From 9586cba698d1783fa858edb5311b74feb6209aed Mon Sep 17 00:00:00 2001 From: Radonirinaunimi Date: Thu, 18 Jan 2024 17:30:20 +0100 Subject: [PATCH 01/18] add bare skeleton of a tutorial --- docs/source/index.rst | 2 +- docs/source/overview/tutorials.ipynb | 849 ++++++++++++++++++ .../overview/tutorials/benchmarks.ipynb | 53 -- docs/source/overview/tutorials/index.rst | 13 - .../overview/tutorials/introduction.ipynb | 81 -- 5 files changed, 850 insertions(+), 148 deletions(-) create mode 100644 docs/source/overview/tutorials.ipynb delete mode 100644 docs/source/overview/tutorials/benchmarks.ipynb delete mode 100644 docs/source/overview/tutorials/index.rst delete mode 100644 docs/source/overview/tutorials/introduction.ipynb diff --git a/docs/source/index.rst b/docs/source/index.rst index 390aabae6..2156aa7db 100644 --- a/docs/source/index.rst +++ b/docs/source/index.rst @@ -52,7 +52,7 @@ In particular: :hidden: overview/features.rst - overview/tutorials/index.rst + Tutorials .. toctree:: :maxdepth: 1 diff --git a/docs/source/overview/tutorials.ipynb b/docs/source/overview/tutorials.ipynb new file mode 100644 index 000000000..aff0911c4 --- /dev/null +++ b/docs/source/overview/tutorials.ipynb @@ -0,0 +1,849 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "nominated-inspection", + "metadata": {}, + "source": [ + "# Tutorials\n", + "\n", + "The following provides a short tutorial on how to use some of the main features of Yadism. After this tutorial, the user will know how to:\n", + "- prepare the observable and theory cards required for any `yadism` computation\n", + "- compute an observable by convoluting `yadism` prediction to a given PDF set\n", + "- tabulate the `yadism` predictions into an interpolation table for a later use" + ] + }, + { + "cell_type": "markdown", + "id": "bfff8f0c-740e-4177-a642-13e9d0a0cc63", + "metadata": {}, + "source": [ + "## Installation \n", + "\n", + "In order to start using Yadism, one first needs to install it. The easiest way to install the latest stable version is via `pip` using the following command\n", + "\n", + "```sh\n", + "pip install yadism\n", + "```\n", + "\n", + "If one wishes in addition to also install the Yadism benchmark pacakge (see yadmark), one can instead run the following command:\n", + "\n", + "```sh\n", + "pip install 'yadism[mark]'\n", + "```\n", + "\n", + "We can check that Yadism was properly installed by checking the version:" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "ded2fb96-9fe9-4503-8418-bfcfb6d53998", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "'0.0.0'" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "import yadism\n", + "yadism.__version__" + ] + }, + { + "cell_type": "markdown", + "id": "valuable-theater", + "metadata": {}, + "source": [ + "## Preparing the run cards\n", + "\n", + "Yadism takes as inputs two runcards (represented as dictionaries):\n", + "- an observable card which contains the details on the observable to be computed\n", + "- a theory card which contains the various theory settings\n", + "\n", + "Below is an example of an observable card in which the meaning of each key is also specified:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "announced-petite", + "metadata": {}, + "outputs": [], + "source": [ + "observable_card = {\n", + " # Process type: \"EM\", \"NC\", \"CC\"\n", + " \"prDIS\": \"NC\",\n", + " # Projectile: \"electron\", \"positron\", \"neutrino\", \"antineutrino\"\n", + " \"ProjectileDIS\": \"electron\",\n", + " # Scattering target: \"proton\", \"neutron\", \"isoscalar\", \"lead\", \"iron\", \"neon\" or \"marble\"\n", + " \"TargetDIS\": \"proton\",\n", + " # Interpolation: if True use log interpolation\n", + " \"interpolation_is_log\": True,\n", + " # Interpolation: polynomial degree, 1 = linear, ...\n", + " \"interpolation_polynomial_degree\": 4,\n", + " # Interpolation: xgrid values\n", + " # Note: for illustrative purposes the grid is chosen very small here\n", + " \"interpolation_xgrid\": [1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1.0],\n", + " # Observables configurations\n", + " \"observables\": {\n", + " \"XSHERANCAVG_charm\": [\n", + " {\n", + " \"y\": 0.8240707777909629,\n", + " \"x\": 3e-05,\n", + " \"Q2\": 2.5,\n", + " },\n", + " {\n", + " \"y\": 0.3531731904818413,\n", + " \"x\": 7e-05,\n", + " \"Q2\": 2.5,\n", + " },\n", + " # Add here the kinematics of other datapoints\n", + " ],\n", + " # Potentially include observables other than XSHERANCAVG_charm,\n", + " # each of them has to be: TYPE_heaviness, where heaviness can take:\n", + " # \"charm\", \"bottom\", \"top\", \"total\" or \"light\".\n", + " },\n", + " # Projectile polarization faction, float from 0 to 1.\n", + " \"PolarizationDIS\": 0.0,\n", + " # Exchanged boson propagator correction\n", + " \"PropagatorCorrection\": 0.0,\n", + " # Restrict boson coupling to a single parton ? Monte Carlo PID or None for all partons\n", + " \"NCPositivityCharge\": None,\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "dc1b79fa-7d14-4ed6-a8ae-0a588ebe5582", + "metadata": {}, + "source": [ + "Similarly, below is an example of a theory card:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "90df79a9-31cb-40db-ac95-0b88469c1723", + "metadata": {}, + "outputs": [], + "source": [ + "theory_card = {\n", + " \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\", # CKM matrix elements\n", + " \"FNS\": \"FFNS\", # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n", + " \"GF\": 1.1663787e-05, # [GeV^-2] Fermi coupling constant\n", + " \"IC\": 1, # 0 = perturbative charm only, 1 = intrinsic charm allowed\n", + " \"MP\": 0.938, # [GeV] proton mass\n", + " \"MW\": 80.398, # [GeV] W boson mass\n", + " \"MZ\": 91.1876, # [GeV] Z boson mass\n", + " \"NfFF\": 4, # (fixed) number of running flavors, only for FFNS or FFN0 schemes\n", + " \"PTO\": 2, # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n", + " \"Q0\": 1.65, # [GeV] reference scale for the flavor patch determination\n", + " \"nf0\": 4, # number of active flavors at the Q0 reference scale\n", + " \"Qref\": 91.2, # [GeV] reference scale for the alphas value\n", + " \"nfref\": 5, # number of active flavors at the reference scale Qref\n", + " \"alphas\": 0.118, # alphas value at the reference scale\n", + " \"TMC\": 1, # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n", + " \"XIF\": 1.0, # ratio of factorization scale over the hard scattering scale\n", + " \"XIR\": 1.0, # ratio of renormalization scale over the hard scattering scale\n", + " \"alphaqed\": 0.007496252, # alpha_em value\n", + " \"kcThr\": 1.0, # ratio of the charm matching scale over the charm mass\n", + " \"kbThr\": 1.0, # ratio of the bottom matching scale over the bottom mass\n", + " \"ktThr\": 1.0, # ratio of the top matching scale over the top mass\n", + " \"mc\": 1.51, # [GeV] charm mass\n", + " \"mb\": 4.92, # [GeV] bottom mass\n", + " \"mt\": 172.5, # [GeV] top mass\n", + " \"n3lo_cf_variation\": 0, # N3LO coefficient functions variation: -1 = lower bound, 0 = central , 1 = upper bound\n", + " \"QED\": 0, # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n", + " \"MaxNfAs\": 5, # maximum number of flavors in running of strong coupling\n", + " \"HQ\": \"POLE\", # heavy quark mass scheme (not yet implemented in yadism)\n", + " \"MaxNfPdf\": 5, # maximum number of flavors in running of PDFs (ignored by yadism)\n", + " \"ModEv\": \"EXA\", # evolution solver for PDFs (ignored by yadism)\n", + "}" + ] + }, + { + "cell_type": "markdown", + "id": "169b82a0-abdd-4687-9ffe-9df38446a550", + "metadata": {}, + "source": [ + "Note that a template observable is provided by `yadmark` (assuming it was installed). One can thus just start from the default card and overwrite the values." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "246f1d7a-e7e3-48ab-9bf2-44c8352adc39", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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already installed as a dependency, only needed for a pretty printing\n", + "from yadmark.data.observables import default_card\n", + "pprint(default_card)" + ] + }, + { + "cell_type": "markdown", + "id": "5083afea-4ac9-483d-93b9-f0473cbc46b0", + "metadata": {}, + "source": [ + "## Computing predictions\n", + "\n", + "Now that we have all the necessary inputs, we can now compute the corresponding predictions:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "b7d95bf6-4536-41a5-9505-07a8743e5f6e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
[17:13:31] INFO     Interpolation: number of points = 8, polynomial degree = 4, logarithmic =  interpolation.py:537\n",
+       "                    True                                                                                           \n",
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+       "                    0.23121, 'MW2': 6463.838403999999}                                                             \n",
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           INFO     {'process': 'NC', 'projectilePID': 11, 'polarization': 0.0,            coupling_constants.py:53\n",
+       "                    'propagatorCorrection': 0.0, 'nc_pos_charge': None}                                            \n",
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           INFO     RenScaleVar: False, FactScaleVar: False                                  scale_variations.py:61\n",
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           INFO     PTO: 2, PTO@evolution: 2, process: NC                                             runner.py:146\n",
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           INFO     FNS: FFNS, NfFF: 4                                                                runner.py:153\n",
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           INFO     Intrinsic: [4]                                                                    runner.py:154\n",
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           INFO     projectile: electron, target: {Z: 1, A: 1}                                        runner.py:155\n",
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+       "                                      │                                    │                                       \n",
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+       "                                                       Plan                                                        \n",
+       "
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\n",
+       " • XSHERANCAVG_charm at 2 pts                                                                                      \n",
+       "
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+       "                                                    Calculation                                                    \n",
+       "
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yadism took off! please stay tuned ...\n",
+       "
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\n"
+      ],
+      "text/plain": [
+       "\u001b[?25l"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\u001b[?25h
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+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[?25h"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
took 0.23 s\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[36mtook \u001b[0m\u001b[1;36m0.23\u001b[0m\u001b[36m s\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "out = yadism.run_yadism(theory_card, observable_card)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a1d79202-30d1-465f-9ce2-008fc760ebf1",
+   "metadata": {},
+   "source": [
+    "`out` is an object of type `yadism.output.Output` from which one can perform various operations. In our example, we are interested in convoluting it with a PDF set in the LHAPDF format.\n",
+    "\n",
+    "To do so, first we need to import the `lhapdf` package. For this example, we will use the NNPDF4.0 set: `NNPDF40_nnlo_as_01180`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "bc6f3aac-802b-4073-9e6a-e18e54f3ef85",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LHAPDF 6.5.0 loading /home/tanjona/miniconda3/envs/yadism/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
+      "NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100\n"
+     ]
+    }
+   ],
+   "source": [
+    "import lhapdf\n",
+    "pdf = lhapdf.mkPDF(\"NNPDF40_nnlo_as_01180\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "359f3118-a317-4345-8e73-bc810b92ea92",
+   "metadata": {},
+   "source": [
+    "The convolution can simply be performed as follow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "9b983dd8-4724-439c-bdab-773879308985",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[17:13:33] INFO     Atlas [0.00e+00 - 2.28e+00 - 2.42e+01 - 2.98e+04 - inf], ref=8317.44 @ 5        matchings.py:69\n",
+       "
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+      ],
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
           INFO     Strong Coupling: a_s(µ_R^2=8317.440000)^(nf=5)=0.009390=0.118000/(4π)          couplings.py:458\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Strong Coupling: \u001b[1;35ma_s\u001b[0m\u001b[1m(\u001b[0mµ_R^\u001b[1;36m2\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.440000\u001b[0m\u001b[1m)\u001b[0m^\u001b[1m(\u001b[0m\u001b[33mnf\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1m)\u001b[0m=\u001b[1;36m0.\u001b[0m\u001b[1;36m009390\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.118000\u001b[0m/\u001b[1m(\u001b[0m4π\u001b[1m)\u001b[0m          \u001b]8;id=48542;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py\u001b\\\u001b[2mcouplings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=745971;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py#458\u001b\\\u001b[2m458\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "
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+      ],
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+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "values = out.apply_pdf(pdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "a56aee13-b08b-492f-80d0-3487bea74318",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
{\n",
+       "│   'XSHERANCAVG_charm': [\n",
+       "│   │   {\n",
+       "│   │   │   'x': 3e-05,\n",
+       "│   │   │   'Q2': 2.5,\n",
+       "│   │   │   'result': -0.9959496128078331,\n",
+       "│   │   │   'error': 1.281070214968848e-08,\n",
+       "│   │   │   'y': 0.8240707777909629\n",
+       "│   │   },\n",
+       "│   │   {\n",
+       "│   │   │   'x': 7e-05,\n",
+       "│   │   │   'Q2': 2.5,\n",
+       "│   │   │   'result': -0.7710853256052412,\n",
+       "│   │   │   'error': 2.3298246570353407e-08,\n",
+       "│   │   │   'y': 0.3531731904818413\n",
+       "│   │   }\n",
+       "│   ]\n",
+       "}\n",
+       "
\n"
+      ],
+      "text/plain": [
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+       "\u001b[2;32m│   \u001b[0m\u001b[32m'XSHERANCAVG_charm'\u001b[0m: \u001b[1m[\u001b[0m\n",
+       "\u001b[2;32m│   │   \u001b[0m\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'x'\u001b[0m: \u001b[1;36m3e-05\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'Q2'\u001b[0m: \u001b[1;36m2.5\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'result'\u001b[0m: \u001b[1;36m-0.9959496128078331\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'error'\u001b[0m: \u001b[1;36m1.281070214968848e-08\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'y'\u001b[0m: \u001b[1;36m0.8240707777909629\u001b[0m\n",
+       "\u001b[2;32m│   │   \u001b[0m\u001b[1m}\u001b[0m,\n",
+       "\u001b[2;32m│   │   \u001b[0m\u001b[1m{\u001b[0m\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'x'\u001b[0m: \u001b[1;36m7e-05\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'Q2'\u001b[0m: \u001b[1;36m2.5\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'result'\u001b[0m: \u001b[1;36m-0.7710853256052412\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'error'\u001b[0m: \u001b[1;36m2.3298246570353407e-08\u001b[0m,\n",
+       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'y'\u001b[0m: \u001b[1;36m0.3531731904818413\u001b[0m\n",
+       "\u001b[2;32m│   │   \u001b[0m\u001b[1m}\u001b[0m\n",
+       "\u001b[2;32m│   \u001b[0m\u001b[1m]\u001b[0m\n",
+       "\u001b[1m}\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pprint(values)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "519b8537-9c09-4a66-bf44-ff47e1879449",
+   "metadata": {},
+   "source": [
+    "## Dumping (loading) predictions into (from) fast-interpolation grids\n",
+    "\n",
+    "One of the main advantages of `yadism` is its interface with [PineAPPL](https://github.com/NNPDF/pineappl) - a library providing fast-interpolation grids. This is quite convenient in that one can re-use the same computations without the need to re-run `yadism`.\n",
+    "\n",
+    "Each observable defined in `observable_card` can be dumped into its own fast-interpolation grid. The steps are as follow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "7f914e87-bb05-47c7-a850-11a18e6cfdb5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from yadbox.export import dump_pineappl_to_file\n",
+    "\n",
+    "# Extract the names of the different observables (in case there are many)\n",
+    "list_observables = observable_card['observables'].keys()\n",
+    "\n",
+    "# Dump each observable into a PineAPPL grid\n",
+    "for obs in list_observables:\n",
+    "    dump_pineappl_to_file(out, f\"outputgrid_{obs}.pineappl.lz4\", f\"{obs}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c887943-be93-4a0f-815b-1317ad04db2c",
+   "metadata": {},
+   "source": [
+    "To load the pre-computed predictions, we need to import the `pineappl` library. `pineappl` is part of the dependency of `yadism` so we don't have to install it."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "ebf75d0e-965a-46b1-a3a3-e20eeb1d5e15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pineappl\n",
+    "\n",
+    "# Read the pineappl grid saved earlier\n",
+    "grid = pineappl.grid.Grid.read(\"./outputgrid_XSHERANCAVG_charm.pineappl.lz4\")\n",
+    "\n",
+    "# Convolute the grid with the same PDF as above\n",
+    "results = grid.convolute_with_one(2212, pdf.xfxQ2, pdf.alphasQ2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "fc268946-3f84-4f63-be98-a899adf9512c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
array([-0.98699882, -0.7640712 ])\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-0.98699882\u001b[0m, \u001b[1;36m-0.7640712\u001b[0m \u001b[1m]\u001b[0m\u001b[1m)\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "pprint(results)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "yadism",
+   "language": "python",
+   "name": "yadism"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/overview/tutorials/benchmarks.ipynb b/docs/source/overview/tutorials/benchmarks.ipynb
deleted file mode 100644
index 6cf61b7b2..000000000
--- a/docs/source/overview/tutorials/benchmarks.ipynb
+++ /dev/null
@@ -1,53 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "russian-guidance",
-   "metadata": {},
-   "source": [
-    "# Running Benchmarks\n",
-    "A good way of learning something about `yadism` it's running the benchmarks suite provided, and check the output through its `navigator`"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "perceived-aspect",
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
-  {
-   "cell_type": "markdown",
-   "id": "solid-paraguay",
-   "metadata": {},
-   "source": [
-    "## Unit tests\n",
-    "For more specific information about single functions and usage another good idea it's to have a look to how they are used in unit-tests.\n",
-    "\n",
-    "But the main option will always be the trivial one: **read the docs**."
-   ]
-  }
- ],
- "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": "3.8.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/docs/source/overview/tutorials/index.rst b/docs/source/overview/tutorials/index.rst
deleted file mode 100644
index d0109f913..000000000
--- a/docs/source/overview/tutorials/index.rst
+++ /dev/null
@@ -1,13 +0,0 @@
-Tutorials
-=========
-
-Instead of bare examples is better to have full tutorials!
-
-If I will have ever the time to write them this section will be populated by
-tutorials on how to use `yadism`, including fully running examples.
-
-.. toctree::
-   :hidden:
-
-   Introduction 
-   Benchmarks 
diff --git a/docs/source/overview/tutorials/introduction.ipynb b/docs/source/overview/tutorials/introduction.ipynb
deleted file mode 100644
index c9861bfd2..000000000
--- a/docs/source/overview/tutorials/introduction.ipynb
+++ /dev/null
@@ -1,81 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "accredited-amateur",
-   "metadata": {},
-   "source": [
-    "# Introduction\n",
-    "\n",
-    "`yadism` it's wonderful to install and wonderful to use, you just need:\n",
-    "\n",
-    "- `pip`\n",
-    "- a couple of fully specified runcards (but you can download some example ones from [here])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "nominated-inspection",
-   "metadata": {},
-   "source": [
-    "## Installation\n",
-    "As written in the `README.md` instructions just run:\n",
-    "\n",
-    "```sh\n",
-    "pip install yadism\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "valuable-theater",
-   "metadata": {},
-   "source": [
-    "## Basic usage"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "announced-petite",
-   "metadata": {},
-   "outputs": [
-    {
-     "ename": "ModuleNotFoundError",
-     "evalue": "No module named 'yadism'",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
-      "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0myadism\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
-      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'yadism'"
-     ]
-    }
-   ],
-   "source": [
-    "import yadism"
-   ]
-  }
- ],
- "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": "3.8.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}

From 553095bfba9d64d9580c1685a732fc49a1522ccd Mon Sep 17 00:00:00 2001
From: Radonirinaunimi 
Date: Thu, 18 Jan 2024 22:06:02 +0100
Subject: [PATCH 02/18] improve a bit the content

---
 docs/source/overview/tutorials.ipynb | 137 ++++++++++++++++++---------
 1 file changed, 92 insertions(+), 45 deletions(-)

