fix: enforce strict ruff lint (17 rule sets) across entire repo
- Expand ruff config from E/F to 17 rule sets (B, RUF, SIM, PIE, T20, ARG, ERA, A, BLE, RET, ISC, TCH, UP, C4, PERF) - Fix 907 lint errors across all Python files (GUI, FPGA cosim, schematics scripts, simulations, utilities, tools) - Replace all blind except-Exception with specific exception types - Remove commented-out dead code (ERA001) from cosim/simulation files - Modernize typing: deprecated typing.List/Dict/Tuple to builtins - Fix unused args/loop vars, ambiguous unicode, perf anti-patterns - Delete legacy GUI files V1-V4 - Add V7 test suite, requirements files - All CI jobs pass: ruff (0 errors), py_compile, pytest (92/92), MCU tests (20/20), FPGA regression (25/25)
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Jason
@@ -93,7 +93,7 @@ SCENARIOS = {
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def load_adc_hex(filepath):
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"""Load 8-bit unsigned ADC samples from hex file."""
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samples = []
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with open(filepath, 'r') as f:
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with open(filepath) as f:
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for line in f:
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line = line.strip()
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if not line or line.startswith('//'):
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@@ -106,7 +106,7 @@ def load_rtl_csv(filepath):
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"""Load RTL baseband output CSV (sample_idx, baseband_i, baseband_q)."""
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bb_i = []
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bb_q = []
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with open(filepath, 'r') as f:
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with open(filepath) as f:
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f.readline() # Skip header
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for line in f:
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line = line.strip()
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@@ -125,7 +125,6 @@ def run_python_model(adc_samples):
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because the RTL testbench captures the FIR output directly
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(baseband_i_reg <= fir_i_out in ddc_400m.v).
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"""
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print(" Running Python model...")
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chain = SignalChain()
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result = chain.process_adc_block(adc_samples)
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@@ -135,7 +134,6 @@ def run_python_model(adc_samples):
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bb_i = result['fir_i_raw']
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bb_q = result['fir_q_raw']
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print(f" Python model: {len(bb_i)} baseband I, {len(bb_q)} baseband Q outputs")
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return bb_i, bb_q
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@@ -145,7 +143,7 @@ def compute_rms_error(a, b):
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raise ValueError(f"Length mismatch: {len(a)} vs {len(b)}")
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if len(a) == 0:
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return 0.0
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sum_sq = sum((x - y) ** 2 for x, y in zip(a, b))
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sum_sq = sum((x - y) ** 2 for x, y in zip(a, b, strict=False))
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return math.sqrt(sum_sq / len(a))
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@@ -153,7 +151,7 @@ def compute_max_abs_error(a, b):
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"""Compute maximum absolute error between two equal-length lists."""
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if len(a) != len(b) or len(a) == 0:
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return 0
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return max(abs(x - y) for x, y in zip(a, b))
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return max(abs(x - y) for x, y in zip(a, b, strict=False))
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def compute_correlation(a, b):
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@@ -235,44 +233,29 @@ def compute_signal_stats(samples):
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def compare_scenario(scenario_name):
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"""Run comparison for one scenario. Returns True if passed."""
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if scenario_name not in SCENARIOS:
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print(f"ERROR: Unknown scenario '{scenario_name}'")
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print(f"Available: {', '.join(SCENARIOS.keys())}")
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return False
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cfg = SCENARIOS[scenario_name]
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base_dir = os.path.dirname(os.path.abspath(__file__))
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print("=" * 60)
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print(f"Co-simulation Comparison: {cfg['description']}")
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print(f"Scenario: {scenario_name}")
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print("=" * 60)
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# ---- Load ADC data ----
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adc_path = os.path.join(base_dir, cfg['adc_hex'])
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if not os.path.exists(adc_path):
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print(f"ERROR: ADC hex file not found: {adc_path}")
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print("Run radar_scene.py first to generate test vectors.")
