Update approval test

Author: greenape

.circleci/approved/npl-approvalstest-2016-01-01/notebooks/reports/active_crisis.ipynb

@@ -1458,18 +1458,18 @@
     "        excess_arrivals_df=regional_dataframe,\n",
     "        arrivals_from_aa=arrivals_from_aa,\n",
     "        key_dates=key_dates,\n",
-    "        aa_name=aa,\n",
+    "        aa_name=excess_arrivals_past_week_w_geo.index_AA.unique().values[0],\n",
     "        output_folder=output_path,\n",
     "        date_string=date_string,\n",
     "    )\n",
     "    outputs_dict[\"affected_areas\"][aa][\"top3_adm_hosts\"] = str(top_3_adm_hosts_path)\n",
     "\n",
     "# National level top3 hosts\n",
     "top_3_adm_hosts_multi_aa_path = top_3_adm_hosts_multi_aa(\n",
-    "    excess_arrivals_df=regional_dataframe,\n",
+    "    excess_arrivals_df=excess_arrivals_past_week_w_geo,\n",
     "    arrivals_from_aa=arrivals_from_aa,\n",
     "    key_dates=key_dates,\n",
-    "    aa_name=list(excess_arrivals_past_week_w_geo.name.unique()),\n",
+    "    aa_name=list(excess_arrivals_past_week_w_geo.index_AA.unique()),\n",
     "    output_folder=output_path,\n",
     "    date_string=date_string,\n",
     ")\n",

.circleci/approved/npl-approvalstest-2016-01-01/notebooks/reports/visualisations/active_crisis/plotting.py

@@ -5,6 +5,7 @@
 from pandas import DataFrame
 import numpy as np
 from slugify import slugify
+from cycler import cycler
 
 px = 1 / plt.rcParams["figure.dpi"]
 
@@ -106,6 +107,9 @@ def top_3_adm_hosts(
     aa_name: str,
     output_folder: Path,
 ):
+    color_cycle_iter = cycler(
+        color=["#034174", "#CBA45A", "#701F53", "#006E8C", "#BF6799", "#00989A", "#9E6257"]
+    )()
     def _plot_arrivals(df, ax):
         df = df.set_index("date")
 
@@ -206,6 +210,9 @@ def top_3_adm_hosts_multi_aa(
     aa_name: list[str],
     output_folder: Path,
 ):
+    color_cycle_iter = cycler(
+        color=["#034174", "#CBA45A", "#701F53", "#006E8C", "#BF6799", "#00989A", "#9E6257"]
+    )()
     def _plot_arrivals(df, ax):
         df = df.groupby("date").sum()