UI refinement

src/phyphox_app_block.py

@@ -16,8 +16,6 @@ import streamlit as st
 
 from phyphox_pipeline import process_phyphox_files, FS, WINDOW, STEP
 
-# ── Constants ─────────────────────────────────────────────────────────────────
-
 LABEL_MAP = {
     0: "WALKING",
     1: "WALKING_UPSTAIRS",
@@ -36,8 +34,6 @@ EXPLANATIONS = {
     "WALKING_UPSTAIRS": "Elevated vertical acceleration effort: climbing stairs.",
 }
 
-# ── Normalisation ─────────────────────────────────────────────────────────────
-
 @st.cache_resource
 def _load_norm_params(norm_path: str):
     """Load per-feature min/max from norm_params.json (keys are string indices 0-560)."""
@@ -62,8 +58,6 @@ def _normalize(features: np.ndarray, min_vals: np.ndarray, max_vals: np.ndarray)
     return 2.0 * (clipped - min_vals) / rng - 1.0
 
 
-# ── Public render function ────────────────────────────────────────────────────
-
 def render_phyphox_tab(
     ffn_model, ffn_status: str,
     cnn_model, cnn_status: str,
@@ -108,7 +102,6 @@ def render_phyphox_tab(
         st.info("Upload both files to continue.")
         return
 
-    # ── Raw signal sanity check ───────────────────────────────────────────────
     try:
         import io as _io
         _raw = acc_file.read()
@@ -144,7 +137,6 @@ def render_phyphox_tab(
     except Exception:
         pass
 
-    # ── Feature extraction ────────────────────────────────────────────────────
     try:
         with st.spinner("Extracting 561 features from sensor data…"):
             features, pipeline_warnings = process_phyphox_files(acc_file, gyro_file)
@@ -170,7 +162,6 @@ def render_phyphox_tab(
         f"50% overlap ({STEP / FS:.2f} s hop)"
     )
 
-    # ── Normalisation ─────────────────────────────────────────────────────────
     if os.path.exists(norm_params_path):
         min_vals, max_vals = _load_norm_params(norm_params_path)
         features = _normalize(features, min_vals, max_vals)
@@ -185,7 +176,6 @@ def render_phyphox_tab(
             "Predictions will be unreliable until normalisation is applied."
         )
 
-    # ── Predictions ───────────────────────────────────────────────────────────
     if ffn_status != "ready" and cnn_status != "ready":
         st.warning("Models not loaded: cannot predict yet.")
         return

src/phyphox_pipeline.py

@@ -17,8 +17,6 @@ import pandas as pd
 from scipy import signal as sp_signal
 from scipy.stats import skew, kurtosis as sp_kurtosis
 
-# ── Constants ─────────────────────────────────────────────────────────────────
-
 FS = 50        # target sampling rate Hz
 WINDOW = 128   # samples per window (2.56 s)
 STEP = 64      # hop size — 50% overlap
@@ -35,8 +33,6 @@ ACC_COLS = ["Time (s)", "X (m/s^2)", "Y (m/s^2)", "Z (m/s^2)"]
 GYRO_COLS = ["Time (s)", "X (rad/s)", "Y (rad/s)", "Z (rad/s)"]
 
 
-# ── CSV helpers ───────────────────────────────────────────────────────────────
-
 def _parse_csv(file_obj, expected_cols: list) -> pd.DataFrame:
     """Parse a Phyphox CSV export and validate required columns.
 
@@ -68,8 +64,6 @@ def _parse_csv(file_obj, expected_cols: list) -> pd.DataFrame:
     return df[expected_cols].apply(pd.to_numeric, errors="coerce").dropna()
 
 
-# ── DSP helpers ───────────────────────────────────────────────────────────────
-
 def _butter_lp(data: np.ndarray, cutoff: float, fs: float = FS, order: int = 3) -> np.ndarray:
     """Zero-phase Butterworth low-pass filter applied along axis 0.
 
@@ -212,8 +206,6 @@ def _angle(u: np.ndarray, v: np.ndarray) -> float:
     return float(np.arccos(np.clip(np.dot(u, v) / (un * vn), -1.0, 1.0)))
 
 
-# ── Feature extractors ────────────────────────────────────────────────────────
-
 def _t3ax(sig: np.ndarray) -> np.ndarray:
     """40 time-domain features from a 3-axis signal (N, 3).
 
