mirror of
https://github.com/Richard-Sti/csiborgtools.git
synced 2024-10-18 22:15:06 +02:00
04119a5314
* pep8 * fix convention * Update script * enforce optimisation boundaries to be finite * Update TODO * Remove sky matching * FIx a small bug * fix bug * Remove import * Add halo fitted quantities * Update nbs * update README * Add load_initial comments * Rename nbs * Delete nb * Update imports * Rename function * Update matcher * Add overlap paths * Update the matching script * Update verbosity * Add verbosity flags * Simplify make_bckg_delta * bug fix * fix bug
1306 lines
116 KiB
Plaintext
1306 lines
116 KiB
Plaintext
{
|
|
"cells": [
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 1,
|
|
"id": "5a38ed25",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T14:16:01.928614Z",
|
|
"start_time": "2023-03-24T14:15:34.242247Z"
|
|
},
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"../csiborgtools/field/__init__.py:20: UserWarning: MAS_library not found, `DensityField` will not be available\n",
|
|
" warn(\"MAS_library not found, `DensityField` will not be available\", UserWarning) # noqa\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"import sys\n",
|
|
"from os.path import join\n",
|
|
"import numpy as np\n",
|
|
"import matplotlib.pyplot as plt\n",
|
|
"from numba import jit\n",
|
|
"from tqdm import tqdm, trange\n",
|
|
"import joblib\n",
|
|
"sys.path.append(\"../\")\n",
|
|
"import csiborgtools\n",
|
|
"\n",
|
|
"%matplotlib widget\n",
|
|
"%load_ext autoreload\n",
|
|
"%autoreload 2"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "6f3ae40e",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"srcdir = \"/cosma8/data/dp016/dc-stis1/csiborg_new\"\n",
|
|
"dumpdir = \"/cosma8/data/dp016/dc-stis1/csiborg_dump\"\n",
|
|
"paths = csiborgtools.read.CSiBORGPaths(srcdir=srcdir, dumpdir=dumpdir)\n",
|
|
"\n",
|
|
"\n",
|
|
"reader = csiborgtools.read.ParticleReader(paths)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "33abfe57",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Reading in output `00001` with ncpu = `324`.\n",
|
|
"Opened 324 particle files.\n"
|
|
]
|
|
},
|
|
{
|
|
"name": "stderr",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"100%|██████████| 324/324 [03:57<00:00, 1.36it/s]\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"part = reader.read_particle(1, 7444, [\"x\", \"y\", \"z\", \"M\", \"ID\"], verbose=True)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"id": "32ab40ee",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ls: cannot access /cosma8/data/dp016/dc-stis1/csiborg_new/ramsess_out_7444/outputs_00001/: No such file or directory\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"/cosma8/data/dp016/dc-stis1/csiborg_new/ramses_out_7444_new/output_00001/info_00001.txt"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 9,
|
|
"id": "fc116dff",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"cat: /cosma8/data/dp016/dc-stis1/csiborg_new/ramses_out_7444/output_00001/info_00001.txt: No such file or directory\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"!cat /cosma8/data/dp016/dc-stis1/csiborg_new/ramses_out_7444/output_00001/info_00001.txt"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "e6b05ceb",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"ncpu = 324\n",
|
|
"ndim = 3\n",
|
|
"levelmin = 8\n",
|
|
"levelmax = 19\n",
|
|
"ngridmax = 2800000\n",
|
|
"nstep_coarse= 0\n",
|
|
"\n",
|
|
"boxlen = 0.100000000000000E+01\n",
|
|
"time = -0.260788354371079E+02\n",
|
|
"aexp = 0.142857000000000E-01\n",
|
|
"H0 = 0.705000000000000E+02\n",
|
|
"omega_m = 0.307000011205673E+00\n",
|
|
"omega_l = 0.693000018596649E+00\n",
|
|
"omega_k = -0.298023223876953E-07\n",
|
|
"omega_b = 0.000000000000000E+00\n",
|
|
"unit_l = 0.423740962969913E+26\n",
|
|
"unit_d = 0.983942902810118E-24\n",
|
|
"unit_t = 0.893232429772148E+14\n",
|
|
"\n",
|
|
"ordering type=hilbert \n",
|
|
" DOMAIN ind_min ind_max\n",
|
|
" 1 0.000000000000000E+00 0.890921902481080E+17\n",
|
|
" 2 0.890921902481080E+17 0.903741664479150E+17\n",
|
|
" 3 0.903741664479150E+17 0.905655754235576E+17\n",
|
|
" 4 0.905655754235576E+17 0.907569842649825E+17\n",
|
|
" 5 0.907569842649825E+17 0.910375727335997E+17\n",
|
|
" 6 0.910375727335997E+17 0.916149055929713E+17\n",
|
|
" 7 0.916149055929713E+17 0.918096761858294E+17\n",
|
|
" 8 0.918096761858294E+17 0.920010850272543E+17\n",
|
|
" 9 0.920010850272543E+17 0.942688305781146E+17\n",
|
|
" 10 0.942688305781146E+17 0.945672973849723E+17\n",
|
|
" 11 0.945672973849723E+17 0.947587062263972E+17\n",
|
|
" 12 0.947587062263972E+17 0.949501751973642E+17\n",
|
|
" 13 0.949501751973642E+17 0.955129510703923E+17\n",
|
|
" 14 0.955129510703923E+17 0.958726141818962E+17\n",
|
|
" 15 0.958726141818962E+17 0.963097707172332E+17\n",
|
|
" 16 0.963097707172332E+17 0.965012398224179E+17\n",
|
|
" 17 0.965012398224179E+17 0.966926486638428E+17\n",
|
|
" 18 0.966926486638428E+17 0.968840576394854E+17\n",
|
|
" 19 0.968840576394854E+17 0.970754664809103E+17\n",
|
|
" 20 0.970754664809103E+17 0.972668753223352E+17\n",
|
|
" 21 0.972668753223352E+17 0.974582842979779E+17\n",
|
|
" 22 0.974582842979779E+17 0.976496931394028E+17\n",
|
|
" 23 0.976496931394028E+17 0.978411019808276E+17\n",
|
|
" 24 0.978411019808276E+17 0.980325109564703E+17\n",
|
|
" 25 0.980325109564703E+17 0.982239197978952E+17\n",
|
|
" 26 0.982239197978952E+17 0.984153286393201E+17\n",
|
|
" 27 0.984153286393201E+17 0.986067376149627E+17\n",
|
|
" 28 0.986067376149627E+17 0.987981464563876E+17\n",
|
|
" 29 0.987981464563876E+17 0.989895554320302E+17\n",
|
|
" 30 0.989895554320302E+17 0.991810244029972E+17\n",
|
|
" 31 0.991810244029972E+17 0.993724332444221E+17\n",
|
|
" 32 0.993724332444221E+17 0.995638422200648E+17\n",
|
|
" 33 0.995638422200648E+17 0.997552510614897E+17\n",
|
|
" 34 0.997552510614897E+17 0.999467200324567E+17\n",
|
|
" 35 0.999467200324567E+17 0.100143568852615E+18\n",
|
|
" 36 0.100143568852615E+18 0.100840961751384E+18\n",
|
|
" 37 0.100840961751384E+18 0.101193427034571E+18\n",
|
|
" 38 0.101193427034571E+18 0.101812721724424E+18\n",
|
|
" 39 0.101812721724424E+18 0.107245430957408E+18\n",
|
|
" 40 0.107245430957408E+18 0.115866535335035E+18\n",
|
|
" 41 0.115866535335035E+18 0.204958656863666E+18\n",
|
|
" 42 0.204958656863666E+18 0.252936659161580E+18\n",
|
|
" 43 0.252936659161580E+18 0.257043514674643E+18\n",
|
|
" 44 0.257043514674643E+18 0.258590894486192E+18\n",
|
|
" 45 0.258590894486192E+18 0.259300492205621E+18\n",
|
|
" 46 0.259300492205621E+18 0.259620404321059E+18\n",
|
|
" 47 0.259620404321059E+18 0.260240103140491E+18\n",
|
|
" 48 0.260240103140491E+18 0.260431693444284E+18\n",
|
|
" 49 0.260431693444284E+18 0.260623102285709E+18\n",
|
|
" 50 0.260623102285709E+18 0.260814511127134E+18\n",
|
|
" 51 0.260814511127134E+18 0.261005920102777E+18\n",
|
|
" 52 0.261005920102777E+18 0.261197381557551E+18\n",
|
|
" 53 0.261197381557551E+18 0.261388790398976E+18\n",
|
|
" 54 0.261388790398976E+18 0.261580199374619E+18\n",
|
|
" 55 0.261580199374619E+18 0.261771608216044E+18\n",
|
|
" 56 0.261771608216044E+18 0.261963017057468E+18\n",
|
|
" 57 0.261963017057468E+18 0.262154426033111E+18\n",
|
|
" 58 0.262154426033111E+18 0.262345834874536E+18\n",
|
|
" 59 0.262345834874536E+18 0.262537243850179E+18\n",
|
|
" 60 0.262537243850179E+18 0.262728652691603E+18\n",
|
|
" 61 0.262728652691603E+18 0.262920061533028E+18\n",
|
|
" 62 0.262920061533028E+18 0.263111470508671E+18\n",
|
|
" 63 0.263111470508671E+18 0.263302879350096E+18\n",
|
|
" 64 0.263302879350096E+18 0.263494288191521E+18\n",
|
|
" 65 0.263494288191521E+18 0.263685697167163E+18\n",
|
|
" 66 0.263685697167163E+18 0.263877106008588E+18\n",
|
|
" 67 0.263877106008588E+18 0.264074332383216E+18\n",
|
|
" 68 0.264074332383216E+18 0.264505062976389E+18\n",
|
|
" 69 0.264505062976389E+18 0.265212269338558E+18\n",
|
|
" 70 0.265212269338558E+18 0.265425398098035E+18\n",
|
|
" 71 0.265425398098035E+18 0.265616859552809E+18\n",
|
|
" 72 0.265616859552809E+18 0.265859579026342E+18\n",
|
|
" 73 0.265859579026342E+18 0.268130852221747E+18\n",
|
|
" 74 0.268130852221747E+18 0.268372849603903E+18\n",
|
|
" 75 0.268372849603903E+18 0.268567500742984E+18\n",
|
|
" 76 0.268567500742984E+18 0.268759689523626E+18\n",
|
|
" 77 0.268759689523626E+18 0.269423404241650E+18\n",
|
|
" 78 0.269423404241650E+18 0.269614813217292E+18\n",
