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04_Intro_to_Butler.ipynb

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"The goals of this notebook are to:<br>\n",
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"1. create an instance of the Butler<br>\n",
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"2. explore the DP0.1 data repository<br>\n",
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"3. retrive and display some image and catalog data<br>\n",
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"4. create in image cutout at a user-specified coordinate<br>\n",
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"3. retrieve and display some image and catalog data<br>\n",
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"4. create an image cutout at a user-specified coordinate<br>\n",
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"5. retrieve and plot catalog data \n",
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"\n",
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"\n",
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"* `refcats` - refers to the reference catalogs used for astrometric and photometric calibration\n",
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"* `skymaps` - are the geometric representations of the sky coverage\n",
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"\n",
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"Collections can be nested, so we can access to everything for DC2 Run 2.2i (the primary DP0.1 data set) by selecting the collection `2.2i/runs/DP0.1`. This is a pointer to other collections that expand out recursively... More on collections can be found here: https://pipelines.lsst.io/v/weekly/modules/lsst.daf.butler/organizing.html#collections"
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"Collections can be nested, so we can access everything for DC2 Run 2.2i (the primary DP0.1 data set) by selecting the collection `2.2i/runs/DP0.1`. This is a pointer to other collections that expand out recursively... More on collections can be found here: https://pipelines.lsst.io/v/weekly/modules/lsst.daf.butler/organizing.html#collections"
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]
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},
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{
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"source": [
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"Again, this list may seem a bit overwhelming, but we can extract some information from the names of the dataset types:\n",
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"\n",
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"- `calexp` - Refers to individual calibrated exposure\n",
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"- `deepCoadd` - Refers to products produced on the coadd images (both images and and source catalogs)\n",
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"- `src` - refers the the catalog of sources\n",
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"- `calexp` - refers to individual calibrated exposure\n",
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"- `deepCoadd` - refers to products produced on the coadd images (both images and and source catalogs)\n",
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"- `src` - refers to the catalog of sources\n",
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"- `skyMap` - refers to geometric representations of the sky coverage\n",
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"\n",
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"<b> Which data sets are most appropriate for DP0.1? </b><br>\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"We access specific data sets through a set of specifications known as a data identifier (`dataId`). Each `DatasetType` can be identified with a different set of properties, so it is important to be able to determine what properties need to be specified to access data of a specific type. It is possible to get all `DatasetRef` (which include the `dataId`) for a specific `datasetType` in a specific collection with a query like this. Note that this doesn't necessarily guarentee that the specific data set exists, so we include a check that the data set has a valid Uniform Resource Identifier (URI)."
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"We access specific data sets through a set of specifications known as a data identifier (`dataId`). Each `DatasetType` can be identified with a different set of properties, so it is important to be able to determine what properties need to be specified to access data of a specific type. It is possible to get all `DatasetRef` (which include the `dataId`) for a specific `datasetType` in a specific collection with a query like this. Note that this doesn't necessarily guarantee that the specific data set exists, so we include a check that the data set has a valid Uniform Resource Identifier (URI)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"The `calexp` is a calibrated CCD from a single exposure. We'll use the afwDisplay interface to show the pixel values and mask plane (more on afwDisplay can be found in other notebooks)."
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"The `calexp` is a calibrated CCD image from a single exposure. We'll use the afwDisplay interface to show the pixel values and mask plane (more on afwDisplay can be found in other notebooks)."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now that we have a calibrated image, we may want to get the catlog of sources that were extracted from it. The `src` catalog associated with this `calexp` we pass the `dataId` to the butler with the `src` datasetType. Note that this performs another query to the registry database to find the `src` catalog that matches our dataId requirements."
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"Now that we have a calibrated image, we may want to get the catalog of sources that were extracted from it. To get the `src` catalog associated with this `calexp` we pass the `dataId` to the butler with the `src` datasetType. Note that this performs another query to the registry database to find the `src` catalog that matches our dataId requirements."
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]
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{
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"metadata": {},
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"source": [
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"<br>\n",
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"The catalogs are very large and it is not feasible to try and retrieve it in its entirety.\n",
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"The catalogs are very large and it is not feasible to try and retrieve them in their entirety.\n",
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"Instead, in this example we identify the tract and patch of interest and retrieve only catalog data for a small region of sky.\n",
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"Use the same ra and dec coordinates as above to find the patch and tract."
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"We use the same ra and dec coordinates as above to find the patch and tract."
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]
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},
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{
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"plt.ylabel('Dec')\n",
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"plt.title('Butler coadd_forced_src objects in tract 4638 patch 43')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {

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