add sex and race groups

app.py

@@ -50,15 +50,15 @@ save_name = "dataset/customized_neuro_synth.csv"
 example_df = pd.read_csv(file_name)
 
 
-def infer(num_sample):
+def infer(sex, race, num_sample):
     num_sample = int(num_sample)
     col_dict = np.load("model/col_dict.npz", allow_pickle=True)['dict'].item()
-    input = np.load("model/kde_white_female.npz", allow_pickle=True)['model'].item()
+    input = np.load("model/kde_{}_{}.npz".format(race.lower(), sex.lower()), allow_pickle=True)['model'].item() # "model/kde_white_female.npz"
     kde, scaler, cols_names = input['model'], input['scaler'], input['columns']
     
     sample = kde.sample(num_sample, random_state=0)
     sample = scaler.inverse_transform(sample)
-    cov_list = np.array([[f'Synth_{i+1}', 'F', 'White'] for i in range(num_sample)])
+    cov_list = np.array([[f'Synth_{i+1}', sex[0], race] for i in range(num_sample)]) # 'F', 'White'
     new_data = np.concatenate([cov_list, sample], axis=1)
     cols=['PTID','Sex','Race','Age']
     cols.extend([col_dict[i] for i in fnmatch.filter(cols_names,'H_*')])
@@ -79,7 +79,22 @@ with gr.Blocks() as demo:
         gr.Markdown("## Customized data generation")
         gr.Interface(
             fn=infer,
-            inputs= [gr.Textbox(
+            inputs= [
+                gr.Radio(
+                choices=['Female', 'Male'],
+                value='Female',
+                type='index',
+                label='Gender',
+                interactive=True,
+                ),
+                gr.Radio(
+                choices=['White', 'Black', 'Asian'],
+                value='Asian',
+                type='index',
+                label='Race',
+                interactive=True,
+                ),
+                gr.Textbox(
                 label='Generate samples',
                 show_label=True,
                 placeholder='Enter sample number (in integer)...'