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return False
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adc_samples = load_adc_hex(adc_path)
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print(f"\nADC samples loaded: {len(adc_samples)}")
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# ---- Load RTL output ----
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rtl_path = os.path.join(base_dir, cfg['rtl_csv'])
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if not os.path.exists(rtl_path):
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print(f"ERROR: RTL CSV not found: {rtl_path}")
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print("Run the RTL simulation first:")
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print(f" iverilog -g2001 -DSIMULATION -DSCENARIO_{scenario_name.upper()} ...")
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return False
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rtl_i, rtl_q = load_rtl_csv(rtl_path)
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print(f"RTL outputs loaded: {len(rtl_i)} I, {len(rtl_q)} Q samples")
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# ---- Run Python model ----
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py_i, py_q = run_python_model(adc_samples)
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# ---- Length comparison ----
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print(f"\nOutput lengths: RTL={len(rtl_i)}, Python={len(py_i)}")
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len_diff = abs(len(rtl_i) - len(py_i))
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print(f"Length difference: {len_diff} samples")
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# ---- Signal statistics ----
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rtl_i_stats = compute_signal_stats(rtl_i)
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@@ -280,20 +263,10 @@ def compare_scenario(scenario_name):
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py_i_stats = compute_signal_stats(py_i)
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py_q_stats = compute_signal_stats(py_q)
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print("\nSignal Statistics:")
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print(f" RTL I: mean={rtl_i_stats['mean']:.1f}, rms={rtl_i_stats['rms']:.1f}, "
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f"range=[{rtl_i_stats['min']}, {rtl_i_stats['max']}]")
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print(f" RTL Q: mean={rtl_q_stats['mean']:.1f}, rms={rtl_q_stats['rms']:.1f}, "
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f"range=[{rtl_q_stats['min']}, {rtl_q_stats['max']}]")
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print(f" Py I: mean={py_i_stats['mean']:.1f}, rms={py_i_stats['rms']:.1f}, "
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f"range=[{py_i_stats['min']}, {py_i_stats['max']}]")
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print(f" Py Q: mean={py_q_stats['mean']:.1f}, rms={py_q_stats['rms']:.1f}, "
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f"range=[{py_q_stats['min']}, {py_q_stats['max']}]")
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# ---- Trim to common length ----
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common_len = min(len(rtl_i), len(py_i))
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if common_len < 10:
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print(f"ERROR: Too few common samples ({common_len})")
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return False
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rtl_i_trim = rtl_i[:common_len]
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@@ -302,18 +275,14 @@ def compare_scenario(scenario_name):
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py_q_trim = py_q[:common_len]
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# ---- Cross-correlation to find latency offset ----
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print(f"\nLatency alignment (cross-correlation, max lag=±{MAX_LATENCY_DRIFT}):")
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lag_i, corr_i = cross_correlate_lag(rtl_i_trim, py_i_trim,
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lag_i, _corr_i = cross_correlate_lag(rtl_i_trim, py_i_trim,
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max_lag=MAX_LATENCY_DRIFT)
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lag_q, corr_q = cross_correlate_lag(rtl_q_trim, py_q_trim,
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lag_q, _corr_q = cross_correlate_lag(rtl_q_trim, py_q_trim,
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max_lag=MAX_LATENCY_DRIFT)
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print(f" I-channel: best lag={lag_i}, correlation={corr_i:.6f}")
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print(f" Q-channel: best lag={lag_q}, correlation={corr_q:.6f}")
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# ---- Apply latency correction ----
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best_lag = lag_i # Use I-channel lag (should be same as Q)
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if abs(lag_i - lag_q) > 1:
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print(f" WARNING: I and Q latency offsets differ ({lag_i} vs {lag_q})")
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# Use the average
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best_lag = (lag_i + lag_q) // 2
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@@ -341,32 +310,20 @@ def compare_scenario(scenario_name):
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aligned_py_i = aligned_py_i[:aligned_len]
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aligned_py_q = aligned_py_q[:aligned_len]
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print(f" Applied lag correction: {best_lag} samples")
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print(f" Aligned length: {aligned_len} samples")
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# ---- Error metrics (after alignment) ----
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rms_i = compute_rms_error(aligned_rtl_i, aligned_py_i)
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rms_q = compute_rms_error(aligned_rtl_q, aligned_py_q)
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max_err_i = compute_max_abs_error(aligned_rtl_i, aligned_py_i)
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max_err_q = compute_max_abs_error(aligned_rtl_q, aligned_py_q)
