why it run correctly but no result

[AdotaLover]

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Hi, when I use infercnvpy on my own dataset, the run does not throw an error, and I have also normalized and log1p transformed it normally. However, there are hardly any colors on the heatmap after running my data. Why is this? Is it because my adata structure is wrong or are there other reasons? This is definitely a cancer sample.

---

We provide all immune cell types as "normal cells".

cnv.tl.infercnv(
    adata,
    reference_key="cell_type",
    reference_cat=[
        'B cells',
        'tumor-associated macrophages (TAMs)',
        'tumorassociated endothelial cells (TECs)',
    ],
    window_size=50,
)

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[AdotaLover]

this is my adata:

AnnData object with n_obs × n_vars = 5734 × 18082
    obs: 'n_genes_by_counts', 'log1p_n_genes_by_counts', 'total_counts', 'log1p_total_counts', 'pct_counts_in_top_50_genes', 'pct_counts_in_top_100_genes', 'pct_counts_in_top_200_genes', 'pct_counts_in_top_500_genes', 'total_counts_mt', 'log1p_total_counts_mt', 'pct_counts_mt', 'total_counts_ribo', 'log1p_total_counts_ribo', 'pct_counts_ribo', 'total_counts_hb', 'log1p_total_counts_hb', 'pct_counts_hb', 'n_genes', 'doublet_score', 'predicted_doublet', 'leiden_0.5', 'cell_type', 'leiden_0.8', 'T cell', 'cnv_leiden', 'cnv_score'
    var: 'gene_ids', 'feature_types', 'mt', 'ribo', 'hb', 'n_cells_by_counts', 'mean_counts', 'log1p_mean_counts', 'pct_dropout_by_counts', 'total_counts', 'log1p_total_counts', 'chromosome', 'start', 'end'
    uns: 'scrublet', 'log1p', 'pca', 'neighbors', 'umap', 'leiden', 'leiden_colors', 'rank_genes_groups', 'leiden_0.5_colors', 'cell_type_colors', 'leiden_0.8_colors', 'predicted_doublet_colors', 'cnv', 'cnv_neighbors', 'cnv_leiden', 'cnv_leiden_colors', 'dendrogram_cnv_leiden'
    obsm: 'X_pca', 'X_umap', 'X_cnv', 'X_cnv_pca', 'X_cnv_umap'
    varm: 'PCs'
    layers: 'counts', 'norm_log1p'
    obsp: 'distances', 'connectivities', 'cnv_neighbors_distances', 'cnv_neighbors_connectivities'

[AdotaLover]

this is the onlyone sample？maybe i should concat all the sample from different patients？