Merge remote-tracking branch 'origin/main' into dev_ecosystem

Author: ledm

.github/workflows/build-and-deploy-on-pypi.yml

@@ -14,10 +14,10 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@master
-      - name: Set up Python 3.12
+      - name: Set up Python 3.13
         uses: actions/setup-python@v4
         with:
-          python-version: "3.12"
+          python-version: "3.13"
       - name: Install pep517
         run: >-
           python -m

.github/workflows/run-tests-push.yml

@@ -8,12 +8,12 @@ jobs:
     runs-on: "ubuntu-latest"
     strategy:
       matrix:
-        python-version: ["3.12"]
+        python-version: ["3.13"]
       fail-fast: false
     name: Linux Python ${{ matrix.python-version }}
     steps:
-      - uses: actions/checkout@v2
-      - uses: conda-incubator/setup-miniconda@v2
+      - uses: actions/checkout@v4
+      - uses: conda-incubator/setup-miniconda@v3
         with:
           activate-environment: bgcval2
           environment-file: environment.yml
@@ -38,6 +38,7 @@ jobs:
           bgcval2_make_report --help
           download_from_mass --help 
       - shell: bash -l {0}
-        run: pytest
+        run: |
+          pytest
       - shell: bash -l {0}
         run: sphinx-build -Ea doc doc/build

.github/workflows/run-tests.yml

@@ -13,12 +13,12 @@ jobs:
     runs-on: "ubuntu-latest"
     strategy:
       matrix:
-        python-version: ["3.9", "3.10", "3.11", "3.12"]
+        python-version: ["3.10", "3.11", "3.12", "3.13"]
       fail-fast: false
     name: Linux Python ${{ matrix.python-version }}
     steps:
-      - uses: actions/checkout@v2
-      - uses: conda-incubator/setup-miniconda@v2
+      - uses: actions/checkout@v4
+      - uses: conda-incubator/setup-miniconda@v3
         with:
           activate-environment: bgcval2
           environment-file: environment.yml

README.md

@@ -19,7 +19,8 @@ This work was funded through WP1 of the Terrafirma project.
 
 Current version notes:
 
-- Suported versions of Python: 3.9, 3.10, 3.11, and 3.12
+- Suported versions of Python: 3.10, 3.11, 3.12, and 3.13
+- Numpy 2+ compatible
 
 Environment and installation
 ============================
@@ -110,7 +111,7 @@ conda env remove -n ENV_NAME
 
 Executable name | What it does | Command
 :--------------:|:------------:|:------------:
-`analysis_timeseries` | runs timeseries analysis for single model run. | analysis_timeseries jobID key
+`analysis_timeseries` | runs timeseries analysis for single model run. | analysis_timeseries -j jobID -k key
 `analysis_p2p` | runs point to point analysis of model against observational dataset. | analysis_p2p jobID YEAR
 `bgcval` | runs time series and point to point. | bgcval jobID
 `bgcval2_make_report` | makes the single model HTML report. | bgcval2_make_report jobID

bgcval2/_runtime_config.py

@@ -61,7 +61,9 @@ def _establish_hostname():
     elif gethostname().find('pmpc') > -1:
         hostname = "pml"
     elif gethostname().find('-az') > -1:
-        hostname = "local-test-only"  # for testing on GA machine
+        hostname = "local-test-only"  # for testing on GA machine (old type)
+    elif os.environ.get("INPUT_RUN_POST", None):
+        hostname = "local-test-only"  # for testing on GA machine (new type)
     # FIXME local testing only
     elif gethostname().find('valeriu-PORTEGE-Z30-C') > -1:
         hostname = "local-test-only"  # for testing on V's laptop

bgcval2/bgcval2_make_report.py

@@ -1600,8 +1600,7 @@ def newImageLocation(fn):
         csvFolder = paths.imagedir + '/TimeseriesCompare_CSV/' + analysis_name
 
         for catfn in catfiles:
-#            print('png:', catfn)
-            json_fn = csvFolder+'/'+analysis_name+'_'+os.path.basename(catfn)
+            json_fn = ''.join([csvFolder, '/', analysis_name, '_', os.path.basename(catfn)])
             together = json_fn.find('Together')
             json_fn = json_fn[:together] + 'Together.json'
             print('json:', json_fn)

bgcval2/bgcvaltools/generic_map_legend.py

@@ -144,7 +144,6 @@ def make_figure(region):
     paths = paths_setter(paths_dict)   
     orcaGridfn = paths.orcaGridfn
 
