{
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  {
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"
    },
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Introduction to zfit\n",
    "\n",
    "In this notebook, we will have a walk through the main components of zfit and their features. Especially the extensive model building part will be discussed separately.\n",
    "zfit consists of 5 mostly independent parts. Other libraries can rely on this parts to do plotting or statistical inference, such as hepstats does. Therefore we will discuss two libraries in this tutorial: zfit to build models, data and a loss, minimize it and get a fit result and hepstats, to use the loss we built here and do inference.\n",
    "\n",
    "<img src=\"attachment:screenshot%20from%202020-07-16%2014-29-15.png\" style=\"max-width:50%\">\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Data\n",
    "\n",
    "This component in general plays a minor role in zfit: it is mostly to provide a unified interface for data.\n",
    "\n",
    "Preprocessing is therefore not part of zfit and should be done beforehand. Python offers many great possibilities to do so (e.g. Pandas).\n",
    "\n",
    "zfit `Data` can load data from various sources, most notably from Numpy, Pandas DataFrame, TensorFlow Tensor and ROOT (using uproot). It is also possible, for convenience, to convert it directly `to_pandas`. The constructors are named `from_numpy`, `from_root` etc."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "import zfit\n",
    "from zfit import z\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "A `Data` needs not only the data itself but also the observables: the human readable string identifiers of the axes (corresponding to \"columns\" of a Pandas DataFrame). It is convenient to define the `Space` not only with the observable but also with a limit: this can directly be re-used as the normalization range in the PDF.\n",
    "\n",
    "First, let's define our observables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "obs = zfit.Space('obs1', (-5, 10))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "This `Space` has limits. Next to the effect of handling the observables, we can also play with the limits: multiple `Spaces` can be added to provide disconnected ranges. More importantly, `Space` offers functionality:\n",
    "- limit1d: return the lower and upper limit in the 1 dimensional case (raises an error otherwise)\n",
    "- rect_limits: return the n dimensional limits\n",
    "- area(): calculate the area (e.g. distance between upper and lower)\n",
    "- inside(): return a boolean Tensor corresponding to whether the value is _inside_ the `Space`\n",
    "- filter(): filter the input values to only return the one inside"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "size_normal = 10000\n",
    "data_normal_np = np.random.normal(size=size_normal, scale=2)\n",
    "\n",
    "data_normal = zfit.Data.from_numpy(obs=obs, array=data_normal_np)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The main functionality is\n",
    "- nevents: attribute that returns the number of events in the object\n",
    "- data_range: a `Space` that defines the limits of the data; if outside, the data will be cut\n",
    "- n_obs: defines the number of dimensions in the dataset\n",
    "- with_obs: returns a subset of the dataset with only the given obs\n",
    "- weights: event based weights\n",
    "\n",
    "Furthermore, `value` returns a Tensor with shape `(nevents, n_obs)`.\n",
    "\n",
    "To retrieve values, in general `z.unstack_x(data)` should be used; this returns a single Tensor with shape (nevents) or a list of tensors if `n_obs` is larger then 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "We have 9946 events in our dataset with the minimum of -4.978826801974078"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(f\"We have {data_normal.nevents} events in our dataset with the minimum of {np.min(data_normal.unstack_x())}\")  # remember! The obs cut out some of the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 5,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_normal.n_obs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Model\n",
    "\n",
    "Building models is by far the largest part of zfit. We will therefore cover an essential part, the possibility to build custom models, in an extra chapter. Let's start out with the idea that you define your parameters and your observable space; the latter is the expected input data.\n",
    "\n",
    "There are two types of models in zfit:\n",
    "- functions, which are rather simple and \"underdeveloped\"; their usage is often not required.\n",
    "- PDF that are function which are normalized (over a specified range); this is the main model and is what we gonna use throughout the tutorials.\n",
    "\n",
    "A PDF is defined by\n",
    "\n",
    "\\begin{align}\n",
    "\\mathrm{PDF}_{f(x)}(x; \\theta) = \\frac{f(x; \\theta)}{\\int_{a}^{b} f(x; \\theta)}\n",
    "\\end{align}\n",
    "\n",
    "where a and b define the normalization range (`norm_range`), over which (by inserting into the above definition) the integral of the PDF is unity.\n",
    "\n",
    "zfit has a modular approach to things and this is also true for models. While the normalization itself (e.g. what are parameters, what is normalized data) will already be pre-defined in the model, models are composed of functions that are transparently called inside. For example, a Gaussian would usually be implemented by writing a Python function `def gauss(x, mu, sigma)`, which does not care about the normalization and then be wrapped in a PDF, where the normalization and what is a parameter is defined.\n",
    "\n",
    "In principle, we can go far by using simply functions (e.g. [TensorFlowAnalysis/AmpliTF](https://github.com/apoluekt/AmpliTF) by Anton Poluektov uses this approach quite successfully for Amplitude Analysis), but this design has limitations for a more general fitting library such as zfit (or even [TensorWaves](https://github.com/ComPWA/tensorwaves), being built on top of AmpliTF).\n",
    "The main thing is to keep track of the different ordering of the data and parameters, especially the dependencies. \n",
    "\n",
    "\n",
    "Let's create a simple Gaussian PDF. We already defined the `Space` for the data before, now we only need the parameters. This are a different object than a `Space`.\n",
