finish setting up the tests

configure.ac

@@ -127,8 +127,12 @@ AC_CHECK_PROGS(BATS, [bats])
 AC_CHECK_PROGS(PROVE, [prove])
 AM_CONDITIONAL([WITH_CHECK_PROGS], [test -n "$PROVE" -a -n "$BATS"])
 
-AC_CHECK_PROGS(python3, [required])
-AC_PYTHON_MODULE(xarray, required, python3)
+AC_PYTHON_MODULE(xarray, [], python3)
+if test ${HAVE_PYMOD_XARRAY} = yes; then
+  AM_CONDITIONAL([SKIP_XARRAY_TESTS], true )
+else
+  AM_CONDITIONAL([SKIP_XARRAY_TESTS], false )
+fi
 
 # Check if openacc.h exists
 if test "$enable_acc" = yes ; then

postprocessing/timavg/time_average.f90

@@ -600,7 +600,9 @@ program time_average
         if (itime > 0) then
             istat =  NF90_GET_VAR (ncid_in, varid_recdim, time, start=(/itime/))
             if (istat /= NF90_NOERR) call error_handler ('getting time coord value', ncode=istat)
+        endif
 
+        if (do_avg .and. itime > 0) then
             !--- read time bnds_info
             istat = NF90_GET_VAR (ncid_in, time_bnds_id, tavg(1:2), (/1, itime/))
             if (istat /= NF90_NOERR) call error_handler &

t/Makefile.am

@@ -23,8 +23,15 @@ else
 skip_MPI="skip"
 endif
 
+if SKIP_XARRAY_TESTS
+skipflag="skip"
+else
+skipflag=""
+endif
+
 TESTS_ENVIRONMENT = top_srcdir=$(abs_top_srcdir); export top_srcdir;\
                     export skip_mpi=$(skip_MPI);                    \
+                    export skip_xarray=$(skipflag);                 \
     for d in $$( find $(abs_top_builddir)/postprocessing $(abs_top_builddir)/tools -mindepth 1 -not -path '*/\.*' -type d ); do \
       PATH="$$d"'$(PATH_SEPARATOR)'"$$PATH"; \
     done;

t/Test34-timavg.sh

@@ -23,16 +23,21 @@
 load test_utils
 
 @test "Test timavg" {
-cat <<_EOF > input.nml
+if [ -z "$skip_mpi" ]; then
+cat <<_EOF > instantaneous.nml
  &input
-    file_names(1) =  '20120101.ice_shelf.nc' ,
-    file_name_out =  'new.nc' ,
-    use_end_time  =  .false. ,
-    verbose  =  .false. ,
-    add_cell_methods =  .false. ,
-    skip_tavg_errors =  .false. ,
-    suppress_warnings =  .false.,
+    file_names(1) =  'timavg_instantaneous_in.nc' ,
+    file_name_out =  'timavg_instantaneous_out.nc' ,
  &end
 _EOF
+
+cat <<_EOF > standard.nml
+ &input
+    file_names(1) =  'timavg_standard_in.nc' ,
+    file_name_out =  'timavg_standard_out.nc' ,
+ &end
+_EOF
+
     python3 $top_srcdir/t/test_time_avg.py
+fi
 }

t/test_time_avg.py

@@ -4,55 +4,98 @@
 import numpy as np
 import os
 
-def init_fake_data(a, count=0., factor=1.):
-    with np.nditer(a, op_flags=['readwrite']) as it:
-        for x in it:
-            count = count + 1
-            x[...] = count * factor
+class TestTimeAvg:
+    def __init__(self, Test_case):
+        self.Test_case = Test_case
+        if self.Test_case == 1:
+            self.In_file = "timavg_instantaneous_in.nc"
+            self.Out_file = "timavg_instantaneous_out.nc"
+            self.Namelist_file = "instantaneous.nml"
+            self.Error_msg = "timavg with instantaneous input"
+        elif self.Test_case == 2:
+            self.In_file = "timavg_standard_in.nc"
+            self.Out_file = "timavg_standard_out.nc"
+            self.Namelist_file = "standard.nml"
+            self.Error_msg = "timavg with standard input"
 