|
|
" 79 0.269614813217292E+18 0.269806222058717E+18\n",
|
|
" 80 0.269806222058717E+18 0.269997630900142E+18\n",
|
|
" 81 0.269997630900142E+18 0.306265813826929E+18\n",
|
|
" 82 0.306265813826929E+18 0.306556648074248E+18\n",
|
|
" 83 0.306556648074248E+18 0.306748056915673E+18\n",
|
|
" 84 0.306748056915673E+18 0.306939465757098E+18\n",
|
|
" 85 0.306939465757098E+18 0.307221961728066E+18\n",
|
|
" 86 0.307221961728066E+18 0.307794217399222E+18\n",
|
|
" 87 0.307794217399222E+18 0.307988715395875E+18\n",
|
|
" 88 0.307988715395875E+18 0.308180124237300E+18\n",
|
|
" 89 0.308180124237300E+18 0.310444717550600E+18\n",
|
|
" 90 0.310444717550600E+18 0.310740185664979E+18\n",
|
|
" 91 0.310740185664979E+18 0.310931594506404E+18\n",
|
|
" 92 0.310931594506404E+18 0.311123041063010E+18\n",
|
|
" 93 0.311123041063010E+18 0.311680816251929E+18\n",
|
|
" 94 0.311680816251929E+18 0.312038281548136E+18\n",
|
|
" 95 0.312038281548136E+18 0.312471011985457E+18\n",
|
|
" 96 0.312471011985457E+18 0.312662450891653E+18\n",
|
|
" 97 0.312662450891653E+18 0.312853859867296E+18\n",
|
|
" 98 0.312853859867296E+18 0.313045268708721E+18\n",
|
|
" 99 0.313045268708721E+18 0.313236677684363E+18\n",
|
|
" 100 0.313236677684363E+18 0.313428086525788E+18\n",
|
|
" 101 0.313428086525788E+18 0.313619495367213E+18\n",
|
|
" 102 0.313619495367213E+18 0.313810904342856E+18\n",
|
|
" 103 0.313810904342856E+18 0.314002313184281E+18\n",
|
|
" 104 0.314002313184281E+18 0.314193722025705E+18\n",
|
|
" 105 0.314193722025705E+18 0.314385131001348E+18\n",
|
|
" 106 0.314385131001348E+18 0.314576539842773E+18\n",
|
|
" 107 0.314576539842773E+18 0.314767948684198E+18\n",
|
|
" 108 0.314767948684198E+18 0.314959357659841E+18\n",
|
|
" 109 0.314959357659841E+18 0.315150766501265E+18\n",
|
|
" 110 0.315150766501265E+18 0.315342175476908E+18\n",
|
|
" 111 0.315342175476908E+18 0.315533614383104E+18\n",
|
|
" 112 0.315533614383104E+18 0.315725023224529E+18\n",
|
|
" 113 0.315725023224529E+18 0.315916432200172E+18\n",
|
|
" 114 0.315916432200172E+18 0.316107878622560E+18\n",
|
|
" 115 0.316107878622560E+18 0.316302087245791E+18\n",
|
|
" 116 0.316302087245791E+18 0.316995494012256E+18\n",
|
|
" 117 0.316995494012256E+18 0.317341733203476E+18\n",
|
|
" 118 0.317341733203476E+18 0.317950474621813E+18\n",
|
|
" 119 0.317950474621813E+18 0.322765279123735E+18\n",
|
|
" 120 0.322765279123735E+18 0.323602548101480E+18\n",
|
|
" 121 0.323602548101480E+18 0.404285202853003E+18\n",
|
|
" 122 0.404285202853003E+18 0.493377324381635E+18\n",
|
|
" 123 0.493377324381635E+18 0.505798757690900E+18\n",
|
|
" 124 0.505798757690900E+18 0.506944051119915E+18\n",
|
|
" 125 0.506944051119915E+18 0.507135512574689E+18\n",
|
|
" 126 0.507135512574689E+18 0.507326921550332E+18\n",
|
|
" 127 0.507326921550332E+18 0.507518330391757E+18\n",
|
|
" 128 0.507518330391757E+18 0.507896890285621E+18\n",
|
|
" 129 0.507896890285621E+18 0.508206872973541E+18\n",
|
|
" 130 0.508206872973541E+18 0.508401475257369E+18\n",
|
|
" 131 0.508401475257369E+18 0.508600811534680E+18\n",
|
|
" 132 0.508600811534680E+18 0.509602348381766E+18\n",
|
|
" 133 0.509602348381766E+18 0.514502795336876E+18\n",
|
|
" 134 0.514502795336876E+18 0.515690615787225E+18\n",
|
|
" 135 0.515690615787225E+18 0.516460272584491E+18\n",
|
|
" 136 0.516460272584491E+18 0.516797047278404E+18\n",
|
|
" 137 0.516797047278404E+18 0.516988456254046E+18\n",
|
|
" 138 0.516988456254046E+18 0.517179865095471E+18\n",
|
|
" 139 0.517179865095471E+18 0.517371326550245E+18\n",
|
|
" 140 0.517371326550245E+18 0.517587226905805E+18\n",
|
|
" 141 0.517587226905805E+18 0.517778688494797E+18\n",
|
|
" 142 0.517778688494797E+18 0.517970097336222E+18\n",
|
|
" 143 0.517970097336222E+18 0.518161506177647E+18\n",
|
|
" 144 0.518161506177647E+18 0.518352915153289E+18\n",
|
|
" 145 0.518352915153289E+18 0.518544323994714E+18\n",
|
|
" 146 0.518544323994714E+18 0.518735732970357E+18\n",
|
|
" 147 0.518735732970357E+18 0.518927141811782E+18\n",
|
|
" 148 0.518927141811782E+18 0.519118550653207E+18\n",
|
|
" 149 0.519118550653207E+18 0.519309959628849E+18\n",
|
|
" 150 0.519309959628849E+18 0.519501368470274E+18\n",
|
|
" 151 0.519501368470274E+18 0.519692777311699E+18\n",
|
|
" 152 0.519692777311699E+18 0.519884186287342E+18\n",
|
|
" 153 0.519884186287342E+18 0.520075595128766E+18\n",
|
|
" 154 0.520075595128766E+18 0.520267003970191E+18\n",
|
|
" 155 0.520267003970191E+18 0.520458412945834E+18\n",
|
|
" 156 0.520458412945834E+18 0.520649874400608E+18\n",
|
|
" 157 0.520649874400608E+18 0.520844424205304E+18\n",
|
|
" 158 0.520844424205304E+18 0.521057601685815E+18\n",
|
|
" 159 0.521057601685815E+18 0.521249010661458E+18\n",
|
|
" 160 0.521249010661458E+18 0.521948424208122E+18\n",
|
|
" 161 0.521948424208122E+18 0.522338053038014E+18\n",
|
|
" 162 0.522338053038014E+18 0.598485619475218E+18\n",
|
|
" 163 0.598485619475218E+18 0.630677923535258E+18\n",
|
|
" 164 0.630677923535258E+18 0.631528434165613E+18\n",
|
|
" 165 0.631528434165613E+18 0.631765173702492E+18\n",
|
|
" 166 0.631765173702492E+18 0.631956582543917E+18\n",
|
|
" 167 0.631956582543917E+18 0.632172306134729E+18\n",
|
|
" 168 0.632172306134729E+18 0.632363767589503E+18\n",
|
|
" 169 0.632363767589503E+18 0.632555176430928E+18\n",
|
|
" 170 0.632555176430928E+18 0.632746585406570E+18\n",
|
|
" 171 0.632746585406570E+18 0.632937994247995E+18\n",
|
|
" 172 0.632937994247995E+18 0.633129403089420E+18\n",
|
|
" 173 0.633129403089420E+18 0.633320812065063E+18\n",
|
|
" 174 0.633320812065063E+18 0.633512220906488E+18\n",
|
|
" 175 0.633512220906488E+18 0.633703629747913E+18\n",
|
|
" 176 0.633703629747913E+18 0.633895038723555E+18\n",
|
|
" 177 0.633895038723555E+18 0.634086447564980E+18\n",
|
|
" 178 0.634086447564980E+18 0.634277856540623E+18\n",
|
|
" 179 0.634277856540623E+18 0.634469265382048E+18\n",
|
|
" 180 0.634469265382048E+18 0.634660674223473E+18\n",
|
|
" 181 0.634660674223473E+18 0.634852083199115E+18\n",
|
|
" 182 0.634852083199115E+18 0.635043492040540E+18\n",
|
|
" 183 0.635043492040540E+18 0.635234938462929E+18\n",
|
|
" 184 0.635234938462929E+18 0.635447299497001E+18\n",
|
|
" 185 0.635447299497001E+18 0.635641591737876E+18\n",
|
|
" 186 0.635641591737876E+18 0.635833030778290E+18\n",
|
|
" 187 0.635833030778290E+18 0.636024439619715E+18\n",
|
|
" 188 0.636024439619715E+18 0.636215848461140E+18\n",
|
|
" 189 0.636215848461140E+18 0.636750937767018E+18\n",
|
|
" 190 0.636750937767018E+18 0.638195828250378E+18\n",
|
|
" 191 0.638195828250378E+18 0.643163132008595E+18\n",
|
|
" 192 0.643163132008595E+18 0.643481123736781E+18\n",
|
|
" 193 0.643481123736781E+18 0.644410277365809E+18\n",
|
|
" 194 0.644410277365809E+18 0.644604712548565E+18\n",
|
|
" 195 0.644604712548565E+18 0.644796121389990E+18\n",
|
|
" 196 0.644796121389990E+18 0.645181291506958E+18\n",
|
|
" 197 0.645181291506958E+18 0.645480259617030E+18\n",
|
|
" 198 0.645480259617030E+18 0.645671668458455E+18\n",
|
|
" 199 0.645671668458455E+18 0.645863077434098E+18\n",
|
|
" 200 0.645863077434098E+18 0.646078413001458E+18\n",
|
|
" 201 0.646078413001458E+18 0.647196133008867E+18\n",
|
|
" 202 0.647196133008867E+18 0.692703801651495E+18\n",
|
|
" 203 0.692703801651495E+18 0.781795991899603E+18\n",
|
|
" 204 0.781795991899603E+18 0.829396574483251E+18\n",
|
|
" 205 0.829396574483251E+18 0.833478057611231E+18\n",
|
|
" 206 0.833478057611231E+18 0.835041939358220E+18\n",
|
|
" 207 0.835041939358220E+18 0.835748986135511E+18\n",
|
|
" 208 0.835748986135511E+18 0.836066892501221E+18\n",
|
|
" 209 0.836066892501221E+18 0.836684653485097E+18\n",
|
|
" 210 0.836684653485097E+18 0.836876197752209E+18\n",
|
|
" 211 0.836876197752209E+18 0.837067606593634E+18\n",
|
|
" 212 0.837067606593634E+18 0.837259015435059E+18\n",
|
|
" 213 0.837259015435059E+18 0.837450424410702E+18\n",
|
|
" 214 0.837450424410702E+18 0.837641863316898E+18\n",
|
|
" 215 0.837641863316898E+18 0.837833272158323E+18\n",
|
|
" 216 0.837833272158323E+18 0.838024681133965E+18\n",
|
|
" 217 0.838024681133965E+18 0.838216089975390E+18\n",
|
|
" 218 0.838216089975390E+18 0.838407498951033E+18\n",
|
|
" 219 0.838407498951033E+18 0.838598907792458E+18\n",
|
|
" 220 0.838598907792458E+18 0.838790316633883E+18\n",
|
|
" 221 0.838790316633883E+18 0.838981725609525E+18\n",
|
|
" 222 0.838981725609525E+18 0.839173134450950E+18\n",
|
|
