diff --git a/docs/examples/notebooks/learn/neyman/NeymanConstruction.ipynb b/docs/examples/notebooks/learn/neyman/NeymanConstruction.ipynb
index 261ff0f1c9..50d822c147 100644
--- a/docs/examples/notebooks/learn/neyman/NeymanConstruction.ipynb
+++ b/docs/examples/notebooks/learn/neyman/NeymanConstruction.ipynb
@@ -9,6 +9,7 @@
     "import scipy.stats\n",
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
+    "\n",
     "%load_ext autoreload\n",
     "%autoreload 2"
    ]
@@ -92,8 +93,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def tmu_teststat(mu,muhat,sigma):\n",
-    "    a = (mu-muhat)**2/sigma**2\n",
+    "def tmu_teststat(mu, muhat, sigma):\n",
+    "    a = (mu - muhat) ** 2 / sigma ** 2\n",
     "    return a"
    ]
   },
@@ -117,7 +118,8 @@
    ],
    "source": [
     "from utils import *\n",
-    "jointplot(mu = 1.0,sigma = 1.0,teststat = tmu_teststat)"
+    "\n",
+    "jointplot(mu=1.0, sigma=1.0, teststat=tmu_teststat)"
    ]
   },
   {
@@ -179,14 +181,15 @@
     }
    ],
    "source": [
-    "def tmu_tilde_teststat(mu,muhat,sigma):\n",
-    "    a = tmu_teststat(mu,muhat,sigma)\n",
+    "def tmu_tilde_teststat(mu, muhat, sigma):\n",
+    "    a = tmu_teststat(mu, muhat, sigma)\n",
     "\n",
-    "    b = (0-muhat)**2/sigma**2\n",
-    "    r = np.where(muhat<0,a-b,a)\n",
+    "    b = (0 - muhat) ** 2 / sigma ** 2\n",
+    "    r = np.where(muhat < 0, a - b, a)\n",
     "    return r\n",
     "\n",
-    "jointplot(mu = 1.0,sigma = 1.0,teststat = tmu_tilde_teststat)"
+    "\n",
+    "jointplot(mu=1.0, sigma=1.0, teststat=tmu_tilde_teststat)"
    ]
   },
   {
@@ -229,13 +232,14 @@
     }
    ],
    "source": [
-    "def qmu_teststat(mu,muhat,sigma):\n",
-    "    r = tmu_teststat(mu,muhat,sigma)\n",
+    "def qmu_teststat(mu, muhat, sigma):\n",
+    "    r = tmu_teststat(mu, muhat, sigma)\n",
     "    zero = np.zeros_like(r)\n",
-    "    r = np.where(muhat>mu,zero,r)\n",
+    "    r = np.where(muhat > mu, zero, r)\n",
     "    return r\n",
     "\n",
-    "jointplot(mu = 0.0,sigma = 1.0,teststat = qmu_teststat)"
+    "\n",
+    "jointplot(mu=0.0, sigma=1.0, teststat=qmu_teststat)"
    ]
   },
   {
@@ -275,13 +279,14 @@
     }
    ],
    "source": [
-    "def qmu_tilde_teststat(mu,muhat,sigma):\n",
-    "    r = tmu_tilde_teststat(mu,muhat,sigma)\n",
+    "def qmu_tilde_teststat(mu, muhat, sigma):\n",
+    "    r = tmu_tilde_teststat(mu, muhat, sigma)\n",
     "    zero = np.zeros_like(r)\n",
-    "    r = np.where(muhat>mu,zero,r)\n",
+    "    r = np.where(muhat > mu, zero, r)\n",
     "    return r\n",
     "\n",
-    "jointplot(1.0,sigma = 1.0,teststat = qmu_tilde_teststat)"
+    "\n",
+    "jointplot(1.0, sigma=1.0, teststat=qmu_tilde_teststat)"
    ]
   },
   {
@@ -299,14 +304,19 @@
    "source": [
     "sigma = 1.0\n",
     "test_size = 0.05\n",
-    "min_mu,max_mu,myteststat = 0,5, tmu_tilde_teststat\n",
-    "# min_mu,max_mu,myteststat = 0,5, qmu_tilde_teststat \n",
+    "min_mu, max_mu, myteststat = 0, 5, tmu_tilde_teststat\n",
+    "# min_mu,max_mu,myteststat = 0,5, qmu_tilde_teststat\n",