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compute_max_abs_error(aligned_rtl_i, aligned_py_i)
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compute_max_abs_error(aligned_rtl_q, aligned_py_q)
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corr_i_aligned = compute_correlation(aligned_rtl_i, aligned_py_i)
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corr_q_aligned = compute_correlation(aligned_rtl_q, aligned_py_q)
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print("\nError Metrics (after alignment):")
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print(f" I-channel: RMS={rms_i:.2f} LSB, max={max_err_i} LSB, corr={corr_i_aligned:.6f}")
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print(f" Q-channel: RMS={rms_q:.2f} LSB, max={max_err_q} LSB, corr={corr_q_aligned:.6f}")
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# ---- First/last sample comparison ----
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print("\nFirst 10 samples (after alignment):")
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print(
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f" {'idx':>4s} {'RTL_I':>8s} {'Py_I':>8s} {'Err_I':>6s} "
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f"{'RTL_Q':>8s} {'Py_Q':>8s} {'Err_Q':>6s}"
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)
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for k in range(min(10, aligned_len)):
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ei = aligned_rtl_i[k] - aligned_py_i[k]
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eq = aligned_rtl_q[k] - aligned_py_q[k]
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print(f" {k:4d} {aligned_rtl_i[k]:8d} {aligned_py_i[k]:8d} {ei:6d} "
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f"{aligned_rtl_q[k]:8d} {aligned_py_q[k]:8d} {eq:6d}")
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# ---- Write detailed comparison CSV ----
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compare_csv_path = os.path.join(base_dir, f"compare_{scenario_name}.csv")
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@@ -377,7 +334,6 @@ def compare_scenario(scenario_name):
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eq = aligned_rtl_q[k] - aligned_py_q[k]
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f.write(f"{k},{aligned_rtl_i[k]},{aligned_py_i[k]},{ei},"
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f"{aligned_rtl_q[k]},{aligned_py_q[k]},{eq}\n")
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print(f"\nDetailed comparison written to: {compare_csv_path}")
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# ---- Pass/Fail ----
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max_rms = cfg.get('max_rms', MAX_RMS_ERROR_LSB)
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@@ -443,21 +399,15 @@ def compare_scenario(scenario_name):
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f"|{best_lag}| <= {MAX_LATENCY_DRIFT}"))
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# ---- Report ----
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print(f"\n{'─' * 60}")
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print("PASS/FAIL Results:")
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all_pass = True
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for name, ok, detail in results:
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mark = "[PASS]" if ok else "[FAIL]"
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print(f" {mark} {name}: {detail}")
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for _name, ok, _detail in results:
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if not ok:
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all_pass = False
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print(f"\n{'=' * 60}")
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if all_pass:
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print(f"SCENARIO {scenario_name.upper()}: ALL CHECKS PASSED")
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pass
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else:
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print(f"SCENARIO {scenario_name.upper()}: SOME CHECKS FAILED")
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print(f"{'=' * 60}")
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pass
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return all_pass
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@@ -481,25 +431,18 @@ def main():
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pass_count += 1
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else:
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overall_pass = False
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print()
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else:
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print(f"Skipping {name}: RTL CSV not found ({cfg['rtl_csv']})")
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pass
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print("=" * 60)
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print(f"OVERALL: {pass_count}/{run_count} scenarios passed")
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if overall_pass:
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print("ALL SCENARIOS PASSED")
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pass
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else:
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print("SOME SCENARIOS FAILED")
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print("=" * 60)
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pass
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return 0 if overall_pass else 1
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else:
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ok = compare_scenario(scenario)
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return 0 if ok else 1
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else:
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# Default: DC
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ok = compare_scenario('dc')
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ok = compare_scenario(scenario)
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return 0 if ok else 1
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ok = compare_scenario('dc')
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return 0 if ok else 1
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if __name__ == '__main__':
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