From f020f16c51ac7bd9af4483bf8521cebfdf98b86d Mon Sep 17 00:00:00 2001 From: Matt Craig Date: Sun, 3 Dec 2023 11:04:11 -0600 Subject: [PATCH] Remove find_apass_stars and replace uses of it --- .../photometry/get_apass_comp_mags.ipynb | 335 +++--------------- stellarphot/utils/catalog_search.py | 56 --- stellarphot/utils/comparison_utils.py | 11 +- .../utils/tests/test_catalog_search.py | 3 +- 4 files changed, 56 insertions(+), 349 deletions(-) diff --git a/stellarphot/notebooks/photometry/get_apass_comp_mags.ipynb b/stellarphot/notebooks/photometry/get_apass_comp_mags.ipynb index 84aaa4b8..52fa92de 100644 --- a/stellarphot/notebooks/photometry/get_apass_comp_mags.ipynb +++ b/stellarphot/notebooks/photometry/get_apass_comp_mags.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "84f2e230-770d-4e7d-8985-1066d787f2ae", "metadata": {}, "outputs": [], @@ -22,16 +22,16 @@ "from astropy.table import Table\n", "\n", "# We will use this to get the APASS stars in the field of view of an image\n", - "from stellarphot.utils import find_apass_stars\n", + "from stellarphot import apass_dr9\n", "\n", "import requests\n", "import pandas as pd\n", - "import json" + "import json\n" ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "0dc7b9a4-828d-4f81-9368-df02f48a282f", "metadata": {}, "outputs": [], @@ -44,23 +44,15 @@ "\n", "# You chould not need to change these....\n", "fov = 40\n", - "limiting_magnitude = 16" + "limiting_magnitude = 16\n" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "c5b2d933-078d-4d18-8fba-98531f2734a2", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "https://app.aavso.org/vsp/api/chart/?format=json&star=V0533+Her&fov=40&maglimit=16\n" - ] - } - ], + "outputs": [], "source": [ "payload = {'format':'json',\n", " 'star': var_star_name,\n", @@ -72,7 +64,7 @@ "\n", "print(r.url)\n", "\n", - "aavso_response = r.json()" + "aavso_response = r.json()\n" ] }, { @@ -87,41 +79,29 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "9556a746-4e01-4d20-adfb-008548ed0185", "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "# Chop off the format argument at the end\n", "image_uri = aavso_response['image_uri'].split(\"?\")[0]\n", - "Image(image_uri)" + "Image(image_uri)\n" ] }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "7af32e82-d57a-43b7-8a36-4c9cda5f0d09", "metadata": {}, "outputs": [], "source": [ - "var_coord = SkyCoord(ra=aavso_response['ra'], dec=aavso_response['dec'], unit=('hour', 'degree'))" + "var_coord = SkyCoord(ra=aavso_response['ra'], dec=aavso_response['dec'], unit=('hour', 'degree'))\n" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "55b5b042-a11f-4716-8496-64b4cdfd7009", "metadata": {}, "outputs": [], @@ -132,211 +112,55 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "881fec02-448f-46f4-b6d0-4b224c973645", "metadata": {}, "outputs": [], "source": [ "json = json.dumps(aavso_response['photometry'])\n", - "panda = pd.read_json(json, orient = 'records')" + "panda = pd.read_json(json, orient = 'records')\n" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "a39117f7-72a8-4c8b-88f8-51230815fbe6", "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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auidradeclabelbandscomments
0000-BCS-52018:14:34.0241:51:18.5119[{'band': 'V', 'mag': 11.935, 'error': 0.096},...
1000-BCS-52418:14:37.9341:54:53.9123[{'band': 'V', 'mag': 12.256, 'error': 0.066},...
2000-BCS-53118:14:52.9441:53:00.3128[{'band': 'V', 'mag': 12.756, 'error': 0.074},...
3000-BCS-52918:14:48.0741:49:26.0131[{'band': 'V', 'mag': 13.09, 'error': 0.005}, ...
4000-BCS-51218:14:20.2041:49:18.3133[{'band': 'V', 'mag': 13.273, 'error': 0.006},...
5000-BCS-53218:14:54.6141:54:03.3134[{'band': 'V', 'mag': 13.437, 'error': 0.064},...