    "\n",
    "### Parameter\n",
    "A `Parameter` (there are different kinds actually, more on that later) takes the following arguments as input:\n",
    "`Parameter(human readable name, initial value[, lower limit, upper limit])` where the limits are recommended but not mandatory. Furthermore, `step_size` can be given (which is useful to be around the given uncertainty, e.g. for large yields or small values it can help a lot to set this). Also, a `floating` argument is supported, indicating whether the parameter is allowed to float in the fit or not (just omitting the limits does _not_ make a parameter constant).\n",
    "\n",
    "Parameters have a unique name. This is served as the identifier for e.g. fit results. However, a parameter _cannot_ be retrieved by its string identifier (its name) but the object itself should be used. In places where a parameter maps to something, the object itself is needed, not its name."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "mu = zfit.Parameter('mu', 1, -3, 3, step_size=0.2)\n",
    "sigma_num = zfit.Parameter('sigma42', 1, 0.1, 10, floating=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "These attributes can be changed:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sigma is float: False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sigma is float: True"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(f\"sigma is float: {sigma_num.floating}\")\n",
    "sigma_num.floating = True\n",
    "print(f\"sigma is float: {sigma_num.floating}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "*PITFALL NOTEBOOKS: since the parameters have a unique name, a second parameter with the same name cannot be created; the behavior is undefined and therefore it raises an error.\n",
    "While this does not pose a problem in a normal Python script, it does in a Jupyter-like notebook, since it is an often practice to \"rerun\" a cell as an attempt to \"reset\" things. Bear in mind that this does not make sense, from a logic point of view. The parameter already exists. Best practice: write a small wrapper, do not rerun the parameter creation cell or simply rerun the notebook (restart kernel & run all). For further details, have a look at the discussion and arguments [here](https://github.com/zfit/zfit/issues/186)*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Now we have everything to create a Gaussian PDF:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "gauss = zfit.pdf.Gauss(obs=obs, mu=mu, sigma=sigma_num)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Since this holds all the parameters and the observables are well defined, we can retrieve them"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 9,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.n_obs  # dimensions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('obs1',)"
      ]
     },
     "execution_count": 10,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<zfit Space obs=('obs1',), axes=(0,), limits=(array([[-5.]]), array([[10.]]))>"
      ]
     },
     "execution_count": 11,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.space"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<zfit Space obs=('obs1',), axes=(0,), limits=(array([[-5.]]), array([[10.]]))>"
      ]
     },
     "execution_count": 12,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.norm_range"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "As we've seen, the `obs` we defined is the `space` of Gauss: this acts as the default limits whenever needed (e.g. for sampling). `gauss` also has a `norm_range`, which equals by default as well to the `obs` given, however, we can explicitly change that with `set_norm_range`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We can also access the parameters of the PDF in two ways, depending on our intention: \n",
    "either by _name_ (the parameterization name, e.g. `mu` and `sigma`, as defined in the `Gauss`), which is useful if we are interested in the parameter that _describes_ the shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([('mu', <zfit.Parameter 'mu' floating=True value=1>),\n",
       "             ('sigma', <zfit.Parameter 'sigma42' floating=True value=1>)])"
      ]
     },
     "execution_count": 13,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.params"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "or to retrieve all the parameters that the PDF depends on. As this now may sounds trivial, we will see later that models can depend on other models (e.g. sums) and parameters on other parameters. There is one function that automatically retrieves _all_ dependencies, `get_params`. It takes three arguments to filter:\n",
    "- floating: whether to filter only floating parameters, only non-floating or don't discriminate\n",
    "- is_yield: if it is a yield, or not a yield, or both\n",
    "- extract_independent: whether to recursively collect all parameters. This, and the explanation for why independent, can be found later on in the `Simultaneous` tutorial.\n",
    "\n",
    "Usually, the default is exactly what we want if we look for _all free parameters that this PDF depends on_."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedSet([<zfit.Parameter 'mu' floating=True value=1>, <zfit.Parameter 'sigma42' floating=True value=1>])"
      ]
     },
     "execution_count": 14,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gauss.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The difference will also be clear if we e.g. use the same parameter twice:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "params=OrderedDict([('mu', <zfit.Parameter 'mu' floating=True value=1>), ('sigma', <zfit.Parameter 'mu' floating=True value=1>)])"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "get_params=OrderedSet([<zfit.Parameter 'mu' floating=True value=1>])"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "gauss_only_mu = zfit.pdf.Gauss(obs=obs, mu=mu, sigma=mu)\n",
    "print(f\"params={gauss_only_mu.params}\")\n",
    "print(f\"get_params={gauss_only_mu.get_params()}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Functionality\n",
    "\n",
    "PDFs provide a few useful methods. The main features of a zfit PDF are:\n",
    "\n",
    "- `pdf`: the normalized value of the PDF. It takes an argument `norm_range` that can be set to `False`, in which case we retrieve the unnormalized value\n",
