WARNING: Plotting more than 100 genes might take some while, consider selecting only highly variable genes, for example.
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
TypeError: float() argument must be a string or a real number, not 'csr_matrix'

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

ValueError                                Traceback (most recent call last)
Cell In[85], line 1
----> 1 sc.pl.dpt_timeseries(a1)

File D:\anaconda\Lib\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 D:\anaconda\Lib\site-packages\scanpy\plotting\_tools\__init__.py:245, in dpt_timeseries(adata, color_map, show, save, as_heatmap, marker)
    242 # only if number of genes is not too high
    243 if as_heatmap:
    244     # plot time series as heatmap, as in Haghverdi et al. (2016), Fig. 1d
--> 245     timeseries_as_heatmap(
    246         adata.X[adata.obs["dpt_order_indices"].values],
    247         var_names=adata.var_names,
    248         highlights_x=adata.uns["dpt_changepoints"],
    249         color_map=color_map,
    250     )
    251 else:
    252     # plot time series as gene expression vs time
    253     timeseries(
    254         adata.X[adata.obs["dpt_order_indices"].values],
    255         var_names=adata.var_names,
   (...)
    258         marker=marker,
    259     )

File D:\anaconda\Lib\site-packages\scanpy\plotting\_utils.py:227, in timeseries_as_heatmap(X, var_names, highlights_x, color_map)
    223     x_new[:, _hold:] = X[:, hold:]
    225 _, ax = plt.subplots(figsize=(1.5 * 4, 2 * 4))
    226 img = ax.imshow(
--> 227     np.array(X, dtype=np.float_),
    228     aspect="auto",
    229     interpolation="nearest",
    230     cmap=color_map,
    231 )
    232 plt.colorbar(img, shrink=0.5)
    233 plt.yticks(range(X.shape[0]), var_names)

ValueError: setting an array element with a sequence.

ValueError                                Traceback (most recent call last)
Cell In[91], line 1
----> 1 sc.pl.dpt_groups_pseudotime(a1)

File D:\anaconda\Lib\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 D:\anaconda\Lib\site-packages\scanpy\plotting\_tools\__init__.py:276, in dpt_groups_pseudotime(adata, color_map, palette, show, save, marker)
    274 """Plot groups and pseudotime."""
    275 _, (ax_grp, ax_ord) = plt.subplots(2, 1)
--> 276 timeseries_subplot(
    277     adata.obs["dpt_groups"].cat.codes,
    278     time=adata.obs["dpt_order"].values,
    279     color=np.asarray(adata.obs["dpt_groups"]),
    280     highlights_x=adata.uns["dpt_changepoints"],
    281     ylabel="dpt groups",
    282     yticks=(
    283         np.arange(len(adata.obs["dpt_groups"].cat.categories), dtype=int)
    284         if len(adata.obs["dpt_groups"].cat.categories) < 5
    285         else None
    286     ),
    287     palette=palette,
    288     ax=ax_grp,
    289     marker=marker,
    290 )
    291 timeseries_subplot(
    292     adata.obs["dpt_pseudotime"].values,
    293     time=adata.obs["dpt_order"].values,
   (...)
    301     marker=marker,
    302 )
    303 savefig_or_show("dpt_groups_pseudotime", save=save, show=show)

File D:\anaconda\Lib\site-packages\scanpy\plotting\_utils.py:140, in timeseries_subplot(X, time, color, var_names, highlights_x, xlabel, ylabel, yticks, xlim, legend, palette, color_map, ax, marker)
    138 x_range = np.arange(X.shape[0]) if time is None else time
    139 if X.ndim == 1:
--> 140     X = X[:, None]
    141 if X.shape[1] > 1:
    142     colors = palette[: X.shape[1]].by_key()["color"]

File ~\AppData\Roaming\Python\Python311\site-packages\pandas\core\series.py:1153, in Series.__getitem__(self, key)
   1150     key = np.asarray(key, dtype=bool)
   1151     return self._get_rows_with_mask(key)
-> 1153 return self._get_with(key)

File ~\AppData\Roaming\Python\Python311\site-packages\pandas\core\series.py:1163, in Series._get_with(self, key)
   1158     raise TypeError(
   1159         "Indexing a Series with DataFrame is not "
   1160         "supported, use the appropriate DataFrame column"
   1161     )
   1162 elif isinstance(key, tuple):
-> 1163     return self._get_values_tuple(key)
   1165 elif not is_list_like(key):
   1166     # e.g. scalars that aren't recognized by lib.is_scalar, GH#32684
   1167     return self.loc[key]

File ~\AppData\Roaming\Python\Python311\site-packages\pandas\core\series.py:1203, in Series._get_values_tuple(self, key)
   1198 if com.any_none(*key):
   1199     # mpl compat if we look up e.g. ser[:, np.newaxis];
   1200     #  see tests.series.timeseries.test_mpl_compat_hack
   1201     # the asarray is needed to avoid returning a 2D DatetimeArray
   1202     result = np.asarray(self._values[key])
-> 1203     disallow_ndim_indexing(result)
   1204     return result
   1206 if not isinstance(self.index, MultiIndex):

File ~\AppData\Roaming\Python\Python311\site-packages\pandas\core\indexers\utils.py:341, in disallow_ndim_indexing(result)
    333 """
    334 Helper function to disallow multi-dimensional indexing on 1D Series/Index.
    335 
   (...)
    338 in GH#30588.
    339 """
    340 if np.ndim(result) > 1:
--> 341     raise ValueError(
    342         "Multi-dimensional indexing (e.g. `obj[:, None]`) is no longer "
    343         "supported. Convert to a numpy array before indexing instead."
    344     )

ValueError: Multi-dimensional indexing (e.g. `obj[:, None]`) is no longer supported. Convert to a numpy array before indexing instead.