" 223 0.839173134450950E+18 0.839364543292375E+18\n",
|
|
" 224 0.839364543292375E+18 0.839555952268018E+18\n",
|
|
" 225 0.839555952268018E+18 0.839747361109443E+18\n",
|
|
" 226 0.839747361109443E+18 0.839938769950867E+18\n",
|
|
" 227 0.839938769950867E+18 0.840130178926510E+18\n",
|
|
" 228 0.840130178926510E+18 0.840321587767935E+18\n",
|
|
" 229 0.840321587767935E+18 0.840515962821149E+18\n",
|
|
" 230 0.840515962821149E+18 0.840945666917138E+18\n",
|
|
" 231 0.840945666917138E+18 0.841646435928637E+18\n",
|
|
" 232 0.841646435928637E+18 0.841858285861601E+18\n",
|
|
" 233 0.841858285861601E+18 0.842049724767797E+18\n",
|
|
" 234 0.842049724767797E+18 0.842281563210121E+18\n",
|
|
" 235 0.842281563210121E+18 0.842722369393918E+18\n",
|
|
" 236 0.842722369393918E+18 0.844794685611311E+18\n",
|
|
" 237 0.844794685611311E+18 0.844986094452736E+18\n",
|
|
" 238 0.844986094452736E+18 0.845180402799739E+18\n",
|
|
" 239 0.845180402799739E+18 0.845839342990524E+18\n",
|
|
" 240 0.845839342990524E+18 0.846030781896720E+18\n",
|
|
" 241 0.846030781896720E+18 0.846222190738145E+18\n",
|
|
" 242 0.846222190738145E+18 0.846413599713788E+18\n",
|
|
" 243 0.846413599713788E+18 0.864502974527832E+18\n",
|
|
" 244 0.864502974527832E+18 0.882968182065725E+18\n",
|
|
" 245 0.882968182065725E+18 0.883159590907150E+18\n",
|
|
" 246 0.883159590907150E+18 0.883350999882793E+18\n",
|
|
" 247 0.883350999882793E+18 0.883542438788989E+18\n",
|
|
" 248 0.883542438788989E+18 0.884202639686894E+18\n",
|
|
" 249 0.884202639686894E+18 0.884397114195444E+18\n",
|
|
" 250 0.884397114195444E+18 0.884588523036869E+18\n",
|
|
" 251 0.884588523036869E+18 0.886662527579062E+18\n",
|
|
" 252 0.886662527579062E+18 0.887140268334121E+18\n",
|
|
" 253 0.887140268334121E+18 0.887338684146254E+18\n",
|
|
" 254 0.887338684146254E+18 0.887530145735246E+18\n",
|
|
" 255 0.887530145735246E+18 0.887743060014793E+18\n",
|
|
" 256 0.887743060014793E+18 0.888448298610852E+18\n",
|
|
" 257 0.888448298610852E+18 0.888883030502932E+18\n",
|
|
" 258 0.888883030502932E+18 0.889075884332417E+18\n",
|
|
" 259 0.889075884332417E+18 0.889267293308060E+18\n",
|
|
" 260 0.889267293308060E+18 0.889458702149485E+18\n",
|
|
" 261 0.889458702149485E+18 0.889650110990909E+18\n",
|
|
" 262 0.889650110990909E+18 0.889841519966552E+18\n",
|
|
" 263 0.889841519966552E+18 0.890032928807977E+18\n",
|
|
" 264 0.890032928807977E+18 0.890224337783620E+18\n",
|
|
" 265 0.890224337783620E+18 0.890415746625044E+18\n",
|
|
" 266 0.890415746625044E+18 0.890607155466469E+18\n",
|
|
" 267 0.890607155466469E+18 0.890798564442112E+18\n",
|
|
" 268 0.890798564442112E+18 0.890989973283537E+18\n",
|
|
" 269 0.890989973283537E+18 0.891181382124962E+18\n",
|
|
" 270 0.891181382124962E+18 0.891372791100604E+18\n",
|
|
" 271 0.891372791100604E+18 0.891564199942029E+18\n",
|
|
" 272 0.891564199942029E+18 0.891755608783454E+18\n",
|
|
" 273 0.891755608783454E+18 0.891947055340061E+18\n",
|
|
" 274 0.891947055340061E+18 0.892138464181486E+18\n",
|
|
" 275 0.892138464181486E+18 0.892329873022910E+18\n",
|
|
" 276 0.892329873022910E+18 0.892521312063324E+18\n",
|
|
" 277 0.892521312063324E+18 0.892712833647641E+18\n",
|
|
" 278 0.892712833647641E+18 0.893333954101248E+18\n",
|
|
" 279 0.893333954101248E+18 0.893653827830415E+18\n",
|
|
" 280 0.893653827830415E+18 0.894359090988319E+18\n",
|
|
" 281 0.894359090988319E+18 0.899130547593282E+18\n",
|
|
" 282 0.899130547593282E+18 0.900009270521627E+18\n",
|
|
" 283 0.900009270521627E+18 0.958721087984632E+18\n",
|
|
" 284 0.958721087984632E+18 0.104545954810770E+19\n",
|
|
" 285 0.104545954810770E+19 0.104631566863643E+19\n",
|
|
" 286 0.104631566863643E+19 0.105113412305525E+19\n",
|
|
" 287 0.105113412305525E+19 0.105174324551772E+19\n",
|
|
" 288 0.105174324551772E+19 0.105209241884269E+19\n",
|
|
" 289 0.105209241884269E+19 0.105278706349926E+19\n",
|
|
" 290 0.105278706349926E+19 0.105298166296451E+19\n",
|
|
" 291 0.105298166296451E+19 0.105317312455351E+19\n",
|
|
" 292 0.105317312455351E+19 0.105336453339493E+19\n",
|
|
" 293 0.105336453339493E+19 0.105355594223636E+19\n",
|
|
" 294 0.105355594223636E+19 0.105374735121200E+19\n",
|
|
" 295 0.105374735121200E+19 0.105393881266677E+19\n",
|
|
" 296 0.105393881266677E+19 0.105413022150820E+19\n",
|
|
" 297 0.105413022150820E+19 0.105432163048384E+19\n",
|
|
" 298 0.105432163048384E+19 0.105451303932527E+19\n",
|
|
" 299 0.105451303932527E+19 0.105470444830091E+19\n",
|
|
" 300 0.105470444830091E+19 0.105489585714233E+19\n",
|
|
" 301 0.105489585714233E+19 0.105508726598376E+19\n",
|
|
" 302 0.105508726598376E+19 0.105527867495940E+19\n",
|
|
" 303 0.105527867495940E+19 0.105547008380083E+19\n",
|
|
" 304 0.105547008380083E+19 0.105566149264225E+19\n",
|
|
" 305 0.105566149264225E+19 0.105585290161789E+19\n",
|
|
" 306 0.105585290161789E+19 0.105604431045932E+19\n",
|
|
" 307 0.105604431045932E+19 0.105623571930074E+19\n",
|
|
" 308 0.105623571930074E+19 0.105642712827639E+19\n",
|
|
" 309 0.105642712827639E+19 0.105661858973116E+19\n",
|
|
" 310 0.105661858973116E+19 0.105705459105451E+19\n",
|
|
" 311 0.105705459105451E+19 0.105742519707160E+19\n",
|
|
" 312 0.105742519707160E+19 0.105797542036583E+19\n",
|
|
" 313 0.105797542036583E+19 0.105816688182061E+19\n",
|
|
" 314 0.105816688182061E+19 0.105835829066203E+19\n",
|
|
" 315 0.105835829066203E+19 0.105865633938067E+19\n",
|
|
" 316 0.105865633938067E+19 0.106092287187170E+19\n",
|
|
" 317 0.106092287187170E+19 0.106111428071313E+19\n",
|
|
" 318 0.106111428071313E+19 0.106130893198642E+19\n",
|
|
" 319 0.106130893198642E+19 0.106188462242346E+19\n",
|
|
" 320 0.106188462242346E+19 0.106216483535087E+19\n",
|
|
" 321 0.106216483535087E+19 0.106235624432651E+19\n",
|
|
" 322 0.106235624432651E+19 0.106254765316794E+19\n",
|
|
" 323 0.106254765316794E+19 0.106382938307822E+19\n",
|
|
" 324 0.106382938307822E+19 0.115292150460685E+19\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"!cat /cosma8/data/dp016/dc-stis1/csiborg_new/ramses_out_7444_new/output_00001/info_00001.txt"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 10,
|
|
"id": "dc8ade85",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"'/cosma8/data/dp016/dc-stis1/csiborg_dump'"
|
|
]
|
|
},
|
|
"execution_count": 10,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"paths.dumpdir\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 8,
|
|
"id": "1891c6ff",
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"101"
|
|
]
|
|
},
|
|
"execution_count": 8,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"len(paths.get_ics(tonew=True))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "7101a155",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
" fname = \"ramses_out_{}_{}.npy\".format(\n",
|
|
" str(self.nsim).zfill(5), str(self.nsnap).zfill(5))\n",
|
|
" data = numpy.load(join(self.paths.dumpdir, fname))\n"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 2,
|
|
"id": "190d39e6",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T14:16:12.485845Z",
|
|
"start_time": "2023-03-24T14:16:01.930739Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"cat0 = csiborgtools.read.ClumpsCatalogue(7468)\n",
|
|
"catx = csiborgtools.read.ClumpsCatalogue(7588)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"id": "09c93ab0",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T14:16:31.435607Z",
|
|
"start_time": "2023-03-24T14:16:12.487458Z"
|
|
},
|
|
"scrolled": true
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"reader = csiborgtools.read.PairOverlap(cat0, catx, max_dist=150 / 0.705)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 31,
|
|
"id": "650cbe8a",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T14:27:04.213308Z",
|
|
"start_time": "2023-03-24T14:27:00.679174Z"
|
|
},
|
|
"scrolled": false
|
|
