Ryan Malloy
90cd07d9bc
17 tests: round_sig/compact_list rounding, downsample_indices stride vs peak-preserving (a narrow spike must survive), and extract_waveform/ analyze_signal across AC/transient/x-range/error/all-analysis paths.
53 lines
1.7 KiB
Python
53 lines
1.7 KiB
Python
"""Tests for the JSON output-formatting helpers."""
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import math
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import numpy as np
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from mcltspice.output_format import compact_list, downsample_indices, round_sig
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class TestRoundSig:
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def test_significant_figures(self):
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assert round_sig(123456.789, 3) == 123000.0
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assert round_sig(0.00123456, 3) == 0.00123
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def test_zero_and_nonfinite_pass_through(self):
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assert round_sig(0.0) == 0.0
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assert math.isinf(round_sig(float("inf")))
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assert math.isnan(round_sig(float("nan")))
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class TestCompactList:
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def test_decimal_places(self):
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assert compact_list([1.23456, 2.98765], decimal_places=2) == [1.23, 2.99]
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def test_sig_figs(self):
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assert compact_list([123456.0], sig_figs=3) == [123000.0]
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def test_no_rounding_returns_floats(self):
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out = compact_list([1, 2, 3])
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assert out == [1.0, 2.0, 3.0]
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assert all(isinstance(v, float) for v in out)
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class TestDownsampleIndices:
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def test_no_downsample_when_under_limit(self):
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idx = downsample_indices(50, 100)
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assert np.array_equal(idx, np.arange(50))
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def test_stride_for_transient(self):
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idx = downsample_indices(1000, 100)
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assert len(idx) <= 100
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# plain stride: evenly spaced
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assert idx[0] == 0
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assert idx[1] - idx[0] == idx[2] - idx[1]
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def test_peak_preserving_keeps_a_narrow_spike(self):
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# A flat magnitude with one sharp spike: peak-preserving must keep it.
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n = 1000
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mag = np.ones(n, dtype=complex)
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mag[497] = 1000.0 # narrow resonance peak
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idx = downsample_indices(n, 50, signals=[mag])
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assert 497 in idx # spike survived downsampling
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