diff --git a/benchmark/test.ipynb b/benchmark/test.ipynb deleted file mode 100644 index ef880f9..0000000 --- a/benchmark/test.ipynb +++ /dev/null @@ -1,1672 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "%load_ext autoreload\n", - "%autoreload 2" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "%pip install --quiet git+https://github.com/Schwarzam/lsdb@server-test" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Note: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "%pip install --quiet splusdata --upgrade" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "import splusdata\n", - "import lsdb\n", - "\n", - "# Explore the HiPSCat catalogs and plot sky maps\n", - "from hipscat.catalog import Catalog\n", - "from hipscat.inspection import plot_pixels" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Checking for all S-PLUS available hipscats" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'dr4_vacs': {'qso_z': {'hipscats': ['qso_z'], 'margins': ['qso_z_2arcsec']},\n", - " 'photozs': {'hipscats': ['photozs'], 'margins': ['photozs_2arcsec']},\n", - " 'calib_flag': {'hipscats': ['calib_flag'],\n", - " 'margins': ['calib_flag_2arcsec']},\n", - " 'sqg': {'hipscats': ['sqg'], 'margins': ['sqg_2arcsec']}},\n", - " 'sdr1': {'hipscats': ['shorts'], 'margins': ['shorts_2arcsec']},\n", - " 'dr4': {'hipscats': ['single', 'dual', 'psf'],\n", - " 'margins': ['psf_2arcsec', 'single_2arcsec', 'dual_2arcsec']}}" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "splusdata.get_hipscats()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Exploring splus dual's hipscat" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Searching for a SPLUS HiPSCat catalogs...\n", - "['https://splus.cloud/HIPS/catalogs/dr4/dual', 'https://splus.cloud/HIPS/catalogs/dr4/dual_2arcsec']\n" - ] - } - ], - "source": [ - "print(\"Searching for a SPLUS HiPSCat catalogs...\")\n", - "res = splusdata.get_hipscats(\"dr4/dual\")[0]\n", - "print(res)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "# Read the HiPSCat catalog metadata, it does not load any data, just healpix pixels and other metadata\n", - "dual_splus_hipscat_catalog = Catalog.read_from_hipscat(splusdata.get_hipscats(\"dr4/dual\")[0][0])\n", - "plot_pixels(dual_splus_hipscat_catalog)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Creating cluster client (optional)\n", - "\n", - "This dask client is optional, but it can be useful to monitor the progress of the computation." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Client

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Client-be2ee0b2-1ace-11ef-b80e-56385136253b

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Connection method: Cluster objectCluster type: distributed.LocalCluster
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Cluster Info

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LocalCluster

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eb262829

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Status: runningUsing processes: True
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Scheduler Info

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Scheduler

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Scheduler-36e619d9-6d89-4ad3-9da4-cbb069878f97

