added reader for noresm runs

wavy/collocation_module.py

@@ -75,6 +75,7 @@ def find_valid_fc_dates_for_model_and_leadtime(fc_dates, model, leadtime):
     of complete hours
     '''
     fc_dates_new = hour_rounder_pd(fc_dates)
+    fc_dates_new = np.unique(fc_dates_new)
     #if (leadtime is None or leadtime == 'best'):
     #    pass
     #else:
@@ -149,7 +150,7 @@ def __init__(self, oco=None, model=None, poi=None,
         self.distlim = kwargs.get('distlim', 6)
         print(" ")
         print(" ## Collocate ... ")
-#        for i in range(1):
+        #for i in range(1):
         try:
             t0 = time.time()
             results_dict = self.collocate(**kwargs)
@@ -329,10 +330,11 @@ def _collocate_track(self, **kwargs):
                 'collocation_idx_y': [],
                 }
         for i in tqdm(range(len(fc_date))):
+            print(fc_date[i])
         #for i in range(len(fc_date)):
             try:
-                #for j in range(1):
-                with NoStdStreams():
+                for j in range(1):
+                #with NoStdStreams():
                     # filter needed obs within time period
                     target_date = [parse_date(str(fc_date[i]))]
                     idx = collocate_times(ndt_datetime,
@@ -376,7 +378,8 @@ def _collocate_track(self, **kwargs):
                                         results_dict_tmp['collocation_idx_x'])
                         results_dict['collocation_idx_y'].append(
                                         results_dict_tmp['collocation_idx_y'])
-                    else: pass
+                    else:
+                        pass
                     if 'results_dict_tmp' in locals():
                         del results_dict_tmp
             except (ValueError, FileNotFoundError, OSError) as e:

wavy/config/model_cfg.yaml.default

@@ -330,3 +330,26 @@ cmems_MY_L4:
         remoteHostName: my.cmems-du.eu
     # optional, to ease grouping
     tags:
+
+# interpolated grid 1 degree by 1 degree
+noresmf19:
+    name:
+    download:
+    vardef:
+        Hs: HS
+        time: time
+        lons: longitude
+        lats: latitude
+    coords:
+    wavy_input:
+        src_tmplt: "/lustre/storeB/users/anac/TMP/wavy/NorESMdata/2011/12/"
+        fl_tmplt: "f19_tn14_wtn14n_DecemberBETAmax1.43_1X1deg_every3hours_2011.nc"
+    reader: read_noresm_making_waves
+    collector:
+    misc:
+        init_times: [0]
+        init_step: 24
+        grid_date: 2011-12-02 00:00:00
+        date_incr_unit: h
+        date_incr: 3
+        proj4: "+proj=longlat +a=6367470 +e=0 +no_defs"

wavy/config/satellite_cfg.yaml.default

@@ -82,7 +82,7 @@ cmems_L3_MY:
         ftp: # downloading method
             src_tmplt: "/Core/WAVE_GLO_PHY_SWH_L3_MY_014_005\
                         /cci_obs-wave_glo_phy-swh_my_name-l3_PT1S/%Y/%m/"
-            trgt_tmplt: /home/patrikb/tmp_altimeter/L3_MY/name/%Y/%m
+            trgt_tmplt: /home/patrikb/tmp_altimeter/L3/MY/name/%Y/%m
             path_date_incr_unit: 'm'
             path_date_incr: 1
             search_str: '%Y%m%dT'
@@ -91,7 +91,7 @@ cmems_L3_MY:
     # optional: where to read from
     #           can be defined directly when calling wavy
     wavy_input:
-        src_tmplt: /home/patrikb/tmp_altimeter/L3_MY/name/%Y/%m
+        src_tmplt: /home/patrikb/tmp_altimeter/L3/MY/name/%Y/%m
         fl_tmplt: "varalias_name_region_\
                         %Y%m%d%H%M%S_%Y%m%d%H%M%S.nc"
         strsub: ['name']
@@ -100,7 +100,7 @@ cmems_L3_MY:
     # optional: where to write to
     #           can be defined directly when calling wavy
     wavy_output:
-        trgt_tmplt: /home/patrikb/tmp_altimeter/L3_MY/name/%Y/%m
+        trgt_tmplt: /home/patrikb/tmp_altimeter/L3/MY/name/%Y/%m
         fl_tmplt: "varalias_name_region_\
                         %Y%m%d%H%M%S_%Y%m%d%H%M%S.nc"
         strsub: ['varalias','name','region']

wavy/grid_readers.py

@@ -158,6 +158,38 @@ def build_xr_ds_grid(var_means, lon_grid, lat_grid, t, **kwargs):
          )
     return ds
 
