diff --git a/docs/getting_started/asset_level_impacts.ipynb b/docs/getting_started/asset_level_impacts.ipynb
index b29e3b02..e92fad23 100644
--- a/docs/getting_started/asset_level_impacts.ipynb
+++ b/docs/getting_started/asset_level_impacts.ipynb
@@ -181,10 +181,31 @@
     "\n",
     "fig1 = make_subplots(rows=1, cols=1)\n",
     "\n",
-    "fig1.add_scatter(x=exceedance_histo[\"exceed_probabilities\"], y=exceedance_histo[\"values\"], name=\"baseline wind\", row=1, col=1)\n",
-    "fig1.add_scatter(x=exceedance_ssp585[\"exceed_probabilities\"], y=exceedance_ssp585[\"values\"], name=\"wind SSP585\", row=1, col=1)\n",
-    "fig1.update_xaxes(title=\"Annual exceedance probability\", title_font={\"size\": 14}, row=1, col=1, type=\"log\", autorange=\"reversed\")\n",
-    "fig1.update_yaxes(title=\"Damage as fraction of insurable value\", title_font={\"size\": 14}, row=1, col=1)\n"
+    "fig1.add_scatter(\n",
+    "    x=exceedance_histo[\"exceed_probabilities\"],\n",
+    "    y=exceedance_histo[\"values\"],\n",
+    "    name=\"baseline wind\",\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
+    "fig1.add_scatter(\n",
+    "    x=exceedance_ssp585[\"exceed_probabilities\"],\n",
+    "    y=exceedance_ssp585[\"values\"],\n",
+    "    name=\"wind SSP585\",\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
+    "fig1.update_xaxes(\n",
+    "    title=\"Annual exceedance probability\",\n",
+    "    title_font={\"size\": 14},\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    "    type=\"log\",\n",
+    "    autorange=\"reversed\",\n",
+    ")\n",
+    "fig1.update_yaxes(\n",
+    "    title=\"Damage as fraction of insurable value\", title_font={\"size\": 14}, row=1, col=1\n",
+    ")"
    ]
   },
   {
@@ -229,7 +250,9 @@
     "asset_measures_dict = {}\n",
     "for i in asset_measures:\n",
     "    key = i[\"key\"]\n",
-    "    asset_measures_dict[Key(key[\"hazard_type\"], key[\"measure_id\"], key[\"scenario_id\"], key[\"year\"])] = i\n",
+    "    asset_measures_dict[\n",
+    "        Key(key[\"hazard_type\"], key[\"measure_id\"], key[\"scenario_id\"], key[\"year\"])\n",
+    "    ] = i\n",
     "\n",
     "wind_impact_scores = asset_measures_dict[Key(\"Wind\", \"measure_set_0\", \"ssp585\", \"2050\")]\n",
     "\n",
@@ -280,7 +303,11 @@
     }
    ],
    "source": [
-    "pp.pprint(response[\"risk_measures\"][\"score_based_measure_set_defn\"][\"score_definitions\"][\"measure_1\"])"
+    "pp.pprint(\n",
+    "    response[\"risk_measures\"][\"score_based_measure_set_defn\"][\"score_definitions\"][\n",
+    "        \"measure_1\"\n",
+    "    ]\n",
+    ")"
    ]
   },
   {
diff --git a/docs/getting_started/hazard_indicators.ipynb b/docs/getting_started/hazard_indicators.ipynb
index cc6ef42e..c535781e 100644
--- a/docs/getting_started/hazard_indicators.ipynb
+++ b/docs/getting_started/hazard_indicators.ipynb
@@ -70,8 +70,30 @@
     "request = {\n",
     "    \"items\": [\n",
     "        {\n",
-    "            \"longitudes\": [69.4787, 68.71, 20.1047, 19.8936, 19.6359, 0.5407, 6.9366, 6.935, 13.7319, 13.7319],\n",
-    "            \"latitudes\": [34.556, 35.9416, 39.9116, 41.6796, 42.0137, 35.7835, 36.8789, 36.88, -12.4706, -12.4706],\n",
+    "            \"longitudes\": [\n",
+    "                69.4787,\n",
+    "                68.71,\n",
+    "                20.1047,\n",
+    "                19.8936,\n",
+    "                19.6359,\n",
+    "                0.5407,\n",
+    "                6.9366,\n",
+    "                6.935,\n",
