update figures

pcmdi_metrics/sea_ice/scripts/sea_ice_figures.py

@@ -37,10 +37,12 @@
 metrics = {"RESULTS": {}}
 for metrics_file in glob.glob(filelist):
  with open(metrics_file) as mf:
- results = json.load(mf)["RESULTS"]
- model_list.append(list(results.keys())[0])
- metrics["RESULTS"].update(results)
+ results = json.load(mf)
+ for item in results["DIMENSIONS"]["model"]:
+ model_list.append(item)
+ metrics["RESULTS"].update(results["RESULTS"])
 
+model_list.sort()
 tmp = model_list[0]
 reference_data_set = list(metrics["RESULTS"][tmp]["arctic"]["model_mean"].keys())[0]
 
@@ -115,27 +117,18 @@
  mark_size = 1
  ax7[inds].bar(ind - width / 2.0, mse_clim, width, color="b", label="Ann. Cycle")
  ax7[inds].bar(ind, mse_ext, width, color="r", label="Ann. Mean")
- if len(clim_err_x) > 0:
- ax7[inds].scatter(
- [x - width / 2.0 for x in clim_err_x],
- clim_err_y,
- marker="D",
- s=mark_size,
- color="k",
- )
- ax7[inds].scatter(clim_err_x, ext_err_y, marker="D", s=mark_size, color="k")
- # xticks
+
+ # X axis label
  if inds == len(sector_list) - 1:
  ax7[inds].set_xticks(ind + width / 2.0, mlabels, rotation=90, size=7)
  else:
  ax7[inds].set_xticks(ind + width / 2.0, labels="")
- # yticks
- if len(clim_err_y) > 0:
- datamax = np.max(np.array(clim_err_y))
- else:
- datamax = np.max(np.array(mse_clim))
+
+ # Y axis
+ datamax = np.nanmax(np.concatenate((np.array(mse_clim), np.array(mse_ext))))
  ymax = (datamax) * 1.3
  ax7[inds].set_ylim(0.0, ymax)
+ print(ymax)
  if ymax < 0.1:
  ticks = np.linspace(0, 0.1, 6)
  labels = [str(round(x, 3)) for x in ticks]
@@ -151,8 +144,8 @@
  else:
  ticks = range(0, round(ymax))
  labels = [str(round(x, 0)) for x in ticks]
-
  ax7[inds].set_yticks(ticks, labels, fontsize=8)
+
  # labels etc
  ax7[inds].set_ylabel("10${^1}{^2}$km${^4}$", size=8)
  ax7[inds].grid(True, linestyle=":")
@@ -162,6 +155,8 @@
  xycoords="axes fraction",
  size=9,
  )
+ aw = 0.07
+
 # Add legend, save figure
 ax7[0].legend(loc="upper right", fontsize=6)
 plt.suptitle("Mean Square Error relative to " + reference_data_set, y=0.91)