Installation issues on linux machine

[chiwwong]

I use conda for managing packages but the stLearn seems to have some dependencies (numpy >1.18, <1.22) that were outdated, while I used numpy=1.26.4.

conda install -c conda-forge stlearn=0.4.11
Channels:
 - conda-forge
 - bioconda
 - defaults
Platform: linux-64
Collecting package metadata (repodata.json): done
Solving environment: - warning  libmamba Added empty dependency for problem type SOLVER_RULE_UPDATE
failed

LibMambaUnsatisfiableError: Encountered problems while solving:
  - package stlearn-0.4.11-pyhd8ed1ab_0 requires numpy >=1.18,<1.22, but none of the providers can be installed

Could not solve for environment specs
The following packages are incompatible
├─ pin-1 is installable and it requires
│  └─ python 3.12.* , which can be installed;
└─ stlearn 0.4.11**  is not installable because it requires
   └─ numpy >=1.18,<1.22  but there are no viable options
      ├─ numpy [1.18.1|1.18.4|...|1.19.5] would require
      │  └─ python >=3.6,<3.7.0a0 , which conflicts with any installable versions previously reported;
      ├─ numpy [1.18.1|1.18.4|...|1.21.6] would require
      │  └─ python >=3.7,<3.8.0a0 , which conflicts with any installable versions previously reported;
      ├─ numpy [1.18.1|1.18.4|...|1.21.6] would require
      │  └─ python >=3.8,<3.9.0a0 , which conflicts with any installable versions previously reported;
      ├─ numpy [1.19.2|1.19.4|...|1.21.6] would require
      │  └─ python >=3.9,<3.10.0a0 , which conflicts with any installable versions previously reported;
      └─ numpy [1.21.2|1.21.3|1.21.4|1.21.5|1.21.6] would require
         └─ python >=3.10,<3.11.0a0 , which conflicts with any installable versions previously reported.

Pins seem to be involved in the conflict. Currently pinned specs:
 - python 3.12.* (labeled as 'pin-1')

But I can confirm a successful installation after forcing the python back to 3.10 (from 3.12.2).

[duypham2108]

Thank you for reporting it. We will update all the dependencies soon

[chiwwong]

@duypham2108 I would also like to know how to save the PSTS analysis with adata. The following code does not work:
adata.write_h5ad("adata_after_StLean_PSTS.h5ad",compression='gzip')

---

TypeError Traceback (most recent call last)
File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:246, in report_write_key_on_error..func_wrapper(*args, **kwargs)
245 try:
--> 246 return func(*args, **kwargs)
247 except Exception as e:

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:280, in Writer.write_elem(self, store, k, elem, dataset_kwargs, modifiers)
279 # Normalize k to abosulte path
--> 280 if not PurePosixPath(k).is_absolute():
281 k = str(PurePosixPath(store.name) / k)

File /miniconda3/envs/spatial.p/lib/python3.8/pathlib.py:651, in PurePath.new(cls, *args)
650 cls = PureWindowsPath if os.name == 'nt' else PurePosixPath
--> 651 return cls._from_parts(args)

File /miniconda3/envs/spatial.p/lib/python3.8/pathlib.py:683, in PurePath._from_parts(cls, args, init)
682 self = object.new(cls)
--> 683 drv, root, parts = self._parse_args(args)
684 self._drv = drv

File /miniconda3/envs/spatial.p/lib/python3.8/pathlib.py:667, in PurePath._parse_args(cls, args)
666 else:
--> 667 a = os.fspath(a)
668 if isinstance(a, str):
669 # Force-cast str subclasses to str (issue #21127)

TypeError: expected str, bytes or os.PathLike object, not int

The above exception was the direct cause of the following exception:

TypeError Traceback (most recent call last)
Cell In[67], line 1
----> 1 adata.write_h5ad("adata_after_StLean_PSTS.h5ad",compression='gzip')

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_core/anndata.py:1959, in AnnData.write_h5ad(self, filename, compression, compression_opts, as_dense)
1956 if filename is None:
1957 filename = self.filename
-> 1959 _write_h5ad(
1960 Path(filename),
1961 self,
1962 compression=compression,
1963 compression_opts=compression_opts,
1964 as_dense=as_dense,
1965 )
1967 if self.isbacked:
1968 self.file.filename = filename