6000-BCS-51418:14:23.1941:54:06.0135[{'band': 'V', 'mag': 13.491, 'error': 0.0}, {...
7000-BCS-51718:14:30.1041:50:39.5139[{'band': 'V', 'mag': 13.939, 'error': 0.005},...
8000-BCS-51518:14:23.3541:53:14.3151[{'band': 'V', 'mag': 15.078, 'error': 0.005},...
9000-BCS-51018:14:12.8141:51:05.1153[{'band': 'V', 'mag': 15.32, 'error': 0.013000...
\n", - "
" - ], - "text/plain": [ - " auid ra dec label \\\n", - "0 000-BCS-520 18:14:34.02 41:51:18.5 119 \n", - "1 000-BCS-524 18:14:37.93 41:54:53.9 123 \n", - "2 000-BCS-531 18:14:52.94 41:53:00.3 128 \n", - "3 000-BCS-529 18:14:48.07 41:49:26.0 131 \n", - "4 000-BCS-512 18:14:20.20 41:49:18.3 133 \n", - "5 000-BCS-532 18:14:54.61 41:54:03.3 134 \n", - "6 000-BCS-514 18:14:23.19 41:54:06.0 135 \n", - "7 000-BCS-517 18:14:30.10 41:50:39.5 139 \n", - "8 000-BCS-515 18:14:23.35 41:53:14.3 151 \n", - "9 000-BCS-510 18:14:12.81 41:51:05.1 153 \n", - "\n", - " bands comments \n", - "0 [{'band': 'V', 'mag': 11.935, 'error': 0.096},... \n", - "1 [{'band': 'V', 'mag': 12.256, 'error': 0.066},... \n", - "2 [{'band': 'V', 'mag': 12.756, 'error': 0.074},... \n", - "3 [{'band': 'V', 'mag': 13.09, 'error': 0.005}, ... \n", - "4 [{'band': 'V', 'mag': 13.273, 'error': 0.006},... \n", - "5 [{'band': 'V', 'mag': 13.437, 'error': 0.064},... \n", - "6 [{'band': 'V', 'mag': 13.491, 'error': 0.0}, {... \n", - "7 [{'band': 'V', 'mag': 13.939, 'error': 0.005},... \n", - "8 [{'band': 'V', 'mag': 15.078, 'error': 0.005},... \n", - "9 [{'band': 'V', 'mag': 15.32, 'error': 0.013000... " - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "panda" + "panda\n" ] }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "bcd91195-e60f-484b-89a3-4e5ad5a7329b", "metadata": {}, "outputs": [], "source": [ - "aavso_comps = Table.from_pandas(panda)" + "aavso_comps = Table.from_pandas(panda)\n" ] }, { "cell_type": "code", - "execution_count": 10, + "execution_count": null, "id": "82efa3de-1f8e-45f8-8700-059f4b55b012", "metadata": {}, "outputs": [], "source": [ - "aavso_comps['coords'] = SkyCoord(ra=aavso_comps['ra'], dec=aavso_comps['dec'], unit=('hour', 'degree'))" + "aavso_comps['coords'] = SkyCoord(ra=aavso_comps['ra'], dec=aavso_comps['dec'], unit=('hour', 'degree'))\n" ] }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "5902ab0b-ec2b-44a9-bd2c-45b8819ca4d6", "metadata": {}, "outputs": [], "source": [ - "apass, apass_low_error = find_apass_stars(var_coord, max_mag_error=0.1, max_color_error=0.2)\n", + "apass = apass_dr9(var_coord)\n", "\n", - "apass['coords'] = SkyCoord(ra=apass['RAJ2000'], dec=apass['DEJ2000'], unit=('degree', 'degree'))\n", - "\n" + "apass['coords'] = SkyCoord(ra=apass['RAJ2000'], dec=apass['DEJ2000'], unit=('degree', 'degree'))\n" ] }, { @@ -353,49 +177,49 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "544511b1-2060-4835-b254-a8334aea57ac", "metadata": {}, "outputs": [], "source": [ - "index, d2d, _ = aavso_comps['coords'].match_to_catalog_sky(apass['coords'])" + "index, d2d, _ = aavso_comps['coords'].match_to_catalog_sky(apass['coords'])\n" ] }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "03b527a0-da24-4f0a-b067-4b41497a851c", "metadata": {}, "outputs": [], "source": [ "if (d2d.arcsec > 1.5).any():\n", - " raise RuntimeError('Coordinate mismatch')" + " raise RuntimeError('Coordinate mismatch')\n" ] }, { "cell_type": "code", - "execution_count": 