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MelissaGrahamMelissaGraham
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add ddf and filter functionality
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‎Commissioning/102_rubin_schedule_viewer.ipynb‎

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@@ -18,10 +18,10 @@
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"\n",
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"</div>\n",
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"\n",
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"For the Rubin Science Platform at data.lsst.cloud. <br>\n",
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"Container Size: Large <br>\n",
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"LSST Science Pipelines version: v29.2.0 <br>\n",
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"Last verified to run: 2025-12-04 <br>\n",
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"For the Rubin Science Platform at data.lsst.cloud.\\\n",
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"Container Size: Large\\\n",
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"LSST Science Pipelines version: v29.2.0\\\n",
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"Last verified to run: 2025-01-28\\\n",
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"Repository: [github.com/lsst/tutorial-notebooks](https://github.com/lsst/tutorial-notebooks)\\\n",
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"DOI: [10.11578/rubin/dc.20250909.20](https://doi.org/10.11578/rubin/dc.20250909.20)"
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]
@@ -88,28 +88,32 @@
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"The ObsLocTAP data model (table schema) for the scheduled observations is defined in the `ivoa.obsplan` table -- <a href=\"https://www.ivoa.net/documents/ObsLocTAP/20210609/PR-ObsLocTAP-1.0-20210609.pdf\">Observation Locator \n",
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"Table Access Protocol Version 1.0</a>\n",
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"\n",
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"The database contains 28 columns in total, but these are the key columns used in this tutorial.\n",
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"The database contains 28 columns in total, but these are the key columns.\n",
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"\n",
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"* `t_planning` : Time (MJD) when this observation has been added or modified into the planning log.\n",
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"* `target_name` : The name of the astronomical object observed, if any.\n",
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"* `obs_id` : The observation ID from the Camera.\n",
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"* `t_min` : The start time (MJD).\n",
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"* `t_max` : The stop time (MJD).\n",
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"* `s_ra` : The Right Ascension of the visit or planned observation (degrees).\n",
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"* `s_dec` : The Declination of the visit or planned observation (degrees).\n",
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"* `s_fov` : The diameter (bounds) of the covered region.\n",
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"* `s_region` : Sky region covered by the data product (expressed in ICRS frame).\n",
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"* `s_resolution` : The spatial resolution of the data expressed as FWHM.\n",
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"* `t_min` : The start time (MJD).\n",
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"* `t_max` : The stop time (MJD).\n",
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"* `t_exptime` : The total exposure time = `t_max - t_min`.\n",
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"* `t_resolution` : Temporal resolution.\n",
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"* `facility_name` : Name of the facility used for this observation e.g Rubin Simonyi, AuxTel.\n",
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"* `instrument_name` : Name of the instrument used for this observation e.g LSSTCam, LSSTComCam.\n",
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"* `t_plan_exptime` : The planned or scheduled exposure time.\n",
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"* `em_min` : The filter minimum wavelength (m).\n",
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"* `em_max` : The filter maximum wavelength (m).\n",
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"* `target_name` : The name of the astronomical object observed, if any.\n",
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"* `tracking_type` : One of the following values: Sidereal, Solar-system-object-tracking, Fixed-az-el-transit.\n",
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"* `priority` : The Priority level { 0, 1, 2}. 0 = in the target queue as the next visit\n",
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"(meaning its execution is highly likely), 1 = in the 1 hour look-ahead summit queue (meaning likely),\n",
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"2 = 24 hour pre-night simulation, meaning it is not in the summit queue and has a high degree of uncertainty. \n",
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"* `execution_status` : Execution status of the prediction: One of the following values: Planned, Scheduled, Unscheduled, Performed, Aborted.\n",
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"* `tracking_type` : One of the following values: Sidereal, Solar-system-object-tracking, Fixed-az-el-transit.\n",
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"* `obs_id` : The observation ID from the Camera.\n",
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"* `t_planning` : Time (MJD) when this observation has been added or modified into the planning log.\n",
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"\n",
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"These are also columns of interest, but which are the same for most observations taken with LSSTCam.\n",
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"\n",
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"* `t_plan_exptime` : The planned or scheduled exposure time.\n",
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"* `t_exptime` : The total exposure time = `t_max - t_min`.\n",
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"* `s_fov` : The diameter (bounds) of the covered region.\n",
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"* `s_resolution` : The spatial resolution of the data expressed as FWHM.\n",
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"* `facility_name` : Name of the facility used for this observation e.g Rubin Simonyi, AuxTel.\n",
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"* `instrument_name` : Name of the instrument used for this observation e.g LSSTCam, LSSTComCam.\n",
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"\n",
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"See <a href=\"https://dmtn-263.lsst.io/\">DMTN-263</a> for a description of all fields in the schema."
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"warnings.filterwarnings(\"ignore\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cd2a8cab-f364-420d-80ec-3c9f99e47cf7",
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"metadata": {},
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"source": [
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"### 1.4. Define functions\n",
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"\n",
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"Define a function to convert the `em_min` and `em_max` columns into the bandpass (filter) name."
