sc.pl.paga_path error in dimensions of array passed to ax.imshow #3025
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What happened?
sc.pl.paga_path is supposed to output a heatmap. However, with the default parameter n_avg=1, the plotting fails. Internally, the function passes an array X,
X = np.asarray(X).squeeze()to ax.imshowimg = ax.imshow(X, aspect="auto", interpolation="nearest", cmap=color_map). X is one dimensional because of the squeeze() and imshow only accepts 2d arrays. It's fixed for n_avg=1 when squeeze is removed but still fails when n_avg is other numbersMinimal code sample
Error output
TypeError Traceback (most recent call last) Cell In[1], line 15 13 import matplotlib.pyplot as plt 14 fig,ax=plt.subplots(1,1,figsize=(7,1)) ---> 15 path_data = sc.pl.paga_path( 16 adata, 17 [4, 5], 18 ["Elane"], 19 ax=ax, 20 show_node_names=False, 21 ytick_fontsize=12, 22 return_data=True, 23 #n_avg=1, 24 color_map="Greys", 25 groups_key="leiden", 26 color_maps_annotations={"dpt_pseudotime": "viridis"} 27 ) File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\legacy_api_wrap\__init__.py:80, in legacy_api.<locals>.wrapper.<locals>.fn_compatible(*args_all, **kw) 77 @wraps(fn) 78 def fn_compatible(*args_all: P.args, **kw: P.kwargs) -> R: 79 if len(args_all) <= n_positional: ---> 80 return fn(*args_all, **kw) 82 args_pos: P.args 83 args_pos, args_rest = args_all[:n_positional], args_all[n_positional:] File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\scanpy\plotting\_tools\paga.py:1255, in paga_path(adata, nodes, keys, use_raw, annotations, color_map, color_maps_annotations, palette_groups, n_avg, groups_key, xlim, title, left_margin, ytick_fontsize, title_fontsize, show_node_names, show_yticks, show_colorbar, legend_fontsize, legend_fontweight, normalize_to_zero_one, as_heatmap, return_data, show, save, ax) 1253 print(X.shape) 1254 if as_heatmap: -> 1255 img = ax.imshow(X, aspect="auto", interpolation="nearest", cmap=color_map) 1256 if show_yticks: 1257 ax.set_yticks(range(len(X))) File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\matplotlib\__init__.py:1459, in _preprocess_data.<locals>.inner(ax, data, *args, **kwargs) 1456 @functools.wraps(func) 1457 def inner(ax, *args, data=None, **kwargs): 1458 if data is None: -> 1459 return func(ax, *map(sanitize_sequence, args), **kwargs) 1461 bound = new_sig.bind(ax, *args, **kwargs) 1462 auto_label = (bound.arguments.get(label_namer) 1463 or bound.kwargs.get(label_namer)) File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\matplotlib\axes\_axes.py:5665, in Axes.imshow(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, interpolation_stage, filternorm, filterrad, resample, url, **kwargs) 5657 self.set_aspect(aspect) 5658 im = mimage.AxesImage(self, cmap=cmap, norm=norm, 5659 interpolation=interpolation, origin=origin, 5660 extent=extent, filternorm=filternorm, 5661 filterrad=filterrad, resample=resample, 5662 interpolation_stage=interpolation_stage, 5663 **kwargs) -> 5665 im.set_data(X) 5666 im.set_alpha(alpha) 5667 if im.get_clip_path() is None: 5668 # image does not already have clipping set, clip to axes patch File ~\AppData\Local\Packages\PythonSoftwareFoundation.Python.3.11_qbz5n2kfra8p0\LocalCache\local-packages\Python311\site-packages\matplotlib\image.py:710, in _ImageBase.set_data(self, A) 706 self._A = self._A[:, :, 0] 708 if not (self._A.ndim == 2 709 or self._A.ndim == 3 and self._A.shape[-1] in [3, 4]): --> 710 raise TypeError("Invalid shape {} for image data" 711 .format(self._A.shape)) 713 if self._A.ndim == 3: 714 # If the input data has values outside the valid range (after 715 # normalisation), we issue a warning and then clip X to the bounds 716 # - otherwise casting wraps extreme values, hiding outliers and 717 # making reliable interpretation impossible. 718 high = 255 if np.issubdtype(self._A.dtype, np.integer) else 1 TypeError: Invalid shape (633,) for image dataVersions
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