Fix float32 JSON serialization

.devcontainer/devcontainer.json

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

src/app.py

@@ -3,7 +3,8 @@
 import os
 import tempfile
 import anndata as ad
-import pandas as pd
+import json
+import numpy as np
 
 from sliders import slider_ui, slider_server
 from distributions import distributions_server
@@ -12,13 +13,36 @@
 from helpers import calculate_qc_metrics
 
 
+def convert_float32_to_float(data):
+    if isinstance(data, dict):
+        #print('dict')
+        return {k: convert_float32_to_float(v) for k, v in data.items()}
+    elif isinstance(data, list):
+        #print('list')
+        return [convert_float32_to_float(v) for v in data]
+    elif isinstance(data, np.float32) or isinstance(data, np.float64):
+        #print(f"Converting {data} to float")
+        return float(data)
+    elif isinstance(data, np.ndarray):
+        #print('ndarray')
+        return data.tolist()
+    return data
+
+# Monkey-patch json.dumps
+original_json_dumps = json.dumps
+
+def custom_json_dumps(data, *args, **kwargs):
+    non_float_32_data = convert_float32_to_float(data)
+    return original_json_dumps(non_float_32_data, *args, **kwargs)
+
+json.dumps = custom_json_dumps
+
 _pretty_names = reactive.value({
     'total_counts': 'Total counts',
     'n_genes_by_counts': 'Number of genes with counts',
     '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)