added formatting, added resolution None error catch

scripts/shinymerfish.py

@@ -110,7 +110,7 @@ def _generate_traces(self) -> None:
         for resolution in self.resolution_keys:
             cluster_dict = {}
             for cluster_id in np.unique(self.gdf[resolution]):
-                cluster = self.gdf.loc[self.gdf[resolution] == cluster_id, 'geometry']
+                cluster = self.gdf.loc[self.gdf[resolution] == cluster_id, 'geometry'].copy()
                 cluster = cluster.geometry.buffer(3).union_all().buffer(-3)
 
                 x_coords, y_coords = extract_polygon_coords(cluster)
@@ -122,6 +122,7 @@ def _generate_traces(self) -> None:
         traces['cells'] = {'x': cells_x_coords, 'y': cells_y_coords}
 
         self.traces = traces
+        self.sdata['table'].uns['traces'] = self.traces
 
     def _differential_expression(self, resolutions: list) -> None:
         """Perform differential expression analysis for each resolution key."""
@@ -131,8 +132,5 @@ def _differential_expression(self, resolutions: list) -> None:
 
     def _export(self, output_path: str) -> None:
         """Export the processed data to the output path."""
-
-        with open(os.path.join(output_path, self.sample + '_traces.json'), 'w') as f:
-            json.dump(self.traces, f)
 
         self.sdata['table'].write_h5ad(os.path.join(output_path, self.sample + '.h5ad'))

src/spaceolotl/fct/expression.py

@@ -4,13 +4,13 @@
 
 def plot_gene_expression(input):  
 
-    spatial_data = get_data(input)
+    adata = get_data(input)
     plot_genes = list(input.select_gene_expression())
 
-    if spatial_data is None or not plot_genes:
+    if adata is None or not plot_genes:
         return
 
-    plot_ex = sc.pl.dotplot(spatial_data['a'],
+    plot_ex = sc.pl.dotplot(adata,
                             var_names = plot_genes,
                             swap_axes = True,
                             groupby = input.select_resolution(),
@@ -26,13 +26,11 @@ def plot_gene_expression(input):
 
 def plot_de(input):  
 
-    spatial_data = get_data(input)
-
-    if spatial_data is None:
-        return
+    if not (adata := get_data(input)):
+        return None
 
     plot_de = sc.pl.rank_genes_groups_dotplot(
-        spatial_data['a'],
+        adata,
         n_genes = input.slider_n_genes(),
         key = 'rank_' + input.select_resolution(),
         min_logfoldchange=input.slider_lfc(),

src/spaceolotl/fct/load.py

@@ -5,16 +5,14 @@
 from spaceolotl._constants import *
 
 def get_data(input):
-        name = input.select_dataset()
-        if not name:
-            return None
 
-        try:
-            adata = sc.read_h5ad(os.path.join(DATA_DIR, name + '.h5ad'))
-            with open(os.path.join(DATA_DIR, name + '_traces.json'), 'r') as f:
-                traces = json.load(f)
-            return {'a': adata, 't': traces}
-
-        except (FileNotFoundError, IOError):
-            print("File not found")
-            return None
+    if not (name := input.select_dataset()):
+        return None
+
+    try:
+        adata = sc.read_h5ad(os.path.join(DATA_DIR, name + '.h5ad'))
+        return adata
+
+    except (FileNotFoundError, IOError):
+        print("File not found")
+        return None

src/spaceolotl/fct/spatial_widget.py

@@ -7,11 +7,10 @@
 
 def plot_space(input):
 
-    if not (spatial_data := get_data(input)):
+    if not get_data(input):
         return None
 
     fig = go.Figure()
-
     fig.update_layout(
         template="plotly_dark",
         showlegend=True,
@@ -20,12 +19,10 @@ def plot_space(input):
         xaxis=dict(title="[mm]"),
         yaxis=dict(title="[mm]")
     )
-
     fig.update_xaxes(
         tickvals=[-1000, 0, 1000],
         ticktext=[-1, 0, 1]
     )
-
     fig.update_yaxes(
         tickvals=[-1000, 0, 1000],
         ticktext=[-1, 0, 1]
@@ -35,19 +32,21 @@ def plot_space(input):
 
 def add_space_clusters(input, widget):
 
-    if not (spatial_data := get_data(input)):
+    if not (adata := get_data(input)):
+        return None
+
+    if not input.select_resolution():
         return None
 
-    p = widget
-    p.data = [trace for trace in p.data if not trace.name.isdigit()]
+    widget.data = [trace for trace in widget.data if not trace.name.isdigit()]
 
     if input.switch_clusters():
 
