add multi variable support for phenology

pmlmodelling · Feb 4, 2025 · 339d44e · 339d44e
1 parent 82f2c66
commit 339d44e
Showing 1 changed file with 7 additions and 1 deletion.
diff --git a/ecoval/data/simdiff_phenology.ipynb b/ecoval/data/simdiff_phenology.ipynb
@@ -92,7 +92,8 @@
     "for mm in set(measures):\n",
     "\n",
     "\n",
-    "    mm_variables = list(set(df_options[df_options[\"measure\"] == mm][\"variable\"].values))\n",
+    "    mm_variables = list(set(df_options[df_options[\"measure\"] == mm].variable))\n",
+    "    # mm_variables = list(set(df_options[df_options[\"measure\"] == mm][\"variable\"].values))\n",
     "    rr_plot = True\n",
     "    for vv in mm_variables:\n",
     "        if True:\n",
@@ -123,9 +124,11 @@
     "            var = ds1_ave.variables[0]\n",
     "            ds1_ave = float(ds1_ave.to_dataframe()[var].values[0])\n",
     "            df_add = pd.DataFrame({\"simulation\": sim_0_name, \"variable\": var, \"value\": ds1_ave}, index = [0])\n",
+    "            df_add = df_add.assign(variable = vv)\n",
     "            df_ave.append(df_add)\n",
     "            ds2_ave = float(ds2_ave.to_dataframe()[var].values[0])\n",
     "            df_add = pd.DataFrame({\"simulation\": sim_1_name, \"variable\": var, \"value\": ds2_ave}, index = [0])\n",
+    "            df_add = df_add.assign(variable = vv)\n",
     "            df_ave.append(df_add)\n",
     "            # append to df_ave\n",
     "\n",
@@ -135,9 +138,12 @@
     "            df1[\"simulation\"] = sim_0_name\n",
     "            df2 = extract_df(ds2)\n",
     "            df2[\"simulation\"] = sim_1_name\n",
+    "            df1 = df1.assign(variable = vv)\n",
+    "            df2 = df2.assign(variable = vv)\n",
     "            df_all.append(pd.concat([df1, df2]))\n",
     "            ds1-ds2\n",
     "            df1 = extract_df(ds1)\n",
+    "            df1 = df1.assign(variable = vv)\n",
     "            df1[\"simulation\"] = sim_0_name\n",
     "            df_diff.append(df1)\n",
     "df_all = pd.concat(df_all).reset_index(drop = True)\n",