diff --git a/book/UpperLimitsTable.ipynb b/book/UpperLimitsTable.ipynb
index 1df6cf1..bf9b40d 100644
--- a/book/UpperLimitsTable.ipynb
+++ b/book/UpperLimitsTable.ipynb
@@ -7,21 +7,22 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import pyhf\n",
-    "import pyhf.contrib.utils\n",
-    "from pyhf.contrib.viz import brazil\n",
-    "import tarfile\n",
     "import json\n",
+    "import tarfile\n",
+    "\n",
     "import matplotlib.pyplot as plt\n",
     "import numpy as np\n",
+    "import pyhf\n",
+    "import pyhf.contrib.utils\n",
     "import scipy\n",
+    "from pyhf.contrib.viz import brazil\n",
     "\n",
     "pyhf.set_backend(\"numpy\", \"minuit\")\n",
     "\n",
+    "from rich import box\n",
     "# for making tables\n",
     "from rich.console import Console\n",
-    "from rich.table import Table\n",
-    "from rich import box"
+    "from rich.table import Table"
    ]
   },
   {
@@ -61,7 +62,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pyhf.contrib.utils.download(\"https://doi.org/10.17182/hepdata.116034.v1/r34\", \"workspace_2L2J\")"
+    "pyhf.contrib.utils.download(\n",
+    "    \"https://doi.org/10.17182/hepdata.116034.v1/r34\", \"workspace_2L2J\"\n",
+    ")"
    ]
   },
   {
@@ -81,7 +84,7 @@
    "source": [
     "with tarfile.open(\"workspace_2L2J/ewk_discovery_bkgonly.json.tgz\") as fp:\n",
     "    bkgonly = pyhf.Workspace(json.load(fp.extractfile(\"ewk_discovery_bkgonly.json\")))\n",
-    "    \n",
+    "\n",
     "with tarfile.open(\"workspace_2L2J/ewk_discovery_patchset.json.tgz\") as fp:\n",
     "    patchset = pyhf.PatchSet(json.load(fp.extractfile(\"ewk_discovery_patchset.json\")))"
    ]
@@ -200,16 +203,18 @@
     }
    ],
    "source": [
-    "pars_uncrt_bonly, corr_bonly = pyhf.infer.mle.fixed_poi_fit(0.0, data, model, return_uncertainties=True, return_correlations=True)\n",
+    "pars_uncrt_bonly, corr_bonly = pyhf.infer.mle.fixed_poi_fit(\n",
+    "    0.0, data, model, return_uncertainties=True, return_correlations=True\n",
+    ")\n",
     "pars_bonly, uncrt_bonly = pars_uncrt_bonly.T\n",
     "\n",
     "table = Table(title=\"Per-region yields from background-only fit\", box=box.HORIZONTALS)\n",
     "table.add_column(\"Region\", justify=\"left\", style=\"cyan\", no_wrap=True)\n",
     "table.add_column(\"Total Bkg.\", justify=\"center\")\n",
     "\n",
-    "for (region, count) in zip(model.config.channels, model.expected_actualdata(pars_bonly)):\n",
+    "for region, count in zip(model.config.channels, model.expected_actualdata(pars_bonly)):\n",
     "    table.add_row(region, f\"{count:0.2f}\")\n",
-    "    \n",
+    "\n",
     "console = Console()\n",
     "console.print(table)"
    ]
@@ -267,7 +272,7 @@
    "source": [
     "npars = len(model.config.parameters)\n",
     "model_batch = ws.model(batch_size=npars)\n",
-    "pars_batch = np.tile(pars_bonly, (npars,1))"
+    "pars_batch = np.tile(pars_bonly, (npars, 1))"
    ]
   },
   {
@@ -287,7 +292,7 @@
    "source": [
     "up_yields = model_batch.expected_actualdata(pars_batch + np.diag(uncrt_bonly))\n",
     "dn_yields = model_batch.expected_actualdata(pars_batch - np.diag(uncrt_bonly))\n",
-    "variations = (up_yields - dn_yields)/2"
+    "variations = (up_yields - dn_yields) / 2"
    ]
   },
   {
@@ -317,7 +322,7 @@
     }
    ],
    "source": [
-    "error_sq = np.diag(np.einsum('ij,ik,kl->jl', variations, corr_bonly, variations))\n",
+    "error_sq = np.diag(np.einsum(\"ij,ik,kl->jl\", variations, corr_bonly, variations))\n",
     "error_sq"
    ]
   },
@@ -374,9 +379,11 @@
     "table.add_column(\"Region\", justify=\"left\", style=\"cyan\", no_wrap=True)\n",
     "table.add_column(\"Total Bkg.\", justify=\"center\")\n",
     "\n",
-    "for (region, count, uncrt) in zip(model.config.channels, model.expected_actualdata(pars_bonly), np.sqrt(error_sq)):\n",
+    "for region, count, uncrt in zip(\n",
+    "    model.config.channels, model.expected_actualdata(pars_bonly), np.sqrt(error_sq)\n",
+    "):\n",
     "    table.add_row(region, f\"{count:0.2f} ± {uncrt:0.2f}\")\n",
