From 7f540d193ccc272eb6bc0cf45c6c7a2508975b52 Mon Sep 17 00:00:00 2001 From: plazas Date: Tue, 9 Sep 2025 17:29:01 +0000 Subject: [PATCH 1/8] Start notebook --- .../102_5_LSDB_data_access.ipynb | 1315 +++++++++++++++++ 1 file changed, 1315 insertions(+) create mode 100644 DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb new file mode 100644 index 00000000..d52c6c32 --- /dev/null +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -0,0 +1,1315 @@ +{ + "cells": [ + { + "attachments": { + "e896e5f2-e65f-41ca-9744-e4fd43d227b5.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "a6075d0b-691a-4c10-aaaa-77ec23d1efb0", + "metadata": {}, + "source": [ + "# 102.5. Rubin data access with LSDB\n", + "\n", + "
\n", + "\n", + "![logo.png](attachment:e896e5f2-e65f-41ca-9744-e4fd43d227b5.png)\n", + "\n", + "
\n", + "\n", + "For the Rubin Science Platform at data.lsst.cloud.
\n", + "Data Release: Data Preview 1
\n", + "Container Size: Large
\n", + "LSST Science Pipelines version: Release r29.2.0
\n", + "Last verified to run: 2025-09-09
\n", + "Repository: github.com/lsst/tutorial-notebooks
" + ] + }, + { + "cell_type": "markdown", + "id": "5dc26261-63f4-4dc4-b702-09110bd7fd3b", + "metadata": {}, + "source": [ + "**Learning objective:** How to access Rubin data in LSDB format.\n", + "\n", + "**LSST data products:** `Object`, `DIAObject`\n", + "\n", + "**Packages:** `lsdb`\n", + "\n", + "**Credit:**\n", + "Originally developed by the Rubin Community Science team.\n", + "Please consider acknowledging them if this notebook is used for the preparation of journal articles, software releases, or other notebooks.\n", + "\n", + "**Get Support:**\n", + "Everyone is encouraged to ask questions or raise issues in the\n", + "Support Category\n", + "of the Rubin Community Forum.\n", + "Rubin staff will respond to all questions posted there." + ] + }, + { + "cell_type": "markdown", + "id": "e0c817af-220b-4f3c-96a6-e9143f1205cc", + "metadata": {}, + "source": [ + "## 1. Introduction\n", + "\n", + "[LSDB](https://docs.lsdb.io/) (Large Scale Database) is an open-source framework built for catalog-scale analysis, including fast cross-matching, bulk user-defined functions, and time-domain work. It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", + "\n", + " is a python tool for scalable analysis of large catalogs (query and cross-match).\n", + "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format to efficiently perform spatial operations.\n", + "Find LSDB tutorials for accessing Rubin data at [lsdb.io/dp1](lsdb.io/dp1).\n", + "Additional information and explanations of different DP1 LSDB data products are available at [data.lsdb.io](data.lsdb.io).\n", + "\n", + "**Related tutorials:** The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. The 100-level tutorials on the TAP (Table Access Protocol) service, the Butler, and displaying images with Firefly.\n", + "\n", + "### 1.1. Import packages\n", + "\n", + "Import the [LSDB package](https://github.com/astronomy-commons/lsdb/) to work with LSDB-formatted files, along with standard astronomy packages and LSST software for data access." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "963c1141-196b-49c1-8db0-019f3a22c6ad", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:22:25.696774Z", + "iopub.status.busy": "2025-09-09T15:22:25.696447Z", + "iopub.status.idle": "2025-09-09T15:22:31.920917Z", + "shell.execute_reply": "2025-09-09T15:22:31.920316Z", + "shell.execute_reply.started": "2025-09-09T15:22:25.696745Z" + } + }, + "outputs": [], + "source": [ + "import lsdb\n", + "from astropy import units as u\n", + "from astropy.coordinates import SkyCoord\n", + "import matplotlib.pyplot as plt\n", + "import warnings\n", + "\n", + "from lsst.rsp import get_tap_service\n", + "import lsst.afw.display as afwDisplay\n", + "from lsst.daf.butler import Butler" + ] + }, + { + "cell_type": "markdown", + "id": "859ab9a5-4c4d-44d3-8c5d-d340d9b85d09", + "metadata": {}, + "source": [ + "### 1.2. Define parameters and functions\n", + "\n", + "Create an instance of the TAP service." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "91980659-d05a-4ae2-801b-0de81d2575f6", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:22:31.921960Z", + "iopub.status.busy": "2025-09-09T15:22:31.921659Z", + "iopub.status.idle": "2025-09-09T15:22:31.955050Z", + "shell.execute_reply": "2025-09-09T15:22:31.954295Z", + "shell.execute_reply.started": "2025-09-09T15:22:31.921921Z" + } + }, + "outputs": [], + "source": [ + "service = get_tap_service(\"tap\")\n", + "assert service is not None" + ] + }, + { + "cell_type": "markdown", + "id": "f39cd931-da3f-4e35-9dd7-b18a1bbf7ffd", + "metadata": {}, + "source": [ + "Suppress the user warning that will otherwise be printed by `dask`:\n", + "\n", + "> `/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.0.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting double[pyarrow] to object dtype.`" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "e398dc6d-e0e8-4fc0-915d-3d1225fb2e5f", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:24:08.683744Z", + "iopub.status.busy": "2025-09-09T15:24:08.683541Z", + "iopub.status.idle": "2025-09-09T15:24:08.703466Z", + "shell.execute_reply": "2025-09-09T15:24:08.702908Z", + "shell.execute_reply.started": "2025-09-09T15:24:08.683727Z" + } + }, + "outputs": [], + "source": [ + "warnings.filterwarnings('ignore', category=UserWarning)" + ] + }, + { + "cell_type": "markdown", + "id": "ae385043-acc1-455e-9f70-5ad0a0b85636", + "metadata": {}, + "source": [ + "Set the backend for `afwDisplay` to be Firefly, and open the Firefly tab." + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "8e93fbe0-3bce-4b90-aa47-dd37ad8ed88a", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:24:08.704256Z", + "iopub.status.busy": "2025-09-09T15:24:08.704054Z", + "iopub.status.idle": "2025-09-09T15:24:08.931284Z", + "shell.execute_reply": "2025-09-09T15:24:08.930305Z", + "shell.execute_reply.started": "2025-09-09T15:24:08.704239Z" + } + }, + "outputs": [], + "source": [ + "afwDisplay.setDefaultBackend(\"firefly\")\n", + "afw_display = afwDisplay.Display(frame=1)" + ] + }, + { + "cell_type": "markdown", + "id": "471c8443-32a8-4166-9dea-dabda823fa9d", + "metadata": {}, + "source": [ + "Create an instance of the Butler." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "9a0d2abd-f48e-4860-aa8b-269d90c8e2a0", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:24:08.933038Z", + "iopub.status.busy": "2025-09-09T15:24:08.931958Z", + "iopub.status.idle": "2025-09-09T15:24:09.271504Z", + "shell.execute_reply": "2025-09-09T15:24:09.270757Z", + "shell.execute_reply.started": "2025-09-09T15:24:08.933010Z" + } + }, + "outputs": [], + "source": [ + "butler = Butler(\"dp1\", collections=\"LSSTComCam/DP1\")\n", + "assert butler is not None" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ae50ca76-7a91-47c2-bb29-65198ba05096", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c2a3535c-592a-4acd-b4b5-c920e62d0aff", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "966562c6-f5d9-4195-b1b2-14ad5f17fb30", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "14c81508-8944-493d-b7f0-b4f5a2622e18", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "13df4656-f715-4ab8-9816-440d677abd2c", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4be65b33-82a4-4f2c-aa68-839c790ea4da", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "bc55909b-767c-4f33-801d-3d0cd6f09796", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "d3ce71f2-018c-49a1-8933-999707d40990", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "016f2de7-84f9-4bee-aa2c-4f5b73159af2", + "metadata": {}, + "source": [ + "Open the read-only LSDB PZ catalog, which has been added by Rubin staff to the `/rubin` directory." + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "e8dd3508-9aff-4157-a911-d555128c9a37", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:22:35.634472Z", + "iopub.status.busy": "2025-09-09T15:22:35.634182Z", + "iopub.status.idle": "2025-09-09T15:22:35.849953Z", + "shell.execute_reply": "2025-09-09T15:22:35.849262Z", + "shell.execute_reply.started": "2025-09-09T15:22:35.634451Z" + } + }, + "outputs": [], + "source": [ + "pz_cat = lsdb.open_catalog(\"/rubin/lsdb_data/object_photoz\")" + ] + }, + { + "cell_type": "markdown", + "id": "6b086a2a-31cd-4139-9a37-116278944f8d", + "metadata": {}, + "source": [ + "Display the results." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "6cfe9c30-21dc-4b22-8ae0-d0552ecdcef3", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:22:37.178114Z", + "iopub.status.busy": "2025-09-09T15:22:37.177752Z", + "iopub.status.idle": "2025-09-09T15:22:37.255279Z", + "shell.execute_reply": "2025-09-09T15:22:37.254579Z", + "shell.execute_reply.started": "2025-09-09T15:22:37.178089Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
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coord_deccoord_rag_cModelMagg_cModelMagErrg_gaap1p0Magg_gaap1p0MagErrg_gaap3p0Magg_gaap3p0MagErrg_kronMagg_kronMagErrg_psfMagg_psfMagErrg_sersicMagg_sersicMagErri_cModelMagi_cModelMagErri_gaap1p0Magi_gaap1p0MagErri_gaap3p0Magi_gaap3p0MagErri_kronMagi_kronMagErri_psfMagi_psfMagErri_sersicMagi_sersicMagErrobjectIdr_cModelMagr_cModelMagErrr_gaap1p0Magr_gaap1p0MagErrr_gaap3p0Magr_gaap3p0MagErrr_kronMagr_kronMagErrr_psfMagr_psfMagErrr_sersicMagr_sersicMagErru_cModelMagu_cModelMagErru_gaap1p0Magu_gaap1p0MagErru_gaap3p0Magu_gaap3p0MagErru_kronMagu_kronMagErru_psfMagu_psfMagErru_sersicMagu_sersicMagErry_cModelMagy_cModelMagErry_gaap1p0Magy_gaap1p0MagErry_gaap3p0Magy_gaap3p0MagErry_kronMagy_kronMagErry_psfMagy_psfMagErry_sersicMagy_sersicMagErrz_cModelMagz_cModelMagErrz_gaap1p0Magz_gaap1p0MagErrz_gaap3p0Magz_gaap3p0MagErrz_kronMagz_kronMagErrz_psfMagz_psfMagErrz_sersicMagz_sersicMagErrlephare_z_medianlephare_z_meanlephare_z_modelephare_z_err95_lowlephare_z_err95_highlephare_z_err68_lowlephare_z_err68_highknn_z_medianknn_z_modeknn_z_err95_lowknn_z_err95_highknn_z_err68_lowknn_z_err68_hightpz_z_mediantpz_z_meantpz_z_modetpz_z_err95_lowtpz_z_err95_hightpz_z_err68_lowtpz_z_err68_highcmnn_z_mediancmnn_z_meancmnn_z_modecmnn_z_err95_lowcmnn_z_err95_highcmnn_z_err68_lowcmnn_z_err68_highgpz_z_mediangpz_z_meangpz_z_modegpz_z_err95_lowgpz_z_err95_highgpz_z_err68_lowgpz_z_err68_highbpz_z_medianbpz_z_meanbpz_z_modebpz_z_err95_lowbpz_z_err95_highbpz_z_err68_lowbpz_z_err68_highdnf_z_mediandnf_z_meandnf_z_modednf_z_err95_lowdnf_z_err95_highdnf_z_err68_lowdnf_z_err68_highfzboost_z_medianfzboost_z_meanfzboost_z_modefzboost_z_err95_lowfzboost_z_err95_highfzboost_z_err68_lowfzboost_z_err68_high
npartitions=4
Order: 3, Pixel: 2double[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]int64[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]
Order: 5, Pixel: 4471......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 2, Pixel: 80......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 0, Pixel: 8......................................................................................................................................................................................................................................................................................................................................................................................................
\n", + "
130 out of 130 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_ra g_cModelMag g_cModelMagErr g_gaap1p0Mag g_gaap1p0MagErr g_gaap3p0Mag g_gaap3p0MagErr g_kronMag g_kronMagErr g_psfMag g_psfMagErr g_sersicMag g_sersicMagErr i_cModelMag i_cModelMagErr i_gaap1p0Mag i_gaap1p0MagErr i_gaap3p0Mag i_gaap3p0MagErr i_kronMag i_kronMagErr i_psfMag i_psfMagErr i_sersicMag i_sersicMagErr objectId r_cModelMag r_cModelMagErr r_gaap1p0Mag r_gaap1p0MagErr r_gaap3p0Mag r_gaap3p0MagErr r_kronMag r_kronMagErr r_psfMag r_psfMagErr r_sersicMag r_sersicMagErr u_cModelMag u_cModelMagErr u_gaap1p0Mag u_gaap1p0MagErr u_gaap3p0Mag u_gaap3p0MagErr u_kronMag u_kronMagErr u_psfMag u_psfMagErr u_sersicMag u_sersicMagErr y_cModelMag y_cModelMagErr y_gaap1p0Mag y_gaap1p0MagErr y_gaap3p0Mag y_gaap3p0MagErr y_kronMag y_kronMagErr y_psfMag y_psfMagErr y_sersicMag y_sersicMagErr z_cModelMag z_cModelMagErr z_gaap1p0Mag z_gaap1p0MagErr z_gaap3p0Mag z_gaap3p0MagErr z_kronMag z_kronMagErr z_psfMag z_psfMagErr z_sersicMag z_sersicMagErr lephare_z_median lephare_z_mean lephare_z_mode lephare_z_err95_low lephare_z_err95_high lephare_z_err68_low lephare_z_err68_high knn_z_median knn_z_mode knn_z_err95_low knn_z_err95_high knn_z_err68_low knn_z_err68_high tpz_z_median tpz_z_mean tpz_z_mode tpz_z_err95_low tpz_z_err95_high tpz_z_err68_low tpz_z_err68_high cmnn_z_median cmnn_z_mean cmnn_z_mode cmnn_z_err95_low cmnn_z_err95_high cmnn_z_err68_low cmnn_z_err68_high gpz_z_median gpz_z_mean gpz_z_mode gpz_z_err95_low gpz_z_err95_high gpz_z_err68_low gpz_z_err68_high bpz_z_median bpz_z_mean bpz_z_mode bpz_z_err95_low bpz_z_err95_high bpz_z_err68_low bpz_z_err68_high dnf_z_median dnf_z_mean dnf_z_mode dnf_z_err95_low dnf_z_err95_high dnf_z_err68_low dnf_z_err68_high fzboost_z_median fzboost_z_mean fzboost_z_mode fzboost_z_err95_low fzboost_z_err95_high fzboost_z_err68_low fzboost_z_err68_high\n", + "npartitions=4 \n", + "9007199254740992 double[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] int64[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow]\n", + "1258474620873342976 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "1441151880758558720 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2305843009213693952 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2594073385365405696 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "pz_cat" + ] + }, + { + "cell_type": "markdown", + "id": "5d9ed2d3-f725-47a8-af44-7bed0eacea21", + "metadata": {}, + "source": [ + "**Lazily loaded catalogs:** note the message under the displayed table above, that all of the columns have been loaded \"lazily\".\n", + "This is always the default for LSDB catalogs, and it means that only the metadata is loaded at first.\n", + "This way, LSDB can plan how tasks will be executed in the future without actually doing any computation." + ] + }, + { + "cell_type": "markdown", + "id": "a4ac250f-7f71-48a4-b1a7-0091a9042e02", + "metadata": {}, + "source": [ + "### 2.1. Column names\n", + "\n", + "The columns of the LSDB PZ catalog include:\n", + "\n", + "* the `objectId`, `coord_ra`, `coord_dec`\n", + "* photometry measurements for each filter `f_` (*ugrizy*):\n", + " * `f_cModelMag` and `f_cModelMagErr`\n", + " * `f_gaap1p0Mag` and `f_gaap1p0MagErr`\n", + " * `f_gaap3p0Mag` and `f_gaap3p0MagErr`\n", + " * `f_kronMag` and `f_kronMagErr`\n", + " * `f_psfMag` and `f_psfMagErr`\n", + "* standardized outputs from the PZ estimators\n", + "\n", + "Option to display all 130 column names." + ] + }, + { + "cell_type": "markdown", + "id": "eae22309-0935-4674-a8af-8b193e5aff50", + "metadata": {}, + "source": [ + "### 2.2. Sky partitions\n", + "\n", + "When `pz_cat` is displayed (above) there are four rows, one for each of the partitions of the LSDB PZ catalog.\n", + "These partitions are how the LSDB-formatted files are stored, with each partition typically having about the same number of objects.\n", + "\n", + "Show the four partitions of `pz_cat` on the sky.\n", + "This is not necessarily the same as a sky coverage map, but rather shows the file's polygonal partition boundaries." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "4817c9f6-1ba8-4258-bfca-cbc6ebd7d689", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-09T15:22:44.139441Z", + "iopub.status.busy": "2025-09-09T15:22:44.139145Z", + "iopub.status.idle": "2025-09-09T15:22:44.506091Z", + "shell.execute_reply": "2025-09-09T15:22:44.505134Z", + "shell.execute_reply.started": "2025-09-09T15:22:44.139417Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = pz_cat.plot_pixels(plot_title=\"Sky Partition Map\")" + ] + }, + { + "cell_type": "markdown", + "id": "5fcf4588-7649-4ec3-bcd0-c473c72eb7be", + "metadata": {}, + "source": [ + "> **Figure 1:** The sky partitions of the lazily-loaded PZ catalog." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "88bf6c2c-88e4-4a34-a20c-cb0a9c81ca41", + "metadata": {}, + "outputs": [], + "source": [ + "pz_cat = lsdb.open_catalog(\"/rubin/lsdb_data/object_photoz\",\n", + " columns=use_columns)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1c1ebc65-e21f-42a7-9859-143979f66c40", + "metadata": {}, + "outputs": [], + "source": [ + "pz_cat" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fd20d489-d98f-423f-8a8d-0c3e3e073786", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "LSST", + "language": "python", + "name": "lsst" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.11" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} From ff6fed95acbd9c3d5c2c1a4476ec19da2ad4292c Mon Sep 17 00:00:00 2001 From: plazas Date: Thu, 11 Sep 2025 16:12:13 +0000 Subject: [PATCH 2/8] Update notebook Update notebooks --- .../102_5_LSDB_data_access.ipynb | 1839 +++++++++++++++-- 1 file changed, 1646 insertions(+), 193 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index d52c6c32..0a9c40b0 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -50,19 +50,28 @@ }, { "cell_type": "markdown", - "id": "e0c817af-220b-4f3c-96a6-e9143f1205cc", + "id": "90c4f595-1939-4a8f-b77e-221acd582cc8", "metadata": {}, "source": [ "## 1. Introduction\n", "\n", - "[LSDB](https://docs.lsdb.io/) (Large Scale Database) is an open-source framework built for catalog-scale analysis, including fast cross-matching, bulk user-defined functions, and time-domain work. It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", + "[LSDB](https://docs.lsdb.io/) (Large Scale Database) is an open-source Python framework that enables fast all-sky cross-matching, bulk application of user-defined functions, \n", + " and simplified analysis of time-domain (light curve) data.\n", + "It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", + "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format ([HEALPix](https://healpix.sourceforge.io/documentation.php)-sharded [Parquet](https://parquet.apache.org/docs/)) to efficiently perform spatial operations.\n", "\n", - " is a python tool for scalable analysis of large catalogs (query and cross-match).\n", - "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format to efficiently perform spatial operations.\n", - "Find LSDB tutorials for accessing Rubin data at [lsdb.io/dp1](lsdb.io/dp1).\n", - "Additional information and explanations of different DP1 LSDB data products are available at [data.lsdb.io](data.lsdb.io).\n", + "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial.\n", "\n", - "**Related tutorials:** The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. The 100-level tutorials on the TAP (Table Access Protocol) service, the Butler, and displaying images with Firefly.\n", + "**Note:** This notebook is intended only as a very simple tutorial. For more detailed examples and advanced use cases, see the full set of LSDB tutorials at [LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html). \n", + "\n", + "**References:**\n", + "\n", + "- Descriptions of LSDB-formatted Data Preview 1 (DP1) data: [https://data.lsdb.io/](https://data.lsdb.io/ )\n", + "- LSDB documentation: [docs.lsdb.io](https://docs.lsdb.io/en/latest/index.html)\n", + "- [Working with Rubin Data using LSDB](https://docs.lsdb.io/en/latest/tutorial_toc/toc_rubin.html)\n", + "- [LSDB hackathon at the Rubin Community Workshop 2025](https://github.com/lincc-frameworks/RCW_Hackathon_2025_LSDB/tree/main)\n", + "\n", + "**Related tutorials:** The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. \n", "\n", "### 1.1. Import packages\n", "\n", @@ -75,141 +84,1340 @@ "id": "963c1141-196b-49c1-8db0-019f3a22c6ad", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:22:25.696774Z", - "iopub.status.busy": "2025-09-09T15:22:25.696447Z", - "iopub.status.idle": "2025-09-09T15:22:31.920917Z", - "shell.execute_reply": "2025-09-09T15:22:31.920316Z", - "shell.execute_reply.started": "2025-09-09T15:22:25.696745Z" + "iopub.execute_input": "2025-09-16T13:31:14.197045Z", + "iopub.status.busy": "2025-09-16T13:31:14.196725Z", + "iopub.status.idle": "2025-09-16T13:31:23.116793Z", + "shell.execute_reply": "2025-09-16T13:31:23.116177Z", + "shell.execute_reply.started": "2025-09-16T13:31:14.197022Z" } }, "outputs": [], "source": [ "import lsdb\n", - "from astropy import units as u\n", - "from astropy.coordinates import SkyCoord\n", - "import matplotlib.pyplot as plt\n", - "import warnings\n", - "\n", - "from lsst.rsp import get_tap_service\n", - "import lsst.afw.display as afwDisplay\n", + "from upath import UPath\n", "from lsst.daf.butler import Butler" ] }, { "cell_type": "markdown", - "id": "859ab9a5-4c4d-44d3-8c5d-d340d9b85d09", + "id": "5305936d-dd18-4ceb-b6bf-c362f7e268d0", + "metadata": {}, + "source": [ + "## 2. Accessing catalogs" + ] + }, + { + "cell_type": "markdown", + "id": "dbe24ce4-ca74-4edb-8a33-a0689cefe8eb", "metadata": {}, "source": [ - "### 1.2. Define parameters and functions\n", + "The `lsdb` read-only catalogs at the `data.lsst.cloud` Rubin Science Platform are located at `/rubin/lsdb_data`, and they consist of `Object`, `DIAObject` and photometric redshift (photo-z) catalogs:\n", + "- `dia_object_collection`\n", + "- `object_collection` \n", + "- `object_collection_lite` \n", + "- `object_photoz`\n", "\n", - "Create an instance of the TAP service." + "The schemas for `dia_object_collection`, `object_collection`, and `object_collection_lite` with column names, units, and descriptions can be checked at the [Data Preview 1 (DP1) schema website](https://sdm-schemas.lsst.io/dp1.html) via the `Object` and `DiaObject` tables." + ] + }, + { + "cell_type": "markdown", + "id": "d7f22845-3128-4d62-8bbf-b0afec98ee75", + "metadata": {}, + "source": [ + "Set the base path." ] }, { "cell_type": "code", "execution_count": 2, - "id": "91980659-d05a-4ae2-801b-0de81d2575f6", + "id": "14c81508-8944-493d-b7f0-b4f5a2622e18", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:22:31.921960Z", - "iopub.status.busy": "2025-09-09T15:22:31.921659Z", - "iopub.status.idle": "2025-09-09T15:22:31.955050Z", - "shell.execute_reply": "2025-09-09T15:22:31.954295Z", - "shell.execute_reply.started": "2025-09-09T15:22:31.921921Z" + "iopub.execute_input": "2025-09-16T13:31:23.117785Z", + "iopub.status.busy": "2025-09-16T13:31:23.117576Z", + "iopub.status.idle": "2025-09-16T13:31:23.123618Z", + "shell.execute_reply": "2025-09-16T13:31:23.123068Z", + "shell.execute_reply.started": "2025-09-16T13:31:23.117767Z" } }, "outputs": [], "source": [ - "service = get_tap_service(\"tap\")\n", - "assert service is not None" + "base_path = UPath(\"/rubin/lsdb_data\")" ] }, { "cell_type": "markdown", - "id": "f39cd931-da3f-4e35-9dd7-b18a1bbf7ffd", + "id": "1d77f3c2-3e21-462e-bb61-23a66ecdfdc0", "metadata": {}, "source": [ - "Suppress the user warning that will otherwise be printed by `dask`:\n", - "\n", - "> `/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.0.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting double[pyarrow] to object dtype.`" + "### 2.1. Object catalog" + ] + }, + { + "cell_type": "markdown", + "id": "05a9db77-bcdc-4c83-8c12-cf3c83dc4c95", + "metadata": {}, + "source": [ + "#### 2.1.1 Load and display the catalog" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "e398dc6d-e0e8-4fc0-915d-3d1225fb2e5f", + "execution_count": 41, + "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:24:08.683744Z", - "iopub.status.busy": "2025-09-09T15:24:08.683541Z", - "iopub.status.idle": "2025-09-09T15:24:08.703466Z", - "shell.execute_reply": "2025-09-09T15:24:08.702908Z", - "shell.execute_reply.started": "2025-09-09T15:24:08.683727Z" + "iopub.execute_input": "2025-09-16T15:48:08.214880Z", + "iopub.status.busy": "2025-09-16T15:48:08.214556Z", + "iopub.status.idle": "2025-09-16T15:48:10.876983Z", + "shell.execute_reply": "2025-09-16T15:48:10.876429Z", + "shell.execute_reply.started": "2025-09-16T15:48:08.214858Z" } }, "outputs": [], "source": [ - "warnings.filterwarnings('ignore', category=UserWarning)" + "object_cat = lsdb.open_catalog(base_path / \"object_collection\")" ] }, { - "cell_type": "markdown", - "id": "ae385043-acc1-455e-9f70-5ad0a0b85636", - "metadata": {}, + "cell_type": "code", + "execution_count": 42, + "id": "c6626b82-07b8-4a06-80dc-96aa78fe1dbe", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:48:10.877930Z", + "iopub.status.busy": "2025-09-16T15:48:10.877727Z", + "iopub.status.idle": "2025-09-16T15:48:10.910916Z", + "shell.execute_reply": "2025-09-16T15:48:10.910430Z", + "shell.execute_reply.started": "2025-09-16T15:48:10.877912Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_lc:
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", + "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=389 \n", + "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat" + ] + }, + { + "cell_type": "markdown", + "id": "e912591d-0798-4a31-8f57-56fb885a721b", + "metadata": {}, + "source": [ + "**Lazily loaded catalogs:** note the message under the displayed table above, that all of the columns have been loaded \"lazily\".\n", + "This is always the default for LSDB catalogs, and it means that only the metadata is loaded at first.\n", + "This way, LSDB can plan how tasks will be executed in the future without actually doing any computation.\n", + "\n", + "`Order` is the HEALPix resolution, and `Pixel` is the HEALPix index of the specific sky patch." + ] + }, + { + "cell_type": "markdown", + "id": "acdce8d8-9727-4ea2-880b-afbfe0fa7d83", + "metadata": {}, + "source": [ + "#### 2.1.2 Columns" + ] + }, + { + "cell_type": "markdown", + "id": "4d29b2c6-7576-4df7-a03d-b2c20e955679", + "metadata": {}, + "source": [ + "Display the 42 loaded columns." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:32:09.381718Z", + "iopub.status.busy": "2025-09-16T13:32:09.381384Z", + "iopub.status.idle": "2025-09-16T13:32:09.386331Z", + "shell.execute_reply": "2025-09-16T13:32:09.385754Z", + "shell.execute_reply.started": "2025-09-16T13:32:09.381692Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", + " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", + " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", + " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", + " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", + " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", + " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", + " 'objectForcedSource'],\n", + " dtype='object')" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat.columns" + ] + }, + { + "cell_type": "markdown", + "id": "d251a7d0-620a-45d6-aa32-4cc3138f70e6", + "metadata": {}, + "source": [ + "Optional: uncomment the cell below to display the names of all the 1304 columns from the `Object` catalog." + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:32:59.117863Z", + "iopub.status.busy": "2025-09-16T13:32:59.117520Z", + "iopub.status.idle": "2025-09-16T13:32:59.120931Z", + "shell.execute_reply": "2025-09-16T13:32:59.120087Z", + "shell.execute_reply.started": "2025-09-16T13:32:59.117839Z" + } + }, + "outputs": [], + "source": [ + "# object_cat.all_columns" + ] + }, + { + "cell_type": "markdown", + "id": "7e026aec-03d7-496d-9fdb-3ac317558732", + "metadata": {}, + "source": [ + "Check which columns are [nested](https://docs.lsdb.io/en/latest/tutorials/pre_executed/nestedframe.html)." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "c27232da-4cfd-423d-a17e-cb4e69499b12", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:32:11.564506Z", + "iopub.status.busy": "2025-09-16T13:32:11.564230Z", + "iopub.status.idle": "2025-09-16T13:32:11.575082Z", + "shell.execute_reply": "2025-09-16T13:32:11.574437Z", + "shell.execute_reply.started": "2025-09-16T13:32:11.564485Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['objectForcedSource']" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat.nested_columns" + ] + }, + { + "cell_type": "markdown", + "id": "63faee7e-3de1-4612-a94b-6248ec63f16d", + "metadata": {}, + "source": [ + "Display the fields in the nested column." + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "3678573c-8f9a-4076-8c3b-f5e2cbb7a2c7", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:32:12.996627Z", + "iopub.status.busy": "2025-09-16T13:32:12.996316Z", + "iopub.status.idle": "2025-09-16T13:32:13.002897Z", + "shell.execute_reply": "2025-09-16T13:32:13.002159Z", + "shell.execute_reply.started": "2025-09-16T13:32:12.996602Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['coord_ra',\n", + " 'coord_dec',\n", + " 'visit',\n", + " 'detector',\n", + " 'band',\n", + " 'psfFlux',\n", + " 'psfFluxErr',\n", + " 'psfFlux_flag',\n", + " 'psfDiffFlux',\n", + " 'psfDiffFluxErr',\n", + " 'psfDiffFlux_flag',\n", + " 'pixelFlags_bad',\n", + " 'pixelFlags_cr',\n", + " 'pixelFlags_crCenter',\n", + " 'pixelFlags_edge',\n", + " 'pixelFlags_interpolated',\n", + " 'pixelFlags_interpolatedCenter',\n", + " 'pixelFlags_nodata',\n", + " 'pixelFlags_saturated',\n", + " 'pixelFlags_saturatedCenter',\n", + " 'pixelFlags_suspect',\n", + " 'pixelFlags_suspectCenter',\n", + " 'invalidPsfFlag',\n", + " 'forcedSourceId',\n", + " 'psfMag',\n", + " 'psfMagErr',\n", + " 'midpointMjdTai']" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat[\"objectForcedSource\"].nest.fields" + ] + }, + { + "cell_type": "markdown", + "id": "420d6fba-a9f1-4cd7-9a07-5c679721edc8", + "metadata": {}, + "source": [ + "Load only selected columns" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "af22e340-5692-4864-8ca6-4d5a665e7178", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:36:33.847193Z", + "iopub.status.busy": "2025-09-16T15:36:33.846903Z", + "iopub.status.idle": "2025-09-16T15:36:33.849892Z", + "shell.execute_reply": "2025-09-16T15:36:33.849363Z", + "shell.execute_reply.started": "2025-09-16T15:36:33.847172Z" + } + }, + "outputs": [], + "source": [ + "use_columns = ['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr',\n", + " 'g_psfFlux', 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr']" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "bf5d271e-3968-4583-b743-47cdab5e5561", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:36:34.520037Z", + "iopub.status.busy": "2025-09-16T15:36:34.519766Z", + "iopub.status.idle": "2025-09-16T15:36:37.100016Z", + "shell.execute_reply": "2025-09-16T15:36:37.099428Z", + "shell.execute_reply.started": "2025-09-16T15:36:34.520016Z" + } + }, + "outputs": [], + "source": [ + "object_cat_selected_columns = lsdb.open_catalog(base_path / \"object_collection\",\n", + " columns=use_columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "6a6eda41-db4f-43d1-b769-c4df1a1c6e84", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:36:48.761964Z", + "iopub.status.busy": "2025-09-16T15:36:48.761676Z", + "iopub.status.idle": "2025-09-16T15:36:48.765650Z", + "shell.execute_reply": "2025-09-16T15:36:48.765172Z", + "shell.execute_reply.started": "2025-09-16T15:36:48.761943Z" + }, + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr'],\n", + " dtype='object')" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat_selected_columns.columns" + ] + }, + { + "cell_type": "markdown", + "id": "5a6394d7-ecc3-4f90-9269-dfad81b2872e", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:54:01.218661Z", + "iopub.status.busy": "2025-09-16T15:54:01.218363Z", + "iopub.status.idle": "2025-09-16T15:54:01.221205Z", + "shell.execute_reply": "2025-09-16T15:54:01.220723Z", + "shell.execute_reply.started": "2025-09-16T15:54:01.218637Z" + } + }, + "source": [ + "#### 2.1.3 Cone searchs" + ] + }, + { + "cell_type": "markdown", + "id": "d5021222-fc50-4f94-8095-c68e3afd39ff", + "metadata": {}, + "source": [ + "Execute a cone search on the object catalog using the coordinates (in degrees) of the Extended Chandra Deep Field South DP1 target field, with a radius of 0.1 deg." + ] + }, + { + "cell_type": "code", + "execution_count": 44, + "id": "bffa951f-f910-4103-837d-e095ef63db41", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:53:00.854171Z", + "iopub.status.busy": "2025-09-16T15:53:00.853859Z", + "iopub.status.idle": "2025-09-16T15:53:00.856999Z", + "shell.execute_reply": "2025-09-16T15:53:00.856434Z", + "shell.execute_reply.started": "2025-09-16T15:53:00.854150Z" + } + }, + "outputs": [], + "source": [ + "ra_ecdfs = 53.16\n", + "dec_ecdfs = -28.10" + ] + }, + { + "cell_type": "code", + "execution_count": 45, + "id": "5a5d8111-6c2e-4c76-a939-447a9cd7b96f", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:53:37.420367Z", + "iopub.status.busy": "2025-09-16T15:53:37.420091Z", + "iopub.status.idle": "2025-09-16T15:53:40.009457Z", + "shell.execute_reply": "2025-09-16T15:53:40.008888Z", + "shell.execute_reply.started": "2025-09-16T15:53:37.420347Z" + } + }, + "outputs": [], + "source": [ + "object_cat_ecdfs = object_cat.cone_search(ra=ra_ecdfs, dec=dec_ecdfs,\n", + " radius_arcsec=0.1 * 3600.0)" + ] + }, + { + "cell_type": "markdown", + "id": "7063bda2-a191-42f6-abe3-697029771006", + "metadata": {}, + "source": [ + "This table contains only 8 partitions, compared to the 389 described in Section 2.1.1, due to the 0.1-degree spatial restriction." + ] + }, + { + "cell_type": "code", + "execution_count": 47, + "id": "d3b6022c-7e0b-4c52-a178-fe0c35f6ada3", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:54:13.805443Z", + "iopub.status.busy": "2025-09-16T15:54:13.805177Z", + "iopub.status.idle": "2025-09-16T15:54:13.835632Z", + "shell.execute_reply": "2025-09-16T15:54:13.835147Z", + "shell.execute_reply.started": "2025-09-16T15:54:13.805422Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=8
Order: 9, Pixel: 2299851double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 9, Pixel: 2299854..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2299876..............................................................................................................................
Order: 9, Pixel: 2299878..............................................................................................................................
