Update app.py

app.py

@@ -51,32 +51,32 @@ default_values = {
 interface = gr.Interface(
     fn=demo,
     inputs=[
-        gr.File(label="SPM Upload CSV file", default=None),
-        gr.Textbox(label="SPM identifier_column", default="Identifier"),
-        gr.Textbox(label="SPM sequence_column", default="Sequence"),
-        gr.Dropdown(label="SPM sortby", choices=["S-Support", "I-Support"], default="S-Support"),
-        gr.Number(label="SPM sliding_window_min", default=1),
-        gr.Number(label="SPM sliding_window_max", default=4),
-        gr.Number(label="SPM min_gap", default=1),
-        gr.Number(label="SPM max_gap", default=12),
-        gr.Number(label="SPM S_support_thresh", default=0.4),
-        gr.Number(label="SPM I_support_thresh", default=0),
-        gr.Number(label="SPM dataset_format", default=0),
-        gr.File(label="DSM Upload CSV file for left Dataset", default=None),
-        gr.File(label="DSM Upload CSV file for right Dataset", default=None),
-        gr.Textbox(label="DSM identifier_column", default="Identifier"),
-        gr.Textbox(label="DSM sequence_column", default="Sequence"),
-        gr.Dropdown(label="DSM sortby", choices=["S-Support", "I-Support"], default="S-Support"),
-        gr.Number(label="DSM sliding_window_min", default=1),
-        gr.Number(label="DSM sliding_window_max", default=1),
-        gr.Number(label="DSM min_gap", default=1),
-        gr.Number(label="DSM max_gap", default=12),
-        gr.Number(label="DSM S_support_thresh", default=0.4),
-        gr.Number(label="DSM I_support_thresh", default=0),
-        gr.Number(label="DSM threshold_pvalue", default=0.1),
-        gr.Number(label="DSM dataset_format", default=0),
-        gr.Dropdown(label="DSM test_type", choices=["poisson_means_test", "ttest_ind", "mannwhitneyu", "bws_test", "ranksums", "brunnermunzel", "mood", "ansari", "cramervonmises_2samp", "epps_singleton_2samp", "ks_2samp", "kstest"], default="ttest_ind"),
-        gr.Dropdown(label="Select method for which you want to view result", choices=["SPM", "DSM"], default="DSM")
+        gr.File(label="SPM Upload CSV file"),
+        gr.Textbox(label="SPM identifier_column", value="Identifier"),
+        gr.Textbox(label="SPM sequence_column", value="Sequence"),
+        gr.Dropdown(label="SPM sortby", choices=["S-Support", "I-Support"], value="S-Support"),
+        gr.Number(label="SPM sliding_window_min", value=1),
+        gr.Number(label="SPM sliding_window_max", value=4),
+        gr.Number(label="SPM min_gap", value=1),
+        gr.Number(label="SPM max_gap", value=12),
+        gr.Number(label="SPM S_support_thresh", value=0.4),
+        gr.Number(label="SPM I_support_thresh", value=0),
+        gr.Number(label="SPM dataset_format", value=0),
+        gr.File(label="DSM Upload CSV file for left Dataset", value=None),
+        gr.File(label="DSM Upload CSV file for right Dataset", value=None),
+        gr.Textbox(label="DSM identifier_column", value="Identifier"),
+        gr.Textbox(label="DSM sequence_column", value="Sequence"),
+        gr.Dropdown(label="DSM sortby", choices=["S-Support", "I-Support"], value="S-Support"),
+        gr.Number(label="DSM sliding_window_min", value=1),
+        gr.Number(label="DSM sliding_window_max", value=1),
+        gr.Number(label="DSM min_gap", value=1),
+        gr.Number(label="DSM max_gap", value=12),
+        gr.Number(label="DSM S_support_thresh", value=0.4),
+        gr.Number(label="DSM I_support_thresh", value=0),
+        gr.Number(label="DSM threshold_pvalue", value=0.1),
+        gr.Number(label="DSM dataset_format", value=0),
+        gr.Dropdown(label="DSM test_type", choices=["poisson_means_test", "ttest_ind", "mannwhitneyu", "bws_test", "ranksums", "brunnermunzel", "mood", "ansari", "cramervonmises_2samp", "epps_singleton_2samp", "ks_2samp", "kstest"], value="ttest_ind"),
+        gr.Dropdown(label="Select method for which you want to view result", choices=["SPM", "DSM"], value="DSM")
     ],
     outputs=[gr.File(label="SPM result"), gr.File(label="DSM result"), "dataframe"],
     title="SPM And DSM Implementation in Python"