MJO xcdat conversion

pcmdi_metrics/mjo/lib/__init__.py

@@ -2,9 +2,7 @@
 from .debug_chk_plot import debug_chk_plot  # noqa
 from .dict_merge import dict_merge  # noqa
 from .lib_mjo import (  # noqa
-    Remove_dailySeasonalCycle,
     calculate_ewr,
-    decorate_2d_array_axes,
     generate_axes_and_decorate,
     get_daily_ano_segment,
     interp2commonGrid,
@@ -13,7 +11,6 @@
     space_time_spectrum,
     subSliceSegment,
     taper,
-    unit_conversion,
     write_netcdf_output,
 )
 from .mjo_metric_calc import mjo_metric_ewr_calculation  # noqa

pcmdi_metrics/mjo/lib/debug_chk_plot.py

@@ -4,29 +4,15 @@
 import matplotlib.pyplot as plt
 from cartopy.mpl.ticker import LatitudeFormatter, LongitudeFormatter
 
+from pcmdi_metrics.io import get_latitude, get_longitude
+
 
 def debug_chk_plot(d_seg_x_ano, Power, OEE, segment_year, daSeaCyc, segment_ano_year):
     os.makedirs("debug", exist_ok=True)
 
-    """ FIX ME ---
-    x = vcs.init()
-    x.plot(d_seg_x_ano)
-    x.png('debug/d_seg_x_ano.png')
-
-    x.clear()
-    x.plot(Power)
-    x.png('debug/power.png')
-
-    x.clear()
-    x.plot(OEE)
-    x.png('debug/OEE.png')
-    """
-
     print("type(segment_year)", type(segment_year))
     print("segment_year.shape:", segment_year.shape)
-    print(segment_year.getAxis(0))
-    print(segment_year.getAxis(1))
-    print(segment_year.getAxis(2))
+
     plot_map(segment_year[0], "debug/segment.png")
 
     print("type(daSeaCyc)", type(daSeaCyc))
@@ -35,16 +21,14 @@ def debug_chk_plot(d_seg_x_ano, Power, OEE, segment_year, daSeaCyc, segment_ano_
 
     print("type(segment_ano_year)", type(segment_ano_year))
     print("segment_ano_year.shape:", segment_ano_year.shape)
-    print(segment_ano_year.getAxis(0))
-    print(segment_ano_year.getAxis(1))
-    print(segment_ano_year.getAxis(2))
+
     plot_map(segment_ano_year[0], "debug/segment_ano.png")
 
 
 def plot_map(data, filename):
     fig = plt.figure(figsize=(10, 6))
-    lons = data.getLongitude()
-    lats = data.getLatitude()
+    lons = get_longitude(data)
+    lats = get_latitude(data)
     ax = plt.axes(projection=ccrs.PlateCarree(central_longitude=180))
     im = ax.contourf(lons, lats, data, transform=ccrs.PlateCarree(), cmap="viridis")
     ax.coastlines()