+    "                13.7319,\n",
+    "                13.7319,\n",
+    "            ],\n",
+    "            \"latitudes\": [\n",
+    "                34.556,\n",
+    "                35.9416,\n",
+    "                39.9116,\n",
+    "                41.6796,\n",
+    "                42.0137,\n",
+    "                35.7835,\n",
+    "                36.8789,\n",
+    "                36.88,\n",
+    "                -12.4706,\n",
+    "                -12.4706,\n",
+    "            ],\n",
     "            \"request_item_id\": \"my_flood_request\",\n",
     "            \"hazard_type\": \"RiverineInundation\",\n",
     "            \"indicator_id\": \"flood_depth\",\n",
@@ -79,8 +101,30 @@
     "            \"year\": 1980,\n",
     "        },\n",
     "        {\n",
-    "            \"longitudes\": [69.4787, 68.71, 20.1047, 19.8936, 19.6359, 0.5407, 6.9366, 6.935, 13.7319, 13.7319],\n",
-    "            \"latitudes\": [34.556, 35.9416, 39.9116, 41.6796, 42.0137, 35.7835, 36.8789, 36.88, -12.4706, -12.4706],\n",
+    "            \"longitudes\": [\n",
+    "                69.4787,\n",
+    "                68.71,\n",
+    "                20.1047,\n",
+    "                19.8936,\n",
+    "                19.6359,\n",
+    "                0.5407,\n",
+    "                6.9366,\n",
+    "                6.935,\n",
+    "                13.7319,\n",
+    "                13.7319,\n",
+    "            ],\n",
+    "            \"latitudes\": [\n",
+    "                34.556,\n",
+    "                35.9416,\n",
+    "                39.9116,\n",
+    "                41.6796,\n",
+    "                42.0137,\n",
+    "                35.7835,\n",
+    "                36.8789,\n",
+    "                36.88,\n",
+    "                -12.4706,\n",
+    "                -12.4706,\n",
+    "            ],\n",
     "            \"request_item_id\": \"my_flood_request\",\n",
     "            \"hazard_type\": \"RiverineInundation\",\n",
     "            \"indicator_id\": \"flood_depth\",\n",
@@ -204,14 +248,44 @@
    ],
    "source": [
     "fig1 = make_subplots(rows=1, cols=2)\n",
-    "fig1.add_scatter(x=flood_results_baseline[0][\"index_values\"], y=flood_results_baseline[0][\"intensities\"], name=\"baseline flood\", row=1, col=1)\n",
-    "fig1.add_scatter(x=flood_results_rcp585[0][\"index_values\"], y=flood_results_rcp585[0][\"intensities\"], name=\"flood RCP 8.5 2050\", row=1, col=1)\n",
-    "fig1.update_xaxes(title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=1, type=\"log\")\n",
+    "fig1.add_scatter(\n",
+    "    x=flood_results_baseline[0][\"index_values\"],\n",
+    "    y=flood_results_baseline[0][\"intensities\"],\n",
+    "    name=\"baseline flood\",\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
+    "fig1.add_scatter(\n",
+    "    x=flood_results_rcp585[0][\"index_values\"],\n",
+    "    y=flood_results_rcp585[0][\"intensities\"],\n",
+    "    name=\"flood RCP 8.5 2050\",\n",
+    "    row=1,\n",
+    "    col=1,\n",
+    ")\n",
+    "fig1.update_xaxes(\n",
+    "    title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=1, type=\"log\"\n",
+    ")\n",
     "fig1.update_yaxes(title=\"Flood depth (m)\", title_font={\"size\": 14}, row=1, col=1)\n",
-    "fig1.add_scatter(x=wind_results_baseline[0][\"index_values\"], y=wind_results_baseline[0][\"intensities\"], name=\"baseline wind\", row=1, col=2)\n",