diff --git a/docs/source/overview/tutorials.ipynb b/docs/source/overview/tutorials.ipynb
index aff0911c4..3b12d6936 100644
--- a/docs/source/overview/tutorials.ipynb
+++ b/docs/source/overview/tutorials.ipynb
@@ -7,10 +7,10 @@
    "source": [
     "# Tutorials\n",
     "\n",
-    "The following provides a short tutorial on how to use some of the main features of Yadism. After this tutorial, the user will know how to:\n",
+    "The following tutorial provides a brief introduction on some of the main features of `yadism`. This tutorial has three main objectives, namely to introduce the user on how to:\n",
     "- prepare the observable and theory cards required for any `yadism` computation\n",
-    "- compute an observable by convoluting `yadism` prediction to a given PDF set\n",
-    "- tabulate the `yadism` predictions into an interpolation table for a later use"
+    "- compute observables by convoluting `yadism` predictions to PDFs (Parton Distribution Functions)\n",
+    "- tabulate the `yadism` predictions into fast-interpolation grids for later use"
    ]
   },
   {
@@ -20,19 +20,15 @@
    "source": [
     "## Installation \n",
     "\n",
-    "In order to start using Yadism, one first needs to install it. The easiest way to install the latest stable version is via `pip` using the following command\n",
+    "In order to start using `yadism`, one first needs to install it and some of its extra-dependencies. The easiest way to install the latest stable version of `yadism` is via `pip` using the following command:\n",
     "\n",
     "```sh\n",
-    "pip install yadism\n",
+    "pip install 'yadism[mark, box]'\n",
     "```\n",
     "\n",
-    "If one wishes in addition to also install the Yadism benchmark pacakge (see yadmark), one can instead run the following command:\n",
+    "In addition to installing the main `yadism` package, the above command also installs `yadmark` and `yadbox`. `yadmark` is package that provides APIs to perform the benchmkar of `yadism` to other DIS codes (e.g. `APFEL`, `APFEL++`, `QCDNUM`). `yadbox` instead provides an interface to `PineAPPL` to store predictions in the form of fast-interpolation grids.\n",
     "\n",
-    "```sh\n",
-    "pip install 'yadism[mark]'\n",
-    "```\n",
-    "\n",
-    "We can check that Yadism was properly installed by checking the version:"
+    "In order to check that `yadism` was installed properly, one can check the version:"
    ]
   },
   {
@@ -64,9 +60,9 @@
    "source": [
     "## Preparing the run cards\n",
     "\n",
-    "Yadism takes as inputs two runcards (represented as dictionaries):\n",
-    "- an observable card which contains the details on the observable to be computed\n",
-    "- a theory card which contains the various theory settings\n",
+    "Yadism takes as inputs **two runcards** whose representations are given in terms of python dictionaries. That is, one needs:\n",
+    "- an **observable card** which contains the details on the observable to be computed\n",
+    "- a **theory card** which contains the various theory settings to compute the observable in question\n",
     "\n",
     "Below is an example of an observable card in which the meaning of each key is also specified:"
    ]
@@ -125,6 +121,8 @@
    "id": "dc1b79fa-7d14-4ed6-a8ae-0a588ebe5582",
    "metadata": {},
    "source": [
+    "The `observables` key in the `observable_card` (which is also a dictionary) can contain multiple elements whose keys must represent structure functions or cross-sections. For the list of available observables, refer to the following [part](https://yadism.readthedocs.io/en/latest/theory/intro.html#) of the documentation.\n",
+    "\n",
     "Similarly, below is an example of a theory card:"
    ]
   },
@@ -174,7 +172,7 @@
    "id": "169b82a0-abdd-4687-9ffe-9df38446a550",
    "metadata": {},
    "source": [
-    "Note that a template observable is provided by `yadmark` (assuming it was installed). One can thus just start from the default card and overwrite the values."
+    "Note that a template observable card is provided by `yadmark` and contains the default `yadism` values. One can thus just start from the default card and overwrite the values."
    ]
   },
   {
@@ -321,7 +319,8 @@
    ],
    "source": [
     "from rich.pretty import pprint # already installed as a dependency, only needed for a pretty printing\n",
-    "from yadmark.data.observables import default_card\n",
+    "from yadmark.data.observables import default_card # imports the default yadism observable card\n",
+    "\n",
     "pprint(default_card)"
    ]
   },
@@ -332,24 +331,24 @@
    "source": [
     "## Computing predictions\n",
     "\n",
-    "Now that we have all the necessary inputs, we can now compute the corresponding predictions:"
+    "Now that we have defined our observable and theory, we can now compute the corresponding preditions. This can be easily done by running the following:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 6,
    "id": "b7d95bf6-4536-41a5-9505-07a8743e5f6e",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
-       "
[17:13:31] INFO     Interpolation: number of points = 8, polynomial degree = 4, logarithmic =  interpolation.py:537\n",
+       "
[21:32:59] INFO     Interpolation: number of points = 8, polynomial degree = 4, logarithmic =  interpolation.py:537\n",
        "                    True                                                                                           \n",
        "
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       "text/plain": [
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+       "\u001b[2;36m[21:32:59]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Interpolation: number of points = \u001b[1;36m8\u001b[0m, polynomial degree = \u001b[1;36m4\u001b[0m, logarithmic =  \u001b]8;id=704949;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/interpolation.py\u001b\\\u001b[2minterpolation.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=162454;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/interpolation.py#537\u001b\\\u001b[2m537\u001b[0m\u001b]8;;\u001b\\\n",
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@@ -366,7 +365,7 @@
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+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m \u001b[1m{\u001b[0m\u001b[32m'MZ2'\u001b[0m: \u001b[1;36m8315.178393760001\u001b[0m, \u001b[32m'CKM'\u001b[0m: \u001b[1;35mCKM\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m9.49221518e-01\u001b[0m \u001b[1;36m5.07600900e-02\u001b[0m  \u001b]8;id=56181;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/coefficient_functions/coupling_constants.py\u001b\\\u001b[2mcoupling_constants.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=853819;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/coefficient_functions/coupling_constants.py#52\u001b\\\u001b[2m52\u001b[0m\u001b]8;;\u001b\\\n",
        "\u001b[2;36m           \u001b[0m         \u001b[1;36m1.20409000e-05\u001b[0m\u001b[1m]\u001b[0m \u001b[1m[\u001b[0m\u001b[1;36m5.07150400e-02\u001b[0m \u001b[1;36m9.47604903e-01\u001b[0m \u001b[1;36m1.68100000e-03\u001b[0m\u001b[1m]\u001b[0m         \u001b[2m                        \u001b[0m\n",
        "\u001b[2;36m           \u001b[0m         \u001b[1m[\u001b[0m\u001b[1;36m7.43044000e-05\u001b[0m \u001b[1;36m1.62409000e-03\u001b[0m \u001b[1;36m9.98304719e-01\u001b[0m\u001b[1m]\u001b[0m\u001b[1m]\u001b[0m\u001b[1m)\u001b[0m, \u001b[32m'sin2theta_weak'\u001b[0m:    \u001b[2m                        \u001b[0m\n",
        "\u001b[2;36m           \u001b[0m         \u001b[1;36m0.23121\u001b[0m, \u001b[32m'MW2'\u001b[0m: \u001b[1;36m6463.838403999999\u001b[0m\u001b[1m}\u001b[0m                                     \u001b[2m                        \u001b[0m\n"
@@ -383,7 +382,7 @@
        "\n"
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+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m \u001b[1m{\u001b[0m\u001b[32m'process'\u001b[0m: \u001b[32m'NC'\u001b[0m, \u001b[32m'projectilePID'\u001b[0m: \u001b[1;36m11\u001b[0m, \u001b[32m'polarization'\u001b[0m: \u001b[1;36m0.0\u001b[0m,            \u001b]8;id=326312;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/coefficient_functions/coupling_constants.py\u001b\\\u001b[2mcoupling_constants.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=908778;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/coefficient_functions/coupling_constants.py#53\u001b\\\u001b[2m53\u001b[0m\u001b]8;;\u001b\\\n",
        "\u001b[2;36m           \u001b[0m         \u001b[32m'propagatorCorrection'\u001b[0m: \u001b[1;36m0.0\u001b[0m, \u001b[32m'nc_pos_charge'\u001b[0m: \u001b[3;35mNone\u001b[0m\u001b[1m}\u001b[0m                    \u001b[2m                        \u001b[0m\n"
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@@ -397,7 +396,7 @@
        "\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m RenScaleVar: \u001b[3;91mFalse\u001b[0m, FactScaleVar: \u001b[3;91mFalse\u001b[0m                                  \u001b]8;id=321435;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/esf/scale_variations.py\u001b\\\u001b[2mscale_variations.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=492824;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/esf/scale_variations.py#61\u001b\\\u001b[2m61\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m RenScaleVar: \u001b[3;91mFalse\u001b[0m, FactScaleVar: \u001b[3;91mFalse\u001b[0m                                  \u001b]8;id=344383;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/esf/scale_variations.py\u001b\\\u001b[2mscale_variations.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=760986;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/esf/scale_variations.py#61\u001b\\\u001b[2m61\u001b[0m\u001b]8;;\u001b\\\n"
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      "metadata": {},
@@ -410,7 +409,7 @@
        "\n"
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+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m0.00e+00\u001b[0m - inf - inf - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m2\u001b[0m\u001b[1;36m.7224999999999997\u001b[0m @ \u001b[1;36m4\u001b[0m       \u001b]8;id=684830;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=962601;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
       ]
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      "metadata": {},
@@ -423,7 +422,7 @@
        "\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m PTO: \u001b[1;36m2\u001b[0m, PTO@evolution: \u001b[1;36m2\u001b[0m, process: NC                                             \u001b]8;id=528897;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=838475;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#146\u001b\\\u001b[2m146\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m PTO: \u001b[1;36m2\u001b[0m, PTO@evolution: \u001b[1;36m2\u001b[0m, process: NC                                             \u001b]8;id=493106;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=661291;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#146\u001b\\\u001b[2m146\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -436,7 +435,7 @@
        "\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m FNS: FFNS, NfFF: \u001b[1;36m4\u001b[0m                                                                \u001b]8;id=952394;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=688311;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#153\u001b\\\u001b[2m153\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m FNS: FFNS, NfFF: \u001b[1;36m4\u001b[0m                                                                \u001b]8;id=905679;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=440153;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#153\u001b\\\u001b[2m153\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -449,7 +448,7 @@
        "\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Intrinsic: \u001b[1m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1m]\u001b[0m                                                                    \u001b]8;id=15986;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=831273;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#154\u001b\\\u001b[2m154\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Intrinsic: \u001b[1m[\u001b[0m\u001b[1;36m4\u001b[0m\u001b[1m]\u001b[0m                                                                    \u001b]8;id=537556;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=331787;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#154\u001b\\\u001b[2m154\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -462,7 +461,7 @@
        "\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m projectile: electron, target: \u001b[1m{\u001b[0mZ: \u001b[1;36m1\u001b[0m, A: \u001b[1;36m1\u001b[0m\u001b[1m}\u001b[0m                                        \u001b]8;id=634484;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=493872;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#155\u001b\\\u001b[2m155\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m projectile: electron, target: \u001b[1m{\u001b[0mZ: \u001b[1;36m1\u001b[0m, A: \u001b[1;36m1\u001b[0m\u001b[1m}\u001b[0m                                        \u001b]8;id=366914;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py\u001b\\\u001b[2mrunner.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=376500;file:///home/tanjona/Documents/WORK/NNPDF/yadism/src/yadism/runner.py#155\u001b\\\u001b[2m155\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -586,11 +585,11 @@
     {
      "data": {
       "text/html": [
-       "
took 0.23 s\n",
+       "
took 0.24 s\n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[36mtook \u001b[0m\u001b[1;36m0.23\u001b[0m\u001b[36m s\u001b[0m\n"
+       "\u001b[36mtook \u001b[0m\u001b[1;36m0.24\u001b[0m\u001b[36m s\u001b[0m\n"
       ]
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      "metadata": {},
@@ -606,14 +605,14 @@
    "id": "a1d79202-30d1-465f-9ce2-008fc760ebf1",
    "metadata": {},
    "source": [
-    "`out` is an object of type `yadism.output.Output` from which one can perform various operations. In our example, we are interested in convoluting it with a PDF set in the LHAPDF format.\n",
+    "`out` is an object of type `yadism.output.Output` from which one can perform various operations. In our example, we are interested in convoluting it with a PDF set in the [LHAPDF](https://lhapdf.hepforge.org/) format.\n",
     "\n",
-    "To do so, first we need to import the `lhapdf` package. For this example, we will use the NNPDF4.0 set: `NNPDF40_nnlo_as_01180`."
+    "To do so, first we need to import the `lhapdf` package. For this example, we will use the NNLO NNPDF4.0 set: `NNPDF40_nnlo_as_01180`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 7,
    "id": "bc6f3aac-802b-4073-9e6a-e18e54f3ef85",
    "metadata": {},
    "outputs": [
@@ -628,6 +627,8 @@
    ],
    "source": [
     "import lhapdf\n",
+    "\n",
+    "# load the PDF set\n",
     "pdf = lhapdf.mkPDF(\"NNPDF40_nnlo_as_01180\")"
    ]
   },
@@ -641,18 +642,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "id": "9b983dd8-4724-439c-bdab-773879308985",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/html": [
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+       "
[21:37:46] INFO     Atlas [0.00e+00 - 2.28e+00 - 2.42e+01 - 2.98e+04 - inf], ref=8317.44 @ 5        matchings.py:69\n",
        "
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       ],
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+       "\u001b[2;36m[21:37:46]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m2.28e+00\u001b[0m - \u001b[1;36m2.42e+01\u001b[0m - \u001b[1;36m2.98e+04\u001b[0m - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.44\u001b[0m @ \u001b[1;36m5\u001b[0m        \u001b]8;id=996071;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=24744;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
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      "metadata": {},
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        "
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       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Strong Coupling: \u001b[1;35ma_s\u001b[0m\u001b[1m(\u001b[0mµ_R^\u001b[1;36m2\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.440000\u001b[0m\u001b[1m)\u001b[0m^\u001b[1m(\u001b[0m\u001b[33mnf\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1m)\u001b[0m=\u001b[1;36m0.\u001b[0m\u001b[1;36m009390\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.118000\u001b[0m/\u001b[1m(\u001b[0m4π\u001b[1m)\u001b[0m          \u001b]8;id=48542;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py\u001b\\\u001b[2mcouplings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=745971;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py#458\u001b\\\u001b[2m458\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Strong Coupling: \u001b[1;35ma_s\u001b[0m\u001b[1m(\u001b[0mµ_R^\u001b[1;36m2\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.440000\u001b[0m\u001b[1m)\u001b[0m^\u001b[1m(\u001b[0m\u001b[33mnf\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1m)\u001b[0m=\u001b[1;36m0.\u001b[0m\u001b[1;36m009390\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.118000\u001b[0m/\u001b[1m(\u001b[0m4π\u001b[1m)\u001b[0m          \u001b]8;id=295081;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py\u001b\\\u001b[2mcouplings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=206002;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py#458\u001b\\\u001b[2m458\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -678,7 +679,7 @@
        "
\n"
       ],
       "text/plain": [
-       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m2.28e+00\u001b[0m - \u001b[1;36m2.42e+01\u001b[0m - \u001b[1;36m2.98e+04\u001b[0m - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.44\u001b[0m @ \u001b[1;36m5\u001b[0m        \u001b]8;id=596034;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=509149;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m2.28e+00\u001b[0m - \u001b[1;36m2.42e+01\u001b[0m - \u001b[1;36m2.98e+04\u001b[0m - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.44\u001b[0m @ \u001b[1;36m5\u001b[0m        \u001b]8;id=842613;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=103523;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
       ]
      },
      "metadata": {},
@@ -691,7 +692,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "id": "a56aee13-b08b-492f-80d0-3487bea74318",
    "metadata": {},
    "outputs": [
@@ -747,25 +748,36 @@
     "pprint(values)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "2c0ffc4a-bb6b-4d89-9a01-1d2c93e49995",
+   "metadata": {},
+   "source": [
+    "We can see that `values` is a dictionary containing one element whose key is the name of the observable (as we defined above). If we had defined two observables in the `observable_card`, `values` would also contain two elements."
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "519b8537-9c09-4a66-bf44-ff47e1879449",
    "metadata": {},
    "source": [
-    "## Dumping (loading) predictions into (from) fast-interpolation grids\n",
+    "## Dumping predictions into fast-interpolation grids\n",
     "\n",
-    "One of the main advantages of `yadism` is its interface with [PineAPPL](https://github.com/NNPDF/pineappl) - a library providing fast-interpolation grids. This is quite convenient in that one can re-use the same computations without the need to re-run `yadism`.\n",
+    "We learned from the previous sections how to compute an observable using `yadism` and now we'll see how to tabulate the output of `yadism.run_yadism` into a fast-interpolation table. This has the convenient advantage that one can re-use the same computations without the need to re-run `yadism` (to convolute with different PDF sets for example).\n",
+    "\n",
+    "One of the main advantage of `yadism` is its interface with PineAPPL - a library providing fast interpolation into a unique format suitable for various HEP-related softwares. \n",
     "\n",
     "Each observable defined in `observable_card` can be dumped into its own fast-interpolation grid. The steps are as follow:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 10,
    "id": "7f914e87-bb05-47c7-a850-11a18e6cfdb5",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# import function that dumps the predictions into a Pineappl format\n",
     "from yadbox.export import dump_pineappl_to_file\n",
     "\n",
     "# Extract the names of the different observables (in case there are many)\n",
@@ -776,21 +788,48 @@
     "    dump_pineappl_to_file(out, f\"outputgrid_{obs}.pineappl.lz4\", f\"{obs}\")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "7dffb5fd-9e84-4982-b9d4-a4f077a573e8",
+   "metadata": {},
+   "source": [
+    "Our PineAPPL grid has now been written on the disk. Note that the extension has to be `pineappl.lz4`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "703b29ce-9068-44af-b72b-1144bad805e6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "outputgrid_XSHERANCAVG_charm.pineappl.lz4\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls outputgrid_*"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "0c887943-be93-4a0f-815b-1317ad04db2c",
    "metadata": {},
    "source": [
-    "To load the pre-computed predictions, we need to import the `pineappl` library. `pineappl` is part of the dependency of `yadism` so we don't have to install it."
+    "To load the pre-computed predictions, we need to import the `pineappl` package. Given that `pineappl` is a dependency of `yadism` it was already installed so we don't have to install it again."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 12,
    "id": "ebf75d0e-965a-46b1-a3a3-e20eeb1d5e15",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# imports the pineappl package\n",
     "import pineappl\n",
     "\n",
     "# Read the pineappl grid saved earlier\n",
@@ -802,7 +841,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 13,
    "id": "fc268946-3f84-4f63-be98-a899adf9512c",
    "metadata": {},
    "outputs": [
@@ -823,6 +862,14 @@
    "source": [
     "pprint(results)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c114b40d-9a40-4d73-8609-ab8761fe37a0",
+   "metadata": {},
+   "source": [
+    "As we can see, we get similar results to what we got before. Now, the `results` is just an array of two dimension corresponding to the different kinematic values."
+   ]
   }
  ],
  "metadata": {

From 5dd7de6d7b2b589249380f637e5697eb2559f1d5 Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Fri, 19 Jan 2024 11:26:59 +0200
Subject: [PATCH 03/18] Improve nb handling in docs

---
 docs/source/overview/tutorials.ipynb |    6 +-
 poetry.lock                          | 1650 ++++++++++++++------------
 pyproject.toml                       |    2 +
 3 files changed, 871 insertions(+), 787 deletions(-)

diff --git a/docs/source/overview/tutorials.ipynb b/docs/source/overview/tutorials.ipynb
index 3b12d6936..e8fc4bf31 100644
--- a/docs/source/overview/tutorials.ipynb
+++ b/docs/source/overview/tutorials.ipynb
@@ -26,7 +26,7 @@
     "pip install 'yadism[mark, box]'\n",
     "```\n",
     "\n",
-    "In addition to installing the main `yadism` package, the above command also installs `yadmark` and `yadbox`. `yadmark` is package that provides APIs to perform the benchmkar of `yadism` to other DIS codes (e.g. `APFEL`, `APFEL++`, `QCDNUM`). `yadbox` instead provides an interface to `PineAPPL` to store predictions in the form of fast-interpolation grids.\n",
+    "In addition to installing the main `yadism` package, the above command also installs `yadmark` and `yadbox`. `yadmark` is package that provides APIs to perform the benchmark of `yadism` to other DIS codes (e.g. `APFEL`, `APFEL++`, `QCDNUM`). `yadbox` instead provides an interface to `PineAPPL` to store predictions in the form of fast-interpolation grids.\n",
     "\n",
     "In order to check that `yadism` was installed properly, one can check the version:"
    ]
@@ -874,9 +874,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "yadism",
+   "display_name": "yadism-QljnF84o-py3.10",
    "language": "python",
-   "name": "yadism"
+   "name": "yadism-qljnf84o-py3.10"
   },
   "language_info": {
    "codemirror_mode": {
diff --git a/poetry.lock b/poetry.lock
index c9d5993c8..7db9bc332 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand.
 
 [[package]]
 name = "adani"
@@ -113,31 +113,32 @@ hg = ["python-hglib (>=1.5)"]
 
 [[package]]
 name = "attrs"
-version = "23.1.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"},
-    {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"},
+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
 ]
 
 [package.extras]
 cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
-dev = ["attrs[docs,tests]", "pre-commit"]
+dev = ["attrs[tests]", "pre-commit"]
 docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
 tests = ["attrs[tests-no-zope]", "zope-interface"]
-tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "babel"
-version = "2.13.1"
+version = "2.14.0"
 description = "Internationalization utilities"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "Babel-2.13.1-py3-none-any.whl", hash = "sha256:7077a4984b02b6727ac10f1f7294484f737443d7e2e66c5e4380e41a3ae0b4ed"},
-    {file = "Babel-2.13.1.tar.gz", hash = "sha256:33e0952d7dd6374af8dbf6768cc4ddf3ccfefc244f9986d4074704f2fbd18900"},
+    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
+    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
 ]
 
 [package.dependencies]
@@ -159,13 +160,13 @@ files = [
 
 [[package]]
 name = "banana-hep"
-version = "0.6.11"
+version = "0.6.12"
 description = "Benchmark QCD physics"
 optional = true
 python-versions = ">=3.8.0,<3.12"
 files = [
-    {file = "banana_hep-0.6.11-py3-none-any.whl", hash = "sha256:5eed795c5e9b2cdcb93a49df1180832a43cabfa7a4703e7dcb7ed26c3a897e4f"},
-    {file = "banana_hep-0.6.11.tar.gz", hash = "sha256:e1e7f4af2f64ca17c9992ab3a4fc857fb43fbb316a3e781156d465f1ddea452d"},
+    {file = "banana_hep-0.6.12-py3-none-any.whl", hash = "sha256:3cb065926a774689f6dee606dde0453e4e856dc1372c99e12f6b54aca26c41dd"},
+    {file = "banana_hep-0.6.12.tar.gz", hash = "sha256:0cf4a78f5affa5e1afe138ae6c9df5414deb9785901b585fcbdf6bbf531a1b9b"},
 ]
 
 [package.dependencies]
@@ -182,19 +183,22 @@ SQLAlchemy = ">=1.4.29,<2.0.0"
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.2"
+version = "4.12.3"
 description = "Screen-scraping library"
 optional = false
 python-versions = ">=3.6.0"
 files = [
-    {file = "beautifulsoup4-4.12.2-py3-none-any.whl", hash = "sha256:bd2520ca0d9d7d12694a53d44ac482d181b4ec1888909b035a3dbf40d0f57d4a"},
-    {file = "beautifulsoup4-4.12.2.tar.gz", hash = "sha256:492bbc69dca35d12daac71c4db1bfff0c876c00ef4a2ffacce226d4638eb72da"},
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
 ]
 
 [package.dependencies]
 soupsieve = ">1.2"
 
 [package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
@@ -218,13 +222,13 @@ css = ["tinycss2 (>=1.1.0,<1.3)"]
 
 [[package]]
 name = "certifi"
-version = "2023.7.22"
+version = "2023.11.17"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"},
-    {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"},
+    {file = "certifi-2023.11.17-py3-none-any.whl", hash = "sha256:e036ab49d5b79556f99cfc2d9320b34cfbe5be05c5871b51de9329f0603b0474"},
+    {file = "certifi-2023.11.17.tar.gz", hash = "sha256:9b469f3a900bf28dc19b8cfbf8019bf47f7fdd1a65a1d4ffb98fc14166beb4d1"},
 ]
 
 [[package]]
@@ -415,6 +419,23 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
+[[package]]
+name = "comm"
+version = "0.2.1"
+description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "comm-0.2.1-py3-none-any.whl", hash = "sha256:87928485c0dfc0e7976fd89fc1e187023cf587e7c353e4a9b417555b44adf021"},
+    {file = "comm-0.2.1.tar.gz", hash = "sha256:0bc91edae1344d39d3661dcbc36937181fdaddb304790458f8b044dbc064b89a"},
+]
+
+[package.dependencies]
+traitlets = ">=4"
+
+[package.extras]
+test = ["pytest"]
+
 [[package]]
 name = "commonmark"
 version = "0.9.1"
@@ -502,63 +523,63 @@ test-no-images = ["pytest", "pytest-cov", "wurlitzer"]
 
 [[package]]
 name = "coverage"
-version = "7.3.2"
+version = "7.4.0"
 description = "Code coverage measurement for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "coverage-7.3.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d872145f3a3231a5f20fd48500274d7df222e291d90baa2026cc5152b7ce86bf"},
-    {file = "coverage-7.3.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:310b3bb9c91ea66d59c53fa4989f57d2436e08f18fb2f421a1b0b6b8cc7fffda"},
-    {file = "coverage-7.3.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f47d39359e2c3779c5331fc740cf4bce6d9d680a7b4b4ead97056a0ae07cb49a"},
-    {file = "coverage-7.3.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:aa72dbaf2c2068404b9870d93436e6d23addd8bbe9295f49cbca83f6e278179c"},
-    {file = "coverage-7.3.2-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:beaa5c1b4777f03fc63dfd2a6bd820f73f036bfb10e925fce067b00a340d0f3f"},
-    {file = "coverage-7.3.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:dbc1b46b92186cc8074fee9d9fbb97a9dd06c6cbbef391c2f59d80eabdf0faa6"},
-    {file = "coverage-7.3.2-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:315a989e861031334d7bee1f9113c8770472db2ac484e5b8c3173428360a9148"},
-    {file = "coverage-7.3.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:d1bc430677773397f64a5c88cb522ea43175ff16f8bfcc89d467d974cb2274f9"},
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 docs = ["ipython", "matplotlib", "numpydoc", "sphinx"]
 tests = ["pytest", "pytest-cov", "pytest-xdist"]
 
+[[package]]
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+version = "1.8.0"
+description = "An implementation of the Debug Adapter Protocol for Python"
+optional = false
+python-versions = ">=3.8"
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 name = "decorator"
 version = "5.1.1"
@@ -631,13 +679,13 @@ files = [
 
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+version = "0.14.1"
 description = "Evolution Kernel Operators"
 optional = false
 python-versions = ">=3.8,<3.12"
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 [package.dependencies]
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 [[package]]
 name = "exceptiongroup"
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 description = "Backport of PEP 654 (exception groups)"
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 python-versions = ">=3.7"
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 [package.extras]
@@ -696,13 +744,13 @@ pyrepl = ">=0.8.2"
 
 [[package]]
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+version = "2.19.1"
 description = "Fastest Python implementation of JSON schema"
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 python-versions = "*"
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 [package.extras]
@@ -710,59 +758,59 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
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 name = "fonttools"
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 description = "Tools to manipulate font files"
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 python-versions = ">=3.8"
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 test = ["objgraph", "psutil"]
 
 [[package]]
 name = "hypothesis"
-version = "6.88.4"
+version = "6.96.1"
 description = "A library for property-based testing"
 optional = false
 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
-attrs = ">=19.2.0"
+attrs = ">=22.2.0"
 exceptiongroup = {version = ">=1.0.0", markers = "python_version < \"3.11\""}
 sortedcontainers = ">=2.1.0,<3.0.0"
 
 [package.extras]
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+all = ["backports.zoneinfo (>=0.2.1)", "black (>=19.10b0)", "click (>=7.0)", "django (>=3.2)", "dpcontracts (>=0.4)", "lark (>=0.10.1)", "libcst (>=0.3.16)", "numpy (>=1.17.3)", "pandas (>=1.1)", "pytest (>=4.6)", "python-dateutil (>=1.4)", "pytz (>=2014.1)", "redis (>=3.0.0)", "rich (>=9.0.0)", "tzdata (>=2023.4)"]
 cli = ["black (>=19.10b0)", "click (>=7.0)", "rich (>=9.0.0)"]
 codemods = ["libcst (>=0.3.16)"]
 dateutil = ["python-dateutil (>=1.4)"]
@@ -873,17 +922,17 @@ pandas = ["pandas (>=1.1)"]
 pytest = ["pytest (>=4.6)"]
 pytz = ["pytz (>=2014.1)"]
 redis = ["redis (>=3.0.0)"]
-zoneinfo = ["backports.zoneinfo (>=0.2.1)", "tzdata (>=2023.3)"]
+zoneinfo = ["backports.zoneinfo (>=0.2.1)", "tzdata (>=2023.4)"]
 
 [[package]]
 name = "idna"
-version = "3.4"
+version = "3.6"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.5"
 files = [
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-    {file = "idna-3.4.tar.gz", hash = "sha256:814f528e8dead7d329833b91c5faa87d60bf71824cd12a7530b5526063d02cb4"},
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+    {file = "idna-3.6.tar.gz", hash = "sha256:9ecdbbd083b06798ae1e86adcbfe8ab1479cf864e4ee30fe4e46a003d12491ca"},
 ]
 
 [[package]]
@@ -899,20 +948,20 @@ files = [
 
 [[package]]
 name = "importlib-metadata"
-version = "6.8.0"
+version = "7.0.1"
 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "importlib_metadata-7.0.1.tar.gz", hash = "sha256:f238736bb06590ae52ac1fab06a3a9ef1d8dce2b7a35b5ab329371d6c8f5d2cc"},
 ]
 
 [package.dependencies]
 zipp = ">=0.5"
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (<7.2.5)", "sphinx (>=3.5)", "sphinx-lint"]
 perf = ["ipython"]
 testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
@@ -945,6 +994,39 @@ files = [
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 ]
 
+[[package]]
+name = "ipykernel"
+version = "6.29.0"
+description = "IPython Kernel for Jupyter"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "ipykernel-6.29.0.tar.gz", hash = "sha256:b5dd3013cab7b330df712891c96cd1ab868c27a7159e606f762015e9bf8ceb3f"},
+]
+
+[package.dependencies]
+appnope = {version = "*", markers = "platform_system == \"Darwin\""}
+comm = ">=0.1.1"
+debugpy = ">=1.6.5"
+ipython = ">=7.23.1"
+jupyter-client = ">=6.1.12"
+jupyter-core = ">=4.12,<5.0.dev0 || >=5.1.dev0"
+matplotlib-inline = ">=0.1"
+nest-asyncio = "*"
+packaging = "*"
+psutil = "*"
+pyzmq = ">=24"
+tornado = ">=6.1"
+traitlets = ">=5.4.0"
+
+[package.extras]
+cov = ["coverage[toml]", "curio", "matplotlib", "pytest-cov", "trio"]
+docs = ["myst-parser", "pydata-sphinx-theme", "sphinx", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling", "trio"]
+pyqt5 = ["pyqt5"]
+pyside6 = ["pyside6"]
+test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio (==0.23.2)", "pytest-cov", "pytest-timeout"]
+
 [[package]]
 name = "ipython"
 version = "8.12.3"
@@ -986,20 +1068,17 @@ test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.21)", "pa
 