@@ -420,8 +412,6 @@ def _window_features(
     return result
 
 
-# ── Public API ────────────────────────────────────────────────────────────────
-
 def process_phyphox_files(
     acc_file,
     gyro_file,
@@ -460,7 +450,6 @@ def process_phyphox_files(
     gyro_t = gyro_df["Time (s)"].values
     gyro_xyz = gyro_df[["X (rad/s)", "Y (rad/s)", "Z (rad/s)"]].values
 
-    # Common time window
     t0 = max(acc_t[0], gyro_t[0])
     t1 = min(acc_t[-1], gyro_t[-1])
     duration = t1 - t0

src/streamlit_app.py

@@ -9,8 +9,6 @@ _REPO_ROOT = os.path.dirname(_SRC_DIR)
 _SAMPLES_PATH = os.path.join(_REPO_ROOT, "data", "samples.csv")
 _NORM_PATH    = os.path.join(_REPO_ROOT, "data", "norm_params.json")
 
-# ── Constants ──────────────────────────────────────────────────────────────
-
 LABEL_MAP = {
     0: "WALKING",
     1: "WALKING_UPSTAIRS",
@@ -29,8 +27,6 @@ EXPLANATIONS = {
     "WALKING_UPSTAIRS": "Elevated vertical acceleration effort with upward body displacement: consistent with climbing stairs.",
 }
 
-# ── Model loader ────────────────────────────────────────────────────────────
-
 @st.cache_resource
 def load_model(filename: str):
     try:
@@ -54,8 +50,6 @@ def load_model(filename: str):
     except Exception as e:
         return None, f"error: {e}"
 
-# ── Page config ─────────────────────────────────────────────────────────────
-
 st.set_page_config(
     page_title="Human Activity Recognition",
     page_icon="🏃",
@@ -69,8 +63,6 @@ st.markdown(
     "Classifies six daily activities from accelerometer and gyroscope readings."
 )
 
-# ── Sidebar ──────────────────────────────────────────────────────────────────
-
 with st.sidebar:
     st.header("About")
     st.markdown("""
@@ -95,8 +87,6 @@ with st.sidebar:
     st.markdown("---")
     st.caption("DAT606 Group Assignment · Pan-Atlantic University")
 
-# ── Load both models at startup ───────────────────────────────────────────────
-
 ffn_model, ffn_status = load_model("model.keras")
 cnn_model, cnn_status = load_model("har_cnn.keras")
 
@@ -106,12 +96,8 @@ if ffn_status != "ready" or cnn_status != "ready":
     if cnn_status != "ready":
         st.warning(f"CNN not loaded: {cnn_status}")
 
-# ── Tabs ─────────────────────────────────────────────────────────────────────
-
 tab1, tab2 = st.tabs(["Select a Sample", "Upload Phyphox CSV"])
 
-# ── Tab 1: Sample selector ───────────────────────────────────────────────────
-
 with tab1:
     st.subheader("Select a pre-loaded test sample")
     st.caption(
@@ -161,7 +147,6 @@ with tab1:
 
                 left, right = st.columns(2)
 
-                # ── FFN column ──────────────────────────────────────────────
                 with left:
                     st.markdown("#### Feedforward Network")
                     if ffn_label == true_label:
@@ -176,7 +161,6 @@ with tab1:
                         index=[LABEL_MAP[i] for i in range(6)]
                     ))
 
-                # ── CNN column ──────────────────────────────────────────────
                 with right:
                     st.markdown("#### 1D Convolutional Network")
                     if cnn_label == true_label:
@@ -194,8 +178,6 @@ with tab1:
     except FileNotFoundError:
         st.error("Sample data file not found. Add `data/samples.csv` to the repo.")
 
-# ── Tab 2: Phyphox upload ─────────────────────────────────────────────────────
-
 with tab2:
     from phyphox_app_block import render_phyphox_tab
     render_phyphox_tab(ffn_model, ffn_status, cnn_model, cnn_status, _NORM_PATH)