Feature 1954 semilatlon

.github/jobs/build_docker_image.sh

@@ -15,5 +15,8 @@ time_command docker build -t ${DOCKERHUB_TAG} \
     -f $DOCKERFILE_PATH ${GITHUB_WORKSPACE}
 if [ $? != 0 ]; then
   cat ${GITHUB_WORKSPACE}/docker_build.log
+  # Append the full make_install.log file
+  echo "Appending make_install.log to docker_build.log. See the logs artifact for details."
+  cat ${GITHUB_WORKSPACE}/make_install.log >> ${GITHUB_WORKSPACE}/docker_build.log
   exit 1
 fi

docs/Users_Guide/appendixB.rst

@@ -23,6 +23,8 @@ The following map projections are currently supported in MET:
 
 * Gaussian Projection
 
+* Semi Lat/Lon
+
 Grid Specification Strings
 ==========================
 
@@ -82,6 +84,10 @@ For a Gaussian grid, the syntax is
 
 The parameters **Nx** and **Ny** are as before, while **lon_zero** defines the first longitude.
 
+For a Semi Lat/Lon grid, no grid specification string is supported. This grid type is only supported via Python embedding or when reading NetCDF files generated by another MET tool. A Semi Lat/Lon grid defines the information about 2D field of data whose dimension are defined by arrays of latitude (**lats**), longitude (**lons**), level (**levels**), and time (**times**). Times are defined as unixtime, the number of seconds since January 1, 1970. Typically, the lats or lons array and the levels or times array has non-zero length. For example, a zonal mean field is defined using the lats and levels array. A meridional mean field is defined using the lons and levels array. A Hovmoeller field is defined using lats or lons versus times. An arbitrary cross-section is defined by specifying both the lats and lons array with exactly the same length versus levels or times.
+
+Statistics can be computed from data on Semi Lat/Lon grids but only when all data resides on the same Semi Lat/Lon grid. Two Semi Lat/Lon grids are equal when their lats, lons, levels, and times arrays match. No functionality is provided to regrid Semi Lat/Lon data. The MET tools can plot Semi Lat/Lon data, however no map data is overlaid since these grids lack two spatial dimensions.
+
 Grids
 =====
 

docs/Users_Guide/appendixF.rst

@@ -173,6 +173,15 @@ When specified as a dictionary, the contents of the **grid** dictionary vary bas
   • lon_zero (double)
   • nx, ny   (int)
 
+• **SemiLatLon** grid dictionary entries:
+
+  • type     ("SemiLatLon")
+  • name     (string)
+  • lats     (list of doubles)
+  • lons     (list of doubles)
+  • levels   (list of doubles)
+  • times    (list of doubles)
+
 Additional information about supported grids can be found in :ref:`appendixB`.
 
 **Using Xarray DataArrays**

internal/test_unit/xml/unit_python.xml

@@ -587,4 +587,45 @@
     </output>
   </test>
 
+  <test name="python_plot_data_plane_SEMILATLON_ZONAL_MEAN">
+    <exec>&MET_BIN;/plot_data_plane</exec>
+    <param> \
+    PYTHON_NUMPY \
+    &OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_ZONAL_MEAN.ps \
+    'name="&MET_BASE;/python/derive_WRF_semilatlon.py &DATA_DIR_MODEL;/p_interp/wrfout_d01_2008-08-08_12:00:00_PLEV TT lat";' \
+    -title "WRF Zonal Mean" \
+    -v 1
+    </param>
+    <output>
+      <ps>&OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_ZONAL_MEAN.ps</ps>
+    </output>
+  </test>
+
+  <test name="python_pcp_combine_SEMILATLON_MERIDIONAL_MEAN">
+    <exec>&MET_BIN;/pcp_combine</exec>
+    <param> \
+    -add PYTHON_NUMPY \
+    'name="&MET_BASE;/python/derive_WRF_semilatlon.py &DATA_DIR_MODEL;/p_interp/wrfout_d01_2008-08-08_12:00:00_PLEV TT lon";' \
+    &OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_MERIDIONAL_MEAN.nc \
+    -name "TT_MERIDIONAL_MEAN" -v 1
+    </param>
+    <output>
+      <grid_nc>&OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_MERIDIONAL_MEAN.nc</grid_nc>
+    </output>
+  </test>
+
+  <test name="python_plot_data_plane_SEMILATLON_MERIDIONAL_MEAN">
+    <exec>&MET_BIN;/plot_data_plane</exec>
+    <param> \
+    &OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_MERIDIONAL_MEAN.nc \
+    &OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_MERIDIONAL_MEAN.ps \
+    'name="TT_MERIDIONAL_MEAN"; level="(*,*)";' \
+    -title "WRF Meridional Mean" \
+    -v 1
+    </param>
+    <output>
+      <ps>&OUTPUT_DIR;/python/wrfout_d01_2008-08-08_12_00_00_PLEV_MERIDIONAL_MEAN.ps</ps>
+    </output>
+  </test>
+
 </met_test>