+def build_xr_ds_grid_2D(var_means, lon_grid, lat_grid, t, **kwargs):
+    print(" building xarray dataset from grid")
+    varstr = kwargs.get('varstr')
+    lon_grid_coord = kwargs.get('lon_grid_coord')
+    lat_grid_coord = kwargs.get('lat_grid_coord')
+
+    ds = xr.Dataset({
+            varstr: xr.DataArray(
+                     data=var_means,
+                     dims=['time', 'latitude', 'longitude'],
+                     coords={'latitude': lat_grid_coord,
+                             'longitude': lon_grid_coord,
+                             'time': t},
+                     attrs=variable_def[varstr],
+                     ),
+            'lons': xr.DataArray(
+                     data=lon_grid,
+                     dims=['latitude', 'longitude'],
+                     coords={'longitude': lon_grid_coord},
+                     attrs=variable_def['lons'],
+                     ),
+            'lats': xr.DataArray(
+                     data=lat_grid,
+                     dims=['latitude', 'longitude'],
+                     coords={'latitude': lat_grid_coord},
+                     attrs=variable_def['lats'],
+                     ),
+                 },
+             attrs={'title': 'wavy dataset'}
+         )
+    return ds
+
 
 def grid_point_cloud_ds(values, lons, lats, t, **kwargs):
     print(' gridding point cloud')

wavy/model_readers.py

@@ -17,7 +17,7 @@
 from wavy.wconfig import load_or_default
 from wavy.utils import build_xr_ds
 from wavy.grid_readers import get_gridded_dataset
-from wavy.grid_readers import build_xr_ds_grid
+from wavy.grid_readers import build_xr_ds_grid, build_xr_ds_grid_2D
 from wavy.ncmod import ncdumpMeta, get_filevarname
 from wavy.ncmod import read_netcdfs_with_credentials_aggregated
 from wavy.utils import parse_date
@@ -63,6 +63,49 @@ def read_ww3_4km(**kwargs):
 
     return combined
 
+def read_noresm_making_waves(**kwargs):
+    pathlst = kwargs.get('pathlst')
+    nID = kwargs.get('nID')
+    fc_dates = kwargs.get('fc_dates')
+    varname = kwargs.get('varname')
+    varalias = kwargs.get('varalias')
+    timename = model_dict[nID]['vardef']['time']
+    lonsname = model_dict[nID]['vardef']['lons']
+    latsname = model_dict[nID]['vardef']['lats']
+
+    ds_lst = []
+    for i in range(len(pathlst)):
+        ds = xr.open_dataset(pathlst[i])
+        ds2 = ds.convert_calendar("all_leap")
+        datetimeindex = ds2.indexes[timename].to_datetimeindex()
+        ds[timename] = datetimeindex
+        del ds2
+        var = ds[varname].values
+        lons = ds[lonsname].values
+        lats = ds[latsname].values
+        Mlons, Mlats = np.meshgrid(lons, lats)
+        timedt = ds[timename].values
+        tlst = [parse_date(str(d)) for d in timedt]
+        idx = collocate_times(tlst, target_t=[fc_dates[i]])
+        time = np.array([np.array(tlst)[idx[0]]]).reshape((1,))
+        varin = var[idx[0], :, :].reshape((1, len(lats), len(lons)))
+        ds = build_xr_ds_grid_2D(varin, Mlons, Mlats, time,
+                                 lon_grid_coord=lons,
+                                 lat_grid_coord=lats,
+                                 varstr=varalias)
+        ds_lst.append(ds)
+
+    print(" Concatenate ...")
+    combined = xr.concat(ds_lst, timename,
+                         coords='minimal',
+                         data_vars='minimal',
+                         compat='override',
+                         combine_attrs='override',
+                         join='override')
+    print(" ... done concatenating")
+
+    return combined
+
 def read_remote_ncfiles_aggregated_credentials(**kwargs):
     """
     Wrapping function to read remote opendap satellite netcdf files

wavy/quicklookmod.py

@@ -157,7 +157,7 @@ def quicklook(self, a=False, projection=None, **kwargs):
                                  s=.2, c='b', marker='.',
                                  edgecolor='face',
                                  transform=ccrs.PlateCarree())
-            if len(self.vars[self.varalias].shape) > 1:
+            if len(plot_var.shape) > 1:
                 sc = ax.contourf(plot_lons.squeeze(),
                                  plot_lats.squeeze(),
                                  plot_var.squeeze(),