 [[package]]
 name = "isort"
-version = "5.12.0"
+version = "5.13.2"
 description = "A Python utility / library to sort Python imports."
 optional = false
 python-versions = ">=3.8.0"
 files = [
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-plugins = ["setuptools"]
-requirements-deprecated-finder = ["pip-api", "pipreqs"]
+colors = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "jedi"
@@ -1039,13 +1118,13 @@ i18n = ["Babel (>=2.7)"]
 
 [[package]]
 name = "jsonschema"
-version = "4.19.2"
+version = "4.21.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1062,18 +1141,18 @@ format-nongpl = ["fqdn", "idna", "isoduration", "jsonpointer (>1.13)", "rfc3339-
 
 [[package]]
 name = "jsonschema-specifications"
-version = "2023.7.1"
+version = "2023.12.1"
 description = "The JSON Schema meta-schemas and vocabularies, exposed as a Registry"
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 python-versions = ">=3.8"
 files = [
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 [package.dependencies]
 importlib-resources = {version = ">=1.4.0", markers = "python_version < \"3.9\""}
-referencing = ">=0.28.0"
+referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter-client"
@@ -1100,13 +1179,13 @@ test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pyt
 
 [[package]]
 name = "jupyter-core"
-version = "5.5.0"
+version = "5.7.1"
 description = "Jupyter core package. A base package on which Jupyter projects rely."
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 ]
 
 [package.dependencies]
@@ -1120,13 +1199,13 @@ test = ["ipykernel", "pre-commit", "pytest", "pytest-cov", "pytest-timeout"]
 
 [[package]]
 name = "jupyterlab-pygments"
-version = "0.2.2"
+version = "0.3.0"
 description = "Pygments theme using JupyterLab CSS variables"
 optional = false
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 ]
 
 [[package]]
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 [package.dependencies]
@@ -1534,7 +1605,6 @@ packaging = ">=20.0"
 pillow = ">=6.2.0"
 pyparsing = ">=2.3.1"
 python-dateutil = ">=2.7"
-setuptools_scm = ">=7"
 
 [[package]]
 name = "matplotlib-inline"
@@ -1596,13 +1666,13 @@ test = ["flaky", "ipykernel (>=6.19.3)", "ipython", "ipywidgets", "nbconvert (>=
 
 [[package]]
 name = "nbconvert"
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+version = "7.14.2"
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 python-versions = ">=3.8"
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 [package.dependencies]
@@ -1629,7 +1699,7 @@ docs = ["ipykernel", "ipython", "myst-parser", "nbsphinx (>=0.2.12)", "pydata-sp
 qtpdf = ["nbconvert[qtpng]"]
 qtpng = ["pyqtwebengine (>=5.15)"]
 serve = ["tornado (>=6.1)"]
-test = ["flaky", "ipykernel", "ipywidgets (>=7)", "pytest"]
+test = ["flaky", "ipykernel", "ipywidgets (>=7.5)", "pytest"]
 webpdf = ["playwright"]
 
 [[package]]
@@ -1672,6 +1742,17 @@ nbformat = "*"
 sphinx = ">=1.8"
 traitlets = ">=5"
 
+[[package]]
+name = "nest-asyncio"
+version = "1.5.9"
+description = "Patch asyncio to allow nested event loops"
+optional = false
+python-versions = ">=3.5"
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 version = "0.57.1"
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 [[package]]
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+version = "1.5.1"
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 [[package]]
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 [package.extras]
 docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
+fpx = ["olefile"]
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 tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
+typing = ["typing-extensions"]
+xmp = ["defusedxml"]
 
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 [package.dependencies]
@@ -2029,13 +2130,13 @@ files = [
 
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 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
 optional = false
-python-versions = ">=3.7"
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@@ -2059,18 +2160,46 @@ testing = ["pytest", "pytest-benchmark"]
 
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 python-versions = ">=3.7.0"
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 [package.dependencies]
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+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
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+
+[package.extras]
+test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
+
 [[package]]
 name = "ptyprocess"
 version = "0.7.0"
@@ -2143,17 +2272,18 @@ files = [
 
 [[package]]
 name = "pygments"
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 description = "Pygments is a syntax highlighting package written in Python."
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 python-versions = ">=3.7"
 files = [
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 [package.extras]
 plugins = ["importlib-metadata"]
+windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
 name = "pylint"
@@ -2220,13 +2350,13 @@ files = [
 
 [[package]]
 name = "pytest"
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+version = "7.4.4"
 description = "pytest: simple powerful testing with Python"
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 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
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 [package.dependencies]
@@ -3030,7 +3112,7 @@ greenlet = {version = "!=0.4.17", markers = "python_version >= \"3\" and (platfo
 
 [package.extras]
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-aiosqlite = ["aiosqlite", "greenlet (!=0.4.17)", "typing-extensions (!=3.10.0.1)"]
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 mariadb-connector = ["mariadb (>=1.0.1,!=1.1.2)"]
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 mysql-connector = ["mysql-connector-python"]
-oracle = ["cx-oracle (>=7)", "cx-oracle (>=7,<8)"]
+oracle = ["cx_oracle (>=7)", "cx_oracle (>=7,<8)"]
 postgresql = ["psycopg2 (>=2.7)"]
 postgresql-asyncpg = ["asyncpg", "greenlet (!=0.4.17)"]
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 postgresql-psycopg2cffi = ["psycopg2cffi"]
 pymysql = ["pymysql", "pymysql (<1)"]
-sqlcipher = ["sqlcipher3-binary"]
+sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "stack-data"
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+    {file = "tornado-6.4-cp38-abi3-macosx_10_9_x86_64.whl", hash = "sha256:27787de946a9cffd63ce5814c33f734c627a87072ec7eed71f7fc4417bb16263"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:f7894c581ecdcf91666a0912f18ce5e757213999e183ebfc2c3fdbf4d5bd764e"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:e43bc2e5370a6a8e413e1e1cd0c91bedc5bd62a74a532371042a18ef19e10579"},
+    {file = "tornado-6.4-cp38-abi3-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:f0251554cdd50b4b44362f73ad5ba7126fc5b2c2895cc62b14a1c2d7ea32f212"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_aarch64.whl", hash = "sha256:fd03192e287fbd0899dd8f81c6fb9cbbc69194d2074b38f384cb6fa72b80e9c2"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_i686.whl", hash = "sha256:88b84956273fbd73420e6d4b8d5ccbe913c65d31351b4c004ae362eba06e1f78"},
+    {file = "tornado-6.4-cp38-abi3-musllinux_1_1_x86_64.whl", hash = "sha256:71ddfc23a0e03ef2df1c1397d859868d158c8276a0603b96cf86892bff58149f"},
+    {file = "tornado-6.4-cp38-abi3-win32.whl", hash = "sha256:6f8a6c77900f5ae93d8b4ae1196472d0ccc2775cc1dfdc9e7727889145c45052"},
+    {file = "tornado-6.4-cp38-abi3-win_amd64.whl", hash = "sha256:10aeaa8006333433da48dec9fe417877f8bcc21f48dda8d661ae79da357b2a63"},
+    {file = "tornado-6.4.tar.gz", hash = "sha256:72291fa6e6bc84e626589f1c29d90a5a6d593ef5ae68052ee2ef000dfd273dee"},
 ]
 
 [[package]]
 name = "traitlets"
-version = "5.13.0"
+version = "5.14.1"
 description = "Traitlets Python configuration system"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "traitlets-5.13.0-py3-none-any.whl", hash = "sha256:baf991e61542da48fe8aef8b779a9ea0aa38d8a54166ee250d5af5ecf4486619"},
-    {file = "traitlets-5.13.0.tar.gz", hash = "sha256:9b232b9430c8f57288c1024b34a8f0251ddcc47268927367a0dd3eeaca40deb5"},
+    {file = "traitlets-5.14.1-py3-none-any.whl", hash = "sha256:2e5a030e6eff91737c643231bfcf04a65b0132078dad75e4936700b213652e74"},
+    {file = "traitlets-5.14.1.tar.gz", hash = "sha256:8585105b371a04b8316a43d5ce29c098575c2e477850b62b848b964f1444527e"},
 ]
 
 [package.extras]
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
-test = ["argcomplete (>=3.0.3)", "mypy (>=1.6.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
+test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<7.5)", "pytest-mock", "pytest-mypy-testing"]
 
 [[package]]
 name = "typing-extensions"
-version = "4.8.0"
+version = "4.9.0"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "typing_extensions-4.8.0-py3-none-any.whl", hash = "sha256:8f92fc8806f9a6b641eaa5318da32b44d401efaac0f6678c9bc448ba3605faa0"},
-    {file = "typing_extensions-4.8.0.tar.gz", hash = "sha256:df8e4339e9cb77357558cbdbceca33c303714cf861d1eef15e1070055ae8b7ef"},
+    {file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
+    {file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
 ]
 
 [[package]]
@@ -3172,13 +3254,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "wcwidth"
-version = "0.2.10"
+version = "0.2.13"
 description = "Measures the displayed width of unicode strings in a terminal"
 optional = false
 python-versions = "*"
 files = [
-    {file = "wcwidth-0.2.10-py2.py3-none-any.whl", hash = "sha256:aec5179002dd0f0d40c456026e74a729661c9d468e1ed64405e3a6c2176ca36f"},
-    {file = "wcwidth-0.2.10.tar.gz", hash = "sha256:390c7454101092a6a5e43baad8f83de615463af459201709556b6e4b1c861f97"},
+    {file = "wcwidth-0.2.13-py2.py3-none-any.whl", hash = "sha256:3da69048e4540d84af32131829ff948f1e022c1c6bdb8d6102117aac784f6859"},
+    {file = "wcwidth-0.2.13.tar.gz", hash = "sha256:72ea0c06399eb286d978fdedb6923a9eb47e1c486ce63e9b4e64fc18303972b5"},
 ]
 
 [[package]]
@@ -3310,4 +3392,4 @@ mark = ["banana-hep", "sqlalchemy"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8,<3.12"
-content-hash = "ad042a74a077766ce436ee2ab3cfbbaa90e57c76071c6b3ea923c7fbbd555bdb"
+content-hash = "bcc0109269c0c850ddc515f83d30306c384d606adaf219f33e1cbaeb1ae68fa5"
diff --git a/pyproject.toml b/pyproject.toml
index c9b996300..e8d7ac505 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -76,6 +76,7 @@ recommonmark = "^0.7.1"
 sphinxcontrib-bibtex = "^2.3.0"
 sphinxcontrib-details-directive = "^0.1.0"
 nbsphinx = "^0.8.6"
+ipykernel = "^6.13.0"
 
 [tool.poetry.extras]
 mark = ["banana-hep", "sqlalchemy"]
@@ -104,6 +105,7 @@ docs-view = { "shell" = "cd docs; make view" }
 docs-server = { "shell" = "cd docs; make server" }
 docs-clean = { "shell" = "cd docs; make clean" }
 docs-cleanall = { "shell" = "cd docs; make cleanall" }
+docs-install-nb = { "shell" = "python -m ipykernel install --user --name=$(basename $(poetry env info -p))" }
 
 [tool.poetry-dynamic-versioning]
 enable = true

From 1b8cad863e04f80847bd832eb19f6bb42d8da885 Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Fri, 19 Jan 2024 12:42:37 +0200
Subject: [PATCH 04/18] Fix ref->cite

---
 src/yadism/coefficient_functions/light/n3lo/common.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/yadism/coefficient_functions/light/n3lo/common.py b/src/yadism/coefficient_functions/light/n3lo/common.py
index 21c3314e6..fc2e30bd2 100644
--- a/src/yadism/coefficient_functions/light/n3lo/common.py
+++ b/src/yadism/coefficient_functions/light/n3lo/common.py
@@ -1,4 +1,4 @@
-"""Common factors see :ref:`Larin:1996wd` (Table 2)"""
+"""Common factors see :cite:`Larin:1996wd` (Table 2)."""
 import numba as nb
 import numpy as np
 
@@ -10,7 +10,7 @@
 
 
 def nc_color_factor(coupling_constants, nf, channel, skip_heavylight):
-    """Returns the |N3LO| color factor.
+    """Compute a |N3LO| color factor.
 
     Parameters
     ----------
@@ -49,7 +49,7 @@ def nc_color_factor(coupling_constants, nf, channel, skip_heavylight):
 
 @nb.njit("f8(f8[:])", cache=True)
 def fl(nc_weights):
-    """:math:`fl_{11}` Non Singlet as defined in :ref:`Larin:1996wd` (Table 2) and generalized for |NC|"""
+    """:math:`fl_{11}` Non Singlet as defined in :cite:`Larin:1996wd` (Table 2) and generalized for |NC|."""
     # fl = [2.0, 0.5, 0.0, 0.5, 0.2, 0.5]
     avg = np.mean(nc_weights)
     return 3 * avg
@@ -57,7 +57,7 @@ def fl(nc_weights):
 
 @nb.njit("f8(f8[:])", cache=True)
 def fls(nc_weights):
-    """:math:`fl_{11}` pure Singlet as defined in :ref:`Larin:1996wd` (Table 2) and generalized for |NC|"""
+    """:math:`fl_{11}` pure Singlet as defined in :cite:`Larin:1996wd` (Table 2) and generalized for |NC|."""
     avg_2 = np.mean(nc_weights) ** 2
     sum_w2 = np.mean(nc_weights**2)
     # fls = [1.0, 0.1, 0.0, 0.1, 0.01818181818, 0.1]
@@ -66,5 +66,5 @@ def fls(nc_weights):
 
 @nb.njit("f8(f8[:])", cache=True)
 def flg(nc_weights):
-    """:math:`fl_{11}^g` pure Singlet as defined in :ref:`Larin:1996wd` (Table 2) and generalized for |NC|"""
+    """:math:`fl_{11}^g` pure Singlet as defined in :cite:`Larin:1996wd` (Table 2) and generalized for |NC|."""
     return fls(nc_weights)

From 9b38b7820d7487365bf33f1cf94a6a1e2f3b5d69 Mon Sep 17 00:00:00 2001
From: giacomomagni 
Date: Fri, 19 Jan 2024 11:59:50 +0100
Subject: [PATCH 05/18] start cleaning docs: dev-tool section

---
 docs/source/dev-tools/bench-coverage.csv | 14 +++++------
 docs/source/dev-tools/bench-fns.csv      |  2 +-
 docs/source/dev-tools/benchmarks.rst     | 21 ++++++++++++++--
 docs/source/dev-tools/metrics.rst        | 31 ------------------------
 docs/source/implementation/runner.rst    |  4 ---
 docs/source/index.rst                    |  3 +--
 docs/source/overview/features.rst        |  2 +-
 docs/source/shared/abbreviations.rst     |  3 +++
 8 files changed, 32 insertions(+), 48 deletions(-)
 delete mode 100644 docs/source/dev-tools/metrics.rst

diff --git a/docs/source/dev-tools/bench-coverage.csv b/docs/source/dev-tools/bench-coverage.csv
index f79b58f2f..1ca89586e 100644
--- a/docs/source/dev-tools/bench-coverage.csv
+++ b/docs/source/dev-tools/bench-coverage.csv
@@ -1,7 +1,7 @@
-"feature \\ reference"    APFEL                 QCDNUM                  xspace-bench
-projectiles               |T|                   ""                      |T|
-EM                        |T|                   |T|                     |T|
-NC                        |T|                   |T|                     |T|
-CC                        |T|                   ""                      |T|
-scale-variatons           |T|                   |T|                     ""
-target-mass-corrections   |T|                   ""                      ""
+"feature \\ reference"    APFEL                 QCDNUM                  xspace-bench                  APFEL++
+projectiles               |T|                   ""                      |T|                           |T|
+EM                        |T|                   |T|                     |T|                           |T|
+NC                        |T|                   |T|                     |T|                           |T|
+CC                        |T|                   ""                      |T|                           |T|
+scale-variatons           |T|                   |T|                     ""                            |T|
+target-mass-corrections   |T|                   ""                      ""                            |T|
diff --git a/docs/source/dev-tools/bench-fns.csv b/docs/source/dev-tools/bench-fns.csv
index c2c3e9eef..d52826aa8 100644
--- a/docs/source/dev-tools/bench-fns.csv
+++ b/docs/source/dev-tools/bench-fns.csv
@@ -1,4 +1,4 @@
 "|FNS| \\ reference" APFEL                QCDNUM                    xspace-bench
 |FFNS|               |T|                  |T|                       "|T| [#f1]_"
 |ZM-VFNS|            |T|                  |T|                       |T|
-FONLL                "|T| [#f2]_"         ""                        "|T| [#f2]_"
+|FFNS0|                |T|                  ""                        |T|
diff --git a/docs/source/dev-tools/benchmarks.rst b/docs/source/dev-tools/benchmarks.rst
index 4bdd1549a..09706a53d 100644
--- a/docs/source/dev-tools/benchmarks.rst
+++ b/docs/source/dev-tools/benchmarks.rst
@@ -30,7 +30,6 @@ also incoming projectiles, different type of currents, SV and TMC.
    :align: center
 
 .. [#f1] Only for NfFF=3
-.. [#f2] Only for charm threshold (FFNS3 to FFNS4 interpolation)
 
 .. csv-table:: Banchmarks coverage
    :file: ./bench-coverage.csv
@@ -131,5 +130,23 @@ In |xspace-bench| |SF| are defined as follows:
 
 Given these definitions, benchmarks with `yadism` are possible only in the region
 :math:`m^2_{charm} < Q^2 < m^2_{bottom}` selecting  either |ZM-VFNS| with :math:`F_X^{total}`
-or |FFNS| with NfFF=3 and FONLL with NfFF=4.
+or |FFNS| with NfFF=3.
 FONLL is implemented in the so called `scheme A` with and without damping factor.
+
+APFEL++
+-------
+
+
+|APFEL++| is a C++ rewriting of the Fortran 77 evolution code |APFEL|. However, |APFEL++| is based on a completely new code design and 
+guarantees a better performance along with a more optimal memory management. 
+|APFEL++| is suitable for a wide range of tasks: from the solution of the DGLAP evolution equations to the computation of DIS
+and single-inclusive-annihilation cross sections. 
+
+|APFEL++| is also currently interfaced to PARTONS, a software dedicated to the phenomenology of Generalised Parton Distributions (GPDs) and TMDs, 
+and to xFitter.
+
+
+SF in APFEL++
+~~~~~~~~~~~~~
+
+The |APFEL++| definitions follows the one of |APFEL|
diff --git a/docs/source/dev-tools/metrics.rst b/docs/source/dev-tools/metrics.rst
deleted file mode 100644
index 1732eb60b..000000000
--- a/docs/source/dev-tools/metrics.rst
+++ /dev/null
@@ -1,31 +0,0 @@
-Insights & Metrics
-==================
-
-CodeCov
--------
-
-.. image:: https://codecov.io/gh/N3PDF/yadism/branch/master/graph/badge.svg?token=qgCFyUQ6oG
-   :target: https://codecov.io/gh/N3PDF/yadism
-   :alt: CodeCov-badge
-
-Powered by `pytest` coverage reports (in our use case), just display a nice
-interface to navigate these reports and compare code coverage across multiple
-commits/branches.
-
-Also able to merge different code coverage reports, even coming from different
-tools.
-
-.. image:: https://codecov.io/gh/N3PDF/yadism/branch/master/graphs/sunburst.svg
-   :align: center
-
-CodeFactor
-----------
-
-.. image:: https://www.codefactor.io/repository/github/n3pdf/yadism/badge
-   :target: https://www.codefactor.io/repository/github/n3pdf/yadism
-   :alt: CodeFactor-badge
-
-Powered by `pylint` static analysis reports (in our use case).
-
-Also able to merge different code coverage reports, even coming from different
-tools.
diff --git a/docs/source/implementation/runner.rst b/docs/source/implementation/runner.rst
index ff0d8ca19..c02c74ab0 100644
--- a/docs/source/implementation/runner.rst
+++ b/docs/source/implementation/runner.rst
@@ -59,10 +59,6 @@ Some **handlers objects** are used to dispatch some isolated services. They are
 mostly not defined internally in :mod:`yadism` package, but mainly imported from
 :mod:`eko`.
 
-Another common trait that characterize these handlers is the presence of a
-method :func:`from_dict`, with which the object can be created loading the
-required options directly from a suitable dictionary (that in a :class:`Runner`
-object is always either `theory` or `observable` dictionary).
 