    "- `integrate`: given a certain range, the PDF is integrated. As `pdf`, it takes a `norm_range` argument that integrates over the unnormalized `pdf` if set to `False`\n",
    "- `sample`: samples from the pdf and returns a `Data` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(1,), dtype=float64, numpy=array([0.95449974])>"
      ]
     },
     "execution_count": 16,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "integral = gauss.integrate(limits=(-1, 3))  # corresponds to 2 sigma integral\n",
    "integral"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Tensors\n",
    "\n",
    "As we see, many zfit functions return Tensors. This is however no magical thing! If we're outside of models, than we can always safely convert them to a numpy array by calling `zfit.run(...)` on it (or any structure containing potentially multiple Tensors). However, this may not even be required often! They can be added just like numpy arrays and interact well with Python and Numpy:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.97698502])"
      ]
     },
     "execution_count": 17,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.sqrt(integral)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "They also have shapes, dtypes, can be slices etc. So do not convert them except you need it. More on this can be seen in the talk later on about zfit and TensorFlow 2.0."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<zfit.core.data.SampleData at 0x7f90f5f2e278>"
      ]
     },
     "execution_count": 18,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample = gauss.sample(n=1000)  # default space taken as limits\n",
    "sample"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(10,), dtype=float64, numpy=\n",
       "array([3.53428249, 2.21623497, 0.74033309, 0.94986531, 1.16898151,\n",
       "       1.3350581 , 0.2433266 , 1.68229119, 1.81464923, 1.35160915])>"
      ]
     },
     "execution_count": 19,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.unstack_x()[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1"
      ]
     },
     "execution_count": 20,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.n_obs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('obs1',)"
      ]
     },
     "execution_count": 21,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sample.obs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We see that sample returns also a zfit `Data` object with the same space as it was sampled in. This can directly be used e.g."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(10,), dtype=float64, numpy=\n",
       "array([0.01607914, 0.19041445, 0.38571675, 0.39844123, 0.3932869 ,\n",
       "       0.37716576, 0.29962732, 0.31609921, 0.28628564, 0.37502859])>"
      ]
     },
     "execution_count": 22,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "probs = gauss.pdf(sample)\n",
    "probs[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "**NOTE**: In case you want to do this repeatedly (e.g. for toy studies), there is a way more efficient way (see later on)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Plotting\n",
    "\n",
    "so far, we have a dataset and a PDF. Before we go for fitting, we can make a plot. This functionality is not _directly_ provided in zfit (but can be added to [zfit-physics](https://github.com/zfit/zfit-physics)). It is however simple enough to do it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "def plot_model(model, data, scale=1, plot_data=True):  # we will use scale later on\n",
    "\n",
    "    nbins = 50\n",
    "\n",
    "    lower, upper = data.data_range.limit1d\n",
    "    x = tf.linspace(lower, upper, num=1000)  # np.linspace also works\n",
    "    y = model.pdf(x) * size_normal / nbins * data.data_range.area()\n",
    "    y *= scale\n",
    "    plt.plot(x, y)\n",
    "    data_plot = zfit.run(z.unstack_x(data))  # we could also use the `to_pandas` method\n",
    "    if plot_data:\n",
    "        plt.hist(data_plot, bins=nbins)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/ipykernel/__main__.py:5: UserWarning: The function <function Space.limit1d at 0x7f913a2d66a8> may does not return the actual area/limits but rather the rectangular limits. <zfit Space obs=('obs1',), axes=(0,), limits=(array([[-5.]]), array([[10.]]))> can also have functional limits that are arbitrarily defined and lay inside the rect_limits. To test if a value is inside, use `inside` or `filter`.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/dist-packages/ipykernel/__main__.py:7: UserWarning: The function <function Space.area at 0x7f913a2d6488> may does not return the actual area/limits but rather the rectangular limits. <zfit Space obs=('obs1',), axes=(0,), limits=(array([[-5.]]), array([[10.]]))> can also have functional limits that are arbitrarily defined and lay inside the rect_limits. To test if a value is inside, use `inside` or `filter`.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 24,
     "metadata": {
      "image/png": {
       "height": 411,
       "width": 716
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(gauss, data_normal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We can of course do better (and will see that later on, continuously improve the plots), but this is quite simple and gives us the full power of matplotlib."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Different models\n",
    "\n",
    "zfit offers a selection of predefined models (and extends with models from zfit-physics that contain physics specific models such as ARGUS shaped models)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['BasePDF', 'BaseFunctor', 'Exponential', 'CrystalBall', 'DoubleCB', 'Gauss', 'Uniform', 'TruncatedGauss', 'WrapDistribution', 'Cauchy', 'Chebyshev', 'Legendre', 'Chebyshev2', 'Hermite', 'Laguerre', 'RecursivePolynomial', 'ProductPDF', 'SumPDF', 'GaussianKDE1DimV1', 'ZPDF', 'SimplePDF', 'SimpleFunctorPDF']"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(zfit.pdf.__all__)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "To create a more realistic model, we can build some components for a mass fit with a\n",
    "- signal component: CrystalBall\n",
    "- combinatorial background: Exponential\n",
    "- partial reconstructed background on the left: Kernel Density Estimation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "mass_obs = zfit.Space('mass', (0, 1000))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# Signal component\n",
