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csiborgtools/notebooks/test_cosma.ipynb

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Add cleaner paths (#43) * ignore venv * ignore pylians if unavaible * Edit loading paths * Edit paths * Stop having default paths * Add nb * Add glamdring paths --------- Co-authored-by: Richard Stiskalek <dc-stis1@login8b.pri.cosma7.alces.network> Co-authored-by: Richard Stiskalek <dc-stis1@login8a.pri.cosma7.alces.network>
2023-04-14 22:24:52 +00:00
{
"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",
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" 15 0.958726141818962E+17 0.963097707172332E+17\n",
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" 17 0.965012398224179E+17 0.966926486638428E+17\n",
" 18 0.966926486638428E+17 0.968840576394854E+17\n",
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" 214 0.837450424410702E+18 0.837641863316898E+18\n",
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" 218 0.838216089975390E+18 0.838407498951033E+18\n",
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" 221 0.838790316633883E+18 0.838981725609525E+18\n",
" 222 0.838981725609525E+18 0.839173134450950E+18\n",
" 223 0.839173134450950E+18 0.839364543292375E+18\n",
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" 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",
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" 243 0.846413599713788E+18 0.864502974527832E+18\n",
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" 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": [
Add mmain and other major updates (#44) * Move paths to a separate file * Add mmain reader * Add a verbosity flag * Fix imports * Fix bug * Rename files * Return ultimate parents * Add script to generate mmain * Remove mmain path * edit path * Add mmain path * Change function name * Rename function * Turn off verbose * Fix list requirement * Edit init match paths * Fix init pathing * Edit paths docs * Edit dumpdir name * Rename path * Fix split paths * Remove unused import * Add comment * Update readme * remove read mmain * Rename haloatalogue * Fix minor bugs * Update nbs * Add create directory option * Move split jobs * Move spliot jobs * Remove splitting * Add import * Edit script * Deeper split folder * Fix paths bug * Rename catalogue * Rename Catalogue * Add new clumpread * Edit paths * add knn paths * Update commenting * Update imports * Add more conversions * Update temp file * Add a note * Add catalogue * Cooment * Update TODO * Update script * add nb * Update * pep8 * edit paths & pep8 * Fix knn auto paths * add paths docs * Add auto and cross knn paths * Add new paths * Simplify tpcf reading * pep8 patch * update readme * Update progress * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * Pep 8 and restructure * add lambda spin * add clump and halo * add checks * Edit halo profile fit * Update gitignore * backup script
2023-04-18 09:02:36 +00:00
"len(paths.get_ics(tonew=True))"
Add cleaner paths (#43) * ignore venv * ignore pylians if unavaible * Edit loading paths * Edit paths * Stop having default paths * Add nb * Add glamdring paths --------- Co-authored-by: Richard Stiskalek <dc-stis1@login8b.pri.cosma7.alces.network> Co-authored-by: Richard Stiskalek <dc-stis1@login8a.pri.cosma7.alces.network>
2023-04-14 22:24:52 +00:00
]
},
{
"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": [
Add mmain and other major updates (#44) * Move paths to a separate file * Add mmain reader * Add a verbosity flag * Fix imports * Fix bug * Rename files * Return ultimate parents * Add script to generate mmain * Remove mmain path * edit path * Add mmain path * Change function name * Rename function * Turn off verbose * Fix list requirement * Edit init match paths * Fix init pathing * Edit paths docs * Edit dumpdir name * Rename path * Fix split paths * Remove unused import * Add comment * Update readme * remove read mmain * Rename haloatalogue * Fix minor bugs * Update nbs * Add create directory option * Move split jobs * Move spliot jobs * Remove splitting * Add import * Edit script * Deeper split folder * Fix paths bug * Rename catalogue * Rename Catalogue * Add new clumpread * Edit paths * add knn paths * Update commenting * Update imports * Add more conversions * Update temp file * Add a note * Add catalogue * Cooment * Update TODO * Update script * add nb * Update * pep8 * edit paths & pep8 * Fix knn auto paths * add paths docs * Add auto and cross knn paths * Add new paths * Simplify tpcf reading * pep8 patch * update readme * Update progress * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * pep8 * Pep 8 and restructure * add lambda spin * add clump and halo * add checks * Edit halo profile fit * Update gitignore * backup script
2023-04-18 09:02:36 +00:00
"cat0 = csiborgtools.read.ClumpsCatalogue(7468)\n",
"catx = csiborgtools.read.ClumpsCatalogue(7588)"
Add cleaner paths (#43) * ignore venv * ignore pylians if unavaible * Edit loading paths * Edit paths * Stop having default paths * Add nb * Add glamdring paths --------- Co-authored-by: Richard Stiskalek <dc-stis1@login8b.pri.cosma7.alces.network> Co-authored-by: Richard Stiskalek <dc-stis1@login8a.pri.cosma7.alces.network>
2023-04-14 22:24:52 +00:00
]
},
{
"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": {
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"<IPython.core.display.Javascript object>"
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],
"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_clumplims(clumps0, overlapper.inv_clength, overlapper.nshift)\n",
"minsx, maxsx = csiborgtools.match.get_clumplims(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
}
Reference in a new issue Copy permalink