},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"application/javascript": "/* Put everything inside the global mpl namespace */\n/* global mpl */\nwindow.mpl = {};\n\nmpl.get_websocket_type = function () {\n if (typeof WebSocket !== 'undefined') {\n return WebSocket;\n } else if (typeof MozWebSocket !== 'undefined') {\n return MozWebSocket;\n } else {\n alert(\n 'Your browser does not have WebSocket support. ' +\n 'Please try Chrome, Safari or Firefox ≥ 6. ' +\n 'Firefox 4 and 5 are also supported but you ' +\n 'have to enable WebSockets in about:config.'\n );\n }\n};\n\nmpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n this.id = figure_id;\n\n this.ws = websocket;\n\n this.supports_binary = this.ws.binaryType !== undefined;\n\n if (!this.supports_binary) {\n var warnings = document.getElementById('mpl-warnings');\n if (warnings) {\n warnings.style.display = 'block';\n warnings.textContent =\n 'This browser does not support binary websocket messages. ' +\n 'Performance may be slow.';\n }\n }\n\n this.imageObj = new Image();\n\n this.context = undefined;\n this.message = undefined;\n this.canvas = undefined;\n this.rubberband_canvas = undefined;\n this.rubberband_context = undefined;\n this.format_dropdown = undefined;\n\n this.image_mode = 'full';\n\n this.root = document.createElement('div');\n this.root.setAttribute('style', 'display: inline-block');\n this._root_extra_style(this.root);\n\n parent_element.appendChild(this.root);\n\n this._init_header(this);\n this._init_canvas(this);\n this._init_toolbar(this);\n\n var fig = this;\n\n this.waiting = false;\n\n this.ws.onopen = function () {\n fig.send_message('supports_binary', { value: fig.supports_binary });\n fig.send_message('send_image_mode', {});\n if (fig.ratio !== 1) {\n fig.send_message('set_device_pixel_ratio', {\n device_pixel_ratio: fig.ratio,\n });\n }\n fig.send_message('refresh', {});\n };\n\n this.imageObj.onload = function () {\n if (fig.image_mode === 'full') {\n // Full images could contain transparency (where diff images\n // almost always do), so we need to clear the canvas so that\n // there is no ghosting.\n fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n }\n fig.context.drawImage(fig.imageObj, 0, 0);\n };\n\n this.imageObj.onunload = function () {\n fig.ws.close();\n };\n\n this.ws.onmessage = this._make_on_message_function(this);\n\n this.ondownload = ondownload;\n};\n\nmpl.figure.prototype._init_header = function () {\n var titlebar = document.createElement('div');\n titlebar.classList =\n 'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n var titletext = document.createElement('div');\n titletext.classList = 'ui-dialog-title';\n titletext.setAttribute(\n 'style',\n 'width: 100%; text-align: center; padding: 3px;'\n );\n titlebar.appendChild(titletext);\n this.root.appendChild(titlebar);\n this.header = titletext;\n};\n\nmpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n\nmpl.figure.prototype._init_canvas = function () {\n var fig = this;\n\n var canvas_div = (this.canvas_div = document.createElement('div'));\n canvas_div.setAttribute(\n 'style',\n 'border: 1px solid #ddd;' +\n 'box-sizing: content-box;' +\n 'clear: both;' +\n 'min-height: 1px;' +\n 'min-width: 1px;' +\n 'outline: 0;' +\n 'overflow: hidden;' +\n 'position: relative;' +\n 'resize: both;'\n );\n\n function on_keyboard_event_closure(name) {\n return function (event) {\n return fig.key_event(event, name);\n };\n }\n\n canvas_div.addEventListener(\n 'keydown',\n on_keyboard_event_closure('key_press')\n );\n canvas_div.addEventListener(\n 'keyup',\n on_keyboard_event_closure('key_release')\n );\n\n this._canvas_extra_style(canvas_div);\n this.root.appendChild(canvas_div);\n\n var canvas = (this.canvas = document.createElement('canvas'));\n canvas.classList.add('mpl-canvas');\n canvas.setAttribute('style', 'box-sizing: content-box;');\n\n this.context = canvas.getContext('2d');\n\n var backingStore =\n this.context.backingStorePixelRatio ||\n this.context.webkitBackingStorePixelRatio ||\n this.context.mozBackingStorePixelRatio ||\n this.context.msBackingStorePixelRatio ||\n this.context.oBackingStorePixelRatio ||\n this.context.backingStorePixelRatio ||\n 1;\n\n this.ratio = (window.devicePixelRatio || 1) / backingStore;\n\n var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n 'canvas'\n ));\n rubberband_canvas.setAttribute(\n 'style',\n 'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n );\n\n // Apply a ponyfill if ResizeObserver is not implemented by browser.\n if (this.ResizeObserver === undefined) {\n if (window.ResizeObserver !== undefined) {\n this.ResizeObserver = window.ResizeObserver;\n } else {\n var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n this.ResizeObserver = obs.ResizeObserver;\n }\n }\n\n this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n var nentries = entries.length;\n for (var i = 0; i < nentries; i++) {\n var entry = entries[i];\n var width, height;\n if (entry.contentBoxSize) {\n if (entry.contentBoxSize instanceof Array) {\n // Chrome 84 implements new version of spec.\n width = entry.contentBoxSize[0].inlineSize;\n height = entry.contentBoxSize[0].blockSize;\n } else {\n // Firefox implements old version of spec.\n width = entry.contentBoxSize.inlineSize;\n height = entry.contentBoxSize.blockSize;\n }\n } else {\n // Chrome <84 implements even older version of spec.\n width = entry.contentRect.width;\n height = entry.contentRect.height;\n }\n\n // Keep the size of the canvas and rubber band canvas in sync with\n // the canvas container.\n if (entry.devicePixelContentBoxSize) {\n // Chrome 84 implements new version of spec.\n canvas.setAttribute(\n 'width',\n entry.devicePixelContentBoxSize[0].inlineSize\n );\n canvas.setAttribute(\n 'height',\n entry.devicePixelContentBoxSize[0].blockSize\n );\n } else {\n canvas.setAttribute('width', width * fig.ratio);\n canvas.setAttribute('height', height * fig.ratio);\n }\n canvas.setAttribute(\n 'style',\n 'width: ' + width + 'px; height: ' + height + 'px;'\n );\n\n rubberband_canvas.setAttribute('width', width);\n rubberband_canvas.setAttribute('height', height);\n\n // And update the size in Python. We ignore the initial 0/0 size\n // that occurs as the element is placed into the DOM, which should\n // otherwise not happen due to the minimum size styling.\n if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n fig.request_resize(width, height);\n }\n }\n });\n this.resizeObserverInstance.observe(canvas_div);\n\n function on_mouse_event_closure(name) {\n return function (event) {\n return fig.mouse_event(event, name);\n };\n }\n\n rubberband_canvas.addEventListener(\n 'mousedown',\n on_mouse_event_closure('button_press')\n );\n rubberband_canvas.addEventListener(\n 'mouseup',\n on_mouse_event_closure('button_release')\n );\n rubberband_canvas.addEventListener(\n 'dblclick',\n on_mouse_event_closure('dblclick')\n );\n // Throttle sequential mouse events to 1 every 20ms.\n rubberband_canvas.addEventListener(\n 'mousemove',\n on_mouse_event_closure('motion_notify')\n );\n\n rubberband_canvas.addEventListener(\n 'mouseenter',\n on_mouse_event_closure('figure_enter')\n );\n rubberband_canvas.addEventListener(\n 'mouseleave',\n on_mouse_event_closure('figure_leave')\n );\n\n canvas_div.addEventListener('wheel', function (event) {\n if (event.deltaY < 0) {\n event.step = 1;\n } else {\n event.step = -1;\n }\n on_mouse_event_closure('scroll')(event);\n });\n\n canvas_div.appendChild(canvas);\n canvas_div.appendChild(rubberband_canvas);\n\n this.rubberband_context = rubberband_canvas.getContext('2d');\n this.rubberband_context.strokeStyle = '#000000';\n\n this._resize_canvas = function (width, height, forward) {\n if (forward) {\n canvas_div.style.width = width + 'px';\n canvas_div.style.height = height + 'px';\n }\n };\n\n // Disable right mouse context menu.