feat: added column filter for exclusion of columns that are not topologically relevant

Author: lucasimi

src/tdamapper/app.py

@@ -4,7 +4,7 @@
 
 import logging
 import os
-from dataclasses import asdict, dataclass
+from dataclasses import asdict, dataclass, field
 from typing import Any, Callable, Literal, Optional
 
 import networkx as nx
@@ -91,11 +91,12 @@
 RANDOM_SEED = 42
 
 
-@dataclass
+@dataclass(frozen=True)
 class MapperConfig:
     """
     Configuration for the Mapper algorithm.
 
+    :param excluded_columns: List of columns to exclude from the input data.
     :param lens_type: Type of lens to use for dimensionality reduction.
     :param cover_scale_data: Whether to scale the data before covering.
     :param cover_type: Type of cover to use for the Mapper algorithm.
@@ -119,6 +120,7 @@ class MapperConfig:
     :param plot_seed: Random seed for reproducibility.
     """
 
+    excluded_columns: list[str] = field(default_factory=list)
     lens_type: str = LENS_PCA
     cover_scale_data: bool = COVER_SCALE_DATA
     cover_type: str = COVER_CUBICAL
@@ -222,6 +224,7 @@ def run_mapper(
     params: dict[str, Any] = kwargs
     mapper_config = MapperConfig(**params)
 
+    excluded_columns = mapper_config.excluded_columns
     lens_type = mapper_config.lens_type
     cover_scale_data = mapper_config.cover_scale_data
     cover_type = mapper_config.cover_type
@@ -284,7 +287,11 @@ def run_mapper(
         return None
 
     mapper = MapperAlgorithm(cover=cover, clustering=clustering)
-    X = df.to_numpy()
+    if excluded_columns:
+        X = df.drop(columns=excluded_columns, errors="ignore").to_numpy()
+    else:
+        X = df.to_numpy()
+
     y = lens(X)
     df_y = pd.DataFrame(y, columns=[f"{lens_type} {i}" for i in range(y.shape[1])])
     if cover_scale_data:
@@ -435,6 +442,9 @@ def __init__(self, storage: dict[str, Any]) -> None:
                 color="themelight",
             ).classes("w-full text-themedark")
 
+            with ui.column().classes("w-full gap-2"):
+                self._init_columns()
+
             with ui.column().classes("w-full gap-2"):
                 self._init_lens()
 
@@ -512,6 +522,17 @@ def _init_file_upload(self) -> None:
             value=LOAD_EXAMPLE,
         )
 
+    def _init_columns(self) -> None:
+        ui.label("⚙️ Settings").classes("text-h6")
+        self._init_columns_settings()
+
+    def _init_columns_settings(self) -> None:
+        self.excluded_columns = ui.select(
+            options=[],
+            label="Exclude columns",
+            multiple=True,
+        ).classes("w-full")
+
     def _init_lens(self) -> None:
         ui.label("🔎 Lens").classes("text-h6")
         self._init_lens_settings()
@@ -726,6 +747,9 @@ def get_mapper_config(self) -> MapperConfig:
         else:
             plot_dimensions = PLOT_DIMENSIONS
         return MapperConfig(
+            excluded_columns=(
+                self.excluded_columns.value if self.excluded_columns.value else []
+            ),
             lens_type=str(self.lens_type.value) if self.lens_type.value else LENS_PCA,
             cover_type=(
                 str(self.cover_type.value) if self.cover_type.value else COVER_CUBICAL
@@ -854,6 +878,8 @@ def load_data(self) -> None:
         df = self.storage.get("df", pd.DataFrame())
         if df is not None and not df.empty:
             logger.info("Load data completed.")
+            self.excluded_columns.set_options(list(df.columns))
+            self.excluded_columns.set_value([])
             ui.notify("Load data completed.", type="positive")
         else:
             error = "Load data failed: no data found, please upload a file first."
@@ -910,21 +936,26 @@ async def async_run_mapper(self) -> None:
             self.notification_running_stop(notification, error, type="warning")
             return
         mapper_config = self.get_mapper_config()
-        result = await run.cpu_bound(run_mapper, df_X, **asdict(mapper_config))
-        if result is None:
-            error = "Run Mapper failed: something went wrong."
+        try:
+            result = await run.cpu_bound(run_mapper, df_X, **asdict(mapper_config))
+            if result is None:
+                error = "Run Mapper failed: something went wrong."
+                logger.error(error)
+                self.notification_running_stop(notification, error, type="error")
+                return
+            mapper_graph, df_y = result
+            if mapper_graph is not None:
+                self.storage["mapper_graph"] = mapper_graph
+            if df_y is not None:
+                self.storage["df_y"] = df_y
+            self.notification_running_stop(
+                notification, "Run Mapper completed.", type="positive"
+            )
+            await self.async_draw_mapper()
+        except Exception as e:
+            error = f"Run Mapper failed: {e}"
             logger.error(error)
             self.notification_running_stop(notification, error, type="error")
-            return
-        mapper_graph, df_y = result
-        if mapper_graph is not None:
-            self.storage["mapper_graph"] = mapper_graph
-        if df_y is not None:
-            self.storage["df_y"] = df_y
-        self.notification_running_stop(
-            notification, "Run Mapper completed.", type="positive"
-        )
-        await self.async_draw_mapper()
 
     async def async_draw_mapper(self) -> None:
         """