     "# min_mu,max_mu,myteststat = -5,5, tmu_teststat\n",
     "# min_mu,max_mu,myteststat = -5,5, qmu_teststat\n",
-    "hypos_over_sigma = np.linspace(min_mu,max_mu,50)\n",
-    "scans = np.array([scan_tests_for_size(h*sigma,sigma = sigma,teststat = myteststat) for h in hypos_over_sigma])\n",
-    "cuts  = np.argmax(scans[:,:,-1] > test_size,axis=1)\n",
-    "atcut = np.asarray([s[c] for s,c in zip(scans,cuts)])"
+    "hypos_over_sigma = np.linspace(min_mu, max_mu, 50)\n",
+    "scans = np.array(\n",
+    "    [\n",
+    "        scan_tests_for_size(h * sigma, sigma=sigma, teststat=myteststat)\n",
+    "        for h in hypos_over_sigma\n",
+    "    ]\n",
+    ")\n",
+    "cuts = np.argmax(scans[:, :, -1] > test_size, axis=1)\n",
+    "atcut = np.asarray([s[c] for s, c in zip(scans, cuts)])"
    ]
   },
   {
@@ -337,8 +347,8 @@
     }
    ],
    "source": [
-    "f = plot_teststat(min_mu,sigma = sigma, teststat = myteststat)\n",
-    "f.set_size_inches(3,6)\n",
+    "f = plot_teststat(min_mu, sigma=sigma, teststat=myteststat)\n",
+    "f.set_size_inches(3, 6)\n",
     "f.set_tight_layout(True)"
    ]
   },
@@ -370,12 +380,12 @@
     }
    ],
    "source": [
-    "f,axarr = plt.subplots(4,1)\n",
-    "plot_oneinterval(axarr[0],10.0,sigma,test_size,myteststat)\n",
-    "plot_oneinterval(axarr[1],1.0,sigma,test_size,myteststat)\n",
-    "plot_oneinterval(axarr[2],0.4,sigma,test_size,myteststat)\n",
-    "plot_oneinterval(axarr[3],0.0,sigma,test_size,myteststat)\n",
-    "f.set_size_inches(3,12)"
+    "f, axarr = plt.subplots(4, 1)\n",
+    "plot_oneinterval(axarr[0], 10.0, sigma, test_size, myteststat)\n",
+    "plot_oneinterval(axarr[1], 1.0, sigma, test_size, myteststat)\n",
+    "plot_oneinterval(axarr[2], 0.4, sigma, test_size, myteststat)\n",
+    "plot_oneinterval(axarr[3], 0.0, sigma, test_size, myteststat)\n",
+    "f.set_size_inches(3, 12)"
    ]
   },
   {
@@ -413,10 +423,10 @@
     }
    ],
    "source": [
-    "f,axarr = plt.subplots(2,1)\n",
-    "plot_neyman_construction(axarr[0],min_mu,max_mu,hypos_over_sigma,atcut,delta = True)\n",
-    "plot_neyman_construction(axarr[1],min_mu,max_mu,hypos_over_sigma,atcut,delta = False)\n",
-    "f.set_size_inches(3,6)\n",
+    "f, axarr = plt.subplots(2, 1)\n",
+    "plot_neyman_construction(axarr[0], min_mu, max_mu, hypos_over_sigma, atcut, delta=True)\n",
+    "plot_neyman_construction(axarr[1], min_mu, max_mu, hypos_over_sigma, atcut, delta=False)\n",
+    "f.set_size_inches(3, 6)\n",
     "f.set_tight_layout(True)"
    ]
   },
@@ -449,10 +459,10 @@
     }
    ],
    "source": [
-    "f,axarr = plt.subplots(2,1)\n",
-    "plot_cuts(axarr[0],hypos_over_sigma,atcut,sigma,myteststat)\n",
-    "plot_pvalue(axarr[1],hypos_over_sigma,scans,sigma,myteststat,atcut[:,0])\n",
-    "f.set_size_inches(3,6)\n",
+    "f, axarr = plt.subplots(2, 1)\n",
+    "plot_cuts(axarr[0], hypos_over_sigma, atcut, sigma, myteststat)\n",
+    "plot_pvalue(axarr[1], hypos_over_sigma, scans, sigma, myteststat, atcut[:, 0])\n",
+    "f.set_size_inches(3, 6)\n",
     "f.set_tight_layout(True)"
    ]
   },