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Worker: 0

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Worker: 1

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Worker: 2

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Worker: 3

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Worker: 4

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Worker: 5

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Worker: 6

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Worker: 7

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Worker: 8

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Worker: 9

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" - ], - "text/plain": [ - "" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from dask.distributed import Client\n", - "\n", - "client = Client(n_workers=10, memory_limit=\"8GB\")\n", - "client" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Exploring the data \n", - "\n", - "Lets print the columns of the data and the first few rows." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Now here is where lsdb shines\n", - "\n", - "Lets do a cone search around the coordinates of the galaxy and plot the results." - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "dual_splus_margin = lsdb.read_hipscat(splusdata.get_hipscats(\"dr4/dual\")[0][1])\n", - "dual_splus_hips = lsdb.read_hipscat(\n", - " splusdata.get_hipscats(\"dr4/dual\")[0][0],\n", - " margin_cache=dual_splus_margin,\n", - " columns = [\"ID\", \"RA\", \"DEC\", # Try messing with the columns\n", - " \"r_auto\", \"e_r_auto\",\n", - " \"g_auto\", \"e_g_auto\",\n", - " \"i_auto\", \"e_i_auto\",\n", - " \"z_auto\", \"e_z_auto\",\n", - " \"u_auto\", \"e_u_auto\",\n", - " \"J0378_auto\", \"e_J0378_auto\",\n", - " \"J0395_auto\", \"e_J0395_auto\",\n", - " \"J0410_auto\", \"e_J0410_auto\",\n", - " \"J0430_auto\", \"e_J0430_auto\",\n", - " \"J0515_auto\", \"e_J0515_auto\",\n", - " \"J0660_auto\", \"e_J0660_auto\",\n", - " \"J0861_auto\", \"e_J0861_auto\",\n", - " ],\n", - " filters=[\"r_auto < 14\"], # Try messing with this query\n", - " dtype_backend=\"numpy_nullable\"\n", - ")\n", - "\n", - "res = dual_splus_hips.cone_search(\n", - " 0.1,\n", - " 0.1,\n", - " 5 * 3600\n", - ")\n", - "\n", - "dual_cat = res.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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1DR4_3_STRIPE82-0003_00026771.372322-1.31865411.9352680.00047512.5991660.00067111.7044610.00051911.610344...13.1978120.0020513.0948570.00183112.3752710.00118911.8812540.00055111.6464810.00075
2DR4_3_STRIPE82-0003_00013941.260432-1.34522913.3081260.00091213.9028270.00124813.1593010.00089613.125454...14.4751910.00398214.3233020.00342913.7066920.00227413.2780030.00106813.1465150.001586
3DR4_3_STRIPE82-0003_00022331.281982-1.32195813.2922920.00090114.0551490.0013413.0276790.00083612.907902...14.8035290.00478214.6045980.00398613.8546960.00244713.2223350.00103612.9409010.00142
4DR4_3_STRIPE82-0003_00048071.396255-1.27076311.6167280.24999811.5681030.00048111.1715030.06915411.222666...11.8934660.00109111.8175970.00099311.4029540.0007511.1671460.00039311.0997350.000577
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312DR4_3_STRIPE82-0004_00314011.3107371.39142912.9187390.00077713.6859650.00116812.6551480.00071312.557542...14.4424990.00403914.2640970.00348713.5956190.00227412.8422230.0009112.6017950.00117
313DR4_3_STRIPE82-0170_0036126358.5715451.21986412.4868650.00061512.5806630.00069712.5054440.00064112.453873...12.701920.00174512.6363240.0016212.3559840.00119512.412010.00068112.2928350.000997
314DR4_3_STRIPE82-0170_0048499358.532181.29360512.354980.00058212.771450.0007712.2007640.00055812.057802...13.4501330.00253513.2994170.00225412.5838180.00134312.1847260.00061611.9466510.000844
315DR4_3_STRIPE82-0170_0043414358.5073651.39952313.7490580.00115114.1285170.00148813.6443850.00114413.648451...14.4603990.00423814.3986290.00392213.9619930.00263313.7558080.00131813.6657360.002002
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4753 rows × 27 columns