-    "    \n",
+    "\n",
     "console = Console()\n",
     "console.print(table)"
    ]
@@ -411,7 +418,11 @@
     "pyhf.set_backend(\"numpy\", \"scipy\")\n",
     "\n",
     "mu_tests = np.linspace(15, 25, 10)\n",
-    "obs_limit, exp_limit_and_bands, (poi_tests, tests) = pyhf.infer.intervals.upper_limits.upper_limit(\n",
+    "(\n",
+    "    obs_limit,\n",
+    "    exp_limit_and_bands,\n",
+    "    (poi_tests, tests),\n",
+    ") = pyhf.infer.intervals.upper_limits.upper_limit(\n",
     "    data, model, scan=mu_tests, return_results=True\n",
     ")"
    ]
@@ -432,8 +443,10 @@
     }
    ],
    "source": [
-    "print(f'Observed UL: {obs_limit:0.2f}')\n",
-    "print(f'Expected UL: {exp_limit_and_bands[2]:0.2f} [{exp_limit_and_bands[1]-exp_limit_and_bands[2]:0.2f}, +{exp_limit_and_bands[3]-exp_limit_and_bands[2]:0.2f}]')"
+    "print(f\"Observed UL: {obs_limit:0.2f}\")\n",
+    "print(\n",
+    "    f\"Expected UL: {exp_limit_and_bands[2]:0.2f} [{exp_limit_and_bands[1]-exp_limit_and_bands[2]:0.2f}, +{exp_limit_and_bands[3]-exp_limit_and_bands[2]:0.2f}]\"\n",
+    ")"
    ]
   },
   {
@@ -461,7 +474,7 @@
     }
    ],
    "source": [
-    "print(f'Limit on visible cross-section: {obs_limit / 140:0.2f}') # 140 ifb"
+    "print(f\"Limit on visible cross-section: {obs_limit / 140:0.2f}\")  # 140 ifb"
    ]
   },
   {
@@ -566,9 +579,11 @@
     }
    ],
    "source": [
-    "p0 = pyhf.infer.hypotest(0.0, data, model, test_stat='q0')#, calctype='toybased', ntoys=10000)\n",
+    "p0 = pyhf.infer.hypotest(\n",
+    "    0.0, data, model, test_stat=\"q0\"\n",
+    ")  # , calctype='toybased', ntoys=10000)\n",
     "p0_Z = scipy.stats.norm.isf(p0)\n",
-    "print(f'p(s)=0 (Z): {p0:0.2f} ({p0_Z:0.2f})')"
+    "print(f\"p(s)=0 (Z): {p0:0.2f} ({p0_Z:0.2f})\")"
    ]
   },
   {
@@ -595,7 +610,7 @@
    ],
    "source": [
     "_, (_, CLb) = pyhf.infer.hypotest(obs_limit, data, model, return_tail_probs=True)\n",
-    "print(f'CLb: {CLb:0.2f}')"
+    "print(f\"CLb: {CLb:0.2f}\")"
    ]
   },
   {
@@ -615,7 +630,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "region_mask = model.config.channels.index('DRInt_cuts')\n",
+    "region_mask = model.config.channels.index(\"DRInt_cuts\")\n",
     "bkg_count = model.expected_actualdata(pars_bonly)[region_mask]\n",
     "bkg_uncrt = np.sqrt(error_sq)[region_mask]"
    ]
@@ -653,7 +668,10 @@
     }
    ],
    "source": [
-    "table = Table(title=\"Model-independent upper limits on the observed visible cross-section in the five electroweak search discovery regions; derived using asymptotics, pyhf, and published likelihoods.\", box=box.HORIZONTALS)\n",
+    "table = Table(\n",
+    "    title=\"Model-independent upper limits on the observed visible cross-section in the five electroweak search discovery regions; derived using asymptotics, pyhf, and published likelihoods.\",\n",
+    "    box=box.HORIZONTALS,\n",
+    ")\n",
     "table.add_column(\"Signal Region\", justify=\"left\", style=\"cyan\", no_wrap=True)\n",
     "table.add_column(\"Total Bkg.\", justify=\"center\")\n",
     "table.add_column(\"Data\")\n",
@@ -664,14 +682,14 @@
     "table.add_column(\"p(s=0) (Z)\")\n",
     "\n",
     "table.add_row(\n",
-    "    model.config.channels[region_mask], \n",
-    "    f\"{bkg_count:0.0f} ± {bkg_uncrt:0.0f}\", \n",
-    "    f\"{data[region_mask]:0.0f}\", \n",
-    "    f'{obs_limit / 140:0.2f}', \n",
-    "    f\"{obs_limit:0.1f}\", \n",
+    "    model.config.channels[region_mask],\n",
+    "    f\"{bkg_count:0.0f} ± {bkg_uncrt:0.0f}\",\n",
+    "    f\"{data[region_mask]:0.0f}\",\n",
+    "    f\"{obs_limit / 140:0.2f}\",\n",
+    "    f\"{obs_limit:0.1f}\",\n",
     "    f\"{exp_limit_and_bands[2]:0.1f} + {exp_limit_and_bands[3] - exp_limit_and_bands[2]:0.1f} - {exp_limit_and_bands[2] - exp_limit_and_bands[1]:0.1f}\",\n",
     "    f\"{CLb:0.2f}\",\n",
-    "    f\"{p0:0.2f} ({p0_Z:0.1f})\"\n",
+    "    f\"{p0:0.2f} ({p0_Z:0.1f})\",\n",
     ")\n",
     "\n",
     "console = Console()\n",