[pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

examples/binning.ipynb

@@ -1329,6 +1329,7 @@
     "num_bins = 5\n",
     "pars = jnp.linspace(0, 8, num_bins + 1)\n",
     "\n",
+    "\n",
     "# differentiable significance pipeline\n",
     "def asimov_pipe(bins, s, b, bandwidth=1e-2):\n",
     "    # restrict bin edges so they don't overlap during optimisation\n",
@@ -1394,6 +1395,7 @@
     "\n",
     "from copy import deepcopy\n",
     "\n",
+    "\n",
     "# specify the workspace for a simple model with a three-point background systematic\n",
     "def correlated_background(signal, bkg, bkg_up, bkg_down):\n",
     "    spec = {\n",
@@ -1430,6 +1432,7 @@
     "\n",
     "from pyhf import interpolators\n",
     "\n",
+    "\n",
     "# pipeline to calculate the full CLs for the model, given a number of bins\n",
     "def pipe(num_bins):\n",
     "    def cls_pipe(bins, s, b, bup, bdown, bandwidth=1e-2, skeleton_model=None):\n",

examples/cuts.ipynb

@@ -391,6 +391,7 @@
     "from jaxopt import OptaxSolver\n",
     "from optax import adam\n",
     "\n",
+    "\n",
     "# define something to minimise (1/significance)\n",
     "def loss(cut):\n",
     "    s_weights = relaxed.cut(sig, cut, slope) + 1e-4\n",

examples/neos.ipynb

@@ -389,7 +389,6 @@
     "    scale_factors: dict[str, float],\n",
     "    include_bins: bool = True,\n",
     ") -> tuple[Array, dict[str, list]]:\n",
-    "\n",
     "    loss = partial(\n",
     "        pipeline,\n",
     "        nn=nn,\n",

examples/simple-analysis-optimisation.ipynb

@@ -130,7 +130,6 @@
    "source": [
     "# our analysis pipeline, from phi to p-value\n",
     "def pipeline(phi, return_yields=False, uncertainty=True):\n",
-    "\n",
     "    # grab the yields at the value of phi we want\n",
     "    y = yields(phi, uncertainty=uncertainty)\n",
     "\n",