Overflows were counted but the samples the driver dropped were simply missing, so a 5 s capture with 300 overflows still read as a clean 5.000 s file. Each read's hardware timestamp is now compared with where the previous read ended; gaps are sized exactly, zero-filled by default so the file timeline stays true, and reported as completed_with_gaps with a warning, samples_dropped and a gap list. This also catches drops the plugin never flags as overflows (libusb transfer timeouts). Timestamps are differenced before rounding: rounding each absolute timestamp to a sample index flips by +/-1 near half-sample boundaries and produced phantom 1-sample gaps. - stream buffers 128 x 64K samples (~280 ms at 30 Msps, was ~4 ms) - reject out-of-range gain, frequency, rate and bandwidth instead of letting the plugin clamp silently; default bandwidth clamps to range - spectrum returns a max-hold decimated summary (256 points) plus noise_floor_db; full arrays were 139 KB at fft_size 4096 - capture_iq background=True with stream_status polling, so stop_capture is reachable; device-changing tools refuse while it runs - OSError returned in the error shape; status drops "unknown" fields - README: gap accounting, keep captures off tmpfs; captures/ ignored
125 lines
3.9 KiB
Python
125 lines
3.9 KiB
Python
import numpy as np
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import pytest
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from mcbladerf import capture, device
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from mcbladerf.device import ReadResult
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RATE = 1e6 # one sample per microsecond keeps timestamps readable
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@pytest.fixture
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def fake_stream(monkeypatch):
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"""Script readStream results; data reads fill the buffer with 1, 2, 3, ..."""
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monkeypatch.setattr(capture, "_SETTLE_SAMPLES", 0)
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for name in ("setup_rx_stream", "activate_rx_stream", "close_rx_stream"):
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monkeypatch.setattr(device, name, lambda *a, **k: None)
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def load(script):
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it = iter(script)
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value = 0
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def read_stream(buff, num_samples, timeout_us=0):
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nonlocal value
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r = next(it)
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if r.count:
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value += 1
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buff[: 2 * r.count] = value
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return r
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monkeypatch.setattr(device, "read_stream", read_stream)
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return load
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def _us(n):
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return int(n * 1000)
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def _run(total, fill_gaps):
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stats = capture._StreamStats()
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out = np.concatenate(
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[c.copy() for c in capture._rx_chunks(total, RATE, "CS16", stats, fill_gaps)]
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)
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return out.reshape(-1, 2)[:, 0], stats
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SCRIPT = [
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ReadResult(1000, time_ns=_us(0)),
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ReadResult(1000, time_ns=_us(1000)),
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ReadResult(0, overflow=True),
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ReadResult(1000, time_ns=_us(3000)), # 1000 samples dropped before this
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ReadResult(1000, time_ns=_us(4000)),
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]
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def test_gap_is_zero_filled_at_exact_position(fake_stream):
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fake_stream(SCRIPT)
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i, stats = _run(5000, fill_gaps=True)
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assert len(i) == 5000
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assert (i[2000:3000] == 0).all()
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assert (i[:1000] == 1).all() and (i[3000:4000] == 3).all()
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assert stats.overflows == 1
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assert stats.dropped == 1000
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assert [(g.offset_samples, g.length_samples) for g in stats.gaps] == [(2000, 1000)]
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def test_gap_reported_without_fill(fake_stream):
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fake_stream(SCRIPT + [ReadResult(1000, time_ns=_us(5000))])
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i, stats = _run(5000, fill_gaps=False)
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assert len(i) == 5000
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assert not (i == 0).any()
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assert stats.dropped == 1000
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assert stats.gaps[0].offset_samples == 2000
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def test_zero_fill_never_exceeds_requested_length(fake_stream):
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fake_stream([ReadResult(1000, time_ns=_us(0)), ReadResult(1000, time_ns=_us(50000))])
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i, stats = _run(3000, fill_gaps=True)
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assert len(i) == 3000
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assert stats.dropped == 49000
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def test_overflow_without_timestamp_is_flagged(fake_stream):
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fake_stream([ReadResult(1000), ReadResult(0, overflow=True), ReadResult(1000)])
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_, stats = _run(2000, fill_gaps=True)
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assert stats.overflows == 1
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assert stats.unmeasured_overflows == 1
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assert stats.dropped == 0
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def test_timestamp_rounding_is_not_a_gap(fake_stream):
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# 30 Msps: 4096 samples is 136533.33 ns, so timestamps alternate rounding
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rate = 30e6
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fake_stream([ReadResult(4096, time_ns=round(k * 4096 * 1e9 / rate)) for k in range(50)])
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stats = capture._StreamStats()
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for _ in capture._rx_chunks(50 * 4096, rate, "CS16", stats):
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pass
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assert stats.gap_count == 0
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def test_real_timestamps_near_half_sample_are_not_gaps(fake_stream):
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# Logged from the bladeRF at 30 Msps. Each absolute timestamp sits near a
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# half-sample boundary, so rounding them one by one gave +1, 0, -1 and a
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# phantom 1-sample gap every third read.
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rate = 30e6
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t0, step = 102678001063517, [2184534, 2184533, 2184533]
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times = [t0]
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for k in range(11):
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times.append(times[-1] + step[k % 3])
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fake_stream([ReadResult(65536, time_ns=t) for t in times])
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stats = capture._StreamStats()
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for _ in capture._rx_chunks(12 * 65536, rate, "CS16", stats):
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pass
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assert stats.gap_count == 0
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def test_warning_text_states_dropped_time():
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r = capture.CaptureResult("f", 5000, 1.0, RATE, 1e9, "cs16", 20000,
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overflows=1, samples_dropped=1000)
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assert "1000 samples (1.0 ms)" in r.warning
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assert "zeros" in r.warning
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