From 6d1c5f3526b9f8601afa224462ba273d3ff8efd7 Mon Sep 17 00:00:00 2001 From: Julieanna Bacon Date: Sun, 17 Mar 2024 22:57:31 -0400 Subject: [PATCH] feature preproces: Update crop functionality to use geolocation function for lat/lon crop windows --- config/preprocess_netcdf.toml | 11 ++++--- icedyno/preprocess/crop.py | 30 ++++++++++-------- workspaces/julieanna/ims_latlong.ipynb | 44 +++++--------------------- 3 files changed, 31 insertions(+), 54 deletions(-) diff --git a/config/preprocess_netcdf.toml b/config/preprocess_netcdf.toml index e371ca0..cf8e343 100644 --- a/config/preprocess_netcdf.toml +++ b/config/preprocess_netcdf.toml @@ -1,14 +1,15 @@ -[CropFiles] +[CropRotateNetCDF] # Full relative directory is data/input_dir, data/output_dir input_dir = "ims_1km" # Change this output_dir name to reflect the window size and center coordinates selected # Example: _50000x_15000y -output_dir = "ims_netcdf_1km_cropped_1_000km_window +output_dir = "ims_netcdf_1km_cropped_1_000km_window" # Final shape will be (window_size*2, window_size*2) window_size = 1000 #km -# Expect str format in x,y coordinates if provided. Example: "1000, 2000" -# Defaults to center of current grid system if "None" -center_coordinates = "-1078660.2392965402, 1285497.2153701815" +# Longitude, latitude coordinates IN DEGREES for center of cropped window. +# Defaults to center of current grid system if either is "None" +center_latitude = 74.0 +center_longitude = -140.0 diff --git a/icedyno/preprocess/crop.py b/icedyno/preprocess/crop.py index 6a657be..877d90b 100644 --- a/icedyno/preprocess/crop.py +++ b/icedyno/preprocess/crop.py @@ -12,6 +12,8 @@ import numpy as np import xarray as xr +import icedyno.preprocess.geolocation + class CropRotateNetCDF(luigi.Task): """ @@ -24,7 +26,8 @@ class CropRotateNetCDF(luigi.Task): input_dir = luigi.Parameter() output_dir = luigi.Parameter() - center_coordinates = luigi.Parameter() + center_latitude = luigi.FloatParameter() + center_longitude = luigi.FloatParameter() window_size = luigi.IntParameter(default=4000) year = luigi.IntParameter() # Determined at runtime @@ -49,31 +52,32 @@ def run(self) -> None: os.path.join(year_output_dir, pathlib.Path(cdf_filepath).stem) + f"_grid{self.window_size}" ) - if self.center_coordinates != "None": - output_filename += ( - f"_{self.center_coordinates.replace(' ', '')}center.nc" - ) + if (self.center_latitude != "None") and (self.center_longitude != "None"): + output_filename += f"_{str(self.center_latitude).replace('.', ',')}lat_{str(self.center_longitude).replace('.', ',')}lon.nc" else: output_filename += ".nc" + # Don't recompute file if the expected filename in the output folder already exists. if os.path.exists(output_filename): print(cdf_filepath, "already on disk, skipping...") - # Open the original NetCDF file ds = xr.open_dataset(cdf_filepath, engine="h5netcdf") - if self.center_coordinates != "None": - # Expects self.center_coordinates x,y to be "x, y" float values. - x, y = [float(coord) for coord in self.center_coordinates.split(",")] + # Correct the netCDF files with a 90 degree rotation so the xarray x,y grid matches polar stereographic + ds = rotate_netcdf(ds) + + # If specified, center the window on the lat/lon coordinates provided. Otherwise, center on middle of grid. + if (self.center_latitude != "None") and (self.center_longitude != "None"): + # Project the lat/lon coordinates to the polar stereographic coordinates. + x, y = icedyno.preprocess.geolocation.polar_lonlat_to_xy( + longitude=self.center_longitude, latitude=self.center_latitude + ) else: x = np.min(np.abs(ds.x)) y = np.min(np.abs(ds.y)) window = self.window_size * 1000 # from km to meters - # Correct the netCDF files with a 90 degree rotation so the xarray x,y grid matches polar stereographic - ds = rotate_netcdf(ds) - cropped_ds = ds.sel( x=slice(x - window // 2, x + window // 2), y=slice(y - window // 2, y + window // 2), @@ -116,7 +120,7 @@ def rotate_netcdf(ds: xr.Dataset) -> xr.Dataset: luigi.configuration.add_config_path(config_path) ## Change acording to your number of cores - n_workers = 10 + n_workers = 2 years = range(2015, 2025) tasks = [CropRotateNetCDF(year=year) for year in years] diff --git a/workspaces/julieanna/ims_latlong.ipynb b/workspaces/julieanna/ims_latlong.ipynb index 1f0c529..22b5e9b 100644 --- a/workspaces/julieanna/ims_latlong.ipynb +++ b/workspaces/julieanna/ims_latlong.ipynb @@ -198,6 +198,14 @@ "plot_sie(sie[0], marker=(sie.shape[1] // 2, sie.shape[2] // 2))" ] }, + { + "cell_type": "markdown", + "id": "3ab11331-28b5-4a66-bf0a-db7a90fcc4af", + "metadata": {}, + "source": [ + "## Prototyping the netcdf grid correction" + ] + }, { "cell_type": "code", "execution_count": 36, @@ -210,20 +218,6 @@ "x, y = ipg.polar_lonlat_to_xy(longitude=lon, latitude=lat)" ] }, - { - "cell_type": "markdown", - "id": "520fb48b-7149-4a24-8bda-6a2c4514fd7f", - "metadata": {}, - "source": [ - "## TODO:\n", - "- Test what's going on with the SIE rotation\n", - "- Minimum 5 lat/lon pairs\n", - "- Correct the index slicing in crop.py\n", - "\n", - "- Once this logic is fixed for y coord, preprocess netcdf files with corrected SIE (& grid)\n", - "- Update the window centering for polar convert functions (for lat lon specification)-" - ] - }, { "cell_type": "code", "execution_count": 37, @@ -328,28 +322,6 @@ "plt.show()" ] }, - { - "cell_type": "code", - "execution_count": 13, - "id": "cc4868b8-29d2-4d28-8c7f-382f36e82d11", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "cropped_ds.IMS_Surface_Values.plot()\n", - "plt.show()" - ] - }, { "cell_type": "code", "execution_count": 20,