 Interpolator Dispatcher
 ~~~~~~~~~~~~~~~~~~~~~~~
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 2156aa7db..a22504f45 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -84,9 +84,8 @@ In particular:
    :caption: Dev Tools
    :hidden:
 
-   dev-tools/tests.rst
+   dev-tools/benchmarks.rst
    dev-tools/yadmark.rst
-   dev-tools/metrics.rst
    dev-tools/code-todos.rst
 
 .. toctree::
diff --git a/docs/source/overview/features.rst b/docs/source/overview/features.rst
index a6ffce436..d8671abd7 100644
--- a/docs/source/overview/features.rst
+++ b/docs/source/overview/features.rst
@@ -28,7 +28,7 @@ according to their :ref:`heavyness ` (e.g.
 
 Moreover the following features are all available:
 
-1. :doc:`flavor number schemes <../theory/fns>`: |FFNS|, |ZM-VFNS|, |FONLL|
+1. :doc:`flavor number schemes <../theory/fns>`: |FFNS|, |ZM-VFNS|, |FFNS0|
 2. :doc:`scale variations <../theory/scale-variations>`: independent variations
    of factorization scale :math:`\mu_F` and renormalization scale :math:`\mu_R`
 3. :ref:`target mass corrections `
diff --git a/docs/source/shared/abbreviations.rst b/docs/source/shared/abbreviations.rst
index 2271fb666..be89c15e5 100644
--- a/docs/source/shared/abbreviations.rst
+++ b/docs/source/shared/abbreviations.rst
@@ -93,6 +93,9 @@
 .. |FFNS| replace::
    :abbr:`FFNS (Fixed Flavor Number Scheme)`
 
+.. |FFNS0| replace::
+   :abbr:`FFNS0 (Asymptotic Fixed Flavor Number Scheme)`
+
 .. |VFNS| replace::
    :abbr:`VFNS (Variable Flavor Number Scheme)`
 

From 652ceec7e679aaa999e9afb47a636fbac73b74d9 Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Fri, 19 Jan 2024 14:34:08 +0200
Subject: [PATCH 06/18] Replace FFNS0->FFN0

---
 docs/source/dev-tools/bench-fns.csv             | 2 +-
 docs/source/overview/features.rst               | 2 +-
 docs/source/shared/abbreviations.rst            | 4 ++--
 src/yadmark/benchmark/external/apfelpy_utils.py | 9 ++++-----
 4 files changed, 8 insertions(+), 9 deletions(-)

diff --git a/docs/source/dev-tools/bench-fns.csv b/docs/source/dev-tools/bench-fns.csv
index d52826aa8..9187f212b 100644
--- a/docs/source/dev-tools/bench-fns.csv
+++ b/docs/source/dev-tools/bench-fns.csv
@@ -1,4 +1,4 @@
 "|FNS| \\ reference" APFEL                QCDNUM                    xspace-bench
 |FFNS|               |T|                  |T|                       "|T| [#f1]_"
 |ZM-VFNS|            |T|                  |T|                       |T|
-|FFNS0|                |T|                  ""                        |T|
+|FFN0|                |T|                  ""                        |T|
diff --git a/docs/source/overview/features.rst b/docs/source/overview/features.rst
index d8671abd7..569bd320a 100644
--- a/docs/source/overview/features.rst
+++ b/docs/source/overview/features.rst
@@ -28,7 +28,7 @@ according to their :ref:`heavyness ` (e.g.
 
 Moreover the following features are all available:
 
-1. :doc:`flavor number schemes <../theory/fns>`: |FFNS|, |ZM-VFNS|, |FFNS0|
+1. :doc:`flavor number schemes <../theory/fns>`: |FFNS|, |ZM-VFNS|, |FFN0|
 2. :doc:`scale variations <../theory/scale-variations>`: independent variations
    of factorization scale :math:`\mu_F` and renormalization scale :math:`\mu_R`
 3. :ref:`target mass corrections `
diff --git a/docs/source/shared/abbreviations.rst b/docs/source/shared/abbreviations.rst
index be89c15e5..3afcf2af1 100644
--- a/docs/source/shared/abbreviations.rst
+++ b/docs/source/shared/abbreviations.rst
@@ -93,8 +93,8 @@
 .. |FFNS| replace::
    :abbr:`FFNS (Fixed Flavor Number Scheme)`
 
-.. |FFNS0| replace::
-   :abbr:`FFNS0 (Asymptotic Fixed Flavor Number Scheme)`
+.. |FFN0| replace::
+   :abbr:`FFN0 (Asymptotic Fixed Flavor Number Scheme)`
 
 .. |VFNS| replace::
    :abbr:`VFNS (Variable Flavor Number Scheme)`
diff --git a/src/yadmark/benchmark/external/apfelpy_utils.py b/src/yadmark/benchmark/external/apfelpy_utils.py
index 43200b93a..b6f8c5fda 100644
--- a/src/yadmark/benchmark/external/apfelpy_utils.py
+++ b/src/yadmark/benchmark/external/apfelpy_utils.py
@@ -62,7 +62,7 @@ def map_apfelpy_sf(init, observables, fns):
         "F2": init.InitializeF2NCObjectsMassive,
         "FL": init.InitializeFLNCObjectsMassive,
     }
-    MAP_FFNS0_NC = {
+    MAP_FFN0_NC = {
         "F2": init.InitializeF2NCObjectsMassiveZero,
         "FL": init.InitializeFLNCObjectsMassiveZero,
     }
@@ -76,8 +76,8 @@ def map_apfelpy_sf(init, observables, fns):
         return MAP_ZM_NC
     if fns == "FFNS":
         return MAP_FFNS_NC
-    if fns == "FFNS0":
-        return MAP_FFNS0_NC
+    if fns == "FFN0":
+        return MAP_FFN0_NC
 
 
 def couplings(ap, pids, proc_type, obs_name):
@@ -100,7 +100,6 @@ def couplings(ap, pids, proc_type, obs_name):
 
     """
 
-    # Effective charges
     def _fBq(Q):
         if proc_type == "EM":
             # For Q=0 we only have electric charges
@@ -300,7 +299,7 @@ def compute_apfelpy_data(theory, observables, pdf):
 
     # Setting the theory
     fns = theory["FNS"]
-    if fns not in ["ZM-VFNS", "FFNS", "FFNS0"]:
+    if fns not in ["ZM-VFNS", "FFNS", "FFN0"]:
         raise ValueError(f"APFEL++ does not contain {fns}.")
 
     # Perturbative Order

From 60e28dd7b8a872f770c5020adba68ea57306ddae Mon Sep 17 00:00:00 2001
From: giacomomagni 
Date: Fri, 19 Jan 2024 14:46:14 +0100
Subject: [PATCH 07/18] docs: continue cleaning

---
 docs/source/dev-tools/bench-fns.csv     |  8 +++----
 docs/source/implementation/ESF.rst      |  2 +-
 docs/source/implementation/input.rst    | 29 -------------------------
 docs/source/theory/scale-variations.rst |  7 ------
 src/yadism/input/__init__.py            | 11 ----------
 5 files changed, 5 insertions(+), 52 deletions(-)
 delete mode 100644 docs/source/implementation/input.rst

diff --git a/docs/source/dev-tools/bench-fns.csv b/docs/source/dev-tools/bench-fns.csv
index 9187f212b..f598e2508 100644
--- a/docs/source/dev-tools/bench-fns.csv
+++ b/docs/source/dev-tools/bench-fns.csv
@@ -1,4 +1,4 @@
-"|FNS| \\ reference" APFEL                QCDNUM                    xspace-bench
-|FFNS|               |T|                  |T|                       "|T| [#f1]_"
-|ZM-VFNS|            |T|                  |T|                       |T|
-|FFN0|                |T|                  ""                        |T|
+"|FNS| \\ reference" APFEL                QCDNUM                    xspace-bench                  APFEL++
+|FFNS|               |T|                  |T|                       "|T| [#f1]_"                  |T|
+|ZM-VFNS|            |T|                  |T|                       |T|                           |T|
+|FFN0|                |T|                  ""                        |T|                         |T|
diff --git a/docs/source/implementation/ESF.rst b/docs/source/implementation/ESF.rst
index 3559e8d6c..4d87596bd 100644
--- a/docs/source/implementation/ESF.rst
+++ b/docs/source/implementation/ESF.rst
@@ -20,7 +20,7 @@ belong to a :class:`StructureFunction` instance of the respective kind.
 
 The kinds are defined by choosing one option for each of the following classes:
 
-- ``F2`` or ``FL``
+- ``F2``, ``FL``, ``F3``, ``g1``, `gL``, `g4``
 - ``light``, ``charm``, ``bottom``, ``top``, or ``total``
 
 Sometimes an instance of a different kind it is needed to complete the
diff --git a/docs/source/implementation/input.rst b/docs/source/implementation/input.rst
deleted file mode 100644
index f78306e15..000000000
--- a/docs/source/implementation/input.rst
+++ /dev/null
@@ -1,29 +0,0 @@
-Input layer
-===========
-
-The input layer parse and validate the user input for launching the actual run,
-enforcing:
-
-- single field constraints
-- multiple fields constraints (*cross-constraints*)
-
-This layer can be used directly, so it is principle independent from anything
-else in `yadism`, but it has been developed to be used mainly inside a `Runner`
-instance.
-
-Example
--------
-
-Theory runcard
-~~~~~~~~~~~~~~
-
-.. todo::
-
-   - provide an example of a theory card
-
-Observables runcard
-~~~~~~~~~~~~~~~~~~~
-
-.. todo::
-
-   - provide at least a couple of examples of observables' cards
diff --git a/docs/source/theory/scale-variations.rst b/docs/source/theory/scale-variations.rst
index 88ff09325..eb017be1c 100644
--- a/docs/source/theory/scale-variations.rst
+++ b/docs/source/theory/scale-variations.rst
@@ -146,10 +146,3 @@ Procedures
 - **scheme C**: varying the scales in the context of |PDF| determination only in
   the coefficient functions corresponds to scheme C in
   :cite:`AbdulKhalek:2019ihb`.
-
-Sector Isolated
----------------
-
-.. todo::
-
-   Independent singlet/non-singlet scale variations
diff --git a/src/yadism/input/__init__.py b/src/yadism/input/__init__.py
index e774827fd..5267fefea 100644
--- a/src/yadism/input/__init__.py
+++ b/src/yadism/input/__init__.py
@@ -1,15 +1,4 @@
 """
-Goal
-----
-
-These subpackage has the main goal of parsing and validate user input, in
-particular the following three operations are performed:
-
-#. **constraints**: constraints on single fields are enforced, raising an error
-    for each violation
-#. **cross-constraints**: constraints involving multiple fields are enforced,
-    raising an error for each violation
-
 Note
 ----
 

From c1df43cd7807826375c3c9f1cf1aa6062fddeefd Mon Sep 17 00:00:00 2001
From: giacomomagni 
Date: Fri, 19 Jan 2024 14:52:42 +0100
Subject: [PATCH 08/18] reorder the theory card

---
 docs/source/overview/tutorials.ipynb | 41 ++++++++++++++++++----------
 1 file changed, 27 insertions(+), 14 deletions(-)

diff --git a/docs/source/overview/tutorials.ipynb b/docs/source/overview/tutorials.ipynb
index e8fc4bf31..9ce588b46 100644
--- a/docs/source/overview/tutorials.ipynb
+++ b/docs/source/overview/tutorials.ipynb
@@ -128,39 +128,52 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "id": "90df79a9-31cb-40db-ac95-0b88469c1723",
    "metadata": {},
    "outputs": [],
    "source": [
     "theory_card = {\n",
+    "    # QCD perturbative order\n",
+    "    \"PTO\": 2,  # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n",
+    "   \n",
+    "    # SM parameters and masses\n",
     "    \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\",  # CKM matrix elements\n",
-    "    \"FNS\": \"FFNS\",  # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n",
     "    \"GF\": 1.1663787e-05,  # [GeV^-2] Fermi coupling constant\n",
-    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed\n",
     "    \"MP\": 0.938,  # [GeV] proton mass\n",
     "    \"MW\": 80.398,  # [GeV] W boson mass\n",
     "    \"MZ\": 91.1876,  # [GeV] Z boson mass\n",
+    "    \"alphaqed\": 0.007496252,  # alpha_em value\n",
+    "    \"kcThr\": 1.0,  # ratio of the charm matching scale over the charm mass\n",
+    "    \"kbThr\": 1.0,  # ratio of the bottom matching scale over the bottom mass\n",
+    "    \"ktThr\": 1.0,  # ratio of the top matching scale over the top mass\n",
+    "    \"mc\": 1.51,  # [GeV] charm mass\n",
+    "    \"mb\": 4.92,  # [GeV] bottom mass\n",
+    "    \"mt\": 172.5,  # [GeV] top mass\n",
+    "    \n",
+    "    # Flavor number scheme settings\n",
+    "    \"FNS\": \"FFNS\",  # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n",
     "    \"NfFF\": 4,  # (fixed) number of running flavors, only for FFNS or FFN0 schemes\n",
-    "    \"PTO\": 2,  # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n",
     "    \"Q0\": 1.65,  # [GeV] reference scale for the flavor patch determination\n",
     "    \"nf0\": 4,  # number of active flavors at the Q0 reference scale\n",
+    "    \n",
+    "    # Alphas settings and boundary conditions\n",
     "    \"Qref\": 91.2,  # [GeV] reference scale for the alphas value\n",
     "    \"nfref\": 5,  # number of active flavors at the reference scale Qref\n",
     "    \"alphas\": 0.118,  # alphas value at the reference scale\n",
-    "    \"TMC\": 1,  # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n",
+    "    \"MaxNfAs\": 5,  # maximum number of flavors in running of strong coupling\n",
+    "    \"QED\": 0,  # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n",
+    "    \n",
+    "    # Scale Variations \n",
     "    \"XIF\": 1.0,  # ratio of factorization scale over the hard scattering scale\n",
     "    \"XIR\": 1.0,  # ratio of renormalization scale over the hard scattering scale\n",
-    "    \"alphaqed\": 0.007496252,  # alpha_em value\n",
-    "    \"kcThr\": 1.0,  # ratio of the charm matching scale over the charm mass\n",
-    "    \"kbThr\": 1.0,  # ratio of the bottom matching scale over the bottom mass\n",
-    "    \"ktThr\": 1.0,  # ratio of the top matching scale over the top mass\n",
-    "    \"mc\": 1.51,  # [GeV] charm mass\n",
-    "    \"mb\": 4.92,  # [GeV] bottom mass\n",
-    "    \"mt\": 172.5,  # [GeV] top mass\n",
+    "    \n",
+    "    # Other settings\n",
+    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed \n",
+    "    \"TMC\": 1,  # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n",
     "    \"n3lo_cf_variation\": 0,  # N3LO coefficient functions variation: -1 = lower bound, 0 = central , 1 = upper bound\n",
-    "    \"QED\": 0,  # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n",
-    "    \"MaxNfAs\": 5,  # maximum number of flavors in running of strong coupling\n",
+    "    \n",
+    "    # Other EKO settings, not relevant for Yadism\n",
     "    \"HQ\": \"POLE\",  # heavy quark mass scheme (not yet implemented in yadism)\n",
     "    \"MaxNfPdf\": 5,  # maximum number of flavors in running of PDFs (ignored by yadism)\n",
     "    \"ModEv\": \"EXA\",  # evolution solver for PDFs (ignored by yadism)\n",

From a1ebe2f22fdeaa9cc95d95832e6a47632ba53658 Mon Sep 17 00:00:00 2001
From: giacomomagni 
Date: Fri, 19 Jan 2024 15:16:27 +0100
Subject: [PATCH 09/18] more work on docs implementation

---
 docs/source/implementation/kernels.rst   | 15 ++++++---------
 docs/source/implementation/structure.rst | 19 ++++++++-----------
 2 files changed, 14 insertions(+), 20 deletions(-)

diff --git a/docs/source/implementation/kernels.rst b/docs/source/implementation/kernels.rst
index fcc5ab308..9e7467aa2 100644
--- a/docs/source/implementation/kernels.rst
+++ b/docs/source/implementation/kernels.rst
@@ -16,8 +16,8 @@ The actual physical combination are not as many as flavors, indeed |QCD| is
 flavor blind (in the massless case, and the only difference in the massive case
 are the value of the masses themselves).
 
-In particular there are 3 relevant combinations, as described in
-:doc:`../theory/coeff-funcs`.
+In particular there are 3 relevant combinations, for polarized and 
+unpolarized |DIS| as described in :doc:`../theory/coeff-funcs`.
 
 .. todo::
 
@@ -37,11 +37,8 @@ In particular there are 3 relevant combinations, as described in
      (partons, operator, operator-error) by convolutions
 
 
-Rearrange Singlet & Non-singlet
--------------------------------
+Singlet & Non-singlet
+---------------------
 
-.. todo::
-
-   describe redefinition of the singlet -> pure singlet from Vogt notation
-
-   essentially include the already written note
+For the distinction about singlet and non-singlet coefficient function, 
+see :doc:`../theory/nonsinglet`.
\ No newline at end of file
diff --git a/docs/source/implementation/structure.rst b/docs/source/implementation/structure.rst
index 1b7f1fae3..162ff144b 100644
--- a/docs/source/implementation/structure.rst
+++ b/docs/source/implementation/structure.rst
@@ -29,12 +29,10 @@ Essentially the flow of an execution is the following:
 1. (**user** initiated) a :class:`~yadism.runner.Runner` is instantiated and it
    is passed the theory configuration, and the requested observables to compute
    (together with related configurations)
-2. a check is performed on the user input (by an
-   :class:`~yadism.input.inspector.Inspector`)
-3. the relevant global *service providers* are initialized and stored by the
+2. the relevant global *service providers* are initialized and stored by the
    :class:`~yadism.runner.Runner` (like the :math:`\alpha_s` evolution, or the
    interpolation dispatcher, or the couplings computer)
-4. the requested observables are scanned, and they are assigned to the
+3. the requested observables are scanned, and they are assigned to the
    respective :class:`~yadism.sf.StructureFunction` /
    :class:`~yadism.xs.CrossSection` (acting as manager and caching storage)
    according to their kind and heavyness (but multiple kinematics will belong to
@@ -42,17 +40,17 @@ Essentially the flow of an execution is the following:
    :class:`~yadism.xs.CrossSection`) each kinematic point will correspond to an instance of
    :class:`~yadism.esf.esf.EvaluatedStructureFunction` / :class:`~yadism.esf.exs.EvaluatedCrossSection`
 
-5. (**user** initiated) output is requested
-6. the request is propagated to the managers, and then to all the required
+4. (**user** initiated) output is requested
+5. the request is propagated to the managers, and then to all the required
    `ESF` objects
-7. the `ESF` issues a request to the
+6. the `ESF` issues a request to the
    :class:`~yadism.coefficient_functions.Combiner` for the relevant
    :class:`~yadism.coefficient_functions.kernels.Kernel`
-8. all the :class:`~yadism.coefficient_functions.kernels.Kernel` are numerically
+7. all the :class:`~yadism.coefficient_functions.kernels.Kernel` are numerically
    convoluted with the |PDF| interpolation polynomials
-9. all the results are collected in an :class:`~yadism.output.Output` object and
+8. all the results are collected in an :class:`~yadism.output.Output` object and
    returned to the user
-10. (**user** initiated) the :class:`~yadism.output.Output` object might be
+9. (**user** initiated) the :class:`~yadism.output.Output` object might be
     dumped on disk in one of the available formats
 
 Elements
@@ -62,7 +60,6 @@ Elements
    :maxdepth: 2
 
    runner
-   input
    kernels
    SF
    ESF

From f6c330ddd00735fe5371378f1f22522449a41c95 Mon Sep 17 00:00:00 2001
From: Radonirinaunimi 
Date: Mon, 22 Jan 2024 15:40:44 +0100
Subject: [PATCH 10/18] restructure tutorial to include comparison with data

---
 docs/source/index.rst                         |   2 +-
 docs/source/overview/tutorials.ipynb          | 909 ------------------
 .../overview/tutorials/compare_data.ipynb     | 585 +++++++++++
 .../overview/tutorials/getting_started.ipynb  | 679 +++++++++++++
 docs/source/overview/tutorials/tutorials.rst  |  16 +
 5 files changed, 1281 insertions(+), 910 deletions(-)
 delete mode 100644 docs/source/overview/tutorials.ipynb
 create mode 100644 docs/source/overview/tutorials/compare_data.ipynb
 create mode 100644 docs/source/overview/tutorials/getting_started.ipynb
 create mode 100644 docs/source/overview/tutorials/tutorials.rst

diff --git a/docs/source/index.rst b/docs/source/index.rst
index a22504f45..605c3b9b5 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -52,7 +52,7 @@ In particular:
    :hidden:
 
    overview/features.rst
-   Tutorials 
+   overview/tutorials/tutorials.rst
 
 .. toctree::
    :maxdepth: 1
diff --git a/docs/source/overview/tutorials.ipynb b/docs/source/overview/tutorials.ipynb
deleted file mode 100644
index 9ce588b46..000000000
--- a/docs/source/overview/tutorials.ipynb
+++ /dev/null
@@ -1,909 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "id": "nominated-inspection",
-   "metadata": {},
-   "source": [
-    "# Tutorials\n",
-    "\n",
-    "The following tutorial provides a brief introduction on some of the main features of `yadism`. This tutorial has three main objectives, namely to introduce the user on how to:\n",
-    "- prepare the observable and theory cards required for any `yadism` computation\n",
-    "- compute observables by convoluting `yadism` predictions to PDFs (Parton Distribution Functions)\n",
-    "- tabulate the `yadism` predictions into fast-interpolation grids for later use"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bfff8f0c-740e-4177-a642-13e9d0a0cc63",
-   "metadata": {},
-   "source": [
-    "## Installation \n",
-    "\n",
-    "In order to start using `yadism`, one first needs to install it and some of its extra-dependencies. The easiest way to install the latest stable version of `yadism` is via `pip` using the following command:\n",
-    "\n",
-    "```sh\n",
-    "pip install 'yadism[mark, box]'\n",
-    "```\n",
-    "\n",
-    "In addition to installing the main `yadism` package, the above command also installs `yadmark` and `yadbox`. `yadmark` is package that provides APIs to perform the benchmark of `yadism` to other DIS codes (e.g. `APFEL`, `APFEL++`, `QCDNUM`). `yadbox` instead provides an interface to `PineAPPL` to store predictions in the form of fast-interpolation grids.\n",
-    "\n",
-    "In order to check that `yadism` was installed properly, one can check the version:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "ded2fb96-9fe9-4503-8418-bfcfb6d53998",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "'0.0.0'"
-      ]
-     },
-     "execution_count": 1,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "import yadism\n",
-    "yadism.__version__"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "valuable-theater",
-   "metadata": {},
-   "source": [
-    "## Preparing the run cards\n",
-    "\n",
-    "Yadism takes as inputs **two runcards** whose representations are given in terms of python dictionaries. That is, one needs:\n",
-    "- an **observable card** which contains the details on the observable to be computed\n",
-    "- a **theory card** which contains the various theory settings to compute the observable in question\n",
-    "\n",
-    "Below is an example of an observable card in which the meaning of each key is also specified:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "announced-petite",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "observable_card = {\n",
-    "    # Process type: \"EM\", \"NC\", \"CC\"\n",
-    "    \"prDIS\": \"NC\",\n",
-    "    # Projectile: \"electron\", \"positron\", \"neutrino\", \"antineutrino\"\n",
-    "    \"ProjectileDIS\": \"electron\",\n",
-    "    # Scattering target: \"proton\", \"neutron\", \"isoscalar\", \"lead\", \"iron\", \"neon\" or \"marble\"\n",
-    "    \"TargetDIS\": \"proton\",\n",
-    "    # Interpolation: if True use log interpolation\n",
-    "    \"interpolation_is_log\": True,\n",
-    "    # Interpolation: polynomial degree, 1 = linear, ...\n",
-    "    \"interpolation_polynomial_degree\": 4,\n",
-    "    # Interpolation: xgrid values\n",
-    "    # Note: for illustrative purposes the grid is chosen very small here\n",
-    "    \"interpolation_xgrid\": [1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1.0],\n",
-    "    # Observables configurations\n",
-    "    \"observables\": {\n",
-    "        \"XSHERANCAVG_charm\": [\n",
-    "            {\n",
-    "                \"y\": 0.8240707777909629,\n",
-    "                \"x\": 3e-05,\n",
-    "                \"Q2\": 2.5,\n",
-    "            },\n",
-    "            {\n",
-    "                \"y\": 0.3531731904818413,\n",
-    "                \"x\": 7e-05,\n",
-    "                \"Q2\": 2.5,\n",
-    "            },\n",
-    "            # Add here the kinematics of other datapoints\n",
-    "        ],\n",
-    "        # Potentially include observables other than XSHERANCAVG_charm,\n",
-    "        # each of them has to be: TYPE_heaviness, where heaviness can take:\n",
-    "        # \"charm\", \"bottom\", \"top\", \"total\" or \"light\".\n",
-    "    },\n",
-    "    # Projectile polarization faction, float from 0 to 1.\n",
-    "    \"PolarizationDIS\": 0.0,\n",
-    "    # Exchanged boson propagator correction\n",
-    "    \"PropagatorCorrection\": 0.0,\n",
-    "    # Restrict boson coupling to a single parton ? Monte Carlo PID or None for all partons\n",
-    "    \"NCPositivityCharge\": None,\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "dc1b79fa-7d14-4ed6-a8ae-0a588ebe5582",
-   "metadata": {},
-   "source": [
-    "The `observables` key in the `observable_card` (which is also a dictionary) can contain multiple elements whose keys must represent structure functions or cross-sections. For the list of available observables, refer to the following [part](https://yadism.readthedocs.io/en/latest/theory/intro.html#) of the documentation.\n",
-    "\n",
-    "Similarly, below is an example of a theory card:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "90df79a9-31cb-40db-ac95-0b88469c1723",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "theory_card = {\n",
-    "    # QCD perturbative order\n",
-    "    \"PTO\": 2,  # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n",
-    "   \n",
-    "    # SM parameters and masses\n",
-    "    \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\",  # CKM matrix elements\n",
-    "    \"GF\": 1.1663787e-05,  # [GeV^-2] Fermi coupling constant\n",
-    "    \"MP\": 0.938,  # [GeV] proton mass\n",
-    "    \"MW\": 80.398,  # [GeV] W boson mass\n",
-    "    \"MZ\": 91.1876,  # [GeV] Z boson mass\n",
-    "    \"alphaqed\": 0.007496252,  # alpha_em value\n",
-    "    \"kcThr\": 1.0,  # ratio of the charm matching scale over the charm mass\n",
-    "    \"kbThr\": 1.0,  # ratio of the bottom matching scale over the bottom mass\n",
-    "    \"ktThr\": 1.0,  # ratio of the top matching scale over the top mass\n",
-    "    \"mc\": 1.51,  # [GeV] charm mass\n",
-    "    \"mb\": 4.92,  # [GeV] bottom mass\n",
-    "    \"mt\": 172.5,  # [GeV] top mass\n",
-    "    \n",
-    "    # Flavor number scheme settings\n",
-    "    \"FNS\": \"FFNS\",  # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n",
-    "    \"NfFF\": 4,  # (fixed) number of running flavors, only for FFNS or FFN0 schemes\n",
-    "    \"Q0\": 1.65,  # [GeV] reference scale for the flavor patch determination\n",
-    "    \"nf0\": 4,  # number of active flavors at the Q0 reference scale\n",
-    "    \n",
-    "    # Alphas settings and boundary conditions\n",
-    "    \"Qref\": 91.2,  # [GeV] reference scale for the alphas value\n",
-    "    \"nfref\": 5,  # number of active flavors at the reference scale Qref\n",
-    "    \"alphas\": 0.118,  # alphas value at the reference scale\n",
-    "    \"MaxNfAs\": 5,  # maximum number of flavors in running of strong coupling\n",
-    "    \"QED\": 0,  # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n",
-    "    \n",
-    "    # Scale Variations \n",
-    "    \"XIF\": 1.0,  # ratio of factorization scale over the hard scattering scale\n",
-    "    \"XIR\": 1.0,  # ratio of renormalization scale over the hard scattering scale\n",
-    "    \n",
-    "    # Other settings\n",
-    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed \n",
-    "    \"TMC\": 1,  # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n",
-    "    \"n3lo_cf_variation\": 0,  # N3LO coefficient functions variation: -1 = lower bound, 0 = central , 1 = upper bound\n",
-    "    \n",
-    "    # Other EKO settings, not relevant for Yadism\n",
-    "    \"HQ\": \"POLE\",  # heavy quark mass scheme (not yet implemented in yadism)\n",
-    "    \"MaxNfPdf\": 5,  # maximum number of flavors in running of PDFs (ignored by yadism)\n",
-    "    \"ModEv\": \"EXA\",  # evolution solver for PDFs (ignored by yadism)\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "169b82a0-abdd-4687-9ffe-9df38446a550",
-   "metadata": {},
-   "source": [
-    "Note that a template observable card is provided by `yadmark` and contains the default `yadism` values. One can thus just start from the default card and overwrite the values."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "246f1d7a-e7e3-48ab-9bf2-44c8352adc39",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
{\n",
-       "│   'NCPositivityCharge': None,\n",
-       "│   'PolarizationDIS': 0,\n",
-       "│   'ProjectileDIS': 'electron',\n",
-       "│   'PropagatorCorrection': 0,\n",
-       "│   'TargetDIS': 'proton',\n",
-       "│   'interpolation_is_log': True,\n",
-       "│   'interpolation_polynomial_degree': 4,\n",
-       "│   'interpolation_xgrid': [\n",
-       "│   │   1e-07,\n",
-       "│   │   1.6102620275609392e-07,\n",
-       "│   │   2.592943797404667e-07,\n",
-       "│   │   4.1753189365604003e-07,\n",
-       "│   │   6.723357536499335e-07,\n",
-       "│   │   1.0826367338740541e-06,\n",
-       "│   │   1.7433288221999873e-06,\n",
-       "│   │   2.8072162039411756e-06,\n",
-       "│   │   4.520353656360241e-06,\n",
-       "│   │   7.2789538439831465e-06,\n",
-       "│   │   1.1721022975334793e-05,\n",
-       "│   │   1.8873918221350995e-05,\n",
-       "│   │   3.039195382313195e-05,\n",
-       "│   │   4.893900918477499e-05,\n",
-       "│   │   7.880462815669905e-05,\n",
-       "│   │   0.0001268961003167922,\n",
-       "│   │   0.00020433597178569417,\n",
-       "│   │   0.00032903445623126676,\n",
-       "│   │   0.0005298316906283707,\n",
-       "│   │   0.0008531678524172806,\n",
-       "│   │   0.0013738237958832637,\n",
-       "│   │   0.00221221629107045,\n",
-       "│   │   0.003562247890262444,\n",
-       "│   │   0.005736152510448681,\n",
-       "│   │   0.009236708571873866,\n",
-       "│   │   0.014873521072935119,\n",
-       "│   │   0.02395026619987486,\n",
-       "│   │   0.03856620421163472,\n",
-       "│   │   0.06210169418915616,\n",
-       "│   │   0.1,\n",
-       "│   │   0.1473684210526316,\n",
-       "│   │   0.19473684210526315,\n",
-       "│   │   0.24210526315789474,\n",
-       "│   │   0.2894736842105263,\n",
-       "│   │   0.33684210526315794,\n",
-       "│   │   0.38421052631578945,\n",
-       "│   │   0.43157894736842106,\n",
-       "│   │   0.4789473684210527,\n",
-       "│   │   0.5263157894736842,\n",
-       "│   │   0.5736842105263158,\n",
-       "│   │   0.6210526315789474,\n",
-       "│   │   0.6684210526315789,\n",
-       "│   │   0.7157894736842105,\n",
-       "│   │   0.7631578947368421,\n",
-       "│   │   0.8105263157894737,\n",
-       "│   │   0.8578947368421053,\n",
-       "│   │   0.9052631578947369,\n",
-       "│   │   0.9526315789473684,\n",
-       "│   │   1.0\n",
-       "│   ],\n",
-       "│   'observables': {},\n",
-       "│   'prDIS': 'EM'\n",
-       "}\n",
-       "
\n"
-      ],
-      "text/plain": [
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-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.6210526315789474\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.6684210526315789\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.7157894736842105\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.7631578947368421\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.8105263157894737\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.8578947368421053\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.9052631578947369\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m0.9526315789473684\u001b[0m,\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1;36m1.0\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[1m]\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[32m'observables'\u001b[0m: \u001b[1m{\u001b[0m\u001b[1m}\u001b[0m,\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[32m'prDIS'\u001b[0m: \u001b[32m'EM'\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "from rich.pretty import pprint # already installed as a dependency, only needed for a pretty printing\n",
-    "from yadmark.data.observables import default_card # imports the default yadism observable card\n",
-    "\n",
-    "pprint(default_card)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "5083afea-4ac9-483d-93b9-f0473cbc46b0",
-   "metadata": {},
-   "source": [
-    "## Computing predictions\n",
-    "\n",
-    "Now that we have defined our observable and theory, we can now compute the corresponding preditions. This can be easily done by running the following:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "b7d95bf6-4536-41a5-9505-07a8743e5f6e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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[21:32:59] INFO     Interpolation: number of points = 8, polynomial degree = 4, logarithmic =  interpolation.py:537\n",
-       "                    True                                                                                           \n",
-       "
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-       "\u001b[2;36m           \u001b[0m         \u001b[3;92mTrue\u001b[0m                                                                       \u001b[2m                    \u001b[0m\n"
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           INFO     {'MZ2': 8315.178393760001, 'CKM': CKM([[9.49221518e-01 5.07600900e-02  coupling_constants.py:52\n",
-       "                    1.20409000e-05] [5.07150400e-02 9.47604903e-01 1.68100000e-03]                                 \n",
-       "                    [7.43044000e-05 1.62409000e-03 9.98304719e-01]]), 'sin2theta_weak':                            \n",
-       "                    0.23121, 'MW2': 6463.838403999999}                                                             \n",
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           INFO     RenScaleVar: False, FactScaleVar: False                                  scale_variations.py:61\n",
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\n",
-       " • XSHERANCAVG_charm at 2 pts                                                                                      \n",
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-       "\u001b[1;33m • \u001b[0mXSHERANCAVG_charm at 2 pts                                                                                      \n"
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-       "                                                    Calculation                                                    \n",
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-       "\n",
-       "                                                    \u001b[1;4mCalculation\u001b[0m                                                    \n"
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-       "
yadism took off! please stay tuned ...\n",
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-       "yadism took off! please stay tuned \u001b[33m...\u001b[0m\n"
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-       "\u001b[?25l"
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-       "\u001b[?25h
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took 0.24 s\n",
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-       "\u001b[36mtook \u001b[0m\u001b[1;36m0.24\u001b[0m\u001b[36m s\u001b[0m\n"
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-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "out = yadism.run_yadism(theory_card, observable_card)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "a1d79202-30d1-465f-9ce2-008fc760ebf1",
-   "metadata": {},
-   "source": [
-    "`out` is an object of type `yadism.output.Output` from which one can perform various operations. In our example, we are interested in convoluting it with a PDF set in the [LHAPDF](https://lhapdf.hepforge.org/) format.\n",
-    "\n",
-    "To do so, first we need to import the `lhapdf` package. For this example, we will use the NNLO NNPDF4.0 set: `NNPDF40_nnlo_as_01180`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "bc6f3aac-802b-4073-9e6a-e18e54f3ef85",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "LHAPDF 6.5.0 loading /home/tanjona/miniconda3/envs/yadism/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
-      "NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100\n"
-     ]
-    }
-   ],
-   "source": [
-    "import lhapdf\n",
-    "\n",
-    "# load the PDF set\n",
-    "pdf = lhapdf.mkPDF(\"NNPDF40_nnlo_as_01180\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "359f3118-a317-4345-8e73-bc810b92ea92",
-   "metadata": {},
-   "source": [
-    "The convolution can simply be performed as follow:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "9b983dd8-4724-439c-bdab-773879308985",
-   "metadata": {},
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[21:37:46] INFO     Atlas [0.00e+00 - 2.28e+00 - 2.42e+01 - 2.98e+04 - inf], ref=8317.44 @ 5        matchings.py:69\n",
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           INFO     Strong Coupling: a_s(µ_R^2=8317.440000)^(nf=5)=0.009390=0.118000/(4π)          couplings.py:458\n",
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-   "source": [
-    "values = out.apply_pdf(pdf)"
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-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "a56aee13-b08b-492f-80d0-3487bea74318",
-   "metadata": {},
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-       "│   │   │   'Q2': 2.5,\n",
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-       "│   │   │   'y': 0.3531731904818413\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'result'\u001b[0m: \u001b[1;36m-0.9959496128078331\u001b[0m,\n",
-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'error'\u001b[0m: \u001b[1;36m1.281070214968848e-08\u001b[0m,\n",
-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'y'\u001b[0m: \u001b[1;36m0.8240707777909629\u001b[0m\n",
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-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'Q2'\u001b[0m: \u001b[1;36m2.5\u001b[0m,\n",
-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'result'\u001b[0m: \u001b[1;36m-0.7710853256052412\u001b[0m,\n",
-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'error'\u001b[0m: \u001b[1;36m2.3298246570353407e-08\u001b[0m,\n",
