate)
Sys.setenv(OMP_NUM_THREADS="1") reticulate::use_condaenv('/miniconda3/envs/mofa/') reticulate::py_config()
-----------------------------------------------------------------------------
data <- make_example_data( n_views = 2, n_samples = 200, n_features = 1000, n_factors = 10 )[[1]]
lapply(data,dim)
----message=FALSE------------------------------------------------------------
MOFAobject <- create_mofa(data)
-----------------------------------------------------------------------------
plot_data_overview(MOFAobject)
----message=FALSE------------------------------------------------------------
N = ncol(data[[1]]) groups = c(rep("A",N/2), rep("B",N/2))
MOFAobject <- create_mofa(data, groups=groups)
-----------------------------------------------------------------------------
plot_data_overview(MOFAobject)
-----------------------------------------------------------------------------
filepath <- system.file("extdata", "test_data.RData", package = "MOFA2") load(filepath)
head(dt)
-----------------------------------------------------------------------------
MOFAobject <- create_mofa(dt) print(MOFAobject)
----out.width = "80%"--------------------------------------------------------
plot_data_overview(MOFAobject)
-----------------------------------------------------------------------------
data_opts <- get_default_data_options(MOFAobject) head(data_opts)
-----------------------------------------------------------------------------
model_opts <- get_default_model_options(MOFAobject) model_opts$num_factors <- 10 head(model_opts)
-----------------------------------------------------------------------------
train_opts <- get_default_training_options(MOFAobject) train_opts
----message=FALSE------------------------------------------------------------
MOFAobject <- prepare_mofa( object = MOFAobject, data_options = data_opts, model_options = model_opts, training_options = train_opts )
-----------------------------------------------------------------------------
outfile = file.path("/MOFA/model.hdf5") MOFAobject.trained <- run_mofa(MOFAobject, outfile)
-----------------------------------------------------------------------------
sessionInfo()
This is the result of sessionInfo: R version 4.1.2 (2021-11-01) Platform: x86_64-pc-linux-gnu (64-bit) Running under: Red Hat Enterprise Linux Server 7.9 (Maipo)
Matrix products: default BLAS: /usr/lib64/libblas.so.3.4.2 LAPACK: /usr/lib64/liblapack.so.3.4.2
locale: [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C LC_TIME=C LC_COLLATE=C LC_MONETARY=C LC_MESSAGES=C
[7] LC_PAPER=C LC_NAME=C LC_ADDRESS=C LC_TELEPHONE=C LC_MEASUREMENT=C LC_IDENTIFICATION=C
attached base packages: [1] stats graphics grDevices utils datasets methods base
other attached packages: [1] BiocManager_1.30.19 RColorBrewer_1.1-3 tibble_3.1.8 ggrepel_0.9.2 dplyr_1.0.10 tidyr_1.2.1
[7] ggplot2_3.4.0 readxl_1.4.1 reticulate_1.28-9000 data.table_1.14.6 MOFA2_1.4.0
loaded via a namespace (and not attached): [1] Rcpp_1.0.10 here_1.0.1 dir.expiry_1.2.0 lattice_0.20-45 png_0.1-8 assertthat_0.2.1
[7] rprojroot_2.0.3 utf8_1.2.2 R6_2.5.1 cellranger_1.1.0 plyr_1.8.8 stats4_4.1.2
[13] pillar_1.8.1 basilisk_1.6.0 rlang_1.0.6 rstudioapi_0.14 S4Vectors_0.32.4 Matrix_1.5-3
[19] Rtsne_0.16 stringr_1.4.1 pheatmap_1.0.12 munsell_0.5.0 uwot_0.1.14 DelayedArray_0.20.0 [25] HDF5Array_1.22.1 compiler_4.1.2 pkgconfig_2.0.3 BiocGenerics_0.40.0 tidyselect_1.2.0 IRanges_2.28.0
[31] matrixStats_0.62.0 fansi_1.0.3 withr_2.5.0 rhdf5filters_1.6.0 basilisk.utils_1.6.0 grid_4.1.2
[37] jsonlite_1.8.4 gtable_0.3.1 lifecycle_1.0.3 DBI_1.1.3 magrittr_2.0.3 scales_1.2.1
[43] cli_3.4.1 stringi_1.7.8 farver_2.1.1 reshape2_1.4.4 filelock_1.0.2 generics_0.1.3
[49] vctrs_0.5.2 cowplot_1.1.1 Rhdf5lib_1.16.0 tools_4.1.2 forcats_0.5.2 glue_1.6.2
[55] purrr_1.0.1 MatrixGenerics_1.9.1 parallel_4.1.2 colorspace_2.0-3 rhdf5_2.38.1 corrplot_0.92
Previously, I ran into an issue that said that I should use the most recent version of mofapy2 (0.6.4) while I was trying to use mofapy2 (0.6.7). I solved this by force installing the requested version with py_install("mofapy2 == 0.6.4").
Thanks for the help!