Getting "TypeError: Topology argument required to make Universe" when clustering a universe from sliced trajectory

[leffetripel]

Expected behavior

Getting a clustered trajectory from a universe.

Actual behavior

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[129], line 10
      6 p = u.select_atoms('protein')
      7 protein = mda.Merge(p).load_new(
      8     AnalysisFromFunction(lambda ag: ag.positions.copy(),p).run(step=2).results['timeseries']) 
---> 10 encore.cluster([protein,])

File ~/miniconda3/envs/bpti/lib/python3.9/site-packages/mdaencore/clustering/cluster.py:163, in cluster(ensembles, method, select, distance_matrix, allow_collapsed_result, ncores, **kwargs)
    161         for ensemble in ensembles:
    162             ensemble.transfer_to_memory()
--> 163         merged_ensembles.append(merge_universes(ensembles))
    165 methods = method
    166 if not hasattr(method, '__iter__'):

File ~/miniconda3/envs/bpti/lib/python3.9/site-packages/mdaencore/utils.py:404, in merge_universes(universes)
    401 for universe in universes:
    402     universe.transfer_to_memory()
--> 404 return mda.Universe(
    405     universes[0].filename,
    406     np.concatenate(tuple([e.trajectory.timeseries(order='fac') for e in universes]),
    407                    axis=0),
    408     format=MemoryReader)

File ~/miniconda3/envs/bpti/lib/python3.9/site-packages/MDAnalysis/core/universe.py:364, in Universe.__init__(self, topology, all_coordinates, format, topology_format, transformations, guess_bonds, vdwradii, fudge_factor, lower_bound, in_memory, in_memory_step, *coordinates, **kwargs)
    361     self._topology = topology
    362 else:
    363     # point to Universe.empty instead of making empty universe
--> 364     raise TypeError('Topology argument required to make Universe. '
    365                     'Try Universe.empty(n_atoms, ...) to construct '
    366                     'your own Universe.')
    368 _generate_from_topology(self)  # make real atoms, res, segments
    370 coordinates = _resolve_coordinates(self.filename, *coordinates,
    371                                    format=format,
    372                                    all_coordinates=all_coordinates)

TypeError: Topology argument required to make Universe. Try Universe.empty(n_atoms, ...) to construct your own Universe.

Code to reproduce the behavior

from MDAnalysisTests.datafiles import TPR, TRR
import MDAnalysis as mda
import mdaencore as encore

u = mda.Universe(TPR,TRR)
p = u.select_atoms('protein')
protein = mda.Merge(p).load_new(
    AnalysisFromFunction(lambda ag: ag.positions.copy(),p).run(step=2).results['timeseries']) 

encore.cluster([protein,])

Current environment

• Which version are you using? mdaencore 1.0.0 py39h44dd56e_0 conda-forge
• Which version of Python (python -V)? Python 3.9.18
• Which operating system? linux
• If you use conda, what is the output of conda list?

Name Version Build Channel

_libgcc_mutex 0.1 conda_forge conda-forge
_openmp_mutex 4.5 2_gnu conda-forge
aiohttp 3.8.6 py39hd1e30aa_1 conda-forge
aiohttp-retry 2.8.3 pyhd8ed1ab_0 conda-forge
aiosignal 1.3.1 pyhd8ed1ab_0 conda-forge
alsa-lib 1.2.10 hd590300_0 conda-forge
amqp 5.2.0 pyhd8ed1ab_0 conda-forge
annotated-types 0.6.0 pyhd8ed1ab_0 conda-forge
antlr-python-runtime 4.9.3 pyhd8ed1ab_1 conda-forge
anyio 4.0.0 pyhd8ed1ab_0 conda-forge
appdirs 1.4.4 pyh9f0ad1d_0 conda-forge
argon2-cffi 23.1.0 pyhd8ed1ab_0 conda-forge
argon2-cffi-bindings 21.2.0 py39hd1e30aa_4 conda-forge
arrow 1.3.0 pyhd8ed1ab_0 conda-forge
asttokens 2.4.1 pyhd8ed1ab_0 conda-forge
async-lru 2.0.4 pyhd8ed1ab_0 conda-forge
async-timeout 4.0.3 pyhd8ed1ab_0 conda-forge
asyncssh 2.14.0 pyhd8ed1ab_0 conda-forge
atk-1.0 2.38.0 hd4edc92_1 conda-forge
atpublic 3.0.1 pyhd8ed1ab_0 conda-forge
attr 2.5.1 h166bdaf_1 conda-forge
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aws-c-common 0.9.8 hd590300_0 conda-forge
aws-c-compression 0.2.17 hfd9eb17_6 conda-forge
aws-c-event-stream 0.3.2 hae413d4_6 conda-forge
aws-c-http 0.7.14 h162056d_1 conda-forge
aws-c-io 0.13.35 hc23c90e_8 conda-forge
aws-c-mqtt 0.9.9 h1387108_0 conda-forge
aws-c-s3 0.3.23 h7630044_1 conda-forge
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qtpy 2.4.1 pyhd8ed1ab_0 conda-forge
rdma-core 28.9 h59595ed_1 conda-forge
re2 2023.06.02 h2873b5e_0 conda-forge
readline 8.2 h8228510_1 conda-forge
referencing 0.30.2 pyhd8ed1ab_0 conda-forge
requests 2.31.0 pyhd8ed1ab_0 conda-forge
rfc3339-validator 0.1.4 pyhd8ed1ab_0 conda-forge
rfc3986-validator 0.1.1 pyh9f0ad1d_0 conda-forge
rich 13.6.0 pyhd8ed1ab_0 conda-forge
rpds-py 0.12.0 py39h9fdd4d6_0 conda-forge
ruamel.yaml 0.18.5 py39hd1e30aa_0 conda-forge
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s2n 1.3.56 h06160fa_0 conda-forge
scikit-learn 1.3.2 py39ha22ef79_1 conda-forge
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semver 3.0.2 pyhd8ed1ab_0 conda-forge
send2trash 1.8.2 pyh41d4057_0 conda-forge
setuptools 68.2.2 pyhd8ed1ab_0 conda-forge
shellingham 1.5.4 pyhd8ed1ab_0 conda-forge
shortuuid 1.0.11 pyhd8ed1ab_0 conda-forge
shtab 1.6.4 pyhd8ed1ab_1 conda-forge
sip 6.7.12 py39h3d6467e_0 conda-forge
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sniffio 1.3.0 pyhd8ed1ab_0 conda-forge
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sqlite 3.44.0 h2c6b66d_0 conda-forge
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xcb-util-image 0.4.0 h8ee46fc_1 conda-forge
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zlib 1.2.13 hd590300_5 conda-forge
zstd 1.5.5 hfc55251_0 conda-forge

[orbeckst]

It looks as if mdaencore expect a Universe with an underlying topology file as opposed to a custom Universe. Does it work if you first write out to a temporary file

protein.atoms.write("protein.gro")
protein.atoms.write("protein.dcd", frames="all")

p = mda.Universe("protein.gro", "protein.dcd")
encore.cluster([p,])