-        cluster_traces = spatial_data['t'].get(input.select_resolution(), {})
+        cluster_traces = adata.uns['traces'].get(input.select_resolution(), {})
         colors = glasbey.create_palette(palette_size=len(cluster_traces), lightness_bounds=(50, 100))
 
         for color, (cluster_id, cluster_trace) in zip(colors, cluster_traces.items()):
-            p.add_trace(
+            widget.add_trace(
                 go.Scatter(
                     x=cluster_trace['x'],
                     y=cluster_trace['y'],
@@ -61,15 +60,17 @@ def add_space_clusters(input, widget):
 
 def add_space_outlines(input, widget):
 
-    if not (spatial_data := get_data(input)):
+    adata = get_data(input)
+
+    if adata is None:
         return None
 
     p = widget
     p.data = [trace for trace in p.data if trace.name != 'cells']
 
     if input.switch_outlines():
 
-        cell_traces = spatial_data['t']['cells']
+        cell_traces = adata.uns['traces']['cells']
         p.add_trace(
             go.Scatter(
                 name='cells',
@@ -82,20 +83,19 @@ def add_space_outlines(input, widget):
 
 def add_space_expression(input, widget):
 
-    if not (spatial_data := get_data(input)):
+    if not (adata := get_data(input)):
         return None
 
-    p = widget
-    p.data = [trace for trace in p.data if trace.name not in GENES_LABEL]
+    widget.data = [trace for trace in widget.data if trace.name not in GENES_LABEL]
 
     if input.switch_expression() and input.select_gene():
 
         gene_name = input.select_gene().split('-')[1]
-        gene_expression = np.array(spatial_data['a'][:,input.select_gene()].X.flatten())
-        x_coords = spatial_data['a'].obs['x']
-        y_coords = spatial_data['a'].obs['y']
+        gene_expression = np.array(adata[:,input.select_gene()].X.flatten())
+        x_coords = adata.obs['x']
+        y_coords = adata.obs['y']
 
-        p.add_trace(
+        widget.add_trace(
             go.Scatter(
                 name = gene_name,
                 x = x_coords,

src/spaceolotl/fct/umap_widget.py

@@ -1,3 +1,4 @@
+from shiny import ui
 from spaceolotl.fct.load import get_data
 from spaceolotl._constants import GENES_LABEL
 
@@ -7,9 +8,7 @@
 
 def plot_umap(input):
 
-    spatial_data = get_data(input)
-
-    if spatial_data is None:
+    if not get_data(input):
         return None
 
     fig = go.Figure()
@@ -18,25 +17,25 @@ def plot_umap(input):
         showlegend=False,
         autosize=True,
         scene=dict(
-    xaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False),
-    yaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False),
-    zaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False))
+            xaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False),
+            yaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False),
+            zaxis=dict(showgrid=False, showticklabels=False, title='', zeroline=False))
     )
 
     return fig
 
 def add_umap_clusters(input, widget):
-    spatial_data = get_data(input)
-
-    if spatial_data is None:
-        return
+
+    if not (adata := get_data(input)):
+        return None
+
+    if not input.select_resolution():
+        return None
 
-    p = widget
-    p.data = [trace for trace in p.data if not trace.name.isdigit()]
+    widget.data = [trace for trace in widget.data if not trace.name.isdigit()]
 
     if input.switch_clusters():
 
-        adata = spatial_data['a']
         cluster_ids = np.unique(adata.obs[input.select_resolution()])
         colors = glasbey.create_palette(palette_size=len(cluster_ids), lightness_bounds=(50, 100))
 
@@ -46,7 +45,7 @@ def add_umap_clusters(input, widget):
             y_coords = adata.obsm['X_umap'][adata.obs[input.select_resolution()] == cluster_id, 1]
             z_coords = adata.obsm['X_umap'][adata.obs[input.select_resolution()] == cluster_id, 2]
 
-            p.add_trace(
+            widget.add_trace(
                 go.Scatter3d(
                 name = cluster_id,
                 x = x_coords,
@@ -61,24 +60,21 @@ def add_umap_clusters(input, widget):
             )
 
 def add_umap_expression(input, widget):
-    spatial_data = get_data(input)
 
-    if spatial_data is None:
-        return
+    if not (adata := get_data(input)):
+        return None
 