-class TestTimeAvg():
-    def create_input(self):
-        print("Creating input files to test with")
-        nx = 96
-        ny = 96
-        nt = 12
-
-        a = np.zeros([nt, ny, nx])
-        for k in range(0,nt):
-          for j in range(0,ny):
-            for i in range(0,nx):
-                a[k, j, i] = (i+1.)*1000 + (j+1.)*10 + (k+1.)/100.
-        self.a = a
-
-        Time_attrs = {"units": "days since 2000-01-01", "axis": "T", "calendar_type": "JULIAN", "calendar": "julian"} 
+
+    def create_instantaneous(self):
+        Time_attrs = {"units": "days since 2000-01-01", "axis": "T", "calendar_type": "JULIAN", "calendar": "julian"}
+        ds1 = xr.Dataset(
+        data_vars={
+            ## This is backwards #FORTRAN4LYFE
+            "a": (("Time", "y", "x"), self.a),
+            "Time": (("Time", self.time_data, Time_attrs))
+        },
+        coords={
+            "x": np.arange(self.nx)*1.0,
+            "y": np.arange(self.ny)*1.0,
+        },
+        )
+        ds1.to_netcdf(self.In_file, unlimited_dims="Time")
+
+    def create_standard(self):
+        Time_attrs = {"units": "days since 2000-01-01", "axis": "T", "calendar_type": "JULIAN", "calendar": "julian",
+                      "bounds": "time_bnds"}
         ds1 = xr.Dataset(
         data_vars={
             ## This is backwards #FORTRAN4LYFE
-            "a": (("Time", "y", "x"), a),
-            "Time": (("Time", np.arange(nt)*1.0+1, Time_attrs))
+            "a": (("Time", "y", "x"), self.a),
+            "Time": (("Time", self.time_data, Time_attrs)),
+            "time_bnds": (("Time", "nv"), self.time_bnds_data)
         },
         coords={
-            "x": np.arange(nx)*1.0,
-            "y": np.arange(ny)*1.0,
+            "x": np.arange(self.nx)*1.0,
+            "y": np.arange(self.ny)*1.0,
+            "nv": np.arange(2)*1.0+1,
         },
         )
-        ds1.to_netcdf("20120101.ice_shelf.nc", unlimited_dims="Time")
+        ds1.to_netcdf(self.In_file, unlimited_dims="Time")
+
+
+    def create_input(self):
+        self.nx = 96
+        self.ny = 96
+        self.nt = 12
+        self.time_data = np.arange(self.nt)*1.0+1
+
+        self.a = np.zeros([self.nt, self.ny, self.nx])
+        for k in range(0,self.nt):
+            for j in range(0,self.ny):
+              for i in range(0,self.nx):
+                  self.a[k, j, i] = (i+1.)*1000 + (j+1.)*10 + (k+1.)/100.
+
+        if self.Test_case == 1:
+            self.create_instantaneous()
+        elif self.Test_case == 2:
+            self.time_bnds_data = np.zeros([self.nt, 2])
+            self.time_bnds_data[:,1] = self.time_data[0:]
+            self.time_bnds_data[1:,0] = self.time_data[0:-1]
+            self.create_standard()
+
+
+    def run_test(self):
+      exit_code = os.system("TAVG.exe < " + self.Namelist_file)
+      if exit_code != 0 :
+          raise Exception(self.Error_msg + ":: Failed to complete")
 
 
     def check_output(self):
-      out_file = xr.open_dataset("new.nc")
+      out_file = xr.open_dataset(self.Out_file)
       if not (out_file.a.values == np.average(self.a, axis=0)).all():
-          raise Exception("Test failed")
+          raise Exception(self.Error_msg + ":: answers were not the expected result!")
 
 
-test_class = TestTimeAvg()
+# Test time_average when the input is instantaneous (so no time bounds)
+Test_Instantaneous = 1
+test_class = TestTimeAvg(Test_Instantaneous)
 test_class.create_input()
+test_class.run_test()
+test_class.check_output()
 
-exit_code = os.system("TAVG.exe < input.nml")
-if exit_code != 0 :
-    raise Exception("Failed to run timavg")
-
-try:
-    test_class.check_output()
-except:
-    raise Exception("Failed to check the timavg output")
+# Test time_average when the input is standard (with time_bounds, no average_* variables)
+Test_Standard = 2
+test_class = TestTimeAvg(Test_Standard)
+test_class.create_input()
+test_class.run_test()
+test_class.check_output()