lars
1046 lines
32 KiB
Plaintext
1046 lines
32 KiB
Plaintext
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"#19d3f3",
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"#FF6692",
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"#B6E880",
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"#FECB52"
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],
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"geo": {
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"lakecolor": "white",
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"landcolor": "#E5ECF6",
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"showlakes": true,
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"showland": true,
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"subunitcolor": "white"
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},
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"hoverlabel": {
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"align": "left"
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"hovermode": "closest",
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"style": "light"
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},
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"polar": {
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},
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"radialaxis": {
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}
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},
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"scene": {
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"zerolinecolor": "white"
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},
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"yaxis": {
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"gridcolor": "white",
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"gridwidth": 2,
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"linecolor": "white",
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"showbackground": true,
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"ticks": "",
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"zerolinecolor": "white"
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},
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"zaxis": {
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"backgroundcolor": "#E5ECF6",
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"gridcolor": "white",
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"gridwidth": 2,
|
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"linecolor": "white",
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"showbackground": true,
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"ticks": "",
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"zerolinecolor": "white"
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}
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},
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"shapedefaults": {
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"line": {
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"color": "#2a3f5f"
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}
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},
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"ternary": {
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"aaxis": {
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"gridcolor": "white",
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"linecolor": "white",
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"ticks": ""
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},
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"baxis": {
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"gridcolor": "white",
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"linecolor": "white",
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"ticks": ""
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},
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"bgcolor": "#E5ECF6",
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"caxis": {
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"linecolor": "white",
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"ticks": ""
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}
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},
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"title": {
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"x": 0.05
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},
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"automargin": true,
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"linecolor": "white",
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"ticks": "",
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"title": {
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"standoff": 15
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},
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"zerolinecolor": "white",
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"zerolinewidth": 2
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"yaxis": {
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"automargin": true,
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"gridcolor": "white",
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"linecolor": "white",
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"ticks": "",
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"title": {
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"standoff": 15
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},
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"zerolinecolor": "white",
|
|
"zerolinewidth": 2
|
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}
|
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}
|
|
},
|
|
"title": {
|
|
"text": "Interactive 3D Scatter Plot"
|
|
}
|
|
}
|
|
},
|
|
"text/html": [
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"<div> <div id=\"e6eecc96-9f2e-401c-ad5b-31e4fce3d0e6\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div> <script type=\"text/javascript\"> require([\"plotly\"], function(Plotly) { window.PLOTLYENV=window.PLOTLYENV || {}; if (document.getElementById(\"e6eecc96-9f2e-401c-ad5b-31e4fce3d0e6\")) { Plotly.newPlot( \"e6eecc96-9f2e-401c-ad5b-31e4fce3d0e6\", [{\"hovertemplate\":\"x=%{x}\\u003cbr\\u003ey=%{y}\\u003cbr\\u003ez=%{z}\\u003cextra\\u003e\\u003c\\u002fextra\\u003e\",\"legendgroup\":\"\",\"marker\":{\"color\":\"#636efa\",\"symbol\":\"circle\"},\"mode\":\"markers\",\"name\":\"\",\"scene\":\"scene\",\"showlegend\":false,\"x\":[1,2,3,4,5],\"y\":[5,4,3,2,1],\"z\":[10,20,15,25,30],\"type\":\"scatter3d\"},{\"line\":{\"color\":\"red\",\"width\":2},\"opacity\":0.2,\"x\":[-1,1,1,-1,-1,1,1,-1,-1],\"y\":[-1,-1,1,1,-1,-1,1,1,-1],\"z\":[0,0,0,0,30,30,30,30,0],\"type\":\"scatter3d\"}], 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Label\"}},\"yaxis\":{\"title\":{\"text\":\"Y Label\"}},\"zaxis\":{\"title\":{\"text\":\"Z Label\"}},\"dragmode\":\"orbit\"},\"legend\":{\"tracegroupgap\":0},\"margin\":{\"t\":60},\"title\":{\"text\":\"Interactive 3D Scatter Plot\"}}, {\"responsive\": true} ).then(function(){\n",
|
|
" \n",
|
|
"var gd = document.getElementById('e6eecc96-9f2e-401c-ad5b-31e4fce3d0e6');\n",
|
|
"var x = new MutationObserver(function (mutations, observer) {{\n",
|
|
" var display = window.getComputedStyle(gd).display;\n",
|
|
" if (!display || display === 'none') {{\n",
|
|
" console.log([gd, 'removed!']);\n",
|
|
" Plotly.purge(gd);\n",
|
|
" observer.disconnect();\n",
|
|
" }}\n",
|
|
"}});\n",
|
|
"\n",
|
|
"// Listen for the removal of the full notebook cells\n",
|
|
"var notebookContainer = gd.closest('#notebook-container');\n",
|
|
"if (notebookContainer) {{\n",
|
|
" x.observe(notebookContainer, {childList: true});\n",
|
|
"}}\n",
|
|
"\n",
|
|
"// Listen for the clearing of the current output cell\n",
|
|
"var outputEl = gd.closest('.output');\n",
|
|
"if (outputEl) {{\n",
|
|
" x.observe(outputEl, {childList: true});\n",
|
|
"}}\n",
|
|
"\n",
|
|
" }) }; }); </script> </div>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"from G4Calo import ConstructionWrapper, G4System\n",
|
|
"\n",
|
|
"cw = ConstructionWrapper() #the width of the calorimeter is 50 cm times 50 cm (also steerable, but I'd leave it)\n",
|
|
"\n",
|
|
"cw.addLayer(3,\"G4_Si\",True, 7)\n",
|
|
"cw.addLayer(4,\"G4_Pb\",False) \n",
|
|
"cw.addLayer(3,\"G4_Si\",True, 7)\n",
|
|
"cw.addLayer(4,\"G4_Pb\",False)\n",
|
|
"cw.addLayer(3,\"G4_Si\",True, 7)\n",
|
|
"cw.addLayer(4,\"G4_Pb\",False)\n",
|
|
"\n",
|
|
"G4s = G4System()\n",
|
|
"G4s.init(cw)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"G4s.displayEvent(\"pi-\", 100000)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df = G4s.run_batch(10, 'gamma',1 , 1)"
|
|
]
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},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"df"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "caloML",
|
|
"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": "3.9.16"
|
|
},
|
|
"orig_nbformat": 4
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|