diff --git a/notebooks/LST1_observation_simulator.ipynb b/notebooks/LST1_observation_simulator.ipynb
index 10db5b9db..35d109a29 100644
--- a/notebooks/LST1_observation_simulator.ipynb
+++ b/notebooks/LST1_observation_simulator.ipynb
@@ -2,7 +2,7 @@
"cells": [
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+ "execution_count": null,
"id": "8d7fb8ab-7034-47be-a392-17612fd611b7",
"metadata": {},
"outputs": [],
@@ -28,7 +28,7 @@
},
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+ "execution_count": null,
"id": "ef3576a4",
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@@ -56,8 +56,8 @@
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{
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- "execution_count": 3,
- "id": "0844c0a4",
+ "execution_count": null,
+ "id": "df170ecd",
"metadata": {},
"outputs": [],
"source": [
@@ -69,7 +69,7 @@
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+ "execution_count": null,
"id": "c59f8666",
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@@ -83,392 +83,34 @@
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+ "outputs": [],
"source": [
"background_data"
]
},
{
"cell_type": "code",
- "execution_count": 7,
+ "execution_count": null,
"id": "90114613",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Available zeniths: [ 6. 9.579 16.08 23.16 30.39 37.66 44.92 52.16 59.34 66.44 ] (degrees)\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# CHECK that we have the same pointing zenith values in both tables:\n",
"assert np.alltrue(np.unique(gamma_data.ZD_deg) == np.unique(background_data.ZD_deg))\n",
@@ -488,18 +130,10 @@
},
{
"cell_type": "code",
- "execution_count": 8,
+ "execution_count": null,
"id": "a5a9386a",
"metadata": {},
- "outputs": [
- {
- "name": "stdout",
- "output_type": "stream",
- "text": [
- "Selected ZD = 16.08 degrees\n"
- ]
- }
- ],
+ "outputs": [],
"source": [
"# Choose the bins among those above. Just set the bin number (from 0)\n",
"# Make sure you choose values which make sense for the declination of your source\n",
@@ -522,7 +156,7 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": null,
"id": "0c58505b",
"metadata": {},
"outputs": [],
@@ -544,7 +178,7 @@
},
{
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+ "execution_count": null,
"id": "7d8d3a2e",
"metadata": {},
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@@ -562,7 +196,7 @@
},
{
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- "execution_count": 11,
+ "execution_count": null,
"id": "ea9bca3c",
"metadata": {},
"outputs": [],
@@ -593,7 +227,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": null,
"id": "e24f72ce",
"metadata": {},
"outputs": [],
@@ -617,7 +251,7 @@
},
{
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- "execution_count": 13,
+ "execution_count": null,
"id": "014476b0",
"metadata": {},
"outputs": [],
@@ -638,7 +272,7 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": null,
"id": "80627c34",
"metadata": {},
"outputs": [],
@@ -655,7 +289,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": null,
"id": "24e8394c",
"metadata": {},
"outputs": [],
@@ -666,7 +300,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": null,
"id": "056ea33b",
"metadata": {},
"outputs": [],
@@ -697,7 +331,7 @@
},
{
"cell_type": "code",
- "execution_count": 17,
+ "execution_count": null,
"id": "1b79d5b2",
"metadata": {},
"outputs": [],
@@ -708,7 +342,7 @@
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": null,
"id": "2038bb5b",
"metadata": {},
"outputs": [],
@@ -723,7 +357,7 @@
},
{
"cell_type": "code",
- "execution_count": 19,
+ "execution_count": null,
"id": "48a34458",
"metadata": {},
"outputs": [],
@@ -742,7 +376,7 @@
},
{
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- "execution_count": 20,
+ "execution_count": null,
"id": "54b22527",
"metadata": {},
"outputs": [],
@@ -771,21 +405,10 @@
},
{
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- "execution_count": 21,
+ "execution_count": null,
"id": "4eff20a0",
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- "outputs": [
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",
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