    "\n",
    "mu_sig = zfit.Parameter('mu_sig', 400, 100, 600)\n",
    "sigma_sig = zfit.Parameter('sigma_sig', 50, 1, 100)\n",
    "alpha_sig = zfit.Parameter('alpha_sig', 300, 100, 400)\n",
    "n_sig = zfit.Parameter('n sig', 4, 0.1, 30)\n",
    "signal = zfit.pdf.CrystalBall(obs=mass_obs, mu=mu_sig, sigma=sigma_sig, alpha=alpha_sig, n=n_sig)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# combinatorial background\n",
    "\n",
    "lam = zfit.Parameter('lambda', -0.01, -0.05, -0.001)\n",
    "comb_bkg = zfit.pdf.Exponential(lam, obs=mass_obs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "part_reco_data = np.random.normal(loc=200, scale=150, size=700)\n",
    "part_reco_data = zfit.Data.from_numpy(obs=mass_obs, array=part_reco_data)  # we don't need to do this but now we're sure it's inside the limits\n",
    "\n",
    "part_reco = zfit.pdf.GaussianKDE1DimV1(obs=mass_obs, data=part_reco_data, bandwidth='adaptive')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Composing models\n",
    "\n",
    "We can also compose multiple models together. Here we'll stick to one dimensional models, the extension to multiple dimensions is explained in the \"custom models tutorial\".\n",
    "\n",
    "Here we will use a `SumPDF`. This takes pdfs and fractions. If we provide n pdfs and:\n",
    "- n - 1 fracs: the nth fraction will be 1 - sum(fracs)\n",
    "- n fracs: no normalization attempt is done by `SumPDf`. If the fracs are not implicitly normalized, this can lead to bad fitting\n",
    "  behavior if there is a degree of freedom too much\n",
    "  \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "sig_frac = zfit.Parameter('sig_frac', 0.3, 0, 1)\n",
    "comb_bkg_frac = zfit.Parameter('comb_bkg_frac', 0.25, 0, 1)\n",
    "model = zfit.pdf.SumPDF([signal, comb_bkg, part_reco], [sig_frac, comb_bkg_frac])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "In order to have a corresponding data sample, we can just create one. Since we want to fit to this dataset later on, we will create it with slightly different values. Therefore, we can use the ability of a parameter to be set temporarily to a certain value with"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "before: <zfit.Parameter 'sig_frac' floating=True value=0.3>"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "new value: <zfit.Parameter 'sig_frac' floating=True value=0.25>"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "after 'with': <zfit.Parameter 'sig_frac' floating=True value=0.3>"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(f\"before: {sig_frac}\")\n",
    "with sig_frac.set_value(0.25):\n",
    "    print(f\"new value: {sig_frac}\")\n",
    "print(f\"after 'with': {sig_frac}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "While this is useful, it does not fully scale up. We can use the `zfit.param.set_values` helper therefore.\n",
    "(_Sidenote: instead of a list of values, we can also use a `FitResult`, the given parameters then take the value from the result_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "with zfit.param.set_values([mu_sig, sigma_sig, sig_frac, comb_bkg_frac, lam], [370, 34, 0.18, 0.15, -0.006]):\n",
    "    data = model.sample(n=10000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 33,
     "metadata": {
      "image/png": {
       "height": 411,
       "width": 710
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_model(model, data);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Plotting the components is not difficult now: we can either just plot the pdfs separately (as we still can access them) or in a generalized manner by accessing the `pdfs` attribute:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "def plot_comp_model(model, data):\n",
    "    for mod, frac in zip(model.pdfs, model.params.values()):\n",
    "        plot_model(mod, data, scale=frac, plot_data=False)\n",
    "    plot_model(model, data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 35,
     "metadata": {
      "image/png": {
       "height": 411,
       "width": 710
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_comp_model(model, data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Now we can add legends etc. Btw, did you notice that actually, the `frac` params are zfit `Parameters`? But we just used them as if they were Python scalars and it works."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([('frac_0', <zfit.Parameter 'sig_frac' floating=True value=0.3>), ('frac_1', <zfit.Parameter 'comb_bkg_frac' floating=True value=0.25>), ('frac_2', <zfit.ComposedParameter 'Composed_autoparam_2' params=OrderedDict([('param_0', <zfit.Parameter 'sig_frac' floating=True value=0.3>), ('param_1', <zfit.Parameter 'comb_bkg_frac' floating=True value=0.25>)]) value=0.45>)])"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(model.params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Extended PDFs\n",
    "\n",
    "So far, we have only looked at normalized PDFs that do contain information about the shape but not about the _absolute_ scale. We can make a PDF extended by adding a yield to it.\n",
    "\n",
    "The behavior of the new, extended PDF does **NOT change**, any methods we called before will act the same. Only exception, some may require an argument _less_ now. All the methods we used so far will return the same values. What changes is that the flag `model.is_extended` now returns `True`. Furthermore, we have now a few more methods that we can use which would have raised an error before:\n",
    "- `get_yield`: return the yield parameter (notice that the yield is _not_ added to the shape parameters `params`)\n",
    "- `ext_{pdf,integrate}`: these methods return the same as the versions used before, however, multiplied by the yield\n",
    "- `sample` is still the same, but does not _require_ the argument `n` anymore. By default, this will now equal to a _poissonian sampled_ n around the yield.\n",
    "\n",
    "The `SumPDF` now does not strictly need `fracs` anymore: if _all_ input PDFs are extended, the sum will be as well and use the (normalized) yields as fracs\n",
    "\n",
    "The preferred way to create an extended PDf is to use `PDF.create_extended(yield)`. However, since this relies on copying the PDF (which may does not work for different reasons), there is also a `set_yield(yield)` method that sets the yield in-place. This won't lead to ambiguities, as everything is supposed to work the same."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "yield_model = zfit.Parameter('yield_model', 10000, 0, 20000, step_size=10)\n",