\n this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n event.preventDefault();\n return false;\n });\n\n function set_focus() {\n canvas.focus();\n canvas_div.focus();\n }\n\n window.setTimeout(set_focus, 100);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n var fig = this;\n\n var toolbar = document.createElement('div');\n toolbar.classList = 'mpl-toolbar';\n this.root.appendChild(toolbar);\n\n function on_click_closure(name) {\n return function (_event) {\n return fig.toolbar_button_onclick(name);\n };\n }\n\n function on_mouseover_closure(tooltip) {\n return function (event) {\n if (!event.currentTarget.disabled) {\n return fig.toolbar_button_onmouseover(tooltip);\n }\n };\n }\n\n fig.buttons = {};\n var buttonGroup = document.createElement('div');\n buttonGroup.classList = 'mpl-button-group';\n for (var toolbar_ind in mpl.toolbar_items) {\n var name = mpl.toolbar_items[toolbar_ind][0];\n var tooltip = mpl.toolbar_items[toolbar_ind][1];\n var image = mpl.toolbar_items[toolbar_ind][2];\n var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n if (!name) {\n /* Instead of a spacer, we start a new button group. */\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n buttonGroup = document.createElement('div');\n buttonGroup.classList = 'mpl-button-group';\n continue;\n }\n\n var button = (fig.buttons[name] = document.createElement('button'));\n button.classList = 'mpl-widget';\n button.setAttribute('role', 'button');\n button.setAttribute('aria-disabled', 'false');\n button.addEventListener('click', on_click_closure(method_name));\n button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n\n var icon_img = document.createElement('img');\n icon_img.src = '_images/' + image + '.png';\n icon_img.srcset = '_images/' + image + '_large.png 2x';\n icon_img.alt = tooltip;\n button.appendChild(icon_img);\n\n buttonGroup.appendChild(button);\n }\n\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n\n var fmt_picker = document.createElement('select');\n fmt_picker.classList = 'mpl-widget';\n toolbar.appendChild(fmt_picker);\n this.format_dropdown = fmt_picker;\n\n for (var ind in mpl.extensions) {\n var fmt = mpl.extensions[ind];\n var option = document.createElement('option');\n option.selected = fmt === mpl.default_extension;\n option.innerHTML = fmt;\n fmt_picker.appendChild(option);\n }\n\n var status_bar = document.createElement('span');\n status_bar.classList = 'mpl-message';\n toolbar.appendChild(status_bar);\n this.message = status_bar;\n};\n\nmpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n // which will in turn request a refresh of the image.\n this.send_message('resize', { width: x_pixels, height: y_pixels });\n};\n\nmpl.figure.prototype.send_message = function (type, properties) {\n properties['type'] = type;\n properties['figure_id'] = this.id;\n this.ws.send(JSON.stringify(properties));\n};\n\nmpl.figure.prototype.send_draw_message = function () {\n if (!this.waiting) {\n this.waiting = true;\n this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n var format_dropdown = fig.format_dropdown;\n var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n fig.ondownload(fig, format);\n};\n\nmpl.figure.prototype.handle_resize = function (fig, msg) {\n var size = msg['size'];\n if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n fig._resize_canvas(size[0], size[1], msg['forward']);\n fig.send_message('refresh', {});\n }\n};\n\nmpl.figure.prototype.handle_rubberband = function (fig, msg) {\n var x0 = msg['x0'] / fig.ratio;\n var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n var x1 = msg['x1'] / fig.ratio;\n var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n x0 = Math.floor(x0) + 0.5;\n y0 = Math.floor(y0) + 0.5;\n x1 = Math.floor(x1) + 0.5;\n y1 = Math.floor(y1) + 0.5;\n var min_x = Math.min(x0, x1);\n var min_y = Math.min(y0, y1);\n var width = Math.abs(x1 - x0);\n var height = Math.abs(y1 - y0);\n\n fig.rubberband_context.clearRect(\n 0,\n 0,\n fig.canvas.width / fig.ratio,\n fig.canvas.height / fig.ratio\n );\n\n fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n};\n\nmpl.figure.prototype.handle_figure_label = function (fig, msg) {\n // Updates the figure title.\n fig.header.textContent = msg['label'];\n};\n\nmpl.figure.prototype.handle_cursor = function (fig, msg) {\n fig.rubberband_canvas.style.cursor = msg['cursor'];\n};\n\nmpl.figure.prototype.handle_message = function (fig, msg) {\n fig.message.textContent = msg['message'];\n};\n\nmpl.figure.prototype.handle_draw = function (fig, _msg) {\n // Request the server to send over a new figure.\n fig.send_draw_message();\n};\n\nmpl.figure.prototype.handle_image_mode = function (fig, msg) {\n fig.image_mode = msg['mode'];\n};\n\nmpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n for (var key in msg) {\n if (!(key in fig.buttons)) {\n continue;\n }\n fig.buttons[key].disabled = !msg[key];\n fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n }\n};\n\nmpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n if (msg['mode'] === 'PAN') {\n fig.buttons['Pan'].classList.add('active');\n fig.buttons['Zoom'].classList.remove('active');\n } else if (msg['mode'] === 'ZOOM') {\n fig.buttons['Pan'].classList.remove('active');\n fig.buttons['Zoom'].classList.add('active');\n } else {\n fig.buttons['Pan'].classList.remove('active');\n fig.buttons['Zoom'].classList.remove('active');\n }\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n // Called whenever the canvas gets updated.\n this.send_message('ack', {});\n};\n\n// A function to construct a web socket function for onmessage handling.\n// Called in the figure constructor.\nmpl.figure.prototype._make_on_message_function = function (fig) {\n return function socket_on_message(evt) {\n if (evt.data instanceof Blob) {\n var img = evt.data;\n if (img.type !== 'image/png') {\n /* FIXME: We get \"Resource interpreted as Image but\n * transferred with MIME type text/plain:\" errors on\n * Chrome. But how to set the MIME type? It doesn't seem\n * to be part of the websocket stream */\n img.type = 'image/png';\n }\n\n /* Free the memory for the previous frames */\n if (fig.imageObj.src) {\n (window.URL || window.webkitURL).revokeObjectURL(\n fig.imageObj.src\n );\n }\n\n fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n img\n );\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n } else if (\n typeof evt.data === 'string' &&\n evt.data.slice(0, 21) === 'data:image/png;base64'\n ) {\n fig.imageObj.src = evt.data;\n fig.updated_canvas_event();\n fig.waiting = false;\n return;\n }\n\n var msg = JSON.parse(evt.data);\n var msg_type = msg['type'];\n\n // Call the \"handle_{type}\" callback, which takes\n // the figure and JSON message as its only arguments.\n try {\n var callback = fig['handle_' + msg_type];\n } catch (e) {\n console.log(\n \"No handler for the '\" + msg_type + \"' message type: \",\n msg\n );\n return;\n }\n\n if (callback) {\n try {\n // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n callback(fig, msg);\n } catch (e) {\n console.log(\n \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n e,\n e.stack,\n msg\n );\n }\n }\n };\n};\n\n// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\nmpl.findpos = function (e) {\n //this section is from http://www.quirksmode.org/js/events_properties.html\n var targ;\n if (!e) {\n e = window.event;\n }\n if (e.target) {\n targ = e.target;\n } else if (e.srcElement) {\n targ = e.srcElement;\n }\n if (targ.nodeType === 3) {\n // defeat Safari bug\n targ = targ.parentNode;\n }\n\n // pageX,Y are the mouse positions relative to the document\n var boundingRect = targ.getBoundingClientRect();\n var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n\n return { x: x, y: y };\n};\n\n/*\n * return a copy of an object with only non-object keys\n * we need this to avoid circular references\n * https://stackoverflow.com/a/24161582/3208463\n */\nfunction simpleKeys(original) {\n return Object.keys(original).reduce(function (obj, key) {\n if (typeof original[key] !== 'object') {\n obj[key] = original[key];\n }\n return obj;\n }, {});\n}\n\nmpl.figure.prototype.mouse_event = function (event, name) {\n var canvas_pos = mpl.findpos(event);\n\n if (name === 'button_press') {\n this.canvas.focus();\n this.canvas_div.focus();\n }\n\n var x = canvas_pos.x * this.ratio;\n var y = canvas_pos.y * this.ratio;\n\n this.send_message(name, {\n x: x,\n y: y,\n button: event.button,\n step: event.step,\n guiEvent: simpleKeys(event),\n });\n\n /* This prevents the web browser from automatically changing to\n * the text insertion cursor when the button is pressed. We want\n * to control all of the cursor setting manually through the\n * 'cursor' event from matplotlib */\n event.preventDefault();\n return false;\n};\n\nmpl.figure.prototype._key_event_extra = function (_event, _name) {\n // Handle any extra behaviour associated with a key event\n};\n\nmpl.figure.prototype.key_event = function (event, name) {\n // Prevent repeat events\n if (name === 'key_press') {\n if (event.key === this._key) {\n return;\n } else {\n this._key = event.key;\n }\n }\n if (name === 'key_release') {\n this._key = null;\n }\n\n var value = '';\n if (event.ctrlKey && event.key !== 'Control') {\n value += 'ctrl+';\n }\n else if (event.altKey && event.key !== 'Alt') {\n value += 'alt+';\n }\n else if (event.shiftKey && event.key !