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

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

demo.ipynb

@@ -427,7 +427,6 @@
     "    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/binning.ipynb

@@ -668,6 +668,7 @@
     "num_bins = 4\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",
@@ -732,6 +733,7 @@
     "\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",
@@ -768,6 +770,7 @@
     "\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

@@ -341,6 +341,7 @@
     "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",

setup.cfg

@@ -21,11 +21,6 @@ classifiers =
     Programming Language :: Python
     Programming Language :: Python :: 3
     Programming Language :: Python :: 3 :: Only
-    Programming Language :: Python :: 3.6
-    Programming Language :: Python :: 3.7
-    Programming Language :: Python :: 3.8
-    Programming Language :: Python :: 3.9
-    Programming Language :: Python :: 3.10
     Topic :: Scientific/Engineering
 project_urls =
     Documentation = https://neos.readthedocs.io/
@@ -41,7 +36,7 @@ install_requires =
     relaxed>=0.2.0
     sklearn
     typing-extensions>=3.7;python_version<'3.8'
-python_requires = >=3.6
+python_requires = >=3.7
 include_package_data = True
 package_dir =
     =src

src/neos/losses.py

@@ -10,7 +10,6 @@
 
 import jax.numpy as jnp
 import pyhf
-
 import relaxed
 
 Array = jnp.ndarray

src/neos/top_level.py

@@ -10,8 +10,8 @@
 
 import jax.numpy as jnp
 import pyhf
-
 import relaxed
+
 from neos.losses import (
     cls_value,
     discovery_significance,