\n", + "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=8 \n", + "2528712916652261376 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "2528716215187144704 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2528742603466211328 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2528743702977839104 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: search_points, 5 expressions\n", + "Expr=MapPartitions(search_points)" + ] + }, + "execution_count": 47, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat_ecdfs" + ] + }, + { + "cell_type": "code", + "execution_count": 48, + "id": "21c7d923-dec5-4c75-bfd6-4602864420ec", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T16:59:24.769248Z", + "iopub.status.busy": "2025-09-16T16:59:24.768980Z", + "iopub.status.idle": "2025-09-16T16:59:24.773261Z", + "shell.execute_reply": "2025-09-16T16:59:24.772787Z", + "shell.execute_reply.started": "2025-09-16T16:59:24.769227Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", + " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", + " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", + " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", + " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", + " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", + " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", + " 'objectForcedSource'],\n", + " dtype='object')" + ] + }, + "execution_count": 48, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat_ecdfs.columns" + ] + }, + { + "cell_type": "code", + "execution_count": 50, + "id": "f7dafb69-0a7b-4091-9bfa-3c43460744bf", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T17:01:08.296897Z", + "iopub.status.busy": "2025-09-16T17:01:08.296591Z", + "iopub.status.idle": "2025-09-16T17:01:29.547195Z", + "shell.execute_reply": "2025-09-16T17:01:29.546556Z", + "shell.execute_reply.started": "2025-09-16T17:01:08.296874Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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cqDVu3FgLDw/XAGjp6ekeexUrVjT1j5XlOnjwYG3mzJlagwYNtPDwcK1x48ba+++/X6r/xo0btTZt2mgVK1bUrrrqKi09PV2bO3duqSzXnJwcrXPnzlpMTIwGwDOmWZarpmnaDz/8oN16661axYoVtejoaO3GG2/UFi9e7NNGzw7dtGmTz3Y9K3XVqlWmx+zN559/rt1www1aVFSUVrFiRa1Dhw7amjVrTO2JZLnq7Ny5U+vTp49Wu3ZtLTw8XKtWrZrWpUsX7euvvy7VVj+OZcuWab1799aqVq2qRUdHa127dtX27t3r07ZPnz5avXr1Stn4z3/+o91www2e89WgQQPt4Ycf1jZv3uzT7ptvvtHatWunVaxYUatQoYLWpEkTbdKkSZ79RUVFWv/+/bUrrrhCc7lcnusoeg8SBFEal6YJpL8RBFFmzJgxA8OGDcOOHTvQtGnTQLtDXIbcfffdOHz4sNC6rwRBlA/olStBlBO2bduGAwcOYPz48ejevTtN5ogy59ChQ1i7di1WrVqF3r17B9odgiAkIIWOIMoJ9erVQ35+Pm6++Wa8++67puUlCMKfjB07Fq+++ipuvfVWzJkzx5FMX4Igygaa0BEEQRAEQQQ5VLaEIAiCIAhCgrFjx8Llcvl8Av1WhWLoCIIgCIIgJGnatClWrFjh+Ts0NDSA3tCEjiAIgiAIQpqwsLCAq3Le0ISuHOF2u5Gbm4uYmBhHipoSBEEQRFmiaRpOnz6NWrVqISTE/1Fd586dw/nz5x2xpWlaqX97IyMjPSubGNm7dy9q1aqFyMhI3HDDDXjppZeQmJjoiC8qUFJEOeLIkSOlFtImCIIgiGDj8OHDnuX7/MW5c+dQP6ES8o8VWzcWoFKlSvjrr798tqWnp2Ps2LGl2n777bcoLCzE1Vdfjd9++w0vvPACdu/ejZ07d3LXRfYnNKErRxQUFKBq1aq4CV0RhvBAu0MQjlPcPgkAEJq1XbqPGSw7IuMY7Yq01dvkPXWDz/4rtxWVsiNjnyAuFS7iAlbjG/z555+oUqWKX8c6deoUqlSpggNbElA5xp4aeOq0G/VbHsThw4dRuXJlz3aeQufNmTNn0KBBAzzzzDN4+umnbfmiCr1yLUfoUm8YwhHmogkdUT4p7tASABCaucXnb2/0fUbCvttZ8j8m97fRrs6xG0v+Uag1aW1pgwY7uc+2AQDEb/7fBKvjjUx/PL4wbHn7FKn3/1+bOq9u9dn/241//8MVH1Yypv7jqo+dO7Kdz3F4nzfWuTRuZ51Xgig3/E8iKsuwocoxIbYndB5blSv7TOhEqVixIpo3b469e/c64ocKVLaEIAiCIIigpVhzO/KxQ1FREXbt2oWaNWs6dFTykEJHEIQj/Nbq79cStTJL/mulLJmpVEZ0tY1nS99nVPH07TJqmAx6H/14rfxk7Rf1ReR8EcTlhhsa3LAXPSbbf8SIEbjzzjtRt25dHDt2DC+88AJOnTqFPn362PLDDjShI4jLGNbrU95kgbXP7JWosa3RvsikxOib96RGn0SavcY062vWxrjdZ2Jq9prXpK3nFa+3T4ZJLctHkeMwG8foC03wCKLsOHLkCB544AGcOHECV1xxBW688UasX78eCQkJAfOJJnQEQRAEQQQtbrhh74UppC0sWrTI5ojOQxM6grhEsaO2ycB7BcpqoycveCtgZtusxhN9tStznPEwV/DMxjGOD5T2X0T9NFPevOGpeyz7pNwRlwvFmoZimwU77PYvD1BSBEEQBEEQRJBDCh1BXOLwYs6M8NQcUQWNZ88siUBHVJnjxqAZ7PISEFhKlndbYxkUq5hAnv2D/UuKnyaaHLuVymZsJwLvfFn1IYhgIhBJEeURmtARBEEQBBG0uKGhmCZ0NKEjiGCCV36Dpch4Z20aS4AY4Sk0VhmfZnacVJx445gpfiysxty/MMnz/4kPsGPXWL6xVEldmTNT9Yzqp4yqxhpXRZ2UuZYEQZQvaEJHEARBEETQQq9cS6C1XMsR+rp07dGdlv4ilLGjpIj0VWlj/LvUEl0m9pxQ85zuw2qjHw9QOmNVpkiwlX0zldRKbfX2TTT+kZQ6QpWL2gVk4QsUFBQoLaElg/5v5q+74hFjc+mv06fduPqa38rEb39BWa4EQRAEQRBBDr1yJYhyhEwtMdY+ntJlpYLZ8ZWnUhn78JQmmVUkrPrylCZjXxGMx6ofh4jSyLtOVqqXTGaxEasad2bjy9xvpNgRgcb9v49dG8EOTegIgiAIgghaih3IcrXbvzxAEzqCCAJklDqRumq64iOiqlgpTPp+3jqjVrZ54/Fi6axi80Tq6hnbiiiadmrxGcf39kFGBbNSxpxQX71h1foTsUPxdwThf2hCRxAEQRBE0FKslXzs2gh2aEJHEGWESjycjtl2lVgmq9g2nkrlRHwf7xhY9o2rW/CUJ/34jGqSWR8Re6KKmYziJLKOrRPr8Mpk64rE9+nnVmTFENH4ToJwAoqhK4GyXAmCIAiCIIIcUugIws+IKFu6ohQP+RUJZJQzJzMweeNZKTEysVS81S1YPhiVOe/VMnRliaU0mbVlxfHJHAcv/k4kE5Vlz+gTr51orT8RFdTYRybLWSRekSBEccOFYrhs2wh2aEJHEARBEETQ4tZKPnZtBDs0oSMIG8hkYJq10WFlWoooJkZ1T6YOnch4KqqOqBIo4psRn5UPMsV89FbFjEqZMdvVTEFjxfGJxByy/OfFoIlcd1ZbFfXQTGXTscroNctyFq31Z3dFEoIg/oYmdARBEARBBC3FDrxytdu/PEATOoKwgcqqDCKxbaz9vGxNMx9EbJvZLytVRCVD1kwxkqmvZzxWoz2ztU9ZdeJ4aptMDTvR7GYZRZN3bllteJm/KvGCpK4RZQFN6EqgLFeCIAiCIIgghxQ6ghDAKpZJVyJ8MiQZNdBEqv4blQ1jnJeILzKI1GKTGVdUMTNTnGT8Z61SIaNSisTbsRRSM0XLSm0Tuf5WK2DI9PE+HivV2I6yplIzTyWGkiCMuDUX3JrNLFeb/csDNKEjCIIgCCJooVeuJdCEjiAEsMo65K1nKhPDxrIrs3aoCCzFT2alCI8CxFmNwQqVeCzeOEZVyuij2dgsBZXnr8yasUbMag6yMpWN19/bN9baqiJr61qtECFT889o26wPC6fUZFLzCIImdARBEARBBDHFCEGxzZSAYod8CSQ0oSOI/yFSU+5g/5KvfeID2wHIKTUqWYIiiK436r2N5a9IJi5PAdJhKYpOrP9qhnGFCKMfIoqj0Q/ePpV1TLn3SquSfVY1Bb3/Nq4qoqIEy6wZy8rodXrVB5nVK5yowUcEP5oDMXQaxdARxKWH2ass/R+GRMPrxVLFaSH+j5rdQPr9C5MAAAlzze2aFYs1TnCMbc1eB7L+QeX9Q8tqK1NORKaPFTKlYkTKffAm/1blVkRKz4hg9ZpeZCLEmnTK+KPyqp2HTFFlmrgRxN/QhI4gCIIgiKCFkiJKoAkdcdnDWtidh5VqxeujwytxIhKsritzVsH9MkVvzV4Hso6RlYBgNqbK600RRMvJ8BaOV1GyZFQwVh8VVFRdnh0nXqNb+cMbT6R0j0xSDCl2lyfFWgiKNZsxdJfAWq5UWJggCIIgCCLIIYWOuCyQUYLMFABdTTuXVAjg76QIEVWPpTDwlDOrsiLeqMQ9GX0TwRhbaIwJEyl6LBIfJ6OuiCpnvGLBRlsqypaMr2W1hJZI4gnrb14SCc++EZl7U/T88NRjT9JSZun9pNpdurjhgtumPuVG8Et0NKEjCIIgCCJooRi6EmhCR1zS8GJ19Kd5Y5ao2ZO8neK5Vr6ZwYpBk0FEHWEpXGbKBquArUhWqIw6IqPQsPY5oaSJ7POoliYKoKgaxhuTV7bE6vqqlIixcy1N7xlGZq/KNeSNo6Mr505n3hJEMEATOoIgCIIgghZnkiLolStBlGt4MVqJmaV2+WCWtSmiToj4wNputMNTYZi18P4Xy+ZkbTOzcZ0oZGumtsicY9FMUp+MYgvVyHR5LUYfXm05q/NjN6tXNJPYbEwrFdEMmaLHrHGN6LUUASBhbqhQHzOV0pidbYx5BYAEht+UGRv8lMTQ2Xtlard/eYCyXAmCIAiCIIIcUuiISwI7MVsq4zgZF2W2z6i+iSx7pFLd3ywGjNWWVR/M6I9IX14fFqY15cC3r8PLKBaJZRSJ52LZVVE9RfrKrKhh5aNxu9k4IlnMLN9Y+xMfED8+M1j3Le9+NqreKteLKF+4HVjL9VLIcg0KhS4nJwf9+vVD/fr1ER0djQYNGiA9PR3nz5/3abdp0yZ06NABVatWRWxsLDp37ozt27dzbRcVFWHo0KGIi4tDxYoV0a1bNxw5ckR6bJfLVeoze/Zsx84BQRAEQRCl0WPo7H6CnaBQ6Hbv3g2324233noLDRs2xI4dO/Doo4/izJkzmDp1KgDg9OnTSE1NRffu3TFz5kxcvHgR6enpSE1NxZEjRxAeHm5q+8knn8TixYuxaNEiVK9eHcOHD8cdd9yBLVu2IDQ0VGhsnXnz5qFLly6ev6tUqeK/k0L44MQqA0YbvNplIlmCdhQaOyoPD6N94wLvRuUOKB2jx1I2zMYxIhITaBXjJKNEmtXzMyp9MuqkTHaok8pPWa1EYYbKsZutCWzVR0dFBReJhxTNvFWJhyWI8kBQTOi6dOniM1FKTEzEnj17MGvWLM+kas+ePTh58iTGjx+POnXqAADS09PRokULHDp0CA0aNChlt6CgABkZGXj33XfRsWNHAMB7772HOnXqYMWKFUhNTRUaW6dq1aqoUaOG48dPEARBEIQ5boRQYWEEyYTOjIKCAlSrVs3zd6NGjRAXF4eMjAw899xzKC4uRkZGBpo2bYqEhARTG1u2bMGFCxfQuXNnz7ZatWqhWbNmWLt2LVJTU4XG1hkyZAj69++P+vXro1+/fhgwYABCQtg3WVFREYqK/lYOTp06ZXnchC+iqg4vtk1EsWH1UYl1ElHSZGpwyagGrKxA47F715yzUrLMxmeNo/9tdnyiMYe8a2n0lbc2LSs+TiQjluezE2qrEV69OzvxiXaymkXua6uYQ7u1+Kz6el9LVrwlT6mnuLrgoFhzoVizWVjYZv/yQFC+NN63bx9mzJiBgQMHerbFxMQgKysL7733HqKjo1GpUiUsXboU33zzDcLCzOet+fn5iIiIQGxsrM/2+Ph45OfnC48NABMmTMBHH32EFStWoFevXhg+fDheeukl7nFMnDgRVapU8Xx0ZZEgCIIgCEIGl6YFrpre2LFjMW7cOG6bTZs2oVWrVp6/c3Nz0a5dO7Rr1w5z5/5d4v/s2bNo3749GjdujCFDhqC4uBhTp07F7t27sWnTJkRHR5eyvWDBAvTt29dHJQOATp06oUGDBqWSGlhjmzFt2jSMHz8eBQUFzDZmCl2dOnXQHt0R5jKP+buc8dfKBFbj8WApRIB1rJdM7JlTMVSsY1LJdmWpcDxfZK6hjp34SJl7ReT86XXTjCsS2FG6zHwy+iaDzAoR/lrRQyVrV3ZcEXu8eDt/ZR9f7lzULiALX6CgoACVK1f261inTp1ClSpVMH/btagQE2rdgUPh6WKkXfdjmfjtLwL6ynXIkCHo1asXt029evU8/5+bm4uUlBQkJydjzpw5Pu0WLFiAnJwcrFu3zvOac8GCBYiNjcUXX3xhOk6NGjVw/vx5nDx50kelO3bsGNq0aePTlje2GTfeeCNOnTqF3377DfHx8aZtIiMjERkZabqPIAiCIAhr3FoI3DazVN20UoQ94uLiEBcXJ9T26NGjSElJQcuWLTFv3rxSsWmFhYUICQmBy/X3e3D9b7fbbWqzZcuWCA8Px/Lly9GjRw8AQF5eHnbs2IHJkycLj23Gtm3bEBUVhapVqwodH2GNSP02HZm4NdbTt4rSJVOry0zRYo0jE6fGs8lqI5I5ajxPvPVmWbF5IkqHiqonEz9mJztUV+ZExlGxb8c3XnyaKCLjmWUOi/pkvB9kFDTTDOxMcPG2YfRbJk6VIIKBoIihy83NRfv27VGnTh1MnToVx48fR35+vk+cW6dOnXDy5EkMHjwYu3btws6dO9G3b1+EhYUhJSUFQMnErHHjxti4cSOAkrIi/fr1w/Dhw5GZmYlt27bhoYceQvPmzT1ZryJjL168GG+//TZ27NiBffv2Ye7cuRg9ejQGDBhAChxBEARB+JHi/xUWtvsJdoIiy3XZsmXIzs5GdnY2ateu7bNPDwFs3LgxFi9ejHHjxiE5ORkhISG47rrrsGTJEtSsWRMAcOHCBezZsweFhX+v7zd9+nSEhYWhR48eOHv2LDp06ID58+cjNDRUeOzw8HDMnDkTTz/9NNxuNxITEzF+/HgMHjzYb+fkcsKJLDSZLFTWuAB7bU8z+3q8FWuNSpl6Wjq8GD078T3+Oscq68my7PIyY1k+ml0DOxnLMrXrrOISVWI0ef2din9j+WbMVFa5z4zqmBlWmctmqpxIDKJKTCvFzAUHbtjPUjV/jxdcBMWELi0tDWlpaZbtOnXqhE6dOjH316tXD8YckKioKMyYMQMzZsxQHttYq44gCIIgCKIsCYoJHXF5IxIHpxL/ZqUE8GqXGX0zw5gJacSsr6fCPkPJMKtDZrSnEj9oREStEInv0zGqOiK+scY1G4elvhhj3niI3DMiyqyOlTInEkPJ6uuN8VyyVGTvtjJqq5VvdpRGkfuMF6tp/L6oxBpa+SjShuLuAoszhYXplStBEARBEETAcGItVlrLlSAcxEoBUlHqzGDZ52XMsewZlSgzVUamxptKvJWVYma3PpzRvkjMoZWSJVMzT0UF49mQ8UlUzeEpNDL3Mes7YFSizMbxxLgZ1k/lZXo6oSbxjoe1pquoUmgFayUPnpIpmk1r1pcFqXJEeYAmdES5RTRRQBbRV4ci/0iLBP0b2xiL05rZZ/nqjWeiaJiIykz+WOOblYZQ+UfNTgkSO2VYjPtFymPw/Pe82s0U81UE3iST9apdZBIoMgGWKZNj9TBjFqLgGY9xvkTHNtsu8tChcj3MXt+Lnid65RpY3HDBDbtJEcG/9BdN6AiCIAiCCFrolWsJAV36i/BFX8bkcl/6S6WYqhOv9FQK2KogEtgus18m4JyF06qC1bl1+lxLFaN1oJQKa3xvrNRQu9dH5RyzCvvaeYUs0sc4vllRYhWVWuX7T6VI/Esglv6avrkNoivZ06fO/nURT7VaS0t/EQRBEARBBAInCgNfCoWFSaErR1yOCp3MYva8PnaeumXUPCNOK05OKA7Gv73PlxPB8E4Gk/PsisROskp1iIwj46PKNTQiE+dlRwVzOuZU1CczFdTKF6cKZcvcK1bfLZXfJJ5Pl5sSGAiFbvKmmx1R6J5p/UNQK3TBPyUlCIIgCIK4zKFXrkRAMXsCtlI4RBYF59kUjWFSiXFSjXETjR8yUw+sFACRrD3WeGaw9tlROL3/n6XUmSlB+r1gpQiZnWtPtrEhS1gFmSxH3n6rBeR5mbHG+DhjZq6V3yK+m42rY/a9tFJOzyUVmm73ti+joNmJBTTLXBct8+KUqkeo4XbglSsVFiYIgiAIggggbi0EbptZqnb7lwdoQkeUCVYFUwH207YTMUE8ZUOkjw5rqSmRorQidbusMFNBZOqQqWTEOhELJBJvxyoOa+zrrTiJKH/Gv/U+iQ/Yr11mZt9K1eGpuDKFpUudF4NKKVLIWiUOUkahNd6vxnOTMLf0PqvfAZEMWRl1nWXDeywrdc9MBbf6rvk785q4/KAJHUEQBEEQQUsxXCi2WRjYbv/yAE3oCL9gpRp5nmxN4ntUqr6r1KHTYS3fpRJDZ5ZRyvpbRhWTqSnG8s2sjaj6wvNN1X8WMvXIjEtLOZFR6H2OWAvd88axUlvsKMw+9xdniS9RWN9TnlInojSz7kXjd8C7Ly/Wj9WHNa7ZcVip62b2Rc+pTAyljoyqR/ChV64lBP8REARBEARBXOZQHbpyxKVch874FGyW/SYae2Kntpk3rCd2Gbs6vMXTZTIvrY5RJpvObl04lj0n67apKBsqmYuqPjthTwaVGnx2vg/+qlnHGpc3jlVNQZHrwxvXjorP6iPj0+WiwgWiDt2/N3REVCV7/2ae++sCxt+wIqjr0NErV4IgCIIgghZ65VoCTegIv8KK83I6q0tGaWD5wKrjBVjXoeLV0xN5UhdVgmQUTV48FAueqiejnIpmHaqoFT7ZgYa4KzsxgSKoKFsifTzZn+AraHbjLp1ARdlWUatYbcy+l1bKIw/RWnOi9u0ozZeLikf4B5rQEQRBEAQRtBRrISi2qbDZ7V8eoAkd4VesKrmbwXpKVamvxmtrHMeYgedEbB0gpmiwjtWJDDwz/2RqiVlhJwvZDCsfva+TaEwYL5bKW/EDfFU/lfMkqrLwFGARhYl1z/Cyn1nHLlKzTqfUShQOrHfq7Zt+/lnX0iwbViXmkGdPtC+vnqJIHKyO7gMpc2pocMFts+yIZqP/xIkT8dxzz+GJJ57Aq6++assPOwT/lJQgCIIgCCIAbNq0CXPmzEGLFi0C7QopdIQ6KnFrRsz6OJXF6r1dJeNQJsaFFxcnsgKGlX0VRYjnkz+QiSuSydq0qmloZlfvIxKvKBI7pcOKsxTJbjYiEndpXI+Vdy3NMq2tEFHXZOJGjb6x7muRc22sMWjmj0zWrkeNzOT3lfmuqbwZMB4Pz77VdqKEQL1y/euvv/Cvf/0Lb7/9Nl544QVb4zsBKXQEQRAEQQQtbs3lyAcoKYXi/SkqYj8gDR48GLfffjs6duxYVofKhRQ6QhkZRU7kKVgl00uk/pSor07UlhKpq8azz1r5wEztYa1iYFRqRFQ5J2rMyZwvsz5OZPqxrodKrJMZRlWKp7IZEYkjZGU1m8WrlWpriAWzW7fNOI7MOsZWiqzIubcTm2dm12q1D/3v/QuTPNsSH9jus0/ku3SwfzEAIIGhLPJssTJ6aa3XsqNOnTo+f6enp2Ps2LGl2i1atAhbt27Fpk2bysgza2hCRxAEQRBE0FKMEBTbfOGo9z98+LBPYeHIyMhSbQ8fPownnngCy5YtQ1RUlK1xnYRWiihHXEorRYgqASKxVCqxLTwlSFSZUYmh86mRJpENyPKX19eJuBoZJdNqfG9bItmTsr6UhzgiJ+vpmdmVUTSt+rJsWNmz8tHYV0UJVPGNp2ip1KET+Y5ZwTtOK7siCl0wEoiVIoat7o5ImytFFP11Aa/fJOb3559/jrvvvhuhoaGebcXFxXC5XAgJCUFRUZHPvrKCFDqCIAiCIAhBOnTogJ9//tlnW9++fdG4cWM8++yzAZnMATShI/yEypOziqqnouaJKj+8OD/j07dZTStWlisP43GwKuHz/JdRJ+xkAfPOFyuTkOUzz65xu4pSo5oZKapgyqgtvJgzO7GMMvex3pZVs867j2jsnEj8qLGvmZ9W96LM918mTlHlTYBZJq4nm1Ui29gqdq48qNPlGTdC4Lb5ylWmf0xMDJo1a+azrWLFiqhevXqp7WUJTegIYWRe7Vj9oyyzjxfgLvoPOe91oMhkw7hNJDDcap+ZT8ZkCLO2OiJtWD6ptFFB5j5Q+QedhUzyjchYxrYi5Sv88Y+wysTbu5At7wHEe7v3OKyJiczEUceYsGM2cTSOJ1MoWcQno2+8hxvWA5zIw5rVdecdu/EcGEuumPl/OVOsuVCs2SssbLd/eYAmdARBEARBEDbIysoKtAs0oSPMEVHbjE+tZoumq7wKsXrylFGczMYRLV8g8wqJVQSV19d7O6tMCU894KkdVqi8qpZB9LWm2Tm28klEoWEparxxRFB5pati1+iriALMUnnNFDYZH0W/wyLqu/FVvLcNlurNWz7QyYQQ3rU0nkMZBV3knrEKyzArQeSv724w4l1Hzo6NYIcmdARBEARBBC2aFgK3zZUiNJv9ywNUtqQcUV7LlhjjO1gFbb1ReVpUUXVY+1hBxt5+s8Y32uTZ5SFaikKkTfK0jQCAjUnW2VN2Sl2UlVIn4pNKkLqMTzq8JbOcuBdZ+0XuSZbP3naMbUQUTStV0lttF/VRBhVlUyVOVaSNjIrHssnr68RvUjCpb4EoWzLgu/sRYbNsyfm/LmBOu4/KxG9/QQodQRAEQRBBSzFcKIbNpAib/csDNKEjLCm13BEjM84bo6onEocjmuVq9lRvVVrBW31xotSBERH1gHU8PPS2PGVOJpbJifhEO6qBiHokU5BVJY7I2EdlkXmjLRGMbb3HtaOY8uIFWX2t7n2RkhtOqEcycapmfWQQvYZm9q3UVhUVlPebJOKbv9X1YMKt2Y+Bc18C7yqD/6UxQRAEQRDEZQ4pdIQyvCdClurBe3pkFesVUfWMqqHIeKJPxXaxkxXoRFwfTykQiVsTvS6842CNZ3Y8rHvHTLkz2pNZxklGzTP+zaqZxusjgqr6BMhlPcsoTqw+dr4nIuOInEcZtd14z3muIex/x1S+y6L9CWvcDiRF2O1fHgiKI8jJyUG/fv1Qv359REdHo0GDBkhPT8f58+d92m3atAkdOnRA1apVERsbi86dO2P79u1c20VFRRg6dCji4uJQsWJFdOvWDUeOHPFpU69ePbhcLp/PyJEjfdocOnQId955JypWrIi4uDgMGzaslH8EQRAEQTiLGy5HPsFOUGS5LlmyBB988AEeeOABNGzYEDt27MCjjz6K3r17Y+rUqQCA06dPIyEhAd27d8fIkSNx8eJFpKen44cffsCRI0cQHm6eAfP4449j8eLFmD9/PqpXr47hw4fjjz/+wJYtWzzrsdWrVw/9+vXDo48+6ulXqVIlVKpUCQBQXFyMpKQkXHHFFZg2bRp+//139OnTB/fccw9mzJghfJzlIctVJVvMTvYZL9NLpuaXjp2MUieekmViXFTbGlHJCpRBJfvUSV+cGE8lVssbJxdwdyojM1Cqjsz1YMXSBtInmT5Wvy/ev186drKBVVTQ8hY7F4gs196rHkBEpQhbts7/dR7vpiykLFd/06VLF3Tp0sXzd2JiIvbs2YNZs2Z5JnR79uzByZMnMX78eNSpUwcAkJ6ejhYtWuDQoUNo0KBBKbsFBQXIyMjAu+++i44dOwIA3nvvPdSpUwcrVqxAamqqp21MTAxq1Khh6t+yZcvwyy+/4PDhw6hVqxYAYNq0aUhLS8OLL74YtDcHQRAEQZR3aOmvEoJiQmdGQUEBqlWr5vm7UaNGiIuLQ0ZGBp577jkUFxcjIyMDTZs2RUJCgqmNLVu24MKFC+jcubNnW61atdCsWTOsXbvWZ0I3adIkTJgwAXXq1MH999+P//u//0NERMkTwbp169CsWTPPZA4AUlNTUVRUhC1btiAlJcV0/KKiIhQV/R2Dc+rUKbWT4QAicVY6rNgWXrwKC5G1EGVqPbH2i+CEOslTKc3WYxRFRmlyQjE1uy5Wx85TW51Q5ozn0WwcO/eBSEyoSka0zPeF9be/FCiVReBlfJBRq+xk+trJQhaxz/ru8takVVnvmVcT0bsdz18nYx2DBYqhKyEoj2Dfvn2YMWMGBg4c6NkWExODrKwsvPfee4iOjkalSpWwdOlSfPPNNwgLM5+35ufnIyIiArGxsT7b4+PjkZ+f7/n7iSeewKJFi7Bq1SoMGTIEr776KgYNGuRjJz4+3sdGbGwsIiIifOwYmThxIqpUqeL56MoiQRAEQRCEDAGNoRs7dizGjRvHbbNp0ya0atXK83dubi7atWuHdu3aYe7cuZ7tZ8+eRfv27dG4cWMMGTIExcXFmDp1Knbv3o1NmzYhOjq6lO0FCxagb9++PioZAHTq1AkNGjTA7NmzTX365JNPcN999+HEiROoXr06BgwYgIMHD2Lp0qU+7SIiIvDOO++gV69epnbMFLo6deoEJIZORXmwEwtk3G81tug4IrZE60TxYvVkbImcNyt1wrg6hxkqaosIRjv7FyYBABLmhvq0czqbU0VdsXPM+vk7l1To2Zb4wHYfuyzfnMpglImdFB1HJlbTTqygDHZUZBG7PKyunV2fZH5XnKS8xNIFIoauR2ZvRFS0GUN35jw+7PAuxdCpMmTIEOZkR6devXqe/8/NzUVKSgqSk5MxZ84cn3YLFixATk4O1q1bh5CQEM+22NhYfPHFF6bj1KhRA+fPn8fJkyd9VLpjx46hTZvSwa46N954IwAgOzsb1atXR40aNbBhwwafNidPnsSFCxdKKXfeREZGIjKy9BI7BEEQBEGIoTmQpapdAlmuAZ3QxcXFIS4uTqjt0aNHkZKSgpYtW2LevHmeSZtOYWEhQkJC4HL9fVH0v91ut6nNli1bIjw8HMuXL0ePHj0AAHl5edixYwcmT57M9GXbtm0AgJo1awIAkpOT8eKLLyIvL8+zbdmyZYiMjETLlup1pQKJU3E3Mk/DdjJWWf6KPK06uTatzNO9jDppFlOjK2W6iiRS3d/KJzOMbXRlTiYDU6W2mJ14NRXFTCRuUAY7mctGGyKKlogfxnvGaM/sHvJnfKpI3K1KzT8797dMG7NxnHiTIZPhz4q7s/M7RgQnQRFDl5ubi/bt26NOnTqYOnUqjh8/jvz8fJ/4tE6dOuHkyZMYPHgwdu3ahZ07d6Jv374ICwvzJCUcPXoUjRs3xsaNJQudV6lSBf369cPw4cORmZmJbdu24aGHHkLz5s09Wa/r1q3D9OnTsX37dhw4cAAffvghHnvsMXTr1g1169YFAHTu3BlNmjRB7969sW3bNmRmZmLEiBF49NFHg1a6JQiCIIhgwK25HPkEO0GR5bps2TJkZ2cjOzsbtWvX9tmnhwA2btwYixcvxrhx45CcnIyQkBBcd911WLJkiUc1u3DhAvbs2YPCwr9jZKZPn46wsDD06NEDZ8+eRYcOHTB//nxPDbrIyEh88MEHGDduHIqKipCQkIBHH30UzzzzjMdGaGgovv76awwaNAht27ZFdHQ0HnzwQU9JlfKISmybDiuDUURxUlF1ZOLHrNaONfWlVRvTtjKKk8yTr1lblfg3XWUxIpOxrKIeqKihrCxBEYWGdw9ZxXyJKFoq8WpGWyrjqMRjyfho1jbxAfn72MpPmZhQo02R4zFeW59s6kzf8Xhqu4zKZgXvuqiMw1Iajb9r3seub1NZledSg7JcSwiKCV1aWhrS0tIs23Xq1AmdOnVi7q9Xrx6MOSBRUVGYMWMGswDw9ddfj/Xr11uOXbduXXz11VeW7QiCIAiCIJwmKCZ0hPOw1AKZLDc7NatkVCRerTHdvugqE2Y+sarY8xQHo12eiigSU8OK33MiG5CnnLKuO6+mnIof+jlmjQtY1+czs2+lTsjEEdmJceK1tdougkgfq/g4EbtOZUqqqJGi8Nby5a3LqoKTWdQybyd0jPe38fhEEBkn2HHilSm9ciUIgiAIggggTqzFeims5UoTussU1pMnT42xUql4GavGTCwzBUXl6Vcl9swqbkdF1THG8oj04Y2popyoxGTpGK+7nfvAbBvreHhqi9W4ZtucyMgUQeY62KkPKKMIsuLjROyz/ubBOi5vO1axkzKqKC/bVcV/nYP9iwEAiRYKsZl9p1VXlj3emrF23rIQlxY0oSMIgiAIImihV64l0ITuMsMqRksmY42nABhjyljxUSLrcvKefllPoSp1yESQyapUib9RUQBkVCkrJcspxYGlpshk+omoFazYQ5V4JaewigFVseX0PSMzHuvc8tbrNSqwMlnhMm8PZNR21nnSlU2zYxdVi0ViTu0ojDI1MkWui9V4wQZN6EoI/jxdgiAIgiCIyxxS6C5TVOpDyTzdiWZGej+tMuPuwH66Z6kRIrXrVBQ01tO1nad7oHQcj0r8E2scbxWUldEralMUJ2pjiWb+ebfVj5lVl9AMFTXXqZhGK5xQGu2q1VYKIO/el6mbJzu+1T4jVr9fIrGgnu+pIV5RaJWR/9W7FImhtbQl0ddf16U8QQpdCTShu8wQ/XH2xmppLJXXgiL/kMgEUquUOhH5QWf1EXmFxPLXrK1xEfhSgeCwPva//7HZ7tPW7HW31atj3j9qrEB3s/4yk2UnkiJ0jOVXvMs9yPjE6qMC77tmNTHh3WesyavZNZb5x98KmeORsae63xuR77LRLu8c69sSBMqGsO4r3tJcVudL5R4V+Z2083qeKH/QhI4gCIIgiKCFFLoSaEJ3mWKlzHk/sRlLcthROFh+iLTlBSCrLAFl5Suv6K1IIDrrlbEZLPVB5JWhvs/4ulbllbiICsZS5swUBzslO0SwssMLJndyXDP7xmPnfW+sVCJj0WBvziWVLGUYOsl3n8hi9jJYvcYWuUdFSmrIhAOwzptIcoeI3yr3jaiKL6I0q/ghcm9eaq9eNdivI6dZNyn3UFIEQRAEQRBEkOPSjIubEgHj1KlTqFKlCtqjO8Jc4cp2nEhNF4nvkFFbnC6lwGpjRCQ5gmXDrooko2iqnB/RPiqxWt5YlVtwSm1zoiAq65ybJYaIwLp2/rqfrVQwXmyjv+KgWPZVvi8yCRr++k5Y+e29n1UQnWdTb2NUVUXOV6k4VT8p28bxnLR7UbuALHyBgoICVK5c2TG7Zuj/Zt769UCEVYy07sDh4pkirLx9dpn47S/olStBEARBEEELxdCVQApdOcIphU5H5OlLf4pMmBtq2VYkI1bHShmzo1LI2BOJ0bPKEgTYT8p2nnBFCuTKlF/RMWa78saWKcxsdcwqGYWi+1j7WX14MWdOqGs85caOcmpH9WapO6wxZcd1IgZNJo5QxKaMglpWGZ1WvsjEtNnJ1jU7Xtb33snlwgKh0LX/6nFHFLqsO2aRQkcQBEEQBBEISKErgRS6coTTCh0PmfgX0SdOkbpHMk+cRnhPkSwfePFfIhm+VvZ5OKGG2IkFMmsnqrLZ9U2lrUofUaVR1Vc7iqyxLS+mimVP5v6VuZ9lcFLZ4vnqRKyunT4yOP09MSKimFllqMqMG+wK3U1fDnZEoVvd7c2gVugoy5UgCIIgCCLIoVeulzkqT48i9adEn05lYuhUnh5l4vB4KoxoXI/TqpuI2iJzjmXiIJ1AJr7L2IeFt8+sFUF4NlhqhFkf46oYMt8X47EnzDXf743MeWLZcTrm1Mo3GSWKd9+x7Kh8p+zEaPLsiJw3fZ+dWFCRc2snBtTYVybzuzyiaS5oNl+Z2u1fHqAJHUEQBEEQQYsbLtuFhe32Lw9QDF05wl8xdDJ1lZzKpuL5YNXWCl7cjZ14OBn1SiX2zA5GdQSwrgsnEn9ltC8TB2kHkQw8kfhLO75YZfwB4t8TO1mpvP5OZL2qKFxOnWM7qKiIKrGOMj44kSGtkrlqtt94/8rE3Tl9nrwJRAxd8hdDHYmhW9d9RlDH0JFCRxAEQRBE0EJZriWQQleOUFXoWE9mTj2hG2NmWMqPSs0nFSVARqETwYnsUBHfVOA9oftDOTOzzcoc5t0P5U3VsWtPx1/qpNU+M4XWKr7OW2kU7cNDJpvWCQXTaruMDZk2Kt97VX/t9GH1lTkHMrGaogRCofvnZ084otBtvPu1oFboKMuVIAiCIAgiyCGFrhzhlEKnogA4WYfIDH/F6rAUOSee0M3i1WRqfRkVEpGMWxWVwklV0gwRRdYKO9eJhzFe0GpFD7NtMvekSryolS2ZNjIquIxyqvKbwWoHiGfC8q4Ly2feOLI+y7ZV6euEL7zvAuscBCqmLhAKXatPn3REodt8z6tBrdBRDB1BEARBEEELlS0pgSZ0lwAyVfJZT2IydYhElBNjNi3PJ5Z9EXVEpqaU0Te9thhrPO/zqqIwydTAM2L0iWeDdU1FFCDjeGZP+1bHoaLuGpU1b6yyd73R/RapKceyJxPvZeeelDlPIhm+VoisqCKjguqw6kR6t9O/WywbVtt5PvPGUVGYnFbmZL67VvZEFFqWCmqntlx5yHIm5KEJHUEQBEEQQYvmQJYrKXREucD4ZMbLXFKJt1LJWDM+ObMws2Xc9vcamOrxPT6+WcRZifgkMr6MAmSlyMgoTrxxrNQVketmVNXM7jPWOEbsxmyqXBcrGzLqhMy1FIlBVPHb6jttV3EUHV/leMzOtZ14rrLKLHU6Ns/qOni+T7COOeRhVIntKKflCQ2A3WyAskwmWLJkCSpVqoSbbroJAPDmm2/i7bffRpMmTfDmm28iNjZWyS5luRIEQRAEQZQR//d//4dTp04BAH7++WcMHz4cXbt2xf79+/H0008r2yWFLohhPQGy4tYAIHnaRgDAxqRQnzYyT/FW41vtY/nGapswN7RUW2Mf0SdPs75W48vY4LUx+m+3Bp/KuKLxljzfWCs5iGCndhnvnlKJT1OJobOyyevPuldlxla5r1Xsi1x/lfF48WWisWflKb5LJa5XJu6Od69Y3bdm4zhZq7Q84YYLriBa+uvAgQNo0qQJAOCTTz7BHXfcgZdeeglbt25F165dle2SQkcQBEEQRNCiZ7na/ZQVERERKCwsBACsWLECnTt3BgBUq1bNo9ypQApdEGPM1tQxPmV711PTlTmZ2mL+rNMkEufFa6tjJ6OLhUztMhF4T9DGa8WqeyfyJM0b1ypukLf+K0sR+DvGcbtnn5VS5jlOsFU+lupqdl2sVCMZJVDEFxkbxnOsEjeoEqtpB94945Rdb9uBgPUdEFEAnY7vY/nCW2fYSinnvdFg+S8TP0yoc9NNN+Hpp59G27ZtsXHjRnzwwQcAgF9//RW1a9dWtis0oVOZMQZrYb5gQqSQsHc7Xl8dM1vGiaPxH32ziaPKqz3RvmbjqCQgqLzeYk1EzMa3Kq5q9g+Hblcl4NzYhrf0k0ipFhZG3/RkFZEyKZ5/qAz3ktnYrAQNkUQEXltWX+51kXi4cKJshcyEweo7zJugiDw8+eMfdJmSOk6NI/pQafe1NssHkT6sh3Sz8jyiD8sq57o8vdYWwa254AqitVzfeOMNDBo0CB9//DFmzZqFq666CgDw7bffokuXLsp2hSZ0VatWhcslfrAulwu//vorEhMTlR0jCIIgCIKwQtMcyHItwzTXunXr4quvviq1ffr06bbsCr9y/fjjj1GtWjXLdpqm2QrqI/jw0vyNbVTUKV4gvdlTovd23ms6ladeltLBe03n76dJ1rGLKI0i6ouMWmClSvLUNhWFwfi3ndfQrHuJN44IIoH0rD5mbXivoFl9WPexzELoKscs88pdx07xax39lXvU9gqebVbHqKJamvVltZG5d1QKYztRXkZE5WWp/DI+qSjawaDKBTOhoaHIy8vDlVde6bP9999/x5VXXoni4mIlu0ITuoSEBNxyyy2oXr26kNHExESEh4uvRUoQBEEQBKFCsC39pTHkwKKiIkRERCjbFZrQHThwQMrojh07lJwh1JAp2cF6ehMpJ8FSZFRUJB2feLhM8/GsjkHER96TrUgcEev8OBXkLao08BRalpLGi20U8ddKieMlOKgoJzJlRVhtjcqGqpIimpzifY6NcZDGuEGj7yL+6ft5MYdOBejLopcVApxNTLITyyajAPK+Eyrfb7Pvndk4ZljFkZrd+zLfF+M2q98dM8qjehcsE7rXX38dQElY2ty5c1GpUiXPvuLiYnz//fdo3Lixsn3KciUIgiAIgvAzeoycpmmYPXs2QkNDPfsiIiJQr149zJ49W9m+S2Npfwz0GWYpQy4XoqKi0LBhQ9xyyy0+jtolJycHEyZMwMqVK5Gfn49atWrhoYcewujRo33kyU2bNmHkyJHYsmULXC4XWrdujcmTJyMpKYlpu6ioCCNGjMDChQtx9uxZdOjQATNnzvSkDmdlZSElJcW078aNG9G6dWvP8RuZNWsWBg4cKHycp06dQpUqVdAe3RHmEn9l7Y+yIt5KACvOhlXyAnC2NIOK6qWSHSiTFSbiq9UTs0gJAjuxbnZsqMQ46bFUwN8lTFhLgInEeerYibdi2ZT1xR9ZgTLlMWRts2DFi9n5DfE3dmI0/X08ZuOoKGYy9lV9NPPJie+WkYvaBWThCxQUFPi92oX+b2ajBSMRWiHSugOH4sIi7Hnw5TLxOyUlBZ9++qnyEl8spBW66dOn4/jx4ygsLERsbCw0TcOff/6JChUqoFKlSjh27BgSExOxatUq1KlTxxEnd+/eDbfbjbfeegsNGzbEjh078Oijj+LMmTOYOnUqAOD06dNITU1F9+7dMXPmTFy8eBHp6elITU3FkSNHmDF9Tz75JBYvXoxFixahevXqGD58OO644w5s2bIFoaGhaNOmDfLy8nz6jBkzBitWrECrVq18ts+bN88n5bhKlSqOHD9BEARBEOYEW5brqlWr/GJXWqFbuHAh5syZg7lz56JBgwYAgOzsbDz22GMYMGAA2rZti169eqFGjRr4+OOP/eI0AEyZMgWzZs3C/v37AQCbN29G69atcejQIc9E8ueff0aLFi2QnZ3t8dWbgoICXHHFFXj33XfRs2dPAEBubi7q1KmDb775BqmpqaX6XLhwAbVr18aQIUMwZswYz3aXy4XPPvsMd911l/IxiSh0KjWlvLF6auQ9cVrZ5PlrJ5aKN56TT+KiC8qb+WYsCGzWn2dfNAZQRtFy6imcFRPEUt14Y4qoFTL3G0slVslYPNi/JLPMu0CyTCymmX9m45jdK8a+dtRqGdVY5V6xg0w8pNV2XpvyEAOmktVqde/IqMiBUl0DodBd/b4zCt2v/yobhe6+++5Dq1atMHLkSJ/tU6ZMwcaNG/HRRx8p2ZVe+uv555/H9OnTfSZIDRs2xNSpUzFq1CjUrl0bkydPxpo1a5QcEqWgoMCnjEqjRo0QFxeHjIwMnD9/HmfPnkVGRgaaNm2KhIQEUxtbtmzBhQsXPMtuAECtWrXQrFkzrF1r/g/Cl19+iRMnTiAtLa3UviFDhiAuLg6tW7fG7Nmz4Xa7ucdQVFSEU6dO+XwIgiAIghCnRKGzu/RX2fn73Xff4fbbby+1vUuXLvj++++V7Uq/cs3Ly8PFixdLbb948SLy8/MBlEyKTp8+reyUFfv27cOMGTMwbdo0z7aYmBhkZWWhe/fumDBhAgDg6quvxtKlSxEWZn6Y+fn5iIiIKPUeOz4+3nMsRjIyMpCamlrqdfKECRPQoUMHREdHIzMzE8OHD8eJEyfw/PPPM49j4sSJGDdunNAx6/CUM5ZiwsvAM9qSyZDl9XUijkREPRBVHEXsy9REM/pizNA168NT/mQUIKN9ow2eTatxzM61SJamsQ9LjeRddz0GL2Gu+X4ZJdAIr4/+d6Lh+Hhtzewat7F808+JWfaxTIa36L0ic785EY9rZp91/UWupczvAKsPz75IJrkdRH5rrcZRie+0E9usGnMaKIIly1Xnr7/+Mi1PEh4ebkvYkVboUlJS8Nhjj2Hbtm2ebdu2bcPjjz+OW2+9FUDJq8769etb2ho7dixcLhf3s3nzZp8+ubm56NKlC+6//37079/fs/3s2bN45JFH0LZtW6xfvx5r1qxB06ZN0bVrV5w9e1bqGDVNM01yOHLkCJYuXYp+/fqV2vf8888jOTkZSUlJGD58OMaPH48pU6Zwxxk1ahQKCgo8n8OHD0v5SRAEQRBEcNGsWTPP+q3eLFq0CE2aNFG2Kx1Dl5+fj969eyMzM9OTaHDx4kV06NAB7777LuLj47Fq1apSrzLNOHHiBE6cOMFtU69ePURFRQEomcylpKTghhtuwPz58xES8vd8NCMjA8899xzy8vI828+fP4/Y2FhkZGSgV69epWyvXLkSHTp0wB9//OGj0l177bW46667SqlnEyZMwIwZM3D06FHLwslr1qzBTTfdhPz8fMTHx3Pb6vBi6JyOoRCt3yVqTxSVuBKRtsY+Im2Ni8o7nfnlZMaqWV/RjEU7WbsibUTsG9vKrJogglW8parq4mSWq0z8mIji7IQ6KXJNnYzNciKjWATjd9vpcXg2ROpaercDrOtDyvwmGbkcYugavDsKoRWibNkqLjyHfb0nlonfX375Je699148+OCDHiEsMzMTCxcuxEcffaQciy/9yrVGjRpYvnw5du/ejV9//RWapqFx48Zo1KiRpw2rzIeRuLg4xMXFCbU9evQoUlJS0LJlS8ybN89nMgcAhYWFCAkJ8VHW9L9ZsWwtW7ZEeHg4li9fjh49egAoeaW8Y8cOTJ482aetpmmYN28eHn74YaFVMLZt24aoqChUrVpV6PgIgiAIgpAn2F65duvWDZ9//jleeuklfPzxx4iOjkaLFi2wYsUKtGvXTtmutEKnc/78eRw4cAANGjRgxqg5RW5uLtq1a4e6devinXfe8alxV6NGDQAlpU2SkpLwyCOPYOjQoXC73Xj55ZexePFi7Nq1CzVr1sTRo0fRoUMHvPPOO/jnP/8JAHj88cfx1VdfYf78+ahWrRpGjBiB33//3VO2RCczMxMdO3bEL7/8gmuuucbHv8WLFyM/Px/JycmIjo7GqlWrMHz4cKSlpeG1114TPs5A1KGTsa/DGsesdp2xj52aUmYEOmvPiIyCIhPbZmbTX0oJz0+Ara6pZBaqxDg5hUqGrKj6whvHuN3MjtNqsaxPIgqaTEZxWSvaZjaciOuVwc54MueLtd6r028ERAmEQpf4znOOKHT7H36pTPz2F9IzscLCQgwdOhT//e9/AQC//vorEhMTMWzYMNSqVatUGq4TLFu2DNnZ2cjOzvYU/NXR56ONGzfG4sWLMW7cOCQnJyMkJATXXXcdlixZgpo1awIoKTmyZ88eFBYWevpPnz4dYWFh6NGjh6ew8Pz580sVRs7IyECbNm1KTeaAkkDGmTNn4umnn4bb7UZiYiLGjx+PwYMHO30qCIIgCILwRvvfx66NMuTPP//Exx9/jP3792PEiBGoVq0atm7divj4eFx11VVKNqUVuieeeAJr1qzBq6++ii5duuCnn35CYmIivvzyS6Snp/skSxByyCp0Vk/IKrFNdhQBkWwqEQXA6KuduBuRTEArlU+kjUpsI88Hkf1W6oqMYubv2CaZmDAnVzNQqUsns0qKGaJxcE4pNKzvoUi9Q5VxRTCqR3YUTadUfZXYRpk2rD4yvy8qPjkR46jfM+eSSsQOs9hDUfsBUejmj0aITYXOXXgO+9NeFPZ71qxZmDVrFnJycgAATZs2xb///W/cdtttln1/+ukndOzYEVWqVEFOTg727NmDxMREjBkzBgcPHsQ777yjdAzSWa6ff/453njjDdx0000+8WpNmjTBvn37lJwgCIIgCIIIFmrXro2XX34ZmzdvxubNm3Hrrbeie/fu2Llzp2Xfp59+Gmlpadi7d68n6RMAbrvttrKtQ3f8+HFceeWVpbafOXPGtNQH4QwyWVV6G94TmtWqCCLqlBHvp3ArtUimFpMdtcBfMUgyY8usQGHlg4qPZgqN8W8Zn0QUFCuFgTeuncxXo13dlojqxhvfaFfkOqiooKy+3v7rsFaE4Z0/K59UsmntXEuzcYx27Nzz3vZZfvorzlbmu2x1fzkVb8nC7HvCoqzjkkUIxNJfd955p8/fL774ImbNmoX169ejadOm3L6bNm3CW2+9VWr7VVddxayBK4K0Qte6dWt8/fXXnr/1Sdzbb7+N5ORkZUcIgiAIgiBksb9KxN9ZssbVm4qK2Etp6hQXF2PRokU4c+aM0DwoKirKtIDwnj17cMUVV8ifgP8hHUO3du1adOnSBf/6178wf/58PPbYY9i5cyfWrVuH7777Di1bWscsEeaYxdDxYoD8GQ9jN76DZ8+7j0ysC8sWz56dmDA7cTgi9mV8UskgNevrRLwNy76KDZUq9ryx7azlKlMbT0Uxl7HHyqbV15sFSsc5+Tsz1om+MjaciFcNBFaxbSq1PnkquJNKnRMEIoau3n+edySGLueRF0ptT09Px9ixY037/Pzzz0hOTsa5c+dQqVIlLFiwAF27drUca8CAATh+/Dg+/PBDVKtWDT/99BNCQ0Nx11134ZZbbsGrr76qdAzSCl2bNm2wZs0aFBYWokGDBli2bBni4+Oxbt06mswRBEEQBFG2aC5nPgAOHz7ss4LTqFGjmMM2atQI27dvx/r16/H444+jT58++OWXXyzdnTp1qid87ezZs2jXrh0aNmyImJgYvPjii8qnQbkOHeE8IlmuvNg243YZVLJBRcZzUs2ToTxkIcr4KKqc2cnaFbHP8804tjGDkadWGWtkmakUVhm+RpveY7Nw+hpanQOzsUWumbGPjoja50Q9uLLOqjQbV7S/vxRnO7GgZtj5vbSjspaVUscaJxAKXcLcMY4odAf7T7Dld8eOHdGgQQPT+DgzVq5cia1bt8LtduP6669Hx44dlcbVEUqKkFksNlgL8hEEQRAEQaiiaZpQzJ3Orbfe6ln6ywmEJnRVq1YVzmAtLi62bkQI48TTPe/JXVQVEd1nZde43+xp2CqWSSQDVyYLUSW+z46ap5JZarbdSr0RyaZUeZr3ZJBmsm3rbVj1x+IhH59ozFzltWHt926jkklo3G48B2bI+MTC850wGU9mhQCjHatsdG+slCAV5UxFiZLJDrWL1Xmx8zvDuyftKHVlFVNXrmL3AlBY+LnnnsNtt92GOnXq4PTp01i0aBGysrKwZMkS0/avv/46BgwYgKioKLz++utc25UqVULTpk1xww03SPkk9Mr1u+++8/x/Tk4ORo4cibS0NE82x7p16/Df//4XEydORJ8+faQcIP6G98rVLEjazisKmddnvIWuvW2pvErw9sNqCRuZ1H2nf2REX2/YTY6w45Od88WyqeKP2Xg6rFewPL9lfLG6V73tO3FdRILV7dhzIhFA5bWmlR1RH/2Nik8qk38nffMXZZUkYWU3EK9c6875tyOvXA8NGC/sd79+/ZCZmYm8vDxUqVIFLVq0wLPPPotOnTqZtq9fvz42b96M6tWro379+lzbRUVFOHbsGJ566ilMmTJF+BiEFDrvxWLHjx+PV155BQ888IBnW7du3dC8eXPMmTOHJnQEQRAEQVzSZGRkSLU/cOCA6f+zWL58OR588EGpCZ10UkSFChXw448/4h//+IfP9l9//RVJSUk+66QScngrdK6ON/rskwmGdkox442tCu+pVfTVp8hTt4wSJKJwiTzN89pZIRp87cTrbp4dEcXJidIgZkqw6FJ2vO+CSKkQfygXKqqOTMkWO+fc7nHaUX5kkgqs7i+Z18FO4YTqJfK75sSrVju+iCD6HQuYQhdtU6E7K6fQ+ZuzZ89izpw5eOKJJ4T7SJctqVOnDmbPnl1q+1tvvYU6derImiMIgiAIglDGycLCZUVmZibuuOMONGjQAA0bNsQdd9yBFStWePZHR0dLTeYABYXum2++wb333osGDRrgxhtLVKT169dj3759+OSTT4SK6hHmiBQW9vdTqtMKjZ0nThEVUSWO0KqvnUQHEfsiftpRJ0XsG+2JjCOqoJnZVYlXElEEyioezojIeHa+JzL3voyPogqN3Tgy1m+G8VqK/J45oZzz2rJ89hdlFd+r0seJmNBAKHR13kp3RKE7/Ni4MvH7jTfewFNPPYX77rvPk4uwfv16fPzxx3jllVcwZMgQJbvSa7l27doVe/fuxaxZs7Br1y5omobu3btj4MCBpNARBEEQBFG2BCDL1Q4TJ07E9OnTfSZuw4YNQ9u2bfHiiy8qT+iosHA5wiyGzk6Mm0qWo8o4/saJmECRvqwsW2+sFAeZscsqa9df8YMy47BwIg7Lu42/MxdZiMTDyZxjmRhXIzKZnqzxRXAiA9cuKoq2qE0Ruyrn2I56yOujEhet8haE9XupExCFbvZYZxS6gWPLxO+YmBhs27YNDRs29Nm+d+9eXHfddfjrr7+U7ArF0P30009wu93CRnfu3ImLFy8qOUQQBEEQBHGp0q1bN3z22Weltn/xxRe48847le0KvXK97rrrkJ+fjyuuuELIaHJyMrZv347ExERlxy53jE9Q+qLciQ9Yx/fIPDXK7Jd5ShVVTJKnbfRs25gUatrWzlO+iDInst14rCIZeCqqgYgCY2zrhAoici1ZfVh/i+4zYvQh0CqPiA9mS5hZqSB2z5fRvrFosB3lTEZttZN97G8lWERp0uEVNBdVnEX6qNjS0f8dAIDETP54dr4/IvemXhy8rNRYLkHwytW7mPA111yDF198EVlZWT4xdGvWrMHw4cOVxxCa0GmahjFjxqBChQpCRs+fP6/sEEEQBEEQhDBBMKGbPn26z9+xsbH45Zdf8Msvv3i2Va1aFf/5z3/w/PPPK40hFEPXvn174aW/dBYsWICaNWsqOXW5wlspQgR/xV3plNUTmJWiJfNUb0c9dCJrzAyz7Ecnr5Udv+1kuZnFkfk7A88fOB1vp5KF6oS6qxJzKtPWiXtW5D7zVyygiHJm5/rbibtz4pw6EXssaw8IUAzdTIdi6AaVTQydvxBS6LKysvzsBkEQBEEQhAKaq+Rj10YZc+LECbhcLlSvXt0Re9JlS4jAIPJEa0eZsxN3wfONF5fCwmpsu6qJVX89TiUB7Cd1q3Pvvc2oyOnxRCJKAC8GifVErpKx6sQ9473OsNV4RhsibY3n03tMq0w8mTWQVVQjEUWb19bq/ItcSxlli/VbYdZH1CeRe1Pl98VOrKHI91HGpsz3ROaecTIOlmdTNG4voPFwCmhayceujbLgzz//xOjRo/HBBx/g5MmTAEpev/bq1QsvvPACqlatqmybJnQEQRAEQRB+5o8//kBycjKOHj2Kf/3rX7jmmmugaRp27dqF+fPnIzMzE2vXrkVsbKySfapDV47Q4wFubp+OyO92AhBTAnSMT1VGdcesrZ1YGn/FtrBsiOCvuDcn4lOciAGzmxUo29fMjlHpMLu/WOM4fQ6sxrUTR2S2z4n72mib568d5VRFHZf5fVHBCSVYJHO1rL5j3mqxjsz5No7ppDLmtE3R70IgYuhqzxjnSAzdkaHpfvX7ySefRGZmJlasWIH4+Hifffn5+ejcuTM6dOhQKoFCFOm1XAmCIAiCIMoNegyd3Y+f+fzzzzF16tRSkzkAqFGjBiZPnmxan04UeuVaDgnN2o5iw0oRIutCGp+YeHFXMhll/qhdtX9hEgAg8YHtlsfBG1d0vUzvJ+lzSYX/G1tcBbG6DrzYI5lMMrN9Zn6YwTpvdp/QWU/mKmuUqiiaRlTir2TiFb2PS1QpU1FORWLOeLB88sQ0orQN1ji6mqcjc22N44r4KGJX7yNSX4/lg93rYoVT61lbff95aquVqiuiuopcy2CLqyuP5OXloWnTpsz9zZo1Q35+vrJ9pQndr7/+iqysLBw7dqzUChL//ve/lZ0hCIIgCIKQwaWVfOza8DdxcXHIyclB7dq1TfcfOHDAVsardAzd22+/jccffxxxcXGoUaOGT306l8uFrVu3KjtzucNby9UsXkkl7saJmBxjzJTTT25OxADZifOTydpj9WWNadbXDJGnbSv7Kk/oduKURBRaf8UritoSsSej6jihQIm0FfVHdmx/xTSK3vv+Un3sxI36K47QTjy0GaJvJ1TuZzNfrK6dvv/ixXP4IWtc2dahe3W8M3Xonvy3X/3u168fsrOzsXz5ckRERPjsKyoqQmpqKho0aICMjAwl+9IK3QsvvIAXX3wRzz77rNKABEEQBEEQlxvjxo1Dq1at8I9//AODBw9G48aNAQC//PILZs6ciaKiIrz77rvK9qUVusqVK9M6rX5CZKUIkac6Y+aVSNyFE4hk7RmfKp3KWOPZNdqQUeaMiD6leu8z+sZ7smbFFor4xqpZJ6PQsVRYEbzjsFjXwWhf5LrwUInvNMK7hkaV2G7WrFM2RNqabbdaW9XYV6SNv2OrdJ/12Neo7X8vQSlzHDoyx8P6/bIaVxWZaylrw2yfzO+K8feKtT0gK0VMn+CMQvfUGL/7feDAAQwaNAjLli2DPv1yuVzo1KkT3njjDTRs2FDZtrRCd//992PZsmUYOHCg8qAEQRAEQRCOEARruerUr18f3377LU6ePIm9e/cCABo2bIhq1arZti2t0E2cOBGvvPIKbr/9djRv3hzh4b5K0rBhw2w7dbniXYcuLKzkaUM0+9EbO4qWnRgqGXjrmbLgKU4qGV4sG2aIKnM8lcpO3JJMLBhLEQRKK28qCpRxfB2VODWnFQcZnIwFtBOzxfOlPKDim4xibsU/txcDANYN/2epff74bVK5/jKrlzgdDyujTov+e6Jy/vRzUFx0DnumP1e2Ct0rDil0T/tfofMn0grdnDlzUKlSJXz33Xf47rvvfPa5XC6a0BEEQRAEUXYEkULnT2iliHKE2UoRIvFwOlZPxYB4lqZIVqixr1lbXsyUlY/GNv566pbJyHTyidbMrkzmMmulBpE4NTtP4Kx7kBc/6GRmtIiywfveOHkN7WREqyCTsWiGTB1F1j5/qKLe+3Sczrw12jXem07VerM6TzIVC2Swc1+LHI9oLHBAYuimOqTQjQhuhc7WShGapoHmgwRBEARBEIFFqbDwO++8gylTpngC+q6++mr83//9H3r37u2oc5cr3itF8LINjU9kLOVERD0QqWlkpYaYVdjXq7urxP75q0aWcTyRNUlZfY327SooOsbq+GYw495atWGOL6oemN0HMjGB+jYrZc5bSRPJAmYdl9EHkSxElThLFmbHwcyQhHpMoEpmrPfxqawzarSnklEqE69oRLTemoiP3mMa7Zn9Vul2VL7LrD5OVR0QjTl2qm+p86VwL/kNJ5bu8vPSX9dffz0yMzMRGxuL8ePHY8SIEahQoYJ1RwmkX7m+8sorGDNmDIYMGYK2bdtC0zSsWbMGb775Jl544QU89dRTjjp4OcErWyLzakfkH1qrH0+Z1wG814FWr+dEfHP6x84qocGpkipWr0DsTHKtxrbq41RSgtV+JyflZuftYP+SgHmzJeRkx7czIfHX63nWvckbR2XSZ0QkyJ81voh9EYx27RQaN/PJH5Mou+P4I4FK5jdD5neN9XAWiKSIupNfcOSV66Fnnveb39HR0di7dy9q166N0NBQ5OXl4corr3R0DGmFbsaMGZg1axYefvhhz7bu3bujadOmGDt2LE3oCIIgCIIgvEhKSkLfvn1x0003QdM0TJ06FZUqVTJtq7qEqrRCFxUVhR07dpQqfrd37140b94c586dU3KER05ODiZMmICVK1ciPz8ftWrVwkMPPYTRo0f7LJ+xadMmjBw5Elu2bIHL5ULr1q0xefJkJCUlMW3PmTMHCxYswNatW3H69GmcPHkSVatW9Wlz8uRJDBs2DF9++SUAoFu3bpgxY4ZPu0OHDmHw4MFYuXIloqOj8eCDD2Lq1Kmllvfg4Z0UcXRgiUKXMDcUgPNBxFaKg1n5DatxVZQgu32MfVlt7SqBVsdsVpBX5ilb1CeZp22e2soan4fM6zNWX964okkETiundhRtEawUDUBcdRJ5tVsesCqLpGLLX8V8RZBRzkTvX1XV2GhX5TdWR+Tcyib5BCIpou4khxS6Z/2n0O3Zswfp6enYt28ftm7diiZNmiAsrLSmZmcJVWmFrmHDhvjwww/x3HPP+Wz/4IMP8I9//EPJCSt2794Nt9uNt956Cw0bNsSOHTvw6KOP4syZM5g6dSoA4PTp00hNTUX37t0xc+ZMXLx4Eenp6UhNTcWRI0dK1cvTKSwsRJcuXdClSxeMGjXKtM2DDz6II0eOYMmSJQCAAQMGoHfv3li8eDEAoLi4GLfffjuuuOIKrF69Gr///jv69OkDTdMwY8YMP5wRgiAIgiCChUaNGmHRokUAgJCQEGRmZjr+ylVaofvkk0/Qs2dPdOzYEW3btoXL5cLq1auRmZmJDz/8EHfffbejDrKYMmUKZs2ahf379wMANm/ejNatW+PQoUOoU6cOAODnn39GixYtkJ2djQYNGnDtZWVlISUlpZRCt2vXLjRp0gTr16/HDTfcAABYv349kpOTsXv3bjRq1Ajffvst7rjjDhw+fBi1atUCACxatAhpaWk4duyY8Gxff9po9NRLCI0sedrgPeHaKd5pRwUTecJ0ojyCle/eyMTXiD5ti6hhdhQhM6yemFVUMLP+Mkogaxx/xc4xkwlMklas/C2ruD6zfSwfVBRbFfXQjo8i8Gw4GQtmRPW6qaiGdn6TZPo4Ed/Hsm9X0ZR9o0EKXeCQLlty7733YsOGDYiLi8Pnn3+OTz/9FHFxcdi4cWOZTeYAoKCgwGepjEaNGiEuLg4ZGRk4f/48zp49i4yMDDRt2hQJCQnK46xbtw5VqlTxTOYA4MYbb0SVKlWwdu1aT5tmzZp5JnMAkJqaiqKiImzZwv4yFRUV4dSpUz4fgiAIgiDEcQFwaTY/Zezzvn37MHToUHTs2BGdOnXCsGHDsG/fPls2lcqWtGzZEu+9956tge2wb98+zJgxA9OmTfNsi4mJQVZWFrp3744JEyYAKCmnsnTpUtP31KLk5+ebyqJXXnkl8vPzPW3i4+N99sfGxiIiIsLTxoyJEydi3LhxpW1vK0Lkd77v0M3KWKjEp4g+pfJsiah6RjVFJEaLZY/nm95GH0/kXDDj32Dto0p8l4xyZqVo2lUTWPuciCOTURx4ioaxDS++x0qltpuByTp24z3jvV9UMROJH1VRZI2Kpuo9aQejuqryW+WEjypximZYKY4qKqiKeszLPjb+nqm8rZChPMVsBkPZEm+WLl2Kbt26ISkpyVMtZO3atWjatCkWL16MTp06KdkVUui8lSOjomRHYRo7dixcLhf3s3nzZp8+ubm56NKlC+6//37079/fs/3s2bN45JFH0LZtW6xfvx5r1qxB06ZN0bVrV5w9e1bKLyMuV+kLrWmaz3aRNkZGjRqFgoICz+fw4cO2/CQIgiAIonwzcuRIPPXUU9iwYQNeeeUVTJ8+HRs2bMCTTz6JZ599VtmukHQVGxvrqZlStWpV7uSluLhYePAhQ4agV69e3Db16tXz/H9ubi5SUlKQnJyMOXPm+LRbsGABcnJysG7dOoSEhHi2xcbG4osvvrAch0WNGjXw22+/ldp+/PhxjypXo0YNbNiwwWf/yZMnceHChVLKnTeRkZGIjIwstT00azvwvzp0LAUKYCsaxv0imXEi8TDGfbynVBVFzthXJH5MVNkwe5rUt7GKH/tk+mb67HI0Ngwwv77ebVWydXXMMpZVlFmjfaNqLKJSOBm3BLALF6vEk5rB6sfL/LZSJ3k1Gu3EnIn4xkJFPRQ5p0ZfZL7TTiBSKF3mt0ImNtC4TSQW1OrYecfDqqMp8lvOQ/Se1PcXXzwHZH1haddRgmwt1127duHDDz8stf2RRx7Bq6++qmxXaEK3cuVKT7zaqlWrlAczEhcXh7i4OKG2R48eRUpKClq2bIl58+Z5Jm06hYWFCAkJ8Zls6n+73W5lH5OTk1FQUICNGzfin//8JwBgw4YNKCgoQJs2bTxtXnzxReTl5aFmzZoAgGXLliEyMhItW6pPbAiCIAiCsCDIJnRXXHEFtm/fXqoyyPbt221lvgpN6Nq1a+f5//r166NOnTqlVDpN0/z2yjA3Nxft27dH3bp1MXXqVBw/ftyzr0aNGgCATp064f/+7/8wePBgDB06FG63Gy+//DLCwsKQkpICoGRS2KFDB7zzzjueyVl+fj7y8/ORnZ0NoCQzNiYmBnXr1kW1atVwzTXXoEuXLnj00Ufx1ltvASgpW3LHHXegUaNGAIDOnTujSZMm6N27N6ZMmYI//vgDI0aMwKOPPqqcLaOiZLCeOHkLk4uoPMYnP6sMVjN7InEdVk+L/spYNNpnqQtmbUR81PEoZa3YCo0TMUbG7WbLhzmhTojEHMpgpSSJKLTG7WZ9rVRJ77YstVNEBWF9L0Wuu0rWIyuGyqn4KDsxlDLjsOyqxD7yxpK591lxiSrxsSp9RWJPZZYuZC0tKKOYqizJRpTw6KOPYsCAAdi/fz/atGnjqRYyadIkDB8+XNmudLZA/fr1TZes+OOPP1C/fn2pV66iLFu2DNnZ2cjOzkbt2rV99ulVVxo3bozFixdj3LhxSE5ORkhICK677josWbLEo5pduHABe/bsQWFhoaf/7NmzfRITbrnlFgDAvHnzkJaWBgB4//33MWzYMHTu3BlASWHhN954w9MnNDQUX3/9NQYNGoS2bdv6FBYmCIIgCMJ/6Jmqdm2UFWPGjEFMTAymTZvmqX9bq1YtjB07FsOGDVO2K12HLiQkBL/99huuuOIKn+0HDx5EkyZNcObMGWVnLndE1nL1hvXEKaKGydYW4vki8vQoYt9O7SoZxUx0HJG4KJFxnMg6c0qJlLl2RqxiZ2T6OO0bazwR31TiiozIxNDx+ljFwZqp7Vb3l0qmp4raZjam6Coz3vucuPdlfmdk7IjEQ7Kui4zaJvJdsBNvKfN7aaXEGfcHog5dvRdeREiUzTp0584h5/nRZV6H7vTp0wBKKnXYRVihe/rppwGUZHOOGTMGFSpU8OwrLi7Ghg0buEtsEQRBEARBEH/jxEROR1ih0+PQvvvuOyQnJ/usURoREYF69ephxIgRflv+63LATKFz8umLZ4dXz8uOYmZX7VAdTyRrT9YPM59UFAcR+1bjsMY0s8/LcmONI7KWr51ra+e68OwacXocFZ+cUpZUx/fGiWsmsl9EjVL1Rwans2hF1FY74/njnvnn9r/DoDYmhfr08YePAVHoJjik0I0pe4XOSYQVOj27tW/fvnjttdeC9oAJgiAIgrh0CLYYOn8hnRQxb948f/hBeFHcPglh3+0036egNPDqqXm2Myrts7aJ+mZVyd8bq+xDM1i1nVRs6djJNFWN9/KHoqGSqejZ36pNqX1OqEcyWZo6KveO0aaISmlmyyqWiXc8KjGaMsfB8tFo0y4qMW1OqPoycar+UB7N2rDaOh3bKpNBavVWYmOSf+JujfvLSvkm2CitibVp0yZ89NFHOHToEM6fP++z79NPP3XEMYIgCIIgCEuCaOmvCxcuoHPnznjrrbdw9dVXO2pbekK3aNEiPPzww+jcuTOWL1+Ozp07Y+/evcjPz8fdd9/tqHOXK94rRfCyqXRk6l6xnqaMSpdMDBXvCc3JSvFm58DqCVa3f7D/33EkiQ9s5/aRUQKM501VQWHVhRLxidVG5p6x8tW7rYqyIYLeVuYcsMYzHodMRqnduCsnFA0VVc8JpURkNQPR7Wbwzo2ooinSx46KaJYVLPI911Gpz8b7zbZCJX5UJa7X6rdC/5tWiuATHh6OHTt2cJcFVUVoLVdvXnrpJUyfPh1fffUVIiIi8Nprr2HXrl3o0aMH6tat67iDBEEQBEEQlwoPP/wwMjIyHLcrrdDt27cPt99+O4CStUjPnDkDl8uFp556CrfeeqtPkV5CjeL2SXCF+WbsqDyxycStGOOUZKqO854EZWLKWL55lBsbsVTeqpxoRixPQWM9SYs8DZv5bxUDKKOcsK4pzyfjfpZKxuvLi78UUVtkFDNjGyfUQ5E4NZFramVXJTbTTD0yrtThhFInkuUugtV3yqNimdxndo7DiVhDs99a1u8v77uscp/ZuSdZipnd2ENZZVbTLljadJpgS4o4f/485s6di+XLl6NVq1aoWLGiz/5XXnlFya70hK5atWqeQnhXXXUVduzYgebNm+PPP//0WYGBIAiCIAjC7wTRK1cA2LFjB66//noAwK+//uqzz86rWOkJ3c0334zly5ejefPm6NGjB5544gmsXLkSy5cvR4cOHZQdIf4mNGs7Qg0rRejsX5jk+f+EuaHm/W3EApn1FX3SFFFbjPDG0VUxXYlQeaLlnQs7sYBWtgDrWBqe4sFSJ/0F73rZiYfzxNVIXBcrm2bIXEtWG5F4K9Z4KrFaIsfOU49Er4vI74DI8aj4zfLRTvamDLxjN96bxv28sUV/38zgvdEw/maI/JazfLRzP/vEEWaatyHU0cvAOY30hO6NN97AuXPnAACjRo1CeHg4Vq9ejXvuuQdjxoxx3EGCIAiCIAgmDrxyLUuFTic7Oxv79u3DLbfcgujoaGiaVrYKXbVq1Tz/HxISgmeeeQbPPPOMsgOEHGaqnJXioBJzJhODItKf9QToHRNm7CMSx2cno5AVxyOitvGOw+i/SGyY1dO2nfguM2T6sJRSEYXWSVXPDqqZfjLXgWVHxQYvxswKme8YazvvHMicNxn1UNQ3nzhCQ9apzG+digIoqtjx7Nl5E2CG6G8Hr62Iglqulbkge+X6+++/o0ePHli1ahVcLhf27t2LxMRE9O/fH1WrVsW0adOU7Aov/eWN2+1GdnY2jh07Brfb7bPvlltuUXKEEFv6y+zHzIjMDxNrYW+RH1reKyTWD6zIj6hMiQBRVF4/O3U8IsHYTrzasZMQYOWrlV0rZF6JiiatiNgTKd1iROY4RZI7ROzamfyxxhW5F1UmNTLfTzuTJdY4Ir9NKr6IXEsr37z3iYZpmGHnuEReIVuNY2eCGoilvxKffwmhNpf+Kj53DvtfeK5M/H744Ydx7NgxzJ07F9dccw1+/PFHJCYmYtmyZXjqqaewc6f5wgJWSCt069evx4MPPoiDBw/COBd0uVwoLi5WcoQgCIIgCEKaIFPoli1bhqVLl6J27do+2//xj3/g4MGDynalJ3QDBw5Eq1at8PXXX6NmzZp+KY5HmCho/3v1wnt94lHvWomrEkaVT6WAMcsf722sp1EzxdGqPIlTrypZiATUW/U1Q+VViMi4eqJMwlxzX+wGbKtgpQSIvOLV73neuWG98tbbqhR3NbNj9TpQ5Fo68WqP14Z17VRea/IQSfJR+R5avfbj3ZMiqqgdhdnYlxcOIlPyiTWOyL0j+lsho2ia/f6L/A57/x2IwsLBVrbkzJkzqFChQqntJ06cQGRkpEkPMaQLC+/duxcvvfQSrrnmGlStWhVVqlTx+RAEQRAEQRDm3HLLLXjnnXc8f7tcLrjdbkyZMgUpKSnKdqUVuhtuuAHZ2dlo2LCh8qCEOCLFdI1tebBi5njjWSkAIk++rCdNkaBvYx+fZckyzdsaEQmk5gVyiypWvCdokXFkApx1jMqcjtlyYqIKo0hMGK+PKGb3mZ0SLTKB4TIqkh11TVThEBnH7DhYqrqIqqOru8bl8FTUNhmFXiWmlXc+Rb4noqqxU4qmTCylTFyfsY/K7wyrj0wimsg5J8yZMmUK2rdvj82bN+P8+fN45plnsHPnTvzxxx9Ys2aNsl3pCd3QoUMxfPhw5Ofno3nz5ggP962X1qJFC2VnCIIgCIIgpAiyGLomTZrgp59+wqxZsxAaGoozZ87gnnvuweDBg1GzZk1lu9JZriEhpd/SulwuT/0USopQR8/Yubl9OiK/s85yEVUNVLPCzPp7IxPfYSczTkUR/Of2kvtw3fB/WvotY1dU4eD18VYLdaziklRiAHVEzjUPFVWPtU/kPvBHJq7d+C4WTlwfb4z3pqdkjMSSb1btVFG5r6zOtcpvEy9ekXe+WOPw4oaN+0TUV9Zx8O59lRhg0RhNs2L0MueABWu8QGS5NhjlTJbrvollk+XqL6QVugMHDvjDD4IgCIIgCGmCLSkCAE6ePImMjAzs2rULLpcL11xzDfr27etT61cWpTp0hH8wq0PHg6V+sJ4mzfrqiDxxWvWRUVtUsvhkUFGeZNQDkSdaFaVJJZbGCp6iYTWuiC8yMU12+oj4IrvfCieUJjvn2o6PIm3tKE52z60TOKFG28kKtXPuRQiUfRkVuTwodA1HvoTQSJsKXdE5ZL9cNgrdd999h+7du6Ny5cpo1aoVAGDLli34888/8eWXX6Jdu3ZKdoUUui+//BK33XYbwsPD8eWXX3LbduvWTckRgiAIgiCIS53BgwejR48enhg6ACguLsagQYMwePBg7NixQ8mukEIXEhKC/Px8XHnllaYxdB5jFENnC2+FztXxRgB/P/0szf0RANCx9yOl+lmpR07Fqdjp40S8mtWY3m2diNWR8UUkjlDmqZe13V/qDssfVRuiSiAv+5hlXyT2SISyVpj8pWSLjuttR0apE1WYVTI/Zb4vKr45FadmNZ6IPSfUNu/vi/77zvu9N9pg7bOyIeo3ECCF7lmHFLpJZaPQRUdHY/v27WjUqJHP9j179iApKQlnz55Vsiuk0Hkv72Vc6osgCIIgCCJQBFsM3fXXX49du3aVmtDt2rULSUlJynalkyKIssH4NJRa69qS7bBWq4xxXd62rGpWWdWp827LU4/8nXFnZc+sBpsRmWM29rEaX7WP8ZzaURpFlDMn/JdRII2I3Gc8G1bHwztOFQVFJKvZaE/UV1Ws4jlFxmFdUzNklGdWH1U/je1UYgKN50slhk7kvrIT38c6HpHfKJXj4f2bwaI8xFAGEz/99JPn/4cNG4YnnngC2dnZuPHGkrdx69evx5tvvomXX35ZeQyhCd3rr78ubHDYsGHKzhAEQRAEQUgRBHXokpKSPCXedJ555plS7R588EH07NlTaQyhGLr69euLGXO5sH//fiVHCPMsV5VMPzsZSjxEY1xkbIjYF/HZyYxSsz5WbVXqOPH6q9TtM9bgUskOtXOOeYhk09lRHGXOl6hvdts6CU8FNyrMIqquinpkda+YxXcFCqfi4kRjznhj+zt+WCVeWea3VcdYP5N1jQMRQ3f1CGdi6H6d6r8YuoMHDwq3TUhIUBpDSKGj2nMEQRAEQRBqqE7SZKAYunKKjKJhpWh5r30aD/OnalZMnQgyT8F2FBqRODIRtVI0Lkbm6VjmSd3MrlXGmtl1KuUDJ15QxSdRG8btZvYP9i8GACRmlm4rap93n8mseWxE5tj9pfwZ+xjH48Vq1RI4p7Lje4/H8t+43Xt1BitfzL6fVgqzSKyuyHfX6vvvs1Y043fRuBKFyO8Y7ztnFdcnY4+l2Jr1Zdky28daA5tls0wJwCvXiRMn4tNPP8Xu3bsRHR2NNm3aYNKkSaUSHVgcPXoUa9aswbFjx0olm6qGrklP6O677z60atUKI0eO9Nk+ZcoUbNy4ER999JGSIwRBEARBENIEYEL33XffYfDgwWjdujUuXryI0aNHo3Pnzvjll19QsWJFbt958+Zh4MCBiIiIQPXq1eFyuTz7XC6X8oROeqWIK664AitXrkTz5s19tv/888/o2LEjfvvtNyVHCPkYOqsnJDvxd3aVCCfjO/yFTNydSjalVeaa2T6VWDAnVTbjflm7Ok6uDem0b3ZwMjvYrC0r41omY1lkzVCWT3ZiXEXassY1g6XyycQRmvVTeftg9SbD7n3ojzhFmXMg8+bE6jcqIDF0TzsUQ/eKegzd8ePHceWVV+K7777DLbfcwm1bp04dDBw4EKNGjeLW9pVFWqH766+/EBERUWp7eHg4Tp065YhTBEEQBEEQIjhZh844j4mMjERkZKRJD18KCgoAQGgt1sLCQvTq1cvRyRygoNC1bt0ad955J/7973/7bB87diwWL16MLVsC+B49yOEpdGbYedpy8mnbbFyVLErWuCzfvbdZZYla+SvrG8tXnhpiNb6ZHTtxKiqZkSK+GduIKLSiii1rbFXsxrF5Yv8E6s6Jji0SD2m1XbaNbJ+yUkFFrj/vOyFzvkR+EwDzGLqyVidlcEIllDkeKwKh0DV60hmFbs+rz5Xanp6ejrFjx3L7apqG7t274+TJk/jhhx8sx3rmmWdQrVq1UqFrdpFW6MaMGYN7770X+/btw6233goAyMzMxMKFCyl+jiAIgiCIoOXw4cM+E1ERdW7IkCH46aefsHr1aqExJk6ciDvuuANLlixB8+bNER4e7rP/lVdekXP6f0grdADw9ddf46WXXsL27dsRHR2NFi1aID09He3atVNygijBTKHj4Q8VTKesYpNklACVp0g7Wa6qvvDGFrUvMo7T6p1oW5HMaBk1V9SnsoqtFFlfVgWn/bdSjeyoLnbjR3n2RNs6ec4BuRVhWL6IvK2wE48s6odT9nRYKjJgnUFeHmLoGj3hkEL3mnwM3dChQ/H555/j+++/F67ZO2HCBKSnp6NRo0aIj48vlRSxcuVKaf8BxbIlt99+O26//XalAQmCIAiCIJwiEGu5apqGoUOH4rPPPkNWVpbwZA4oUeD+85//IC0tTW5QC5QUuj///BMff/wx9u/fjxEjRqBatWrYunUr4uPjcdVVVznq4OWEiEInEz8io06JZFdaxYTxYk+sfDbDKovPexyjPZmMUpkafE7ExYhkgIrEulllNToVF6OSfWrEyXhF3phlnfVqhhPZuk7Ec7Js2+0jc2/KjCt6DlRVMSczfK1sm+HEbx/PJ9FYZ944LF/NYPkWCIWu8TBnFLrdr4srdIMGDcKCBQvwxRdf+NSeq1KlCqKjo7l9a9SogR9++AH/+Mc/bPlsRHpC99NPP6Fjx46oUqUKcnJysGfPHiQmJmLMmDE4ePAg3nnnHUcdBICcnBxMmDABK1euRH5+PmrVqoWHHnoIo0eP9sm43bRpE0aOHIktW7bA5XKhdevWmDx5MpKSkpi258yZgwULFmDr1q04ffo0Tp48iapVq0qP7S2Z6syaNQsDBw4UPk67S38ZsfMPucwrFxE7Rhtmrz/88UqNt5i6E6+BeDZUlu9iYecH1u4/tKKvqkReuao8bKggM2l2KgnGqq2OUw8bKq+1WT7J9DXa4CUgOFFaQ2SColLuxeirWbKEyutm0VffMr+xvEQaFrxraDxm3nc8GJIiGg91aEI3Q3xCZ/ZvPlBSY85KeZs4cSLy8vLw+uuvq7jKRPqV69NPP420tDRMnjwZMTExnu233XYbHnzwQUed09m9ezfcbjfeeustNGzYEDt27MCjjz6KM2fOYOrUqQCA06dPIzU1Fd27d8fMmTNx8eJFpKenIzU1FUeOHCkVdKhTWFiILl26oEuXLhg1apTS2Drz5s1Dly5dPH9XqVLFwbNAEARBEISRQL1yVWXjxo1YuXIlvvrqKzRt2rTU/OTTTz9Vsiut0FWpUgVbt25FgwYNEBMTgx9//BGJiYk4ePAgGjVqhHPnzik5IsuUKVMwa9Ys7N+/HwCwefNmtG7dGocOHUKdOnUAlBQ7btGiBbKzs9GgQQOuvaysLKSkpJRS6ETGBkpm65999hnuuusu5WMSeeXKe93oL1WirPoY++o4oaDYfb0lE3BuxycVJUDUBs8nlg2eHX8djxOvtcsap45dpZyMmQ9mfphhpQha9bfyyQp/vXaWGdvfCq2xj47IGxSVAt1GW3rpHcC6/I6Ioml17IFQ6K4Z4oxCt+sN9cLCMvTt25e7f968eUp2pRW6qKgo0wLCe/bswRVXXKHkhAoFBQU+BfwaNWqEuLg4ZGRk4LnnnkNxcTEyMjLQtGlTxxfFNY6tM2TIEPTv3x/169dHv379MGDAAG7hwKKiIhQV/S3zU2FmgiAIgpAkAEt/2UF1wmaF9ISue/fuGD9+PD788EMAJcrUoUOHMHLkSNx7772OO2jGvn37MGPGDEybNs2zLSYmBllZWejevTsmTJgAALj66quxdOlShIUpJfMKjw2UpCF36NAB0dHRyMzMxPDhw3HixAk8//zzTFsTJ07EuHHjhMbVn4rMFsDWn5RYT3FOBSvLPJXaeapWCTy2o5yJjGfHPssuT22Tib+TOV+isW0qMUFmfqjEaqosf8by1V99jIgcO28cz3c407ctzz7r++BR+TJ9/wbYvxH6uTZThEQVU5W4SBWVSiS+0+ml52TuEdbYxvNoVh7HiIz/3va8baoUxVb5vQkoQTah8xfS605MnTrVs2bZ2bNn0a5dOzRs2BAxMTF48cUXpWyNHTsWLpeL+9m8ebNPn9zcXHTp0gX3338/+vfv79l+9uxZPPLII2jbti3Wr1+PNWvWoGnTpujatSvOnj0re5imsMYGgOeffx7JyclISkrC8OHDMX78eEyZMoVrb9SoUSgoKPB8Dh8+7IifBEEQBEGUT+rXr4/ExETmRxWlsiUAsHLlSmzduhVutxvXX389OnbsKG3jxIkTOHHiBLdNvXr1EBVV8m48NzcXKSkpuOGGGzB//nyf15n6q9a8vDzP9vPnzyM2NhYZGRno1asXdxyrGDre2GasWbMGN910E/Lz8xEfH89tqyNbWNjjG2PZK145AV72pxGr+B6VJzaZmB07sWEiMUfJ0zYCADYmhZqOb4aKKsZDtCyCSiauCjIZq7w+MuMYEcl29Ne9IYoTMUdO+yZzr+jfaRk11IkYTbt2rcbREVEn7Xy3ZJRAnvLM+81mIaN+s/o6mRmvE4gYuiaDnImh+2Vm2cTQvfbaaz5/X7hwAdu2bcOSJUvwf//3f8pLgim/i7z11ls9S3+pEhcXh7i4OKG2R48eRUpKClq2bIl58+aVmlAVFhYiJCTEJ5VY/9vtdtvy02psM7Zt24aoqCjLBAuCIAiCIGwQZK9cn3jiCdPtb775Zqm3kjJIKXRutxvz58/Hp59+ipycHLhcLtSvXx/33XcfevfuzazLYpfc3Fy0a9cOdevWxTvvvIPQ0FDPvho1agAoKS+SlJSERx55BEOHDoXb7cbLL7+MxYsXY9euXahZsyaOHj2KDh064J133sE///lPAEB+fj7y8/OxefNmPProo/j+++8RExODunXrolq1akJjL168GPn5+UhOTkZ0dDRWrVqF4cOHIy0trdRMnEcgCwuzbADiBXhVMhZF4khEsvWs6lCpxIT5G178mMgTv8o5Fomz9O4rMr5TNaxEVUozP2X6lnXmtZ14OJnYRiN2MiTtIno8vH16dqb+FkEk9tRoS8RHJ2IBZe4vp+M87cSciowj629AFLrHHVLoZpWNQsdi//79SEpKUk6QFFboNE1Dt27d8M033+Daa69F8+bNoWkadu3ahbS0NHz66af4/PPPlZywYtmyZcjOzkZ2djZq165dyi8AaNy4MRYvXoxx48YhOTkZISEhuO6667BkyRLUrFkTQImsuWfPHhQWFnr6z5492ycx4ZZbbgHwd3FAkbHDw8Mxc+ZMPP3003C73UhMTMT48eMxePBg508GQRAEQRAeAlGHzh98/PHHphU0RBFW6ObNm4cnnngCX3zxBVJSUnz2rVy5EnfddRfeeOMNPPzww8rOXO6oxtA5GXejw3sSdGJxazP8GXsk8gStEktjp493fA+rYrsTypDM07aMoqnik45ZdX6RmDnV8byxE6NZVqqXlY/e24y+GZVuFXVa5U0Ab+k/mWvpZCxdWX2XeedYj1eO2l4BQNll3gYqrjQQCl3Tx5xR6Ha+VTYK3XXXXefzRlPTNOTn5+P48eOYOXMmBgwYoGRXWKFbuHAhnnvuuVKTOaAknm7kyJF4//33aUJHEARBEATBwLgAQUhICK644gq0b98ejRs3VrYrPKH76aefMHnyZOb+2267zfF1yQg+vDUIvZGJ7+Dt94cqIfLkqRKrJ6IIGtvyVArRDF8RZUPH7HzGQ12NYt0PMlmhIkqQMTNSVyAS5oYy+xjh3UtOxjLKZKGK2BGJ0RS1xetjPMciShBPmWNt86hqrayzzlnfEx2Z3weR+8yIjDoqEqsn8hthHJP5XQD7O5b4gPibB9a5Nutjdb7MfBPtazeTPCCUg1emoqSnp/vFrvCE7o8//uCW34iPj8fJkycdcYogCIIgCEKESyWGzi7CE7ri4mLuiguhoaG4ePGiI04RYjihFrCQySiVGZf3VGzcJqOCWSlOPF9Y43tjVR9K5ByIHIdKHCFLPeK1ZW0XuYZGJciYhSgyvkxcjw5P1VG5/jJtjD7xVB4rZVlkPBUVSuXescos97ZjFZ8mcj/buR5GtVLEF7vX3+rth9l1sqoKwLtnWNdURHE0jqOyLi/vvJVbZS6IMJZWM8PlcinPpaSyXNPS0hAZGWm633tNUoIgCIIgiDIhSOrQffbZZ8x9a9euxYwZM6C41gMAiSzXvn37Chn016KzlwOyWa7G7DLRGmNA6actszgoVlsncCrb1U7WpnE8Y1uz+m0yKoXM8fhDXXVaBVOxL4OIIssa1+lsYDv2RWNAZZRGJ66pSB9j7J53f5nVZYzY6WvEbnyXyPUwYnZerMZz4rfCyqZZXzvZ2ryMZVECkeXavP9LCI2wmeV6/hx+nlv2deh2796NUaNGYfHixfjXv/6FCRMmoG7dukq2hBU6mqgRBEEQBEHYJzc3F+np6fjvf/+L1NRUbN++Hc2aNbNlU3ktV8J5VOvQ6TihNOj79SrtALtSu0hGqb+zqZyoc+VE3SuVrD1ROyxbooqWmR2VFSlYvsiorSrIZDmz+or0EWnLOlaeAmzWxthO9Dw5nX0ocw95qzYA/94p6++lSPwma2yZ300Z35xQsmXeTqj8HvtDbQ+IQtfPIYUuw/8KXUFBAV566SXMmDEDSUlJmDRpEm6++WZHbCuv5UoQBEEQBBFogiXLdfLkyZg0aRJq1KiBhQsXonv37o7apwndJYTIk1ophSYTpn0SM9njqGR0GvtatfP2kRe3IhqnxOvjRMyeSlycjELDU0z0OlMiWZTGDDiVGDrv2EJvWyL+8869VVaoiuJgN1vP+H1hrZcpEnPIsyGq6vFgxYCK1PwTyW7UfytUYF1Dp+IIRc6T5/wzaj2K3JOivoog8h0Tyey180aDtV1k/WdCnpEjRyI6OhoNGzbEf//7X/z3v/81bffpp58q2acJHUEQBEEQwUuQZLk+/PDDlmVL7EATuksA49OVJ+v1f0/UZk+crKcu3lO9TByRlT2eEmRUBIzj8Z4eVdQXnVJZw16KhMxxGGE9FXv/zbLPyq4za6sSU2fmi9nfZuPKxC1ZjWc1Jms/S5GzE3tkhpUyxxtHx4nVMWRiAVVWbhAZR+Q+Yx2PyHHK9LWTFWzcZ/a9Z2EndlbknrFz7UT94PkWdKpckEzo5s+f71f7IX61ThAEQRAEQfgdUuguQXhrebKwUsW827BidMyeUq0ULZEYKpaPInZl4q949q0qxqs8qYsojUZfVFQxGZVCRtnirRVptC+ifjiR5agSrygTRyZzf7HGM/OJNQ6vxqTVtVOJ71KJOTXDKn5PJU7VuN+sDa+vlepk9h1nXV+WugeYvxmx8o0Fr4/oihQqqGRgB5JgSYrwNzShIwiCIAgieAmSV67+hiZ0lzBmWaKsp22R7EAjvPg1J+yzkMnAElHmjG1l4rtEjotll7fWokgcnEr8mNU4MmqeTHaryComKrFHxmMWOS6rNjKZlzz7rL9l7hURxZz1N09BVVHdrNQqbxu638YVIkSyKe3EfqnEj+rY+U3iKfj+ijlkKXOs8Xl2g0GFI6yhCd0lAOvLKDNhEPkhFH3FY7ZN5DUtaxyjLbMfT54vRpsiPhiRKcRr9Inlo+g+b3ivXvTz4nn904o9oXfiWoogM3m2mhzzfLO6f53+B0vklShrbJUHBydeO5shkwigMq5xqS/jNVQpTsz7LvOQeZ1t1Vfmesig8rBp516/VCZyLk2Dy+YaCXb7lwdoQkcQBEEQRPBCr1wB0NJf5Qq7S3+JYCcwV0cmyFvH+DQs8yqUN47KazrRc6Dio4hvRoUAEFcL/aXUGH0yU/WMOLl8mEhfEfVQxT5rHNY2sz5m2Lm/7LymM7a1owjz7PL8cOJ3xghPUVNR3UTGFX2Fy3vlLnLvOJXAYOWblQ0nFLtALP2V9NCLjiz9tf290WXit78ghY4gCIIgiKCFslxLoAndJYz+1HWwf7FnW8JcsT7esFQQmUQHVmkLmUQKFXhxSlYqCG9cVhyeTPA9r/yKHUSSIVh9jMuI8Wzwjp1l37jknIyPMrFnMoqdiF0reyKxTca2IudLdLv3eDz7rPvWqMzKxDY6Dev7ea5/kmUfXgkdloqnEnOmEgfJU7RFlWARXy+VuDgp6JUrACosTBAEQRAEEfRQDF05wukYurKOoVGJCRLxSSZj1bhdRHFg2VLJ9LWLnWxaER9E7evlJgB2yQmWbRH7Orw4ItZ19x6HtSSXyJiseCvecfgre1Y0I1JE0eb5ZnWPy2RRysQ2smJoVWJbZXwz22dlQ6SPjA2WLZVMcpnvC88Hp3+3vAlEDN31DzgTQ7d1IcXQEQRBEARBBAZ65QqAFLpyhb+yXEWyAnn7najBZDWumV0nxmPt5/lkJwZN5AlaRDF1MpPQW3HSYSklKufc6Qw90XuUZ8cpJcIJuyrX0kpFBqxjGGViQY21HWW+AzL3Ps++k3FkMqi8PXDymtr1kVWHUkW9doKAKHS9HFLoFpFCRxAEQRAEERAoy7UEmtBdpqg8BZfKVPyfQmAWl2WlFjitVhn3GW1413zjLdPDQtQHGd94+1htRWpX8WLE9H3+yCg2881KAVI9X8Yxra6HSoyT2TbRWDeeb2bbra6DMbNYxEcR5Uwk1tEq7tLsnLAyYz0KYyv2bwZrPKffHrDuQZn7TeTYrWzxfOAptPp3yqjUGv9WfWsQVNArVwCU5UoQBEEQBBH0kEJ3mSGqaMhgVOq8tznxBKgS02ZEZa1NER9EnthFzjXrPNlR0MwyGWUUKyMsZYNnyxjHw1McjT6KINrW7FyroJIpKWrDzB5vhRXRe0PkPhO5hjL+s+zy4rp4KqT3fhEllYeVSiXyeyOj1JmtvmJln+UDT23X4WX4Gwl6Zc6LS+GVqV1oQkcQBEEQRPCiaSUfuzaCHJrQXQbYzcAy7mM9aYrE9xi3m9U7U4k9YT058/qw7DqdhWZHEeL1tZOhKBqz5b3P6ryIKCc8Gx41KpM7jCky2cfGfcbVK0QysUXUIqt70sx/q9hDnk8iiMZQ8RQnoy3e+WKpU7w4QqvxZBBRNGVUcFZMm5ly5vm9hPhvrYovrPGIyw+a0BEEQRAEEbRQlmsJVIeuHOGvOnTeqNSsEu0jo4JZtZPFTpYba7/3Gri6eihqW8QXlXgokT524vqsxgTYKyyY9bFzDoyYqT1WiondGE4r5U+kr8h1EVVMZeLhZK4/73uposxZjSPzm2FEpY93P5FVK1h97XxveBmrKvcrK1Yu0JmrgahD1+reFxAWbq8O3cUL57D5k+eDug4dZbkSBEEQBEEEOfTK9TJDJrvNiFU2mErsFs8XlXgVXlujXavM0kSvWC47yiYLkZgzFeVUBZ4tozLGiusSUdtE7hnW8RhjkczGZtUuM2vLUmq8axayai3yzpdo3TbedTPakFG0VOKuZFQ3EZVdNKaRpwTy7Bv7yPyusa63WewZ67dORNG0+i6L/DbxtrPWGebFYQZKtfM3LnfJx66NYIcmdARBEARBBC9UWBgATeguO4xPcVZZaN7YebqTUfNY+0Sq2qu0FYH11KuihoggkuWoYl9F1bE6VpmsUDvxfTLnmtfXo5D8T4E1qmFmWbYiqxYY27KUQB1eJjErU5GnCMpkO8soWqL3mdkqBiylSSXuVub7I6IaGu8DmVg63jhWKqiZLavfR5V4Rad/A4nyD03oCIIgCIIIWijLtYSgmNDl5ORgwoQJWLlyJfLz81GrVi089NBDGD16NCIiIjztNm3ahJEjR2LLli1wuVxo3bo1Jk+ejKSkJKbtOXPmYMGCBdi6dStOnz6NkydPomrVqj5t6tWrh4MHD/pse/bZZ/Hyyy97/j506BAGDx6MlStXIjo6Gg8++CCmTp3q4195wPgUJ1Pnyir2SKaPjkwMXyCxyigzOz6VuCvj+ozGGmlmsJ7unYqHslJGzMYrFZ/EUPlksvnMFAdRdYqnhsgoGSyFmxfXabx2djImzWK1rFbjEEFGlWL5L6Mmi2CVJazaltVHBDvnmGVLxheZPoHOdi1TqLAwgCDJct29ezfcbjfeeust7Ny5E9OnT8fs2bPx3HPPedqcPn0aqampqFu3LjZs2IDVq1ejcuXKSE1NxYULF5i2CwsL0aVLFx9bZowfPx55eXmez/PPP+/ZV1xcjNtvvx1nzpzB6tWrsWjRInzyyScYPny4/YMnCIIgCIKwIGjr0E2ZMgWzZs3C/v37AQCbN29G69atcejQIdSpUwcA8PPPP6NFixbIzs5GgwYNuPaysrKQkpLCVOiefPJJPPnkk6Z9v/32W9xxxx04fPgwatWqBQBYtGgR0tLScOzYMWZNm6KiIhQV/f1Ue+rUKdSpU8evdeiMiGSJycQnsZCJPZOpxWblAy9z0QqRuCI7+LumnFlbo6LEUr9Ua31Z+cCrYeekyuKUCiY7nvc+0WxXb2SyKVWwup/K6nspghNZr7z72Ik6ejKZ9yJcCqpaIOrQ3XDnBEfq0G1YPCao69AFxStXMwoKClCtWjXP340aNUJcXBwyMjLw3HPPobi4GBkZGWjatCkSEhJsjzdp0iRMmDABderUwf3334//+7//87xOXbduHZo1a+aZzAFAamoqioqKsGXLFqSkpJjanDhxIsaNG2fbNzvI/ENo9Q+tyGst3o+o6KsdEZ+MtsxeB6mU1JDByn+nXwcZ+5qNowfbs8p8qIwjE3zPW5ZINDDce7txuTCR19wsv0UmATKTTdY9zwqSN4OVVCLS38xHq+8Lb1Im+tBh5gNrfO8HLdYrW95xWj0oml13ll2Re0Xkdb2TEzmR+8zqweGygLJcAQTJK1cj+/btw4wZMzBw4EDPtpiYGGRlZeG9995DdHQ0KlWqhKVLl+Kbb75BWJi9eesTTzyBRYsWYdWqVRgyZAheffVVDBo0yLM/Pz8f8fHxPn1iY2MRERGB/Px8pt1Ro0ahoKDA8zl8+LAtPwmCIAiCuDwJqEI3duxYS4Vq06ZNaNWqlefv3NxcdOnSBffffz/69+/v2X727Fk88sgjaNu2LRYuXIji4mJMnToVXbt2xaZNmxAdHa3s51NPPeX5/xYtWiA2Nhb33XcfJk2ahOrVqwMAXC5XqX6applu14mMjERkZCRzf3nDjuIkYsuOIqairjnxektE0RRpK6J6suzLBGiLHrO/1EnR15EitoDS5TFESndYKUsq9w7P31LHnGndx0oZ4iHy2lFGbWe+Ns/0tcmDNZ73uVBRqWSKN7O+LzLfYVYfuyEKKq/AdawKDF8OUJZrCQGd0A0ZMgS9evXitqlXr57n/3Nzc5GSkoLk5GTMmTPHp92CBQuQk5ODdevWISQkxLMtNjYWX3zxheU4Mtx4440AgOzsbFSvXh01atTAhg0bfNqcPHkSFy5cKKXcEQRBEAThIJTlCiDAE7q4uDjExcUJtT169ChSUlLQsmVLzJs3zzNp0yksLERISIiPIqb/7XY7u6bHtm3bAAA1a9YEACQnJ+PFF19EXl6eZ9uyZcsQGRmJli3tp7cHGtEnZ5EgfycC3M1iXKwW3BZ5glZRvKx85+2zG7DNwmhLZBFwYwwVL/bIOI6IGsJLhrBzPKJFj1XVVlZ/Y+yWdyyYxzdDvCAvrk8lflBUYRSJbeNtLxU3lmneVkWp88ao/LHg+ei0ciZaFsfu2wmjHREV8XJU4gg+QRFDl5ubi/bt26NOnTqYOnUqjh8/jvz8fJ/4tE6dOuHkyZMYPHgwdu3ahZ07d6Jv374ICwvzJCUcPXoUjRs3xsaNGz398vPzsX37dmRnZwMoyYzdvn07/vjjDwAlCQ/Tp0/H9u3bceDAAXz44Yd47LHH0K1bN9StWxcA0LlzZzRp0gS9e/fGtm3bkJmZiREjRuDRRx8N2mwZgiAIgggG9Feudj/BTlCULZk/fz769u1rus/b/eXLl2PcuHHYsWMHQkJCcN111+HFF1/0vCLNyclB/fr1sWrVKrRv3x4AO45v3rx5SEtLw9atWzFo0CDs3r0bRUVFSEhIQK9evfDMM8+gQoUKnvaHDh3CoEGDShUWlomR01Owy7JsCQu7JRXK+unRH2UqVJQAGSXIzC6rjVPn0UrRlBlPRH2zamOmoFhlLoqoLnbuTRHl1M71UCmX4RRWWae88a2O3Uw5ZY0jc3z7FyYBAKK2VzC1LWuPhT9+Q2SRKe9UXglE2ZLkLuMdKVuybsm/qWyJv0lLS0NaWpplu06dOqFTp07M/fXq1YNx/jp27FiMHTuW2ef666/H+vXrLceuW7cuvvrqK8t2BEEQBEEQThMUEzqi7DFTNGRUHNEnS/3pG/j7CdxOnJXME7NVGxmVQib+TuapW+S4VOpQGduqLOem/82rLWccz+irSuaiCKwCyoD1wvE8nFDmVFRcmRhE3nkyLsUmg5XfPOVMRNFmtUl8wPo7wLqWMvGWInF3IvegHXXd+P1zOibwUoWyXEugCR1BEARBEMGLWyv52LUR5NCEjrDEiQxCFglzQ73+klcNWIj4ZpW9KdJWZjwRmzKKgL7PToV4lrrn7YexfpqdDD9eDJ0Ro8piph6y1BCjCme33p0MKvXtrGKneLXrjPDuIavVGERq5Rn7yGRGs/qKIPJGwGiPd91Zx8M7DpHvp9X9I5MRz8s+JwgjNKEjCIIgCCJ4oaW/ANCEjlBAptK6VRvV+mAsX1h2zWJPrGo+edcWk6lIL9pGJhZIRs2TeYrXFRueQiQabyUTd2fcz2vDUw9FfDBut6pZaNbP6jhElFSeDdY5FomhsrJvprayxuOteWwVZ2lW79Doq9GmCLxzYLQv8r33R+ykTGybnd8xsz6k2hE6NKEjCIIgCCJoccGBpAhHPAksQVGH7nKhPNWh88bOk6CVeiBT88sJP7yxE++mojjIqAcyx6xyXlixcyq198wQ9UVG2RDJjLTaLtJG5BzwfHZCORGpR2altskomXaVclmcUpytMrztripiJ2NV5f66FAhEHbq2HcYiLMxmHbqL57Amc2xQ16ELipUiCIIgCIIgCDb0ypWwxI7aohIzJ7p+onFMnn3veDijXTvKk9PZtDpG5YGnRKg83Rtj54x14XyUDcjHP1qpEyJ11XixYEZUFEeRa2kV0ygTfyeDUU3yvh46Vpm7IveMTCyblX2Z+m0yiiOvr9U58LZldcwiWbRGn2Qyb0XuYx2V2pKXM4GoQ/f9999jypQp2LJlC/Ly8vDZZ5/hrrvusueETUihIwiCIAgieNEc+khw5swZXHvttXjjjTccOQQnoBi6ckR5jaFjYSe+xMyGTGyLlT2RGlkqsTROKHROqTkydcFYyCiBrPHtxPeJZCF6q6ss3/wVEyZqV0TVNY7HywplqV8q96RIrKbK8TiBSiydUzFoKuumyijMVjZErmUwKnWBiKG7KcWZGLrVq9Ri6FwuV7lQ6OiVK0EQBEEQQYtL0+CyqU3p/U+dOuWzPTIyEpGRkWZdyh2k0JUjgk2hcxonM8p4T/Uydcj86asZMtmzdupqlccMPNFYRpXjM1PD7Ki5KhmYvOtkRzU22lOJUzRiVoPRTga20Uez/Spxd06o1OXpTYMTvgSaQCh0N9+S7ohC98P340ptT09Px9ixY7l9SaEjCIIgCIIoRxw+fNhnIhos6hxAEzrCAVRqsKm0MYsnYT31Gv/mrfqg8lTP6itiV+WpWyYDVyQ2yErdU8l+lFEpzNp5FKVMc194MWEs+/rf3tecFZekj69n9Zr5JJJNq/tkZ7UEketipTTz1mNlXR9eX5XviROZpXpfs3NvdRy8OEWRcyx6zCJqqxO/gYQ5Tr5yrVy5ctDWoaMJHUEQBEEQwQut5QqAYujKFZdyDJ1MpppK3JIT2WAy9eh0jEqASAamRwkyqZHF8oXnL8snEexk4MrUFnMiS0/Glkpb3pq1KsduREZpNLJ/YRIAIGFuaKk+KhmrMlmaMrGArLFV7m8R/B1z5pSf5XU8fxCIGLpbbvq3IzF0368eL+z3X3/9hezsbADAddddh1deeQUpKSmoVq0a6tata8sXVWhCV44I9gmdSkC9zD9qdnxyyjbrHxDepEAl0YGFyFJGTkzSRILvWTZ5bVg2ReyLYCzAKzLBNo6r8spNBF6ihtW1tBOo791XdKIr8lpbZCLnRAKSiJ9OJSVZ2ZIJRRB9QAXslUEpbwRkQtd2jDMTujUThP3OyspCSkpKqe19+vTB/PnzbfmiCr1yJQiCIAgiaAnEShHt27dHedPDaEJHOIbMqxenimtaPf0mT9sIANiYFAojrL76663EB7aX6sMaR6Q4KU9NYAXzG8+X2TlgnR+VV3ssf8z62ikNIeKPiLJhPEaZIrEsH8wULd2undfyRszUXCfOqfGVvnc70QLGMuOZYUyukCmTw1KrzGyoKHNWyTa874uIOu1JwGrFV0O9bZkloRCELDShIwiCIAgieNG0ko9dG0EOTeiIMkFG0ZApjGr1hG6mzLH66uMmPmAjKYLzpC2jNMnEblmVx+CVLRHZbqUE8Y5ZRpmxik/kqZMyyhxLkTG7R61iv0TKY4jErclcD6t9etkVkXPBSgSRGVclwcnMFk+FNrMpM46ZvyLfE1G7Pvtb8ZNsgnE5r/KOy13ysWsj2AkJtAMEQRAEQRCEPUihI8oUmSd/7wKvgNxTOE89slLBzDJWrcYUie+zU/BXJvtUJgtRRm0xYlQgeL7ZKUbLU8ms1Cje8ciohlZteSVPRGKorMaViV9zGhWViuWvnexmkb48X0XvEbMYPStVjZexbPSJd68QitArVwA0oSMIgiAIIpihwsIAqA5duSLY69CJIKI8WD1J85bxcsI3nYP9iz3/r2e8surNmR2PMQbQrDgsCyfqdDld80vm2I3YqaMmYoulhoosTC9zL8qonywbvCXsWH1ExhHB6rulkhntVL070fECgUxsq0yNx0uRQNSha996tCN16LI2vVgmfvsLUugIgiAIgghanFzLNZihCR1RpvAyy0Tjrnj1u4x2RZ6K/64759sm0ST+jpXBaIz3M2urK3MiKoixFp5I3T4RlUcli9ZY441nn7VPpg6h0YZKHUJWO5G2Vv2tEI23VFk4Xr8vgNLZ2HaOS+R7KbPqg4pyLnrP8BR6O28AZHxTyT6+1JW5gEIxdAAoy5UgCIIgCCLooRi6csTlEEMnghOxJiqxTiwFwmyflS3vse3UnZKphefvGB07qxiIxBOxVi3wVmS898v4xlPoROKhjH1V1FCnsROrxWpjZ1UWb1QyVmXOrZVdkfqAVn1Z2wg+gYihS7l+FMJCbcbQFZ/Dqq0TKYaOIAiCIAgiEFAMXQk0oSMCiplyYueJ3Ij3E7oOKxbMWLPO26ZxTUojZuqCVR01mYr3MvXb/IWVjypxat59WPW5ePFlVjXljOuamsE7LqsMXpUsRzN46rCVHyoqEss3O6uyyJwLlftZJrNUJcvZuN17HyuOkFZ9IMoTNKEjCIIgCCJ40eBAUoQjngQUmtARAcVuxiFLXfFUZeesJMDKquX5KVpt3qytjEohkxUqWltMtY0RVlvvWDfWeecpZ8a2njYmGcRGe6y+KgqNN6y4Pp4NFbVVP0Yrn+zGd7HOv0z2sQ5P/fRHHKxM5irrevF8ErFvVOr1Y7ebRU3YhLJcAVCWK0EQBEEQRNBDCh1R7hHJelPJ9LNSTlRqj3n3sRNfIxNjVFZZwVZtZY7TbD1bo12Z2EOjDZUVIszsG+3InHOr+DunskNZShbPJ6OCKnOOdVhrLZv1EVnH2KqGnMz3keUHbx/Pvp3MW6IMcANwOWAjyKEJHUEQBEEQQQtluZYQFBO6nJwcTJgwAStXrkR+fj5q1aqFhx56CKNHj0ZERISn3aZNmzBy5Ehs2bIFLpcLrVu3xuTJk5GUlMS0PWfOHCxYsABbt27F6dOncfLkSVStWtWzPysrCykpKaZ9N27ciNatWwMAXK7SjwezZs3CwIED1Q6a8CCShWbMZhVRaFjj2Ik98/6bF/sF+PrMUy7MxhWBp7bIqIfGtjJxhMZxZeKgZFYxYNkXUXOduO6842Eds7cNzzk2xGixYgMB9j0jooYZ4xNlYuhkzrXMfWalFvLuZyfiRe36TxCBJihi6Hbv3g2324233noLO3fuxPTp0zF79mw899xznjanT59Gamoq6tatiw0bNmD16tWoXLkyUlNTceHCBabtwsJCdOnSxceWN23atEFeXp7Pp3///qhXrx5atWrl03bevHk+7fr06ePMCSAIgiAIwhw9KcLuJ8gJ2pUipkyZglmzZmH//v0AgM2bN6N169Y4dOgQ6tSpAwD4+eef0aJFC2RnZ6NBgwZce7oSZ1TojFy4cAG1a9fGkCFDMGbMGM92l8uFzz77DHfddZfyMdFKEWLYrXcm+lRvprqwsidl4qHstJWJPRJRw1hqjkicmkx2qAxWKqTKOeDZt4p1Y9kBxI5T5hyrKIAyiMZKipwLmftMxQ87Wbx21DYRFZxi6NgEYqWIDk1GICw00roDh4vFRcj8ZWpQrxQRFAqdGQUFBahWrZrn70aNGiEuLg4ZGRk4f/48zp49i4yMDDRt2hQJCQmOjfvll1/ixIkTSEtLK7VvyJAhiIuLQ+vWrTF79my43fwoy6KiIpw6dcrnQxAEQRAEIUtQxNAZ2bdvH2bMmIFp06Z5tsXExCArKwvdu3fHhAkTAABXX301li5dirAw5w4zIyMDqampHhVQZ8KECejQoQOio6ORmZmJ4cOH48SJE3j++eeZtiZOnIhx48Y55tvlglNPx1Z2ePXCWG29n+6t1DVeLBjrb5G1KUXqnhlt8Hy1UkrMlA+Wgqnb2L8wCQCQMDdU2G+RDE/WigG8encisFQb3goUIhm3RmRqpFndXyo18sxsWcUyml1/lYxUKwVNpdajiB0ns8WJAEF16AAEWKEbO3YsXC4X97N582afPrm5uejSpQvuv/9+9O/f37P97NmzeOSRR9C2bVusX78ea9asQdOmTdG1a1ecPXvWEX+PHDmCpUuXol+/fqX2Pf/880hOTkZSUhKGDx+O8ePHY8qUKVx7o0aNQkFBgedz+PBhR/wkCIIgiMsGt0OfICegCt2QIUPQq1cvbpt69ep5/j83NxcpKSlITk7GnDlzfNotWLAAOTk5WLduHUJCQjzbYmNj8cUXX1iOI8K8efNQvXp1dOvWzbLtjTfeiFOnTuG3335DfHy8aZvIyEhERtp770+UIBNDJWtL1Z5KW6vjMK436w1rVQPvzEhWbTc7vqpUy098YDtzHysDUyZjVUdFHROJneSpSaL3isz9JRITKBJv6UTWpnEcM5VS9H72xqrmn4xvZn2t6hqKxGYSRHkmoBO6uLg4xMXFCbU9evQoUlJS0LJlS8ybN88zadMpLCxESEiIT/kQ/W+rWDYRNE3DvHnz8PDDDyM83DphYdu2bYiKiuImWBDOYfXjzCvDYNbGap9VKQeztvo+zwSrlXXZEjv/kIhMAo2ITAJZvvm8DrYYU+QfdpV/yI2+2Q2+17cZX7WzJgf+womHA8D6daZIUoxMORGWfeN2nl2ZiZ3IcnEyk2aayAUHVIeuhKBIisjNzUX79u1Rp04dTJ06FcePH0d+fj7y8/M9bTp16oSTJ09i8ODB2LVrF3bu3Im+ffsiLCzMU0fu6NGjaNy4MTZu3Ojpl5+fj+3btyM7OxtASWbs9u3b8ccff/j4sHLlShw4cMD0devixYvx9ttvY8eOHdi3bx/mzp2L0aNHY8CAAaTAEQRBEIQ/obIlAIIkKWLZsmXIzs5GdnY2ateu7bNPr7rSuHFjLF68GOPGjUNycjJCQkJw3XXXYcmSJahZsyaAkpIje/bsQWFhoaf/7NmzfRITbrnlFgAlr1e9M1kzMjLQpk0bXHPNNaX8Cw8Px8yZM/H000/D7XYjMTER48ePx+DBgx07B4QcMuoBq49ZAoJMAWPjeLwgeSv1QeQ1sFVRWjOfWNvNFDYrpUSlSDEPq+vk3UYkuJ9lhxfcL+oj7/4SsSuqBPGO3Vic2E55FJnzJlPE2Xjv+CjBDFVXxifj61+Z5A6CCHaCYkKXlpZmWibESKdOndCpUyfm/nr16sFYdm/s2LEYO3aspe0FCxYw93Xp0gVdunSxtEEQBEEQhMO4NcBlU2Fzk0JHEOUKGaXGSqUwK8