-       "\u001b[2;32m│   │   │   \u001b[0m\u001b[32m'y'\u001b[0m: \u001b[1;36m0.3531731904818413\u001b[0m\n",
-       "\u001b[2;32m│   │   \u001b[0m\u001b[1m}\u001b[0m\n",
-       "\u001b[2;32m│   \u001b[0m\u001b[1m]\u001b[0m\n",
-       "\u001b[1m}\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pprint(values)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "2c0ffc4a-bb6b-4d89-9a01-1d2c93e49995",
-   "metadata": {},
-   "source": [
-    "We can see that `values` is a dictionary containing one element whose key is the name of the observable (as we defined above). If we had defined two observables in the `observable_card`, `values` would also contain two elements."
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "519b8537-9c09-4a66-bf44-ff47e1879449",
-   "metadata": {},
-   "source": [
-    "## Dumping predictions into fast-interpolation grids\n",
-    "\n",
-    "We learned from the previous sections how to compute an observable using `yadism` and now we'll see how to tabulate the output of `yadism.run_yadism` into a fast-interpolation table. This has the convenient advantage that one can re-use the same computations without the need to re-run `yadism` (to convolute with different PDF sets for example).\n",
-    "\n",
-    "One of the main advantage of `yadism` is its interface with PineAPPL - a library providing fast interpolation into a unique format suitable for various HEP-related softwares. \n",
-    "\n",
-    "Each observable defined in `observable_card` can be dumped into its own fast-interpolation grid. The steps are as follow:"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "7f914e87-bb05-47c7-a850-11a18e6cfdb5",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# import function that dumps the predictions into a Pineappl format\n",
-    "from yadbox.export import dump_pineappl_to_file\n",
-    "\n",
-    "# Extract the names of the different observables (in case there are many)\n",
-    "list_observables = observable_card['observables'].keys()\n",
-    "\n",
-    "# Dump each observable into a PineAPPL grid\n",
-    "for obs in list_observables:\n",
-    "    dump_pineappl_to_file(out, f\"outputgrid_{obs}.pineappl.lz4\", f\"{obs}\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7dffb5fd-9e84-4982-b9d4-a4f077a573e8",
-   "metadata": {},
-   "source": [
-    "Our PineAPPL grid has now been written on the disk. Note that the extension has to be `pineappl.lz4`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "703b29ce-9068-44af-b72b-1144bad805e6",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "outputgrid_XSHERANCAVG_charm.pineappl.lz4\n"
-     ]
-    }
-   ],
-   "source": [
-    "!ls outputgrid_*"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0c887943-be93-4a0f-815b-1317ad04db2c",
-   "metadata": {},
-   "source": [
-    "To load the pre-computed predictions, we need to import the `pineappl` package. Given that `pineappl` is a dependency of `yadism` it was already installed so we don't have to install it again."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "ebf75d0e-965a-46b1-a3a3-e20eeb1d5e15",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "# imports the pineappl package\n",
-    "import pineappl\n",
-    "\n",
-    "# Read the pineappl grid saved earlier\n",
-    "grid = pineappl.grid.Grid.read(\"./outputgrid_XSHERANCAVG_charm.pineappl.lz4\")\n",
-    "\n",
-    "# Convolute the grid with the same PDF as above\n",
-    "results = grid.convolute_with_one(2212, pdf.xfxQ2, pdf.alphasQ2)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "fc268946-3f84-4f63-be98-a899adf9512c",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "
array([-0.98699882, -0.7640712 ])\n",
-       "
\n"
-      ],
-      "text/plain": [
-       "\u001b[1;35marray\u001b[0m\u001b[1m(\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m-0.98699882\u001b[0m, \u001b[1;36m-0.7640712\u001b[0m \u001b[1m]\u001b[0m\u001b[1m)\u001b[0m\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "pprint(results)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "c114b40d-9a40-4d73-8609-ab8761fe37a0",
-   "metadata": {},
-   "source": [
-    "As we can see, we get similar results to what we got before. Now, the `results` is just an array of two dimension corresponding to the different kinematic values."
-   ]
-  }
- ],
- "metadata": {
-  "kernelspec": {
-   "display_name": "yadism-QljnF84o-py3.10",
-   "language": "python",
-   "name": "yadism-qljnf84o-py3.10"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.10.13"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/docs/source/overview/tutorials/compare_data.ipynb b/docs/source/overview/tutorials/compare_data.ipynb
new file mode 100644
index 000000000..e088a001a
--- /dev/null
+++ b/docs/source/overview/tutorials/compare_data.ipynb
@@ -0,0 +1,585 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "nominated-inspection",
+   "metadata": {},
+   "source": [
+    "# Compare to Experimental Data\n",
+    "\n",
+    "In the following section, we'll show how to compare `yadism` predictions to an experimentally measured observable. As a test case, we use the combined measurement of two experioments [H1](https://en.wikipedia.org/wiki/H1_(particle_detector)) and [ZEUS](https://en.wikipedia.org/wiki/ZEUS_(particle_detector)) for the collision of an electron with a proton at a center of mass energy of $\\sqrt{s} = 318~\\rm{GeV}$.\n",
+    "\n",
+    "## Preparing the dataset\n",
+    "\n",
+    "Our dataset can be downloaded from the NNPDF server:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "2fada138-79b8-44c7-ad32-8ececc9979f3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!wget -q https://data.nnpdf.science/yadism/HERA12B2_NCem.dat"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "1baa9ce5-ee95-46f9-a2e6-9682d5e295f7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\n",
+       "\n",
+       "  \n",
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+       "      \n",
+       "    \n",
+       "  \n",
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+       "    \n",
+       "  \n",
+       "
xQ2Sigma
00.000860.01.483100
10.001390.01.466000
20.001590.01.421900
30.002090.01.270000
40.0016120.01.438800
............
1540.400020000.00.205990
1550.650020000.00.017364
1560.400030000.00.230730
1570.650030000.00.044179
1580.650050000.00.082210
\n",
+       "
159 rows × 3 columns
\n",
+       "
"
+      ],
+      "text/plain": [
+       "          x       Q2     Sigma\n",
+       "0    0.0008     60.0  1.483100\n",
+       "1    0.0013     90.0  1.466000\n",
+       "2    0.0015     90.0  1.421900\n",
+       "3    0.0020     90.0  1.270000\n",
+       "4    0.0016    120.0  1.438800\n",
+       "..      ...      ...       ...\n",
+       "154  0.4000  20000.0  0.205990\n",
+       "155  0.6500  20000.0  0.017364\n",
+       "156  0.4000  30000.0  0.230730\n",
+       "157  0.6500  30000.0  0.044179\n",
+       "158  0.6500  50000.0  0.082210\n",
+       "\n",
+       "[159 rows x 3 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "# Load the experimental data via pandas\n",
+    "data = pd.read_csv(\"HERA12B2_NCem.dat\", sep=\"\\s+\")\n",
+    "\n",
+    "data[[\"x\", \"Q2\", \"Sigma\"]]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "60da4349-dddc-406e-a3f8-2e81c7e1c767",
+   "metadata": {},
+   "source": [
+    "## Computing the yadism predictions\n",
+    "\n",
+    "We are now going to compute the `yadism` predictions at the same kinematic points as provided by the experimental measurements. In terms of theory, we are going to use the NNLO predictions with Fixed-Flavour Number Schemes (FFNS). As we saw in the previous tutorial, we first need to prepare the theory and observable cards."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "9849edb4-ae32-49b2-ba6d-a96bf2cdb6f4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import warnings\n",
+    "import yadism\n",
+    "\n",
+    "from eko import interpolation\n",
+    "from yadbox.export import dump_pineappl_to_file"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "ff60baae-65ee-4544-af2d-3c7a23a5734d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "observables_card = {\n",
+    "    \"PolarizationDIS\": 0.0,\n",
+    "    \"ProjectileDIS\": \"electron\",\n",
+    "    \"PropagatorCorrection\": 0.0,\n",
+    "    \"TargetDIS\": \"proton\",\n",
+    "    \"interpolation_is_log\": True,\n",
+    "    \"interpolation_polynomial_degree\": 4,\n",
+    "    \"interpolation_xgrid\": interpolation.lambertgrid(60).tolist(),\n",
+    "    \"observables\": {\"XSHERANC_total\": []},\n",
+    "    \"prDIS\": \"NC\",\n",
+    "    \"NCPositivityCharge\": None,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "5920d43e-b8b4-496a-97c8-98b5c2325716",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "theory_card = {\n",
+    "    \"PTO\": 2,\n",
+    "    \"FNS\": \"FONLL-C\",\n",
+    "    \"DAMP\": 0,\n",
+    "    \"IC\": 1,\n",
+    "    \"IB\": 0,\n",
+    "    \"ModEv\": \"TRN\",\n",
+    "    \"ModSV\": \"unvaried\",\n",
+    "    \"XIR\": 1.0,\n",
+    "    \"XIF\": 1.0,\n",
+    "    \"NfFF\": 5,\n",
+    "    \"MaxNfAs\": 5,\n",
+    "    \"MaxNfPdf\": 5,\n",
+    "    \"Q0\": 1.65,\n",
+    "    \"alphas\": 0.118,\n",
+    "    \"Qref\": 91.2,\n",
+    "    \"nf0\": 4,\n",
+    "    \"nfref\": 5,\n",
+    "    \"QED\": 0,\n",
+    "    \"alphaqed\": 0.007496252,\n",
+    "    \"Qedref\": 1.777,\n",
+    "    \"SxRes\": 0,\n",
+    "    \"SxOrd\": \"LL\",\n",
+    "    \"HQ\": \"POLE\",\n",
+    "    \"mc\": 1.51,\n",
+    "    \"Qmc\": 1.51,\n",
+    "    \"kcThr\": 1.0,\n",
+    "    \"mb\": 4.92,\n",
+    "    \"Qmb\": 4.92,\n",
+    "    \"kbThr\": 4.0,\n",
+    "    \"mt\": 172.5,\n",
+    "    \"Qmt\": 172.5,\n",
+    "    \"ktThr\": 1.0,\n",
+    "    \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\",\n",
+    "    \"MZ\": 91.1876,\n",
+    "    \"MW\": 80.398,\n",
+    "    \"GF\": 1.1663787e-05,\n",
+    "    \"SIN2TW\": 0.23126,\n",
+    "    \"TMC\": 1,\n",
+    "    \"MP\": 0.938,\n",
+    "    \"global_nx\": 0,\n",
+    "    \"EScaleVar\": 1,\n",
+    "    \"kDIScThr\": 1.0,\n",
+    "    \"kDISbThr\": 4.0,\n",
+    "    \"kDIStThr\": 1.0,\n",
+    "    \"n3lo_cf_variation\": 0,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "6e68559d-2f4e-4a0c-a372-8dc836bd1f8a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def compute_predicionts() -> None:\n",
+    "    \"\"\"Compute yadism prediction for all experimental bins.\"\"\"\n",
+    "    # prepare the kinematics for all the datapoints\n",
+    "    curobs = data.apply(\n",
+    "        lambda dat: {\"x\": dat[\"x\"], \"Q2\": dat[\"Q2\"], \"y\": dat[\"y\"]},\n",
+    "        axis=1,\n",
+    "    )\n",
+    "\n",
+    "    # Update the observable &b kinematics in the `observable_card`\n",
+    "    obs_def = {\n",
+    "        \"observables\" : {\"XSHERANC_total\": list(curobs.to_dict().values())}\n",
+    "    } # As we saw in the previous tutorial, it has to be a dict[dict[list]]\n",
+    "    observables_card.update(obs_def)\n",
+    "\n",
+    "    with warnings.catch_warnings():\n",
+    "        warnings.simplefilter(\"ignore\") # suppress noisy warnings\n",
+    "        out = yadism.run_yadism(theory_card, observables_card)\n",
+    "        \n",
+    "    # Dump computations as a pineappl grid for later use\n",
+    "    dump_pineappl_to_file(\n",
+    "        out, \"HERA_NC_318GEV_EM_SIGMARED.pineappl.lz4\", \"XSHERANC_total\"\n",
+    "    )"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "006952bf-d2aa-46c0-a1a5-53f19af94068",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "                                                       Plan                                                        \n",
+       "
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+      ],
+      "text/plain": [
+       "\n",
+       "                                                       \u001b[1;4mPlan\u001b[0m                                                        \n"
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+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       " • XSHERANC_total at 159 pts                                                                                       \n",
+       "
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+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;33m • \u001b[0mXSHERANC_total at 159 pts                                                                                       \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "                                                    Calculation                                                    \n",
+       "
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+      ],
+      "text/plain": [
+       "\n",
+       "                                                    \u001b[1;4mCalculation\u001b[0m                                                    \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
yadism took off! please stay tuned ...\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "yadism took off! please stay tuned \u001b[33m...\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[?25l"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "\u001b[?25h
\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[?25h"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
took 55.93 s\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\u001b[36mtook \u001b[0m\u001b[1;36m55.93\u001b[0m\u001b[36m s\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Compute the predictions - slihgtly heavier due to complexity & nb datapoints\n",
+    "compute_predicionts()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ee0cb707-eb66-4888-8ad8-142c3556e26f",
+   "metadata": {},
+   "source": [
+    "## Loading and comparing to HERA\n",
+    "\n",
+    "Now that we have our pre-computed predictions in the form of PineAPPL grid, we can compare the results to the HERA measurements. To do so, we can load the grid and convolute it with a PDF set. As in the previous tutorial we're going to use the NNLO NNPDF4.0 set."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "8fa0f803-de73-4737-a40a-7ffeebf6de77",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import lhapdf\n",
+    "import pineappl"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "b631e769-d706-4d9a-ac30-006a24dffca8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LHAPDF 6.5.0 loading /home/tanjona/miniconda3/envs/yadism/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
+      "NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Load only the central member\n",
+    "pdf = lhapdf.mkPDF(\"NNPDF40_nnlo_as_01180\", 0)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "0e0f5c2e-74ce-45ea-9064-749eb3ad47df",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load the pre-computed grid\n",
+    "grid = pineappl.grid.Grid.read(\"HERA_NC_318GEV_EM_SIGMARED.pineappl.lz4\")\n",
+    "\n",
+    "# Convolute with the PDF\n",
+    "yadism_data = grid.convolute_with_one(2212, pdf.xfxQ2, pdf.alphasQ2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "5995d40f-2e53-4d1d-8d5e-84798e127647",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Combine the exp measurements and Yadism preds into one table\n",
+    "data_vs_yadism_df = pd.concat(\n",
+    "    [\n",
+    "        data[\"Q2\"],\n",
+    "        data[\"x\"],\n",
+    "        data[\"Sigma\"],\n",
+    "        pd.DataFrame([yadism_data], index=[\"yadism\"]).T,\n",
+    "    ],\n",
+    "    axis=1,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "a9ca7478-6101-458a-8f79-ec039111f640",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "def plot_comparisons_q2(df: pd.DataFrame, q2_value: int = 300) -> None:\n",
+    "    fig, ax = plt.subplots(figsize=(5, 3.75), layout=\"tight\")\n",
+    "\n",
+    "    # Select corresponding Q2 values\n",
+    "    df_q2 = df[df.Q2 == q2_value]\n",
+    "\n",
+    "    # Plot measurements and yadism preds\n",
+    "    ax.plot(df_q2.x, df_q2[\"Sigma\"], \"o\", label=\"EXP\")\n",
+    "    ax.plot(df_q2.x, df_q2[\"yadism\"], \"rs\", label=\"Yadism\")\n",
+    "\n",
+    "    ax.set_xlabel(\"x\")\n",
+    "    ax.set_ylabel(\"xsec\")\n",
+    "    ax.legend()\n",
+    "    ax.set_xscale(\"log\")\n",
+    "    ax.set_title(f\"HERA: $Q^2 = {q2_value}~ \\\\mathrm{{GeV}}^2$\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "cde1c144-2195-48d2-ac9c-05b09cb2b088",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "
"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_comparisons_q2(data_vs_yadism_df)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "8bcea746-3151-45c8-a222-3cf4119431c9",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "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": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/overview/tutorials/getting_started.ipynb b/docs/source/overview/tutorials/getting_started.ipynb
new file mode 100644
index 000000000..b9124dda5
--- /dev/null
+++ b/docs/source/overview/tutorials/getting_started.ipynb
@@ -0,0 +1,679 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "bfff8f0c-740e-4177-a642-13e9d0a0cc63",
+   "metadata": {},
+   "source": [
+    "# Getting Started\n",
+    "\n",
+    "## Installation \n",
+    "\n",
+    "In order to start using `yadism`, one first needs to install it and some of its extra-dependencies. The easiest way to install the latest stable version of `yadism` is via `pip` using the following command:\n",
+    "\n",
+    "```sh\n",
+    "pip install 'yadism[mark, box]'\n",
+    "```\n",
+    "\n",
+    "In addition to installing the main `yadism` package, the above command also installs `yadmark` and `yadbox`. `yadmark` is package that provides APIs to perform the benchmark of `yadism` to other DIS codes (e.g. `APFEL`, `APFEL++`, `QCDNUM`). `yadbox` instead provides an interface to `PineAPPL` to store predictions in the form of fast-interpolation grids.\n",
+    "\n",
+    "In order to check that `yadism` was installed properly, one can check the version:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "ded2fb96-9fe9-4503-8418-bfcfb6d53998",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'0.0.0'"
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import yadism\n",
+    "yadism.__version__"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "valuable-theater",
+   "metadata": {},
+   "source": [
+    "## Preparing the run cards\n",
+    "\n",
+    "Yadism takes as inputs **two runcards** whose representations are given in terms of python dictionaries. That is, one needs:\n",
+    "- an **observable card** which contains the details on the observable to be computed\n",
+    "- a **theory card** which contains the various theory settings to compute the observable in question\n",
+    "\n",
+    "Below is an example of an observable card in which the meaning of each key is also specified:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "announced-petite",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "observable_card = {\n",
+    "    # Process type: \"EM\", \"NC\", \"CC\"\n",
+    "    \"prDIS\": \"NC\",\n",
+    "    # Projectile: \"electron\", \"positron\", \"neutrino\", \"antineutrino\"\n",
+    "    \"ProjectileDIS\": \"electron\",\n",
+    "    # Scattering target: \"proton\", \"neutron\", \"isoscalar\", \"lead\", \"iron\", \"neon\" or \"marble\"\n",
+    "    \"TargetDIS\": \"proton\",\n",
+    "    # Interpolation: if True use log interpolation\n",
+    "    \"interpolation_is_log\": True,\n",
+    "    # Interpolation: polynomial degree, 1 = linear, ...\n",
+    "    \"interpolation_polynomial_degree\": 4,\n",
+    "    # Interpolation: xgrid values\n",
+    "    # Note: for illustrative purposes the grid is chosen very small here\n",
+    "    \"interpolation_xgrid\": [1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2, 1e-1, 1.0],\n",
+    "    # Observables configurations\n",
+    "    \"observables\": {\n",
+    "        \"XSHERANCAVG_charm\": [\n",
+    "            {\n",
+    "                \"y\": 0.8240707777909629,\n",
+    "                \"x\": 3e-05,\n",
+    "                \"Q2\": 2.5,\n",
+    "            },\n",
+    "            {\n",
+    "                \"y\": 0.3531731904818413,\n",
+    "                \"x\": 7e-05,\n",
+    "                \"Q2\": 2.5,\n",
+    "            },\n",
+    "            # Add here the kinematics of other datapoints\n",
+    "        ],\n",
+    "        # Potentially include observables other than XSHERANCAVG_charm,\n",
+    "        # each of them has to be: TYPE_heaviness, where heaviness can take:\n",
+    "        # \"charm\", \"bottom\", \"top\", \"total\" or \"light\".\n",
+    "    },\n",
+    "    # Projectile polarization faction, float from 0 to 1.\n",
+    "    \"PolarizationDIS\": 0.0,\n",
+    "    # Exchanged boson propagator correction\n",
+    "    \"PropagatorCorrection\": 0.0,\n",
+    "    # Restrict boson coupling to a single parton ? Monte Carlo PID or None for all partons\n",
+    "    \"NCPositivityCharge\": None,\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "dc1b79fa-7d14-4ed6-a8ae-0a588ebe5582",
+   "metadata": {},
+   "source": [
+    "The `observables` key in the `observable_card` (which is also a dictionary) can contain multiple elements whose keys must represent structure functions or cross-sections. For the list of available observables, refer to the following [part](https://yadism.readthedocs.io/en/latest/theory/intro.html#) of the documentation.\n",
+    "\n",
+    "Similarly, below is an example of a theory card:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "90df79a9-31cb-40db-ac95-0b88469c1723",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "theory_card = {\n",
+    "    # QCD perturbative order\n",
+    "    \"PTO\": 2,  # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n",
+    "   \n",
+    "    # SM parameters and masses\n",
+    "    \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\",  # CKM matrix elements\n",
+    "    \"GF\": 1.1663787e-05,  # [GeV^-2] Fermi coupling constant\n",
+    "    \"MP\": 0.938,  # [GeV] proton mass\n",
+    "    \"MW\": 80.398,  # [GeV] W boson mass\n",
+    "    \"MZ\": 91.1876,  # [GeV] Z boson mass\n",
+    "    \"alphaqed\": 0.007496252,  # alpha_em value\n",
+    "    \"kcThr\": 1.0,  # ratio of the charm matching scale over the charm mass\n",
+    "    \"kbThr\": 1.0,  # ratio of the bottom matching scale over the bottom mass\n",
+    "    \"ktThr\": 1.0,  # ratio of the top matching scale over the top mass\n",
+    "    \"mc\": 1.51,  # [GeV] charm mass\n",
+    "    \"mb\": 4.92,  # [GeV] bottom mass\n",
+    "    \"mt\": 172.5,  # [GeV] top mass\n",
+    "    \n",
+    "    # Flavor number scheme settings\n",
+    "    \"FNS\": \"FFNS\",  # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n",
+    "    \"NfFF\": 4,  # (fixed) number of running flavors, only for FFNS or FFN0 schemes\n",
+    "    \"Q0\": 1.65,  # [GeV] reference scale for the flavor patch determination\n",
+    "    \"nf0\": 4,  # number of active flavors at the Q0 reference scale\n",
+    "    \n",
+    "    # Alphas settings and boundary conditions\n",
+    "    \"Qref\": 91.2,  # [GeV] reference scale for the alphas value\n",
+    "    \"nfref\": 5,  # number of active flavors at the reference scale Qref\n",
+    "    \"alphas\": 0.118,  # alphas value at the reference scale\n",
+    "    \"MaxNfAs\": 5,  # maximum number of flavors in running of strong coupling\n",
+    "    \"QED\": 0,  # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n",
+    "    \n",
+    "    # Scale Variations \n",
+    "    \"XIF\": 1.0,  # ratio of factorization scale over the hard scattering scale\n",
+    "    \"XIR\": 1.0,  # ratio of renormalization scale over the hard scattering scale\n",
+    "    \n",
+    "    # Other settings\n",
+    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed \n",
+    "    \"TMC\": 1,  # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n",
+    "    \"n3lo_cf_variation\": 0,  # N3LO coefficient functions variation: -1 = lower bound, 0 = central , 1 = upper bound\n",
+    "    \n",
+    "    # Other EKO settings, not relevant for Yadism\n",
+    "    \"HQ\": \"POLE\",  # heavy quark mass scheme (not yet implemented in yadism)\n",
+    "    \"MaxNfPdf\": 5,  # maximum number of flavors in running of PDFs (ignored by yadism)\n",
+    "    \"ModEv\": \"EXA\",  # evolution solver for PDFs (ignored by yadism)\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "169b82a0-abdd-4687-9ffe-9df38446a550",
+   "metadata": {},
+   "source": [
+    "Note that a template observable card is provided by `yadmark` and contains the default `yadism` values. One can thus just start from the default card and overwrite the values."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "246f1d7a-e7e3-48ab-9bf2-44c8352adc39",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "    \"NCPositivityCharge\": null,\n",
+      "    \"PolarizationDIS\": 0,\n",
+      "    \"ProjectileDIS\": \"electron\",\n",
+      "    \"PropagatorCorrection\": 0,\n",
+      "    \"TargetDIS\": \"proton\",\n",
+      "    \"interpolation_is_log\": true,\n",
+      "    \"interpolation_polynomial_degree\": 4,\n",
+      "    \"interpolation_xgrid\": [\n",
+      "        1e-07,\n",
+      "        1.6102620275609392e-07,\n",
+      "        2.592943797404667e-07,\n",
+      "        4.1753189365604003e-07,\n",
+      "        6.723357536499335e-07,\n",
+      "        1.0826367338740541e-06,\n",
+      "        1.7433288221999873e-06,\n",
+      "        2.8072162039411756e-06,\n",
+      "        4.520353656360241e-06,\n",
+      "        7.2789538439831465e-06,\n",
+      "        1.1721022975334793e-05,\n",
+      "        1.8873918221350995e-05,\n",
+      "        3.039195382313195e-05,\n",
+      "        4.893900918477499e-05,\n",
+      "        7.880462815669905e-05,\n",
+      "        0.0001268961003167922,\n",
+      "        0.00020433597178569417,\n",
+      "        0.00032903445623126676,\n",
+      "        0.0005298316906283707,\n",
+      "        0.0008531678524172806,\n",
+      "        0.0013738237958832637,\n",
+      "        0.00221221629107045,\n",
+      "        0.003562247890262444,\n",
+      "        0.005736152510448681,\n",
+      "        0.009236708571873866,\n",
+      "        0.014873521072935119,\n",
+      "        0.02395026619987486,\n",
+      "        0.03856620421163472,\n",
+      "        0.06210169418915616,\n",
+      "        0.1,\n",
+      "        0.1473684210526316,\n",
+      "        0.19473684210526315,\n",
+      "        0.24210526315789474,\n",
+      "        0.2894736842105263,\n",
+      "        0.33684210526315794,\n",
+      "        0.38421052631578945,\n",
+      "        0.43157894736842106,\n",
+      "        0.4789473684210527,\n",
+      "        0.5263157894736842,\n",
+      "        0.5736842105263158,\n",
+      "        0.6210526315789474,\n",
+      "        0.6684210526315789,\n",
+      "        0.7157894736842105,\n",
+      "        0.7631578947368421,\n",
+      "        0.8105263157894737,\n",
+      "        0.8578947368421053,\n",
+      "        0.9052631578947369,\n",
+      "        0.9526315789473684,\n",
+      "        1.0\n",
+      "    ],\n",
+      "    \"observables\": {},\n",
+      "    \"prDIS\": \"EM\"\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json # just used for pretty-printing\n",
+    "from yadmark.data.observables import default_card # imports the default yadism observable card\n",
+    "\n",
+    "print(json.dumps(default_card, sort_keys=False, indent=4))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5083afea-4ac9-483d-93b9-f0473cbc46b0",
+   "metadata": {},
+   "source": [
+    "## Computing predictions\n",
+    "\n",
+    "Now that we have defined our observable and theory, we can now compute the corresponding preditions. This can be easily done by running the following:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "b7d95bf6-4536-41a5-9505-07a8743e5f6e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
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+       "                                      │                                    │                                       \n",
+       "                                      │ __     __       _ _                │                                       \n",
+       "                                      │ \\ \\   / /      | (_)               │                                       \n",
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+       "                                      │   \\   / _` |/ _` | / __| '_ ` _ \\  │                                       \n",
+       "                                      │    | | (_| | (_| | \\__ \\ | | | | | │                                       \n",
+       "                                      │    |_|\\__,_|\\__,_|_|___/_| |_| |_| │                                       \n",
+       "                                      │                                    │                                       \n",
+       "                                      └────────────────────────────────────┘                                       \n",
+       "
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+      ],
+      "text/plain": [
+       "                                      \u001b[35m┌────────────────────────────────────┐\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m                                    \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m \u001b[0m\u001b[35m__     __       _ _\u001b[0m\u001b[35m               \u001b[0m\u001b[35m \u001b[0m\u001b[35m│\u001b[0m                                       \n",
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+       "                                      \u001b[35m│\u001b[0m\u001b[35m \u001b[0m\u001b[35m \\ \\_/ /_ _  __| |_ ___ _ __ ___\u001b[0m\u001b[35m  \u001b[0m\u001b[35m \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m \u001b[0m\u001b[35m  \\   / _` |/ _` | / __| '_ ` _ \\\u001b[0m\u001b[35m \u001b[0m\u001b[35m \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m \u001b[0m\u001b[35m   | | (_| | (_| | \\__ \\ | | | | |\u001b[0m\u001b[35m \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m \u001b[0m\u001b[35m   |_|\\__,_|\\__,_|_|___/_| |_| |_|\u001b[0m\u001b[35m \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m│\u001b[0m\u001b[35m                                    \u001b[0m\u001b[35m│\u001b[0m                                       \n",
+       "                                      \u001b[35m└────────────────────────────────────┘\u001b[0m                                       \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "                                                       Plan                                                        \n",
+       "
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+      ],
+      "text/plain": [
+       "\n",
+       "                                                       \u001b[1;4mPlan\u001b[0m                                                        \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       " • XSHERANCAVG_charm at 2 pts                                                                                      \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;33m • \u001b[0mXSHERANCAVG_charm at 2 pts                                                                                      \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
\n",
+       "                                                    Calculation                                                    \n",
+       "
\n"
+      ],
+      "text/plain": [
+       "\n",
+       "                                                    \u001b[1;4mCalculation\u001b[0m                                                    \n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
yadism took off! please stay tuned ...\n",
+       "
\n"
+      ],
+      "text/plain": [
+       "yadism took off! please stay tuned \u001b[33m...\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+      ],
+      "text/plain": [
+       "\u001b[?25l"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
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+       "\u001b[?25h
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+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[?25h"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
took 0.36 s\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[36mtook \u001b[0m\u001b[1;36m0.36\u001b[0m\u001b[36m s\u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import warnings\n",
+    "\n",
+    "with warnings.catch_warnings():\n",
+    "    warnings.simplefilter(\"ignore\") # skip noisy warnings\n",
+    "    out = yadism.run_yadism(theory_card, observable_card)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a1d79202-30d1-465f-9ce2-008fc760ebf1",
+   "metadata": {},
+   "source": [
+    "`out` is an object of type `yadism.output.Output` from which one can perform various operations. In our example, we are interested in convoluting it with a PDF set in the [LHAPDF](https://lhapdf.hepforge.org/) format.\n",
+    "\n",
+    "To do so, first we need to import the `lhapdf` package. For this example, we will use the NNLO NNPDF4.0 set: `NNPDF40_nnlo_as_01180`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "bc6f3aac-802b-4073-9e6a-e18e54f3ef85",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LHAPDF 6.5.0 loading /home/tanjona/miniconda3/envs/yadism/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
+      "NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100\n"
+     ]
+    }
+   ],
+   "source": [
+    "import lhapdf\n",
+    "\n",
+    "# load the PDF set\n",
+    "pdf = lhapdf.mkPDF(\"NNPDF40_nnlo_as_01180\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "359f3118-a317-4345-8e73-bc810b92ea92",
+   "metadata": {},
+   "source": [
+    "The convolution can simply be performed as follow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "9b983dd8-4724-439c-bdab-773879308985",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "
[13:09:24] INFO     Atlas [0.00e+00 - 2.28e+00 - 2.42e+01 - 2.98e+04 - inf], ref=8317.44 @ 5        matchings.py:69\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m[13:09:24]\u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m2.28e+00\u001b[0m - \u001b[1;36m2.42e+01\u001b[0m - \u001b[1;36m2.98e+04\u001b[0m - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.44\u001b[0m @ \u001b[1;36m5\u001b[0m        \u001b]8;id=490630;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=61240;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
           INFO     Strong Coupling: a_s(µ_R^2=8317.440000)^(nf=5)=0.009390=0.118000/(4π)          couplings.py:458\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Strong Coupling: \u001b[1;35ma_s\u001b[0m\u001b[1m(\u001b[0mµ_R^\u001b[1;36m2\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.440000\u001b[0m\u001b[1m)\u001b[0m^\u001b[1m(\u001b[0m\u001b[33mnf\u001b[0m=\u001b[1;36m5\u001b[0m\u001b[1m)\u001b[0m=\u001b[1;36m0.\u001b[0m\u001b[1;36m009390\u001b[0m=\u001b[1;36m0\u001b[0m\u001b[1;36m.118000\u001b[0m/\u001b[1m(\u001b[0m4π\u001b[1m)\u001b[0m          \u001b]8;id=709662;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py\u001b\\\u001b[2mcouplings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=838466;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/couplings.py#458\u001b\\\u001b[2m458\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "
           INFO     Atlas [0.00e+00 - 2.28e+00 - 2.42e+01 - 2.98e+04 - inf], ref=8317.44 @ 5        matchings.py:69\n",
+       "
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+      ],
+      "text/plain": [
+       "\u001b[2;36m          \u001b[0m\u001b[2;36m \u001b[0m\u001b[34mINFO    \u001b[0m Atlas \u001b[1m[\u001b[0m\u001b[1;36m0.00e+00\u001b[0m - \u001b[1;36m2.28e+00\u001b[0m - \u001b[1;36m2.42e+01\u001b[0m - \u001b[1;36m2.98e+04\u001b[0m - inf\u001b[1m]\u001b[0m, \u001b[33mref\u001b[0m=\u001b[1;36m8317\u001b[0m\u001b[1;36m.44\u001b[0m @ \u001b[1;36m5\u001b[0m        \u001b]8;id=369258;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py\u001b\\\u001b[2mmatchings.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=408583;file:///home/tanjona/miniconda3/envs/yadism/lib/python3.10/site-packages/eko/matchings.py#69\u001b\\\u001b[2m69\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "values = out.apply_pdf(pdf)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "a56aee13-b08b-492f-80d0-3487bea74318",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{\n",
+      "    \"XSHERANCAVG_charm\": [\n",
+      "        {\n",
+      "            \"x\": 3e-05,\n",
+      "            \"Q2\": 2.5,\n",
+      "            \"result\": -0.9959496128078331,\n",
+      "            \"error\": 1.281070214968848e-08,\n",
+      "            \"y\": 0.8240707777909629\n",
+      "        },\n",
+      "        {\n",
+      "            \"x\": 7e-05,\n",
+      "            \"Q2\": 2.5,\n",
+      "            \"result\": -0.7710853256052412,\n",
+      "            \"error\": 2.3298246570353407e-08,\n",
+      "            \"y\": 0.3531731904818413\n",
+      "        }\n",
+      "    ]\n",
+      "}\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(json.dumps(values, sort_keys=False, indent=4))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "2c0ffc4a-bb6b-4d89-9a01-1d2c93e49995",
+   "metadata": {},