    "model_ext = model.create_extended(yield_model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "alternatively, we can create the models as extended and sum them up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "sig_yield = zfit.Parameter('sig_yield', 2000, 0, 10000, step_size=1)\n",
    "sig_ext = signal.create_extended(sig_yield)\n",
    "\n",
    "comb_bkg_yield = zfit.Parameter('comb_bkg_yield', 6000, 0, 10000, step_size=1)\n",
    "comb_bkg_ext = comb_bkg.create_extended(comb_bkg_yield)\n",
    "\n",
    "part_reco_yield = zfit.Parameter('part_reco_yield', 2000, 0, 10000, step_size=1)\n",
    "part_reco.set_yield(part_reco_yield)  # unfortunately, `create_extended` does not work here. But no problem, it won't change anyting.\n",
    "part_reco_ext = part_reco"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "model_ext_sum = zfit.pdf.SumPDF([sig_ext, comb_bkg_ext, part_reco_ext])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Loss\n",
    "\n",
    "A loss combines the model and the data, for example to build a likelihood. Furthermore, it can contain constraints, additions to the likelihood. Currently, if the `Data` has weights, these are automatically taken into account."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "nll_gauss = zfit.loss.UnbinnedNLL(gauss, data_normal)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "The loss has several attributes to be transparent to higher level libraries. We can calculate the value of it using `value`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<tf.Tensor: shape=(), dtype=float64, numpy=33016.127669195615>"
      ]
     },
     "execution_count": 41,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll_gauss.value()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Notice that due to graph building, this will take significantly longer on the first run. Rerun the cell above and it will be way faster.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Furthermore, the loss also provides a possibility to calculate the gradients or, often used, the value and the gradients."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We can access the data and models (and possible constraints)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<zfit.Gauss  params=[mu, sigma42] dtype=float64>0]"
      ]
     },
     "execution_count": 42,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll_gauss.model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<zfit.core.data.Data at 0x7f91d4f5ed30>]"
      ]
     },
     "execution_count": 43,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll_gauss.data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[]"
      ]
     },
     "execution_count": 44,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll_gauss.constraints"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Similar to the models, we can also get the parameters via `get_params`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedSet([<zfit.Parameter 'mu' floating=True value=1>, <zfit.Parameter 'sigma42' floating=True value=1>])"
      ]
     },
     "execution_count": 45,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll_gauss.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### Extended loss\n",
    "\n",
    "More interestingly, we can now build a loss for our composite sum model using the sampled data. Since we created an extended model, we can now also create an extended likelihood, taking into account a Poisson term to match the yield to the number of events."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "nll = zfit.loss.ExtendedUnbinnedNLL(model_ext_sum, data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedSet([<zfit.Parameter 'sig_yield' floating=True value=2000>, <zfit.Parameter 'comb_bkg_yield' floating=True value=6000>, <zfit.Parameter 'part_reco_yield' floating=True value=2000>, <zfit.Parameter 'alpha_sig' floating=True value=300>, <zfit.Parameter 'mu_sig' floating=True value=400>, <zfit.Parameter 'n sig' floating=True value=4>, <zfit.Parameter 'sigma_sig' floating=True value=50>, <zfit.Parameter 'lambda' floating=True value=-0.01>])"
      ]
     },
     "execution_count": 47,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nll.get_params()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Minimization\n",
    "\n",
    "While a loss is interesting, we usually want to minimize it. Therefore we can use the minimizers in zfit, most notably `Minuit`, a wrapper around the [iminuit minimizer](https://github.com/scikit-hep/iminuit).\n",
    "\n",
    "The philosophy is to create a minimizer instance that is mostly _stateless_, e.g. does not remember the position (there are considerations to make it possible to have a state, in case you feel interested, [contact us](https://github.com/zfit/zfit#contact))\n",
    "\n",
    "Given that iminuit provides us with a very reliable and stable minimizer, it is usually recommended to use this. Others are implemented as well and could easily be wrapped, however, the convergence is usually not as stable.\n",
    "\n",
    "Minuit has a few options:\n",
    "- `tolerance`: the Estimated Distance to Minimum (EDM) criteria for convergence (default 1e-3)\n",
    "- `verbosity`: between 0 and 10, 5 is normal, 7 is verbose, 10 is maximum\n",
    "- `use_minuit_grad`: if True, uses the Minuit numerical gradient instead of the TensorFlow gradient. This is usually more stable for smaller fits; furthermore the TensorFlow gradient _can_ (experience based) sometimes be wrong."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "minimizer = zfit.minimize.Minuit(use_minuit_grad=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "For the minimization, we can call `minimize`, which takes a\n",
    "- loss as we created above\n",
    "- optionally: the parameters to minimize\n",
    "\n",
    "By default, `minimize` uses all the free floating parameters (obtained with `get_params`). We can also explicitly specify which ones to use by giving them (or better, objects that depend on them) to `minimize`; note however that non-floating parameters, even if given explicitly to `minimize` won 't be minimized."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Pre-fit parts of the PDF\n",
    "\n",