NgVFnsKE5myolezoOXNGBlT2QckeWh7IzLimkTWdDdKsbRbtkRVn8VBU3k2J1MQDDbd7B/MQAgart5O5HzpRLbZvSNV1aEdW963w8qsa0yhZit+hBBDJUtARAkMXQEQRAEQRAEG1LoiMsWmVgaZhkRhxft9i606z0e629vX6yyBL3hLUPFQkXRYPXhFaP1h3IiUyJE1S5rm0g5ESMyPiYKZhTz7MkUlvZXCR9jaRiR82ZlV6QYMXEp4ERSQ/ArdDShIwiCIAgieKFXrgBoQkcQtrL2jOgxcEDpODgZZcOOKsLL2rRS/HixhirniakWtmpTqo9HobHIdvTOjORlNZr19W7Din+UKZAsgowKKjOuVUybSsyhTB06ox8yds18Y113J5VhgriUoQkdQRAEQRDBi1uD7VemlOVKEMGPSuV7lrrjrcrJxE6pxFmxbPDi++yoK6xxeDZYfc2WixJdmom3CoVMpqTKag8q8WN/Zy7L17uTUYtVsk91WMut8XyRUXd5bfyBE0ucEUGE5i752LUR5FCWK0EQBEEQRJBDCh1B/A9erJCV+iVSg0sk+5QFb41KGdXNmElYartFxiRvHLPjYdW7M65qYIZRZZFZAcNOdrAZrLFFsnWjtlfw6WNnJQoZFUykRp6KTyylzmxlFSv1W6Y+pNkxqNQUJC5BKCkCAE3oCIIgCIIIZiiGDgDg0oxrYREB49SpU6hSpQraozvCXOGBdofwwolaXDpmqo7oyg0q8Wq8NixE+srULmNtN1N1nFBodMxW3rC6ljKrJNiJCXO6Phyrj896qQzlSj9Peh1Eb5tW96ZTdf1YiqwRymAt31zULiALX6CgoACVK1f261j6v5kdrxqIsJBI6w4cLrqLsOLo7DLx21+QQkcQBEEQRPBCr1wB0ISOIISwyiiUUXfMVBJR9YNXg03Ud5592f7e+0XWZTVuNzsGo3pnPDciCo3eN2Eu+xyJxNmxzg8v7s6Oasu6D+ysyuAdp2is5affi7y1g61UY6dUatGaggRRCg0OTOgc8SSgUJYrQRAEQRBEkEMKHUHYwMmYKp4do4Lj3YaVMWonJowXqyVSu86JmmWseC+R2DOeemnlk1lcn3FslUxllg3AepUEkSxq43bjeLI+idoTqdvIUql551qHasoRltArVwA0oSMIgiAIIphxuwHYLAzsDv7CwjShIwgHsKvMWdWs49VrM6odrBpzPDs8pVE0fsxOHB6vLSvuy6yNTOyZSg0zFfVLpfaaneMRUdus6g3KZFN7q2w6VvbNFGcWpMwRhBg0oSMIgiAIInihV64AqA5duYLq0F2ayMQcycRDHexfDODv2mEifVTq0JWK1XNQMfFWd1hZjrzadVZ9dfQ6a8DfGZ0idc7srEWqUkeNVUOOlw1sZcup4+HZNdpm3TNOxZoS5ZeA1KGLewRhIRG2bF10n8eKE/8J6jp0lOVKEARBEAQR5NArV4LwMyr1u1hrt3r3STTEKRnj78z6iK7gYLZSgFXGp4wSqLdVWUPUG9GVNRIfYMeT2TkOUT+tbLGui379ZfrylFSr8yRyDpysR0cQjkBLfwGgCR1BlAtES3aY9eG9ljNi9Y+x2cTCaFdlGSyRch+idq0C7gF+0L1VaRjeuZcpxCxTukV0AiwynsjrTavj4CXSiC7R5d3G6CtBOImmuaFp9rJU7fYvD9ArV4IgCIIgiCCHFDqCKIdILcnVqkQx4ZX1sLJfqjSIlyoj+ppOpo0dpYs3jg7r9TDPB/2YRV65iiQXWClzIsWCZYo5y7xCtjq3PLXXjhJMEH5B0+y/Mr0E8kNpQkcQBEEQRPCiORBDRxM6giCcwI4SZFRMVMqLiBSclSk5obL0l5UN3vJnVoWZeWPLLHvmpPKkl50B/i6lwvJRZnkt498iSTGi+3m+EQQRWGhCRxAEQRBE8OJ2Ay6bSQ2XQFIETegIohwjon4Y1RtWVqoZMkViRft6b9ML+pqVDREdR0ckq1Ila9MYNygSb8dDtK13QWhR5YyHzL1CEJcU9MoVAGW5EgRBEARBBD2k0BHEJYJKwVcR5YfVR8Ruwlz5vjqsTEwnVTJArVaaSPFeGR/MsotFfbKznBbFwxGXAprbDc3mK9dLoQ4dTegIgiAIgghe6JUrAJrQEcQli51abyJ11VSWzJKpq2ZEpe6dWVyhTF04YxsdmQxilm9m9lTUNlLVCIIAaEJHEARBEEQw49YAFyl0NKEjiEsUOyoPbxUD49+8emcibY2w1EI7qyXwUKmRJ2LPym+RGnkq4xHEZYemAbBbtiT4J3SU5UoQBEEQBBHkkEJHEAQXK9VLRmmSUducWF1CZLUEFXVSBZlafzKrfZAyR1zuaG4Nms1XrtoloNDRhI4gCIIgiOBFc8P+K1cqW0IQxCWIv+O7zGzpbfWabMYVL4ztVH1TaWulKHrbtOojEvOmkkVLEETZM3PmTEyZMgV5eXlo2rQpXn31Vdx8880B8YVi6AiCIAiCCFo0t+bIR5YPPvgATz75JEaPHo1t27bh5ptvxm233YZDhw754SitcWmXwovjS4RTp06hSpUqaI/uCHOFB9odgvAbMpmxMvY8Ky4YFC5v28Y2Rl/0+DUzO3agbFTicuCidgFZ+AIFBQWoXLmyX8dy8t9MFb9vuOEGXH/99Zg1a5Zn2zXXXIO77roLEydOtOWPCvTKtRyhz60v4oLtotcEUZ4pvngOAKBpF0pt0/HeJ2qvuOh/3yFDX2/bxjZGX4qL/m5rtGMHs2MmiEuNiyi5v8tSK3Li30zd71OnTvlsj4yMRGRkZKn258+fx5YtWzBy5Eif7Z07d8batQEKmdCIcsPhw4f19UvoQx/60Ic+9Anaz+HDh/3+b+bZs2e1GjVqOOZzpUqVSm1LT083Hfvo0aMaAG3NmjU+21988UXt6quv9vuxm0EKXTmiVq1aOHz4MGJiYuByuTzbT506hTp16uDw4cN+l7CJ0tD5Dyx0/gMHnfvAEoznX9M0nD59GrVq1fL7WFFRUThw4ADOnz/viD1N03z+7QVgqs55Y2xvZqOsoAldOSIkJAS1a9dm7q9cuXLQfKkvRej8BxY6/4GDzn1gCbbzX6VKlTIbKyoqClFRUWU2nk5cXBxCQ0ORn5/vs/3YsWOIj48vc38AynIlCIIgCIKQIiIiAi1btsTy5ct9ti9fvhxt2rRh9PIvpNARBEEQBEFI8vTTT6N3795o1aoVkpOTMWfOHBw6dAgDBw4MiD80oQsCIiMjkZ6ebvkun/APdP4DC53/wEHnPrDQ+S/f9OzZE7///jvGjx+PvLw8NGvWDN988w0SEhIC4g/VoSMIgiAIgghyKIaOIAiCIAgiyKEJHUEQBEEQRJBDEzqCIAiCIIgghyZ0BEEQBEEQQQ5N6PzI2LFj4XK5fD41atTw2d+4cWNUrFgRsbGx6NixIzZs2GBp95NPPkGTJk0QGRmJJk2a4LPPPpMa93LBH+d/586duPfee1GvXj24XC68+uqrpu1mzpyJ+vXrIyoqCi1btsQPP/zg5KEFBYE6/3T/++fcv/3227j55psRGxvr6bNx48ZS7ejeD9z5p3v/8oYmdH6madOmyMvL83x+/vlnz76rr74ab7zxBn7++WesXr0a9erVQ+fOnXH8+HGmvXXr1qFnz57o3bs3fvzxR/Tu3Rs9evQo9WPAG/dywunzX1hYiMTERLz88svMH8oPPvgATz75JEaPHo1t27bh5ptvxm233YZDhw45fnzlnUCcf6txLxecPvdZWVl44IEHsGrVKqxbtw5169ZF586dcfToUU8buvf/JhDn32pc4hInICvIXiakp6dr1157rXD7goICDYC2YsUKZpsePXpoXbp08dmWmpqq9erVS3ncSxV/nH9vEhIStOnTp5fa/s9//lMbOHCgz7bGjRtrI0eOFPblUiBQ55/uf/+fe03TtIsXL2oxMTHaf//7X882uvdLCNT5p3v/8oYUOj+zd+9e1KpVC/Xr10evXr2wf/9+03bnz5/HnDlzUKVKFVx77bVMe+vWrUPnzp19tqWmpmLt2rVK417qOH3+rTh//jy2bNlS6hp17ty51DW6HCjr8y877qWMv899YWEhLly4gGrVqnns0L3/N2V9/mXHJS49aELnR2644Qa88847WLp0Kd5++23k5+ejTZs2+P333z1tvvrqK1SqVAlRUVGYPn06li9fjri4OKbN/Pz8Ugv/xsfH+ywQLDLu5YA/zr8VJ06cQHFxseU1uhwIxPkXHfdSpyzO/ciRI3HVVVehY8eOAOje9yYQ5190XOISJtAS4eXEX3/9pcXHx2vTpk3z2bZ3715t3bp12iOPPKLVq1dP++2335g2wsPDtQULFvhse++997TIyEipcS9HnDj/3pi98jt69KgGQFu7dq3P9hdeeEFr1KiR7WMIZsri/IuOe7nh9LmfNGmSFhsbq/3444+ebXTvsymL8y86LnHpQgpdGVKxYkU0b94ce/fu9dnWsGFD3HjjjcjIyEBYWBgyMjKYNmrUqFHqaffYsWOlnoqtxr0cceL8WxEXF4fQ0FDpa3Q5UBbnX3Tcyw0nz/3UqVPx0ksvYdmyZWjRooVnO937bMri/IuOS1y60ISuDCkqKsKuXbtQs2ZNZhtN01BUVMTcn5ycjOXLl/tsW7ZsGdq0aWNr3MsBJ86/FREREWjZsmWpa7R8+XLuNbocKIvzrzrupY5T537KlCmYMGEClixZglatWvnso3ufTVmcf9VxiUuIgOqDlzjDhw/XsrKytP3792vr16/X7rjjDi0mJkbLycnR/vrrL23UqFHaunXrtJycHG3Lli1av379tMjISG3Hjh0eG7179/bJEFuzZo0WGhqqvfzyy9quXbu0l19+WQsLC9PWr18vNO7lhD/Of1FRkbZt2zZt27ZtWs2aNbURI0Zo27Zt0/bu3etps2jRIi08PFzLyMjQfvnlF+3JJ5/UKlasSOe/jM4/3f/+OfeTJk3SIiIitI8//ljLy8vzfE6fPu1pQ/d+CYE6/3TvX97QhM6P9OzZU6tZs6YWHh6u1apVS7vnnnu0nTt3apqmaWfPntXuvvturVatWlpERIRWs2ZNrVu3btrGjRt9bLRr107r06ePz7aPPvpIa9SokRYeHq41btxY++STT4THvZzwx/k/cOCABqDUp127dj793nzzTS0hIUGLiIjQrr/+eu27777z9+GWOwJ1/un+98+5T0hIMD336enpPv3o3g/c+ad7//LGpWmaVraaIEEQBEEQBOEkFENHEARBEAQR5NCEjiAIgiAIIsihCR1BEARBEESQQxM6giAIgiCIIIcmdARBEARBEEEOTegIgiAIgiCCHJrQEQRBEARBBDk0oSMIgiAIgghyaEJHEJcJLpcLn3/+uXD7rKwsuFwu/Pnnn37zKZiQPX8qjB07Fi6XCy6XC6+++mqZ+5OWluYZ39/HShCEs9CEjiCCHO9/hMPCwlC3bl08/vjjOHnypE+7vLw83HbbbY6OPXbsWCQlJQm3P3LkCCIiItC4cWNH/SgL/HH+zGjatCny8vIwYMAAv49l5LXXXkNeXl6Zj0sQhH1oQkcQlwBdunRBXl4ecnJyMHfuXCxevBiDBg3yaVOjRg1ERkYGyMMS5s+fjx49eqCwsBBr1qwJqC+ylNX5CwsLQ40aNVChQgW/j2WkSpUqqFGjRpmPSxCEfWhCRxCXAJGRkahRowZq166Nzp07o2fPnli2bJlPG+NrtLVr1yIpKQlRUVFo1aoVPv/8c7hcLmzfvt2n35YtW9CqVStUqFABbdq0wZ49ewCUTM7GjRuHH3/80aMQzp8/n+mjpmmYN28eevfujQcffBAZGRk++8+fP48hQ4agZs2aiIqKQr169TBx4kTP/j///BMDBgxAfHw8oqKi0KxZM3z11Vc+x3PLLbcgOjoaderUwbBhw3DmzBnP/nr16uGll17CI488gpiYGNStWxdz5swRHt94/n7++WfceuutiI6ORvXq1TFgwAD89ddfnv1paWm46667MHXqVNSsWRPVq1fH4MGDceHCBeY5YrF3717ccsstiIqKQpMmTbB8+fJSbY4ePYqePXsiNjYW1atXR/fu3ZGTk+PZf/HiRQwbNgxVq1ZF9erV8eyzz6JPnz646667pP0hCKL8QRM6grjE2L9/P5YsWYLw8HBmm9OnT+POO+9E8+bNsXXrVkyYMAHPPvusadvRo0dj2rRp2Lx5M8LCwvDII48AAHr27Inhw4d7XhHm5eWhZ8+ezDFXrVqFwsJCdOzYEb1798aHH36I06dPe/a//vrr+PLLL/Hhhx9iz549eO+991CvXj0AgNvtxm233Ya1a9fivffewy+//IKXX34ZoaGhAEomV6mpqbjnnnvw008/4YMPPsDq1asxZMgQHx+mTZuGVq1aYdu2bRg0aBAef/xx7N6923J8I4WFhejSpQtiY2OxadMmfPTRR1ixYkWp8VatWoV9+/Zh1apV+O9//4v58+dzJ71muN1u3HPPPQgNDcX69esxe/bsUteqsLAQKSkpqFSpEr7//nusXr0alSpVQpcuXXD+/HkAwKRJk/D+++9j3rx5WLNmDU6dOkVxcgRxKaERBBHU9OnTRwsNDdUqVqyoRUVFaQA0ANorr7zi0w6A9tlnn2mapmmzZs3Sqlevrp09e9az/+2339YAaNu2bdM0TdNWrVqlAdBWrFjhafP1119rADz90tPTtWuvvVbIzwcffFB78sknPX9fe+212ttvv+35e+jQodqtt96qud3uUn2XLl2qhYSEaHv27DG13bt3b23AgAE+23744QctJCTE42tCQoL20EMPefa73W7tyiuv1GbNmmU5vqb5nr85c+ZosbGx2l9//eXZ//XXX2shISFafn6+pmkl1yUhIUG7ePGip83999+v9ezZ09S+ppmfz6VLl2qhoaHa4cOHPdu+/fZbH38yMjK0Ro0a+fheVFSkRUdHa0uXLtU0TdPi4+O1KVOmePZfvHhRq1u3rta9e3fusRIEERyQQkcQlwApKSnYvn07NmzYgKFDhyI1NRVDhw5ltt+zZw9atGiBqKgoz7Z//vOfpm1btGjh+f+aNWsCAI4dOybl359//olPP/0UDz30kGfbQw89hP/85z+ev9PS0rB9+3Y0atQIw4YN83llvH37dtSuXRtXX321qf0tW7Zg/vz5qFSpkueTmpoKt9uNAwcOmB6Ly+VCjRo1PMfCG9/Irl27cO2116JixYqebW3btoXb7fa8kgZKEhx0FREoOX+y527Xrl2oW7cuateu7dmWnJxc6vizs7MRExPjOf5q1arh3Llz2LdvHwoKCvDbb7/5XOPQ0FC0bNlSyheCIMovYYF2gCAI+1SsWBENGzYEUPLqMCUlBePGjcOECRNM22uaBpfLVWqbGd6vbvU+brdbyr8FCxbg3LlzuOGGG3zGc7vd+OWXX9CkSRNcf/31OHDgAL799lusWLECPXr0QMeOHfHxxx8jOjqaa9/tduOxxx7DsGHDSu2rW7eu6bHox6MfC298I2bnz9umyHiimF0X49hutxstW7bE+++/X6rtFVdcwez3/+3dXSizbxwH8K8dLGltDszLiRwojIRMOTDEgTNCGJlIIq0VZQfLy4nXVk7kZO1ECUneSpYDeUtJ3JiwHcxbkjRxIsn8D/Rfz8zrP8/fM8/3U9fJrmv377q7av363dd97bU1JyLfwwod0Q/U2toKo9GIs7OzF/ujo6Oxvb2Nu7s792fr6+ufjiMWi/Hw8PDuOLPZjMbGRgiC4G5bW1vIzMz0qNJJpVIUFxfDZDJhZGQEY2NjcDqdiI+Px+npKWw224vXT0pKwu7uLiIjI72aWCz+8P28Fv85hUIBQRA8XrpYWVmBSCR6tYr4XykUChwfH3us5erqqseYpKQk2O12BAcHe92/TCaDTCZDSEgI1tbW3N95eHjA5ubml86ViL4PEzqiHygjIwOxsbHo6Oh4sb+0tBQulws1NTXY29uDxWKB0WgE4F3FeUtERAQcDgcEQcDl5aVHgvgvQRCwsbGB6upqxMXFeTS1Wo2BgQHc39+jt7cXw8PD2N/fh81mw+joKEJDQxEYGIj09HSoVCoUFBRgbm7OXUmbnZ0FAOj1eqyurqK+vh6CIMBut2NqaurNx87PvRX/ubKyMvj7+6OiogJWqxXz8/PQarUoLy9HSEjIh2N+RHZ2NqKioqDRaLC1tYWlpSUYDAa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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "Set the backend for `afwDisplay` to be Firefly, and open the Firefly tab." + "# Example 1: Histogram of i-band PSF magnitudes\n", + "#plt.figure(figsize=(7,5))\n", + "#plt.hist(object_cat_ecdfs['i_psfMag'], bins=50, color='steelblue', alpha=0.7)\n", + "#plt.xlabel(\"i-band PSF Magnitude\")\n", + "#plt.ylabel(\"Number of Objects\")\n", + "#plt.title(\"Distribution of i-band PSF Magnitudes\")\n", + "#plt.show()\n", + "\n", + "# Example 2: 2D histogram of sky coordinates (RA vs Dec)\n", + "plt.figure(figsize=(7,5))\n", + "plt.hist2d(object_cat_ecdfs['coord_ra'], object_cat_ecdfs['coord_dec'],\n", + " bins=200, cmap='viridis')\n", + "plt.colorbar(label=\"Number of Objects\")\n", + "plt.xlabel(\"Right Ascension [deg]\")\n", + "plt.ylabel(\"Declination [deg]\")\n", + "plt.title(\"Sky Distribution of Objects\")\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 17, - "id": "8e93fbe0-3bce-4b90-aa47-dd37ad8ed88a", + "execution_count": null, + "id": "5af580e6-8611-4c83-b4ac-d924905fcec2", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:24:08.704256Z", - "iopub.status.busy": "2025-09-09T15:24:08.704054Z", - "iopub.status.idle": "2025-09-09T15:24:08.931284Z", - "shell.execute_reply": "2025-09-09T15:24:08.930305Z", - "shell.execute_reply.started": "2025-09-09T15:24:08.704239Z" + "execution_failed": "2025-09-16T17:06:28.151Z", + "iopub.execute_input": "2025-09-16T17:05:09.111140Z", + "iopub.status.busy": "2025-09-16T17:05:09.110835Z" } }, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting float[pyarrow] to object dtype.\n", + " warnings.warn(\n", + "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting float[pyarrow] to object dtype.\n", + " warnings.warn(\n" + ] + } + ], "source": [ - "afwDisplay.setDefaultBackend(\"firefly\")\n", - "afw_display = afwDisplay.Display(frame=1)" + "# Example 1: Histogram of i-band PSF magnitudes\n", + "plt.figure(figsize=(7,5))\n", + "plt.hist(object_cat_ecdfs['r_psfMag'], bins=50, color='steelblue', alpha=0.7)\n", + "plt.xlabel(\"i-band PSF Magnitude\")\n", + "plt.ylabel(\"Number of Objects\")\n", + "plt.title(\"Distribution of i-band PSF Magnitudes\")\n", + "plt.show()" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "050ef751-3f6d-4805-a6ba-c2f0bf0c5ae8", + "metadata": {}, + "outputs": [], + "source": [] + }, { "cell_type": "markdown", - "id": "471c8443-32a8-4166-9dea-dabda823fa9d", + "id": "5a9cce35-0fe0-46ee-846e-eaf7755e731d", "metadata": {}, "source": [ - "Create an instance of the Butler." + "Optional: uncomment the following cell and press \"tab\" to browse more availabe methods." ] }, { "cell_type": "code", - "execution_count": 18, - "id": "9a0d2abd-f48e-4860-aa8b-269d90c8e2a0", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-09T15:24:08.933038Z", - "iopub.status.busy": "2025-09-09T15:24:08.931958Z", - "iopub.status.idle": "2025-09-09T15:24:09.271504Z", - "shell.execute_reply": "2025-09-09T15:24:09.270757Z", - "shell.execute_reply.started": "2025-09-09T15:24:08.933010Z" - } - }, + "execution_count": null, + "id": "2c19a686-c4ce-49bc-836e-d5becc7f8b7b", + "metadata": {}, "outputs": [], "source": [ - "butler = Butler(\"dp1\", collections=\"LSSTComCam/DP1\")\n", - "assert butler is not None" + "# object_cat." ] }, { "cell_type": "code", "execution_count": null, - "id": "ae50ca76-7a91-47c2-bb29-65198ba05096", + "id": "cb4cdfab-33b6-4f81-b9ac-d5bf459d5740", "metadata": {}, "outputs": [], "source": [] @@ -217,99 +1425,351 @@ { "cell_type": "code", "execution_count": null, - "id": "c2a3535c-592a-4acd-b4b5-c920e62d0aff", + "id": "4ffbca13-0c91-4ce9-a23d-ed4b84c851b4", "metadata": {}, "outputs": [], "source": [] }, { - "cell_type": "code", - "execution_count": null, - "id": "966562c6-f5d9-4195-b1b2-14ad5f17fb30", + "cell_type": "markdown", + "id": "1c52944d-f33f-4d72-9bc3-3430fe26b113", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "### 2.2. Lite object catalog" + ] }, { - "cell_type": "code", - "execution_count": null, - "id": "14c81508-8944-493d-b7f0-b4f5a2622e18", + "cell_type": "markdown", + "id": "83cd7f51-81cb-4ae4-b36b-fa43d3ddb61a", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "The `object_collection_lite` LSDB catalog is a reduced version of the `Object` catalog in `object_collection`. It contains 74 commonly used columns that provide basic object properties, including object identifiers, sky coordinates with uncertainties, basic shape measurements, flags, and PSF- and Kron-based fluxes and magnitudes (with uncertainties) across the six Legacy Survey of Space and Time (LSST) bands (`u`, `g`, `r`, `i`, `z`, and `y`)." + ] }, { - "cell_type": "code", - "execution_count": null, - "id": "13df4656-f715-4ab8-9816-440d677abd2c", + "cell_type": "markdown", + "id": "06d11db7-9188-4534-bd18-3a2ebc6eea2d", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "Get the catalog" + ] }, { "cell_type": "code", - "execution_count": null, - "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", - "metadata": {}, + "execution_count": 15, + "id": "ce101fd1-06bb-4b3b-8f32-7c128079cbb0", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:51:06.294000Z", + "iopub.status.busy": "2025-09-16T13:51:06.293722Z", + "iopub.status.idle": "2025-09-16T13:51:07.843316Z", + "shell.execute_reply": "2025-09-16T13:51:07.842785Z", + "shell.execute_reply.started": "2025-09-16T13:51:06.293978Z" + } + }, "outputs": [], - "source": [] + "source": [ + "object_cat_lite = lsdb.open_catalog(base_path / \"object_collection_lite\")" + ] }, { - "cell_type": "code", - "execution_count": null, - "id": "4be65b33-82a4-4f2c-aa68-839c790ea4da", + "cell_type": "markdown", + "id": "9d4c3445-81da-4ea6-9831-e709874ea5c6", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "Display all the columns." + ] }, { "cell_type": "code", - "execution_count": null, - "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", + "execution_count": 13, + "id": "cf587923-8b43-47fa-af57-6bdce6062035", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T13:38:54.127686Z", + "iopub.status.busy": "2025-09-16T13:38:54.127386Z", + "iopub.status.idle": "2025-09-16T13:38:54.133255Z", + "shell.execute_reply": "2025-09-16T13:38:54.132466Z", + "shell.execute_reply.started": "2025-09-16T13:38:54.127663Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['tract',\n", + " 'patch',\n", + " 'z_psfFlux',\n", + " 'z_psfFluxErr',\n", + " 'z_kronRad',\n", + " 'z_kronFlux',\n", + " 'z_kronFluxErr',\n", + " 'u_psfFlux',\n", + " 'u_psfFluxErr',\n", + " 'u_kronRad',\n", + " 'u_kronFlux',\n", + " 'u_kronFluxErr',\n", + " 'g_psfFlux',\n", + " 'g_psfFluxErr',\n", + " 'g_kronRad',\n", + " 'g_kronFlux',\n", + " 'g_kronFluxErr',\n", + " 'r_psfFlux',\n", + " 'r_psfFluxErr',\n", + " 'r_kronRad',\n", + " 'r_kronFlux',\n", + " 'r_kronFluxErr',\n", + " 'i_psfFlux',\n", + " 'i_psfFluxErr',\n", + " 'i_kronRad',\n", + " 'i_kronFlux',\n", + " 'i_kronFluxErr',\n", + " 'y_psfFlux',\n", + " 'y_psfFluxErr',\n", + " 'y_kronRad',\n", + " 'y_kronFlux',\n", + " 'y_kronFluxErr',\n", + " 'parentObjectId',\n", + " 'coord_ra',\n", + " 'coord_dec',\n", + " 'coord_raErr',\n", + " 'coord_decErr',\n", + " 'refBand',\n", + " 'x',\n", + " 'y',\n", + " 'xErr',\n", + " 'yErr',\n", + " 'refFwhm',\n", + " 'shape_xx',\n", + " 'shape_yy',\n", + " 'shape_xy',\n", + " 'detect_isIsolated',\n", + " 'shape_flag',\n", + " 'objectId',\n", + " 'u_psfMag',\n", + " 'u_psfMagErr',\n", + " 'u_kronMag',\n", + " 'u_kronMagErr',\n", + " 'g_psfMag',\n", + " 'g_psfMagErr',\n", + " 'g_kronMag',\n", + " 'g_kronMagErr',\n", + " 'r_psfMag',\n", + " 'r_psfMagErr',\n", + " 'r_kronMag',\n", + " 'r_kronMagErr',\n", + " 'i_psfMag',\n", + " 'i_psfMagErr',\n", + " 'i_kronMag',\n", + " 'i_kronMagErr',\n", + " 'z_psfMag',\n", + " 'z_psfMagErr',\n", + " 'z_kronMag',\n", + " 'z_kronMagErr',\n", + " 'y_psfMag',\n", + " 'y_psfMagErr',\n", + " 'y_kronMag',\n", + " 'y_kronMagErr',\n", + " 'objectForcedSource']" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "object_cat_lite.all_columns" + ] + }, + { + "cell_type": "markdown", + "id": "73764ef6-ebb6-4b7f-bfd5-d7c5e1a51302", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "### 2.2 Dia Object catalog" + ] }, { "cell_type": "code", - "execution_count": null, - "id": "bc55909b-767c-4f33-801d-3d0cd6f09796", - "metadata": {}, + "execution_count": 20, + "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:19:02.130305Z", + "iopub.status.busy": "2025-09-16T15:19:02.129984Z", + "iopub.status.idle": "2025-09-16T15:19:04.617665Z", + "shell.execute_reply": "2025-09-16T15:19:04.616953Z", + "shell.execute_reply.started": "2025-09-16T15:19:02.130278Z" + } + }, "outputs": [], - "source": [] + "source": [ + "dia_object_cat = lsdb.open_catalog(base_path / \"dia_object_collection\")" + ] }, { "cell_type": "code", - "execution_count": null, - "id": "d3ce71f2-018c-49a1-8933-999707d40990", - "metadata": {}, - "outputs": [], - "source": [] + "execution_count": 21, + "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:19:04.618807Z", + "iopub.status.busy": "2025-09-16T15:19:04.618596Z", + "iopub.status.idle": "2025-09-16T15:19:04.632750Z", + "shell.execute_reply": "2025-09-16T15:19:04.632097Z", + "shell.execute_reply.started": "2025-09-16T15:19:04.618788Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog dia_object_lc:
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decdiaObjectIdnDiaSourcesraradecMjdTaitractdiaObjectForcedSourcediaSource
npartitions=208
Order: 6, Pixel: 130double[pyarrow]int64[pyarrow]int64[pyarrow]double[pyarrow]double[pyarrow]int64[pyarrow]nested<band: [string], coord_dec: [double], co...nested<band: [string], centroid_flag: [bool], ...