14, + "execution_count": null, "id": "e6c5645e-3678-4ccf-b73c-1f48ef42b734", "metadata": {}, "outputs": [], "source": [ - "apass_comp_stars = apass[index]" + "apass_comp_stars = apass[index]\n" ] }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "e0e90de6-9150-4b3e-9909-53bc496bb95b", "metadata": {}, "outputs": [], "source": [ "apass_comp_stars['auid'] = aavso_comps['auid']\n", - "apass_comp_stars['label'] = aavso_comps['label']" + "apass_comp_stars['label'] = aavso_comps['label']\n" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, "id": "f9af1cab-a3d1-41c9-89c2-1142cddf7561", "metadata": {}, "outputs": [], @@ -404,32 +228,32 @@ " Vmag='V', Bmag='B', g_mag='SG', r_mag='SR', i_mag='SI'\n", ")\n", "\n", - "mag_err_cols = {k: f'e_{k}' for k in apass_mag_cols_band_map.keys()}" + "mag_err_cols = {k: f'e_{k}' for k in apass_mag_cols_band_map.keys()}\n" ] }, { "cell_type": "code", - "execution_count": 17, + "execution_count": null, "id": "1f03d7f3-a632-4ea3-ad1e-eaa87594b6d6", "metadata": {}, "outputs": [], "source": [ - "del apass_comp_stars['coords'], apass_comp_stars['B-V'], apass_comp_stars['e_B-V']" + "del apass_comp_stars['coords'], apass_comp_stars['B-V'], apass_comp_stars['e_B-V']\n" ] }, { "cell_type": "code", - "execution_count": 18, + "execution_count": null, "id": "5ff46e2f-3255-4de5-8db8-25adc0284c3f", "metadata": {}, "outputs": [], "source": [ - "constant_cols = set(apass_comp_stars.colnames) - set(apass_mag_cols_band_map.keys()) - set(mag_err_cols.values())" + "constant_cols = set(apass_comp_stars.colnames) - set(apass_mag_cols_band_map.keys()) - set(mag_err_cols.values())\n" ] }, { "cell_type": "code", - "execution_count": 19, + "execution_count": null, "id": "40e0c7b4-21e5-4855-a072-ad27d2e3fa0d", "metadata": {}, "outputs": [], @@ -443,100 +267,39 @@ " for band, band_name in apass_mag_cols_band_map.items():\n", " rearranged['band'].append(band_name)\n", " rearranged['mag'].append(row[band])\n", - " rearranged['mag_err'].append(row[mag_err_cols[band]])" + " rearranged['mag_err'].append(row[mag_err_cols[band]])\n" ] }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "4c2bdfb6-9e18-4bd3-a3bb-22bfd8a2109b", "metadata": {}, "outputs": [], "source": [ - "rearranged = Table(rearranged)" + "rearranged = Table(rearranged)\n" ] }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "3e70455f-fd7d-4d2b-b59a-bd10bb175329", "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "text/html": [ - "
Table length=50\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "\n", - "
auidrecnoe_RAJ2000FieldmobsDEJ2000e_DEJ2000RAJ2000labelnobsbandmagmag_err
str11int32float32int64int16float64float32float64int64int16str2float32float32
000-BCS-520145375790.373201219483641.8551570.246273.6417041194V11.8610.042
000-BCS-520145375790.373201219483641.8551570.246273.6417041194B12.2770.116
000-BCS-520145375790.373201219483641.8551570.246273.6417041194SG12.0390.053
000-BCS-520145375790.373201219483641.8551570.246273.6417041194SR11.7590.052
000-BCS-520145375790.373201219483641.8551570.246273.6417041194SI11.6770.055
000-BCS-524145375850.469201219483641.9149560.493273.6579891234V12.1740.066
000-BCS-524145375850.469201219483641.9149560.493273.6579891234B13.280.114
000-BCS-524145375850.469201219483641.9149560.493273.6579891234SG12.7080.059
000-BCS-524145375850.469201219483641.9149560.493273.6579891234SR11.810.045
.......................................