-    #    ncfn = 'mesh_mask_eORCA1_wrk.nc'
     nc = Dataset(orcaGridfn, 'r')
     dat = nc.variables['mbathy'][:].squeeze()
     lats = nc.variables['nav_lat'][:].squeeze()

bgcval2/functions/standard_functions.py

@@ -136,10 +136,8 @@ def maskzeroes(nc, keys):
     """
     var0 = find_best_var(nc, keys)
     arr = np.ma.array(nc.variables[var0][:]) #, dtype=np.float64)
-    #return np.ma.masked_where(arr == 0. + arr.mask, arr)
     arr = np.ma.masked_where(arr == 0. + arr.mask, arr)
     print('maskzeroes:', arr.min(), '->', arr.max(), arr.dtype, arr.mean())
-    #assert 0
     return arr
 
 def sums(nc,keys):

bgcval2/timeseries/timeseriesAnalysis.py

@@ -312,8 +312,6 @@ def loadModel(self):
                             ], self.metrics)):
                         lats = DL.load[(r, l, 'lat')]
                         lons = DL.load[(r, l, 'lon')]
-                        #print(lats, lons, len(lats), len(lons), lats.max(), lons.max())
-#                       assert 0
                         if l in volumeWeightedLayers:
                             depths = DL.load[(r, l, 'z')]
                             weights = np.array([
@@ -328,9 +326,6 @@ def loadModel(self):
                                    weights.append(0)
                                    continue  
 
-#                                if not self.weightsDict.get((la, lo), False):
-#                                    print('TimeseriesAnalysis: coords not in weights:', (la, lo))
-#                                    assert 0
                                 try:
                                     weights.append(self.weightsDict[(la, lo)])
                                 except:
@@ -475,8 +470,6 @@ def loadModelWeightsDict(self, ):
             if tmask.ndim == 2: 
                 area = np.ma.masked_where(tmask == 0, area)
             area = area.squeeze()
-        #print('loadModelWeightsDict: area:', area.shape, area.max())
-        #assert 0
         self.weightsDict = {}
         if self.modelcoords['lat'] == self.modelcoords['lon'] == False:
             ####
@@ -506,8 +499,6 @@ def loadModelWeightsDict(self, ):
         if self.debug:
             print("timeseriesAnalysis:\t loadModelWeightsDict.",
                   list(self.weightsDict.keys())[0])
-        #print('loadModelWeightsDict:', len(self.weightsDict.keys()), self.weightsDict)
-        #assert 0
 
     def loadModelwcvDict(self, ):
         """

bgcval2/timeseries/timeseriesTools.py

@@ -286,13 +286,6 @@ def save_json(
 
     filename = bvt.folder(csvFolder) + '_'.join([analysisname, name, region, layer, metric, ts ]) + csvformat
 
-#    json_arrD = {job:[float(d) for d in data] for job, data in arrD.items()}
-#    if region in ['IrmingerSea',]:
-#        for j in json_arrD:
-#            print('\n\n',j,name, region,  json_arrD[j])
-#            print('\n\n',j,name, region,  arrD[j])
-#            
-#        assert 0
     jsondata = {
             # json can't save numpy.float32, so we convert to list of floats.
             'timesD': {job:[float(t) for t in times] for job, times in timesD.items()},
@@ -498,11 +491,7 @@ def createDataArray(self, region, layer):
             self.oneDData['arr_lon'],
             self.oneDData['arr'],
         )
-#        print('createDataArray: mask:', len(m), sum(m))
-#        print(self.oneDData['arr_lat'][:3], self.oneDData['arr_lon'][:3])
         lat = np.ma.masked_where(m,self.oneDData['arr_lat'])
-#        print('createDataArray', lat.min(), lat.max())
-        #assert 0
 
         return  np.ma.masked_where(m,self.oneDData['arr']),\
          np.ma.masked_where(m,self.oneDData['arr_t']),\
@@ -532,8 +521,6 @@ def createOneDDataArray(self, layer):
             lat = self.nc.variables[self.coords['lat']][:]
             lon = bvt.makeLonSafeArr(self.nc.variables[self.coords['lon']]
                                      [:])  # makes sure it's between +/-180
-#            print('createOneDDataArray:', lat, lon)
-#            assert 0
             dims = choose_best_ncvar(self.nc, self.details['vars']).dimensions
             dat = self.__getlayerDat__(layer)
 
@@ -677,17 +664,8 @@ def createOneDDataArray(self, layer):
             print("Unknown dimensions order", dims)
             assert False
 
-        #print('lat:', arr_lat, 'lon:', arr_lon)
-        print('createOneDDataArray: Arr:', np.array(arr).min(), np.array(arr).max(), len(arr))
-
         arr = np.ma.masked_invalid(np.ma.array(arr))
-        print('createOneDDataArray: Arr:', np.array(arr).min(), np.array(arr).max(), len(arr))
-        #mask = np.ma.masked_where((arr > 1E20) + arr.mask, arr).mask
-        #print('len:', mask, np.sum(mask), len(mask))
         mask = arr.mask
-        #print('len:', mask, np.sum(mask), len(mask))
-
-        #assert 0  
 
         self.oneDData = {}
         self.oneDData['arr_lat'] = np.ma.masked_where(mask,