internal/test_util/libcode/vx_grid/Makefile.am

@@ -20,6 +20,7 @@ test_grid_area_LDADD = -lvx_grid \
 	-lvx_util_math \
 	-lvx_util \
 	-lvx_math \
+	-lvx_cal \
 	-lvx_log \
 	-lz \
 	-lm

internal/test_util/libcode/vx_grid/Makefile.in

@@ -320,6 +320,7 @@ test_grid_area_LDADD = -lvx_grid \
 	-lvx_util_math \
 	-lvx_util \
 	-lvx_math \
+	-lvx_cal \
 	-lvx_log \
 	-lz \
 	-lm

scripts/python/Makefile.am

@@ -32,7 +32,8 @@ pythonscripts_DATA = \
 	read_ascii_xarray.py \
 	read_ascii_point.py \
 	read_ascii_mpr.py \
-	read_met_point_obs.py
+	read_met_point_obs.py \
+	derive_WRF_semilatlon.py
 
 EXTRA_DIST = ${pythonscripts_DATA}
 

scripts/python/Makefile.in

@@ -303,7 +303,8 @@ pythonscripts_DATA = \
 	read_ascii_xarray.py \
 	read_ascii_point.py \
 	read_ascii_mpr.py \
-	read_met_point_obs.py
+	read_met_point_obs.py \
+	derive_WRF_semilatlon.py
 
 EXTRA_DIST = ${pythonscripts_DATA}
 MAINTAINERCLEANFILES = Makefile.in

scripts/python/derive_WRF_semilatlon.py

@@ -0,0 +1,103 @@
+from __future__ import print_function
+
+import os
+import sys
+import numpy as np
+import datetime as dt
+from netCDF4 import Dataset,chartostring
+
+###########################################
+
+   ##
+   ##  input file specified on the command line
+   ##  load the data into the numpy array
+   ##
+
+if len(sys.argv) == 4:
+    # Read the input file as the first argument
+    input_file = os.path.expandvars(sys.argv[1])
+    var_name   = sys.argv[2]
+    axis       = sys.argv[3]
+
+    try:
+        # Print some output to verify that this script ran
+        print("Input File: " + repr(input_file))
+        print("Variable: "   + repr(var_name))
+        print("Axis: "       + repr(axis))
+
+        # Read input file
+        f = Dataset(input_file, 'r')
+
+        data = np.float64(f.variables[var_name][0,:,:,:])
+        data[data > 1.0e30] = np.nan
+
+        pvals = list(np.float64(f.variables["pressure"][:]))
+
+        if axis == "lon":
+           met_data = np.nanmean(data[::-1], axis=1).copy()
+        elif axis == "lat":
+           met_data = np.nanmean(data[::-1], axis=2).transpose().copy()
+        elif axis == "latlon":
+           met_data = np.nanmean(data[::-1], axis=1).copy()
+        else:
+           print("ERROR: Unsupported axis type: " + axis)
+           sys.exit(1)
+
+        print("Data Shape: " + repr(met_data.shape))
+        print("Data Type:  " + repr(met_data.dtype))
+    except NameError:
+        print("Trouble reading data from input file")
+else:
+    print("Must specify exactly one input file, variable name, and summary axis (lat, lon, latlon).")
+    sys.exit(1)
+
+###########################################
+
+   ##
+   ##  create the metadata dictionary
+   ##
+
+init      = dt.datetime.strptime(getattr(f, "START_DATE"), "%Y-%m-%d_%H:%M:%S")
+valid_ref = dt.datetime.strptime(getattr(f.variables["Time"], "units"), "hours since %Y-%m-%d %H:%M:%S")
+add_hours = float(f.variables["Time"][:])
+valid     = valid_ref + dt.timedelta(hours=add_hours)
+lead, rem = divmod((valid-init).total_seconds(), 3600)
+accum     = "00"
+
+   # Use the first column of lats
+
+if axis == "lon":
+   lats   = list()
+   lons   = list(np.float64(f.variables["XLONG"][0,0,:]))
+elif axis == "lat":
+   lats   = list(np.float64(f.variables["XLAT"][0,:,0]))
+   lons   = list()
+elif axis == "latlon":
+   lats   = list(np.float64(f.variables["XLONG"][0,0,:]))
+   lons   = list(np.float64(f.variables["XLAT"][0,0,:]))
+
+levels = list(pvals)
+times  = list()
+
+attrs = {
+   'valid': valid.strftime("%Y%m%d_%H%M%S"),
+   'init':   init.strftime("%Y%m%d_%H%M%S"),
+   'lead':   str(int(lead)),
+   'accum':  accum,
+
+   'name':      var_name,
+   'long_name': str(getattr(f.variables[var_name], "description")),
+   'level':     axis + "_mean",
+   'units':     str(getattr(f.variables[var_name], "units")),
+
+   'grid': {
+     'type'   : "SemiLatLon",
+     'name'   : axis + "_mean",
+     'lats'   : lats,
+     'lons'   : lons,
+     'levels' : levels,
+     'times'  : times
+   }
+}
+
+print("Attributes: " + repr(attrs))

