Implement Data access, Runoff, Chlorophyll

CrocoDash/data_access.py

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+"""
+Data Access Module -> Query Data Sources like GLORYS & GEBCO
+"""
+import xarray as xr
+import glob
+import os
+import copernicusmarine
+from .rm6.regional_mom6 import regional_mom6 as rm6
+
+def get_glorys_data_from_rda(dates: list,lat_min, lat_max, lon_min,lon_max) -> xr.Dataset:
+    """
+    Gather GLORYS Data on Derecho Computers from the campaign storage and return the dataset sliced to the llc and urc coordinates at the specific dates 
+    2005 Only
+    """
+
+    # Set 
+    drop_var_lst = ['mlotst','bottomT','sithick','siconc','usi','vsi']
+    ds_in_path = '/glade/campaign/cgd/oce/projects/CROCODILE/glorys012/GLOBAL/'
+    ds_in_files = []
+    date_strings = [date.strftime('%Y%m%d') for date in dates]
+    for date in date_strings:
+        pattern = os.path.join(ds_in_path, "**",f'*{date}*.nc')
+        ds_in_files.extend(glob.glob(pattern, recursive=True))
+    ds_in_files = sorted(ds_in_files)
+    dataset = xr.open_mfdataset(ds_in_files,decode_times=False).drop_vars(drop_var_lst).sel(latitude=slice(lat_min,lat_max),longitude=slice(lon_min,lon_max))
+
+    return dataset
+
+def get_glorys_data_from_cds_api(dates: tuple, lat_min, lat_max, lon_min, lon_max) -> xr.Dataset:
+    """
+    Using the copernucismarine api, query GLORYS data (any dates)
+    """
+    ds = copernicusmarine.open_dataset(
+        dataset_id = 'cmems_mod_glo_phy_my_0.083deg_P1D-m',
+            minimum_longitude = lon_min,
+    maximum_longitude = lon_max,
+    minimum_latitude = lat_min,
+    maximum_latitude = lat_max,
+        start_datetime = dates[0],
+    end_datetime = dates[1],
+    variables=["uo","vo","thetao","so","zos"],
+    )
+    return ds
+
+def get_glorys_data_script_for_cli(dates: tuple, lat_min, lat_max, lon_min, lon_max, filename, download_path) -> None:
+    """
+    Script to run the GLORYS data query for the CLI
+    """
+    return rm6.get_glorys_data([lon_min, lon_max],
+    [lat_min,lat_max],
+    [dates[0],dates[-1]],
+    filename,
+    download_path)
+

tests/test_data_access.py

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+from CrocoDash import data_access as da
+import pandas as pd
+
+def test_get_glorys_data_from_rda():
+    dates = ['2005-01-01','2005-02-01']
+    lat_min = 30
+    lat_max = 31
+    lon_min = -71
+    lon_max = -70
+    dataset = da.get_glorys_data_from_rda(pd.date_range(start=dates[0], end=dates[1]).to_pydatetime().tolist(),lat_min, lat_max, lon_min,lon_max)
+    print(dataset)
+
+def test_get_glorys_data_from_api():
+    dates = ['2000-01-01','2020-12-31']
+    lat_min = 3
+    lat_max = 61
+    lon_min = -101
+    lon_max = -34
+    dataset = da.get_glorys_data_from_cds_api(dates,lat_min, lat_max, lon_min,lon_max)
+    dataset.to_netcdf("")