comment cwd

pcmdi_metrics/drcdm/lib/compute_metrics.py

@@ -1,15 +1,16 @@
-#!/usr/bin/env python
 import datetime
 
 import cftime
 import matplotlib.pyplot as plt
 import numpy as np
 import xarray as xr
 import xcdat as xc
-import xclim
 
 from pcmdi_metrics.stats import compute_statistics_dataset as pmp_stats
 
+# import xclim
+
+
 bgclr = [0.45, 0.45, 0.45]
 
 
@@ -1070,6 +1071,7 @@ def get_annual_pxx(
 ):
  varname = "pr"
  index = "annual_pxx"
+ print("Metric:", index)
 
  # Get annual max precipitation
  PR = TimeSeriesData(ds, varname)
@@ -1104,18 +1106,20 @@ def get_annual_pxx(
  return result_dict
 
 
+"""
 def get_annual_cwd(
  ds, sftlf, dec_mode, drop_incomplete_djf, annual_strict, fig_file=None, nc_file=None
 ):
  index = "annual_cwd"
+ print("Metric:", index)
 
  # Get annual max precipitation
  ds["pr"] = ds["pr"].where(sftlf.sftlf >= 0.5).where(sftlf.sftlf <= 1)
  Pcwd = xr.Dataset()
  Pcwd["ANN"] = xclim.indices.maximum_consecutive_wet_days(
  ds.pr, thresh="1 mm/day", freq="YS", resample_before_rl=True
  )
- Pcwd["time"].encoding["calendar"] = ds.time.encoding["calendar"]
+ Pcwd["time"].encoding["calendar"] = ds.time["calendar"]
  Pcwd = update_nc_attrs(Pcwd, dec_mode, drop_incomplete_djf, annual_strict)
 
  result_dict = metrics_json({index: Pcwd}, obs_dict={}, region="land", regrid=False)
@@ -1135,6 +1139,7 @@ def get_annual_cwd(
 
  del Pcwd
  return result_dict
+"""
 
 
 # A couple of statistics that aren't being loaded from mean_climate