TypeError: 'tuple' object does not support item assignment and AttributeError: 'LeastActionPath' object has no attribute 'action'

[Mingsenli]

@Xiaojieqiu, Hi, Dr.Qiu： Congratulations on setting up your own independent lab！Looking forward to your better works I am meetting two errors when plotting the kinetic heatmap of the transcription factor expression along LAP. I hope you can help to solve. Thank you very much.

The codes are as follows:

develope_keys = ["adult_LSC->adult_cornea.superficial"]
from dynamo.plot.utils import map2color
def plot_lap(paths):
    fig, ax = plt.subplots(figsize=(5, 4))
    ax = dyn.pl.streamline_plot(
        adata, basis="umap", save_show_or_return="return", ax=ax, color="leiden_anno", frontier=True
    )
    ax = ax[0]
    x, y = 0, 1
    # plot paths
    for path in paths:
        lap_dict = transition_graph[path]["LAP_umap"]
        for prediction, action in zip(lap_dict["prediction"], lap_dict["action"]):
            ax.scatter(*prediction[:, [x, y]].T, c=map2color(action))
            ax.plot(*prediction[:, [x, y]].T, c="k")
plot_lap(develope_keys)

action_df = pd.DataFrame(index=cell_type, columns=cell_type)
t_df = pd.DataFrame(index=cell_type, columns=cell_type)
for i, start in enumerate(
    [
      #E_cornea_basal_cells_indices,
      #E_cornea_superficial_cells_indices,
       adult_LSC_cells_indices,
       adult_cornea_superficial_cells_indices,

    ]
):
    for j, end in enumerate(
        [
         #E_cornea_basal_cells_indices,
         #E_cornea_superficial_cells_indices,
         adult_LSC_cells_indices,
         adult_cornea_superficial_cells_indices,

        ]
    ):
        if start is not end:
            print(cell_type[i] + "->" + cell_type[j], end=",")
            lap = transition_graph[cell_type[i] + "->" + cell_type[j]]["lap"]  # lap
            gtraj = transition_graph[cell_type[i] + "->" + cell_type[j]]["gtraj"]
            ranking = transition_graph[cell_type[i] + "->" + cell_type[j]]["ranking"].copy()
            ranking["TF"] = [i in human_tfs_names for i in list(ranking["all"])]
            genes = ranking.query("TF == True").head(10)["all"].to_list()
            arr = gtraj.select_gene(genes)
            action_df.loc[cell_type[i], cell_type[j]] = lap.action()[-1]
            t_df.loc[cell_type[i], cell_type[j]] = lap.t[-1]

adult_LSC->adult_cornea.superficial,

AttributeError Traceback (most recent call last) Cell In[52], line 29 27 genes = ranking.query("TF == True").head(10)["all"].to_list() 28 arr = gtraj.select_gene(genes) ---> 29 action_df.loc[cell_type[i], cell_type[j]] = lap.action()[-1] 30 t_df.loc[cell_type[i], cell_type[j]] = lap.t[-1]

AttributeError: 'LeastActionPath' object has no attribute 'action'

init_cells = [adata.obs_names[adult_LSC_cells_indices[0][0]]]
target_cells = [adata.obs_names[adult_cornea_superficial_cells_indices[0][0]]]

dyn.configuration.set_pub_style(scaler=0.6)
lap = dyn.pd.least_action(
    adata,
    init_cells=init_cells,
    target_cells=target_cells,
    basis="pca",
    adj_key="cosine_transition_matrix",)

with open("./Homo_sapiens_TF.csv", 'r') as f:
 human_tfs = f.read().splitlines()
human_tfs_names = list(human_tfs)

is_human_tfs = [gene in human_tfs_names for gene in adata.var_names[adata.var.use_for_transition]]
human_genes = adata.var_names[adata.var.use_for_transition][is_human_tfs]
dyn.configuration.set_pub_style(scaler=0.6)
sns.set(font_scale=0.8)
sns_heatmap = dyn.pl.kinetic_heatmap(
    adata,
    basis="pca",
    mode="lap",
    figsize=(10, 5),
    genes=human_genes,
    project_back_to_high_dim=True,
    save_show_or_return="return",
    color_map="bwr",
    transpose=True,
    xticklabels=True,
    yticklabels=False
)
plt.setp(sns_heatmap.ax_heatmap.yaxis.get_majorticklabels(), rotation=0)
plt.tight_layout()

