enh: add zfit physics

Author: jonas-eschle

_website/tutorials/introduction/upgrade_guide_020.ipynb

@@ -24,6 +24,7 @@
     "# standard imports\n",
     "import zfit\n",
     "import zfit.z.numpy as znp  # use this \"numpy-like\" for mathematical operations\n",
+    "import zfit_physics as zphys  # physics module, with new physics-inspired PDFs\n",
     "from zfit import z"
    ]
   },
@@ -35,6 +36,8 @@
    "outputs": [],
    "source": [
     "# example usage of the numpy-like backend, use it if possible\n",
+    "\n",
+    "\n",
     "@z.function\n",
     "def maximum(x, y):\n",
     "    return znp.maximum(x, y)\n",
@@ -133,7 +136,7 @@
    "outputs": [],
    "source": [
     "# this allows, for example, for a more intuitive way\n",
-    "np.linspace(*obs12.v1.limits, 7)"
+    "np.linspace(*obs12.v1.limits, num=7)"
    ]
   },
   {
@@ -205,7 +208,7 @@
    "source": [
     "## PDFs\n",
     "\n",
-    "- there are a plethora of new PDFs, mostly covering physics inspired use-cases. Amongst the interesting ones are a `GeneralizedCB`, a more general version of the `DoubleCB` that should be preferred in the future. Also a Voigt profile is available, Bernstein polynomials, QGauss, GaussExpTail, etc.\n",
+    "- there are a plethora of new PDFs, mostly covering physics inspired use-cases. Amongst the interesting ones are a `GeneralizedCB`, a more general version of the `DoubleCB` that should be preferred in the future. A Voigt profile is available, Bernstein polynomials, QGauss, GaussExpTail, etc. and in [zfit-physics](https://zfit.readthedocs.io/en/latest/user_api/zfit.pdf.html#physics-pdfs) HEP specific PDFS , from `CMSShape`, `Cruijff`, `Novosibirsk` and more. \n",
     "- the `TruncatedPDF` has been added to allow for a more flexible way of truncating a PDF. Any PDF can be converted to a truncated version using `to_truncated` (which, by default, truncates to the limits of the space).\n",
     "- PDFs have a new `plot` method that allows for a quick plotting of the PDF (it takes an \"obs\" argument that allows to simply project it!). This is still experimental and may changes, the main purpose is to allow for a quick check of the PDF in interactive environments. The function is fully compatible with matplotlib and takes an `ax` argument, it also allows to pass through any keyword arguments to the plotting function."
    ]
@@ -217,7 +220,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "# all the new PDFs"
+    "# all the new PDFs\n",
+    "print(zfit.pdf.__all__)"
    ]
   },
   {
@@ -226,6 +230,16 @@
    "id": "18",
    "metadata": {},
    "outputs": [],
+   "source": [
+    "print(zphys.pdf.__all__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "19",
+   "metadata": {},
+   "outputs": [],
    "source": [
     "# create a PDF\n",
     "pdf = zfit.pdf.Gauss(\n",
@@ -240,7 +254,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "19",
+   "id": "20",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -251,7 +265,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "20",
+   "id": "21",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -261,7 +275,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "21",
+   "id": "22",
    "metadata": {},
    "source": [
     "## Loss and minimizer\n",
@@ -281,7 +295,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "22",
+   "id": "23",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -294,7 +308,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "23",
+   "id": "24",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -304,7 +318,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "24",
+   "id": "25",
    "metadata": {},
    "source": [
     "## Result\n",
@@ -317,7 +331,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "25",
+   "id": "26",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -330,7 +344,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "26",
+   "id": "27",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -341,7 +355,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "27",
+   "id": "28",
    "metadata": {},
    "source": [
     "## Serialization\n",
@@ -357,7 +371,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "28",
+   "id": "29",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -368,7 +382,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "29",
+   "id": "30",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -380,7 +394,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "30",
+   "id": "31",
    "metadata": {},
    "source": [
     "## Parameters as arguments\n",
@@ -393,7 +407,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "31",
+   "id": "32",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -408,7 +422,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "32",
+   "id": "33",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -431,7 +445,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "33",
+   "id": "34",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -444,11 +458,13 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "34",
+   "id": "35",
    "metadata": {},
    "outputs": [],
    "source": [
     "# creating a PDF looks also different, but here we use the name of the parametrization and the axis (integers)\n",
+    "\n",
+    "\n",
     "class MyGauss2D(zfit.pdf.ZPDF):\n",
     "    _PARAMS = (\"mu\", \"sigma\")\n",
     "    _N_OBS = 2\n",
@@ -465,7 +481,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "35",
+   "id": "36",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -476,7 +492,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "36",
+   "id": "37",
    "metadata": {},
    "outputs": [],
    "source": []