Several developments for the AMOC analysis

bgcval2/analysis_compare.py

@@ -175,7 +175,7 @@ def apply_timerange(times, datas, jobID, timeranges):
         print('apply_timerange:', jobID, ti, da)
 
     if not len(n_times):
-        print('apply_timerange: WARNING: No times made the cut?', len(times),
+        print('apply_timerange: WARNING: No times made the cut?', jobID, len(times),
               'original times', [np.min(times), np.max(times)], 
               'timerange:', timerange)
         assert 0
@@ -401,7 +401,7 @@ def timeseries_compare(jobs,
                 title = titleify([region, layer, metric, name])
 
                 times, datas = apply_shifttimes(mdata, jobID, shifttimes)
-                print('post apply_shifttimes:', len(times), len(datas))
+                print('post apply_shifttimes:', jobID, len(times), len(datas))
                 times, datas = apply_timerange(times, datas, jobID, timeranges)
                 timesD[jobID] = times 
                 arrD[jobID] = datas  

bgcval2/bgcval2_make_report.py

@@ -1488,6 +1488,7 @@ def newImageLocation(fn):
         'SouthernTotalIceExtent',
         'Temperature_Global_Surface',
         'Salinty_Global_Surface',
+        'AtlanticSubtropicalSalinity',
         'FreshwaterFlux_Global',
         'TotalHeatFlux',
         'MA_SST',
@@ -1524,7 +1525,6 @@ def newImageLocation(fn):
         'BGC Key Metrics': [],
         'Other Plots': [],
     }
-
 