-    "fig1.add_scatter(x=wind_results_ssp585[0][\"index_values\"], y=wind_results_ssp585[0][\"intensities\"], name=\"wind SSP585 2050\", row=1, col=2)\n",
-    "fig1.update_xaxes(title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=2, type=\"log\")\n",
-    "fig1.update_yaxes(title=\"Max (1 minute) wind speed (m/s)\", title_font={\"size\": 14}, row=1, col=2)\n",
+    "fig1.add_scatter(\n",
+    "    x=wind_results_baseline[0][\"index_values\"],\n",
+    "    y=wind_results_baseline[0][\"intensities\"],\n",
+    "    name=\"baseline wind\",\n",
+    "    row=1,\n",
+    "    col=2,\n",
+    ")\n",
+    "fig1.add_scatter(\n",
+    "    x=wind_results_ssp585[0][\"index_values\"],\n",
+    "    y=wind_results_ssp585[0][\"intensities\"],\n",
+    "    name=\"wind SSP585 2050\",\n",
+    "    row=1,\n",
+    "    col=2,\n",
+    ")\n",
+    "fig1.update_xaxes(\n",
+    "    title=\"Return period (years)\", title_font={\"size\": 14}, row=1, col=2, type=\"log\"\n",
+    ")\n",
+    "fig1.update_yaxes(\n",
+    "    title=\"Max (1 minute) wind speed (m/s)\", title_font={\"size\": 14}, row=1, col=2\n",
+    ")\n",
     "fig1.update_layout(legend=dict(orientation=\"h\", y=-0.15))\n",
     "fig1.update_layout(margin=dict(l=20, r=20, t=20, b=20))"
    ]
diff --git a/docs/getting_started/hazard_inventory.ipynb b/docs/getting_started/hazard_inventory.ipynb
index 6bfdca00..3891f578 100644
--- a/docs/getting_started/hazard_inventory.ipynb
+++ b/docs/getting_started/hazard_inventory.ipynb
@@ -123,18 +123,22 @@
     "hazard_types = set(r[\"hazard_type\"] for r in hazard_resources)\n",
     "print(f\"Hazards: {hazard_types}\")\n",
     "wind_resources = [r for r in hazard_resources if r[\"hazard_type\"] == \"Wind\"]\n",
-    "print(f\"{len(hazard_resources)} hazard resources in the inventory, of which {len(wind_resources)} are Wind resources.\")\n",
+    "print(\n",
+    "    f\"{len(hazard_resources)} hazard resources in the inventory, of which {len(wind_resources)} are Wind resources.\"\n",
+    ")\n",
     "iris_model_resource = next(r for r in wind_resources if \"iris\" in r[\"path\"])\n",
     "# pp.pprint(iris_model_resource[0])\n",
     "path = iris_model_resource[\"path\"]\n",
-    "print(f\"The resource 'path' is a unique identifier. For the IRIS Wind resource, for example, this is: '{path}'.\")\n",
+    "print(\n",
+    "    f\"The resource 'path' is a unique identifier. For the IRIS Wind resource, for example, this is: '{path}'.\"\n",
+    ")\n",
     "print(\n",
     "    \"Where resources are multi-dimensional arrays (as opposed to an external API), this is also the path of the array.\"\n",
     ")\n",
     "print(\"The available climate scenarios and years for the IRIS resource are:\")\n",
     "pp.pprint(iris_model_resource[\"scenarios\"])\n",
     "print(\"The whole IRIS data resource, as an example:\")\n",
-    "pp.pprint(iris_model_resource)\n"
+    "pp.pprint(iris_model_resource)"
    ]
   },
   {
@@ -200,7 +204,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "rcp_display_names = {\"rcp2p6\": \"RCP 2.6\", \"rcp4p5\": \"RCP 4.5\" ,\"rcp6p0\": \"RCP 6.0\", \"rcp8p5\": \"RCP 8.5\", }\n",
+    "rcp_display_names = {\n",
+    "    \"rcp2p6\": \"RCP 2.6\",\n",
+    "    \"rcp4p5\": \"RCP 4.5\",\n",
+    "    \"rcp6p0\": \"RCP 6.0\",\n",
+    "    \"rcp8p5\": \"RCP 8.5\",\n",
+    "}\n",
+    "\n",
     "\n",
     "def scenario_code(id: str):\n",
     "    if id.startswith(\"ssp\"):\n",
@@ -210,19 +220,31 @@
     "    else:\n",
     "        return id\n",
     "\n",
+    "\n",
     "def format_scenario(scenarios):\n",