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" - ], - "text/plain": [ - " ID RA DEC r_auto e_r_auto \\\n", - "0 DR4_3_STRIPE82-0003_0001068 1.471216 -1.346668 13.901836 0.001225 \n", - "1 DR4_3_STRIPE82-0003_0002677 1.372322 -1.318654 11.935268 0.000475 \n", - "2 DR4_3_STRIPE82-0003_0001394 1.260432 -1.345229 13.308126 0.000912 \n", - "3 DR4_3_STRIPE82-0003_0002233 1.281982 -1.321958 13.292292 0.000901 \n", - "4 DR4_3_STRIPE82-0003_0004807 1.396255 -1.270763 11.616728 0.249998 \n", - ".. ... ... ... ... ... \n", - "312 DR4_3_STRIPE82-0004_0031401 1.310737 1.391429 12.918739 0.000777 \n", - "313 DR4_3_STRIPE82-0170_0036126 358.571545 1.219864 12.486865 0.000615 \n", - "314 DR4_3_STRIPE82-0170_0048499 358.53218 1.293605 12.35498 0.000582 \n", - "315 DR4_3_STRIPE82-0170_0043414 358.507365 1.399523 13.749058 0.001151 \n", - "316 DR4_3_STRIPE82-0170_0033850 358.477722 1.39453 11.481477 0.000478 \n", - "\n", - " g_auto e_g_auto i_auto e_i_auto z_auto ... J0410_auto \\\n", - "0 14.799687 0.001956 13.565275 0.001098 13.415218 ... 15.692736 \n", - "1 12.599166 0.000671 11.704461 0.000519 11.610344 ... 13.197812 \n", - "2 13.902827 0.001248 13.159301 0.000896 13.125454 ... 14.475191 \n", - "3 14.055149 0.00134 13.027679 0.000836 12.907902 ... 14.803529 \n", - "4 11.568103 0.000481 11.171503 0.069154 11.222666 ... 11.893466 \n", - ".. ... ... ... ... ... ... ... \n", - "312 13.685965 0.001168 12.655148 0.000713 12.557542 ... 14.442499 \n", - "313 12.580663 0.000697 12.505444 0.000641 12.453873 ... 12.70192 \n", - "314 12.77145 0.00077 12.200764 0.000558 12.057802 ... 13.450133 \n", - "315 14.128517 0.001488 13.644385 0.001144 13.648451 ... 14.460399 \n", - "316 11.753448 0.000489 11.409245 0.051869 11.44068 ... 11.826625 \n", - "\n", - " e_J0410_auto J0430_auto e_J0430_auto J0515_auto e_J0515_auto \\\n", - "0 0.008157 15.452905 0.006523 14.683434 0.003818 \n", - "1 0.00205 13.094857 0.001831 12.375271 0.001189 \n", - "2 0.003982 14.323302 0.003429 13.706692 0.002274 \n", - "3 0.004782 14.604598 0.003986 13.854696 0.002447 \n", - "4 0.001091 11.817597 0.000993 11.402954 0.00075 \n", - ".. ... ... ... ... ... \n", - "312 0.004039 14.264097 0.003487 13.595619 0.002274 \n", - "313 0.001745 12.636324 0.00162 12.355984 0.001195 \n", - "314 0.002535 13.299417 0.002254 12.583818 0.001343 \n", - "315 0.004238 14.398629 0.003922 13.961993 0.002633 \n", - "316 0.001206 11.74588 0.00111 11.302073 0.000754 \n", - "\n", - " J0660_auto e_J0660_auto J0861_auto e_J0861_auto \n", - "0 13.82113 0.001404 13.470127 0.001893 \n", - "1 11.881254 0.000551 11.646481 0.00075 \n", - "2 13.278003 0.001068 13.146515 0.001586 \n", - "3 13.222335 0.001036 12.940901 0.00142 \n", - "4 11.167146 0.000393 11.099735 0.000577 \n", - ".. ... ... ... ... \n", - "312 12.842223 0.00091 12.601795 0.00117 \n", - "313 12.41201 0.000681 12.292835 0.000997 \n", - "314 12.184726 0.000616 11.946651 0.000844 \n", - "315 13.755808 0.001318 13.665736 0.002002 \n", - "316 11.578469 0.000667 11.262803 0.000617 \n", - "\n", - "[4753 rows x 27 columns]" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "dual_cat" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Crossmatching two tables" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [], - "source": [ - "sqg_splus_margin = lsdb.read_hipscat(splusdata.get_hipscats(\"dr4/sqg\")[0][1])\n", - "sqg_splus_hips = lsdb.read_hipscat(splusdata.get_hipscats(\"dr4/sqg\")[0][0], margin_cache=sqg_splus_margin)" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [], - "source": [ - "## res is the result of the cone search in the dual catalog\n", - "crossmatch = res.crossmatch(sqg_splus_hips, radius_arcsec=2, suffixes=(\"_dual\", \"_sqg\"))\n", - "table = crossmatch.compute()" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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ID_dualRA_dualDEC_dualr_auto_duale_r_auto_dualg_auto_duale_g_auto_duali_auto_duale_i_auto_dualz_auto_dual...DEC_sqgCLASS_sqgmodel_flag_sqgPROB_QSO_sqgPROB_STAR_sqgPROB_GAL_sqgNorder_sqgDir_sqgNpix_sqg_dist_arcsec
_hipscat_index
0DR4_3_STRIPE82-0003_00010681.471216-1.34666813.9018360.00122514.7996870.00195613.5652750.00109813.415218...-1.3466681.000.010.970.0220670.000282
1DR4_3_STRIPE82-0003_00026771.372322-1.31865411.9352680.00047512.5991660.00067111.7044610.00051911.610344...-1.3186541.000.050.720.2320670.000282
2DR4_3_STRIPE82-0003_00013941.260432-1.34522913.3081260.00091213.9028270.00124813.1593010.00089613.125454...-1.3452291.000.010.960.0320670.000282
3DR4_3_STRIPE82-0003_00022331.281982-1.32195813.2922920.00090114.0551490.0013413.0276790.00083612.907902...-1.3219581.000.070.90.0320670.000282
4DR4_3_STRIPE82-0003_00048071.396255-1.27076311.6167280.24999811.5681030.00048111.1715030.06915411.222666...-1.2707631.000.00.550.4520670.000282
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312DR4_3_STRIPE82-0004_00314011.3107371.39142912.9187390.00077713.6859650.00116812.6551480.00071312.557542...1.3914291.000.040.80.1610190.000282
313DR4_3_STRIPE82-0170_0036126358.5715451.21986412.4868650.00061512.5806630.00069712.5054440.00064112.453873...1.2198642.000.00.460.5410190.0
314DR4_3_STRIPE82-0170_0048499358.532181.29360512.354980.00058212.771450.0007712.2007640.00055812.057802...1.2936052.000.00.360.6410190.0
315DR4_3_STRIPE82-0170_0043414358.5073651.39952313.7490580.00115114.1285170.00148813.6443850.00114413.648451...1.3995231.000.00.920.0810190.0
316DR4_3_STRIPE82-0170_0033850358.4777221.3945311.4814770.00047811.7534480.00048911.4092450.05186911.44068...1.394532.000.00.250.7510190.0
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1972 rows × 39 columns