== 'Shift') {\n value += 'shift+';\n }\n\n value += 'k' + event.key;\n\n this._key_event_extra(event, name);\n\n this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n return false;\n};\n\nmpl.figure.prototype.toolbar_button_onclick = function (name) {\n if (name === 'download') {\n this.handle_save(this, null);\n } else {\n this.send_message('toolbar_button', { name: name });\n }\n};\n\nmpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n this.message.textContent = tooltip;\n};\n\n///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n// prettier-ignore\nvar _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\nmpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o\", \"download\"]];\n\nmpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\", \"webp\"];\n\nmpl.default_extension = \"png\";/* global mpl */\n\nvar comm_websocket_adapter = function (comm) {\n // Create a \"websocket\"-like object which calls the given IPython comm\n // object with the appropriate methods. Currently this is a non binary\n // socket, so there is still some room for performance tuning.\n var ws = {};\n\n ws.binaryType = comm.kernel.ws.binaryType;\n ws.readyState = comm.kernel.ws.readyState;\n function updateReadyState(_event) {\n if (comm.kernel.ws) {\n ws.readyState = comm.kernel.ws.readyState;\n } else {\n ws.readyState = 3; // Closed state.\n }\n }\n comm.kernel.ws.addEventListener('open', updateReadyState);\n comm.kernel.ws.addEventListener('close', updateReadyState);\n comm.kernel.ws.addEventListener('error', updateReadyState);\n\n ws.close = function () {\n comm.close();\n };\n ws.send = function (m) {\n //console.log('sending', m);\n comm.send(m);\n };\n // Register the callback with on_msg.\n comm.on_msg(function (msg) {\n //console.log('receiving', msg['content']['data'], msg);\n var data = msg['content']['data'];\n if (data['blob'] !== undefined) {\n data = {\n data: new Blob(msg['buffers'], { type: data['blob'] }),\n };\n }\n // Pass the mpl event to the overridden (by mpl) onmessage function.\n ws.onmessage(data);\n });\n return ws;\n};\n\nmpl.mpl_figure_comm = function (comm, msg) {\n // This is the function which gets called when the mpl process\n // starts-up an IPython Comm through the \"matplotlib\" channel.\n\n var id = msg.content.data.id;\n // Get hold of the div created by the display call when the Comm\n // socket was opened in Python.\n var element = document.getElementById(id);\n var ws_proxy = comm_websocket_adapter(comm);\n\n function ondownload(figure, _format) {\n window.open(figure.canvas.toDataURL());\n }\n\n var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n\n // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n // web socket which is closed, not our websocket->open comm proxy.\n ws_proxy.onopen();\n\n fig.parent_element = element;\n fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n if (!fig.cell_info) {\n console.error('Failed to find cell for figure', id, fig);\n return;\n }\n fig.cell_info[0].output_area.element.on(\n 'cleared',\n { fig: fig },\n fig._remove_fig_handler\n );\n};\n\nmpl.figure.prototype.handle_close = function (fig, msg) {\n var width = fig.canvas.width / fig.ratio;\n fig.cell_info[0].output_area.element.off(\n 'cleared',\n fig._remove_fig_handler\n );\n fig.resizeObserverInstance.unobserve(fig.canvas_div);\n\n // Update the output cell to use the data from the current canvas.\n fig.push_to_output();\n var dataURL = fig.canvas.toDataURL();\n // Re-enable the keyboard manager in IPython - without this line, in FF,\n // the notebook keyboard shortcuts fail.\n IPython.keyboard_manager.enable();\n fig.parent_element.innerHTML =\n '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n fig.close_ws(fig, msg);\n};\n\nmpl.figure.prototype.close_ws = function (fig, msg) {\n fig.send_message('closing', msg);\n // fig.ws.close()\n};\n\nmpl.figure.prototype.push_to_output = function (_remove_interactive) {\n // Turn the data on the canvas into data in the output cell.\n var width = this.canvas.width / this.ratio;\n var dataURL = this.canvas.toDataURL();\n this.cell_info[1]['text/html'] =\n '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n};\n\nmpl.figure.prototype.updated_canvas_event = function () {\n // Tell IPython that the notebook contents must change.\n IPython.notebook.set_dirty(true);\n this.send_message('ack', {});\n var fig = this;\n // Wait a second, then push the new image to the DOM so\n // that it is saved nicely (might be nice to debounce this).\n setTimeout(function () {\n fig.push_to_output();\n }, 1000);\n};\n\nmpl.figure.prototype._init_toolbar = function () {\n var fig = this;\n\n var toolbar = document.createElement('div');\n toolbar.classList = 'btn-toolbar';\n this.root.appendChild(toolbar);\n\n function on_click_closure(name) {\n return function (_event) {\n return fig.toolbar_button_onclick(name);\n };\n }\n\n function on_mouseover_closure(tooltip) {\n return function (event) {\n if (!event.currentTarget.disabled) {\n return fig.toolbar_button_onmouseover(tooltip);\n }\n };\n }\n\n fig.buttons = {};\n var buttonGroup = document.createElement('div');\n buttonGroup.classList = 'btn-group';\n var button;\n for (var toolbar_ind in mpl.toolbar_items) {\n var name = mpl.toolbar_items[toolbar_ind][0];\n var tooltip = mpl.toolbar_items[toolbar_ind][1];\n var image = mpl.toolbar_items[toolbar_ind][2];\n var method_name = mpl.toolbar_items[toolbar_ind][3];\n\n if (!name) {\n /* Instead of a spacer, we start a new button group. */\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n buttonGroup = document.createElement('div');\n buttonGroup.classList = 'btn-group';\n continue;\n }\n\n button = fig.buttons[name] = document.createElement('button');\n button.classList = 'btn btn-default';\n button.href = '#';\n button.title = name;\n button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n button.addEventListener('click', on_click_closure(method_name));\n button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n buttonGroup.appendChild(button);\n }\n\n if (buttonGroup.hasChildNodes()) {\n toolbar.appendChild(buttonGroup);\n }\n\n // Add the status bar.\n var status_bar = document.createElement('span');\n status_bar.classList = 'mpl-message pull-right';\n toolbar.appendChild(status_bar);\n this.message = status_bar;\n\n // Add the close button to the window.\n var buttongrp = document.createElement('div');\n buttongrp.classList = 'btn-group inline pull-right';\n button = document.createElement('button');\n button.classList = 'btn btn-mini btn-primary';\n button.href = '#';\n button.title = 'Stop Interaction';\n button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n button.addEventListener('click', function (_evt) {\n fig.handle_close(fig, {});\n });\n button.addEventListener(\n 'mouseover',\n on_mouseover_closure('Stop Interaction')\n );\n buttongrp.appendChild(button);\n var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n titlebar.insertBefore(buttongrp, titlebar.firstChild);\n};\n\nmpl.figure.prototype._remove_fig_handler = function (event) {\n var fig = event.data.fig;\n if (event.target !== this) {\n // Ignore bubbled events from children.\n return;\n }\n fig.close_ws(fig, {});\n};\n\nmpl.figure.prototype._root_extra_style = function (el) {\n el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n};\n\nmpl.figure.prototype._canvas_extra_style = function (el) {\n // this is important to make the div 'focusable\n el.setAttribute('tabindex', 0);\n // reach out to IPython and tell the keyboard manager to turn it's self\n // off when our div gets focus\n\n // location in version 3\n if (IPython.notebook.keyboard_manager) {\n IPython.notebook.keyboard_manager.register_events(el);\n } else {\n // location in version 2\n IPython.keyboard_manager.register_events(el);\n }\n};\n\nmpl.figure.prototype._key_event_extra = function (event, _name) {\n // Check for shift+enter\n if (event.shiftKey && event.which === 13) {\n this.canvas_div.blur();\n // select the cell after this one\n var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n IPython.notebook.select(index + 1);\n }\n};\n\nmpl.figure.prototype.handle_save = function (fig, _msg) {\n fig.ondownload(fig, null);\n};\n\nmpl.find_output_cell = function (html_output) {\n // Return the cell and output element which can be found *uniquely* in the notebook.\n // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n // IPython event is triggered only after the cells have been serialised, which for\n // our purposes (turning an active figure into a static one), is too late.\n var cells = IPython.notebook.get_cells();\n var ncells = cells.length;\n for (var i = 0; i < ncells; i++) {\n var cell = cells[i];\n if (cell.cell_type === 'code') {\n for (var j = 0; j < cell.output_area.outputs.length; j++) {\n var data = cell.output_area.outputs[j];\n if (data.data) {\n // IPython >= 3 moved mimebundle to data attribute of output\n data = data.data;\n }\n if (data['text/html'] === html_output) {\n return [cell, data, j];\n }\n }\n }\n }\n};\n\n// Register the function which deals with the matplotlib target/channel.\n// The kernel may be null if the page has been refreshed.\nif (IPython.notebook.kernel !== null) {\n IPython.notebook.kernel.comm_manager.register_target(\n 'matplotlib',\n mpl.mpl_figure_comm\n );\n}\n",