-    "    return \", \".join(f\"{scenario_code(scen['id'])} ({', '.join(str(y) for y in scen['years'])})\" for scen in scenarios)\n",
+    "    return \", \".join(\n",
+    "        f\"{scenario_code(scen['id'])} ({', '.join(str(y) for y in scen['years'])})\"\n",
+    "        for scen in scenarios\n",
+    "    )\n",
+    "\n",
     "\n",
     "resource_df = pd.json_normalize(hazard_resources)\n",
-    "resource_df = resource_df.filter([\"hazard_type\", \"indicator_id\", \"display_name\", \"path\", \"scenarios\"])\n",
-    "resource_df = resource_df.sort_values(by=[\"hazard_type\", \"indicator_id\", \"display_name\"])\n",
+    "resource_df = resource_df.filter(\n",
+    "    [\"hazard_type\", \"indicator_id\", \"display_name\", \"path\", \"scenarios\"]\n",
+    ")\n",
+    "resource_df = resource_df.sort_values(\n",
+    "    by=[\"hazard_type\", \"indicator_id\", \"display_name\"]\n",
+    ")\n",
     "resource_df.scenarios = resource_df.scenarios.apply(lambda s: format_scenario(s))\n",
-    "resource_df = resource_df.rename(columns={\"hazard_type\": \"Hazard type\",\n",
-    "                                          \"indicator_id\": \"Indicator ID\",\n",
-    "                                          \"display_name\": \"Display name\",\n",
-    "                                          \"path\": \"Path (ID)\",\n",
-    "                                          \"scenarios\": \"Scenarios\",\n",
-    "                                          })\n",
+    "resource_df = resource_df.rename(\n",
+    "    columns={\n",
+    "        \"hazard_type\": \"Hazard type\",\n",
+    "        \"indicator_id\": \"Indicator ID\",\n",
+    "        \"display_name\": \"Display name\",\n",
+    "        \"path\": \"Path (ID)\",\n",
+    "        \"scenarios\": \"Scenarios\",\n",
+    "    }\n",
+    ")\n",
     "\n",
     "style = \"\"\"\n",
     "<style scoped>\n",
diff --git a/docs/user_guide/vulnerability/vulnerability_config.ipynb b/docs/user_guide/vulnerability/vulnerability_config.ipynb
index 0326904c..afc9fbf3 100644
--- a/docs/user_guide/vulnerability/vulnerability_config.ipynb
+++ b/docs/user_guide/vulnerability/vulnerability_config.ipynb
@@ -96,14 +96,15 @@
    "outputs": [],
    "source": [
     "# pip install nbformat pandas plotly requests\n",
-    "from dotenv import load_dotenv\n",
     "from io import StringIO\n",
-    "import plotly.graph_objs as go\n",
     "import plotly.io\n",
     "from plotly.subplots import make_subplots\n",
     "\n",
     "plotly.io.renderers.default = \"notebook\"\n",
-    "from physrisk.vulnerability_models.config_based_impact_curves import config_items_from_csv, config_items_to_df"
+    "from physrisk.vulnerability_models.config_based_impact_curves import (\n",
+    "    config_items_from_csv,\n",
+    "    config_items_to_df,\n",
+    ")"
    ]
   },
   {
@@ -354,18 +355,31 @@
     }
    ],
    "source": [
-    "c1 = next(c for c in config_items if c.asset_class == \"RealEstateAsset\" and c.indicator_id==\"flood_depth\")\n",
-    "c2 = next(c for c in config_items if c.asset_class == \"ManufacturingAsset\" and c.indicator_id==\"days_tas/above/{temp_c}c\")\n",
+    "c1 = next(\n",
+    "    c\n",
+    "    for c in config_items\n",
+    "    if c.asset_class == \"RealEstateAsset\" and c.indicator_id == \"flood_depth\"\n",
+    ")\n",
+    "c2 = next(\n",
+    "    c\n",
+    "    for c in config_items\n",
+    "    if c.asset_class == \"ManufacturingAsset\"\n",
+    "    and c.indicator_id == \"days_tas/above/{temp_c}c\"\n",
