Merge pull request #6 from Mye-InfoBank/sera/float_issue

Fix float32 JSON serialization

.devcontainer/devcontainer.json

@@ -22,7 +22,7 @@
 				"ms-python.black-formatter"
 			]
 		}
-	},
+	}
 
 	// Configure tool-specific properties.
 	// "customizations": {},

docker-compose.yml

@@ -5,4 +5,4 @@ services:
       dockerfile: Dockerfile
     ports:
       - 8080:8080
-    image: bigdatainbiomedicine/simba-qc:0.2.3
+    image: bigdatainbiomedicine/simba-qc:0.2.4

src/app.py

@@ -3,7 +3,7 @@
 import os
 import tempfile
 import anndata as ad
-import pandas as pd
+import json
 
 from sliders import slider_ui, slider_server
 from distributions import distributions_server
@@ -18,7 +18,6 @@
     'pct_counts_mt': 'Percentage of counts from mitochondrial genes',
 })
 
-
 app_ui = ui.page_navbar(
     ui.nav_panel("1. Upload", ui.input_file("file_input", label="Upload your file", accept=".h5ad")),
     ui.nav_panel("2. Metadata", metadata_ui("metadata")),

src/plots.py

@@ -45,9 +45,9 @@ def plot_scatter():
         fig, ax = plt.subplots()
 
         ax.scatter(
-            adata.obs[x_col],
-            adata.obs[y_col],
-            c=adata.obs[color_col],
+            adata.obs[x_col].astype(float),
+            adata.obs[y_col].astype(float),
+            c=adata.obs[color_col].astype(float),
             s=dot_size,
             cmap="viridis",
         )
@@ -133,10 +133,11 @@ def plot_histograms():
 
         return fig
 
+    @output
     @render.text
     def n_cells():
         adata = _adata.get()
 
         if adata is not None:
-            n_cells = adata.n_obs
+            n_cells = int(adata.n_obs)
             return f"{n_cells} cells pass the current filtering thresholds"

src/sliders.py

@@ -39,7 +39,7 @@ def slider_sample():
         if adata is None:
             return
 
-        n_obs = adata.n_obs
+        n_obs = int(adata.n_obs)
         return ui.input_slider(
             "random_sample_size",
             "Random sample size",
@@ -120,9 +120,9 @@ def slider_filters():
                 absolute = ui.input_slider(
                     f"{col}_absolute",
                     "Absolute value",
-                    distributions[col]["min"],
-                    distributions[col]["max"],
-                    [distributions[col]["min"], distributions[col]["max"]],
+                    float(distributions[col]["min"]),
+                    float(distributions[col]["max"]),
+                    [float(distributions[col]["min"]), float(distributions[col]["max"])],
                 )
                 panel = ui.accordion_panel(pretty_name, mads, absolute)
                 panels.append(panel)
@@ -155,12 +155,12 @@ def update_absolute_by_mads():
                 if mads is None or absolute is None:
                     continue
 
-                min_val = (
+                min_val = float((
                     distributions[col]["median"] - mads * distributions[col]["std"]
-                )
-                max_val = (
+                ))
+                max_val = float((
                     distributions[col]["median"] + mads * distributions[col]["std"]
-                )
+                ))
 
                 ui.update_slider(absolute_name, value=[min_val, max_val])