src/basic/vx_cal/time_array.cc

@@ -94,6 +94,30 @@ return ( * this );
 ////////////////////////////////////////////////////////////////////////
 
 
+bool TimeArray::operator==(const TimeArray & a) const
+
+{
+
+if ( Nelements != a.Nelements )  return ( false );
+
+bool status = true;
+
+for (int j=0; j<(Nelements); ++j)  {
+
+   if ( e[j] != a.e[j] )  {
+      status = false;
+      break;
+   }
+}
+
+return ( status );
+
+}
+
+
+////////////////////////////////////////////////////////////////////////
+
+
 void TimeArray::init_from_scratch()
 
 {
@@ -460,6 +484,27 @@ return(u);
 ////////////////////////////////////////////////////////////////////////
 
 
+ConcatString TimeArray::serialize() const
+
+{
+
+   ConcatString s;
+
+   if(n_elements() == 0) return(s);
+
+   int j;
+
+   s << e[0];
+   for(j=1; j<n_elements(); j++) s << " " << unix_to_yyyymmdd_hhmmss(e[j]);
+
+   return(s);
+
+}
+
+
+////////////////////////////////////////////////////////////////////////
+
+
 void TimeArray::sort_array()
 
 {

src/basic/vx_cal/time_array.h

@@ -52,6 +52,7 @@ class TimeArray {
      ~TimeArray();
       TimeArray(const TimeArray &);
       TimeArray & operator=(const TimeArray &);
+      bool operator==(const TimeArray &) const;
 
       void clear();
 
@@ -80,6 +81,8 @@ class TimeArray {
       unixtime min() const;
       unixtime max() const;
 
+      ConcatString serialize() const;
+
       int n_elements() const;
       int n() const;
 
@@ -96,7 +99,7 @@ inline int TimeArray::n()          const { return ( Nelements ); }
 ////////////////////////////////////////////////////////////////////////
 
 
-extern ConcatString write_css                (const TimeArray &);
+extern ConcatString write_css(const TimeArray &);
 
 
 ////////////////////////////////////////////////////////////////////////

src/basic/vx_util/num_array.cc

@@ -93,6 +93,31 @@ NumArray & NumArray::operator=(const NumArray & a)
 ////////////////////////////////////////////////////////////////////////
 
 
+bool NumArray::operator==(const NumArray & a) const
+
+{
+
+   if ( e.size() != a.e.size() )  return ( false );
+
+   bool status = true;
+   int n = e.size();
+
+   for (int j=0; j<n; ++j)  {
+
+      if ( e[j] != a.e[j] )  {
+         status = false;
+         break;
+      }
+   }
+
+   return ( status );
+
+}
+
+
+////////////////////////////////////////////////////////////////////////
+
+
 void NumArray::init_from_scratch()
 
 {
@@ -984,6 +1009,36 @@ ConcatString NumArray::serialize() const
 ////////////////////////////////////////////////////////////////////////
 
 
+ConcatString NumArray::summarize() const
+
+{
+
+   ConcatString s;
+
+   s << "n = " << n_elements();
+
+   if(n_elements() > 0) {
+
+      double min_v, max_v;
+      min_v = max_v = e[0];
+
+      for(int j=0; j<n_elements(); j++) {
+         if(is_bad_data(e[j])) continue;
+         if(e[j] < min_v) min_v = e[j];
+         if(e[j] > max_v) max_v = e[j];
+      }
+
+      s << ", min = " << min_v << ", max = " << max_v;
+   }
+
+   return(s);
+
+}
+
+
+////////////////////////////////////////////////////////////////////////
+
+
 NumArray NumArray::subset(int beg, int end) const
 
 {