     for fn in files:
         found = False

bgcval2/bgcvaltools/generic_map_legend.py

@@ -0,0 +1,247 @@
+#!/usr/bin/ipython
+#
+# Copyright 2024, Plymouth Marine Laboratory
+#
+# This file is part of the bgc-val library.
+#
+# bgc-val is free software: you can redistribute it and/or modify it
+# under the terms of the Revised Berkeley Software Distribution (BSD) 3-clause license.
+
+# bgc-val is distributed in the hope that it will be useful, but
+# without any warranty; without even the implied warranty of merchantability
+# or fitness for a particular purpose. See the revised BSD license for more details.
+# You should have received a copy of the revised BSD license along with bgc-val.
+# If not, see <http://opensource.org/licenses/BSD-3-Clause>.
+#
+# Address:
+# Plymouth Marine Laboratory
+# Prospect Place, The Hoe
+# Plymouth, PL1 3DH, UK
+#
+# Email:
+# [email protected]
+#
+"""
+.. module:: generic_map_legend 
+   :platform: Unix
+   :synopsis: Tool to make a plot showing a regions.
+.. moduleauthor:: Lee de Mora <[email protected]>
+.. active:: No
+"""
+
+# implement correct import of params if module in use
+# from ..Paths.paths import orcaGridfn, WOAFolder_annual
+import matplotlib
+matplotlib.use('Agg')
+import os
+from netCDF4 import Dataset
+import numpy as np
+from bgcval2.bgcvaltools import bv2tools as bvt
+from bgcval2.bgcvaltools.pftnames import getLongName
+from bgcval2.bgcvaltools.makeMask import makeMask
+from matplotlib import pyplot
+import cartopy
+import cartopy.crs as ccrs
+from cartopy import img_transform, feature as cfeature
+from bgcval2._runtime_config import get_run_configuration
+from bgcval2.Paths.paths import paths_setter
+
+
+
+
+# Functions#
+# Make a single plot for each region.
+# one pane for global map centered on the middle of the region.
+# One pane zoomed in on center of region
+# One pane global map.
+
+
+def plot_globe(ax):
+    pyplot.sca(ax)     
+
+    # if quick:
+    ax.add_feature(cfeature.OCEAN, zorder=0)
+    ax.add_feature(cfeature.LAND, zorder=0, edgecolor='black')
+    # else:
+        # nc = Dataset(bathy_fn, 'r')
+        # lats = nc.variables['lat'][::binning]
+        # lons = nc.variables['lon'][::binning]
+
+        # data = nc.variables['elevation'][::binning, ::binning]
+        # nc.close()
+
+        # data = np.ma.masked_where(data>0., data)
+
+        # pyplot.pcolormesh(
+        #             lons, 
+        #             lats,
+        #             data,
+        #             #transform=proj,
+        #             transform=ccrs.PlateCarree(),
+        #             cmap=cmap,
+        #             vmin=vmin, vmax=vmax, 
+        #             )
+        # ax.coastlines()
+        # ax.add_feature(cfeature.LAND, edgecolor='black', facecolor=land_color, linewidth=0.5, zorder=9)
+
+    ax.set_global()
+    ax.gridlines()
+    return ax
+
+
+def plot_platcarre(ax):
+    pyplot.sca(ax)     
+
+    # if quick:
+    ax.add_feature(cfeature.OCEAN, zorder=0)
+    # else:
+        # nc = Dataset(bathy_fn, 'r')
+        # lats = nc.variables['lat'][::binning]
+        # lons = nc.variables['lon'][::binning]
+
+        # data = nc.variables['elevation'][::binning, ::binning]
+        # nc.close()
+
+        # data = np.ma.masked_where(data>0., data)
+
+        # pyplot.pcolormesh(
+        #             lons, 
+        #             lats,
+        #             data,
+        #             #transform=proj,
+        #             transform=ccrs.PlateCarree(),
+        #             cmap=cmap,
+        #             vmin=vmin, vmax=vmax, 
+        #             )
+        # ax.coastlines()
+        # ax.add_feature(cfeature.LAND, edgecolor='black', facecolor=land_color, linewidth=0.5, zorder=9)
+
+    ax.set_global()
+    ax.gridlines()
+    return ax
+
+
+def add_region(fig, ax, lons, lats, data):
+    #im = ax.scatter(lons, lats, c=data)
+    pyplot.sca(ax)
+    #im = ax.contourf(lons, lats, data, zorder=1000)
+    im = ax.pcolormesh(lons, lats, data, zorder=1, transform=ccrs.PlateCarree(),)