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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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"id": "27684781-bdf6-4fb4-a57b-e8b510253375",
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"metadata": {},
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"outputs": [],
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"source": [
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"def em_min_max_to_band(em_min, em_max):\n",
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" \"\"\"\n",
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" Convert the wavelength minimum and maximum to band name.\n",
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"\n",
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" Parameters\n",
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" ----------\n",
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" em_min: float\n",
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" Wavelength minimum, in m.\n",
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" em_max: float\n",
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" Wavelength maximum, in m.\n",
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"\n",
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" Returns\n",
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" -------\n",
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" band: string\n",
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" Band (filter) name.\n",
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" \"\"\"\n",
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"\n",
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" band = None\n",
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" band_dict = {'u': (2.95e-7, 4.00e-7), 'g': (4.00e-7, 5.55e-7),\n",
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" 'r': (5.50e-7, 6.92e-7), 'i': (6.90e-7, 8.20e-7),\n",
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" 'z': (8.15e-7, 9.25e-7), 'y': (9.20e-7, 11.1e-7)}\n",
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" for b in band_dict.keys():\n",
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" if em_min > band_dict[b][0] and em_max < band_dict[b][1]:\n",
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" band = b\n",
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" if band is None:\n",
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" print(em_min, em_max, ' no band found')\n",
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"\n",
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" return band"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d7cbe189-5a7c-4373-8fcb-076d661b0a6f",
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"id": "9",
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"metadata": {},
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"source": [
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"Programmatically check the health of the static UI by executing the following cell, and assert that the static user interface service must be alive."
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"Programmatically check the health of the static UI by executing the following cell, and assert that the static user interface service must be alive.\n",
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"\n",
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"> **Warning:** If `RemoteDisconnect` errors are returned, it means the service is temporarily unstable or unavailable, and to try again later."
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"rubin_static_schedule_url = obsloctap_url + \"/static/viewer.html\"\n",
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"rubin_static_schedule_url = obsloctap_url + \"/static/viewer.html\"\n",
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"response = requests.get(rubin_static_schedule_url)\n",
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"assert response.status_code == 200, f\"request failed with status {response.status_code}\"\n",
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"print(f\"Rubin Schedule Viewer at {response.url} is alive.\")"
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"id": "26",
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"metadata": {},
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"source": [
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"Note that the values in the \"Execution Status\" field are all \"Scheduled\"."
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"Note that the values in the \"Execution Status\" field are all \"Scheduled\".\n",
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"\n",
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"#### 3.1.1. Planned DDF observations\n",
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"\n",
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"When alerts begin streaming in early 2026, template images will only exist for the DDFs, and thus alerts will only stream in the DDFs.\n",
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"\n",
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"Print the number of planned observations per DDF in the next 24h, and in which filters the observations are planned.\n",
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"\n",
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"First, add a column for the band (filter), converted from the `em_min` and `em_max` columns."
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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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"id": "6769ff38-6b03-4649-9f39-01c475a9e478",
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"metadata": {},
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"outputs": [],
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"source": [
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"em_min = forward_24h_schedule['em_min'].values\n",
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"em_max = forward_24h_schedule['em_max'].values\n",
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"temp = []\n",
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"for i in range(len(forward_24h_schedule)):\n",
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" temp.append(em_min_max_to_band(em_min[i], em_max[i]))\n",
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"forward_24h_schedule['band'] = temp\n",
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"del temp"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4148b3ff-9173-484a-991b-495ee6d25b95",
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"metadata": {},
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"source": [
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"Define the names of the DDF fields, in the format of the `target_name` column.\n",
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"For each field, sum the number of planned observations and print the unique filters for those observations."
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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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"id": "fec6e949-a299-4eae-b4b4-f15da82c9e16",
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"metadata": {},
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"outputs": [],
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"source": [
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"ddf_names = ['ddf_cosmos', 'ddf_ecdfs', 'ddf_elaiss1',\n",
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" 'ddf_edfs_a', 'ddf_edfs_b', 'ddf_xmm_lss']\n",
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"\n",
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"for ddf_name in ddf_names:\n",
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" temp = forward_24h_schedule.query(\"target_name.str.contains(@ddf_name)\")\n",
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" band_list = \"\".join(str(value) for value in np.unique(temp['band']))\n",
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" print('%-12s %3i bands: %-15s' % (ddf_name, len(temp), band_list))\n",
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" del temp, band_list"
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"print(f\"Min gap: {np.min(obs_visit_gap):.2f}\")\n",
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"print(f\"Max gap: {np.max(obs_visit_gap):.2f}\")\n",
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"print(f\"Mean gap: {np.mean(obs_visit_gap):.2f}\")"
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"print(f\"Min gap: {np.min(obs_visit_gap): .2f}\")\n",
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"print(f\"Max gap: {np.max(obs_visit_gap): .2f}\")\n",
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"print(f\"Mean gap: {np.mean(obs_visit_gap): .2f}\")"
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]
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},
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{

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