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" - ], - "text/plain": [ - " ID_dual RA_dual DEC_dual \\\n", - "_hipscat_index \n", - "0 DR4_3_STRIPE82-0003_0001068 1.471216 -1.346668 \n", - "1 DR4_3_STRIPE82-0003_0002677 1.372322 -1.318654 \n", - "2 DR4_3_STRIPE82-0003_0001394 1.260432 -1.345229 \n", - "3 DR4_3_STRIPE82-0003_0002233 1.281982 -1.321958 \n", - "4 DR4_3_STRIPE82-0003_0004807 1.396255 -1.270763 \n", - "... ... ... ... \n", - "312 DR4_3_STRIPE82-0004_0031401 1.310737 1.391429 \n", - "313 DR4_3_STRIPE82-0170_0036126 358.571545 1.219864 \n", - "314 DR4_3_STRIPE82-0170_0048499 358.53218 1.293605 \n", - "315 DR4_3_STRIPE82-0170_0043414 358.507365 1.399523 \n", - "316 DR4_3_STRIPE82-0170_0033850 358.477722 1.39453 \n", - "\n", - " r_auto_dual e_r_auto_dual g_auto_dual e_g_auto_dual \\\n", - "_hipscat_index \n", - "0 13.901836 0.001225 14.799687 0.001956 \n", - "1 11.935268 0.000475 12.599166 0.000671 \n", - "2 13.308126 0.000912 13.902827 0.001248 \n", - "3 13.292292 0.000901 14.055149 0.00134 \n", - "4 11.616728 0.249998 11.568103 0.000481 \n", - "... ... ... ... ... \n", - "312 12.918739 0.000777 13.685965 0.001168 \n", - "313 12.486865 0.000615 12.580663 0.000697 \n", - "314 12.35498 0.000582 12.77145 0.00077 \n", - "315 13.749058 0.001151 14.128517 0.001488 \n", - "316 11.481477 0.000478 11.753448 0.000489 \n", - "\n", - " i_auto_dual e_i_auto_dual z_auto_dual ... DEC_sqg \\\n", - "_hipscat_index ... \n", - "0 13.565275 0.001098 13.415218 ... -1.346668 \n", - "1 11.704461 0.000519 11.610344 ... -1.318654 \n", - "2 13.159301 0.000896 13.125454 ... -1.345229 \n", - "3 13.027679 0.000836 12.907902 ... -1.321958 \n", - "4 11.171503 0.069154 11.222666 ... -1.270763 \n", - "... ... ... ... ... ... \n", - "312 12.655148 0.000713 12.557542 ... 1.391429 \n", - "313 12.505444 0.000641 12.453873 ... 1.219864 \n", - "314 12.200764 0.000558 12.057802 ... 1.293605 \n", - "315 13.644385 0.001144 13.648451 ... 1.399523 \n", - "316 11.409245 0.051869 11.44068 ... 1.39453 \n", - "\n", - " CLASS_sqg model_flag_sqg PROB_QSO_sqg PROB_STAR_sqg \\\n", - "_hipscat_index \n", - "0 1.0 0 0.01 0.97 \n", - "1 1.0 0 0.05 0.72 \n", - "2 1.0 0 0.01 0.96 \n", - "3 1.0 0 0.07 0.9 \n", - "4 1.0 0 0.0 0.55 \n", - "... ... ... ... ... \n", - "312 1.0 0 0.04 0.8 \n", - "313 2.0 0 0.0 0.46 \n", - "314 2.0 0 0.0 0.36 \n", - "315 1.0 0 0.0 0.92 \n", - "316 2.0 0 0.0 0.25 \n", - "\n", - " PROB_GAL_sqg Norder_sqg Dir_sqg Npix_sqg _dist_arcsec \n", - "_hipscat_index \n", - "0 0.02 2 0 67 0.000282 \n", - "1 0.23 2 0 67 0.000282 \n", - "2 0.03 2 0 67 0.000282 \n", - "3 0.03 2 0 67 0.000282 \n", - "4 0.45 2 0 67 0.000282 \n", - "... ... ... ... ... ... \n", - "312 0.16 1 0 19 0.000282 \n", - "313 0.54 1 0 19 0.0 \n", - "314 0.64 1 0 19 0.0 \n", - "315 0.08 1 0 19 0.0 \n", - "316 0.75 1 0 19 0.0 \n", - "\n", - "[1972 rows x 39 columns]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "table" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "base", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.12" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -}