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55 lines
1.6 KiB
Python
55 lines
1.6 KiB
Python
# Regressions tests on result types of some signal functions
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import numpy as np
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from numpy.testing import assert_
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import pytest
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from scipy.signal import (decimate,
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lfilter_zi,
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lfiltic,
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sos2tf,
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sosfilt_zi)
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def test_decimate():
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ones_f32 = np.ones(32, dtype=np.float32)
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assert_(decimate(ones_f32, 2).dtype == np.float32)
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ones_i64 = np.ones(32, dtype=np.int64)
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assert_(decimate(ones_i64, 2).dtype == np.float64)
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def test_lfilter_zi():
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b_f32 = np.array([1, 2, 3], dtype=np.float32)
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a_f32 = np.array([4, 5, 6], dtype=np.float32)
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assert_(lfilter_zi(b_f32, a_f32).dtype == np.float32)
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def test_lfiltic():
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# this would return f32 when given a mix of f32 / f64 args
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b_f32 = np.array([1, 2, 3], dtype=np.float32)
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a_f32 = np.array([4, 5, 6], dtype=np.float32)
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x_f32 = np.ones(32, dtype=np.float32)
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b_f64 = b_f32.astype(np.float64)
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a_f64 = a_f32.astype(np.float64)
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x_f64 = x_f32.astype(np.float64)
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assert_(lfiltic(b_f64, a_f32, x_f32).dtype == np.float64)
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assert_(lfiltic(b_f32, a_f64, x_f32).dtype == np.float64)
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assert_(lfiltic(b_f32, a_f32, x_f64).dtype == np.float64)
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assert_(lfiltic(b_f32, a_f32, x_f32, x_f64).dtype == np.float64)
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def test_sos2tf():
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sos_f32 = np.array([[4, 5, 6, 1, 2, 3]], dtype=np.float32)
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b, a = sos2tf(sos_f32)
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assert_(b.dtype == np.float32)
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assert_(a.dtype == np.float32)
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def test_sosfilt_zi():
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sos_f32 = np.array([[4, 5, 6, 1, 2, 3]], dtype=np.float32)
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assert_(sosfilt_zi(sos_f32).dtype == np.float32)
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