|
|
"text/plain": [
|
|
"<IPython.core.display.Javascript object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
},
|
|
{
|
|
"data": {
|
|
"text/html": [
|
|
"<img src=\"data:image/png;base64,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\" width=\"640\">"
|
|
],
|
|
"text/plain": [
|
|
"<IPython.core.display.HTML object>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"ks = np.argsort(reader.cat0(\"totpartmass\"))[::-1]\n",
|
|
"k = ks[1]\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"plt.scatter(reader.dist(False, \"r200\")[k], reader.mass_ratio()[k], c=reader.overlap(False)[k])\n",
|
|
"plt.colorbar(label=\"Overlap\")\n",
|
|
"\n",
|
|
"plt.title(r\"$\\log M_{{\\rm tot}} / M_\\odot = {:.4f}$\".format(np.log10(reader.cat0(\"totpartmass\")[k])))\n",
|
|
"plt.xlabel(r\"$\\Delta r_i / R_{200c}$\")\n",
|
|
"plt.ylabel(r\"$|\\log \\dfrac{M_i}{M_{\\rm tot}}|$\")\n",
|
|
"plt.tight_layout()\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 32,
|
|
"id": "51dd52f0",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T14:49:25.961273Z",
|
|
"start_time": "2023-03-24T14:27:05.607189Z"
|
|
},
|
|
"scrolled": true
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Starting: 2023-03-24 14:27:05.644524.\n",
|
|
"Loaded `clump0`: 2023-03-24 14:41:48.868024.\n",
|
|
"Loaded `clumpx`: 2023-03-24 14:49:25.871648.\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"print(\"Starting: {}.\".format(datetime.now()))\n",
|
|
"clumps0 = np.load(\"/mnt/extraspace/rstiskalek/csiborg/initmatch/clump_7468_particles.npy\", allow_pickle=True)\n",
|
|
"print(\"Loaded `clump0`: {}.\".format(datetime.now()))\n",
|
|
"clumpsx = np.load(\"/mnt/extraspace/rstiskalek/csiborg/initmatch/clump_7588_particles.npy\", allow_pickle=True)\n",
|
|
"print(\"Loaded `clumpx`: {}.\".format(datetime.now()))\n",
|
|
"\n",
|
|
"overlapper = csiborgtools.match.ParticleOverlap()\n",
|
|
"\n",
|
|
"hid2clumps0 = {hid: n for n, hid in enumerate(clumps0[\"ID\"])}\n",
|
|
"hid2clumpsx = {hid: n for n, hid in enumerate(clumpsx[\"ID\"])}"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 33,
|
|
"id": "bcef2505",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T15:09:47.965132Z",
|
|
"start_time": "2023-03-24T15:08:50.141995Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# Convert positions to cell IDs\n",
|
|
"overlapper.clumps_pos2cell(clumps0)\n",
|
|
"overlapper.clumps_pos2cell(clumpsx)\n",
|
|
"\n",
|
|
"mins0, maxs0 = csiborgtools.match.get_halolims(clumps0, overlapper.inv_clength, overlapper.nshift)\n",
|
|
"minsx, maxsx = csiborgtools.match.get_halolims(clumpsx, overlapper.inv_clength, overlapper.nshift)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 34,
|
|
"id": "e2c24b54",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T15:10:35.352871Z",
|
|
"start_time": "2023-03-24T15:09:47.966986Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"delta_bckg = overlapper.make_bckg_delta(clumps0)\n",
|
|
"delta_bckg = overlapper.make_bckg_delta(clumpsx, delta=delta_bckg)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 369,
|
|
"id": "fb4e8c0a",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T17:04:22.358413Z",
|
|
"start_time": "2023-03-24T17:01:54.600744Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"smooth_kwargs = {\"sigma\": 1, \"truncate\": 4, \"mode\": \"constant\", \"cval\": 0.0}\n",
|
|
"\n",
|
|
"delta_bckg_smooth = gaussian_filter(delta_bckg, **smooth_kwargs)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 363,
|
|
"id": "bb707fb2",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T17:00:16.973318Z",
|
|
"start_time": "2023-03-24T17:00:16.011637Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"Ratio is 0.9820815\n",
|
|
"Original overlap is 0.6785714\n",
|
|
"Smoothed overlap is 0.6664124\n"
|
|
]
|
|
},
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"0.32628544480462635"
|
|
]
|
|
},
|
|
"execution_count": 363,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"# k = 24734 # skull!\n",
|
|
"\n",
|
|
"ks = np.argsort(reader.cat0(\"totpartmass\"))[::-1]\n",
|
|
"# k = ks[1]\n",
|
|
"k = 331\n",
|
|
"n = 0\n",
|
|
"\n",
|
|
"print(\"Ratio is \", summed_ratio[k])\n",
|
|
"\n",
|
|
"print(\"Original overlap is \", overlap_raw[k][n])\n",
|
|
"print(\"Smoothed overlap is \", overlap_smoothed[k][n])\n",
|
|
"\n",
|
|
"index_cl0 = hid2clumps0[reader.cat0(\"index\", k)]\n",
|
|
"cl0 = clumps0[index_cl0][0]\n",
|
|
"mins_cl0, maxs_cl0 = mins0[index_cl0], maxs0[index_cl0]\n",
|
|
"\n",
|
|
"index_clx = hid2clumpsx[reader.catx(\"index\", reader[\"match_indxs\"][k][n])]\n",
|
|
"clx = clumpsx[index_clx][0]\n",
|
|
"mins_clx, maxs_clx = minsx[index_clx], maxsx[index_clx]\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"delta1, delta2, cellmins, nonzero = overlapper.make_deltas(\n",
|
|
" cl0, clx, mins_cl0, maxs_cl0, mins_clx, maxs_clx, smooth_kwargs=smooth_kwargs)\n",
|
|
"\n",
|
|
"csiborgtools.match.calculate_overlap(delta1, delta2, cellmins, delta_bckg_smooth)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 364,
|
|
"id": "5eeed44f",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-03-24T17:00:19.825171Z",
|
|
"start_time": "2023-03-24T17:00:19.787750Z"
|
|
}
|
|
},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"NGP/smoothed overlap 0.6785714 0.6664124\n",
|
|
"0.32628544480462635\n",
|
|
"Sum is 0.32628544480462635\n",
|
|
"Originally NGP/smoothed was 0.6785714 0.6664124\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"xs = []\n",
|
|
"for n in range(reader[\"match_indxs\"][k].size):\n",
|
|
"\n",
|
|
" index_clx = hid2clumpsx[reader.catx(\"index\", reader[\"match_indxs\"][k][n])]\n",
|
|
" clx = clumpsx[index_clx][0]\n",
|
|
" mins_clx, maxs_clx = minsx[index_clx], maxsx[index_clx]\n",
|
|
" \n",
|
|
" print(\"NGP/smoothed overlap \", overlap_raw[k][n], overlap_smoothed[k][n])\n",
|
|
" delta1, delta2, cellmins, nonzero1 = overlapper.make_deltas(\n",
|
|
" cl0, clx, mins_cl0, maxs_cl0, mins_clx, maxs_clx, smooth_kwargs=smooth_kwargs)\n",
|
|
" \n",
|
|
" x = csiborgtools.match.calculate_overlap(delta1, delta2, cellmins, delta_bckg_smooth)\n",
|
|
" print(x)\n",
|
|
" xs.append(x)\n",
|
|
" \n",
|
|
"print(\"Sum is \", sum(xs))\n",
|
|
"print(\"Originally NGP/smoothed was \", summed_raw[k], summed_smoothed[k])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1db1bc57",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5883ecc7",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-31T17:51:03.510067Z",
|
|
"start_time": "2023-01-31T17:51:03.469080Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a58b300c",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "56b90375",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T18:54:51.064154Z",
|
|
"start_time": "2023-01-28T18:54:47.314086Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"dlogm = [None] * len(indxs)\n",
|
|
"mass = [None] * len(indxs)\n",
|
|
"for k in trange(len(indxs)):\n",
|
|
" dlogm[k] = np.abs(np.log10(cat[0][\"totpartmass\"][k]) - np.log10(cat[1][\"totpartmass\"][indxs[k]]))\n",
|
|
" mass[k] = np.ones(indxs[k].size) * cat[0][\"totpartmass\"][k]\n",
|
|
"dlogm = np.asanyarray(dlogm)\n",
|
|
"mass = np.asanyarray(mass)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e44414b7",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T18:56:19.841434Z",
|
|
"start_time": "2023-01-28T18:56:19.041227Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.scatter(np.concatenate(dlogm), np.concatenate(overlap), s=1, rasterized=True)\n",