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/h5ad.py:99, in write_h5ad(filepath, adata, as_dense, dataset_kwargs, **kwargs)
97 write_elem(f, "varp", dict(adata.varp), dataset_kwargs=dataset_kwargs)
98 write_elem(f, "layers", dict(adata.layers), dataset_kwargs=dataset_kwargs)
---> 99 write_elem(f, "uns", dict(adata.uns), dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:353, in write_elem(store, k, elem, dataset_kwargs)
329 def write_elem(
330 store: GroupStorageType,
331 k: str,
(...)
334 dataset_kwargs: Mapping = MappingProxyType({}),
335 ) -> None:
336 """
337 Write an element to a storage group using anndata encoding.
338
(...)
351 E.g. for zarr this would be chunks, compressor.
352 """
--> 353 Writer(_REGISTRY).write_elem(store, k, elem, dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:248, in report_write_key_on_error..func_wrapper(*args, **kwargs)
246 return func(*args, **kwargs)
247 except Exception as e:
--> 248 re_raise_error(e, elem, key)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:246, in report_write_key_on_error..func_wrapper(*args, **kwargs)
244 break
245 try:
--> 246 return func(*args, **kwargs)
247 except Exception as e:
248 re_raise_error(e, elem, key)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:311, in Writer.write_elem(self, store, k, elem, dataset_kwargs, modifiers)
302 return self.callback(
303 write_func,
304 store,
(...)
308 iospec=self.registry.get_spec(elem),
309 )
310 else:
--> 311 return write_func(store, k, elem, dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:52, in write_spec..decorator..wrapper(g, k, *args, **kwargs)
50 @wraps(func)
51 def wrapper(g, k, *args, **kwargs):
---> 52 result = func(g, k, *args, **kwargs)
53 g[k].attrs.setdefault("encoding-type", spec.encoding_type)
54 g[k].attrs.setdefault("encoding-version", spec.encoding_version)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/methods.py:281, in write_mapping(f, k, v, _writer, dataset_kwargs)
279 g = f.create_group(k)
280 for sub_k, sub_v in v.items():
--> 281 _writer.write_elem(g, sub_k, sub_v, dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:248, in report_write_key_on_error..func_wrapper(*args, **kwargs)
246 return func(*args, **kwargs)
247 except Exception as e:
--> 248 re_raise_error(e, elem, key)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:246, in report_write_key_on_error..func_wrapper(*args, **kwargs)
244 break
245 try:
--> 246 return func(*args, **kwargs)
247 except Exception as e:
248 re_raise_error(e, elem, key)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:311, in Writer.write_elem(self, store, k, elem, dataset_kwargs, modifiers)
302 return self.callback(
303 write_func,
304 store,
(...)
308 iospec=self.registry.get_spec(elem),
309 )
310 else:
--> 311 return write_func(store, k, elem, dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/registry.py:52, in write_spec..decorator..wrapper(g, k, *args, **kwargs)
50 @wraps(func)
51 def wrapper(g, k, *args, **kwargs):
---> 52 result = func(g, k, *args, **kwargs)
53 g[k].attrs.setdefault("encoding-type", spec.encoding_type)
54 g[k].attrs.setdefault("encoding-version", spec.encoding_version)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/specs/methods.py:281, in write_mapping(f, k, v, _writer, dataset_kwargs)
279 g = f.create_group(k)
280 for sub_k, sub_v in v.items():
--> 281 _writer.write_elem(g, sub_k, sub_v, dataset_kwargs=dataset_kwargs)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:248, in report_write_key_on_error..func_wrapper(*args, **kwargs)
246 return func(*args, **kwargs)
247 except Exception as e:
--> 248 re_raise_error(e, elem, key)

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/anndata/_io/utils.py:229, in report_write_key_on_error..re_raise_error(e, elem, key)
227 else:
228 parent = _get_parent(elem)
--> 229 raise type(e)(
230 f"{e}\n\n"
231 f"Above error raised while writing key {key!r} of {type(elem)} "
232 f"to {parent}"
233 ) from e

TypeError: expected str, bytes or os.PathLike object, not int

Above error raised while writing key 6 of <class 'h5py._hl.group.Group'> to /

[chiwwong]

I found that the clade ID can be saved but not the arrows. Maybe something else is not saved too, but not sure.