TypeError Traceback (most recent call last) Cell In[55], line 5 3 dyn.configuration.set_pub_style(scaler=0.6) 4 sns.set(font_scale=0.8) ----> 5 sns_heatmap = dyn.pl.kinetic_heatmap( 6 adata, 7 basis="pca", 8 mode="lap", 9 figsize=(10, 5), 10 genes=human_genes, 11 project_back_to_high_dim=True, 12 save_show_or_return="return", 13 color_map="bwr", 14 transpose=True, 15 xticklabels=True, 16 yticklabels=False 17 ) 19 plt.setp(sns_heatmap.ax_heatmap.yaxis.get_majorticklabels(), rotation=0) 20 plt.tight_layout()

File ~/.local/lib/python3.8/site-packages/dynamo/plot/time_series.py:408, in kinetic_heatmap(adata, genes, mode, basis, layer, project_back_to_high_dim, tkey, dist_threshold, color_map, gene_order_method, show_colorbar, cluster_row_col, figsize, standard_scale, n_convolve, spaced_num, traj_ind, log, gene_group, gene_group_cmap, cell_group, cell_group_cmap, enforce, hline_rows, hlines_kwargs, vline_cols, vlines_kwargs, save_show_or_return, save_kwargs, transpose, **kwargs) 406 if transpose: 407 row_colors, col_colors = col_colors, row_colors --> 408 cluster_row_col[0], cluster_row_col[1] = cluster_row_col[1], cluster_row_col[0] 409 df = df.T 411 heatmap_kwargs = dict( 412 xticklabels=False, 413 yticklabels=1, (...) 421 standard_scale=None, 422 )

TypeError: 'tuple' object does not support item assignment

[Sichao25]

Hi, thank you very much for reporting those issues. After looking into it, I've identified some bugs within those functions. I will fix it as soon as possible and keep you updated.

[Sichao25]

Hi @Mingsenli, thank you again for raising those issues. For the first error, you can change the lap.action() to lap.action_t(). We will update the LAP tutorial soon. Sorry for the confusion. The second error will be fixed in this pull request. I also updated the networkx API. You can update networkx version If you have some problems with from_scipy_sparse_matrix/from_scipy_sparse_array. Let me know if you have further questions.

[Mingsenli]

Hi @Sichao25 ,Thank you for your help. I don't understand how to solve the second error. How to update networkx version?

[Sichao25]

Once the pull request has been merged, you can download the latest Dynamo from GitHub and the kinetic_heatmap problem will be gone. If the latest Dynamo raises an error like networkx.convert_matrix has no attribute called from_scipy_sparse_array, you may need to update your networkx version. You can do that by pip install <package_name> -U or conda update <package_name> depending on your environment.

[Mingsenli]

Hi, @Sichao25 , I installed the latest Dynamo from GitHub (v1.3.2), but dyn.pl.kinetic_heatmap still failed to work. The same error was reported.

[Sichao25]

It's because the pull request has not been merged. It will be merged in a few days after review.

[Mingsenli]

Hi, @Sichao25 , I see that the pull request has been merged and I installed the latest Dynamo. But dyn.pl.kinetic_heatmap still failed to work. The same error was reported.

[Sichao25]

I see. Could you tell me how you install the Dynamo? If you are using the v1.3.2 Dynamo, the same error will be reported because the released version is "tagged" on a specific commit. You may need to install it from the latest code or wait for the next release.

[Mingsenli]

I downloaded the latest dynamo-release-master from "code" and the time_series.py in my installation file has been updated as indicated in the Github "pull requests". I installed this newest dynamo in a new enviroment. So it is very strange.

[Mingsenli]

hi @Sichao25, so how can i solve this problem related to dyn.pl.kinetic_heatmap?

[Sichao25]

I see. Is the error message still the same? The kinetic_map works in my environment and Google Colab with Dynamo installed from github. Could you also try using Colab to test it, you can find the link in our readthedocs.

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[github-actions[bot]]

This issue is stale because it has been open 90 days with no activity. Remove stale label or comment or this will be closed in 14 days