+
+    #pyplot.colorbar()
+
+    ax.add_feature(cfeature.LAND, zorder=10, edgecolor='black')
+    return fig, ax, im
+
+
+def make_figure(region):
+    fig_fn = bvt.folder('images/regions')+region+'.png'
+    #if os.path.exists(fig_fn): return
+
+    fig = pyplot.figure()
+
+    paths_dict, config_user = get_run_configuration("defaults")
+    # filter paths dict into an object that's usable below
+    paths = paths_setter(paths_dict)    
+    #ncfn = paths.orcaGridfn
+    ncfn = 'mesh_mask_eORCA1_wrk.nc'
+
+    nc = Dataset(ncfn, 'r')
+    print(ncfn)
+
+    dat = nc.variables['mbathy'][:].squeeze()
+    lats = nc.variables['nav_lat'][:].squeeze()
+    lons = nc.variables['nav_lon'][:].squeeze()
+    lons = bvt.makeLonSafeArr(lons)
+
+    old_mask = np.ma.masked_where(dat.mask + dat ==0, dat).mask
+
+    xd = np.ma.masked_where(old_mask, dat).flatten()
+    xt = np.ones_like(xd)
+    xz = xt
+    xy = np.ma.masked_where(old_mask, lats).flatten()
+    xx = np.ma.masked_where(old_mask, lons).flatten()
+    old_mask_flat = old_mask.flatten()
+
+    region_mask = makeMask('bathy', region, xt, xz, xy, xx, xd, debug=True)
+    #print('done makeMask')
+    #assert 0
+    new_dat = np.ma.masked_where(region_mask + old_mask_flat, xd)
+    new_lon = np.ma.masked_where(region_mask+ old_mask_flat, xx)
+    new_lat = np.ma.masked_where(region_mask+ old_mask_flat, xy)
+
+    new_dat = new_dat.reshape(dat.shape)
+    #new_lat = lats # new_lat.reshape(lats.shape)
+    #new_lon = lons # new_lon.reshape(lons.shape)
+
+
+    fig.set_size_inches(12, 8)
+    widths = [1, 1, 1]
+    heights = [1, 1.75]       
+    spec2 = matplotlib.gridspec.GridSpec(
+        ncols=len(widths), 
+        nrows=len(heights), 
+        figure=fig, 
+        width_ratios=widths,
+        height_ratios=heights,
+        hspace=0.30,
+        wspace=0.30,)
+
+    print('lats:', new_lat.mean(), 'lon:', new_lon.mean(), 'data:', new_dat.min(), new_dat.max())
+
+    ortho_pro=ccrs.Orthographic(new_lon.mean(), new_lat.mean(),)    
+    ax_globe = fig.add_subplot(spec2[0, 0], projection=ortho_pro)
+    ax_globe = plot_globe(ax_globe)
+    fig, ax_globe, im = add_region(fig, ax_globe, lons, lats, new_dat)
+
+    ortho_pro=ccrs.Orthographic(new_lon.mean()+120., new_lat.mean(),)    
+    ax_globe1 = fig.add_subplot(spec2[0, 1], projection=ortho_pro)
+    ax_globe1 = plot_globe(ax_globe1)
+    fig, ax_globe1, im1 = add_region(fig, ax_globe1, lons, lats, new_dat)
+
+
+    ortho_pro=ccrs.Orthographic(new_lon.mean()-120., new_lat.mean(),)    
+    ax_globe2 = fig.add_subplot(spec2[0, 2], projection=ortho_pro)
+    ax_globe2 = plot_globe(ax_globe2)
+    fig, ax_globe2, im2 = add_region(fig, ax_globe2, lons, lats, new_dat)
+
+    pc_proj=cartopy.crs.PlateCarree(central_longitude=new_lon.mean())
+    ax_pc = fig.add_subplot(spec2[1, :], projection=pc_proj)    
+    ax_pc = plot_platcarre(ax_pc)
+    fig, ax_pc, im3 = add_region(fig, ax_pc, lons, lats, new_dat)
+    #cbar = pyplot.colorbar(ax=ax_pc, cax=im3)
+
+    pyplot.suptitle(region+': '+getLongName(region))
+    print('saving:', fig_fn)
+    pyplot.savefig(fig_fn,dpi=300.)
+    pyplot.savefig(fig_fn.replace('.png', '_trans.png'), transparent=True)
+    pyplot.close()
+
+
+def main():
+    regions = [
+               'Ascension',
+               'ITCZ',
+               'TristandaCunha',
+               'Pitcairn',
+               'Cornwall',
+               'SubtropicNorthAtlantic',
+               'SPNA',
+               'STNA',        
+               'SouthernOcean',
+               'ArcticOcean',
+               'Equator10',
+               'NorthPacificOcean',
+               'SouthPacificOcean',
+               'NorthAtlanticOcean',
+               'SouthAtlanticOcean',
+               'GINseas',
+               'LabradorSea',
+               'EquatorialAtlanticOcean',
+               'Global',
+               'ignoreInlandSeas',
+    ]
+    for region in regions[:]:
+        make_figure(region)
+
+if __name__ == "__main__":
+    main()