(Sorry, I have recently joined the Python family from R, not very sure how to debug Python yet).

adata = sc.read_h5ad('adata_after_StLean_PSTS.h5ad')
st.pl.cluster_plot(
    adata,
    use_label="leiden",
    show_trajectories=True,
    list_clusters=["0","2"],
    show_subcluster=True,
    zoom_coord=[4500,7000,6500,4000],
    show_node=False
)

---

ValueError Traceback (most recent call last)
Cell In[9], line 1
----> 1 st.pl.cluster_plot(
2 adata,
3 use_label="leiden",
4 show_trajectories=True,
5 list_clusters=["0","2"],
6 show_subcluster=True,
7 zoom_coord=[4500,7000,6500,4000],
8 show_node=False
9 )

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/stlearn/plotting/cluster_plot.py:87, in cluster_plot(adata, title, figsize, cmap, use_label, list_clusters, ax, fig, show_plot, show_axis, show_image, show_color_bar, zoom_coord, crop, margin, size, image_alpha, cell_alpha, fname, dpi, show_subcluster, show_cluster_labels, show_trajectories, reverse, show_node, threshold_spots, text_box_size, color_bar_size, bbox_to_anchor, trajectory_node_size, trajectory_alpha, trajectory_width, trajectory_edge_color, trajectory_arrowsize)
65 """
66 Allows the visualization of a cluster results as the discretes values
67 of dot points in the Spatial transcriptomics array. We also support to
(...)
82
83 """
85 assert use_label != None, "Please select use_label parameter"
---> 87 ClusterPlot(
88 adata,
89 title=title,
90 figsize=figsize,
91 cmap=cmap,
92 use_label=use_label,
93 list_clusters=list_clusters,
94 ax=ax,
95 fig=fig,
96 show_plot=show_plot,
97 show_axis=show_axis,
98 show_image=show_image,
99 show_color_bar=show_color_bar,
100 zoom_coord=zoom_coord,
101 crop=crop,
102 margin=margin,
103 size=size,
104 image_alpha=image_alpha,
105 cell_alpha=cell_alpha,
106 fname=fname,
107 dpi=dpi,
108 show_subcluster=show_subcluster,
109 show_cluster_labels=show_cluster_labels,
110 show_trajectories=show_trajectories,
111 reverse=reverse,
112 show_node=show_node,
113 threshold_spots=threshold_spots,
114 text_box_size=text_box_size,
115 color_bar_size=color_bar_size,
116 bbox_to_anchor=bbox_to_anchor,
117 trajectory_node_size=trajectory_node_size,
118 trajectory_alpha=trajectory_alpha,
119 trajectory_width=trajectory_width,
120 trajectory_edge_color=trajectory_edge_color,
121 trajectory_arrowsize=trajectory_arrowsize,
122 )

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/stlearn/plotting/classes.py:713, in ClusterPlot.init(self, adata, title, figsize, cmap, use_label, list_clusters, ax, fig, show_plot, show_axis, show_image, show_color_bar, crop, zoom_coord, margin, size, image_alpha, cell_alpha, fname, dpi, show_subcluster, show_cluster_labels, show_trajectories, reverse, show_node, threshold_spots, text_box_size, color_bar_size, bbox_to_anchor, trajectory_node_size, trajectory_alpha, trajectory_width, trajectory_edge_color, trajectory_arrowsize)
710 self.trajectory_edge_color = trajectory_edge_color
711 self.trajectory_arrowsize = trajectory_arrowsize
--> 713 self._add_trajectories()
715 if fname != None:
716 self._save_output()

File /miniconda3/envs/spatial.p/lib/python3.8/site-packages/stlearn/plotting/classes.py:907, in ClusterPlot._add_trajectories(self)
904 cmap = plt.get_cmap(cmaps)
906 if "PTS_graph" not in self.adata[0].uns:
--> 907 raise ValueError("Please run stlearn.spatial.trajectory.pseudotimespace!")
909 tmp = _read_graph(self.adata[0], "PTS_graph")
911 G = tmp.copy()

ValueError: Please run stlearn.spatial.trajectory.pseudotimespace!

[duypham2108]

Yes, I know this issue but I haven't solved it yet.
You can try to save with pickle like this
#262 (comment)

[chiwwong]

That works for me. Thanks!

Btw, I wonder if the st.spatial.trajectory.pseudotime can be accelerated by multi-thread? It takes a long time to compute for large clusters/datasets (e.g. 90253 nodes). (I also wonder if I did anything wrong if the program is still running after I have waited for 2 hours without).