CDAT Migration Phase 3 - Port QBO Wavelet feature to Xarray/xCDAT codebase #860
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tomvothecoder
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tomvothecoder
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Oct 1, 2024
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Hey @chengzhuzhang, this PR ended up being trivial to implement (about < 1 hour of work). I copied all of the code updates from #860 and performed some additional refactoring for cleaner code.
The results look visibly close to main. I will merge once the build passes.
mainviewer: https://portal.nersc.gov/project/e3sm/cdat-migration-fy24/main-qbo-wavelet/viewer/qbo/variable/qbo-era-interim/plot.html- dev viewer: https://portal.nersc.gov/project/e3sm/cdat-migration-fy24/850-qbo-wavelet/viewer/qbo/variable/qbo-era-interim/plot.html
- Files diff from PR Qbo wavelet #836
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| def _calculate_wavelet(var: xr.DataArray) -> Tuple[np.ndarray, np.ndarray]: | ||
| """ | ||
| Calculate the wavelet spectrum for a given data array at a specified power | ||
| spectral level. | ||
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| Parameters | ||
| ---------- | ||
| data : xr.DataArray | ||
| The variable data. | ||
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| Returns | ||
| ------- | ||
| Tuple[np.ndarray, np.ndarray] | ||
| The wavelet period and wavelet array. | ||
| """ | ||
| # Find the closest value for power spectral level in the list | ||
| test_lev = xc.get_dim_coords(var, axis="Z") | ||
| test_lev_list = list(test_lev) | ||
| closest_lev = min(test_lev_list, key=lambda x: abs(x - POW_SPEC_LEV)) | ||
| closest_index = test_lev_list.index(closest_lev) | ||
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| # Grab target vertical level | ||
| data_avg = var.values[:, closest_index] | ||
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| # Convert to anomalies | ||
| data_avg = data_avg - data_avg.mean() | ||
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| # Detrend the data | ||
| detrended_data = detrend(data_avg) | ||
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| wave_period, wavelet = _get_psd_from_wavelet(detrended_data) | ||
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| # Get square root values of wavelet spectra | ||
| wavelet = np.sqrt(wavelet) | ||
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| return wave_period, wavelet |
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Extracted this private function since the logic is the same for test and ref (look here).
Thanks GitHub Co-Pilot.
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cdat-migration-fy24branch #850Checklist
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