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56 | 56 | "source": [ |
57 | 57 | "## 1. Introduction\n", |
58 | 58 | "\n", |
59 | | - "This tutorial demonstrates how to make a efficient queries for the common question of \"does LSST have light curves at these sky coordinates?\" \n", |
| 59 | + "This tutorial demonstrates how to make efficient queries for the common question of \"does LSST have light curves at these sky coordinates?\" \n", |
60 | 60 | "\n", |
61 | 61 | "**Avoid: querying the forced photometry tables by coordinate.**\n", |
62 | 62 | "\n", |
63 | 63 | "It is recommended that the fluxes in the forced photometry table, `ForcedSourceOnDiaObject`, be used to generate light curves.\n", |
64 | 64 | "However, queries *by coordinate* on the `ForcedSourceOnDiaObject` table are very inefficient and should be avoided.\n", |
65 | 65 | "This is because the `ForcedSourceOnDiaObject` table contains forced flux measurements made on every difference and direct image, at the location of every `DiaObject`.\n", |
66 | | - "It is much more efficient to do the spatial cross-match with `DiaObject` once and then retrieve forced fluxes for successful matches, rather than spatially cross-matching to the tens or hundreds (and in the future, thousands) of visits.\n", |
| 66 | + "It is much more efficient to do the spatial cross-match with `DiaObject` once and then retrieve forced fluxes for successful matches based on their IDs, rather than spatially cross-matching to the tens or hundreds (and in the future, thousands) of visits.\n", |
67 | 67 | "The same advice applies to the `ForcedSource` and `Object` tables.\n", |
68 | 68 | "\n", |
69 | 69 | "**Avoid: putting asynchronous queries into `for` loops.**\n", |
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74 | 74 | "**Correct: upload a table of coordinates and cross-match using a TAP table join.**\n", |
75 | 75 | "\n", |
76 | 76 | "This notebook demonstrates how to upload a table of coordinates and use the TAP service to cross-match\n", |
77 | | - "to the `DiaObject` table and then retrieve light curves for successfull cross-matches.\n", |
| 77 | + "to the `DiaObject` table and then retrieve light curves for successful cross-matches.\n", |
78 | 78 | "\n", |
79 | 79 | "**Related tutorials**: The 200-level tutorials on the `DiaObject` and `ForcedSourceOnDiaObject` catalogs. The 100-level tutorials on catalog access with TAP and ADQL query statements." |
80 | 80 | ] |
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218 | 218 | "metadata": {}, |
219 | 219 | "outputs": [], |
220 | 220 | "source": [ |
221 | | - "user_table" |
| 221 | + "# user_table" |
222 | 222 | ] |
223 | 223 | }, |
224 | 224 | { |
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253 | 253 | "plt.plot(user_table['ra'][tx3], user_table['dec'][tx3], '^', ms=6, mew=0, alpha=0.7,\n", |
254 | 254 | " color='darkorange', label='random')\n", |
255 | 255 | "plt.legend(loc='best', handletextpad=0)\n", |
| 256 | + "plt.gca().invert_xaxis()\n", |
256 | 257 | "plt.xlabel('RA')\n", |
257 | 258 | "plt.ylabel('Dec')\n", |
258 | 259 | "plt.show()" |
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