Option to replace maps by constant dummy map

examples/4_Custom_Simulations.ipynb

@@ -6,7 +6,7 @@
    "source": [
     "# Custom Simulation and Advanced Tricks\n",
     "\n",
-    "This notebook will demonstrate how one can use the modular structure of fuse to change parts of the simulation by exchanging or adding new pugins. To get the most out of this notebook, you should start with an empty `out_dir` when setting up the simulation context. \n",
+    "This notebook will demonstrate how one can use the modular structure of fuse to change parts of the simulation by exchanging or adding new pugins. To get the most out of this notebook, you should start with an empty `out_dir` when setting up the simulation context. Additionaly the notebook will show how a map can be replaced with a dummy map to disable certain parts of the simulation.\n",
     "\n",
     "## Imports & Simulation Context"
    ]
@@ -434,13 +434,122 @@
     "plugin_output = plugin.compute(microphysics_summary)\n",
     "print(plugin_output[0:10])"
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Replacing a map with a dummy map\n",
+    "\n",
+    "Sometimes you might want to disable a certain feature of the simulation without going into the code and changing a plugin. One example can be that you might want to turn of the effects of a certain map. In this example we will use the `constant_dummy_map` URLConfig protocol to disable the effect of the s2_correction map.\n",
+    "\n",
+    "We can set up a new context. This time we will override the config option for the s2_correction map with the dummy map option. Instead of the real map values, the dummy map will return a constant value that can be configured by the user. In our case we set it to 1. You could also set it to other values if you want to test the effect of the map on the simulation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st = fuse.context.full_chain_context(\n",
+    "    output_folder=\"./fuse_data\", run_without_proper_corrections=True\n",
+    ")\n",
+    "\n",
+    "st.set_config(\n",
+    "    {\n",
+    "        \"path\": \"/project2/lgrandi/xenonnt/simulations/testing\",\n",
+    "        \"file_name\": \"pmt_neutrons_100.root\",\n",
+    "        \"entry_stop\": 10,\n",
+    "        \"s2_correction_map\": \"constant_dummy_map://1\",\n",
+    "    }\n",
+    ")\n",
+    "\n",
+    "run_number = \"00000\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To get a feeling how the map affects your simulation, lets take a look at the number of s2 photons.  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st.make(run_number, \"s2_photons\")\n",
+    "s2_photons = st.get_df(run_number, \"s2_photons\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now that we have the data, lets change the map to a different value and rerun the simulation."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st.set_config(\n",
+    "    {\n",
+    "        \"s2_correction_map\": \"constant_dummy_map://2\",\n",
+    "    }\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "st.make(run_number, \"s2_photons\")\n",
+    "s2_photons_changed_constant = st.get_df(run_number, \"s2_photons\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "And now we can plot the data again. You should see that the distribution of s2 photons is different."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "bins = np.linspace(0, 100, 100)\n",
+    "\n",
+    "plt.hist(s2_photons[\"n_s2_photons\"], bins=bins, alpha=0.5, label=\"Original\")\n",
+    "plt.hist(\n",
+    "    s2_photons_changed_constant[\"n_s2_photons\"], bins=bins, alpha=0.5, label=\"Changed constant\"\n",
+    ")\n",
+    "\n",
+    "plt.legend()\n",
+    "plt.xlabel(\"Number of S2 photons\")\n",
+    "plt.ylabel(\"Counts\")\n",
+    "plt.show()"
+   ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python [conda env:XENONnT_development] *",
+   "display_name": "Python 3 (ipykernel)",
    "language": "python",
-   "name": "conda-env-XENONnT_development-py"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -452,7 +561,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.9.19"
   },
   "orig_nbformat": 4
  },

fuse/context.py

@@ -293,3 +293,31 @@ def from_config(config_name, key):
     """Return a value from a json config file."""
     config = straxen.get_resource(config_name, fmt="json")
     return config[key]
+
+
+class DummyMap:
+    """Return constant results with length equal to that of the input and
+    second dimensions (constand correction) user-defined."""
+
+    def __init__(self, const, shape=()):
+        self.const = float(const)
+        self.shape = shape
+
+    def __call__(self, x, **kwargs):
+        shape = [len(x)] + list(self.shape)
+        return np.ones(shape) * self.const
+
+    def reduce_last_dim(self):
+        assert len(self.shape) >= 1, "Need at least 1 dim to reduce further"
+        const = self.const * self.shape[-1]
+        shape = list(self.shape)
+        shape[-1] = 1
+
+        return DummyMap(const, shape)
+
+
+@URLConfig.register("constant_dummy_map")
+def get_dummy(const, shape=()):
+    """Make an Dummy Map."""
+    itp_map = DummyMap(const, shape)
+    return itp_map