|
|
"t = np.linspace(0, 2)\n",
|
|
"plt.plot(t, 10**(-t), c=\"red\", label=r\"$10^{-|\\log M_1 / M_2|}$\")\n",
|
|
"plt.xlabel(r\"$|\\log M_1 / M_2|$\")\n",
|
|
"plt.ylabel(r\"$\\mathcal{O}$\")\n",
|
|
"plt.legend()\n",
|
|
"plt.tight_layout()\n",
|
|
"# plt.savefig(\"../plots/mass_comparison.png\", dpi=450)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "03cec1b7",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "1cde4797",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:19:36.573717Z",
|
|
"start_time": "2023-01-28T15:19:34.985074Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"for k in trange(len(indxs)):\n",
|
|
" if np.any((dlogm[k] > 1.75) & (overlap[k] > 0.15)):\n",
|
|
" print(k)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "58b2cb87",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:27:57.709539Z",
|
|
"start_time": "2023-01-28T15:27:57.131915Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"k = 97788\n",
|
|
"print(dlogm[k])\n",
|
|
"print(overlap[k])\n",
|
|
"n = np.argmax(overlap[k])\n",
|
|
"\n",
|
|
"index_cl0 = [cl[1] for cl in clumps0].index(cat[0][k][\"index\"])\n",
|
|
"cl0 = clumps0[index_cl0][0]\n",
|
|
"mins_cl0, maxs_cl0 = mins0[index_cl0], maxs0[index_cl0]\n",
|
|
"\n",
|
|
"index_clx = [cl[1] for cl in clumpsx].index(cat[1][\"index\"][indxs[k]][n])\n",
|
|
"clx = clumpsx[index_clx][0]\n",
|
|
"mins_clx, maxs_clx = minsx[index_clx], maxsx[index_clx]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "f5193d37",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:28:02.049121Z",
|
|
"start_time": "2023-01-28T15:28:02.016020Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"delta1, delta2, cellmins = overlapper.make_deltas(cl0, clx, mins_cl0, maxs_cl0, mins_clx, maxs_clx)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6e0176db",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:28:03.044781Z",
|
|
"start_time": "2023-01-28T15:28:03.010050Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"overlapper.overlap(delta1, delta2, cellmins, delta)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a3993216",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:28:03.662552Z",
|
|
"start_time": "2023-01-28T15:28:03.630680Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"delta1.sum() / delta2.sum()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "120b0b61",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "5170b359",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-28T15:28:05.961500Z",
|
|
"start_time": "2023-01-28T15:28:05.857277Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.imshow(np.sum(delta1, axis=2))\n",
|
|
"plt.show()\n",
|
|
"\n",
|
|
"plt.figure()\n",
|
|
"plt.imshow(np.sum(delta2, axis=2))\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "adcca1e1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d74da689",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0989f96e",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.667Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"ncounter = len(indxs[k])\n",
|
|
"true_overlap = np.full(ncounter, np.nan)\n",
|
|
"spherical_overlap = np.full(ncounter, np.nan)\n",
|
|
"\n",
|
|
"for n in trange(len(indxs[k])):\n",
|
|
" clx = clumpsx[[cl[1] for cl in clumpsx].index(cat[1][\"index\"][indxs[k]][n])][0]\n",
|
|
" \n",
|
|
" R1 = (3 * cl0.size / (4 * np.pi))**(1./3) * 1 / 2048\n",
|
|
" R2 = (3 * clx.size / (4 * np.pi))**(1./3) * 1 / 2048\n",
|
|
" d = np.linalg.norm([np.mean(cl0[p]) - np.mean(clx[p]) for p in ('x', 'y', 'z')])\n",
|
|
" \n",
|
|
" spherical_overlap[n] = csiborgtools.match.spherical_overlap(R1, R2, d)\n",
|
|
" true_overlap[n] = overlapper(cl0, clx, delta)\n",
|
|
" \n",
|
|
"# print(true_overlap, spherical_overlap)\n",
|
|
" "
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "6007e537",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.668Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"plt.scatter(true_overlap, spherical_overlap)\n",
|
|
"\n",
|
|
"t = np.linspace(0, 1, 100)\n",
|
|
"plt.plot(t, t, c=\"k\", ls=\"--\")\n",
|
|
"\n",
|
|
"plt.xlabel(\"True overlap\")\n",
|
|
"plt.ylabel(\"Spherical overlap\")\n",
|
|
"# plt.xscale(\"log\")\n",
|
|
"# plt.yscale(\"log\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "fd1a9591",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "2a4062f2",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.670Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"R1 = (3 * cl0.size / (4 * np.pi))**(1./3) * 1 / 2048\n",
|
|
"R2 = (3 * clx.size / (4 * np.pi))**(1./3) * 1 / 2048\n",
|
|
"d = np.linalg.norm([np.mean(cl0[p]) - np.mean(clx[p]) for p in ('x', 'y', 'z')])"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "d2b0dcd5",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-23T20:52:54.565480Z",
|
|
"start_time": "2023-01-23T20:52:54.534775Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "64634315",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "9cfcc924",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"end_time": "2023-01-23T19:00:54.795153Z",
|
|
"start_time": "2023-01-23T19:00:54.447475Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a747a632",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.686Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"box = cat[0].box\n",
|
|
"maverage = box.box2solarmass(clumps0[2][0][\"M\"][0])\n",
|
|
"cell = box.box2mpc(1/2048)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "27bb5c36",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.686Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"n_sim = 0\n",
|
|
"import numpy\n",
|
|
"\n",
|
|
"R = (3 * cat.cats[n_sim][\"npart\"] / (4 * numpy.pi))**(1./3) * 1 / 2048\n",
|
|
"R = cat.cats[n_sim].box.box2mpc(R)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "03a7825f",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.687Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"# dlogm = [None] * len(indxs)\n",
|
|
"# for k in trange(len(indxs)):\n",
|
|
"# dlogm[k] = np.abs(np.log10(cat[0][\"totpartmass\"][k]) - np.log10(cat[1][\"totpartmass\"][indxs[k]]))\n",
|
|
"# dlogm = np.asanyarray(dlogm)\n",
|
|
"\n",
|
|
"normdist = [None] * len(indxs)\n",
|
|
"masses = [None] * len(indxs)\n",
|
|
"for k in trange(len(indxs)):\n",
|
|
" normdist[k] = dist0[k] / ((3 * cat[0][\"totpartmass\"][k] / (4 * np.pi * maverage))**(1/3) * cell)\n",
|
|
" masses[k] = np.log10(np.ones(indxs[k].size) * cat[0][\"totpartmass\"][k])\n",
|
|
" \n",
|
|
"normdist = np.asanyarray(normdist)\n",
|
|
"masses = np.asanyarray(masses)"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "e0330ca5",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.688Z"
|
|
},
|
|
"scrolled": false
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"plt.figure()\n",
|
|
"\n",
|
|
"# plt.scatter(np.concatenate(normdist), np.concatenate(overlap), c=np.concatenate(masses), s=4)\n",
|
|
"\n",
|
|
"plt.scatter(np.concatenate(normdist), np.concatenate(masses), c=np.concatenate(overlap), s=4)\n",
|
|
"\n",
|
|
"\n",
|
|
"plt.colorbar()\n",
|
|
"# plt.xlabel(r\"$z = 0$ normalised separation by $\\hat{R}$\")\n",
|
|
"# plt.xlabel(r\"Absolute difference in total mass [dex]\")\n",
|
|
"# plt.xscale(\"log\")\n",
|
|
"# plt.ylabel(r\"$\\mathcal{O}$\")\n",
|
|
"plt.xscale(\"log\")\n",
|
|
"plt.tight_layout()\n",
|
|
"# plt.savefig(\"../plots/another_view.png\", dpi=450)\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "de23a8a1",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "a6b5e4f8",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "43bc17db",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "b4df25af",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "0d25a16d",
|
|
"metadata": {
|
|
"ExecuteTime": {
|
|
"start_time": "2023-01-26T09:49:07.690Z"
|
|
}
|
|
},
|
|
"outputs": [],
|
|
"source": [
|
|
"cl0 = clumps0[[cl[1] for cl in clumps0].index(cat[0][k][\"index\"])][0]\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"\n",
|
|
"clx = clumpsx[[cl[1] for cl in clumpsx].index(cat[1][\"index\"][indxs[k]][n])][0]"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"id": "be26cbcc",
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
|
"display_name": "Python 3",
|
|
"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": "3.6.8"
|
|
}
|
|
},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 5
|
|
}
|