feat: integrate cascade filter workflow

2026-05-26 15:34:24 +08:00
parent 075f20dd81
commit 3edc4702f3
9 changed files with 568 additions and 44 deletions
@@ -3,7 +3,7 @@ from fastapi import HTTPException
 from scipy import signal

 from .config import BODE_MAX_MULTIPLIER, BODE_POINTS
-from .schemas import BodeCompareParams, BodeParams
+from .schemas import BodeCascadeParams, BodeCompareParams, BodeParams
 from .validation import require_finite, validate_coefficients


@@ -47,3 +47,39 @@ def calculate_bode_compare_response(params: BodeCompareParams):
        "ideal": ideal,
        "fixed": fixed,
    }
+
+
+def calculate_bode_cascade_response(params: BodeCascadeParams):
+    fs_val, f_eval = _frequency_axis(params.fs)
+    h_total_ideal = np.ones(len(f_eval), dtype=complex)
+    h_total_fixed = np.ones(len(f_eval), dtype=complex)
+    any_active = False
+
+    for i, stage in enumerate(params.stages):
+        if not stage.isActive:
+            continue
+        any_active = True
+        b_vals = validate_coefficients(stage.b, f"stages[{i}].b")
+        a_vals = validate_coefficients(stage.a, f"stages[{i}].a")
+        b_fixed_vals = validate_coefficients(stage.b_fixed, f"stages[{i}].b_fixed")
+        a_fixed_vals = validate_coefficients(stage.a_fixed, f"stages[{i}].a_fixed")
+        _, h_ideal = signal.freqz(b_vals, a_vals, worN=f_eval, fs=fs_val)
+        _, h_fixed = signal.freqz(b_fixed_vals, a_fixed_vals, worN=f_eval, fs=fs_val)
+        h_total_ideal *= h_ideal
+        h_total_fixed *= h_fixed
+
+    if not any_active:
+        h_total_ideal = np.ones(len(f_eval), dtype=complex)
+        h_total_fixed = np.ones(len(f_eval), dtype=complex)
+
+    return {
+        "freq": f_eval.tolist(),
+        "ideal": {
+            "mag": (20 * np.log10(np.abs(h_total_ideal) + 1e-12)).tolist(),
+            "phase": np.angle(h_total_ideal, deg=True).tolist(),
+        },
+        "fixed": {
+            "mag": (20 * np.log10(np.abs(h_total_fixed) + 1e-12)).tolist(),
+            "phase": np.angle(h_total_fixed, deg=True).tolist(),
+        },
+    }
@@ -138,7 +138,43 @@ def integer_lfilter(b_int, a_int, x_float, shift_in, shift_out, shift_b, shift_a
    return y_out.astype(float) / (2**shift_out)


-def filter_preview_response(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=None, shift_in=14, shift_out=14, shift_b=14, shift_a=14, use_round=False):
+def _run_filter_paths(x_values, b_vals, a_vals, b_int, a_int, shift_in, shift_out, shift_b, shift_a, use_round, stages=None):
+    if stages is None:
+        y_float = signal.lfilter(b_vals, a_vals, x_values)
+        if b_int is not None and a_int is not None:
+            y_fixed = integer_lfilter(b_int, a_int, x_values, shift_in, shift_out, shift_b, shift_a, use_round)
+        else:
+            y_fixed = y_float
+        return y_float, y_fixed
+
+    y_float = x_values
+    y_fixed = x_values
+    any_active = False
+    for stage in stages:
+        if not stage.get("isActive", True):
+            continue
+        any_active = True
+        y_float = signal.lfilter(stage["b"], stage["a"], y_float)
+        if stage.get("b_int") is not None and stage.get("a_int") is not None:
+            y_fixed = integer_lfilter(
+                stage["b_int"],
+                stage["a_int"],
+                y_fixed,
+                stage["shift_in"],
+                stage["shift_out"],
+                stage["shift_b"],
+                stage["shift_a"],
+                stage["use_round"],
+            )
+        else:
+            y_fixed = y_float
+
+    if not any_active:
+        return x_values, x_values
+    return y_float, y_fixed
+
+
+def filter_preview_response(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=None, shift_in=14, shift_out=14, shift_b=14, shift_a=14, use_round=False, stages=None, start_idx=None, end_idx=None):
    path = get_cached_file_path(file_id)

    # 預先讀取欄位名稱，避免用 usecols 讀取後找不到原始索引
@@ -157,16 +193,27 @@ def filter_preview_response(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=
    if not np.isfinite(x_values).all():
        raise HTTPException(status_code=400, detail=f"欄位 {col_to_filter} 含有非有限數值")

-    # 路徑 1: 理想浮點數路徑
-    y_float = signal.lfilter(b_vals, a_vals, x_values)
+    y_float, y_fixed = _run_filter_paths(
+        x_values, b_vals, a_vals, b_int, a_int,
+        shift_in, shift_out, shift_b, shift_a, use_round, stages=stages,
+    )