    "Before we want to fit the whole PDF however, it can be useful to pre-fit it. A way can be to fix the combinatorial background by fitting the exponential to the right tail.\n",
    "\n",
    "Therefore we create a new data object with an additional cut and furthermore, set the normalization range of the background pdf to the range we are interested in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------------------------------\n",
      "| FCN = 313                     |      Ncalls=17 (17 total)      |\n",
      "| EDM = 1.65e-08 (Goal: 0.001)  |            up = 0.5            |\n",
      "------------------------------------------------------------------\n",
      "|  Valid Min.   | Valid Param.  | Above EDM | Reached call limit |\n",
      "------------------------------------------------------------------\n",
      "|     True      |     True      |   False   |       False        |\n",
      "------------------------------------------------------------------\n",
      "| Hesse failed  |   Has cov.    | Accurate  | Pos. def. | Forced |\n",
      "------------------------------------------------------------------\n",
      "|     False     |     True      |   True    |   True    | False  |\n",
      "------------------------------------------------------------------"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "values = z.unstack_x(data)\n",
    "obs_right_tail = zfit.Space('mass', (700, 1000))\n",
    "data_tail = zfit.Data.from_tensor(obs=obs_right_tail, tensor=values)\n",
    "with comb_bkg.set_norm_range(obs_right_tail):\n",
    "    nll_tail = zfit.loss.UnbinnedNLL(comb_bkg, data_tail)\n",
    "    minimizer.minimize(nll_tail)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "Since we now fit the lambda parameter of the exponential, we can fix it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<zfit.Parameter 'lambda' floating=False value=-0.008049>"
      ]
     },
     "execution_count": 50,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lam.floating = False\n",
    "lam"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "------------------------------------------------------------------\n",
      "| FCN = -1.954e+04              |     Ncalls=167 (167 total)     |\n",
      "| EDM = 0.000128 (Goal: 0.001)  |            up = 0.5            |\n",
      "------------------------------------------------------------------\n",
      "|  Valid Min.   | Valid Param.  | Above EDM | Reached call limit |\n",
      "------------------------------------------------------------------\n",
      "|     True      |     True      |   False   |       False        |\n",
      "------------------------------------------------------------------\n",
      "| Hesse failed  |   Has cov.    | Accurate  | Pos. def. | Forced |\n",
      "------------------------------------------------------------------\n",
      "|     False     |     True      |   True    |   True    | False  |\n",
      "------------------------------------------------------------------"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "result = minimizer.minimize(nll)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 52,
     "metadata": {
      "image/png": {
       "height": 415,
       "width": 710
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot_comp_model(model_ext_sum, data)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Fit result\n",
    "\n",
    "The result of every minimization is stored in a `FitResult`. This is the last stage of the zfit workflow and serves as the interface to other libraries. Its main purpose is to store the values of the fit, to reference to the objects that have been used and to perform (simple) uncertainty estimation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FitResult"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " of\n",
      "<ExtendedUnbinnedNLL model=[<zfit.SumPDF  params=[Composed_autoparam_5, Composed_autoparam_6, Composed_autoparam_7] dtype=float64>0] data=[<zfit.core.data.SampleData object at 0x7f90f5454438>] constraints=[]> \n",
      "with\n",
      "<Minuit strategy=PushbackStrategy tolerance=0.001>\n",
      "\n",
      "╒═════════╤═════════════╤══════════════════╤═════════╤═════════════╕\n",
      "│ valid   │ converged   │ param at limit   │ edm     │ min value   │\n",
      "╞═════════╪═════════════╪══════════════════╪═════════╪═════════════╡\n",
      "│ "
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "True"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "    │ True"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "        │ False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "            │ 0.00013 │ -1.954e+04  │\n",
      "╘═════════╧═════════════╧══════════════════╧═════════╧═════════════╛\n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Parameters\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name               value    at limit\n",
      "---------------  -------  ----------\n",
      "sig_yield           1851       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "comb_bkg_yield      1131       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "part_reco_yield     7018       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "alpha_sig            300       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mu_sig             369.7       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "n sig                  4       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "sigma_sig          34.09       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(result)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "This gives an overview over the whole result. Often we're mostly interested in the parameters and their values, which we can access with a `params` attribute."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name               value    at limit\n",
      "---------------  -------  ----------\n",
      "sig_yield           1851       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "comb_bkg_yield      1131       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "part_reco_yield     7018       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "alpha_sig            300       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mu_sig             369.7       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "n sig                  4       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "sigma_sig          34.09       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(result.params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "This is a `dict` which stores any knowledge about the parameters and can be accessed by the parameter (object) itself:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'value': 369.7337120757637}"