000-BCS-515145375890.542201219483441.8873310.452273.5973471514V15.090.057
000-BCS-515145375890.542201219483441.8873310.452273.5973471514B15.5050.083
000-BCS-515145375890.542201219483441.8873310.452273.5973471514SG15.2440.05
000-BCS-515145375890.542201219483441.8873310.452273.5973471514SR14.9560.05
000-BCS-515145375890.542201219483441.8873310.452273.5973471514SI14.8850.125
000-BCS-510145375740.541201219483441.8514590.46273.5533221534V15.330.039
000-BCS-510145375740.541201219483441.8514590.46273.5533221534B16.0210.117
000-BCS-510145375740.541201219483441.8514590.46273.5533221534SG15.6160.069
000-BCS-510145375740.541201219483441.8514590.46273.5533221534SR15.0890.041
000-BCS-510145375740.541201219483441.8514590.46273.5533221534SI14.9290.115
" - ], - "text/plain": [ - "\n", - " auid recno e_RAJ2000 Field mobs DEJ2000 e_DEJ2000 RAJ2000 label nobs band mag mag_err\n", - " str11 int32 float32 int64 int16 float64 float32 float64 int64 int16 str2 float32 float32\n", - "----------- -------- --------- -------- ----- --------- --------- ---------- ----- ----- ---- ------- -------\n", - "000-BCS-520 14537579 0.373 20121948 36 41.855157 0.246 273.641704 119 4 V 11.861 0.042\n", - "000-BCS-520 14537579 0.373 20121948 36 41.855157 0.246 273.641704 119 4 B 12.277 0.116\n", - "000-BCS-520 14537579 0.373 20121948 36 41.855157 0.246 273.641704 119 4 SG 12.039 0.053\n", - "000-BCS-520 14537579 0.373 20121948 36 41.855157 0.246 273.641704 119 4 SR 11.759 0.052\n", - "000-BCS-520 14537579 0.373 20121948 36 41.855157 0.246 273.641704 119 4 SI 11.677 0.055\n", - "000-BCS-524 14537585 0.469 20121948 36 41.914956 0.493 273.657989 123 4 V 12.174 0.066\n", - "000-BCS-524 14537585 0.469 20121948 36 41.914956 0.493 273.657989 123 4 B 13.28 0.114\n", - "000-BCS-524 14537585 0.469 20121948 36 41.914956 0.493 273.657989 123 4 SG 12.708 0.059\n", - "000-BCS-524 14537585 0.469 20121948 36 41.914956 0.493 273.657989 123 4 SR 11.81 0.045\n", - " ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "000-BCS-515 14537589 0.542 20121948 34 41.887331 0.452 273.597347 151 4 V 15.09 0.057\n", - "000-BCS-515 14537589 0.542 20121948 34 41.887331 0.452 273.597347 151 4 B 15.505 0.083\n", - "000-BCS-515 14537589 0.542 20121948 34 41.887331 0.452 273.597347 151 4 SG 15.244 0.05\n", - "000-BCS-515 14537589 0.542 20121948 34 41.887331 0.452 273.597347 151 4 SR 14.956 0.05\n", - "000-BCS-515 14537589 0.542 20121948 34 41.887331 0.452 273.597347 151 4 SI 14.885 0.125\n", - "000-BCS-510 14537574 0.541 20121948 34 41.851459 0.46 273.553322 153 4 V 15.33 0.039\n", - "000-BCS-510 14537574 0.541 20121948 34 41.851459 0.46 273.553322 153 4 B 16.021 0.117\n", - "000-BCS-510 14537574 0.541 20121948 34 41.851459 0.46 273.553322 153 4 SG 15.616 0.069\n", - "000-BCS-510 14537574 0.541 20121948 34 41.851459 0.46 273.553322 153 4 SR 15.089 0.041\n", - "000-BCS-510 14537574 0.541 20121948 34 41.851459 0.46 273.553322 153 4 SI 14.929 0.115" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "rearranged" + "rearranged\n" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "ba99d38b-9e1c-481a-9d3a-97ee7e15c720", "metadata": {}, "outputs": [], "source": [ - "rearranged.write(apass_mags_comp_stars, overwrite=True)" + "rearranged.write(apass_mags_comp_stars, overwrite=True)\n" ] }, { diff --git a/stellarphot/utils/catalog_search.py b/stellarphot/utils/catalog_search.py index 22213923..4bc71ed0 100644 --- a/stellarphot/utils/catalog_search.py +++ b/stellarphot/utils/catalog_search.py @@ -10,7 +10,6 @@ __all__ = [ 'in_frame', 'catalog_search', - 'find_apass_stars', 'find_known_variables', ] @@ -122,61 +121,6 @@ def catalog_search(frame_wcs_or_center, shape, desired_catalog, return cat[in_fov] -def find_apass_stars(image_or_center, - radius=1, - max_mag_error=0.05, - max_color_error=0.1): - """ - Get APASS data from Vizer. - - Parameters - ---------- - - image_or_center : `astropy.nddata.CCDData` or `astropy.coordinates.SkyCoord` - Either an image with a WCS (from which the RA/Dec will be extracted) or coordinate of - the center. - - radius : float, optional - Radius, in degrees, around which to search. Not needed if the first argument is an image. - - max_mag_error : float, optional - Maximum error in magnitude to allow. Default is 0.05. - - max_color_error : float, optional - Maximum error in color to allow. Default is 0.1. - - Returns - ------- - - all_apass : `astropy.table.Table` - Table of all APASS stars in the field of view. - - apass_lower_error : `astropy.table.Table` - Table of APASS stars in the field of view with errors lower than the specified values. - """ - if isinstance(image_or_center, SkyCoord): - # Center was passed in, just use it. - cen_wcs = image_or_center - shape = None - else: - cen_wcs = image_or_center.wcs - shape = image_or_center.shape - # use the catalog_search function to find the APASS stars in the frame of the image read above - all_apass = catalog_search(cen_wcs, shape, 'II/336/apass9', - ra_column='RAJ2000', dec_column='DEJ2000', radius=radius, - clip_by_frame=False) - - # Creates a boolean array of the APASS stars that have well defined - # magnitudes and color. - apass_lower_error = (all_apass['e_r_mag'] < max_mag_error) & ( - all_apass['e_B-V'] < max_color_error) - - # create new table of APASS stars that meet error restrictions - apass_lower_error = all_apass[apass_lower_error] - - return all_apass, apass_lower_error - - def find_known_variables(image): """ Get any known variable stars in image field from the VSX catalog. diff --git a/stellarphot/utils/comparison_utils.py b/stellarphot/utils/comparison_utils.py index df66bd06..250119ed 100644 --- a/stellarphot/utils/comparison_utils.py +++ b/stellarphot/utils/comparison_utils.py @@ -7,8 +7,9 @@ from astropy.nddata import CCDData from astropy import units as u -from stellarphot.utils.catalog_search import find_apass_stars, find_known_variables +from stellarphot.utils.catalog_search import find_known_variables from stellarphot.photometry import * +from stellarphot import apass_dr9 __all__ = ['read_file', 'set_up', 'crossmatch_APASS2VSX', 'mag_scale', @@ -113,9 +114,9 @@ def crossmatch_APASS2VSX(CCD, RD, vsx): RD_angle : `astropy.units.Quantity` Angular separation between APASS stars and input targets. """ - apass, apass_in_bright = find_apass_stars(CCD) - ra = apass['RAJ2000'] - dec = apass['DEJ2000'] + apass = apass_dr9(CCD) + ra = apass['ra'] + dec = apass['dec'] apass['coords'] = SkyCoord(ra=ra, dec=dec, unit=(u.hour, u.degree)) apass_coord = apass['coords'] @@ -223,4 +224,4 @@ def in_field(apass_good_coord, ccd, apass, good_stars): apass_good_coord[xy_in] nt = apass[good_stars] ent = nt[xy_in] - return ent \ No newline at end of file + return ent diff --git a/stellarphot/utils/tests/test_catalog_search.py b/stellarphot/utils/tests/test_catalog_search.py index 61059f2b..a8ad763d 100644 --- a/stellarphot/utils/tests/test_catalog_search.py +++ b/stellarphot/utils/tests/test_catalog_search.py @@ -9,8 +9,7 @@ from astropy.nddata import CCDData from ..catalog_search import in_frame, \ - catalog_search, find_known_variables, \ - find_apass_stars + catalog_search, find_known_variables from ...tests.make_wcs import make_wcs CCD_SHAPE = [2048, 3073]