+    ")\n",
     "\n",
     "fig1 = make_subplots(rows=1, cols=2)\n",
-    "fig1.add_scatter(x=c1.points_x, y=c1.points_y, name=\"Example damage curve\", row=1, col=1)\n",
-    "fig1.add_scatter(x=c2.points_x, y=c2.points_y, name=\"Example threshold curve\", row=1, col=2)\n",
+    "fig1.add_scatter(\n",
+    "    x=c1.points_x, y=c1.points_y, name=\"Example damage curve\", row=1, col=1\n",
+    ")\n",
+    "fig1.add_scatter(\n",
+    "    x=c2.points_x, y=c2.points_y, name=\"Example threshold curve\", row=1, col=2\n",
+    ")\n",
     "fig1.update_xaxes(title=\"Flood depth (m)\", title_font={\"size\": 14}, row=1, col=1)\n",
     "fig1.update_xaxes(title=\"Threshold (°C)\", title_font={\"size\": 14}, row=1, col=2)\n",
     "fig1.update_yaxes(title=\"Damage as fraction of insurable value\", row=1, col=1)\n",
     "fig1.update_yaxes(title=\"Fractional loss of production\", row=1, col=2)\n",
     "fig1.update_layout(legend=dict(orientation=\"h\", y=-0.15))\n",
-    "#fig1.update_layout(legend=dict(yanchor=\"top\", y=0.99, xanchor=\"left\", x=0.01))\n",
+    "# fig1.update_layout(legend=dict(yanchor=\"top\", y=0.99, xanchor=\"left\", x=0.01))\n",
     "fig1.update_layout(margin=dict(l=20, r=20, t=20, b=20))"
    ]
   }
diff --git a/docs/user_guide/vulnerability/vulnerability_functions/inundation_jrc/onboard.ipynb b/docs/user_guide/vulnerability/vulnerability_functions/inundation_jrc/onboard.ipynb
index 4ec78a8f..627fdb55 100644
--- a/docs/user_guide/vulnerability/vulnerability_functions/inundation_jrc/onboard.ipynb
+++ b/docs/user_guide/vulnerability/vulnerability_functions/inundation_jrc/onboard.ipynb
@@ -54,7 +54,11 @@
     "        # whether zero depth is considered really zero or a flood event with smallest depth\n",
     "        zero_as_minimum = True if location == \"North America\" else False\n",
     "        # for North America, the 0 depth damage is for flooding of any depth. We consider that a 1 cm inundation.\n",
-    "        depth = np.concatenate([[0, 0.01], flood_depth[1:]]) if zero_as_minimum else flood_depth\n",
+    "        depth = (\n",
+    "            np.concatenate([[0, 0.01], flood_depth[1:]])\n",
+    "            if zero_as_minimum\n",
+    "            else flood_depth\n",
+    "        )\n",
     "\n",
     "        mean = type_df[location + \"_Mean\"].to_numpy()\n",
     "        std = type_df[location + \"_Std\"].to_numpy()\n",
diff --git a/docs/user_guide/vulnerability/vulnerability_functions/multi_hazard_wri_power_generating_assets/onboard.ipynb b/docs/user_guide/vulnerability/vulnerability_functions/multi_hazard_wri_power_generating_assets/onboard.ipynb
index d691bdcc..aa777440 100644
--- a/docs/user_guide/vulnerability/vulnerability_functions/multi_hazard_wri_power_generating_assets/onboard.ipynb
+++ b/docs/user_guide/vulnerability/vulnerability_functions/multi_hazard_wri_power_generating_assets/onboard.ipynb
@@ -22,7 +22,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import json, pandas\n",
+    "import json\n",
+    "import pandas\n",
     "\n",
     "data = {\"items\": []}\n",
     "\n",
@@ -53,15 +54,23 @@
     "                        \"event_type\": hazard_type.replace(\" \", \"\"),\n",
     "                        \"location\": \"Global\",\n",
     "                        \"intensity\": list(item[\"Threshold\"].values),\n",
-    "                        \"intensity_units\": item[\"Threshold Unit\"].values[0].replace(\" \", \"\"),\n",
-    "                        \"impact_type\": item[\"Vulnerability Type\"].values[0].replace(\" \", \"\"),\n",