      ]
     },
     "execution_count": 55,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.params[mu_sig]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "'value' is the value at the minimum. To obtain other information about the minimization process, `result` contains more attributes:\n",
    "- fmin: the function minimum\n",
    "- edm: estimated distance to minimum\n",
    "- info: contains a lot of information, especially the original information returned by a specific minimizer\n",
    "- converged: if the fit converged"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-19539.388894488584"
      ]
     },
     "execution_count": 56,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.fmin"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "## Estimating uncertainties\n",
    "\n",
    "The `FitResult` has mainly two methods to estimate the uncertainty:\n",
    "- a profile likelihood method (like MINOS)\n",
    "- Hessian approximation of the likelihood (like HESSE)\n",
    "\n",
    "When using `Minuit`, this uses (currently) it's own implementation. However, zfit has its own implementation, which are likely to become the standard and can be invoked by changing the method name.\n",
    "\n",
    "Hesse is also [on the way to implement](https://github.com/zfit/zfit/pull/244) the [corrections for weights](https://inspirehep.net/literature/1762842).\n",
    "\n",
    "We can explicitly specify which parameters to calculate, by default it does for all."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "OrderedDict([(<zfit.Parameter 'sig_yield' floating=True value=1850>,\n",
       "              {'error': 73.52924652265973}),\n",
       "             (<zfit.Parameter 'comb_bkg_yield' floating=True value=1130>,\n",
       "              {'error': 79.49051306516832}),\n",
       "             (<zfit.Parameter 'part_reco_yield' floating=True value=7020>,\n",
       "              {'error': 136.98379193128127}),\n",
       "             (<zfit.Parameter 'alpha_sig' floating=True value=300>,\n",
       "              {'error': 141.4213562373095}),\n",
       "             (<zfit.Parameter 'mu_sig' floating=True value=369.7>,\n",
       "              {'error': 1.3913704142629884}),\n",
       "             (<zfit.Parameter 'n sig' floating=True value=4>,\n",
       "              {'error': 10.069756698215553}),\n",
       "             (<zfit.Parameter 'sigma_sig' floating=True value=34.09>,\n",
       "              {'error': 1.3407261987832484})])"
      ]
     },
     "execution_count": 89,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.hesse()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# result.hesse(method='hesse_np')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We get the result directly returned. This is also added to `result.params` for each parameter and is nicely displayed with an added column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name               value    minuit_hesse    at limit\n",
      "---------------  -------  --------------  ----------\n",
      "sig_yield           1851     +/-      69       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "comb_bkg_yield      1131     +/-      75       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "part_reco_yield     7018     +/- 1.2e+02       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "alpha_sig            300     +/- 1.4e+02       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mu_sig             369.7     +/-     1.4       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "n sig                  4     +/-      10       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "sigma_sig          34.09     +/-     1.3       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(result.params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/user/.local/lib/python3.6/site-packages/zfit/minimizers/fitresult.py:359: FutureWarning: 'minuit_minos' will be changed as the default errors method to a custom implementationwith the same functionality. If you want to make sure that 'minuit_minos' will be used in the future, add it explicitly as in `errors(method='minuit_minos')`\n",
      "  \"in the future, add it explicitly as in `errors(method='minuit_minos')`\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "errors, new_result = result.errors(params=[sig_yield, part_reco_yield, mu_sig])  # just using three for speed reasons"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "# errors, new_result = result.errors(params=[yield_model, sig_frac, mu_sig], method='zfit_error')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "OrderedDict([(<zfit.Parameter 'sig_yield' floating=True value=1851>, MError(name='sig_yield', is_valid=True, lower=-73.19610573010954, upper=73.2494131480733, lower_valid=True, upper_valid=True, at_lower_limit=False, at_upper_limit=False, at_lower_max_fcn=False, at_upper_max_fcn=False, lower_new_min=False, upper_new_min=False, nfcn=208, min=1850.6452612293656)), (<zfit.Parameter 'part_reco_yield' floating=True value=7018>, MError(name='part_reco_yield', is_valid=True, lower=-134.46090913541406, upper=138.70099174669127, lower_valid=True, upper_valid=True, at_lower_limit=False, at_upper_limit=False, at_lower_max_fcn=False, at_upper_max_fcn=False, lower_new_min=False, upper_new_min=False, nfcn=204, min=7017.782731457284)), (<zfit.Parameter 'mu_sig' floating=True value=369.7>, MError(name='mu_sig', is_valid=True, lower=-1.3846589189505978, upper=1.391857347531778, lower_valid=True, upper_valid=True, at_lower_limit=False, at_upper_limit=False, at_lower_max_fcn=False, at_upper_max_fcn=False, lower_new_min=False, upper_new_min=False, nfcn=131, min=369.7337120757637))])"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(errors)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "name               value    minuit_hesse         minuit_minos    at limit\n",
      "---------------  -------  --------------  -------------------  ----------\n",
