a small BUG in mu.tl.mofa

[liujilei156231]

when

import jax
import numpy as np
import anndata as ad
import muon as mu
from muon import MuData

z = jax.random.normal(key=jax.random.PRNGKey(1), shape=(100,3)) * jax.numpy.array([2, 3, 4])
w = jax.random.normal(key=jax.random.PRNGKey(1), shape=(3,200))
y = z @ w

a1 = ad.AnnData(np.array(y[:,:150]))
a2 = ad.AnnData(np.array(y[:,150:]))
mdata = MuData({"a1": a1, "a2": a2})
mdata.var_names_make_unique()

mdata.obs["group"] = jax.random.choice(key=jax.random.PRNGKey(1), a=jax.numpy.array([0, 1]), shape=(100,))
mdata.obs.group = mdata.obs.group.astype("category")
mu.tl.mofa(mdata, groups_label="group")

        #########################################################
        ###           __  __  ____  ______                    ###
        ###          |  \/  |/ __ \|  ____/\    _             ###
        ###          | \  / | |  | | |__ /  \ _| |_           ###
        ###          | |\/| | |  | |  __/ /\ \_   _|          ###
        ###          | |  | | |__| | | / ____ \|_|            ###
        ###          |_|  |_|\____/|_|/_/    \_\              ###
        ###                                                   ###
        #########################################################



Loaded view='a1' group='0' with N=59 samples and D=150 features...
Loaded view='a1' group='1' with N=41 samples and D=150 features...
Loaded view='a2' group='0' with N=59 samples and D=50 features...
Loaded view='a2' group='1' with N=41 samples and D=50 features...


Model options:
- Automatic Relevance Determination prior on the factors: True
- Automatic Relevance Determination prior on the weights: True
- Spike-and-slab prior on the factors: False
- Spike-and-slab prior on the weights: True
Likelihoods:
- View 0 (a1): gaussian
- View 1 (a2): gaussian




######################################
## Training the model with seed 1 ##
######################################



Converged!



#######################
## Training finished ##
#######################


Saving model in /tmp/mofa_20220802-101431.hdf5...
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Input In [6], in <cell line: 15>()
     13 mdata.obs["group"] = jax.random.choice(key=jax.random.PRNGKey(1), a=jax.numpy.array([0, 1]), shape=(100,))
     14 mdata.obs.group = mdata.obs.group.astype("category")
---> 15 mu.tl.mofa(mdata, groups_label="group")

File ~/miniconda3/envs/scvi-env/lib/python3.9/site-packages/muon/_core/tools.py:581, in mofa(data, groups_label, use_raw, use_layer, use_var, use_obs, likelihoods, n_factors, scale_views, scale_groups, center_groups, ard_weights, ard_factors, spikeslab_weights, spikeslab_factors, n_iterations, convergence_mode, gpu_mode, use_float32, smooth_covariate, smooth_warping, smooth_kwargs, save_parameters, save_data, save_metadata, seed, outfile, expectations, save_interrupted, verbose, quiet, copy)
    579 else:
    580     if groups_label:
--> 581         z = pd.DataFrame(z, index=zs).loc[mdata.obs.index.values].to_numpy()
    582     data.obsm["X_mofa"] = z
    584 # Weights

File ~/miniconda3/envs/scvi-env/lib/python3.9/site-packages/pandas/core/frame.py:694, in DataFrame.__init__(self, data, index, columns, dtype, copy)
    684         mgr = dict_to_mgr(
    685             # error: Item "ndarray" of "Union[ndarray, Series, Index]" has no
    686             # attribute "name"
   (...)
    691             typ=manager,
    692         )
    693     else:
--> 694         mgr = ndarray_to_mgr(
    695             data,
    696             index,
    697             columns,
    698             dtype=dtype,
    699             copy=copy,
    700             typ=manager,
    701         )
    703 # For data is list-like, or Iterable (will consume into list)
    704 elif is_list_like(data):

File ~/miniconda3/envs/scvi-env/lib/python3.9/site-packages/pandas/core/internals/construction.py:351, in ndarray_to_mgr(values, index, columns, dtype, copy, typ)
    346 # _prep_ndarray ensures that values.ndim == 2 at this point
    347 index, columns = _get_axes(
    348     values.shape[0], values.shape[1], index=index, columns=columns
    349 )
--> 351 _check_values_indices_shape_match(values, index, columns)
    353 if typ == "array":
    355     if issubclass(values.dtype.type, str):

File ~/miniconda3/envs/scvi-env/lib/python3.9/site-packages/pandas/core/internals/construction.py:418, in _check_values_indices_shape_match(values, index, columns)
    414 if values.shape[1] != len(columns) or values.shape[0] != len(index):
    415     # Could let this raise in Block constructor, but we get a more
    416     #  helpful exception message this way.
    417     if values.shape[0] == 0:
--> 418         raise ValueError("Empty data passed with indices specified.")
    420     passed = values.shape
    421     implied = (len(index), len(columns))

ValueError: Empty data passed with indices specified.

HOWEVER,

mdata.obs.group = mdata.obs.group.astype(str)

can run !

So,it is a type error.

[gtca]

Thanks @liujilei156231, I can reproduce this, will fix it for the next release.