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update pandas functions to reduce warnings #12

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18 changes: 6 additions & 12 deletions simba/tools/_pbg.py
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Original file line number Diff line number Diff line change
Expand Up @@ -211,40 +211,35 @@ def gen_graph(list_CP=None,
columns=['alias'],
data=[f'{k}.{x}' for x in range(len(dict_cells[k]))])
settings.pbg_params['entities'][k] = {'num_partitions': 1}
entity_alias = entity_alias.append(dict_df_cells[k],
ignore_index=False)
entity_alias = pd.concat([entity_alias, dict_df_cells[k]], ignore_index=False)
if(len(ids_genes) > 0):
df_genes = pd.DataFrame(
index=ids_genes,
columns=['alias'],
data=[f'{prefix_G}.{x}' for x in range(len(ids_genes))])
settings.pbg_params['entities'][prefix_G] = {'num_partitions': 1}
entity_alias = entity_alias.append(df_genes,
ignore_index=False)
entity_alias = pd.concat([entity_alias, df_genes], ignore_index=False)
if(len(ids_peaks) > 0):
df_peaks = pd.DataFrame(
index=ids_peaks,
columns=['alias'],
data=[f'{prefix_P}.{x}' for x in range(len(ids_peaks))])
settings.pbg_params['entities'][prefix_P] = {'num_partitions': 1}
entity_alias = entity_alias.append(df_peaks,
ignore_index=False)
entity_alias = pd.concat([entity_alias, df_peaks], ignore_index=False)
if(len(ids_kmers) > 0):
df_kmers = pd.DataFrame(
index=ids_kmers,
columns=['alias'],
data=[f'{prefix_K}.{x}' for x in range(len(ids_kmers))])
settings.pbg_params['entities'][prefix_K] = {'num_partitions': 1}
entity_alias = entity_alias.append(df_kmers,
ignore_index=False)
entity_alias = pd.concat([entity_alias, df_kmers], ignore_index=False)
if(len(ids_motifs) > 0):
df_motifs = pd.DataFrame(
index=ids_motifs,
columns=['alias'],
data=[f'{prefix_M}.{x}' for x in range(len(ids_motifs))])
settings.pbg_params['entities'][prefix_M] = {'num_partitions': 1}
entity_alias = entity_alias.append(df_motifs,
ignore_index=False)
entity_alias = pd.concat([entity_alias, df_motifs], ignore_index=False)

# generate edges
dict_graph_stats = dict()
Expand Down Expand Up @@ -405,8 +400,7 @@ def gen_graph(list_CP=None,
{'source': key,
'destination': prefix_G,
'n_edges': df_edges_x.shape[0]}
df_edges = df_edges.append(df_edges_x,
ignore_index=True)
df_edges = pd.concat([df_edges, df_edges_x], ignore_index=True)
settings.pbg_params['relations'].append(
{'name': f'r{id_r}',
'lhs': f'{key}',
Expand Down
15 changes: 4 additions & 11 deletions simba/tools/_post_training.py
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Original file line number Diff line number Diff line change
Expand Up @@ -137,10 +137,7 @@ def embed(self):
percentile = self.percentile
list_percentile = self.list_percentile
X_all = adata_ref.X.copy()
# obs_all = pd.DataFrame(
# data=['ref']*adata_ref.shape[0],
# index=adata_ref.obs.index,
# columns=['id_dataset'])

obs_all = adata_ref.obs.copy()
obs_all['id_dataset'] = ['ref']*adata_ref.shape[0]
for i, adata_query in enumerate(list_adata_query):
Expand Down Expand Up @@ -178,15 +175,11 @@ def embed(self):
n_top=n_top,
)
X_all = np.vstack((X_all, adata_query.layers['softmax']))
# obs_all = obs_all.append(
# pd.DataFrame(
# data=[f'query_{i}']*adata_query.shape[0],
# index=adata_query.obs.index,
# columns=['id_dataset'])
# )

obs_query = adata_query.obs.copy()
obs_query['id_dataset'] = [f'query_{i}']*adata_query.shape[0]
obs_all = obs_all.append(obs_query, ignore_index=False)
obs_all = pd.concat([obs_all, obs_query], ignore_index=False)

adata_all = ad.AnnData(X=X_all,
obs=obs_all)
return adata_all
Expand Down