      "sig_yield           1851     +/-      69  -     73   +     73       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "comb_bkg_yield      1131     +/-      75                            False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "part_reco_yield     7018     +/- 1.2e+02  -1.3e+02   +1.4e+02       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "alpha_sig            300     +/- 1.4e+02                            False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "mu_sig             369.7     +/-     1.4  -    1.4   +    1.4       False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "n sig                  4     +/-      10                            False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "sigma_sig          34.09     +/-     1.3                            False"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "print(result.params)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "#### What is 'new_result'?\n",
    "\n",
    "When profiling a likelihood, such as done in the algorithm used in `errors`, a new minimum can be found. If this is the case, this new minimum will be returned, otherwise `new_result` is `None`. Furthermore, the current `result` would be rendered invalid by setting the flag `valid` to `False`. _Note_: this behavior only applies to the zfit internal error estimator."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "### A simple profile\n",
    "\n",
    "There is no default function (yet) for simple profiling plot. However, again, we're in Python and it's simple enough to do that for a parameter. Let's do it for `sig_yield`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "x = np.linspace(1600, 2000, num=50)\n",
    "y = []\n",
    "sig_yield.floating = False\n",
    "for val in x:\n",
    "    sig_yield.set_value(val)\n",
    "    y.append(nll.value())\n",
    "\n",
    "sig_yield.floating = True\n",
    "zfit.param.set_values(nll.get_params(), result)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f90f42cb0b8>]"
      ]
     },
     "execution_count": 65,
     "metadata": {
     },
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 65,
     "metadata": {
      "image/png": {
       "height": 421,
       "width": 705
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plt.plot(x, y)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "We can also access the covariance matrix of the parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 4.80313887e+03,  1.02095082e+03, -3.43531769e+03,\n",
       "         0.00000000e+00, -2.08964215e+01,  0.00000000e+00,\n",
       "         4.67706435e+01],\n",
       "       [ 1.02095082e+03,  5.63159948e+03, -5.91552419e+03,\n",
       "         0.00000000e+00, -7.87129146e+00,  0.00000000e+00,\n",
       "         1.77558437e+01],\n",
       "       [-3.43531769e+03, -5.91552419e+03,  1.46369813e+04,\n",
       "         0.00000000e+00,  3.07633305e+01,  0.00000000e+00,\n",
       "        -6.37418378e+01],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
       "         2.00000000e+04,  0.00000000e+00,  0.00000000e+00,\n",
       "         0.00000000e+00],\n",
       "       [-2.08964215e+01, -7.87129146e+00,  3.07633305e+01,\n",
       "         0.00000000e+00,  1.93158341e+00,  0.00000000e+00,\n",
       "        -4.28578345e-01],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00,\n",
       "         0.00000000e+00,  0.00000000e+00,  1.01400000e+02,\n",
       "         0.00000000e+00],\n",
       "       [ 4.67706435e+01,  1.77558437e+01, -6.37418378e+01,\n",
       "         0.00000000e+00, -4.28578345e-01,  0.00000000e+00,\n",
       "         1.74205276e+00]])"
      ]
     },
     "execution_count": 66,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "result.covariance()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# End of zfit\n",
    "\n",
    "This is where zfit finishes and other libraries take over."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "# Beginning of hepstats"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "`hepstats` is a library containing statistical tools and utilities for high energy physics. In particular you do statistical inferences using the models and likelhoods function constructed in `zfit`.\n",
    "\n",
    "Short example: let's compute for instance a confidence interval at 68 % confidence level on the mean of the gaussian defined above."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "from hepstats.hypotests.parameters import POIarray\n",
    "from hepstats.hypotests.calculators import AsymptoticCalculator\n",
    "from hepstats.hypotests import ConfidenceInterval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "calculator = AsymptoticCalculator(input=result, minimizer=minimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "value = result.params[mu_sig][\"value\"]\n",
    "error = result.params[mu_sig][\"minuit_hesse\"][\"error\"]\n",
    "\n",
    "mean_scan = POIarray(mu_sig, np.linspace(value - 1.5*error, value + 1.5*error, 10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
   ],
   "source": [
    "ci = ConfidenceInterval(calculator, mean_scan)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Confidence interval on mu_sig:\n",
      "\t368.3536149718213 < mu_sig < 371.12167557864825 at 68.0% C.L."
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'observed': 369.7420306479183,\n",
       " 'upper': 371.12167557864825,\n",
       " 'lower': 368.3536149718213}"
      ]
     },
     "execution_count": 92,
     "metadata": {
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ci.interval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'mean')"
      ]
     },
     "execution_count": 93,
     "metadata": {
     },
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 864x504 with 1 Axes>"
      ]
     },
     "execution_count": 93,
     "metadata": {
      "image/png": {
       "height": 427,
       "width": 724
      },
      "needs_background": "light"
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from utils import one_minus_cl_plot\n",
    "\n",
    "ax = one_minus_cl_plot(ci)\n",
    "ax.set_xlabel(\"mean\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": false
   },
   "source": [
    "There will be more of `hepstats` later."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (system-wide)",
   "language": "python",
   "metadata": {
    "cocalc": {
     "description": "Python 3 programming language",
     "priority": 100,
     "url": "https://www.python.org/"
    }
   },
   "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": "3.6.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}