-    "                        \"impact_units\": item[\"Vulnerability Unit\"].values[0].replace(\" \", \"\"),\n",
+    "                        \"intensity_units\": item[\"Threshold Unit\"]\n",
+    "                        .values[0]\n",
+    "                        .replace(\" \", \"\"),\n",
+    "                        \"impact_type\": item[\"Vulnerability Type\"]\n",
+    "                        .values[0]\n",
+    "                        .replace(\" \", \"\"),\n",
+    "                        \"impact_units\": item[\"Vulnerability Unit\"]\n",
+    "                        .values[0]\n",
+    "                        .replace(\" \", \"\"),\n",
     "                        \"impact_mean\": list(item[\"Vulnerability\"].values),\n",
     "                        \"impact_std\": [],\n",
     "                    }\n",
     "                )\n",
     "\n",
-    "with open(\"WRI thermal power plant physical climate vulnerability factors.json\", \"w\") as f:\n",
+    "with open(\n",
+    "    \"WRI thermal power plant physical climate vulnerability factors.json\", \"w\"\n",
+    ") as f:\n",
     "    vulnerability_json = json.dumps(data, sort_keys=True, indent=4)\n",
     "    f.write(vulnerability_json)"
    ]
diff --git a/docs/user_guide/vulnerability/vulnerability_uncertainty.ipynb b/docs/user_guide/vulnerability/vulnerability_uncertainty.ipynb
index 0829a276..d790cc50 100644
--- a/docs/user_guide/vulnerability/vulnerability_uncertainty.ipynb
+++ b/docs/user_guide/vulnerability/vulnerability_uncertainty.ipynb
@@ -44,12 +44,16 @@
    "outputs": [],
    "source": [
     "import numpy as np\n",
-    "from physrisk.vulnerability_models.config_cdf_based_vuln_function import CDFBasedVulnerabilityFunction\n",
+    "from physrisk.vulnerability_models.config_cdf_based_vuln_function import (\n",
+    "    CDFBasedVulnerabilityFunction,\n",
+    ")\n",
     "\n",
     "hazard_indicator = np.array([0.0, 0.5, 1.0, 1.5, 2.0, 3.0, 4.0, 5.0, 6.0])\n",
     "impact_mean = np.array([0.0, 0.327, 0.494, 0.617, 0.721, 0.870, 0.931, 0.984, 1.0])\n",
     "impact_stddev = np.array([0.0, 0.12, 0.11, 0.10, 0.10, 0.08, 0.06, 0.02, 0.0])\n",
-    "vuln = CDFBasedVulnerabilityFunction(hazard_indicator, impact_mean, impact_stddev, kind=\"beta\")"
+    "vuln = CDFBasedVulnerabilityFunction(\n",
+    "    hazard_indicator, impact_mean, impact_stddev, kind=\"beta\"\n",
+    ")"
    ]
   },
   {
@@ -123,14 +127,17 @@
    "source": [
     "import plotly.graph_objects as go\n",
     "import plotly.io\n",
+    "\n",
     "plotly.io.renderers.default = \"notebook\"\n",
     "\n",
     "fig = go.Figure()\n",
     "for i in [0, 2, 4, 6, 8]:\n",
-    "    fig.add_scatter(x=vuln.cdf[i, :], y=vuln.impact, name=f\"Flood depth {hazard_indicator[i]}m\")\n",
+    "    fig.add_scatter(\n",
+    "        x=vuln.cdf[i, :], y=vuln.impact, name=f\"Flood depth {hazard_indicator[i]}m\"\n",
+    "    )\n",
     "# also interpolate for a depth of 0.6m and display\n",
     "interp = vuln.interpolate_cdfs(np.array([0.6]))\n",
-    "fig.add_scatter(x=interp[0, :], y=vuln.impact, name=f\"Interpolated depth 0.6m\")\n",
+    "fig.add_scatter(x=interp[0, :], y=vuln.impact, name=\"Interpolated depth 0.6m\")\n",
     "fig.update_xaxes(title=\"Cumulative probability\", title_font={\"size\": 14})\n",
     "fig.update_yaxes(title=\"Fractional damage\", title_font={\"size\": 14})\n",
     "fig.show()"
@@ -188,8 +195,13 @@
     "impact_bin_width = vuln.impact[1:] - vuln.impact[0:-1]\n",
