fix to inverting y

had to both invert sf/ao and the value itself,
since sf/ao are removed during netcdf storage

himawari/ahi2cmi.py

@@ -372,23 +372,23 @@ class HimawariAHIasCMIP(object):
         _, _, mb = self._hs.coords(lines=1, columns=1, unscaled=True)
         y, x = self.y, self.x
 
-        def yx_pvda(name, v, m, b):
+        def yx_pvda(name, v, m, b, invert=False):
             assert (name in {'y', 'x'})
             a = {
                 '.dtype': np.int16,  # annotation telling goesr.rockfall.nc_write what kind of var to make
                 'units': 'rad',
                 'long_name': "AHI fixed grid projection %s-coordinate" % name,
                 'standard_name': "projection_%s_coordinate" % name,
-                'scale_factor': -m if name=='y' else m,  # PUG has negative y north of equator
-                'add_offset': -b if name=='y' else b  # ref GIT 3ebfc9ab1f
+                'scale_factor': -m if invert else m,  # PUG has negative y north of equator; prefer monotonic +1 raw value however
+                'add_offset': -b if invert else b  # ref GIT 3ebfc9ab1f
             }
             # y/x
-            yield self.p(name), v, self.d(name), a
+            yield self.p(name), -v if invert else v, self.d(name), a
 
             # y_image/x_image single value
             v_image = np.nanmean(v)
             a['long_name'] = "AHI fixed grid projection %s-coordinate center of image" % name,
-            yield self.p('%s_image' % name), v_image, {}, a
+            yield self.p('%s_image' % name), -v_image if invert else v_image, {}, a
 
             # y_image_bounds
             vrange = np.array([np.nanmin(v), np.nanmax(v)])
@@ -398,10 +398,10 @@ class HimawariAHIasCMIP(object):
             }[name]
             a = {}
             a['long_name'] = "AHI fixed grid projection %s-coordinate %s extent of image" % (name, nsew)
-            yield self.p('%s_image_bounds' % name), vrange, self.d(DEFAULT_YX_BOUNDS_NAME), a
+            yield self.p('%s_image_bounds' % name), -vrange if invert else vrange, self.d(DEFAULT_YX_BOUNDS_NAME), a
 
         # y and x variables and their bounds and centerpoints
-        for each in yx_pvda('y', y, mb.my, mb.by):
+        for each in yx_pvda('y', y, mb.my, mb.by, invert=True):
             yield each
 
         for each in yx_pvda('x', x, mb.mx, mb.bx):