Only show config if dataset is present

MannLabs · Sep 10, 2024 · fa23c20 · fa23c20
1 parent f477837
commit fa23c20
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Showing 2 changed files with 15 additions and 17 deletions.
diff --git a/alphastats/gui/pages/03_Preprocessing.py b/alphastats/gui/pages/03_Preprocessing.py
@@ -8,6 +8,7 @@
     update_workflow,
     run_preprocessing,
     reset_preprocessing,
+    PREDEFINED_ORDER
 )
 from alphastats.gui.utils.ui_helper import sidebar_info
 
@@ -16,30 +17,32 @@
 
 if "workflow" not in st.session_state:
     st.session_state['workflow'] = [
-        "remove contaminations",
-        "subset data",
-        "log2 transform",
+        "remove_contaminations",
+        "subset",
+        "log2_transform",
     ]
 
 st.markdown("### Preprocessing")
 c1, c2 = st.columns([1, 1])
 
 with c2:
-    settings = configure_preprocessing(dataset=st.session_state['dataset'])
+    if "dataset" not in st.session_state:
+        settings = {k: True for k in st.session_state.workflow}
+    else:
+        settings = configure_preprocessing(dataset=st.session_state['dataset'])
 
     new_workflow = update_workflow(settings)
 
     if new_workflow != st.session_state.workflow:
         st.session_state.workflow = new_workflow
-        st.rerun()
 
 with c1:
-    st.write("#### Flowchart of currently selected workflow:")
+    st.write("#### Flowchart of preprocessing workflow:")
 
     selected_nodes = draw_workflow(st.session_state.workflow)
 
     if "dataset" not in st.session_state:
-        st.info("Import data first to run preprocessing")
+        st.info("Import data first to configure and run preprocessing")
 
     else:
         c11, c12 = st.columns([1, 1])

diff --git a/alphastats/gui/utils/preprocessing_helper.py b/alphastats/gui/utils/preprocessing_helper.py
@@ -126,15 +126,15 @@ def draw_workflow(workflow: list[str], order: list[str] = PREDEFINED_ORDER):
     return selected
 
 
-def configure_preprocessing(dataset=None):
+def configure_preprocessing(dataset):
     st.markdown(
         "Before analyzing your data, consider normalizing and imputing your data as well as the removal of contaminants. "
         + "A more detailed description about the preprocessing methods can be found in the AlphaPeptStats "
         + "[documentation](https://alphapeptstats.readthedocs.io/en/main/data_preprocessing.html)."
     )
 
     remove_contaminations = st.selectbox(
-        f"Remove contaminations annotated in {'contaminations library' if dataset is None else dataset.filter_columns}",
+        f"Remove contaminations annotated in {dataset.filter_columns}",
         options=[True, False],
     )
 
@@ -143,13 +143,10 @@ def configure_preprocessing(dataset=None):
         options=[True, False],
     )
 
+    # TODO: value of this widget does not persist across dataset reset (likely because the metadata is reset)
     remove_samples = st.multiselect(
         "Remove samples from analysis",
-        options=[]
-        if dataset is None
-        else dataset.metadata[
-            dataset.sample
-        ].to_list(),
+        options=dataset.metadata[dataset.sample].to_list(),
     )
 
     data_completeness = st.number_input(
@@ -175,9 +172,7 @@ def configure_preprocessing(dataset=None):
 
     batch = st.selectbox(
         "Batch",
-        options=[False]
-        if dataset is None
-        else [False] + dataset.metadata.columns.to_list(),
+        options=[False] + dataset.metadata.columns.to_list(),
     )
 
     return {