Merge branch '62-integrate-and-interface-to-uhep'

examples/UHepp.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "\n",
+    "from nnfwtbn import Variable, Process, Cut, hist, McStack, DataStack, Stack\n",
+    "from nnfwtbn import toydata\n",
+    "from nnfwtbn.plot import hist\n",
+    "\n",
+    "import uhepp"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df = toydata.get()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "df.compute()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "p_ztt = Process(r\"$Z\\rightarrow\\tau\\tau$\", range=(0, 0))\n",
+    "p_sig = Process(r\"Signal\", range=(1, 1))\n",
+    "\n",
+    "p_asimov = Process(r\"Asimov\", selection=lambda d: d.fpid >= 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "colors = [\"windows blue\", \"amber\", \"greyish\", \"faded green\", \"dusty purple\"]\n",
+    "palette = sns.xkcd_palette(colors)\n",
+    "\n",
+    "s_bkg = McStack(p_ztt, p_sig, palette=palette)\n",
+    "s_data = DataStack(p_asimov)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "v_higgs_m = Variable(r\"$m^H$\", \"higgs_m\", \"GeV\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "c_vbf = Cut(lambda d: d.dijet_p4__M  > 400) & \\\n",
+    "        Cut(lambda d: d.jet_1_p4__Pt >= 30) & \\\n",
+    "        Cut(lambda d: d.is_dijet_centrality == 1) & \\\n",
+    "        Cut(lambda d: d.jet_0_p4__Eta * df.jet_1_p4__Eta < 0) & \\\n",
+    "        Cut(lambda d: (d.jet_0_p4__Eta - df.jet_1_p4__Eta).abs() > 3)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h = hist(df, v_higgs_m, 20, [s_bkg, s_data], range=(0, 200), selection=None,\n",
+    "     weight=\"weight\",  ratio_label=\"Data / SM\", return_uhepp=True)\n",
+    "h.render()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "scrolled": false
+   },
+   "outputs": [],
+   "source": [
+    "json_string = h.to_jsons()\n",
+    "print(json_string)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h = uhepp.from_jsons(json_string)\n",
+    "h.render()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "h.rebin_edges = [0, 70, 80, 90, 100, 110, 120, 130, 140, 150, 200]\n",
+    "h.subtext = \"Hello\"\n",
+    "h.brand = None\n",
+    "h.render()"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

requirements.txt

@@ -11,3 +11,4 @@ lxml
 keras
 tensorflow
 dask[complete]
+git+https://gitlab.cern.ch/fsauerbu/uhepp.git

setup.py

@@ -25,6 +25,7 @@ setup(name='nnfwtbn',
                         "keras",
                         "dask",
                         "dask[complete]",
+                        "uhepp",
                         "lxml"],
       test_suite='nnfwtbn.tests',
       description='Experimental neural network framework to be named.',