+   "source": [
+    "We can see that `values` is a dictionary containing one element whose key is the name of the observable (as we defined above). If we had defined two observables in the `observable_card`, `values` would also contain two elements."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "519b8537-9c09-4a66-bf44-ff47e1879449",
+   "metadata": {},
+   "source": [
+    "## Dumping predictions into fast-interpolation grids\n",
+    "\n",
+    "We learned from the previous sections how to compute an observable using `yadism` and now we'll see how to tabulate the output of `yadism.run_yadism` into a fast-interpolation table. This has the convenient advantage that one can re-use the same computations without the need to re-run `yadism` (to convolute with different PDF sets for example).\n",
+    "\n",
+    "One of the main advantage of `yadism` is its interface with PineAPPL - a library providing fast interpolation into a unique format suitable for various HEP-related softwares. \n",
+    "\n",
+    "Each observable defined in `observable_card` can be dumped into its own fast-interpolation grid. The steps are as follow:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "7f914e87-bb05-47c7-a850-11a18e6cfdb5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# import function that dumps the predictions into a Pineappl format\n",
+    "from yadbox.export import dump_pineappl_to_file\n",
+    "\n",
+    "# Extract the names of the different observables (in case there are many)\n",
+    "list_observables = observable_card['observables'].keys()\n",
+    "\n",
+    "# Dump each observable into a PineAPPL grid\n",
+    "for obs in list_observables:\n",
+    "    dump_pineappl_to_file(out, f\"outputgrid_{obs}.pineappl.lz4\", f\"{obs}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7dffb5fd-9e84-4982-b9d4-a4f077a573e8",
+   "metadata": {},
+   "source": [
+    "Our PineAPPL grid has now been written on the disk. Note that the extension has to be `pineappl.lz4`."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "703b29ce-9068-44af-b72b-1144bad805e6",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "outputgrid_XSHERANCAVG_charm.pineappl.lz4\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls outputgrid_*"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0c887943-be93-4a0f-815b-1317ad04db2c",
+   "metadata": {},
+   "source": [
+    "To load the pre-computed predictions, we need to import the `pineappl` package. Given that `pineappl` is a dependency of `yadism` it was already installed so we don't have to install it again."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ebf75d0e-965a-46b1-a3a3-e20eeb1d5e15",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# imports the pineappl package\n",
+    "import pineappl\n",
+    "\n",
+    "# Read the pineappl grid saved earlier\n",
+    "grid = pineappl.grid.Grid.read(\"./outputgrid_XSHERANCAVG_charm.pineappl.lz4\")\n",
+    "\n",
+    "# Convolute the grid with the same PDF as above\n",
+    "results = grid.convolute_with_one(2212, pdf.xfxQ2, pdf.alphasQ2)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "fc268946-3f84-4f63-be98-a899adf9512c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[-0.98699882 -0.7640712 ]\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(results)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c114b40d-9a40-4d73-8609-ab8761fe37a0",
+   "metadata": {},
+   "source": [
+    "As we can see, we get similar results to what we got before. Now, the `results` is just an array of two dimension corresponding to the different kinematic values."
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "yadism",
+   "language": "python",
+   "name": "yadism"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/source/overview/tutorials/tutorials.rst b/docs/source/overview/tutorials/tutorials.rst
new file mode 100644
index 000000000..37cec7167
--- /dev/null
+++ b/docs/source/overview/tutorials/tutorials.rst
@@ -0,0 +1,16 @@
+Tutorials
+=========
+
+The following tutorials provide a brief introduction on some of the main features of `yadism`.
+These tutorials have four main objectives, namely to introduce the user on how to:
+
+* prepare the observable and theory cards required for any yadism computationcompute 
+* compute observables by convoluting yadism predictions to PDFs (Parton Distribution Functions)
+* tabulate the yadism predictions into fast-interpolation grids for later use
+* benchmark yadism with other DIS programs
+
+.. toctree::
+   :hidden:
+
+   Getting Started 
+   Compare to Data 

From 499d14ab80bc63ffb140c2e08db6a9e3105d463c Mon Sep 17 00:00:00 2001
From: Tanjona Rabemananjara 
Date: Thu, 25 Jan 2024 11:50:06 +0100
Subject: [PATCH 11/18] remove benchmark part w/ other programs for the time
 being

---
 docs/source/overview/tutorials/tutorials.rst | 1 -
 1 file changed, 1 deletion(-)

diff --git a/docs/source/overview/tutorials/tutorials.rst b/docs/source/overview/tutorials/tutorials.rst
index 37cec7167..48831d03a 100644
--- a/docs/source/overview/tutorials/tutorials.rst
+++ b/docs/source/overview/tutorials/tutorials.rst
@@ -7,7 +7,6 @@ These tutorials have four main objectives, namely to introduce the user on how t
 * prepare the observable and theory cards required for any yadism computationcompute 
 * compute observables by convoluting yadism predictions to PDFs (Parton Distribution Functions)
 * tabulate the yadism predictions into fast-interpolation grids for later use
-* benchmark yadism with other DIS programs
 
 .. toctree::
    :hidden:

From 21a46cda22228faca5d93d4a464ec0df8ea1a12d Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Thu, 25 Jan 2024 16:08:33 +0200
Subject: [PATCH 12/18] Improve data tutorial

---
 .../overview/tutorials/compare_data.ipynb     | 30 +++++++++----------
 docs/source/overview/tutorials/tutorials.rst  |  6 ++--
 2 files changed, 18 insertions(+), 18 deletions(-)

diff --git a/docs/source/overview/tutorials/compare_data.ipynb b/docs/source/overview/tutorials/compare_data.ipynb
index e088a001a..b35af40c2 100644
--- a/docs/source/overview/tutorials/compare_data.ipynb
+++ b/docs/source/overview/tutorials/compare_data.ipynb
@@ -7,7 +7,8 @@
    "source": [
     "# Compare to Experimental Data\n",
     "\n",
-    "In the following section, we'll show how to compare `yadism` predictions to an experimentally measured observable. As a test case, we use the combined measurement of two experioments [H1](https://en.wikipedia.org/wiki/H1_(particle_detector)) and [ZEUS](https://en.wikipedia.org/wiki/ZEUS_(particle_detector)) for the collision of an electron with a proton at a center of mass energy of $\\sqrt{s} = 318~\\rm{GeV}$.\n",
+    "We show how to compare `yadism` predictions to an HERA measurement (see [here](https://www.desy.de/h1zeus/herapdf20) for an overview),\n",
+    "specifically [this dataset](https://www.hepdata.net/record/ins1377206?version=1&table=Table%205).\n",
     "\n",
     "## Preparing the dataset\n",
     "\n",
@@ -166,7 +167,7 @@
    "source": [
     "## Computing the yadism predictions\n",
     "\n",
-    "We are now going to compute the `yadism` predictions at the same kinematic points as provided by the experimental measurements. In terms of theory, we are going to use the NNLO predictions with Fixed-Flavour Number Schemes (FFNS). As we saw in the previous tutorial, we first need to prepare the theory and observable cards."
+    "We are now going to compute the `yadism` predictions at the same kinematic points as provided by the experimental measurements. In terms of theory, we are going to use the NNLO predictions with a Fixed-Flavour Number Schemes (FFNS). First, we need to prepare the theory and observable cards."
    ]
   },
   {
@@ -178,7 +179,6 @@
    "source": [
     "import warnings\n",
     "import yadism\n",
-    "\n",
     "from eko import interpolation\n",
     "from yadbox.export import dump_pineappl_to_file"
    ]
@@ -275,7 +275,7 @@
     "        axis=1,\n",
     "    )\n",
     "\n",
-    "    # Update the observable &b kinematics in the `observable_card`\n",
+    "    # Update the observable & kinematics in the `observable_card`\n",
     "    obs_def = {\n",
     "        \"observables\" : {\"XSHERANC_total\": list(curobs.to_dict().values())}\n",
     "    } # As we saw in the previous tutorial, it has to be a dict[dict[list]]\n",
@@ -427,7 +427,7 @@
     }
    ],
    "source": [
-    "# Compute the predictions - slihgtly heavier due to complexity & nb datapoints\n",
+    "# Compute the predictions - slihgtly heavier due to complexity & number of datapoints\n",
     "compute_predicionts()"
    ]
   },
@@ -438,7 +438,7 @@
    "source": [
     "## Loading and comparing to HERA\n",
     "\n",
-    "Now that we have our pre-computed predictions in the form of PineAPPL grid, we can compare the results to the HERA measurements. To do so, we can load the grid and convolute it with a PDF set. As in the previous tutorial we're going to use the NNLO NNPDF4.0 set."
+    "Now, that we have our pre-computed predictions in the form of a PineAPPL grid, we can compare the results to the HERA measurements. To do so, we can load the grid and convolute it with a PDF set, specifically the NNLO NNPDF4.0 set."
    ]
   },
   {
@@ -505,6 +505,14 @@
     ")"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "16e935e5",
+   "metadata": {},
+   "source": [
+    "Finally, we can compare our theory predictions and the experimental data graphically."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 12,
@@ -514,7 +522,7 @@
    "source": [
     "import matplotlib.pyplot as plt\n",
     "\n",
-    "def plot_comparisons_q2(df: pd.DataFrame, q2_value: int = 300) -> None:\n",
+    "def plot_comparisons_q2(df: pd.DataFrame, q2_value: float = 300) -> None:\n",
     "    fig, ax = plt.subplots(figsize=(5, 3.75), layout=\"tight\")\n",
     "\n",
     "    # Select corresponding Q2 values\n",
@@ -551,14 +559,6 @@
    "source": [
     "plot_comparisons_q2(data_vs_yadism_df)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "8bcea746-3151-45c8-a222-3cf4119431c9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/docs/source/overview/tutorials/tutorials.rst b/docs/source/overview/tutorials/tutorials.rst
index 48831d03a..1e67957d5 100644
--- a/docs/source/overview/tutorials/tutorials.rst
+++ b/docs/source/overview/tutorials/tutorials.rst
@@ -2,10 +2,10 @@ Tutorials
 =========
 
 The following tutorials provide a brief introduction on some of the main features of `yadism`.
-These tutorials have four main objectives, namely to introduce the user on how to:
+These tutorials show how to:
 
-* prepare the observable and theory cards required for any yadism computationcompute 
-* compute observables by convoluting yadism predictions to PDFs (Parton Distribution Functions)
+* prepare the observable and theory cards required for any yadism computation
+* compute observables by convoluting yadism predictions to |PDF|
 * tabulate the yadism predictions into fast-interpolation grids for later use
 
 .. toctree::

From 96c7b3550ab36d373fa1769dae762e702a5b9e48 Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Thu, 25 Jan 2024 16:11:47 +0200
Subject: [PATCH 13/18] Fix typo

---
 docs/source/overview/tutorials/tutorials.rst | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/source/overview/tutorials/tutorials.rst b/docs/source/overview/tutorials/tutorials.rst
index 1e67957d5..fc7bd26a3 100644
--- a/docs/source/overview/tutorials/tutorials.rst
+++ b/docs/source/overview/tutorials/tutorials.rst
@@ -5,7 +5,7 @@ The following tutorials provide a brief introduction on some of the main feature
 These tutorials show how to:
 
 * prepare the observable and theory cards required for any yadism computation
-* compute observables by convoluting yadism predictions to |PDF|
+* compute observables by convoluting yadism predictions with a |PDF|
 * tabulate the yadism predictions into fast-interpolation grids for later use
 
 .. toctree::

From 4fccb875ee6780804302d0c1b48baa7d7f813dda Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Thu, 25 Jan 2024 16:21:33 +0200
Subject: [PATCH 14/18] Add more fixes for tutorials

---
 docs/source/overview/tutorials/.gitignore     |  2 ++
 .../overview/tutorials/compare_data.ipynb     | 32 +++++++++++++------
 2 files changed, 25 insertions(+), 9 deletions(-)
 create mode 100644 docs/source/overview/tutorials/.gitignore

diff --git a/docs/source/overview/tutorials/.gitignore b/docs/source/overview/tutorials/.gitignore
new file mode 100644
index 000000000..819863bc5
--- /dev/null
+++ b/docs/source/overview/tutorials/.gitignore
@@ -0,0 +1,2 @@
+*.pineappl.lz4
+*.dat
diff --git a/docs/source/overview/tutorials/compare_data.ipynb b/docs/source/overview/tutorials/compare_data.ipynb
index b35af40c2..4f910feef 100644
--- a/docs/source/overview/tutorials/compare_data.ipynb
+++ b/docs/source/overview/tutorials/compare_data.ipynb
@@ -167,7 +167,7 @@
    "source": [
     "## Computing the yadism predictions\n",
     "\n",
-    "We are now going to compute the `yadism` predictions at the same kinematic points as provided by the experimental measurements. In terms of theory, we are going to use the NNLO predictions with a Fixed-Flavour Number Schemes (FFNS). First, we need to prepare the theory and observable cards."
+    "We are now going to compute the `yadism` predictions at the same kinematic points as provided by the experimental measurements. First, we need to prepare the theory and observable cards."
    ]
   },
   {
@@ -398,15 +398,29 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "018cd3df32ff4caebcd78bafd13b9a27",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Output()"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
     {
      "data": {
       "text/html": [
        "
\n",
-       "\u001b[?25h
\n"
+       "\n"
       ],
       "text/plain": [
        "\n",
-       "\u001b[?25h"
+       "\u001b[?25h\r\u001b[1A\u001b[2K"
       ]
      },
      "metadata": {},
@@ -415,11 +429,11 @@
     {
      "data": {
       "text/html": [
-       "
took 55.93 s\n",
+       "
took 122.32 s\n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[36mtook \u001b[0m\u001b[1;36m55.93\u001b[0m\u001b[36m s\u001b[0m\n"
+       "\u001b[36mtook \u001b[0m\u001b[1;36m122.32\u001b[0m\u001b[36m s\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -462,7 +476,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "LHAPDF 6.5.0 loading /home/tanjona/miniconda3/envs/yadism/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
+      "LHAPDF 6.4.0 loading /home/felix/local/share/LHAPDF/NNPDF40_nnlo_as_01180/NNPDF40_nnlo_as_01180_0000.dat\n",
       "NNPDF40_nnlo_as_01180 PDF set, member #0, version 1; LHAPDF ID = 331100\n"
      ]
     }
@@ -547,7 +561,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "
"
       ]
@@ -563,9 +577,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "yadism-QljnF84o-py3.10",
    "language": "python",
-   "name": "python3"
+   "name": "yadism-qljnf84o-py3.10"
   },
   "language_info": {
    "codemirror_mode": {

From 3274964b53045729ef315c7bc0838c2b168bdaf3 Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Thu, 25 Jan 2024 16:43:05 +0200
Subject: [PATCH 15/18] Change data tutorial to ZM

---
 .../overview/tutorials/compare_data.ipynb     | 64 +++++++++++--------
 1 file changed, 36 insertions(+), 28 deletions(-)

diff --git a/docs/source/overview/tutorials/compare_data.ipynb b/docs/source/overview/tutorials/compare_data.ipynb
index 4f910feef..59ee6aaf3 100644
--- a/docs/source/overview/tutorials/compare_data.ipynb
+++ b/docs/source/overview/tutorials/compare_data.ipynb
@@ -22,7 +22,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "!wget -q https://data.nnpdf.science/yadism/HERA12B2_NCem.dat"
+    "!wget -q -N https://data.nnpdf.science/yadism/HERA12B2_NCem.dat"
    ]
   },
   {
@@ -186,34 +186,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "ff60baae-65ee-4544-af2d-3c7a23a5734d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "observables_card = {\n",
-    "    \"PolarizationDIS\": 0.0,\n",
-    "    \"ProjectileDIS\": \"electron\",\n",
-    "    \"PropagatorCorrection\": 0.0,\n",
-    "    \"TargetDIS\": \"proton\",\n",
-    "    \"interpolation_is_log\": True,\n",
-    "    \"interpolation_polynomial_degree\": 4,\n",
-    "    \"interpolation_xgrid\": interpolation.lambertgrid(60).tolist(),\n",
-    "    \"observables\": {\"XSHERANC_total\": []},\n",
-    "    \"prDIS\": \"NC\",\n",
-    "    \"NCPositivityCharge\": None,\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
    "id": "5920d43e-b8b4-496a-97c8-98b5c2325716",
    "metadata": {},
    "outputs": [],
    "source": [
     "theory_card = {\n",
     "    \"PTO\": 2,\n",
-    "    \"FNS\": \"FONLL-C\",\n",
+    "    \"FNS\": \"ZM-VFNS\",\n",
     "    \"DAMP\": 0,\n",
     "    \"IC\": 1,\n",
     "    \"IB\": 0,\n",
@@ -254,12 +233,33 @@
     "    \"global_nx\": 0,\n",
     "    \"EScaleVar\": 1,\n",
     "    \"kDIScThr\": 1.0,\n",
-    "    \"kDISbThr\": 4.0,\n",
+    "    \"kDISbThr\": 1.0,\n",
     "    \"kDIStThr\": 1.0,\n",
     "    \"n3lo_cf_variation\": 0,\n",
     "}"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "ff60baae-65ee-4544-af2d-3c7a23a5734d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "observables_card = {\n",
+    "    \"PolarizationDIS\": 0.0,\n",
+    "    \"ProjectileDIS\": \"electron\",\n",
+    "    \"PropagatorCorrection\": 0.0,\n",
+    "    \"TargetDIS\": \"proton\",\n",
+    "    \"interpolation_is_log\": True,\n",
+    "    \"interpolation_polynomial_degree\": 4,\n",
+    "    \"interpolation_xgrid\": interpolation.lambertgrid(60).tolist(),\n",
+    "    \"observables\": {\"XSHERANC_total\": []},\n",
+    "    \"prDIS\": \"NC\",\n",
+    "    \"NCPositivityCharge\": None,\n",
+    "}"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -401,7 +401,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "018cd3df32ff4caebcd78bafd13b9a27",
+       "model_id": "b913a8eaf91d4163baef0654dc9c0a8f",
        "version_major": 2,
        "version_minor": 0
       },
@@ -429,11 +429,11 @@
     {
      "data": {
       "text/html": [
-       "
took 122.32 s\n",
+       "
took 86.98 s\n",
        "
\n"
       ],
       "text/plain": [
-       "\u001b[36mtook \u001b[0m\u001b[1;36m122.32\u001b[0m\u001b[36m s\u001b[0m\n"
+       "\u001b[36mtook \u001b[0m\u001b[1;36m86.98\u001b[0m\u001b[36m s\u001b[0m\n"
       ]
      },
      "metadata": {},
@@ -561,7 +561,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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BAXBzcxO7nS7J1dUVAFBWVgYfH5/rOgzOP7MslJ5XjPlbc4xCGgBKNHWYvzUH6XnFInVGRNRMp9MBAJydnUXupGtr+SOpsbHxurbDoLaATi9g2Z7TEEwsaxlbtuc0dHpTFURE9sX7GYjLWj9/UYP6yJEjiI2NRUBAAGQyGT799NN263ft2oWxY8fC29sbHh4eiI6OxoEDB+zTLICsgspWe9J/JAAo1tQhq6DSbj0REVHnJmpQV1dXIzQ0FKmpqWbVHzlyBGPHjsX+/fuRnZ2NO++8E7Gxsfjhhx9s3Gmzsqq2Q7ojdURERNcialBPnDgRr7zyCu6//36z6letWoUlS5Zg+PDh6Nu3L1asWIG+fftiz549Nu60mY+70qp1RERSptMLyDz/Gz7LvYTM87/Z/Gu9WbNmQSaTtXpMmDABly9fhqenJ/7v//7PaJ3vvvsO3bp1wxdffAEA2Lx5s2E9uVyOnj17Yvbs2YYzsB2RQ5/1rdfrUVVVBS8vrzZr6uvrUV9fb3iu1Wo7/HqRIV7wVylRoqkz+T21DICfqnmqFhGRIxNrdsuECROwadMmozEXFxd4enrin//8J+bNm4eJEyeib9++qK2tRXx8PB577DGMGzfOUO/h4YH8/Hzo9XqcOHECs2fPxuXLl+36Vak1OXRQv/HGG7h69SoeeuihNmtSUlKwbNkyq7yeQi5DSoQH3kjLAwCjsG45ZWDx3SM4n5qIHFrL7JY/75C0zG5Z++gwm4W1i4sL/Pz8TC579NFHsWvXLsyaNQtff/01kpKS0NjYiNdff92oTiaTGbYREBCAp59+Gi+99BJqa2sN06YcicMG9bZt27Bs2TJ89tln8PHxabMuKSkJiYmJhuct9wDtkKIijLl3FMbUtfMd9A4lkJ8PBAV17DWIiER0rdktMjTPbhk7wE+UnZJ169Zh0KBBmDFjBj7++GMcPHgQ3bt3b3cdV1dX6PV6NDU12alL63LI6Vnbt2/HY489ho8++ggxMTHt1rq4uBjuPX3d96CuqADaC2mgeXlFRcdfg4hIRGLPbtm7dy+6d+9u9FixYoVhuY+PD5YvX47t27fj8ccfx6hRo9rd3s8//4x169YhIiIC7u7uNunZ1hxuj/rDDz/EnDlzsH37dkyaNEnsdoiIOhWxZ7fceeedWLt2rdHYH89D0ul02Lx5M9zc3HDs2DE0NTXByck4yjQaDbp37w69Xo+6ujqMHDkSGzdutEm/9iBqUF+9ehXnzp0zPC8oKEBubi68vLwQFBSEpKQkXLp0Ce+//z6A5sPd8fHxWL16NaKiolBSUgKg+bCGSqUS5T0QEXUmYs9uueGGG9CnT582l7/xxhu4cOECjh8/jtGjR2PFihVYunSpUY27uztycnIgl8vh7+/vkN9L/5Goh76PHz+OoUOHYujQoQCAxMREDB061PBDLy4uRlFRkaF+/fr1aGpqQkJCAvz9/Q2PhQsXitK/tdl7KgQR0Z+1zG5p69tnGZrP/hZjdsupU6eQnJyMtWvXon///li7di1eeeUV/Pjjj0Z1crkcffr0Qa9evRw+pAGR96jHjBkDQWg7jDZv3mz0/PDhw7ZtSES80QcRSYFCLkNy7ADM35oDGUzPbkmOHWCzE8nq6+sNR0tbODk54cYbb0R8fDweeOABPPDAAwCABx98EA8++CBmzZqFrKysVofAOwuHPJmss+GNPohISiYM8sfaR4fBT2V8eNtPpbTp1CwASE9PNzpi6u/vj5EjR2LFihW4dOkS1qxZY1SfmpqK4uJioxPOOhuZ0N4ubSek1WqhUqmg0WgsPwM8JwcID792XXY2MGyYWZvU6QWM/N+DbZ5l2XIRlW+eu4vzs4nILHV1dSgoKEBISAiUyo5/l6zTC8gqqERZVR183JsPd/PfIfO193uwJIs653ECW1GrAaWy/SlaSmVznZksmQoR3fsmC5olIro+CrmM/+5IAIPaEkFBzRczaW+etFpt0cVOxJ4KQURE0sagtlRQkFWvOib2VAgiIpI2BrXIIkO8ECZo0FRa3uaNPpx8vXmjDyKiLopBLTLFrxfxyao5UDTUt1mjc3aBImEkrx9ORNQFcXqW2Coq2g1pAM3Lef1wIqIuiUFNREQkYQxqIiIiCWNQExERSRiDmoiIOqVZs2Zh8uTJhudjxozBokWLROuno3jWNxERGSsqsuqFncwhCALGjh0LhUKBAwcOGC17++238cILLyAvLw89e/bs8Gvs2rUL3bp1u95W7Y5BTUREvysqAvr1u/alkvPzrRrWMpkMmzZtwuDBg/HOO+9g3rx5AICCggIsWbIEa9euva6QBgAvL8e8HgUPfYut5frh7bHw+uFERB1WUdF+SAPNy20wZTQwMBCrV6/G4sWLUVBQAEEQMHfuXIwdOxaHDx9GSEgIXF1d0a9fP6xevdpoXZ1Oh8TERNx444246aabsGTJkla3Uf7zoe+3334bffv2hVKphK+vL6ZMmWJUu2DBAixatAienp7w9fXFhg0bUF1djdmzZ8Pd3R19+vTB559/bvWfw58xqMXWcv3w7Oy2H1b+y5WISKri4+Nx9913Y86cOVizZg3y8vKwfv169OzZEx9//DFOnz6NpUuX4oUXXsBHH31kWG/lypXYvHkz3nvvPXzzzTeorKzE7t2723yd48eP4+mnn8bLL7+M/Px8pKenY9SoUUY1W7ZsgVqtRlZWFhYsWID58+dj6tSpGDFiBHJycjBu3DjExcWhpqbGZj8PAIDQxWg0GgGAoNFoxG6FiMgmamtrhdOnTwu1tbWWr5ydLQjAtR/Z2dZv/L9KS0sFtVotyOVyYffu3SZrEhIShAcffNDw3N/fX3jttdcMzxsbG4WePXsK9913n2Fs9OjRwsKFCwVBEIRPPvlE8PDwELRarcntjx49Whg5cqTheVNTk3DDDTcIcXFxhrHi4mIBgJCZmWlyG+39HizJIu5RExGRpPj4+GDevHno37+/4azt1NRUhIeHw9vbG927d8f69etRVFQEANBoNCguLkZUVJRhG05OToiIiGjzNcaOHYubb74ZvXr1QlxcHNLS0lrtGQ8ZMsTw3wqFAjfddBMGDx5sGPP19QUAlJWVXfd7bg+DmoiIJMfJyQlOTs3nO2/fvh2LFy/G3Llz8cUXXyA3NxezZ89GQ0NDh7fv7u6OnJwcfPjhh/D398fSpUsRGhqKK1euGGr+fIa4TCYzGpPJZAAAvV7f4T7MwaAmIiJJ+/bbbzFixAg8+eSTGDp0KPr06YPz588blqtUKvj7++O7774zjDU1NSE7O7vd7To5OSEmJgavvfYafvzxRxQWFuLgwYM2ex8dxelZREQkaX379sX777+PAwcOICQkBB988AG+//57hISEGGoWLlyIV199FX379sWtt96KN99802jv+M/27t2LCxcuYNSoUfD09MT+/fuh1+vRr18/O7wjy3CPmoiIfifBKaPz5s3DAw88gGnTpiEqKgq//fYbnnzySaOav/3tb4iLi0N8fDyio6Ph7u6O+++/v81t3njjjdi1axfuuusu9O/fH+vWrcOHH36IgQMH2vrtWEwmCH+aaNbJabVaqFQqaDQaeHh4iN0OEZHV1dXVoaCgACEhIVBeK3RNEeHKZJ1Re78HS7KIh76JiMhYUBCDWEJ46JuIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYg6qS42qUdyrHXFMp71TUTUyXTr1g0ymQzl5eXw9vY2XOqS7EMQBDQ0NKC8vBxyuRzOzs7XtT0GNRFRJ6NQKNCzZ0/8+uuvKCwsFLudLsvNzQ1BQUGQy6/v4DWDmoioE+revTv69u2LxsZGsVvpkhQKBZycnKxyNINBTUTUSSkUCigUCrHboOvEk8mIiIgkjEFNREQkYaIG9ZEjRxAbG4uAgADIZDJ8+umn11zn8OHDGDZsGFxcXNCnTx9s3rzZ5n0SERGJRdSgrq6uRmhoKFJTU82qLygowKRJk3DnnXciNzcXixYtwmOPPYYDBw7YuFMiIiJxiHoy2cSJEzFx4kSz69etW4eQkBCsXLkSANC/f3988803eOuttzB+/Hhbtdnl6fQCsgoqUVZVBx93JSJDvKCQc14mEZE9ONRZ35mZmYiJiTEaGz9+PBYtWtTmOvX19aivrzc812q1tmqvU0rPK8ayPadRrKkzjPmrlEiOHYAJg/xF7IyIqGtwqKAuKSmBr6+v0Zivry+0Wi1qa2vh6uraap2UlBQsW7bMXi12Koe//B5r0o7CC4DXH8ZlJcCa/DwoZ4zAmLHDxWqPiKhLcKig7oikpCQkJiYanmu1WgQGBorYkWPQFf6C6Htux96mti+WUJ/WDbqff4Yi+GY7dkZE1LU41PQsPz8/lJaWGo2VlpbCw8PD5N40ALi4uMDDw8PoQdd26sR5uLQT0gDg0tSIUyfO26kjIqKuyaGCOjo6GhkZGUZjX375JaKjo0XqqPOqrGmwah0REXWMqEF99epV5ObmIjc3F0Dz9Kvc3FwUFRUBaD5sPXPmTEP9E088gQsXLmDJkiU4c+YM3n77bXz00Ud45plnxGi/U/NyM+9uL+bWERFRx4ga1MePH8fQoUMxdOhQAEBiYiKGDh2KpUuXAgCKi4sNoQ0AISEh2LdvH7788kuEhoZi5cqV2LhxI6dm2cDAHiqr1hERUcfIhC52Z3GtVguVSgWNRsPvq9uTkwOEh1+7LjsbGDbM9v0QEXUilmSRQ31HTURE1NUwqImIiCSMQU2mqdWAUtl+jVLZXEdERDbT6S94Qh0UFATk5wMVFW3XqNXNdUREZDMMampbUBCDmIhIZDz0TUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDmJ3QBRhxUVARUV0OkFnLqkQWVNA7zcnDGwhwoKuQxQq4GgILG7JCK6LgxqckxFRUC/fkBdHRQAhpiqUSqB/HyGNRE5NB76JsdUUQHU1bVfU1fXXEdE5MAY1OSQdHrBqnVERFLFoCaHdOqSxqp1RERSxaAmh1RZ02DVOiIiqWJQk0PycnO2ah0RkVSJHtSpqakIDg6GUqlEVFQUsrKy2q1ftWoV+vXrB1dXVwQGBuKZZ55B3bVOKqJOZ2APlVXriIikStSg3rFjBxITE5GcnIycnByEhoZi/PjxKCsrM1m/bds2PP/880hOTsZPP/2Ed999Fzt27MALL7xg585JbAq5zKp1RERSJWpQv/nmm/jrX/+K2bNnY8CAAVi3bh3c3Nzw3nvvmaw/evQobr/9djzyyCMIDg7GuHHjMH369GvuhVMnpFY3z5Nuj1LZXEdE5MBEu+BJQ0MDsrOzkZSUZBiTy+WIiYlBZmamyXVGjBiBrVu3IisrC5GRkbhw4QL279+PuLi4Nl+nvr4e9fX1hudardZ6b4LEExTUfDETXpmMiDo50YK6oqICOp0Ovr6+RuO+vr44c+aMyXUeeeQRVFRUYOTIkRAEAU1NTXjiiSfaPfSdkpKCZcuWWbV3koigICAoqPnKZBFiN0NEZBuin0xmicOHD2PFihV4++23kZOTg127dmHfvn1Yvnx5m+skJSVBo9EYHhcvXrRjx0RERNdHtD1qtVoNhUKB0tJSo/HS0lL4+fmZXOell15CXFwcHnvsMQDA4MGDUV1djccffxwvvvgi5PLWf3e4uLjAxcXF+m+AiIjIDkTbo3Z2dkZ4eDgyMjIMY3q9HhkZGYiOjja5Tk1NTaswVigUAABB4KUiiYio8xH17lmJiYmIj49HREQEIiMjsWrVKlRXV2P27NkAgJkzZ6JHjx5ISUkBAMTGxuLNN9/E0KFDERUVhXPnzuGll15CbGysIbCJiIg6E1GDetq0aSgvL8fSpUtRUlKCsLAwpKenG04wKyoqMtqD/vvf/w6ZTIa///3vuHTpEry9vREbG4v/+Z//EestEBER2ZRM6GLHjLVaLVQqFTQaDTw8PMRuh4iIuiBLssihzvomIiLqahjUREREEsagJiIikjAGNRERkYQxqImIiCSMQU1ERCRhDGoiIiIJY1ATERFJmMVXJtu0aRO6d++OqVOnGo1//PHHqKmpQXx8vNWaI3JEOr2ArIJKlFXVwcddicgQr+b7YxMRdYDFQZ2SkoJ33nmn1biPjw8ef/xxBjV1ael5xVi25zSKNXWGMX+VEsmxAzBhkL+InRGRo7I4qIuKihASEtJq/Oabb0ZRUZFVmiJyRIe//B5r0o7CC4DXH8ZlJcCa/DwoZ4zAmLHDxWqPiByUxUHt4+ODH3/8EcHBwUbjJ06cwE033WStvogciq7wF0Tfczv2NjW2WVOf1g26n3+GIvhmO3ZGRI7O4pPJpk+fjqeffhqHDh2CTqeDTqfDwYMHsXDhQjz88MO26JFI8k6dOA+XdkIaAFyaGnHqxHk7dUREnYXFe9TLly9HYWEh7r77bjg5Na+u1+sxc+ZMrFixwuoNEjmCypoGq9YREbWwOKidnZ2xY8cOLF++HCdOnICrqysGDx6Mm2/m4TzqurzcnK1aR0TUwuKgbhEcHAxBENC7d2/DnjVRVzWwh8qqdURELSz+jrqmpgZz586Fm5sbBg4caDjTe8GCBXj11Vet3iCRIzB3njTnUxORpSwO6qSkJJw4cQKHDx+GUqk0jMfExGDHjh1WbY6IiKirs/iY9aeffoodO3bgtttug0z2+97BwIEDcf48z2glIiKyJov3qMvLy+Hj49NqvLq62ii4iboUtRr4wxEmk5TK5joiIgtYvEcdERGBffv2YcGCBQBgCOeNGzciOjraut0ROYqgICA/H6ioaLtGrW6uIyKygMVBvWLFCkycOBGnT59GU1MTVq9ejdOnT+Po0aP497//bYseiRxDUBCDmIiszuJD3yNHjkRubi6ampowePBgfPHFF/Dx8UFmZibCw8Nt0SMREVGXJRMEQRC7CXvSarVQqVTQaDTw8PAQux0iIuqCLMkii/eoc3JycPLkScPzzz77DJMnT8YLL7yAhgZeHpGIiMiaLA7qefPm4ezZswCACxcuYNq0aXBzc8PHH3+MJUuWWL1BIiKirszioD579izCwsIAAB9//DFGjx6Nbdu2YfPmzfjkk0+s3R8REVGXZnFQC4IAvV4PAPjqq69wzz33AAACAwNR0d7UFCIiIrKYxUEdERGBV155BR988AH+/e9/Y9KkSQCAgoIC+Pr6Wr1BIiKirszioF61ahWys7Px1FNP4cUXX0SfPn0AADt37sTtt99u9QaJiIi6MosvePLbb78hLy+v1fjrr7+ODRs2WKUpIiIiambxHvWECRPw7LPPorGx0TBWUVGBqVOnYunSpVZtjoiIqKuzOKgPHTqE3bt3Y/jw4Th9+jT27duHQYMGQaPRIDc31wYtEpE16PQCMs//hs9yLyHz/G/Q6bvUtY6IHJbFh75HjBiB3NxcPPHEExg2bBj0ej2WL1+OJUuW8O5ZRBKVnleMZXtOo1hTZxjzVymRHDsAEwb5i9gZEV2LxXvUQPNc6uPHj6Nnz55wcnJCfn4+ampqOtRAamoqgoODoVQqERUVhaysrHbrr1y5goSEBPj7+8PFxQW33HIL9u/f36HXJuoK0vOKMX9rjlFIA0CJpg7zt+YgPa9YpM6IyBwWB/Wrr76K6OhojB07Fnl5ecjKysIPP/yAIUOGIDMz06Jt7dixA4mJiUhOTkZOTg5CQ0Mxfvx4lJWVmaxvaGjA2LFjUVhYiJ07dyI/Px8bNmxAjx49LH0bRF2CTi9g3QeHMKDkHAb+6dEytu6DQzwMTiRlgoX8/PyE/fv3G401NDQIixcvFpydnS3aVmRkpJCQkGB4rtPphICAACElJcVk/dq1a4VevXoJDQ0NlrZtoNFoBACCRqPp8DaIHMXxI7lCraKbIABtPmoV3YTjR3LFbpWoS7Ekiyzeoz558iQmTpxoNNatWze8/vrr+OKLL8zeTkNDA7KzsxETE2MYk8vliImJaXPP/F//+heio6ORkJAAX19fDBo0CCtWrIBOp7P0bRB1CVW/FkOpa2y3RqlrRNWvPPxNJFUWn0ymVqvbXDZ69Gizt1NRUQGdTtfqama+vr44c+aMyXUuXLiAgwcPYsaMGdi/fz/OnTuHJ598Eo2NjUhOTja5Tn19Perr6w3PtVqt2T0SOTovN2er1hGR/XXoZDKx6PV6+Pj4YP369QgPD8e0adPw4osvYt26dW2uk5KSApVKZXgEBgbasWMicQ3sobJqHRHZn2hBrVaroVAoUFpaajReWloKPz8/k+v4+/vjlltugUKhMIz1798fJSUlbd4LOykpCRqNxvC4ePGi9d4EkcQp5OZNmTS3jojsT7SgdnZ2Rnh4ODIyMgxjer0eGRkZiI6ONrnO7bffjnPnzhnu3gU0TxXz9/eHs7PpQ3cuLi7w8PAwehARETkKUQ99JyYmYsOGDdiyZQt++uknzJ8/H9XV1Zg9ezYAYObMmUhKSjLUz58/H5WVlVi4cCHOnj2Lffv2YcWKFUhISBDrLRAREdmUxSeTWdO0adNQXl6OpUuXoqSkBGFhYUhPTzecYFZUVAS5/Pe/JQIDA3HgwAE888wzGDJkCHr06IGFCxfiueeeE+stEBER2ZRMEIQudaUDrVYLlUoFjUbDw+DU+RUVAf36AXV1bdcolUB+PhAUZL++iLo4S7JI1D1qIrKxoKDmEK6oaLtGrWZIE0kYg5qoswsKYhATOTCHmkdNRETU1TCoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCOD2LiESj0wvIKqhEWVUdfNyViAzx4g1CiP6EQU1EokjPK8ayPadRrPn9qmn+KiWSYwdgwiB/ETsjkhYGNRHZ3eEvv8eatKPwAuD1h3FZCbAmPw/KGSMwZuxwsdojkhQGNRHZla7wF0Tfczv2NjW2WVOf1g26n3+GIvhmO3ZGJE08mYyI7OrUifNwaSekAcClqRGnTpy3U0dE0sagJiK7qqxpsGodUWfHoCYiu/Jyc7ZqHVFnx6AmIrsa2ENl1Tqizo5BTUR2Ze48ac6nJmrGoCYiIpIwBjUREZGEMaiJyL7UakCpbL9GqWyuIyJe8ISI7CwoCMjPByoq2q5Rq5vriIhBTUQiCApiEBOZiYe+iYiIJIxBTUREJGEMaiIiIgljUBMREUkYTyYjIjJBpxeQVVCJsqo6+LgrERnixaulkSgY1EREf1RUhKPHfsI7RwpQcbXeMKzu7oJ5o0Iw4rb+PGOd7IpBTUTUoqgIur63YERDPUaYWp4K6JxdoPj5LMOa7IbfURMR/ZeurByKhvp2axQN9dCVldupIyIGNRGRwalLGqvWEVkDg5qI6L8qaxqsWkdkDQxqIqL/8nJztmodkTUwqImI/mtgD5VV64isgUFNRPRf5s6T5nxqsidJBHVqaiqCg4OhVCoRFRWFrKwss9bbvn07ZDIZJk+ebNsGiYiIRCJ6UO/YsQOJiYlITk5GTk4OQkNDMX78eJSVlbW7XmFhIRYvXow77rjDTp0SUaenVgNKZfs1SmVzHZGdyARBEMRsICoqCsOHD8eaNWsAAHq9HoGBgViwYAGef/55k+vodDqMGjUKc+bMwddff40rV67g008/Nev1tFotVCoVNBoNPDw8rPU2iKizKCoCKiraXq5W82IndN0sySJRr0zW0NCA7OxsJCUlGcbkcjliYmKQmZnZ5novv/wyfHx8MHfuXHz99df2aJWIuoqgIAYxSYqoQV1RUQGdTgdfX1+jcV9fX5w5c8bkOt988w3effdd5ObmmvUa9fX1qK///UpDWq22w/0SERHZm+jfUVuiqqoKcXFx2LBhA9RmfkeUkpIClUpleAQGBtq4SyIiIusRdY9arVZDoVCgtLTUaLy0tBR+fn6t6s+fP4/CwkLExsYaxvR6PQDAyckJ+fn56N27t9E6SUlJSExMNDzXarUMayIichiiBrWzszPCw8ORkZFhmGKl1+uRkZGBp556qlX9rbfeipMnTxqN/f3vf0dVVRVWr15tMoBdXFzg4uJik/6JiOyOJ7t1OaLf5jIxMRHx8fGIiIhAZGQkVq1aherqasyePRsAMHPmTPTo0QMpKSlQKpUYNGiQ0fo33ngjALQaJyLqdIqKgH79gLq6tmuUSiA/n2HdiYge1NOmTUN5eTmWLl2KkpIShIWFIT093XCCWVFREeRyh/oqnYjINioq2g9poHl5RQWDuhMRfR61vXEeNRE5rJwcIDz82nXZ2cCwYbbvhzrMkizirioRkYPQ6c3brzK3jhwDg5qIyEGcuqSxah05BgY1EZGDqKxpsGodOQYGNRGRg/Byc7ZqHTkGBjURkYMY2ENl1TpyDAxqIiIHofDxhs65/Qs46ZxdoPDxtlNHZA+iz6MmIiIzBQVB8fNZHD32E945UoCKq7/fcEjd3QXzRoVgxG39OYe6k2FQExE5kqAgjAgKQtQUAVkFlSirqoOPuxKRIV5QyGXWex1eqlQyGNRERA5IIZchuvdNttk4L1UqKfyOmoiIjFlyqVKyOQY1ERGRhDGoiYjICC9VKi0MaiIiMsJLlUoLTyYjIiIjYl2qVKe38ZnsDopBTURERsS4VGl6XjGW7TmNYs3vJ7H5q5RIjh2ACYP8rfY6joiHvomIyIi9L1WanleM+VtzjEIaAEo0dZi/NQfpecVWeR1HxaAmIiIj9rxUqU4vYNme0zB1WlrL2LI9p7v0iWs89E1ERMbseKnSrILKVnvSfyQAKNbUIaug0nYXeJE4BjUREbVmp0uVllVd48IqFtZ1RgxqIiJqk00vVQrAx11p1brOiEFNRESiiQzxQpigQVNpucnvqWUAnHy9ERniZe/WJINBTUREolH8ehGfrJoDRUN9mzU6ZxcoEkZ22RuA8KxvIiIST0VFuyENoHl5F74BCIOaiIhIwhjUREREEsagJiIikjAGNRERkYQxqImIiCSMQU1ERCRhDGoiIhKPWg0or3HVMaWyua6L4gVPiIhIPEFBQH5++/Ok1eoue7ETgEFNRERiCwrq0kF8LTz0TUREJGEMaiIiIgljUBMREUmYJII6NTUVwcHBUCqViIqKQlZWVpu1GzZswB133AFPT094enoiJiam3XoiIiJHJnpQ79ixA4mJiUhOTkZOTg5CQ0Mxfvx4lJWVmaw/fPgwpk+fjkOHDiEzMxOBgYEYN24cLl26ZOfOiYiIbE8mCIKpe3XbTVRUFIYPH441a9YAAPR6PQIDA7FgwQI8//zz11xfp9PB09MTa9aswcyZM69Zr9VqoVKpoNFo4OHhcd39ExERWcqSLBJ1j7qhoQHZ2dmIiYkxjMnlcsTExCAzM9OsbdTU1KCxsRFeXl62apOIiEg0os6jrqiogE6ng6+vr9G4r68vzpw5Y9Y2nnvuOQQEBBiF/R/V19ejvv73m5JrtdqON0xERGRnon9HfT1effVVbN++Hbt374ayjUvQpaSkQKVSGR6BgYF27pKIiKjjRA1qtVoNhUKB0tJSo/HS0lL4+fm1u+4bb7yBV199FV988QWGDBnSZl1SUhI0Go3hcfHiRav0TkREZA+iBrWzszPCw8ORkZFhGNPr9cjIyEB0dHSb67322mtYvnw50tPTERER0e5ruLi4wMPDw+hBRETkKES/1ndiYiLi4+MRERGByMhIrFq1CtXV1Zg9ezYAYObMmejRowdSUlIAAP/7v/+LpUuXYtu2bQgODkZJSQkAoHv37ujevbto74OIiMgWRA/qadOmoby8HEuXLkVJSQnCwsKQnp5uOMGsqKgIcvnvO/5r165FQ0MDpkyZYrSd5ORk/OMf/7Bn60RE1EXo9AKyCipRVlUHH3clIkO8oJDL7PLaos+jtjfOoyYiIkuk5xVj2Z7TKNbUGcb8VUokxw7AhEH+Hdqmw8yjJiIikrL0vGLM35pjFNIAUKKpw/ytOUjPK7Z5DwxqIiIiE3R6Acv2nIapw84tY8v2nIZOb9sD06J/R01ERCRFWQWVkF0swsCati+U9R+tB7IKKhHd+yab9cGgJiIiMqHq7HkcXD8PSl1jmzV1im44EjsQsGFQ89A3ERGRCX4NV9sNaQBQ6hrh13DVpn0wqImIiEwY2ENl1bqOYlATERGZYO48aVvPp2ZQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZEpajWgVLZfo1Q219kQL3hCRERkSlAQkJ8PVFS0XaNWN9fZEIOaiIioLUFBNg/ia+GhbyIiIgljUBMREUkYg5qIiEjCGNREREQS1uVOJhOE5ht8a7Vt31+UiIjIlloyqCWT2tPlgrqqqgoAEBgYKHInRETU1VVVVUGlav/uWzLBnDjvRPR6PS5fvgx3d3fIZNa748nw4cPx/fffi74tS9e1pN7c2mvVabVaBAYG4uLFi/Dw8DC7V0djzc+EVHuw1vbt+Zm3dB1zavmZb8bPvPkiIiJw8OBBBAQEQC5v/1voLrdHLZfL0bNnT6tvV6FQWO1/wOvZlqXrWlJvbq25dR4eHp36Hy1rfiak2oO1tm/Pz7yl65hTy898M37mzefk5GR2FvFkMitJSEiQxLYsXdeSenNrrfmzcGRS+DnYugdrbd+en3lL1zGnVgq/aymQws+hM37mu9yhbxKfVquFSqWCRqMR/a9vInvgZ56uB/eoye5cXFyQnJwMFxcXsVshsgt+5ul6cI+aiIhIwrhHTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNQkWRcvXsSYMWMwYMAADBkyBB9//LHYLRHZ3P333w9PT09MmTJF7FZIInjWN0lWcXExSktLERYWhpKSEoSHh+Ps2bO44YYbxG6NyGYOHz6MqqoqbNmyBTt37hS7HZIA7lGTZPn7+yMsLAwA4OfnB7VajcrKSnGbIrKxMWPGwN3dXew2SEIY1NRhR44cQWxsLAICAiCTyfDpp5+2qklNTUVwcDCUSiWioqKQlZXVodfKzs6GTqfjXc9IVPb8zBO1YFBTh1VXVyM0NBSpqakml+/YsQOJiYlITk5GTk4OQkNDMX78eJSVlRlqwsLCMGjQoFaPy5cvG2oqKysxc+ZMrF+/3ubviag99vrMExkRiKwAgLB7926jscjISCEhIcHwXKfTCQEBAUJKSorZ262rqxPuuOMO4f3337dWq0RWYavPvCAIwqFDh4QHH3zQGm1SJ8A9arKJhoYGZGdnIyYmxjAml8sRExODzMxMs7YhCAJmzZqFu+66C3FxcbZqlcgqrPGZJzKFQU02UVFRAZ1OB19fX6NxX19flJSUmLWNb7/9Fjt27MCnn36KsLAwhIWF4eTJk7Zol+i6WeMzDwAxMTGYOnUq9u/fj549ezLkCU5iN0DUlpEjR0Kv14vdBpFdffXVV2K3QBLDPWqyCbVaDYVCgdLSUqPx0tJS+Pn5idQVke3wM0+2wqAmm3B2dkZ4eDgyMjIMY3q9HhkZGYiOjhaxMyLb4GeebIWHvqnDrl69inPnzhmeFxQUIDc3F15eXggKCkJiYiLi4+MRERGByMhIrFq1CtXV1Zg9e7aIXRN1HD/zJAqxTzsnx3Xo0CEBQKtHfHy8oeaf//ynEBQUJDg7OwuRkZHCsWPHxGuY6DrxM09i4LW+iYiIJIzfURMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1ERGRhDGoiYiIJIxBTUREJGEMaiIiIgljUBMREUkYg5qIiEjCGNREREQSxqAmIiKSMAY1EZmlvLwcfn5+WLFihWHs6NGjcHZ2NroHMxFZF++eRURm279/PyZPnoyjR4+iX79+CAsLw3333Yc333xT7NaIOi0GNRFZJCEhAV999RUiIiJw8uRJfP/993BxcRG7LaJOi0FNRBapra3FoEGDcPHiRWRnZ2Pw4MFit0TUqfE7aiKyyPnz53H58mXo9XoUFhaK3Q5Rp8c9aiIyW0NDAyIjIxEWFoZ+/fph1apVOHnyJHx8fMRujajTYlATkdmeffZZ7Ny5EydOnED37t0xevRoqFQq7N27V+zWiDotHvomIrMcPnwYq1atwgcffAAPDw/I5XJ88MEH+Prrr7F27Vqx2yPqtLhHTUREJGHcoyYiIpIwBjUREZGEMaiJiIgkjEFNREQkYQxqIiIiCWNQExERSRiDmoiISMIY1ERERBLGoCYiIpIwBjUREZGEMaiJiIgkjEFNREQkYf8PFXtC3MGkxfoAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "
"
       ]
@@ -573,6 +573,14 @@
    "source": [
     "plot_comparisons_q2(data_vs_yadism_df)"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "6eeb13ce",
+   "metadata": {},
+   "source": [
+    "Note that we are using the ZM-VFNS here, so we don't expect perfect agreement as heavy quark effects are only entering through the PDF evolution."
+   ]
   }
  ],
  "metadata": {

From 387795b4af5646164594fedec0dcf25e3a9c9b6c Mon Sep 17 00:00:00 2001
From: Felix Hekhorn 
Date: Fri, 26 Jan 2024 10:58:44 +0200
Subject: [PATCH 16/18] Add FFN0 to docs

---
 docs/source/shared/abbreviations.rst |  4 ++++
 docs/source/theory/fns.rst           | 23 +++++++++++++++++++----
 2 files changed, 23 insertions(+), 4 deletions(-)

diff --git a/docs/source/shared/abbreviations.rst b/docs/source/shared/abbreviations.rst
index 3afcf2af1..2a4e7657c 100644
--- a/docs/source/shared/abbreviations.rst
+++ b/docs/source/shared/abbreviations.rst
@@ -141,6 +141,10 @@
 
    eko
 
+.. |pineko| raw:: html
+
+   pineko
+
 .. |banana| raw:: html
 
    banana
diff --git a/docs/source/theory/fns.rst b/docs/source/theory/fns.rst
index 9ff3c9cff..14ac5c58f 100644
--- a/docs/source/theory/fns.rst
+++ b/docs/source/theory/fns.rst
@@ -28,6 +28,7 @@ unpolarized :ref:`kinds`).
 
 FFNS
 ----
+
 As the name |FFNS| suggests we are considering a fixed number of flavors
 :math:`n_f=n_l+1` with :math:`n_l` light flavors and **1 (and only 1) heavy
 flavor** with a finite mass :math:`m`. The number of light quarks :math:`n_l` is
@@ -119,12 +120,26 @@ This scheme is adequate for :math:`Q^2\gg m^2`.
 patches in which :math:`n_f` is constant (and they are of course different from
 the quark masses, that are always considered to be zero or infinite).
 
+FFN0
+----
+
+This is the high-virtuality limit :math:`Q^2 \gg m^2` of the |FFNS|, where only the
+collinear logs :math:`\log(Q^2/m^2)` are retained, but all power-like heavy quark mass
+corrections are neglected. These collinear logs are the finite expansion of the
+|DGLAP| evolution if the heavy quark would be considered massless. Thus these
+terms are the overlap between the |FFNS| using :math:`n_l` light quarks and one
+heavy quark and |FFNS| using :math:`n_l+1` light quarks.
+These terms are needed in the construction of the FONLL scheme :cite:`forte-fonll`.
+
+
 FONLL
 -----
-| FONLL :cite:`forte-fonll` is a |GM-VFNS| that includes parts of the |DGLAP| equations into the
-  matching conditions.
-| That is: two different schemes are considered, and they are matched at a given
-  scale, accounting for the resummation of collinear logarithms.
+
+FONLL :cite:`forte-fonll` is a |GM-VFNS| that includes parts of the |DGLAP| equations into the
+matching conditions, i.e., two different schemes are considered, and they are matched at a given
+scale, accounting for the resummation of collinear logarithms.
+Hence, FONLL relies on both coefficient functions and evolution kernels, so yadism is not
+solely responsible for the scheme, but also |eko| and |pineko|.
 
 In the original paper the prescription is only presented for the charm
 contributions, but we extend it here to an arbitrary quark.

From b4df4527b4a2439a22bef50cc4d646526653729f Mon Sep 17 00:00:00 2001
From: RoyStegeman 
Date: Fri, 26 Jan 2024 11:21:01 +0000
Subject: [PATCH 17/18] tiny changes to docs

---
 docs/source/dev-tools/benchmarks.rst          | 10 ++++-----
 .../overview/tutorials/getting_started.ipynb  | 22 +++++++++----------
 2 files changed, 16 insertions(+), 16 deletions(-)

diff --git a/docs/source/dev-tools/benchmarks.rst b/docs/source/dev-tools/benchmarks.rst
index 09706a53d..275923c14 100644
--- a/docs/source/dev-tools/benchmarks.rst
+++ b/docs/source/dev-tools/benchmarks.rst
@@ -137,16 +137,16 @@ APFEL++
 -------
 
 
-|APFEL++| is a C++ rewriting of the Fortran 77 evolution code |APFEL|. However, |APFEL++| is based on a completely new code design and 
-guarantees a better performance along with a more optimal memory management. 
+|APFEL++| is a C++ rewriting of the Fortran 77 evolution code |APFEL|. However, |APFEL++| is based on a completely new code design and
+guarantees a better performance along with a more optimal memory management.
 |APFEL++| is suitable for a wide range of tasks: from the solution of the DGLAP evolution equations to the computation of DIS
-and single-inclusive-annihilation cross sections. 
+and single-inclusive-annihilation cross sections.
 
-|APFEL++| is also currently interfaced to PARTONS, a software dedicated to the phenomenology of Generalised Parton Distributions (GPDs) and TMDs, 
+|APFEL++| is also currently interfaced to PARTONS, a software dedicated to the phenomenology of Generalised Parton Distributions (GPDs) and TMDs,
 and to xFitter.
 
 
 SF in APFEL++
 ~~~~~~~~~~~~~
 