-    # 路徑 2: 整數模擬路徑
-    if b_int is not None and a_int is not None:
-        y_fixed = integer_lfilter(b_int, a_int, x_values, shift_in, shift_out, shift_b, shift_a, use_round)
-    else:
-        y_fixed = y_float
+    total_points = len(df.index)
+    start_idx_clean = start_idx if isinstance(start_idx, (int, float, str)) else None
+    end_idx_clean = end_idx if isinstance(end_idx, (int, float, str)) else None
+    s_idx = max(0, int(start_idx_clean)) if start_idx_clean is not None else 0
+    e_idx = min(total_points, int(end_idx_clean)) if end_idx_clean is not None else total_points
+    if s_idx >= e_idx:
+        s_idx = 0
+        e_idx = total_points

-    index, original, filtered_float, filtered_fixed, step = downsample_for_plot(df.index.to_numpy(), x_signal, y_float, y_fixed)
+    full_index = df.index.to_numpy()
+    index, original, filtered_float, filtered_fixed, step = downsample_for_plot(
+        full_index[s_idx:e_idx],
+        x_values[s_idx:e_idx],
+        y_float[s_idx:e_idx],
+        y_fixed[s_idx:e_idx],
+    )

    return {
        "index": index.tolist(),
@@ -174,13 +221,13 @@ def filter_preview_response(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=
        "filtered": filtered_float.tolist(),
        "filtered_fixed": filtered_fixed.tolist(),
        "col_name": col_to_filter,
-        "total_points": int(len(df.index)),
+        "total_points": int(total_points),
        "plot_points": int(len(index)),
        "downsample_step": int(step),
    }


-def filtered_csv_text(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=None, shift_in=14, shift_out=14, shift_b=14, shift_a=14, use_round=False):
+def filtered_csv_text(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=None, shift_in=14, shift_out=14, shift_b=14, shift_a=14, use_round=False, stages=None, fs=100000.0, compact=False):
    path = get_cached_file_path(file_id)
    # 匯出時需要原始所有欄位，但仍受限於 MAX_ROWS
    df = pd.read_csv(path, nrows=MAX_ROWS)
@@ -191,14 +238,23 @@ def filtered_csv_text(file_id, b_vals, a_vals, col_idx, b_int=None, a_int=None,
    x_signal = pd.to_numeric(df[col_to_filter], errors="coerce")
    x_values = x_signal.to_numpy(dtype=float)

-    y_float = signal.lfilter(b_vals, a_vals, x_values)
-    if b_int is not None and a_int is not None:
-        y_fixed = integer_lfilter(b_int, a_int, x_values, shift_in, shift_out, shift_b, shift_a, use_round)
-    else:
-        y_fixed = y_float
+    y_float, y_fixed = _run_filter_paths(
+        x_values, b_vals, a_vals, b_int, a_int,
+        shift_in, shift_out, shift_b, shift_a, use_round, stages=stages,
+    )
+
+    if compact:
+        export_df = pd.DataFrame({
+            "Time (s)": df.index.to_numpy(dtype=float) / fs,
+            col_to_filter: x_values,
+            f"{col_to_filter}_filtered_ideal": y_float,
+            f"{col_to_filter}_filtered_fixed": y_fixed,
+        })
+    else:
+        export_df = df.copy()
+        export_df[f"{col_to_filter}_filtered_ideal"] = y_float
+        export_df[f"{col_to_filter}_filtered_fixed"] = y_fixed

-    df[f"{col_to_filter}_filtered_ideal"] = y_float
-    df[f"{col_to_filter}_filtered_fixed"] = y_fixed
    csv_buffer = io.StringIO()
-    df.to_csv(csv_buffer, index=False)
+    export_df.to_csv(csv_buffer, index=False)
    return csv_buffer.getvalue()
@@ -47,3 +47,16 @@ class BodeCompareParams(BaseModel):
 class MCUWriteParams(BaseModel):
    command: str = Field(min_length=1, max_length=128)
    port: Optional[str] = Field(default=None, max_length=256)
+
+
+class CascadeStageParams(BaseModel):
+    b: List[float] = Field(min_length=1, max_length=MAX_COEFFICIENTS)
+    a: List[float] = Field(min_length=1, max_length=MAX_COEFFICIENTS)
+    b_fixed: List[float] = Field(min_length=1, max_length=MAX_COEFFICIENTS)
+    a_fixed: List[float] = Field(min_length=1, max_length=MAX_COEFFICIENTS)
+    isActive: bool = True
+
+
+class BodeCascadeParams(BaseModel):
+    stages: List[CascadeStageParams] = Field(min_length=1)
+    fs: float = Field(gt=0)