Calculate real value of monthly total precipitation #89
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kimlee87
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Pull request overview
This PR implements the calculation of real monthly total precipitation values from ERA5-Land monthly data by multiplying downloaded values by the number of days in each month. The change addresses issue #57 and ensures precipitation data accurately reflects monthly totals rather than daily averages.
- Added
calculate_monthly_precipitationfunction to compute monthly totals - Integrated the calculation into the preprocessing pipeline with new configuration settings
- Updated schema and default settings to support the new feature
Reviewed changes
Copilot reviewed 6 out of 6 changed files in this pull request and generated 4 comments.
Show a summary per file
| File | Description |
|---|---|
| heiplanet_data/preprocess.py | Adds _check_month_start_data and calculate_monthly_precipitation functions, integrates monthly precipitation calculation into _apply_preprocessing, and renames parameter from agg_funcs to downsample_agg_funcs for clarity |
| heiplanet_data/setting_schema.json | Adds schema definitions for cal_monthly_tp, cal_monthly_tp_vname, cal_monthly_tp_tcoord, and cal_monthly_tp_fname settings, updates descriptions for downsampling parameters, and renames resample_agg_funcs to downsample_agg_funcs |
| heiplanet_data/era5_settings.json | Enables monthly precipitation calculation by default with cal_monthly_tp: true and associated configuration |
| heiplanet_data/test/test_preprocess.py | Adds tests for _check_month_start_data, calculate_monthly_precipitation, and integration test for the preprocessing pipeline, updates existing test to use renamed parameter |
| heiplanet_data/test/test_utils.py | Adds validation tests for new settings related to monthly precipitation calculation |
| docs/source/notebooks/tutorial_B_preprocess_data.ipynb | Documents new monthly precipitation calculation settings and additional downsampling parameters in the preprocessing settings table |
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| def calculate_monthly_precipitation( | ||
| dataset: xr.Dataset, var_name: str = "tp", time_coord: str = "time" | ||
| ) -> xr.Dataset: | ||
| """Calculate monthly total precipitation from data downloaded from ERA5-Land monthly data. | ||
| The real precipitation of the month = downloaded value * number of days in the month. | ||
| Args: | ||
| dataset (xr.Dataset): Dataset with total precipitation data. | ||
| var_name (str): Name of the precipitation variable in the dataset. Default is "tp". | ||
| time_coord (str): Name of the time coordinate in the dataset. Default is "time". | ||
| Returns: | ||
| xr.Dataset: Dataset with monthly total precipitation values. | ||
| """ | ||
| # check inputs | ||
| if time_coord not in dataset.coords: | ||
| raise ValueError(f"Time coordinate '{time_coord}' not found in dataset.") | ||
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| if var_name not in dataset.data_vars: | ||
| raise ValueError(f"Variable '{var_name}' not found in dataset.") | ||
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| times = dataset[time_coord] | ||
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| if not _check_month_start_data(times): | ||
| raise ValueError("The dataset does not have month start data.") | ||
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| # calculate number of days in each month | ||
| days_in_month = times.dt.days_in_month | ||
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| # calculate monthly total precipitation | ||
| org_attrs = dataset[var_name].attrs.copy() | ||
| dataset[var_name] = dataset[var_name] * days_in_month | ||
| dataset[var_name].attrs = org_attrs | ||
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| return dataset | ||
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The function mutates the input dataset in place without an option to preserve the original dataset. This is inconsistent with similar functions in the codebase like 'convert_to_celsius_with_attributes' and 'convert_m_to_mm_with_attributes', which have an 'inplace' parameter that defaults to False. Consider adding an 'inplace' parameter and creating a copy of the dataset when it's False to maintain consistency with the existing API design pattern.
Codecov Report✅ All modified and coverable lines are covered by tests. Additional details and impacted files@@ Coverage Diff @@
## main #89 +/- ##
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+ Coverage 98.61% 98.65% +0.04%
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Files 9 9
Lines 2159 2226 +67
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+ Hits 2129 2196 +67
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This PR resolves issue #57
monthly tp = downloaded value * number of days in the month