     "for i in [2, 4, 6]:\n",
     "    probs = vuln.cdf[i, 1:] - vuln.cdf[i, 0:-1]\n",
-    "    fig.add_bar(x=impact_bin_centres, y=probs, width=impact_bin_width, name=f\"Flood depth {hazard_indicator[i]}m\", \n",
-    "                opacity=0.7)\n",
+    "    fig.add_bar(\n",
+    "        x=impact_bin_centres,\n",
+    "        y=probs,\n",
+    "        width=impact_bin_width,\n",
+    "        name=f\"Flood depth {hazard_indicator[i]}m\",\n",
+    "        opacity=0.7,\n",
+    "    )\n",
     "fig.update_xaxes(title=\"Fractional damage\", title_font={\"size\": 14})\n",
     "fig.update_yaxes(title=\"Probability\", title_font={\"size\": 14})\n",
     "fig.show()"
diff --git a/methodology/plots/interp_pixel_is_area.ipynb b/methodology/plots/interp_pixel_is_area.ipynb
index 84ab1702..f075b194 100644
--- a/methodology/plots/interp_pixel_is_area.ipynb
+++ b/methodology/plots/interp_pixel_is_area.ipynb
@@ -6,9 +6,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import os, sys\n",
+    "import os\n",
+    "import sys\n",
     "from affine import Affine\n",
-    "import matplotlib.pyplot as plt\n",
     "import s3fs\n",
     "import hazard.utilities.zarr_utilities as zarr_utilities\n",
     "from hazard.sources.osc_zarr import OscZarr\n",
@@ -17,7 +17,11 @@
     "\n",
     "os.environ[\"CREDENTIAL_DOTENV_DIR\"] = os.path.dirname(os.getcwd())\n",
     "zarr_utilities.set_credential_env_variables()\n",
-    "s3 = s3fs.S3FileSystem(anon=False, key=os.environ[\"OSC_S3_ACCESS_KEY\"], secret=os.environ[\"OSC_S3_SECRET_KEY\"])"
+    "s3 = s3fs.S3FileSystem(\n",
+    "    anon=False,\n",
+    "    key=os.environ[\"OSC_S3_ACCESS_KEY\"],\n",
+    "    secret=os.environ[\"OSC_S3_SECRET_KEY\"],\n",
+    ")"
    ]
   },
   {
@@ -28,7 +32,9 @@
    "source": [
     "longitude = 2.293\n",
     "latitude = 48.855\n",
-    "transform = Affine(0.008333333333333333, 0.0, -180.0, 0.0, -0.008333333333333333, 90.0, 0.0, 0.0, 1.0)"
+    "transform = Affine(\n",
+    "    0.008333333333333333, 0.0, -180.0, 0.0, -0.008333333333333333, 90.0, 0.0, 0.0, 1.0\n",
+    ")"
    ]
   },
   {
@@ -72,7 +78,8 @@
    "source": [
     "delta = 0.02\n",
     "plt1 = da.sel(\n",
-    "    latitude=slice(latitude + delta, latitude - delta), longitude=slice(longitude - delta, longitude + delta)\n",
+    "    latitude=slice(latitude + delta, latitude - delta),\n",
+    "    longitude=slice(longitude - delta, longitude + delta),\n",
     ")[8, :, :].plot.pcolormesh(cmap=\"Blues\", cbar_kwargs={\"label\": \"flood depth (m)\"})"
    ]
   },
@@ -97,10 +104,17 @@
     "# the point falls in pixel 21875, 4937\n",
     "\n",
     "plt1.axes.set_title(\"\")\n",
-    "surrounding_points = [[21874.5, 4936.5], [21874.5, 4937.5], [21875.5, 4936.5], [21875.5, 4937.5]]\n",
+    "surrounding_points = [\n",
+    "    [21874.5, 4936.5],\n",
+    "    [21874.5, 4937.5],\n",
+    "    [21875.5, 4936.5],\n",
+    "    [21875.5, 4937.5],\n",
+    "]\n",
     "for point in surrounding_points:\n",
     "    pointt = transform * point\n",
-    "    plt1.axes.plot([pointt[0], longitude], [pointt[1], latitude], \"--\", color=\"grey\", zorder=1)\n",
+    "    plt1.axes.plot(\n",
+    "        [pointt[0], longitude], [pointt[1], latitude], \"--\", color=\"grey\", zorder=1\n",
+    "    )\n",
     "    plt1.axes.scatter([pointt[0]], [pointt[1]], c=\"black\", marker=\"o\", zorder=2)\n",
     "plt1.axes.scatter([longitude], [latitude], c=\"black\", marker=\"x\", zorder=2)\n",
     "plt1.axes.figure"