-    adata = spatial_data['a']
-    p = widget
-    p.data = [trace for trace in p.data if trace.name not in GENES_LABEL]
+    widget.data = [trace for trace in widget.data if trace.name not in GENES_LABEL]
 
     if input.switch_expression() and input.select_gene():
 
         gene_name = input.select_gene().split('-')[1]
         gene_expression = np.array(adata[:,input.select_gene()].X.flatten())
-        x_coords = adata.obsm['X_umap'][:,0]
-        y_coords = adata.obsm['X_umap'][:,1]
-        z_coords = adata.obsm['X_umap'][:,2]
+        x_coords = adata.obsm['X_umap'][:, 0]
+        y_coords = adata.obsm['X_umap'][:, 1]
+        z_coords = adata.obsm['X_umap'][:, 2]
 
-        p.add_trace(
+        widget.add_trace(
             go.Scatter3d(
                 name = gene_name,
                 x = x_coords,
@@ -88,9 +84,15 @@ def add_umap_expression(input, widget):
                 marker=dict(
                     color = gene_expression,
                     colorscale = 'Viridis',
-                    size = input.slider_dotsize_umap()
-                ),
-
-
+                    showscale = True,
+                    size = input.slider_dotsize_umap(),
+                    colorbar=dict(
+                        orientation = 'h',
+                        lenmode='fraction',
+                        len=0.25,
+                        thickness=10,
+                        y = 0.05,
+                        x = 0.15)
+                )
             )
         )

src/spaceolotl/js/_format.py

@@ -0,0 +1,6 @@
+from shiny import ui
+
+DROPDOWN_CONFIG = ui.js_eval(
+    '{option: function(item, escape) {return "<div style=\\"font-size: 12px; padding: 5px; display: flex; justify-content: space-between; align-items: center;\\">" + escape(item.label) + "<span style=\\"flex-grow: 1;\\"></span></div>";},'
+    + 'item: function(item, escape) {return "<div style=\\"font-size: 12px; display: flex; justify-content: space-between; align-items: center;\\">" + escape(item.label) + "<span style=\\"flex-grow: 1;\\"></span></div>";}}'
+)

src/spaceolotl/mod/ui.py

@@ -2,6 +2,7 @@
 from shinywidgets import output_widget
 
 from spaceolotl._constants import DATA, GENES, LEIDEN_RESOLUTIONS
+from spaceolotl.js._format import DROPDOWN_CONFIG
 
 app_ui = ui.page_navbar(  
 
@@ -17,24 +18,53 @@
         # Sidebar
         ui.page_sidebar(
             ui.sidebar(
-                ui.input_selectize("select_dataset", "Select dataset", ['', *DATA], selected = None),
-                ui.input_selectize("select_resolution", "Cluster resolution", LEIDEN_RESOLUTIONS),
+                ui.input_selectize(
+                    "select_dataset",
+                    "Select dataset",
+                    ['', *DATA],
+                    selected = None,
+                    options={
+                        "render": DROPDOWN_CONFIG
+                        }
+                    ),
+                ui.input_selectize(
+                    "select_resolution",
+                    "Cluster resolution",
+                    LEIDEN_RESOLUTIONS,
+                    ),
                 ui.input_switch("switch_outlines", "Show cell outlines", False),
                 ui.input_switch("switch_clusters", "Show clusters", True),
-                ui.input_selectize("select_gene", "Select gene", ['', *GENES], selected = None),
+                ui.input_selectize(
+                    "select_gene",
+                    "Select gene",
+                    ['', *GENES],
+                    selected=None,
+                    options={
+                        "render": DROPDOWN_CONFIG
+                        }
+                    ),
                 ui.input_switch("switch_expression", "Plot gene expression", False),
                 ui.input_slider("slider_dotsize_umap", "Slider UMAP", 1, 20, 2),
                 ui.input_slider("slider_dotsize_space", "Slider Space", 1, 20, 2),
-                ui.input_selectize("select_gene_expression", "Select genes", ['', *GENES], selected = None, multiple = True),
+                ui.input_selectize(
+                    "select_gene_expression",
+                    "Select genes",
+                    ['', *GENES],
+                    selected=None,
+                    multiple=True,
+                    options={
+                        "render": DROPDOWN_CONFIG
+                        }
+                    ),
                 ui.input_slider("slider_n_genes", "Slider nGenes", 1, 10, 3),
                 ui.input_slider("slider_lfc", "Slider minLFC", 0.5, 2.5, 0.5, step = 0.1)
 
             ),
             ui.layout_columns(
-                ui.card(
-                    ui.card_header("UMAP Projection"),
-                    output_widget('plot_umap'),
-                    full_screen = True),
+                 ui.card(
+                     ui.card_header("UMAP Projection"),
+                     output_widget('plot_umap'),
+                     full_screen = True),
                 ui.card(
                     ui.card_header("Spatial plot"),
                     output_widget("plot_space"),