Coarsened checks in test_ap() again. Import complexfloat traits in config
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@ -42,6 +42,7 @@ if #[cfg(feature = "python-bindings")] {
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use ndarray::OwnedRepr;
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use ndarray::OwnedRepr;
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use num::complex::Complex;
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use num::complex::Complex;
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pub use num::complex::ComplexFloat;
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/// View into 1D array of floats
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/// View into 1D array of floats
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pub type VdView<'a> = ArrayView1<'a, Flt>;
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pub type VdView<'a> = ArrayView1<'a, Flt>;
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@ -451,9 +451,9 @@ mod test {
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}
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}
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#[test]
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#[test]
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fn test_ap() {
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fn test_ap() {
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let nfft = 256;
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let nfft = 1024;
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let distr = Normal::new(1.0, 1.0).unwrap();
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let distr = Normal::new(1.0, 1.0).unwrap();
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let timedata = Dmat::random((100 * nfft, 1), distr);
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let timedata = Dmat::random((150 * nfft, 1), distr);
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let timedata_mean_square = (&timedata * &timedata).sum() / (timedata.len() as Flt);
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let timedata_mean_square = (&timedata * &timedata).sum() / (timedata.len() as Flt);
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for wt in [
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for wt in [
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@ -466,7 +466,7 @@ mod test {
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let mut aps = AvPowerSpectra::build(nfft, wt, None, None).unwrap();
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let mut aps = AvPowerSpectra::build(nfft, wt, None, None).unwrap();
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if let ApsResult::OnlyLastResult(v) = aps.compute_last(&timedata) {
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if let ApsResult::OnlyLastResult(v) = aps.compute_last(&timedata) {
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let ap = v.ap(0);
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let ap = v.ap(0);
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assert_abs_diff_eq!((&ap).sum().abs(), timedata_mean_square, epsilon = 8e-3);
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assert_abs_diff_eq!((&ap).sum().abs(), timedata_mean_square, epsilon = 1e-2);
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} else {
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} else {
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assert!(false);
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assert!(false);
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}
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}
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