bgcval2/bgcvaltools/makeMask.py

@@ -216,20 +216,20 @@ def makeMask(name, newSlice, xt, xz, xy, xx, xd, debug=False):
     if newSlice == 'ignoreExtraArtics':
         return np.ma.masked_outside(xy, -50., 50.).mask
     if newSlice == 'NorthAtlanticOcean':
-        return np.ma.masked_outside(bvt.makeLonSafeArr(xx), -80.,
+        print('NorthAtlanticOcean - pre')
+        #xx = bvt.makeLonSafeArr(xx)
+        print('NorthAtlanticOcean', len(xx))
+        return np.ma.masked_outside(xx, -80.,
                                     0.).mask + np.ma.masked_outside(
                                         xy, 10., 60.).mask
     if newSlice == 'SouthAtlanticOcean':
-        return np.ma.masked_outside(bvt.makeLonSafeArr(xx), -65.,
-                                    20.).mask + np.ma.masked_outside(
+        return np.ma.masked_outside(xx, -65., 20.).mask + np.ma.masked_outside(
                                         xy, -50., -10.).mask
     if newSlice == 'EquatorialAtlanticOcean':
-        return np.ma.masked_outside(bvt.makeLonSafeArr(xx), -65.,
-                                    20.).mask + np.ma.masked_outside(
+        return np.ma.masked_outside(xx, -65., 20.).mask + np.ma.masked_outside(
                                         xy, -15., 15.).mask
     if newSlice == 'ITCZ': #Inter‐Tropical Convergence Zone (johns 2020 Sargassum) in the region 0-15N, 15-55W
-        return np.ma.masked_outside(bvt.makeLonSafeArr(xx), -55.,
-                                    15.).mask + np.ma.masked_outside(
+        return np.ma.masked_outside(xx, -55., 15.).mask + np.ma.masked_outside(
                                         xy, 0., 15.).mask
 
     if newSlice == 'ArcticOcean':
@@ -246,11 +246,36 @@ def makeMask(name, newSlice, xt, xz, xy, xx, xd, debug=False):
             xy, 60., 80.).mask
         return mx
 
+    if newSlice in ['SubtropicNorthAtlantic', 'STNA']:
+        mx = np.ma.masked_outside(xx, -80., -10.).mask + np.ma.masked_outside(
+            xy, 10., 40.).mask
+#       mx *= np.ma.masked_outside(xx, -45., 15.).mask + np.ma.masked_outside(
+#           xy, 60., 80.).mask
+        return mx
+
+    if newSlice in ['SubtropicSouthAtlantic', 'STSA']:
+        mx = np.ma.masked_outside(xx, -80., -10.).mask + np.ma.masked_outside(
+            xy, 10., 40.).mask
+#       mx *= np.ma.masked_outside(xx, -45., 15.).mask + np.ma.masked_outside(
+#           xy, 60., 80.).mask
+        return mx
+
+
     if newSlice in ['SubpolarNorthAtlantic', 'SPNA',]:
         #  Based on  SPNA region here: https://www.nature.com/articles/s43247-021-00120-y#citeas
         mx = np.ma.masked_outside(xx, -35., -10.).mask + np.ma.masked_outside(
             xy, 40., 65.).mask
         return mx
+
+#    if newSlice in ['WesternSubpolarNorthAtlantic', 'WSPNA',]:
+
+
+    if newSlice in ['GINseas',]: #Greenland, icveland and norwegean seas
+        mx = np.ma.masked_outside(xx, -20., 15.).mask + np.ma.masked_outside(
+            xy, 65., 75.).mask
+        return mx
+        #65-75:20W-15E         
+
 
     if newSlice == 'AtlanticSOcean':
         mx = np.ma.masked_outside(xx, -40., 20.).mask + np.ma.masked_outside(
@@ -292,7 +317,7 @@ def makeMask(name, newSlice, xt, xz, xy, xx, xd, debug=False):
     if newSlice == 'Pitcairn': # MPA covers several islands. This is very approximate
         # Ducie Island:  24.66 S 124.75 W (Eastern most)
         # Oeno island: 23.9 S 130.74 W (western most) (Western boundary is not the full EEZ)
-        mx = np.ma.masked_outside(xx, -130.74 - 1.5, 124.75 + 3.).mask # longitude # West
+        mx = np.ma.masked_outside(xx, -130.74 - 1.5, -124.75 + 3.).mask # longitude # West
         mx += np.ma.masked_outside(xy, -24.66 -3, -23.9 + 3.).mask # Lattitue  # South
         return mx