-The |APFEL++| definitions follows the one of |APFEL|
+The |APFEL++| definitions follow the ones of |APFEL|
diff --git a/docs/source/overview/tutorials/getting_started.ipynb b/docs/source/overview/tutorials/getting_started.ipynb
index b9124dda5..581990ef8 100644
--- a/docs/source/overview/tutorials/getting_started.ipynb
+++ b/docs/source/overview/tutorials/getting_started.ipynb
@@ -112,7 +112,7 @@
    "source": [
     "The `observables` key in the `observable_card` (which is also a dictionary) can contain multiple elements whose keys must represent structure functions or cross-sections. For the list of available observables, refer to the following [part](https://yadism.readthedocs.io/en/latest/theory/intro.html#) of the documentation.\n",
     "\n",
-    "Similarly, below is an example of a theory card:"
+    "Similarly, below is an example of a `theory card` defining the theory parameters:"
    ]
   },
   {
@@ -125,7 +125,7 @@
     "theory_card = {\n",
     "    # QCD perturbative order\n",
     "    \"PTO\": 2,  # perturbative order in alpha_s: 0 = LO (alpha_s^0), 1 = NLO (alpha_s^1) ...\n",
-    "   \n",
+    "\n",
     "    # SM parameters and masses\n",
     "    \"CKM\": \"0.97428 0.22530 0.003470 0.22520 0.97345 0.041000 0.00862 0.04030 0.999152\",  # CKM matrix elements\n",
     "    \"GF\": 1.1663787e-05,  # [GeV^-2] Fermi coupling constant\n",
@@ -139,29 +139,29 @@
     "    \"mc\": 1.51,  # [GeV] charm mass\n",
     "    \"mb\": 4.92,  # [GeV] bottom mass\n",
     "    \"mt\": 172.5,  # [GeV] top mass\n",
-    "    \n",
+    "\n",
     "    # Flavor number scheme settings\n",
     "    \"FNS\": \"FFNS\",  # Flavour Number Scheme, options: \"FFNS\", \"FFN0\", \"ZM-VFNS\"\n",
     "    \"NfFF\": 4,  # (fixed) number of running flavors, only for FFNS or FFN0 schemes\n",
     "    \"Q0\": 1.65,  # [GeV] reference scale for the flavor patch determination\n",
     "    \"nf0\": 4,  # number of active flavors at the Q0 reference scale\n",
-    "    \n",
+    "\n",
     "    # Alphas settings and boundary conditions\n",
     "    \"Qref\": 91.2,  # [GeV] reference scale for the alphas value\n",
     "    \"nfref\": 5,  # number of active flavors at the reference scale Qref\n",
     "    \"alphas\": 0.118,  # alphas value at the reference scale\n",
     "    \"MaxNfAs\": 5,  # maximum number of flavors in running of strong coupling\n",
     "    \"QED\": 0,  # QED correction to running of strong coupling: 0 = disabled, 1 = allowed\n",
-    "    \n",
-    "    # Scale Variations \n",
+    "\n",
+    "    # Scale Variations\n",
     "    \"XIF\": 1.0,  # ratio of factorization scale over the hard scattering scale\n",
     "    \"XIR\": 1.0,  # ratio of renormalization scale over the hard scattering scale\n",
-    "    \n",
+    "\n",
     "    # Other settings\n",
-    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed \n",
+    "    \"IC\": 1,  # 0 = perturbative charm only, 1 = intrinsic charm allowed\n",
     "    \"TMC\": 1,  # include target mass corrections: 0 = disabled, 1 = leading twist, 2 = higher twist approximated, 3 = higher twist exact\n",
     "    \"n3lo_cf_variation\": 0,  # N3LO coefficient functions variation: -1 = lower bound, 0 = central , 1 = upper bound\n",
-    "    \n",
+    "\n",
     "    # Other EKO settings, not relevant for Yadism\n",
     "    \"HQ\": \"POLE\",  # heavy quark mass scheme (not yet implemented in yadism)\n",
     "    \"MaxNfPdf\": 5,  # maximum number of flavors in running of PDFs (ignored by yadism)\n",
@@ -174,7 +174,7 @@
    "id": "169b82a0-abdd-4687-9ffe-9df38446a550",
    "metadata": {},
    "source": [
-    "Note that a template observable card is provided by `yadmark` and contains the default `yadism` values. One can thus just start from the default card and overwrite the values."
+    "Note that a template observable card is provided by `yadmark` and contains the default `yadism` values. One can thus start from the default card and overwrite the values."
    ]
   },
   {
@@ -624,7 +624,7 @@
     "# Read the pineappl grid saved earlier\n",
     "grid = pineappl.grid.Grid.read(\"./outputgrid_XSHERANCAVG_charm.pineappl.lz4\")\n",
     "\n",
-    "# Convolute the grid with the same PDF as above\n",
+    "# Convolute the grid with the same PDF as above, 2212 is the PID of the proton\n",
     "results = grid.convolute_with_one(2212, pdf.xfxQ2, pdf.alphasQ2)"
    ]
   },

From aa5ae5e62691b3463d07e183ac6e4ff3c0691f2d Mon Sep 17 00:00:00 2001
From: RoyStegeman 
Date: Fri, 26 Jan 2024 11:26:42 +0000
Subject: [PATCH 18/18] fix typo in docs

---
 docs/source/overview/tutorials/compare_data.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/docs/source/overview/tutorials/compare_data.ipynb b/docs/source/overview/tutorials/compare_data.ipynb
index 59ee6aaf3..0f7eef127 100644
--- a/docs/source/overview/tutorials/compare_data.ipynb
+++ b/docs/source/overview/tutorials/compare_data.ipynb
@@ -284,7 +284,7 @@
     "    with warnings.catch_warnings():\n",
     "        warnings.simplefilter(\"ignore\") # suppress noisy warnings\n",
     "        out = yadism.run_yadism(theory_card, observables_card)\n",
-    "        \n",
+    "\n",
     "    # Dump computations as a pineappl grid for later use\n",
     "    dump_pineappl_to_file(\n",
     "        out, \"HERA_NC_318GEV_EM_SIGMARED.pineappl.lz4\", \"XSHERANC_total\"\n",
@@ -441,7 +441,7 @@
     }
    ],
    "source": [
-    "# Compute the predictions - slihgtly heavier due to complexity & number of datapoints\n",
+    "# Compute the predictions - slightly heavier due to complexity & number of datapoints\n",
     "compute_predicionts()"
    ]
   },