Order: 6, Pixel: 136........................
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Order: 11, Pixel: 36833621........................
Order: 7, Pixel: 143884........................
\n", + "
8 out of 140 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " dec diaObjectId nDiaSources ra radecMjdTai tract diaObjectForcedSource diaSource\n", + "npartitions=208 \n", + "9147936743096320 double[pyarrow] int64[pyarrow] int64[pyarrow] double[pyarrow] double[pyarrow] int64[pyarrow] nested nested\n", + "9570149208162304 ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 21, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dia_object_cat" + ] }, { "cell_type": "markdown", - "id": "016f2de7-84f9-4bee-aa2c-4f5b73159af2", + "id": "a4e7a75f-07e7-443e-b5c0-ac92db031f00", "metadata": {}, "source": [ - "Open the read-only LSDB PZ catalog, which has been added by Rubin staff to the `/rubin` directory." + "### 2.3 Phot-z catalog" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 22, "id": "e8dd3508-9aff-4157-a911-d555128c9a37", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:22:35.634472Z", - "iopub.status.busy": "2025-09-09T15:22:35.634182Z", - "iopub.status.idle": "2025-09-09T15:22:35.849953Z", - "shell.execute_reply": "2025-09-09T15:22:35.849262Z", - "shell.execute_reply.started": "2025-09-09T15:22:35.634451Z" + "iopub.execute_input": "2025-09-16T15:19:04.633550Z", + "iopub.status.busy": "2025-09-16T15:19:04.633334Z", + "iopub.status.idle": "2025-09-16T15:19:04.837954Z", + "shell.execute_reply": "2025-09-16T15:19:04.837238Z", + "shell.execute_reply.started": "2025-09-16T15:19:04.633518Z" } }, "outputs": [], "source": [ - "pz_cat = lsdb.open_catalog(\"/rubin/lsdb_data/object_photoz\")" + "pz_cat = lsdb.open_catalog(base_path / \"object_photoz\")" ] }, { @@ -322,15 +1782,15 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 23, "id": "6cfe9c30-21dc-4b22-8ae0-d0552ecdcef3", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:22:37.178114Z", - "iopub.status.busy": "2025-09-09T15:22:37.177752Z", - "iopub.status.idle": "2025-09-09T15:22:37.255279Z", - "shell.execute_reply": "2025-09-09T15:22:37.254579Z", - "shell.execute_reply.started": "2025-09-09T15:22:37.178089Z" + "iopub.execute_input": "2025-09-16T15:19:04.839108Z", + "iopub.status.busy": "2025-09-16T15:19:04.838890Z", + "iopub.status.idle": "2025-09-16T15:19:04.909614Z", + "shell.execute_reply": "2025-09-16T15:19:04.908926Z", + "shell.execute_reply.started": "2025-09-16T15:19:04.839088Z" } }, "outputs": [ @@ -1170,7 +2630,7 @@ "Expr=MapPartitions(NestedFrame)" ] }, - "execution_count": 4, + "execution_count": 23, "metadata": {}, "output_type": "execute_result" } @@ -1181,66 +2641,59 @@ }, { "cell_type": "markdown", - "id": "5d9ed2d3-f725-47a8-af44-7bed0eacea21", - "metadata": {}, - "source": [ - "**Lazily loaded catalogs:** note the message under the displayed table above, that all of the columns have been loaded \"lazily\".\n", - "This is always the default for LSDB catalogs, and it means that only the metadata is loaded at first.\n", - "This way, LSDB can plan how tasks will be executed in the future without actually doing any computation." - ] - }, - { - "cell_type": "markdown", - "id": "a4ac250f-7f71-48a4-b1a7-0091a9042e02", - "metadata": {}, + "id": "97342caa-6d08-4e1f-bafe-80056c928632", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:19:04.910420Z", + "iopub.status.busy": "2025-09-16T15:19:04.910210Z", + "iopub.status.idle": "2025-09-16T15:19:04.913031Z", + "shell.execute_reply": "2025-09-16T15:19:04.912399Z", + "shell.execute_reply.started": "2025-09-16T15:19:04.910402Z" + } + }, "source": [ - "### 2.1. Column names\n", - "\n", - "The columns of the LSDB PZ catalog include:\n", - "\n", - "* the `objectId`, `coord_ra`, `coord_dec`\n", - "* photometry measurements for each filter `f_` (*ugrizy*):\n", - " * `f_cModelMag` and `f_cModelMagErr`\n", - " * `f_gaap1p0Mag` and `f_gaap1p0MagErr`\n", - " * `f_gaap3p0Mag` and `f_gaap3p0MagErr`\n", - " * `f_kronMag` and `f_kronMagErr`\n", - " * `f_psfMag` and `f_psfMagErr`\n", - "* standardized outputs from the PZ estimators\n", - "\n", - "Option to display all 130 column names." + "## 3. Sky partitions" ] }, { "cell_type": "markdown", - "id": "eae22309-0935-4674-a8af-8b193e5aff50", + "id": "ba831cc9-d052-4a7c-b805-d3b3d89f869b", "metadata": {}, "source": [ - "### 2.2. Sky partitions\n", + "LSDB catalogs are divided into **partitions**, which reflect how the LSDB-formatted files are stored.\n", + "Each partition contains approximately the same number of objects, so partitions are not equal-area regions of the sky.\n", + "The **HATS partitioning scheme** assigns smaller partitions to dense regions (for example, the Galactic bulge) and larger partitions to sparse regions, ensuring balanced row counts across files.\n", "\n", - "When `pz_cat` is displayed (above) there are four rows, one for each of the partitions of the LSDB PZ catalog.\n", - "These partitions are how the LSDB-formatted files are stored, with each partition typically having about the same number of objects.\n", - "\n", - "Show the four partitions of `pz_cat` on the sky.\n", - "This is not necessarily the same as a sky coverage map, but rather shows the file's polygonal partition boundaries." + "The `plot_pixels` method of a catalog object visualizes these partitions.\n", + "The result is not a science-driven sky coverage map but a display of the polygonal partition boundaries.\n", + "Pixel colors represent pixel sizes, with smaller pixels corresponding to regions of higher source density." ] }, { "cell_type": "code", - "execution_count": 8, - "id": "4817c9f6-1ba8-4258-bfca-cbc6ebd7d689", + "execution_count": 34, + "id": "035604c1-816d-4e1e-ad95-061b04249e4f", "metadata": { "execution": { - "iopub.execute_input": "2025-09-09T15:22:44.139441Z", - "iopub.status.busy": "2025-09-09T15:22:44.139145Z", - "iopub.status.idle": "2025-09-09T15:22:44.506091Z", - "shell.execute_reply": "2025-09-09T15:22:44.505134Z", - "shell.execute_reply.started": "2025-09-09T15:22:44.139417Z" + "iopub.execute_input": "2025-09-16T15:27:06.829115Z", + "iopub.status.busy": "2025-09-16T15:27:06.828843Z", + "iopub.status.idle": "2025-09-16T15:27:07.145752Z", + "shell.execute_reply": "2025-09-16T15:27:07.145099Z", + "shell.execute_reply.started": "2025-09-16T15:27:06.829094Z" } }, "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/hats/inspection/visualize_catalog.py:303: UserWarning: This plot contains HEALPix pixels smaller than a pixel of the plot. Some values may be lost\n", + " warnings.warn(\n" + ] + }, { "data": { - "image/png": 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", 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", 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" ] @@ -1250,42 +2703,42 @@ } ], "source": [ - "fig = pz_cat.plot_pixels(plot_title=\"Sky Partition Map\")" - ] - }, - { - "cell_type": "markdown", - "id": "5fcf4588-7649-4ec3-bcd0-c473c72eb7be", - "metadata": {}, - "source": [ - "> **Figure 1:** The sky partitions of the lazily-loaded PZ catalog." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "88bf6c2c-88e4-4a34-a20c-cb0a9c81ca41", - "metadata": {}, - "outputs": [], - "source": [ - "pz_cat = lsdb.open_catalog(\"/rubin/lsdb_data/object_photoz\",\n", - " columns=use_columns)" + "fig = object_cat.plot_pixels(plot_title=\"Object Cat Sky Partition Map\")" ] }, { "cell_type": "code", - "execution_count": null, - "id": "1c1ebc65-e21f-42a7-9859-143979f66c40", - "metadata": {}, - "outputs": [], + "execution_count": 35, + "id": "68bcaa43-c76d-4445-b101-54fc382c7399", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-16T15:27:32.206844Z", + "iopub.status.busy": "2025-09-16T15:27:32.206567Z", + "iopub.status.idle": "2025-09-16T15:27:32.532728Z", + "shell.execute_reply": "2025-09-16T15:27:32.532243Z", + "shell.execute_reply.started": "2025-09-16T15:27:32.206824Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "pz_cat" + "fig = pz_cat.plot_pixels(plot_title=\"Photo-z Cat Sky Partition Map\")" ] }, { "cell_type": "code", "execution_count": null, - "id": "fd20d489-d98f-423f-8a8d-0c3e3e073786", + "id": "6fe57fd1-8e5c-4986-ac1f-8fa8e0fac896", "metadata": {}, "outputs": [], "source": [] From e737eed158e8ca1353df7cedbb4f5139442ee684 Mon Sep 17 00:00:00 2001 From: plazas Date: Wed, 17 Sep 2025 17:41:59 +0000 Subject: [PATCH 3/8] run flake8-nb and pre-commit --- .../102_5_LSDB_data_access.ipynb | 2379 +---------------- 1 file changed, 138 insertions(+), 2241 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 0a9c40b0..4d7ac06e 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -38,7 +38,7 @@ "**Packages:** `lsdb`\n", "\n", "**Credit:**\n", - "Originally developed by the Rubin Community Science team.\n", + "Originally developed by Andrés A. Plazas Malagón, Melissa Graham, and the Rubin Community Science team with input from Neven Caplar and Tianqing Zhang.\n", "Please consider acknowledging them if this notebook is used for the preparation of journal articles, software releases, or other notebooks.\n", "\n", "**Get Support:**\n", @@ -60,9 +60,10 @@ "It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format ([HEALPix](https://healpix.sourceforge.io/documentation.php)-sharded [Parquet](https://parquet.apache.org/docs/)) to efficiently perform spatial operations.\n", "\n", - "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial.\n", + "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial (e.g., Gaia).\n", "\n", - "**Note:** This notebook is intended only as a very simple tutorial. For more detailed examples and advanced use cases, see the full set of LSDB tutorials at [LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html). \n", + "**Note:** This notebook is intended only as a simple tutorial on LSDB DP1 catalogs.\n", + "For more detailed examples and advanced use cases, see the full set of LSDB tutorials at [LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html). \n", "\n", "**References:**\n", "\n", @@ -75,27 +76,19 @@ "\n", "### 1.1. Import packages\n", "\n", - "Import the [LSDB package](https://github.com/astronomy-commons/lsdb/) to work with LSDB-formatted files, along with standard astronomy packages and LSST software for data access." + "Import the [LSDB package](https://github.com/astronomy-commons/lsdb/) to work with LSDB-formatted files, [`upath`](https://github.com/fsspec/universal_pathlib) for handling local and remote file paths uniformly , and `matplotlib.pyplot` for visualization." ] }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "963c1141-196b-49c1-8db0-019f3a22c6ad", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:31:14.197045Z", - "iopub.status.busy": "2025-09-16T13:31:14.196725Z", - "iopub.status.idle": "2025-09-16T13:31:23.116793Z", - "shell.execute_reply": "2025-09-16T13:31:23.116177Z", - "shell.execute_reply.started": "2025-09-16T13:31:14.197022Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import lsdb\n", "from upath import UPath\n", - "from lsst.daf.butler import Butler" + "import matplotlib.pyplot as plt" ] }, { @@ -117,7 +110,26 @@ "- `object_collection_lite` \n", "- `object_photoz`\n", "\n", - "The schemas for `dia_object_collection`, `object_collection`, and `object_collection_lite` with column names, units, and descriptions can be checked at the [Data Preview 1 (DP1) schema website](https://sdm-schemas.lsst.io/dp1.html) via the `Object` and `DiaObject` tables." + "The schemas for `dia_object_collection`, `object_collection`, and `object_collection_lite` with column names, units, and descriptions can be checked at the [Data Preview 1 (DP1) schema website](https://sdm-schemas.lsst.io/dp1.html) via the `Object` and `DiaObject` tables.\n", + "\n", + "\n", + "The `lsdb` read-only catalogs at the `data.lsst.cloud` Rubin Science Platform are located at `/rubin/lsdb_data`, and they consist of `Object`, `DIAObject`, and photometric redshift (photo-z) catalogs:\n", + "\n", + "- `dia_object_collection` \n", + "- `object_collection` \n", + "- `object_collection_lite` \n", + "- `object_photoz` \n", + "\n", + "The **`dia_object_collection`, `object_collection`, and `object_collection_lite`** catalogs have columns that match the [Data Preview 1 (DP1) schema](https://sdm-schemas.lsst.io/dp1.html) for the `Object` and `DiaObject` tables, with some additional convenience columns:\n", + "\n", + "- `psfMag`, `scienceMag` — fluxes already converted to magnitudes \n", + "- `psfMagErr`, `scienceMagErr` — corresponding uncertainties \n", + "\n", + "The `object_photoz` table follows a naming pattern of `{pz_algorithm_name}_z_{point_estimate_type}` \n", + "where:\n", + "\n", + "- `pz_algorithm_name ∈ ['fzboost', 'knn', 'gpz', 'bpz', 'cmnn', 'dnf', 'tpz', 'lephare']` \n", + "- `point_estimate_type ∈ ['mode', 'mean', 'median', 'err68high', 'err68low', 'err95high', 'err95low']` " ] }, { @@ -130,17 +142,9 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "14c81508-8944-493d-b7f0-b4f5a2622e18", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:31:23.117785Z", - "iopub.status.busy": "2025-09-16T13:31:23.117576Z", - "iopub.status.idle": "2025-09-16T13:31:23.123618Z", - "shell.execute_reply": "2025-09-16T13:31:23.123068Z", - "shell.execute_reply.started": "2025-09-16T13:31:23.117767Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "base_path = UPath(\"/rubin/lsdb_data\")" @@ -164,17 +168,9 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:48:08.214880Z", - "iopub.status.busy": "2025-09-16T15:48:08.214556Z", - "iopub.status.idle": "2025-09-16T15:48:10.876983Z", - "shell.execute_reply": "2025-09-16T15:48:10.876429Z", - "shell.execute_reply.started": "2025-09-16T15:48:08.214858Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat = lsdb.open_catalog(base_path / \"object_collection\")" @@ -182,376 +178,10 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "c6626b82-07b8-4a06-80dc-96aa78fe1dbe", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:48:10.877930Z", - "iopub.status.busy": "2025-09-16T15:48:10.877727Z", - "iopub.status.idle": "2025-09-16T15:48:10.910916Z", - "shell.execute_reply": "2025-09-16T15:48:10.910430Z", - "shell.execute_reply.started": "2025-09-16T15:48:10.877912Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog object_lc:
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npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
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\n", - "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=389 \n", - "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat" ] @@ -586,38 +216,10 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:32:09.381718Z", - "iopub.status.busy": "2025-09-16T13:32:09.381384Z", - "iopub.status.idle": "2025-09-16T13:32:09.386331Z", - "shell.execute_reply": "2025-09-16T13:32:09.385754Z", - "shell.execute_reply.started": "2025-09-16T13:32:09.381692Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", - " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", - " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", - " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", - " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", - " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", - " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", - " 'objectForcedSource'],\n", - " dtype='object')" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat.columns" ] @@ -632,17 +234,9 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:32:59.117863Z", - "iopub.status.busy": "2025-09-16T13:32:59.117520Z", - "iopub.status.idle": "2025-09-16T13:32:59.120931Z", - "shell.execute_reply": "2025-09-16T13:32:59.120087Z", - "shell.execute_reply.started": "2025-09-16T13:32:59.117839Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# object_cat.all_columns" @@ -658,29 +252,10 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "c27232da-4cfd-423d-a17e-cb4e69499b12", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:32:11.564506Z", - "iopub.status.busy": "2025-09-16T13:32:11.564230Z", - "iopub.status.idle": "2025-09-16T13:32:11.575082Z", - "shell.execute_reply": "2025-09-16T13:32:11.574437Z", - "shell.execute_reply.started": "2025-09-16T13:32:11.564485Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['objectForcedSource']" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat.nested_columns" ] @@ -695,55 +270,10 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "3678573c-8f9a-4076-8c3b-f5e2cbb7a2c7", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:32:12.996627Z", - "iopub.status.busy": "2025-09-16T13:32:12.996316Z", - "iopub.status.idle": "2025-09-16T13:32:13.002897Z", - "shell.execute_reply": "2025-09-16T13:32:13.002159Z", - "shell.execute_reply.started": "2025-09-16T13:32:12.996602Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['coord_ra',\n", - " 'coord_dec',\n", - " 'visit',\n", - " 'detector',\n", - " 'band',\n", - " 'psfFlux',\n", - " 'psfFluxErr',\n", - " 'psfFlux_flag',\n", - " 'psfDiffFlux',\n", - " 'psfDiffFluxErr',\n", - " 'psfDiffFlux_flag',\n", - " 'pixelFlags_bad',\n", - " 'pixelFlags_cr',\n", - " 'pixelFlags_crCenter',\n", - " 'pixelFlags_edge',\n", - " 'pixelFlags_interpolated',\n", - " 'pixelFlags_interpolatedCenter',\n", - " 'pixelFlags_nodata',\n", - " 'pixelFlags_saturated',\n", - " 'pixelFlags_saturatedCenter',\n", - " 'pixelFlags_suspect',\n", - " 'pixelFlags_suspectCenter',\n", - " 'invalidPsfFlag',\n", - " 'forcedSourceId',\n", - " 'psfMag',\n", - " 'psfMagErr',\n", - " 'midpointMjdTai']" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat[\"objectForcedSource\"].nest.fields" ] @@ -758,17 +288,9 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "af22e340-5692-4864-8ca6-4d5a665e7178", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:36:33.847193Z", - "iopub.status.busy": "2025-09-16T15:36:33.846903Z", - "iopub.status.idle": "2025-09-16T15:36:33.849892Z", - "shell.execute_reply": "2025-09-16T15:36:33.849363Z", - "shell.execute_reply.started": "2025-09-16T15:36:33.847172Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "use_columns = ['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr',\n", @@ -777,17 +299,9 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "id": "bf5d271e-3968-4583-b743-47cdab5e5561", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:36:34.520037Z", - "iopub.status.busy": "2025-09-16T15:36:34.519766Z", - "iopub.status.idle": "2025-09-16T15:36:37.100016Z", - "shell.execute_reply": "2025-09-16T15:36:37.099428Z", - "shell.execute_reply.started": "2025-09-16T15:36:34.520016Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_selected_columns = lsdb.open_catalog(base_path / \"object_collection\",\n", @@ -796,32 +310,10 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "6a6eda41-db4f-43d1-b769-c4df1a1c6e84", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:36:48.761964Z", - "iopub.status.busy": "2025-09-16T15:36:48.761676Z", - "iopub.status.idle": "2025-09-16T15:36:48.765650Z", - "shell.execute_reply": "2025-09-16T15:36:48.765172Z", - "shell.execute_reply.started": "2025-09-16T15:36:48.761943Z" - }, - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr'],\n", - " dtype='object')" - ] - }, - "execution_count": 40, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_selected_columns.columns" ] @@ -829,15 +321,7 @@ { "cell_type": "markdown", "id": "5a6394d7-ecc3-4f90-9269-dfad81b2872e", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:54:01.218661Z", - "iopub.status.busy": "2025-09-16T15:54:01.218363Z", - "iopub.status.idle": "2025-09-16T15:54:01.221205Z", - "shell.execute_reply": "2025-09-16T15:54:01.220723Z", - "shell.execute_reply.started": "2025-09-16T15:54:01.218637Z" - } - }, + "metadata": {}, "source": [ "#### 2.1.3 Cone searchs" ] @@ -847,22 +331,15 @@ "id": "d5021222-fc50-4f94-8095-c68e3afd39ff", "metadata": {}, "source": [ + "Cone searchs are supported and defined by a center (`ra`, `dec`), in degrees, and a radius `r`, in arcseconds.\n", "Execute a cone search on the object catalog using the coordinates (in degrees) of the Extended Chandra Deep Field South DP1 target field, with a radius of 0.1 deg." ] }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "id": "bffa951f-f910-4103-837d-e095ef63db41", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:53:00.854171Z", - "iopub.status.busy": "2025-09-16T15:53:00.853859Z", - "iopub.status.idle": "2025-09-16T15:53:00.856999Z", - "shell.execute_reply": "2025-09-16T15:53:00.856434Z", - "shell.execute_reply.started": "2025-09-16T15:53:00.854150Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ra_ecdfs = 53.16\n", @@ -871,17 +348,9 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": null, "id": "5a5d8111-6c2e-4c76-a939-447a9cd7b96f", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:53:37.420367Z", - "iopub.status.busy": "2025-09-16T15:53:37.420091Z", - "iopub.status.idle": "2025-09-16T15:53:40.009457Z", - "shell.execute_reply": "2025-09-16T15:53:40.008888Z", - "shell.execute_reply.started": "2025-09-16T15:53:37.420347Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_ecdfs = object_cat.cone_search(ra=ra_ecdfs, dec=dec_ecdfs,\n", @@ -898,454 +367,40 @@ }, { "cell_type": "code", - "execution_count": 47, + "execution_count": null, "id": "d3b6022c-7e0b-4c52-a178-fe0c35f6ada3", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:54:13.805443Z", - "iopub.status.busy": "2025-09-16T15:54:13.805177Z", - "iopub.status.idle": "2025-09-16T15:54:13.835632Z", - "shell.execute_reply": "2025-09-16T15:54:13.835147Z", - "shell.execute_reply.started": "2025-09-16T15:54:13.805422Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog object_lc:
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npartitions=8
Order: 9, Pixel: 2299851double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 9, Pixel: 2299854..............................................................................................................................
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Order: 9, Pixel: 2299876..............................................................................................................................
Order: 9, Pixel: 2299878..............................................................................................................................
\n", - "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=8 \n", - "2528712916652261376 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "2528716215187144704 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2528742603466211328 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2528743702977839104 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: search_points, 5 expressions\n", - "Expr=MapPartitions(search_points)" - ] - }, - "execution_count": 47, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_ecdfs" ] }, { "cell_type": "code", - "execution_count": 48, + "execution_count": null, "id": "21c7d923-dec5-4c75-bfd6-4602864420ec", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T16:59:24.769248Z", - "iopub.status.busy": "2025-09-16T16:59:24.768980Z", - "iopub.status.idle": "2025-09-16T16:59:24.773261Z", - "shell.execute_reply": "2025-09-16T16:59:24.772787Z", - "shell.execute_reply.started": "2025-09-16T16:59:24.769227Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", - " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", - " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", - " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", - " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", - " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", - " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", - " 'objectForcedSource'],\n", - " dtype='object')" - ] - }, - "execution_count": 48, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_ecdfs.columns" ] }, + { + "cell_type": "markdown", + "id": "31615876-27b2-44bb-bf18-62bf5926edcd", + "metadata": {}, + "source": [ + "Visualize the object distribution in the region." + ] + }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "id": "f7dafb69-0a7b-4091-9bfa-3c43460744bf", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T17:01:08.296897Z", - "iopub.status.busy": "2025-09-16T17:01:08.296591Z", - "iopub.status.idle": "2025-09-16T17:01:29.547195Z", - "shell.execute_reply": "2025-09-16T17:01:29.546556Z", - "shell.execute_reply.started": "2025-09-16T17:01:08.296874Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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cqDVu3FgLDw/XAGjp6ekeexUrVjT1j5XlOnjwYG3mzJlagwYNtPDwcK1x48ba+++/X6r/xo0btTZt2mgVK1bUrrrqKi09PV2bO3duqSzXnJwcrXPnzlpMTIwGwDOmWZarpmnaDz/8oN16661axYoVtejoaO3GG2/UFi9e7NNGzw7dtGmTz3Y9K3XVqlWmx+zN559/rt1www1aVFSUVrFiRa1Dhw7amjVrTO2JZLnq7Ny5U+vTp49Wu3ZtLTw8XKtWrZrWpUsX7euvvy7VVj+OZcuWab1799aqVq2qRUdHa127dtX27t3r07ZPnz5avXr1Stn4z3/+o91www2e89WgQQPt4Ycf1jZv3uzT7ptvvtHatWunVaxYUatQoYLWpEkTbdKkSZ79RUVFWv/+/bUrrrhCc7lcnusoeg8SBFEal6YJpL8RBFFmzJgxA8OGDcOOHTvQtGnTQLtDXIbcfffdOHz4sNC6rwRBlA/olStBlBO2bduGAwcOYPz48ejevTtN5ogy59ChQ1i7di1WrVqF3r17B9odgiAkIIWOIMoJ9erVQ35+Pm6++Wa8++67puUlCMKfjB07Fq+++ipuvfVWzJkzx5FMX4Igygaa0BEEQRAEQQQ5VLaEIAiCIAhCgrFjx8Llcvl8Av1WhWLoCIIgCIIgJGnatClWrFjh+Ts0NDSA3tCEjiAIgiAIQpqwsLCAq3Le0ISuHOF2u5Gbm4uYmBhHipoSBEEQRFmiaRpOnz6NWrVqISTE/1Fd586dw/nz5x2xpWlaqX97IyMjPSubGNm7dy9q1aqFyMhI3HDDDXjppZeQmJjoiC8qUFJEOeLIkSOlFtImCIIgiGDj8OHDnuX7/MW5c+dQP6ES8o8VWzcWoFKlSvjrr798tqWnp2Ps2LGl2n777bcoLCzE1Vdfjd9++w0vvPACdu/ejZ07d3LXRfYnNKErRxQUFKBq1aq4CV0RhvBAu0MQjlPcPgkAEJq1XbqPGSw7IuMY7Yq01dvkPXWDz/4rtxWVsiNjnyAuFS7iAlbjG/z555+oUqWKX8c6deoUqlSpggNbElA5xp4aeOq0G/VbHsThw4dRuXJlz3aeQufNmTNn0KBBAzzzzDN4+umnbfmiCr1yLUfoUm8YwhHmogkdUT4p7tASABCaucXnb2/0fUbCvttZ8j8m97fRrs6xG0v+Uag1aW1pgwY7uc+2AQDEb/7fBKvjjUx/PL4wbHn7FKn3/1+bOq9u9dn/241//8MVH1Yypv7jqo+dO7Kdz3F4nzfWuTRuZ51Xgig3/E8iKsuwocoxIbYndB5blSv7TOhEqVixIpo3b469e/c64ocKVLaEIAiCIIigpVhzO/KxQ1FREXbt2oWaNWs6dFTykEJHEIQj/Nbq79cStTJL/mulLJmpVEZ0tY1nS99nVPH07TJqmAx6H/14rfxk7Rf1ReR8EcTlhhsa3LAXPSbbf8SIEbjzzjtRt25dHDt2DC+88AJOnTqFPn362PLDDjShI4jLGNbrU95kgbXP7JWosa3RvsikxOib96RGn0SavcY062vWxrjdZ2Jq9prXpK3nFa+3T4ZJLctHkeMwG8foC03wCKLsOHLkCB544AGcOHECV1xxBW688UasX78eCQkJAfOJJnQEQRAEQQQtbrhh74UppC0sWrTI5ojOQxM6grhEsaO2ycB7BcpqoycveCtgZtusxhN9tStznPEwV/DMxjGOD5T2X0T9NFPevOGpeyz7pNwRlwvFmoZimwU77PYvD1BSBEEQBEEQRJBDCh1BXOLwYs6M8NQcUQWNZ88siUBHVJnjxqAZ7PISEFhKlndbYxkUq5hAnv2D/UuKnyaaHLuVymZsJwLvfFn1IYhgIhBJEeURmtARBEEQBBG0uKGhmCZ0NKEjiGCCV36Dpch4Z20aS4AY4Sk0VhmfZnacVJx445gpfiysxty/MMnz/4kPsGPXWL6xVEldmTNT9Yzqp4yqxhpXRZ2UuZYEQZQvaEJHEARBEETQQq9cS6C1XMsR+rp07dGdlv4ilLGjpIj0VWlj/LvUEl0m9pxQ85zuw2qjHw9QOmNVpkiwlX0zldRKbfX2TTT+kZQ6QpWL2gVk4QsUFBQoLaElg/5v5q+74hFjc+mv06fduPqa38rEb39BWa4EQRAEQRBBDr1yJYhyhEwtMdY+ntJlpYLZ8ZWnUhn78JQmmVUkrPrylCZjXxGMx6ofh4jSyLtOVqqXTGaxEasad2bjy9xvpNgRgcb9v49dG8EOTegIgiAIgghaih3IcrXbvzxAEzqCCAJklDqRumq64iOiqlgpTPp+3jqjVrZ54/Fi6axi80Tq6hnbiiiadmrxGcf39kFGBbNSxpxQX71h1foTsUPxdwThf2hCRxAEQRBE0FKslXzs2gh2aEJHEGWESjycjtl2lVgmq9g2nkrlRHwf7xhY9o2rW/CUJ/34jGqSWR8Re6KKmYziJLKOrRPr8Mpk64rE9+nnVmTFENH4ToJwAoqhK4GyXAmCIAiCIIIcUugIws+IKFu6ohQP+RUJZJQzJzMweeNZKTEysVS81S1YPhiVOe/VMnRliaU0mbVlxfHJHAcv/k4kE5Vlz+gTr51orT8RFdTYRybLWSRekSBEccOFYrhs2wh2aEJHEARBEETQ4tZKPnZtBDs0oSMIG8hkYJq10WFlWoooJkZ1T6YOnch4KqqOqBIo4psRn5UPMsV89FbFjEqZMdvVTEFjxfGJxByy/OfFoIlcd1ZbFfXQTGXTscroNctyFq31Z3dFEoIg/oYmdARBEARBBC3FDrxytdu/PEATOoKwgcqqDCKxbaz9vGxNMx9EbJvZLytVRCVD1kwxkqmvZzxWoz2ztU9ZdeJ4aptMDTvR7GYZRZN3bllteJm/KvGCpK4RZQFN6EqgLFeCIAiCIIgghxQ6ghDAKpZJVyJ8MiQZNdBEqv4blQ1jnJeILzKI1GKTGVdUMTNTnGT8Z61SIaNSisTbsRRSM0XLSm0Tuf5WK2DI9PE+HivV2I6yplIzTyWGkiCMuDUX3JrNLFeb/csDNKEjCIIgCCJooVeuJdCEjiAEsMo65K1nKhPDxrIrs3aoCCzFT2alCI8CxFmNwQqVeCzeOEZVyuij2dgsBZXnr8yasUbMag6yMpWN19/bN9baqiJr61qtECFT889o26wPC6fUZFLzCIImdARBEARBBDHFCEGxzZSAYod8CSQ0oSOI/yFSU+5g/5KvfeID2wHIKTUqWYIiiK436r2N5a9IJi5PAdJhKYpOrP9qhnGFCKMfIoqj0Q/ePpV1TLn3SquSfVY1Bb3/Nq4qoqIEy6wZy8rodXrVB5nVK5yowUcEP5oDMXQaxdARxKWH2ass/R+GRMPrxVLFaSH+j5rdQPr9C5MAAAlzze2aFYs1TnCMbc1eB7L+QeX9Q8tqK1NORKaPFTKlYkTKffAm/1blVkRKz4hg9ZpeZCLEmnTK+KPyqp2HTFFlmrgRxN/QhI4gCIIgiKCFkiJKoAkdcdnDWtidh5VqxeujwytxIhKsritzVsH9MkVvzV4Hso6RlYBgNqbK600RRMvJ8BaOV1GyZFQwVh8VVFRdnh0nXqNb+cMbT6R0j0xSDCl2lyfFWgiKNZsxdJfAWq5UWJggCIIgCCLIIYWOuCyQUYLMFABdTTuXVAjg76QIEVWPpTDwlDOrsiLeqMQ9GX0TwRhbaIwJEyl6LBIfJ6OuiCpnvGLBRlsqypaMr2W1hJZI4gnrb14SCc++EZl7U/T88NRjT9JSZun9pNpdurjhgtumPuVG8Et0NKEjCIIgCCJooRi6EmhCR1zS8GJ19Kd5Y5ao2ZO8neK5Vr6ZwYpBk0FEHWEpXGbKBquArUhWqIw6IqPQsPY5oaSJ7POoliYKoKgaxhuTV7bE6vqqlIixcy1N7xlGZq/KNeSNo6Mr505n3hJEMEATOoIgCIIgghZnkiLolStBlGt4MVqJmaV2+WCWtSmiToj4wNputMNTYZi18P4Xy+ZkbTOzcZ0oZGumtsicY9FMUp+MYgvVyHR5LUYfXm05q/NjN6tXNJPYbEwrFdEMmaLHrHGN6LUUASBhbqhQHzOV0pidbYx5BYAEht+UGRv8lMTQ2Xtlard/eYCyXAmCIAiCIIIcUuiISwI7MVsq4zgZF2W2z6i+iSx7pFLd3ywGjNWWVR/M6I9IX14fFqY15cC3r8PLKBaJZRSJ52LZVVE9RfrKrKhh5aNxu9k4IlnMLN9Y+xMfED8+M1j3Le9+NqreKteLKF+4HVjL9VLIcg0KhS4nJwf9+vVD/fr1ER0djQYNGiA9PR3nz5/3abdp0yZ06NABVatWRWxsLDp37ozt27dzbRcVFWHo0KGIi4tDxYoV0a1bNxw5ckR6bJfLVeoze/Zsx84BQRAEQRCl0WPo7H6CnaBQ6Hbv3g2324233noLDRs2xI4dO/Doo4/izJkzmDp1KgDg9OnTSE1NRffu3TFz5kxcvHgR6enpSE1NxZEjRxAeHm5q+8knn8TixYuxaNEiVK9eHcOHD8cdd9yBLVu2IDQ0VGhsnXnz5qFLly6ev6tUqeK/k0L44MQqA0YbvNplIlmCdhQaOyoPD6N94wLvRuUOKB2jx1I2zMYxIhITaBXjJKNEmtXzMyp9MuqkTHaok8pPWa1EYYbKsZutCWzVR0dFBReJhxTNvFWJhyWI8kBQTOi6dOniM1FKTEzEnj17MGvWLM+kas+ePTh58iTGjx+POnXqAADS09PRokULHDp0CA0aNChlt6CgABkZGXj33XfRsWNHAMB7772HOnXqYMWKFUhNTRUaW6dq1aqoUaOG48dPEARBEIQ5boRQYWEEyYTOjIKCAlSrVs3zd6NGjRAXF4eMjAw899xzKC4uRkZGBpo2bYqEhARTG1u2bMGFCxfQuXNnz7ZatWqhWbNmWLt2LVJTU4XG1hkyZAj69++P+vXro1+/fhgwYABCQtg3WVFREYqK/lYOTp06ZXnchC+iqg4vtk1EsWH1UYl1ElHSZGpwyagGrKxA47F715yzUrLMxmeNo/9tdnyiMYe8a2n0lbc2LSs+TiQjluezE2qrEV69OzvxiXaymkXua6uYQ7u1+Kz6el9LVrwlT6mnuLrgoFhzoVizWVjYZv/yQFC+NN63bx9mzJiBgQMHerbFxMQgKysL7733HqKjo1GpUiUsXboU33zzDcLCzOet+fn5iIiIQGxsrM/2+Ph45OfnC48NABMmTMBHH32EFStWoFevXhg+fDheeukl7nFMnDgRVapU8Xx0ZZEgCIIgCEIGl6YFrpre2LFjMW7cOG6bTZs2oVWrVp6/c3Nz0a5dO7Rr1w5z5/5d4v/s2bNo3749GjdujCFDhqC4uBhTp07F7t27sWnTJkRHR5eyvWDBAvTt29dHJQOATp06oUGDBqWSGlhjmzFt2jSMHz8eBQUFzDZmCl2dOnXQHt0R5jKP+buc8dfKBFbj8WApRIB1rJdM7JlTMVSsY1LJdmWpcDxfZK6hjp34SJl7ReT86XXTjCsS2FG6zHwy+iaDzAoR/lrRQyVrV3ZcEXu8eDt/ZR9f7lzULiALX6CgoACVK1f261inTp1ClSpVMH/btagQE2rdgUPh6WKkXfdjmfjtLwL6ynXIkCHo1asXt029evU8/5+bm4uUlBQkJydjzpw5Pu0WLFiAnJwcrFu3zvOac8GCBYiNjcUXX3xhOk6NGjVw/vx5nDx50kelO3bsGNq0aePTlje2GTfeeCNOnTqF3377DfHx8aZtIiMjERkZabqPIAiCIAhr3FoI3DazVN20UoQ94uLiEBcXJ9T26NGjSElJQcuWLTFv3rxSsWmFhYUICQmBy/X3e3D9b7fbbWqzZcuWCA8Px/Lly9GjRw8AQF5eHnbs2IHJkycLj23Gtm3bEBUVhapVqwodH2GNSP02HZm4NdbTt4rSJVOry0zRYo0jE6fGs8lqI5I5ajxPvPVmWbF5IkqHiqonEz9mJztUV+ZExlGxb8c3XnyaKCLjmWUOi/pkvB9kFDTTDOxMcPG2YfRbJk6VIIKBoIihy83NRfv27VGnTh1MnToVx48fR35+vk+cW6dOnXDy5EkMHjwYu3btws6dO9G3b1+EhYUhJSUFQMnErHHjxti4cSOAkrIi/fr1w/Dhw5GZmYlt27bhoYceQvPmzT1ZryJjL168GG+//TZ27NiBffv2Ye7cuRg9ejQGDBhAChxBEARB+JHi/xUWtvsJdoIiy3XZsmXIzs5GdnY2ateu7bNPDwFs3LgxFi9ejHHjxiE5ORkhISG47rrrsGTJEtSsWRMAcOHCBezZsweFhX+v7zd9+nSEhYWhR48eOHv2LDp06ID58+cjNDRUeOzw8HDMnDkTTz/9NNxuNxITEzF+/HgMHjzYb+fkcsKJLDSZLFTWuAB7bU8z+3q8FWuNSpl6Wjq8GD078T3+Oscq68my7PIyY1k+ml0DOxnLMrXrrOISVWI0ef2din9j+WbMVFa5z4zqmBlWmctmqpxIDKJKTCvFzAUHbtjPUjV/jxdcBMWELi0tDWlpaZbtOnXqhE6dOjH316tXD8YckKioKMyYMQMzZsxQHttYq44gCIIgCKIsCYoJHXF5IxIHpxL/ZqUE8GqXGX0zw5gJacSsr6fCPkPJMKtDZrSnEj9oREStEInv0zGqOiK+scY1G4elvhhj3niI3DMiyqyOlTInEkPJ6uuN8VyyVGTvtjJqq5VvdpRGkfuMF6tp/L6oxBpa+SjShuLuAoszhYXplStBEARBEETAcGItVlrLlSAcxEoBUlHqzGDZ52XMsewZlSgzVUamxptKvJWVYma3PpzRvkjMoZWSJVMzT0UF49mQ8UlUzeEpNDL3Mes7YFSizMbxxLgZ1k/lZXo6oSbxjoe1pquoUmgFayUPnpIpmk1r1pcFqXJEeYAmdES5RTRRQBbRV4ci/0iLBP0b2xiL05rZZ/nqjWeiaJiIykz+WOOblYZQ+UfNTgkSO2VYjPtFymPw/Pe82s0U81UE3iST9apdZBIoMgGWKZNj9TBjFqLgGY9xvkTHNtsu8tChcj3MXt+Lnid65RpY3HDBDbtJEcG/9BdN6AiCIAiCCFrolWsJAV36i/BFX8bkcl/6S6WYqhOv9FQK2KogEtgus18m4JyF06qC1bl1+lxLFaN1oJQKa3xvrNRQu9dH5RyzCvvaeYUs0sc4vllRYhWVWuX7T6VI/Esglv6avrkNoivZ06fO/nURT7VaS0t/EQRBEARBBAInCgNfCoWFSaErR1yOCp3MYva8PnaeumXUPCNOK05OKA7Gv73PlxPB8E4Gk/PsisROskp1iIwj46PKNTQiE+dlRwVzOuZU1CczFdTKF6cKZcvcK1bfLZXfJJ5Pl5sSGAiFbvKmmx1R6J5p/UNQK3TBPyUlCIIgCIK4zKFXrkRAMXsCtlI4RBYF59kUjWFSiXFSjXETjR8yUw+sFACRrD3WeGaw9tlROL3/n6XUmSlB+r1gpQiZnWtPtrEhS1gFmSxH3n6rBeR5mbHG+DhjZq6V3yK+m42rY/a9tFJOzyUVmm73ti+joNmJBTTLXBct8+KUqkeo4XbglSsVFiYIgiAIggggbi0EbptZqnb7lwdoQkeUCVYFUwH207YTMUE8ZUOkjw5rqSmRorQidbusMFNBZOqQqWTEOhELJBJvxyoOa+zrrTiJKH/Gv/U+iQ/Yr11mZt9K1eGpuDKFpUudF4NKKVLIWiUOUkahNd6vxnOTMLf0PqvfAZEMWRl1nWXDeywrdc9MBbf6rvk785q4/KAJHUEQBEEQQUsxXCi2WRjYbv/yAE3oCL9gpRp5nmxN4ntUqr6r1KHTYS3fpRJDZ5ZRyvpbRhWTqSnG8s2sjaj6wvNN1X8WMvXIjEtLOZFR6H2OWAvd88axUlvsKMw+9xdniS9RWN9TnlInojSz7kXjd8C7Ly/Wj9WHNa7ZcVip62b2Rc+pTAyljoyqR/ChV64lBP8REARBEARBXOZQHbpyxKVch874FGyW/SYae2Kntpk3rCd2Gbs6vMXTZTIvrY5RJpvObl04lj0n67apKBsqmYuqPjthTwaVGnx2vg/+qlnHGpc3jlVNQZHrwxvXjorP6iPj0+WiwgWiDt2/N3REVCV7/2ae++sCxt+wIqjr0NErV4IgCIIgghZ65VoCTegIv8KK83I6q0tGaWD5wKrjBVjXoeLV0xN5UhdVgmQUTV48FAueqiejnIpmHaqoFT7ZgYa4KzsxgSKoKFsifTzZn+AraHbjLp1ARdlWUatYbcy+l1bKIw/RWnOi9u0ozZeLikf4B5rQEQRBEAQRtBRrISi2qbDZ7V8eoAkd4VesKrmbwXpKVamvxmtrHMeYgedEbB0gpmiwjtWJDDwz/2RqiVlhJwvZDCsfva+TaEwYL5bKW/EDfFU/lfMkqrLwFGARhYl1z/Cyn1nHLlKzTqfUShQOrHfq7Zt+/lnX0iwbViXmkGdPtC+vnqJIHKyO7gMpc2pocMFts+yIZqP/xIkT8dxzz+GJJ57Aq6++assPOwT/lJQgCIIgCCIAbNq0CXPmzEGLFi0C7QopdIQ6KnFrRsz6OJXF6r1dJeNQJsaFFxcnsgKGlX0VRYjnkz+QiSuSydq0qmloZlfvIxKvKBI7pcOKsxTJbjYiEndpXI+Vdy3NMq2tEFHXZOJGjb6x7muRc22sMWjmj0zWrkeNzOT3lfmuqbwZMB4Pz77VdqKEQL1y/euvv/Cvf/0Lb7/9Nl544QVb4zsBKXQEQRAEQQQtbs3lyAcoKYXi/SkqYj8gDR48GLfffjs6duxYVofKhRQ6QhkZRU7kKVgl00uk/pSor07UlhKpq8azz1r5wEztYa1iYFRqRFQ5J2rMyZwvsz5OZPqxrodKrJMZRlWKp7IZEYkjZGU1m8WrlWpriAWzW7fNOI7MOsZWiqzIubcTm2dm12q1D/3v/QuTPNsSH9jus0/ku3SwfzEAIIGhLPJssTJ6aa3XsqNOnTo+f6enp2Ps2LGl2i1atAhbt27Fpk2bysgza2hCRxAEQRBE0FKMEBTbfOGo9z98+LBPYeHIyMhSbQ8fPownnngCy5YtQ1RUlK1xnYRWiihHXEorRYgqASKxVCqxLTwlSFSZUYmh86mRJpENyPKX19eJuBoZJdNqfG9bItmTsr6UhzgiJ+vpmdmVUTSt+rJsWNmz8tHYV0UJVPGNp2ip1KET+Y5ZwTtOK7siCl0wEoiVIoat7o5ImytFFP11Aa/fJOb3559/jrvvvhuhoaGebcXFxXC5XAgJCUFRUZHPvrKCFDqCIAiCIAhBOnTogJ9//tlnW9++fdG4cWM8++yzAZnMATShI/yEypOziqqnouaJKj+8OD/j07dZTStWlisP43GwKuHz/JdRJ+xkAfPOFyuTkOUzz65xu4pSo5oZKapgyqgtvJgzO7GMMvex3pZVs867j2jsnEj8qLGvmZ9W96LM918mTlHlTYBZJq4nm1Ui29gqdq48qNPlGTdC4Lb5ylWmf0xMDJo1a+azrWLFiqhevXqp7WUJTegIYWRe7Vj9oyyzjxfgLvoPOe91oMhkw7hNJDDcap+ZT8ZkCLO2OiJtWD6ptFFB5j5Q+QedhUzyjchYxrYi5Sv88Y+wysTbu5At7wHEe7v3OKyJiczEUceYsGM2cTSOJ1MoWcQno2+8hxvWA5zIw5rVdecdu/EcGEuumPl/OVOsuVCs2SssbLd/eYAmdARBEARBEDbIysoKtAs0oSPMEVHbjE+tZoumq7wKsXrylFGczMYRLV8g8wqJVQSV19d7O6tMCU894KkdVqi8qpZB9LWm2Tm28klEoWEparxxRFB5pati1+iriALMUnnNFDYZH0W/wyLqu/FVvLcNlurNWz7QyYQQ3rU0nkMZBV3knrEKyzArQeSv724w4l1Hzo6NYIcmdARBEARBBC2aFgK3zZUiNJv9ywNUtqQcUV7LlhjjO1gFbb1ReVpUUXVY+1hBxt5+s8Y32uTZ5SFaikKkTfK0jQCAjUnW2VN2Sl2UlVIn4pNKkLqMTzq8JbOcuBdZ+0XuSZbP3naMbUQUTStV0lttF/VRBhVlUyVOVaSNjIrHssnr68RvUjCpb4EoWzLgu/sRYbNsyfm/LmBOu4/KxG9/QQodQRAEQRBBSzFcKIbNpAib/csDNKEjLCm13BEjM84bo6onEocjmuVq9lRvVVrBW31xotSBERH1gHU8PPS2PGVOJpbJifhEO6qBiHokU5BVJY7I2EdlkXmjLRGMbb3HtaOY8uIFWX2t7n2RkhtOqEcycapmfWQQvYZm9q3UVhUVlPebJOKbv9X1YMKt2Y+Bc18C7yqD/6UxQRAEQRDEZQ4pdIQyvCdClurBe3pkFesVUfWMqqHIeKJPxXaxkxXoRFwfTykQiVsTvS6842CNZ3Y8rHvHTLkz2pNZxklGzTP+zaqZxusjgqr6BMhlPcsoTqw+dr4nIuOInEcZtd14z3muIex/x1S+y6L9CWvcDiRF2O1fHgiKI8jJyUG/fv1Qv359REdHo0GDBkhPT8f58+d92m3atAkdOnRA1apVERsbi86dO2P79u1c20VFRRg6dCji4uJQsWJFdOvWDUeOHPFpU69ePbhcLp/PyJEjfdocOnQId955JypWrIi4uDgMGzaslH8EQRAEQTiLGy5HPsFOUGS5LlmyBB988AEeeOABNGzYEDt27MCjjz6K3r17Y+rUqQCA06dPIyEhAd27d8fIkSNx8eJFpKen44cffsCRI0cQHm6eAfP4449j8eLFmD9/PqpXr47hw4fjjz/+wJYtWzzrsdWrVw/9+vXDo48+6ulXqVIlVKpUCQBQXFyMpKQkXHHFFZg2bRp+//139OnTB/fccw9mzJghfJzlIctVJVvMTvYZL9NLpuaXjp2MUieekmViXFTbGlHJCpRBJfvUSV+cGE8lVssbJxdwdyojM1Cqjsz1YMXSBtInmT5Wvy/ev186drKBVVTQ8hY7F4gs196rHkBEpQhbts7/dR7vpiykLFd/06VLF3Tp0sXzd2JiIvbs2YNZs2Z5JnR79uzByZMnMX78eNSpUwcAkJ6ejhYtWuDQoUNo0KBBKbsFBQXIyMjAu+++i44dOwIA3nvvPdSpUwcrVqxAamqqp21MTAxq1Khh6t+yZcvwyy+/4PDhw6hVqxYAYNq0aUhLS8OLL74YtDcHQRAEQZR3aOmvEoJiQmdGQUEBqlWr5vm7UaNGiIuLQ0ZGBp577jkUFxcjIyMDTZs2RUJCgqmNLVu24MKFC+jcubNnW61atdCsWTOsXbvWZ0I3adIkTJgwAXXq1MH999+P//u//0NERMkTwbp169CsWTPPZA4AUlNTUVRUhC1btiAlJcV0/KKiIhQV/R2Dc+rUKbWT4QAicVY6rNgWXrwKC5G1EGVqPbH2i+CEOslTKc3WYxRFRmlyQjE1uy5Wx85TW51Q5ozn0WwcO/eBSEyoSka0zPeF9be/FCiVReBlfJBRq+xk+trJQhaxz/ru8takVVnvmVcT0bsdz18nYx2DBYqhKyEoj2Dfvn2YMWMGBg4c6NkWExODrKwsvPfee4iOjkalSpWwdOlSfPPNNwgLM5+35ufnIyIiArGxsT7b4+PjkZ+f7/n7iSeewKJFi7Bq1SoMGTIEr776KgYNGuRjJz4+3sdGbGwsIiIifOwYmThxIqpUqeL56MoiQRAEQRCEDAGNoRs7dizGjRvHbbNp0ya0atXK83dubi7atWuHdu3aYe7cuZ7tZ8+eRfv27dG4cWMMGTIExcXFmDp1Knbv3o1NmzYhOjq6lO0FCxagb9++PioZAHTq1AkNGjTA7NmzTX365JNPcN999+HEiROoXr06BgwYgIMHD2Lp0qU+7SIiIvDOO++gV69epnbMFLo6deoEJIZORXmwEwtk3G81tug4IrZE60TxYvVkbImcNyt1wrg6hxkqaosIRjv7FyYBABLmhvq0czqbU0VdsXPM+vk7l1To2Zb4wHYfuyzfnMpglImdFB1HJlbTTqygDHZUZBG7PKyunV2fZH5XnKS8xNIFIoauR2ZvRFS0GUN35jw+7PAuxdCpMmTIEOZkR6devXqe/8/NzUVKSgqSk5MxZ84cn3YLFixATk4O1q1bh5CQEM+22NhYfPHFF6bj1KhRA+fPn8fJkyd9VLpjx46hTZvSwa46N954IwAgOzsb1atXR40aNbBhwwafNidPnsSFCxdKKXfeREZGIjKy9BI7BEEQBEGIoTmQpapdAlmuAZ3QxcXFIS4uTqjt0aNHkZKSgpYtW2LevHmeSZtOYWEhQkJC4HL9fVH0v91ut6nNli1bIjw8HMuXL0ePHj0AAHl5edixYwcmT57M9GXbtm0AgJo1awIAkpOT8eKLLyIvL8+zbdmyZYiMjETLlup1pQKJU3E3Mk/DdjJWWf6KPK06uTatzNO9jDppFlOjK2W6iiRS3d/KJzOMbXRlTiYDU6W2mJ14NRXFTCRuUAY7mctGGyKKlogfxnvGaM/sHvJnfKpI3K1KzT8797dMG7NxnHiTIZPhz4q7s/M7RgQnQRFDl5ubi/bt26NOnTqYOnUqjh8/jvz8fJ/4tE6dOuHkyZMYPHgwdu3ahZ07d6Jv374ICwvzJCUcPXoUjRs3xsaNJQudV6lSBf369cPw4cORmZmJbdu24aGHHkLz5s09Wa/r1q3D9OnTsX37dhw4cAAffvghHnvsMXTr1g1169YFAHTu3BlNmjRB7969sW3bNmRmZmLEiBF49NFHg1a6JQiCIIhgwK25HPkEO0GR5bps2TJkZ2cjOzsbtWvX9tmnhwA2btwYixcvxrhx45CcnIyQkBBcd911WLJkiUc1u3DhAvbs2YPCwr9jZKZPn46wsDD06NEDZ8+eRYcOHTB//nxPDbrIyEh88MEHGDduHIqKipCQkIBHH30UzzzzjMdGaGgovv76awwaNAht27ZFdHQ0HnzwQU9JlfKISmybDiuDUURxUlF1ZOLHrNaONfWlVRvTtjKKk8yTr1lblfg3XWUxIpOxrKIeqKihrCxBEYWGdw9ZxXyJKFoq8WpGWyrjqMRjyfho1jbxAfn72MpPmZhQo02R4zFeW59s6kzf8Xhqu4zKZgXvuqiMw1Iajb9r3seub1NZledSg7JcSwiKCV1aWhrS0tIs23Xq1AmdOnVi7q9Xrx6MOSBRUVGYMWMGswDw9ddfj/Xr11uOXbduXXz11VeW7QiCIAiCIJwmKCZ0hPOw1AKZLDc7NatkVCRerTHdvugqE2Y+sarY8xQHo12eiigSU8OK33MiG5CnnLKuO6+mnIof+jlmjQtY1+czs2+lTsjEEdmJceK1tdougkgfq/g4EbtOZUqqqJGi8Nby5a3LqoKTWdQybyd0jPe38fhEEBkn2HHilSm9ciUIgiAIggggTqzFeims5UoTussU1pMnT42xUql4GavGTCwzBUXl6Vcl9swqbkdF1THG8oj04Y2popyoxGTpGK+7nfvAbBvreHhqi9W4ZtucyMgUQeY62KkPKKMIsuLjROyz/ubBOi5vO1axkzKqKC/bVcV/nYP9iwEAiRYKsZl9p1VXlj3emrF23rIQlxY0oSMIgiAIImihV64l0ITuMsMqRksmY42nABhjyljxUSLrcvKefllPoSp1yESQyapUib9RUQBkVCkrJcspxYGlpshk+omoFazYQ5V4JaewigFVseX0PSMzHuvc8tbrNSqwMlnhMm8PZNR21nnSlU2zYxdVi0ViTu0ojDI1MkWui9V4wQZN6EoI/jxdgiAIgiCIyxxS6C5TVOpDyTzdiWZGej+tMuPuwH66Z6kRIrXrVBQ01tO1nad7oHQcj0r8E2scbxWUldEralMUJ2pjiWb+ebfVj5lVl9AMFTXXqZhGK5xQGu2q1VYKIO/el6mbJzu+1T4jVr9fIrGgnu+pIV5RaJWR/9W7FImhtbQl0ddf16U8QQpdCTShu8wQ/XH2xmppLJXXgiL/kMgEUquUOhH5QWf1EXmFxPLXrK1xEfhSgeCwPva//7HZ7tPW7HW31atj3j9qrEB3s/4yk2UnkiJ0jOVXvMs9yPjE6qMC77tmNTHh3WesyavZNZb5x98KmeORsae63xuR77LRLu8c69sSBMqGsO4r3tJcVudL5R4V+Z2083qeKH/QhI4gCIIgiKCFFLoSaEJ3mWKlzHk/sRlLcthROFh+iLTlBSCrLAFl5Suv6K1IIDrrlbEZLPVB5JWhvs/4ulbllbiICsZS5swUBzslO0SwssMLJndyXDP7xmPnfW+sVCJj0WBvziWVLGUYOsl3n8hi9jJYvcYWuUdFSmrIhAOwzptIcoeI3yr3jaiKL6I0q/ghcm9eaq9eNdivI6dZNyn3UFIEQRAEQRBEkOPSjIubEgHj1KlTqFKlCtqjO8Jc4cp2nEhNF4nvkFFbnC6lwGpjRCQ5gmXDrooko2iqnB/RPiqxWt5YlVtwSm1zoiAq65ybJYaIwLp2/rqfrVQwXmyjv+KgWPZVvi8yCRr++k5Y+e29n1UQnWdTb2NUVUXOV6k4VT8p28bxnLR7UbuALHyBgoICVK5c2TG7Zuj/Zt769UCEVYy07sDh4pkirLx9dpn47S/olStBEARBEEELxdCVQApdOcIphU5H5OlLf4pMmBtq2VYkI1bHShmzo1LI2BOJ0bPKEgTYT8p2nnBFCuTKlF/RMWa78saWKcxsdcwqGYWi+1j7WX14MWdOqGs85caOcmpH9WapO6wxZcd1IgZNJo5QxKaMglpWGZ1WvsjEtNnJ1jU7Xtb33snlwgKh0LX/6nFHFLqsO2aRQkcQBEEQBBEISKErgRS6coTTCh0PmfgX0SdOkbpHMk+cRnhPkSwfePFfIhm+VvZ5OKGG2IkFMmsnqrLZ9U2lrUofUaVR1Vc7iqyxLS+mimVP5v6VuZ9lcFLZ4vnqRKyunT4yOP09MSKimFllqMqMG+wK3U1fDnZEoVvd7c2gVugoy5UgCIIgCCLIoVeulzkqT48i9adEn05lYuhUnh5l4vB4KoxoXI/TqpuI2iJzjmXiIJ1AJr7L2IeFt8+sFUF4NlhqhFkf46oYMt8X47EnzDXf743MeWLZcTrm1Mo3GSWKd9+x7Kh8p+zEaPLsiJw3fZ+dWFCRc2snBtTYVybzuzyiaS5oNl+Z2u1fHqAJHUEQBEEQQYsbLtuFhe32Lw9QDF05wl8xdDJ1lZzKpuL5YNXWCl7cjZ14OBn1SiX2zA5GdQSwrgsnEn9ltC8TB2kHkQw8kfhLO75YZfwB4t8TO1mpvP5OZL2qKFxOnWM7qKiIKrGOMj44kSGtkrlqtt94/8rE3Tl9nrwJRAxd8hdDHYmhW9d9RlDH0JFCRxAEQRBE0EJZriWQQleOUFXoWE9mTj2hG2NmWMqPSs0nFSVARqETwYnsUBHfVOA9oftDOTOzzcoc5t0P5U3VsWtPx1/qpNU+M4XWKr7OW2kU7cNDJpvWCQXTaruMDZk2Kt97VX/t9GH1lTkHMrGaogRCofvnZ084otBtvPu1oFboKMuVIAiCIAgiyCGFrhzhlEKnogA4WYfIDH/F6rAUOSee0M3i1WRqfRkVEpGMWxWVwklV0gwRRdYKO9eJhzFe0GpFD7NtMvekSryolS2ZNjIquIxyqvKbwWoHiGfC8q4Ly2feOLI+y7ZV6euEL7zvAuscBCqmLhAKXatPn3REodt8z6tBrdBRDB1BEARBEEELlS0pgSZ0lwAyVfJZT2IydYhElBNjNi3PJ5Z9EXVEpqaU0Te9thhrPO/zqqIwydTAM2L0iWeDdU1FFCDjeGZP+1bHoaLuGpU1b6yyd73R/RapKceyJxPvZeeelDlPIhm+VoisqCKjguqw6kR6t9O/WywbVtt5PvPGUVGYnFbmZL67VvZEFFqWCmqntlx5yHIm5KEJHUEQBEEQQYvmQJYrKXREucD4ZMbLXFKJt1LJWDM+ObMws2Xc9vcamOrxPT6+WcRZifgkMr6MAmSlyMgoTrxxrNQVketmVNXM7jPWOEbsxmyqXBcrGzLqhMy1FIlBVPHb6jttV3EUHV/leMzOtZ14rrLKLHU6Ns/qOni+T7COOeRhVIntKKflCQ2A3WyAskwmWLJkCSpVqoSbbroJAPDmm2/i7bffRpMmTfDmm28iNjZWyS5luRIEQRAEQZQR//d//4dTp04BAH7++WcMHz4cXbt2xf79+/H0008r2yWFLohhPQGy4tYAIHnaRgDAxqRQnzYyT/FW41vtY/nGapswN7RUW2Mf0SdPs75W48vY4LUx+m+3Bp/KuKLxljzfWCs5iGCndhnvnlKJT1OJobOyyevPuldlxla5r1Xsi1x/lfF48WWisWflKb5LJa5XJu6Od69Y3bdm4zhZq7Q84YYLriBa+uvAgQNo0qQJAOCTTz7BHXfcgZdeeglbt25F165dle2SQkcQBEEQRNCiZ7na/ZQVERERKCwsBACsWLECnTt3BgBUq1bNo9ypQApdEGPM1tQxPmV711PTlTmZ2mL+rNMkEufFa6tjJ6OLhUztMhF4T9DGa8WqeyfyJM0b1ypukLf+K0sR+DvGcbtnn5VS5jlOsFU+lupqdl2sVCMZJVDEFxkbxnOsEjeoEqtpB94945Rdb9uBgPUdEFEAnY7vY/nCW2fYSinnvdFg+S8TP0yoc9NNN+Hpp59G27ZtsXHjRnzwwQcAgF9//RW1a9dWtis0oVOZMQZrYb5gQqSQsHc7Xl8dM1vGiaPxH32ziaPKqz3RvmbjqCQgqLzeYk1EzMa3Kq5q9g+Hblcl4NzYhrf0k0ipFhZG3/RkFZEyKZ5/qAz3ktnYrAQNkUQEXltWX+51kXi4cKJshcyEweo7zJugiDw8+eMfdJmSOk6NI/pQafe1NssHkT6sh3Sz8jyiD8sq57o8vdYWwa254AqitVzfeOMNDBo0CB9//DFmzZqFq666CgDw7bffokuXLsp2hSZ0VatWhcslfrAulwu//vorEhMTlR0jCIIgCIKwQtMcyHItwzTXunXr4quvviq1ffr06bbsCr9y/fjjj1GtWjXLdpqm2QrqI/jw0vyNbVTUKV4gvdlTovd23ms6ladeltLBe03n76dJ1rGLKI0i6ouMWmClSvLUNhWFwfi3ndfQrHuJN44IIoH0rD5mbXivoFl9WPexzELoKscs88pdx07xax39lXvU9gqebVbHqKJamvVltZG5d1QKYztRXkZE5WWp/DI+qSjawaDKBTOhoaHIy8vDlVde6bP9999/x5VXXoni4mIlu0ITuoSEBNxyyy2oXr26kNHExESEh4uvRUoQBEEQBKFCsC39pTHkwKKiIkRERCjbFZrQHThwQMrojh07lJwh1JAp2cF6ehMpJ8FSZFRUJB2feLhM8/GsjkHER96TrUgcEev8OBXkLao08BRalpLGi20U8ddKieMlOKgoJzJlRVhtjcqGqpIimpzifY6NcZDGuEGj7yL+6ft5MYdOBejLopcVApxNTLITyyajAPK+Eyrfb7Pvndk4ZljFkZrd+zLfF+M2q98dM8qjehcsE7rXX38dQElY2ty5c1GpUiXPvuLiYnz//fdo3Lixsn3KciUIgiAIgvAzeoycpmmYPXs2QkNDPfsiIiJQr149zJ49W9m+S2Npfwz0GWYpQy4XoqKi0LBhQ9xyyy0+jtolJycHEyZMwMqVK5Gfn49atWrhoYcewujRo33kyU2bNmHkyJHYsmULXC4XWrdujcmTJyMpKYlpu6ioCCNGjMDChQtx9uxZdOjQATNnzvSkDmdlZSElJcW078aNG9G6dWvP8RuZNWsWBg4cKHycp06dQpUqVdAe3RHmEn9l7Y+yIt5KACvOhlXyAnC2NIOK6qWSHSiTFSbiq9UTs0gJAjuxbnZsqMQ46bFUwN8lTFhLgInEeerYibdi2ZT1xR9ZgTLlMWRts2DFi9n5DfE3dmI0/X08ZuOoKGYy9lV9NPPJie+WkYvaBWThCxQUFPi92oX+b2ajBSMRWiHSugOH4sIi7Hnw5TLxOyUlBZ9++qnyEl8spBW66dOn4/jx4ygsLERsbCw0TcOff/6JChUqoFKlSjh27BgSExOxatUq1KlTxxEnd+/eDbfbjbfeegsNGzbEjh078Oijj+LMmTOYOnUqAOD06dNITU1F9+7dMXPmTFy8eBHp6elITU3FkSNHmDF9Tz75JBYvXoxFixahevXqGD58OO644w5s2bIFoaGhaNOmDfLy8nz6jBkzBitWrECrVq18ts+bN88n5bhKlSqOHD9BEARBEOYEW5brqlWr/GJXWqFbuHAh5syZg7lz56JBgwYAgOzsbDz22GMYMGAA2rZti169eqFGjRr4+OOP/eI0AEyZMgWzZs3C/v37AQCbN29G69atcejQIc9E8ueff0aLFi2QnZ3t8dWbgoICXHHFFXj33XfRs2dPAEBubi7q1KmDb775BqmpqaX6XLhwAbVr18aQIUMwZswYz3aXy4XPPvsMd911l/IxiSh0KjWlvLF6auQ9cVrZ5PlrJ5aKN56TT+KiC8qb+WYsCGzWn2dfNAZQRtFy6imcFRPEUt14Y4qoFTL3G0slVslYPNi/JLPMu0CyTCymmX9m45jdK8a+dtRqGdVY5V6xg0w8pNV2XpvyEAOmktVqde/IqMiBUl0DodBd/b4zCt2v/yobhe6+++5Dq1atMHLkSJ/tU6ZMwcaNG/HRRx8p2ZVe+uv555/H9OnTfSZIDRs2xNSpUzFq1CjUrl0bkydPxpo1a5QcEqWgoMCnjEqjRo0QFxeHjIwMnD9/HmfPnkVGRgaaNm2KhIQEUxtbtmzBhQsXPMtuAECtWrXQrFkzrF1r/g/Cl19+iRMnTiAtLa3UviFDhiAuLg6tW7fG7Nmz4Xa7ucdQVFSEU6dO+XwIgiAIghCnRKGzu/RX2fn73Xff4fbbby+1vUuXLvj++++V7Uq/cs3Ly8PFixdLbb948SLy8/MBlEyKTp8+reyUFfv27cOMGTMwbdo0z7aYmBhkZWWhe/fumDBhAgDg6quvxtKlSxEWZn6Y+fn5iIiIKPUeOz4+3nMsRjIyMpCamlrqdfKECRPQoUMHREdHIzMzE8OHD8eJEyfw/PPPM49j4sSJGDdunNAx6/CUM5ZiwsvAM9qSyZDl9XUijkREPRBVHEXsy9REM/pizNA168NT/mQUIKN9ow2eTatxzM61SJamsQ9LjeRddz0GL2Gu+X4ZJdAIr4/+d6Lh+Hhtzewat7F808+JWfaxTIa36L0ic785EY9rZp91/UWupczvAKsPz75IJrkdRH5rrcZRie+0E9usGnMaKIIly1Xnr7/+Mi1PEh4ebkvYkVboUlJS8Nhjj2Hbtm2ebdu2bcPjjz+OW2+9FUDJq8769etb2ho7dixcLhf3s3nzZp8+ubm56NKlC+6//37079/fs/3s2bN45JFH0LZtW6xfvx5r1qxB06ZN0bVrV5w9e1bqGDVNM01yOHLkCJYuXYp+/fqV2vf8888jOTkZSUlJGD58OMaPH48pU6Zwxxk1ahQKCgo8n8OHD0v5SRAEQRBEcNGsWTPP+q3eLFq0CE2aNFG2Kx1Dl5+fj969eyMzM9OTaHDx4kV06NAB7777LuLj47Fq1apSrzLNOHHiBE6cOMFtU69ePURFRQEomcylpKTghhtuwPz58xES8vd8NCMjA8899xzy8vI828+fP4/Y2FhkZGSgV69epWyvXLkSHTp0wB9//OGj0l177bW46667SqlnEyZMwIwZM3D06FHLwslr1qzBTTfdhPz8fMTHx3Pb6vBi6JyOoRCt3yVqTxSVuBKRtsY+Im2Ni8o7nfnlZMaqWV/RjEU7WbsibUTsG9vKrJogglW8parq4mSWq0z8mIji7IQ6KXJNnYzNciKjWATjd9vpcXg2ROpaercDrOtDyvwmGbkcYugavDsKoRWibNkqLjyHfb0nlonfX375Je699148+OCDHiEsMzMTCxcuxEcffaQciy/9yrVGjRpYvnw5du/ejV9//RWapqFx48Zo1KiRpw2rzIeRuLg4xMXFCbU9evQoUlJS0LJlS8ybN89nMgcAhYWFCAkJ8VHW9L9ZsWwtW7ZEeHg4li9fjh49egAoeaW8Y8cOTJ482aetpmmYN28eHn74YaFVMLZt24aoqChUrVpV6PgIgiAIgpAn2F65duvWDZ9//jleeuklfPzxx4iOjkaLFi2wYsUKtGvXTtmutEKnc/78eRw4cAANGjRgxqg5RW5uLtq1a4e6devinXfe8alxV6NGDQAlpU2SkpLwyCOPYOjQoXC73Xj55ZexePFi7Nq1CzVr1sTRo0fRoUMHvPPOO/jnP/8JAHj88cfx1VdfYf78+ahWrRpGjBiB33//3VO2RCczMxMdO3bEL7/8gmuuucbHv8WLFyM/Px/JycmIjo7GqlWrMHz4cKSlpeG1114TPs5A1KGTsa/DGsesdp2xj52aUmYEOmvPiIyCIhPbZmbTX0oJz0+Ara6pZBaqxDg5hUqGrKj6whvHuN3MjtNqsaxPIgqaTEZxWSvaZjaciOuVwc54MueLtd6r028ERAmEQpf4znOOKHT7H36pTPz2F9IzscLCQgwdOhT//e9/AQC//vorEhMTMWzYMNSqVatUGq4TLFu2DNnZ2cjOzvYU/NXR56ONGzfG4sWLMW7cOCQnJyMkJATXXXcdlixZgpo1awIoKTmyZ88eFBYWevpPnz4dYWFh6NGjh6ew8Pz580sVRs7IyECbNm1KTeaAkkDGmTNn4umnn4bb7UZiYiLGjx+PwYMHO30qCIIgCILwRvvfx66NMuTPP//Exx9/jP3792PEiBGoVq0atm7divj4eFx11VVKNqUVuieeeAJr1qzBq6++ii5duuCnn35CYmIivvzyS6Snp/skSxByyCp0Vk/IKrFNdhQBkWwqEQXA6KuduBuRTEArlU+kjUpsI88Hkf1W6oqMYubv2CaZmDAnVzNQqUsns0qKGaJxcE4pNKzvoUi9Q5VxRTCqR3YUTadUfZXYRpk2rD4yvy8qPjkR46jfM+eSSsQOs9hDUfsBUejmj0aITYXOXXgO+9NeFPZ71qxZmDVrFnJycgAATZs2xb///W/cdtttln1/+ukndOzYEVWqVEFOTg727NmDxMREjBkzBgcPHsQ777yjdAzSWa6ff/453njjDdx0000+8WpNmjTBvn37lJwgCIIgCIIIFmrXro2XX34ZmzdvxubNm3Hrrbeie/fu2Llzp2Xfp59+Gmlpadi7d68n6RMAbrvttrKtQ3f8+HFceeWVpbafOXPGtNQH4QwyWVV6G94TmtWqCCLqlBHvp3ArtUimFpMdtcBfMUgyY8usQGHlg4qPZgqN8W8Zn0QUFCuFgTeuncxXo13dlojqxhvfaFfkOqiooKy+3v7rsFaE4Z0/K59UsmntXEuzcYx27Nzz3vZZfvorzlbmu2x1fzkVb8nC7HvCoqzjkkUIxNJfd955p8/fL774ImbNmoX169ejadOm3L6bNm3CW2+9VWr7VVddxayBK4K0Qte6dWt8/fXXnr/1Sdzbb7+N5ORkZUcIgiAIgiBksb9KxN9ZssbVm4qK2Etp6hQXF2PRokU4c+aM0DwoKirKtIDwnj17cMUVV8ifgP8hHUO3du1adOnSBf/6178wf/58PPbYY9i5cyfWrVuH7777Di1bWscsEeaYxdDxYoD8GQ9jN76DZ8+7j0ysC8sWz56dmDA7cTgi9mV8UskgNevrRLwNy76KDZUq9ryx7azlKlMbT0Uxl7HHyqbV15sFSsc5+Tsz1om+MjaciFcNBFaxbSq1PnkquJNKnRMEIoau3n+edySGLueRF0ptT09Px9ixY037/Pzzz0hOTsa5c+dQqVIlLFiwAF27drUca8CAATh+/Dg+/PBDVKtWDT/99BNCQ0Nx11134ZZbbsGrr76qdAzSCl2bNm2wZs0aFBYWokGDBli2bBni4+Oxbt06mswRBEEQBFG2aC5nPgAOHz7ss4LTqFGjmMM2atQI27dvx/r16/H444+jT58++OWXXyzdnTp1qid87ezZs2jXrh0aNmyImJgYvPjii8qnQbkOHeE8IlmuvNg243YZVLJBRcZzUs2ToTxkIcr4KKqc2cnaFbHP8804tjGDkadWGWtkmakUVhm+RpveY7Nw+hpanQOzsUWumbGPjoja50Q9uLLOqjQbV7S/vxRnO7GgZtj5vbSjspaVUscaJxAKXcLcMY4odAf7T7Dld8eOHdGgQQPT+DgzVq5cia1bt8LtduP6669Hx44dlcbVEUqKkFksNlgL8hEEQRAEQaiiaZpQzJ3Orbfe6ln6ywmEJnRVq1YVzmAtLi62bkQI48TTPe/JXVQVEd1nZde43+xp2CqWSSQDVyYLUSW+z46ap5JZarbdSr0RyaZUeZr3ZJBmsm3rbVj1x+IhH59ozFzltWHt926jkklo3G48B2bI+MTC850wGU9mhQCjHatsdG+slCAV5UxFiZLJDrWL1Xmx8zvDuyftKHVlFVNXrmL3AlBY+LnnnsNtt92GOnXq4PTp01i0aBGysrKwZMkS0/avv/46BgwYgKioKLz++utc25UqVULTpk1xww03SPkk9Mr1u+++8/x/Tk4ORo4cibS0NE82x7p16/Df//4XEydORJ8+faQcIP6G98rVLEjazisKmddnvIWuvW2pvErw9sNqCRuZ1H2nf2REX2/YTY6w45Od88WyqeKP2Xg6rFewPL9lfLG6V73tO3FdRILV7dhzIhFA5bWmlR1RH/2Nik8qk38nffMXZZUkYWU3EK9c6875tyOvXA8NGC/sd79+/ZCZmYm8vDxUqVIFLVq0wLPPPotOnTqZtq9fvz42b96M6tWro379+lzbRUVFOHbsGJ566ilMmTJF+BiEFDrvxWLHjx+PV155BQ888IBnW7du3dC8eXPMmTOHJnQEQRAEQVzSZGRkSLU/cOCA6f+zWL58OR588EGpCZ10UkSFChXw448/4h//+IfP9l9//RVJSUk+66QScngrdK6ON/rskwmGdkox442tCu+pVfTVp8hTt4wSJKJwiTzN89pZIRp87cTrbp4dEcXJidIgZkqw6FJ2vO+CSKkQfygXKqqOTMkWO+fc7nHaUX5kkgqs7i+Z18FO4YTqJfK75sSrVju+iCD6HQuYQhdtU6E7K6fQ+ZuzZ89izpw5eOKJJ4T7SJctqVOnDmbPnl1q+1tvvYU6derImiMIgiAIglDGycLCZUVmZibuuOMONGjQAA0bNsQdd9yBFStWePZHR0dLTeYABYXum2++wb333osGDRrgxhtLVKT169dj3759+OSTT4SK6hHmiBQW9vdTqtMKjZ0nThEVUSWO0KqvnUQHEfsiftpRJ0XsG+2JjCOqoJnZVYlXElEEyioezojIeHa+JzL3voyPogqN3Tgy1m+G8VqK/J45oZzz2rJ89hdlFd+r0seJmNBAKHR13kp3RKE7/Ni4MvH7jTfewFNPPYX77rvPk4uwfv16fPzxx3jllVcwZMgQJbvSa7l27doVe/fuxaxZs7Br1y5omobu3btj4MCBpNARBEEQBFG2BCDL1Q4TJ07E9OnTfSZuw4YNQ9u2bfHiiy8qT+iosHA5wiyGzk6Mm0qWo8o4/saJmECRvqwsW2+sFAeZscsqa9df8YMy47BwIg7Lu42/MxdZiMTDyZxjmRhXIzKZnqzxRXAiA9cuKoq2qE0Ruyrn2I56yOujEhet8haE9XupExCFbvZYZxS6gWPLxO+YmBhs27YNDRs29Nm+d+9eXHfddfjrr7+U7ArF0P30009wu93CRnfu3ImLFy8qOUQQBEEQBHGp0q1bN3z22Weltn/xxRe48847le0KvXK97rrrkJ+fjyuuuELIaHJyMrZv347ExERlxy53jE9Q+qLciQ9Yx/fIPDXK7Jd5ShVVTJKnbfRs25gUatrWzlO+iDInst14rCIZeCqqgYgCY2zrhAoici1ZfVh/i+4zYvQh0CqPiA9mS5hZqSB2z5fRvrFosB3lTEZttZN97G8lWERp0uEVNBdVnEX6qNjS0f8dAIDETP54dr4/IvemXhy8rNRYLkHwytW7mPA111yDF198EVlZWT4xdGvWrMHw4cOVxxCa0GmahjFjxqBChQpCRs+fP6/sEEEQBEEQhDBBMKGbPn26z9+xsbH45Zdf8Msvv3i2Va1aFf/5z3/w/PPPK40hFEPXvn174aW/dBYsWICaNWsqOXW5wlspQgR/xV3plNUTmJWiJfNUb0c9dCJrzAyz7Ecnr5Udv+1kuZnFkfk7A88fOB1vp5KF6oS6qxJzKtPWiXtW5D7zVyygiHJm5/rbibtz4pw6EXssaw8IUAzdTIdi6AaVTQydvxBS6LKysvzsBkEQBEEQhAKaq+Rj10YZc+LECbhcLlSvXt0Re9JlS4jAIPJEa0eZsxN3wfONF5fCwmpsu6qJVX89TiUB7Cd1q3Pvvc2oyOnxRCJKAC8GifVErpKx6sQ9473OsNV4RhsibY3n03tMq0w8mTWQVVQjEUWb19bq/ItcSxlli/VbYdZH1CeRe1Pl98VOrKHI91HGpsz3ROaecTIOlmdTNG4voPFwCmhayceujbLgzz//xOjRo/HBBx/g5MmTAEpev/bq1QsvvPACqlatqmybJnQEQRAEQRB+5o8//kBycjKOHj2Kf/3rX7jmmmugaRp27dqF+fPnIzMzE2vXrkVsbKySfapDV47Q4wFubp+OyO92AhBTAnSMT1VGdcesrZ1YGn/FtrBsiOCvuDcn4lOciAGzmxUo29fMjlHpMLu/WOM4fQ6sxrUTR2S2z4n72mib568d5VRFHZf5fVHBCSVYJHO1rL5j3mqxjsz5No7ppDLmtE3R70IgYuhqzxjnSAzdkaHpfvX7ySefRGZmJlasWIH4+Hifffn5+ejcuTM6dOhQKoFCFOm1XAmCIAiCIMoNegyd3Y+f+fzzzzF16tRSkzkAqFGjBiZPnmxan04UeuVaDgnN2o5iw0oRIutCGp+YeHFXMhll/qhdtX9hEgAg8YHtlsfBG1d0vUzvJ+lzSYX/G1tcBbG6DrzYI5lMMrN9Zn6YwTpvdp/QWU/mKmuUqiiaRlTir2TiFb2PS1QpU1FORWLOeLB88sQ0orQN1ji6mqcjc22N44r4KGJX7yNSX4/lg93rYoVT61lbff95aquVqiuiuopcy2CLqyuP5OXloWnTpsz9zZo1Q35+vrJ9pQndr7/+iqysLBw7dqzUChL//ve/lZ0hCIIgCIKQwaWVfOza8DdxcXHIyclB7dq1TfcfOHDAVsardAzd22+/jccffxxxcXGoUaOGT306l8uFrVu3KjtzucNby9UsXkkl7saJmBxjzJTTT25OxADZifOTydpj9WWNadbXDJGnbSv7Kk/oduKURBRaf8UritoSsSej6jihQIm0FfVHdmx/xTSK3vv+Un3sxI36K47QTjy0GaJvJ1TuZzNfrK6dvv/ixXP4IWtc2dahe3W8M3Xonvy3X/3u168fsrOzsXz5ckRERPjsKyoqQmpqKho0aICMjAwl+9IK3QsvvIAXX3wRzz77rNKABEEQBEEQlxvjxo1Dq1at8I9//AODBw9G48aNAQC//PILZs6ciaKiIrz77rvK9qUVusqVK9M6rX5CZKUIkac6Y+aVSNyFE4hk7RmfKp3KWOPZNdqQUeaMiD6leu8z+sZ7smbFFor4xqpZJ6PQsVRYEbzjsFjXwWhf5LrwUInvNMK7hkaV2G7WrFM2RNqabbdaW9XYV6SNv2OrdJ/12Neo7X8vQSlzHDoyx8P6/bIaVxWZaylrw2yfzO+K8feKtT0gK0VMn+CMQvfUGL/7feDAAQwaNAjLli2DPv1yuVzo1KkT3njjDTRs2FDZtrRCd//992PZsmUYOHCg8qAEQRAEQRCOEARruerUr18f3377LU6ePIm9e/cCABo2bIhq1arZti2t0E2cOBGvvPIKbr/9djRv3hzh4b5K0rBhw2w7dbniXYcuLKzkaUM0+9EbO4qWnRgqGXjrmbLgKU4qGV4sG2aIKnM8lcpO3JJMLBhLEQRKK28qCpRxfB2VODWnFQcZnIwFtBOzxfOlPKDim4xibsU/txcDANYN/2epff74bVK5/jKrlzgdDyujTov+e6Jy/vRzUFx0DnumP1e2Ct0rDil0T/tfofMn0grdnDlzUKlSJXz33Xf47rvvfPa5XC6a0BEEQRAEUXYEkULnT2iliHKE2UoRIvFwOlZPxYB4lqZIVqixr1lbXsyUlY/GNv566pbJyHTyidbMrkzmMmulBpE4NTtP4Kx7kBc/6GRmtIiywfveOHkN7WREqyCTsWiGTB1F1j5/qKLe+3Sczrw12jXem07VerM6TzIVC2Swc1+LHI9oLHBAYuimOqTQjQhuhc7WShGapoHmgwRBEARBEIFFqbDwO++8gylTpngC+q6++mr83//9H3r37u2oc5cr3itF8LINjU9kLOVERD0QqWlkpYaYVdjXq7urxP75q0aWcTyRNUlZfY327SooOsbq+GYw495atWGOL6oemN0HMjGB+jYrZc5bSRPJAmYdl9EHkSxElThLFmbHwcyQhHpMoEpmrPfxqawzarSnklEqE69oRLTemoiP3mMa7Zn9Vul2VL7LrD5OVR0QjTl2qm+p86VwL/kNJ5bu8vPSX9dffz0yMzMRGxuL8ePHY8SIEahQoYJ1RwmkX7m+8sorGDNmDIYMGYK2bdtC0zSsWbMGb775Jl544QU89dRTjjp4OcErWyLzakfkH1qrH0+Z1wG814FWr+dEfHP6x84qocGpkipWr0DsTHKtxrbq41RSgtV+JyflZuftYP+SgHmzJeRkx7czIfHX63nWvckbR2XSZ0QkyJ81voh9EYx27RQaN/PJH5Mou+P4I4FK5jdD5neN9XAWiKSIupNfcOSV66Fnnveb39HR0di7dy9q166N0NBQ5OXl4corr3R0DGmFbsaMGZg1axYefvhhz7bu3bujadOmGDt2LE3oCIIgCIIgvEhKSkLfvn1x0003QdM0TJ06FZUqVTJtq7qEqrRCFxUVhR07dpQqfrd37140b94c586dU3KER05ODiZMmICVK1ciPz8ftWrVwkMPPYTRo0f7LJ+xadMmjBw5Elu2bIHL5ULr1q0xefJkJCUlMW3PmTMHCxYswNatW3H69GmcPHkSVatW9Wlz8uRJDBs2DF9++SUAoFu3bpgxY4ZPu0OHDmHw4MFYuXIloqOj8eCDD2Lq1Kmllvfg4Z0UcXRgiUKXMDcUgPNBxFaKg1n5DatxVZQgu32MfVlt7SqBVsdsVpBX5ilb1CeZp22e2soan4fM6zNWX964okkETiundhRtEawUDUBcdRJ5tVsesCqLpGLLX8V8RZBRzkTvX1XV2GhX5TdWR+Tcyib5BCIpou4khxS6Z/2n0O3Zswfp6enYt28ftm7diiZNmiAsrLSmZmcJVWmFrmHDhvjwww/x3HPP+Wz/4IMP8I9//EPJCSt2794Nt9uNt956Cw0bNsSOHTvw6KOP4syZM5g6dSoA4PTp00hNTUX37t0xc+ZMXLx4Eenp6UhNTcWRI0dK1cvTKSwsRJcuXdClSxeMGjXKtM2DDz6II0eOYMmSJQCAAQMGoHfv3li8eDEAoLi4GLfffjuuuOIKrF69Gr///jv69OkDTdMwY8YMP5wRgiAIgiCChUaNGmHRokUAgJCQEGRmZjr+ylVaofvkk0/Qs2dPdOzYEW3btoXL5cLq1auRmZmJDz/8EHfffbejDrKYMmUKZs2ahf379wMANm/ejNatW+PQoUOoU6cOAODnn39GixYtkJ2djQYNGnDtZWVlISUlpZRCt2vXLjRp0gTr16/HDTfcAABYv349kpOTsXv3bjRq1Ajffvst7rjjDhw+fBi1atUCACxatAhpaWk4duyY8Gxff9po9NRLCI0sedrgPeHaKd5pRwUTecJ0ojyCle/eyMTXiD5ti6hhdhQhM6yemFVUMLP+Mkogaxx/xc4xkwlMklas/C2ruD6zfSwfVBRbFfXQjo8i8Gw4GQtmRPW6qaiGdn6TZPo4Ed/Hsm9X0ZR9o0EKXeCQLlty7733YsOGDYiLi8Pnn3+OTz/9FHFxcdi4cWOZTeYAoKCgwGepjEaNGiEuLg4ZGRk4f/48zp49i4yMDDRt2hQJCQnK46xbtw5VqlTxTOYA4MYbb0SVKlWwdu1aT5tmzZp5JnMAkJqaiqKiImzZwv4yFRUV4dSpUz4fgiAIgiDEcQFwaTY/Zezzvn37MHToUHTs2BGdOnXCsGHDsG/fPls2lcqWtGzZEu+9956tge2wb98+zJgxA9OmTfNsi4mJQVZWFrp3744JEyYAKCmnsnTpUtP31KLk5+ebyqJXXnkl8vPzPW3i4+N99sfGxiIiIsLTxoyJEydi3LhxpW1vK0Lkd77v0M3KWKjEp4g+pfJsiah6RjVFJEaLZY/nm95GH0/kXDDj32Dto0p8l4xyZqVo2lUTWPuciCOTURx4ioaxDS++x0qltpuByTp24z3jvV9UMROJH1VRZI2Kpuo9aQejuqryW+WEjypximZYKY4qKqiKeszLPjb+nqm8rZChPMVsBkPZEm+WLl2Kbt26ISkpyVMtZO3atWjatCkWL16MTp06KdkVUui8lSOjomRHYRo7dixcLhf3s3nzZp8+ubm56NKlC+6//37079/fs/3s2bN45JFH0LZtW6xfvx5r1qxB06ZN0bVrV5w9e1bKLyMuV+kLrWmaz3aRNkZGjRqFgoICz+fw4cO2/CQIgiAIonwzcuRIPPXUU9iwYQNeeeUVTJ8+HRs2bMCTTz6JZ599VtmukHQVGxvrqZlStWpV7uSluLhYePAhQ4agV69e3Db16tXz/H9ubi5SUlKQnJyMOXPm+LRbsGABcnJysG7dOoSEhHi2xcbG4osvvrAch0WNGjXw22+/ldp+/PhxjypXo0YNbNiwwWf/yZMnceHChVLKnTeRkZGIjIwstT00azvwvzp0LAUKYCsaxv0imXEi8TDGfbynVBVFzthXJH5MVNkwe5rUt7GKH/tk+mb67HI0Ngwwv77ebVWydXXMMpZVlFmjfaNqLKJSOBm3BLALF6vEk5rB6sfL/LZSJ3k1Gu3EnIn4xkJFPRQ5p0ZfZL7TTiBSKF3mt0ImNtC4TSQW1OrYecfDqqMp8lvOQ/Se1PcXXzwHZH1haddRgmwt1127duHDDz8stf2RRx7Bq6++qmxXaEK3cuVKT7zaqlWrlAczEhcXh7i4OKG2R48eRUpKClq2bIl58+Z5Jm06hYWFCAkJ8Zls6n+73W5lH5OTk1FQUICNGzfin//8JwBgw4YNKCgoQJs2bTxtXnzxReTl5aFmzZoAgGXLliEyMhItW6pPbAiCIAiCsCDIJnRXXHEFtm/fXqoyyPbt221lvgpN6Nq1a+f5//r166NOnTqlVDpN0/z2yjA3Nxft27dH3bp1MXXqVBw/ftyzr0aNGgCATp064f/+7/8wePBgDB06FG63Gy+//DLCwsKQkpICoGRS2KFDB7zzzjueyVl+fj7y8/ORnZ0NoCQzNiYmBnXr1kW1atVwzTXXoEuXLnj00Ufx1ltvASgpW3LHHXegUaNGAIDOnTujSZMm6N27N6ZMmYI//vgDI0aMwKOPPqqcLaOiZLCeOHkLk4uoPMYnP6sMVjN7InEdVk+L/spYNNpnqQtmbUR81PEoZa3YCo0TMUbG7WbLhzmhTojEHMpgpSSJKLTG7WZ9rVRJ77YstVNEBWF9L0Wuu0rWIyuGyqn4KDsxlDLjsOyqxD7yxpK591lxiSrxsSp9RWJPZZYuZC0tKKOYqizJRpTw6KOPYsCAAdi/fz/atGnjqRYyadIkDB8+XNmudLZA/fr1TZes+OOPP1C/fn2pV66iLFu2DNnZ2cjOzkbt2rV99ulVVxo3bozFixdj3LhxSE5ORkhICK677josWbLEo5pduHABe/bsQWFhoaf/7NmzfRITbrnlFgDAvHnzkJaWBgB4//33MWzYMHTu3BlASWHhN954w9MnNDQUX3/9NQYNGoS2bdv6FBYmCIIgCMJ/6Jmqdm2UFWPGjEFMTAymTZvmqX9bq1YtjB07FsOGDVO2K12HLiQkBL/99huuuOIKn+0HDx5EkyZNcObMGWVnLndE1nL1hvXEKaKGydYW4vki8vQoYt9O7SoZxUx0HJG4KJFxnMg6c0qJlLl2RqxiZ2T6OO0bazwR31TiiozIxNDx+ljFwZqp7Vb3l0qmp4raZjam6Coz3vucuPdlfmdk7IjEQ7Kui4zaJvJdsBNvKfN7aaXEGfcHog5dvRdeREiUzTp0584h5/nRZV6H7vTp0wBKKnXYRVihe/rppwGUZHOOGTMGFSpU8OwrLi7Ghg0buEtsEQRBEARBEH/jxEROR1ih0+PQvvvuOyQnJ/usURoREYF69ephxIgRflv+63LATKFz8umLZ4dXz8uOYmZX7VAdTyRrT9YPM59UFAcR+1bjsMY0s8/LcmONI7KWr51ra+e68OwacXocFZ+cUpZUx/fGiWsmsl9EjVL1Rwans2hF1FY74/njnvnn9r/DoDYmhfr08YePAVHoJjik0I0pe4XOSYQVOj27tW/fvnjttdeC9oAJgiAIgrh0CLYYOn8hnRQxb948f/hBeFHcPglh3+0036egNPDqqXm2Myrts7aJ+mZVyd8bq+xDM1i1nVRs6djJNFWN9/KHoqGSqejZ36pNqX1OqEcyWZo6KveO0aaISmlmyyqWiXc8KjGaMsfB8tFo0y4qMW1OqPoycar+UB7N2rDaOh3bKpNBavVWYmOSf+JujfvLSvkm2CitibVp0yZ89NFHOHToEM6fP++z79NPP3XEMYIgCIIgCEuCaOmvCxcuoHPnznjrrbdw9dVXO2pbekK3aNEiPPzww+jcuTOWL1+Ozp07Y+/evcjPz8fdd9/tqHOXK94rRfCyqXRk6l6xnqaMSpdMDBXvCc3JSvFm58DqCVa3f7D/33EkiQ9s5/aRUQKM501VQWHVhRLxidVG5p6x8tW7rYqyIYLeVuYcsMYzHodMRqnduCsnFA0VVc8JpURkNQPR7Wbwzo2ooinSx46KaJYVLPI911Gpz8b7zbZCJX5UJa7X6rdC/5tWiuATHh6OHTt2cJcFVUVoLVdvXnrpJUyfPh1fffUVIiIi8Nprr2HXrl3o0aMH6tat67iDBEEQBEEQlwoPP/wwMjIyHLcrrdDt27cPt99+O4CStUjPnDkDl8uFp556CrfeeqtPkV5CjeL2SXCF+WbsqDyxycStGOOUZKqO854EZWLKWL55lBsbsVTeqpxoRixPQWM9SYs8DZv5bxUDKKOcsK4pzyfjfpZKxuvLi78UUVtkFDNjGyfUQ5E4NZFramVXJTbTTD0yrtThhFInkuUugtV3yqNimdxndo7DiVhDs99a1u8v77uscp/ZuSdZipnd2ENZZVbTLljadJpgS4o4f/485s6di+XLl6NVq1aoWLGiz/5XXnlFya70hK5atWqeQnhXXXUVduzYgebNm+PPP//0WYGBIAiCIAjC7wTRK1cA2LFjB66//noAwK+//uqzz86rWOkJ3c0334zly5ejefPm6NGjB5544gmsXLkSy5cvR4cOHZQdIf4mNGs7Qg0rRejsX5jk+f+EuaHm/W3EApn1FX3SFFFbjPDG0VUxXYlQeaLlnQs7sYBWtgDrWBqe4sFSJ/0F73rZiYfzxNVIXBcrm2bIXEtWG5F4K9Z4KrFaIsfOU49Er4vI74DI8aj4zfLRTvamDLxjN96bxv28sUV/38zgvdEw/maI/JazfLRzP/vEEWaatyHU0cvAOY30hO6NN97AuXPnAACjRo1CeHg4Vq9ejXvuuQdjxoxx3EGCIAiCIAgmDrxyLUuFTic7Oxv79u3DLbfcgujoaGiaVrYKXbVq1Tz/HxISgmeeeQbPPPOMsgOEHGaqnJXioBJzJhODItKf9QToHRNm7CMSx2cno5AVxyOitvGOw+i/SGyY1dO2nfguM2T6sJRSEYXWSVXPDqqZfjLXgWVHxQYvxswKme8YazvvHMicNxn1UNQ3nzhCQ9apzG+digIoqtjx7Nl5E2CG6G8Hr62Iglqulbkge+X6+++/o0ePHli1ahVcLhf27t2LxMRE9O/fH1WrVsW0adOU7Aov/eWN2+1GdnY2jh07Brfb7bPvlltuUXKEEFv6y+zHzIjMDxNrYW+RH1reKyTWD6zIj6hMiQBRVF4/O3U8IsHYTrzasZMQYOWrlV0rZF6JiiatiNgTKd1iROY4RZI7ROzamfyxxhW5F1UmNTLfTzuTJdY4Ir9NKr6IXEsr37z3iYZpmGHnuEReIVuNY2eCGoilvxKffwmhNpf+Kj53DvtfeK5M/H744Ydx7NgxzJ07F9dccw1+/PFHJCYmYtmyZXjqqaewc6f5wgJWSCt069evx4MPPoiDBw/COBd0uVwoLi5WcoQgCIIgCEKaIFPoli1bhqVLl6J27do+2//xj3/g4MGDynalJ3QDBw5Eq1at8PXXX6NmzZp+KY5HmCho/3v1wnt94lHvWomrEkaVT6WAMcsf722sp1EzxdGqPIlTrypZiATUW/U1Q+VViMi4eqJMwlxzX+wGbKtgpQSIvOLV73neuWG98tbbqhR3NbNj9TpQ5Fo68WqP14Z17VRea/IQSfJR+R5avfbj3ZMiqqgdhdnYlxcOIlPyiTWOyL0j+lsho2ia/f6L/A57/x2IwsLBVrbkzJkzqFChQqntJ06cQGRkpEkPMaQLC+/duxcvvfQSrrnmGlStWhVVqlTx+RAEQRAEQRDm3HLLLXjnnXc8f7tcLrjdbkyZMgUpKSnKdqUVuhtuuAHZ2dlo2LCh8qCEOCLFdI1tebBi5njjWSkAIk++rCdNkaBvYx+fZckyzdsaEQmk5gVyiypWvCdokXFkApx1jMqcjtlyYqIKo0hMGK+PKGb3mZ0SLTKB4TIqkh11TVThEBnH7DhYqrqIqqOru8bl8FTUNhmFXiWmlXc+Rb4noqqxU4qmTCylTFyfsY/K7wyrj0wimsg5J8yZMmUK2rdvj82bN+P8+fN45plnsHPnTvzxxx9Ys2aNsl3pCd3QoUMxfPhw5Ofno3nz5ggP962X1qJFC2VnCIIgCIIgpAiyGLomTZrgp59+wqxZsxAaGoozZ87gnnvuweDBg1GzZk1lu9JZriEhpd/SulwuT/0USopQR8/Yubl9OiK/s85yEVUNVLPCzPp7IxPfYSczTkUR/Of2kvtw3fB/WvotY1dU4eD18VYLdaziklRiAHVEzjUPFVWPtU/kPvBHJq7d+C4WTlwfb4z3pqdkjMSSb1btVFG5r6zOtcpvEy9ekXe+WOPw4oaN+0TUV9Zx8O59lRhg0RhNs2L0MueABWu8QGS5NhjlTJbrvollk+XqL6QVugMHDvjDD4IgCIIgCGmCLSkCAE6ePImMjAzs2rULLpcL11xzDfr27etT61cWpTp0hH8wq0PHg6V+sJ4mzfrqiDxxWvWRUVtUsvhkUFGeZNQDkSdaFaVJJZbGCp6iYTWuiC8yMU12+oj4IrvfCieUJjvn2o6PIm3tKE52z60TOKFG28kKtXPuRQiUfRkVuTwodA1HvoTQSJsKXdE5ZL9cNgrdd999h+7du6Ny5cpo1aoVAGDLli34888/8eWXX6Jdu3ZKdoUUui+//BK33XYbwsPD8eWXX3LbduvWTckRgiAIgiCIS53BgwejR48enhg6ACguLsagQYMwePBg7NixQ8mukEIXEhKC/Px8XHnllaYxdB5jFENnC2+FztXxRgB/P/0szf0RANCx9yOl+lmpR07Fqdjp40S8mtWY3m2diNWR8UUkjlDmqZe13V/qDssfVRuiSiAv+5hlXyT2SISyVpj8pWSLjuttR0apE1WYVTI/Zb4vKr45FadmNZ6IPSfUNu/vi/77zvu9N9pg7bOyIeo3ECCF7lmHFLpJZaPQRUdHY/v27WjUqJHP9j179iApKQlnz55Vsiuk0Hkv72Vc6osgCIIgCCJQBFsM3fXXX49du3aVmtDt2rULSUlJynalkyKIssH4NJRa69qS7bBWq4xxXd62rGpWWdWp827LU4/8nXFnZc+sBpsRmWM29rEaX7WP8ZzaURpFlDMn/JdRII2I3Gc8G1bHwztOFQVFJKvZaE/UV1Ws4jlFxmFdUzNklGdWH1U/je1UYgKN50slhk7kvrIT38c6HpHfKJXj4f2bwaI8xFAGEz/99JPn/4cNG4YnnngC2dnZuPHGkrdx69evx5tvvomXX35ZeQyhCd3rr78ubHDYsGHKzhAEQRAEQUgRBHXokpKSPCXedJ555plS7R588EH07NlTaQyhGLr69euLGXO5sH//fiVHCPMsV5VMPzsZSjxEY1xkbIjYF/HZyYxSsz5WbVXqOPH6q9TtM9bgUskOtXOOeYhk09lRHGXOl6hvdts6CU8FNyrMIqquinpkda+YxXcFCqfi4kRjznhj+zt+WCVeWea3VcdYP5N1jQMRQ3f1CGdi6H6d6r8YuoMHDwq3TUhIUBpDSKGj2nMEQRAEQRBqqE7SZKAYunKKjKJhpWh5r30aD/OnalZMnQgyT8F2FBqRODIRtVI0Lkbm6VjmSd3MrlXGmtl1KuUDJ15QxSdRG8btZvYP9i8GACRmlm4rap93n8mseWxE5tj9pfwZ+xjH48Vq1RI4p7Lje4/H8t+43Xt1BitfzL6fVgqzSKyuyHfX6vvvs1Y043fRuBKFyO8Y7ztnFdcnY4+l2Jr1Zdky28daA5tls0wJwCvXiRMn4tNPP8Xu3bsRHR2NNm3aYNKkSaUSHVgcPXoUa9aswbFjx0olm6qGrklP6O677z60atUKI0eO9Nk+ZcoUbNy4ER999JGSIwRBEARBENIEYEL33XffYfDgwWjdujUuXryI0aNHo3Pnzvjll19QsWJFbt958+Zh4MCBiIiIQPXq1eFyuTz7XC6X8oROeqWIK664AitXrkTz5s19tv/888/o2LEjfvvtNyVHCPkYOqsnJDvxd3aVCCfjO/yFTNydSjalVeaa2T6VWDAnVTbjflm7Ok6uDem0b3ZwMjvYrC0r41omY1lkzVCWT3ZiXEXassY1g6XyycQRmvVTeftg9SbD7n3ojzhFmXMg8+bE6jcqIDF0TzsUQ/eKegzd8ePHceWVV+K7777DLbfcwm1bp04dDBw4EKNGjeLW9pVFWqH766+/EBERUWp7eHg4Tp065YhTBEEQBEEQIjhZh844j4mMjERkZKRJD18KCgoAQGgt1sLCQvTq1cvRyRygoNC1bt0ad955J/7973/7bB87diwWL16MLVsC+B49yOEpdGbYedpy8mnbbFyVLErWuCzfvbdZZYla+SvrG8tXnhpiNb6ZHTtxKiqZkSK+GduIKLSiii1rbFXsxrF5Yv8E6s6Jji0SD2m1XbaNbJ+yUkFFrj/vOyFzvkR+EwDzGLqyVidlcEIllDkeKwKh0DV60hmFbs+rz5Xanp6ejrFjx3L7apqG7t274+TJk/jhhx8sx3rmmWdQrVq1UqFrdpFW6MaMGYN7770X+/btw6233goAyMzMxMKFCyl+jiAIgiCIoOXw4cM+E1ERdW7IkCH46aefsHr1aqExJk6ciDvuuANLlixB8+bNER4e7rP/lVdekXP6f0grdADw9ddf46WXXsL27dsRHR2NFi1aID09He3atVNygijBTKHj4Q8VTKesYpNklACVp0g7Wa6qvvDGFrUvMo7T6p1oW5HMaBk1V9SnsoqtFFlfVgWn/bdSjeyoLnbjR3n2RNs6ec4BuRVhWL6IvK2wE48s6odT9nRYKjJgnUFeHmLoGj3hkEL3mnwM3dChQ/H555/j+++/F67ZO2HCBKSnp6NRo0aIj48vlRSxcuVKaf8BxbIlt99+O26//XalAQmCIAiCIJwiEGu5apqGoUOH4rPPPkNWVpbwZA4oUeD+85//IC0tTW5QC5QUuj///BMff/wx9u/fjxEjRqBatWrYunUr4uPjcdVVVznq4OWEiEInEz8io06JZFdaxYTxYk+sfDbDKovPexyjPZmMUpkafE7ExYhkgIrEulllNToVF6OSfWrEyXhF3phlnfVqhhPZuk7Ec7Js2+0jc2/KjCt6DlRVMSczfK1sm+HEbx/PJ9FYZ944LF/NYPkWCIWu8TBnFLrdr4srdIMGDcKCBQvwxRdf+NSeq1KlCqKjo7l9a9SogR9++AH/+Mc/bPlsRHpC99NPP6Fjx46oUqUKcnJysGfPHiQmJmLMmDE4ePAg3nnnHUcdBICcnBxMmDABK1euRH5+PmrVqoWHHnoIo0eP9sm43bRpE0aOHIktW7bA5XKhdevWmDx5MpKSkpi258yZgwULFmDr1q04ffo0Tp48iapVq0qP7S2Z6syaNQsDBw4UPk67S38ZsfMPucwrFxE7Rhtmrz/88UqNt5i6E6+BeDZUlu9iYecH1u4/tKKvqkReuao8bKggM2l2KgnGqq2OUw8bKq+1WT7J9DXa4CUgOFFaQ2SColLuxeirWbKEyutm0VffMr+xvEQaFrxraDxm3nc8GJIiGg91aEI3Q3xCZ/ZvPlBSY85KeZs4cSLy8vLw+uuvq7jKRPqV69NPP420tDRMnjwZMTExnu233XYbHnzwQUed09m9ezfcbjfeeustNGzYEDt27MCjjz6KM2fOYOrUqQCA06dPIzU1Fd27d8fMmTNx8eJFpKenIzU1FUeOHCkVdKhTWFiILl26oEuXLhg1apTS2Drz5s1Dly5dPH9XqVLFwbNAEARBEISRQL1yVWXjxo1YuXIlvvrqKzRt2rTU/OTTTz9Vsiut0FWpUgVbt25FgwYNEBMTgx9//BGJiYk4ePAgGjVqhHPnzik5IsuUKVMwa9Ys7N+/HwCwefNmtG7dGocOHUKdOnUAlBQ7btGiBbKzs9GgQQOuvaysLKSkpJRS6ETGBkpm65999hnuuusu5WMSeeXKe93oL1WirPoY++o4oaDYfb0lE3BuxycVJUDUBs8nlg2eHX8djxOvtcsap45dpZyMmQ9mfphhpQha9bfyyQp/vXaWGdvfCq2xj47IGxSVAt1GW3rpHcC6/I6Ioml17IFQ6K4Z4oxCt+sN9cLCMvTt25e7f968eUp2pRW6qKgo0wLCe/bswRVXXKHkhAoFBQU+BfwaNWqEuLg4ZGRk4LnnnkNxcTEyMjLQtGlTxxfFNY6tM2TIEPTv3x/169dHv379MGDAAG7hwKKiIhQV/S3zU2FmgiAIgpAkAEt/2UF1wmaF9ISue/fuGD9+PD788EMAJcrUoUOHMHLkSNx7772OO2jGvn37MGPGDEybNs2zLSYmBllZWejevTsmTJgAALj66quxdOlShIUpJfMKjw2UpCF36NAB0dHRyMzMxPDhw3HixAk8//zzTFsTJ07EuHHjhMbVn4rMFsDWn5RYT3FOBSvLPJXaeapWCTy2o5yJjGfHPssuT22Tib+TOV+isW0qMUFmfqjEaqosf8by1V99jIgcO28cz3c407ctzz7r++BR+TJ9/wbYvxH6uTZThEQVU5W4SBWVSiS+0+ml52TuEdbYxvNoVh7HiIz/3va8baoUxVb5vQkoQTah8xfS605MnTrVs2bZ2bNn0a5dOzRs2BAxMTF48cUXpWyNHTsWLpeL+9m8ebNPn9zcXHTp0gX3338/+vfv79l+9uxZPPLII2jbti3Wr1+PNWvWoGnTpujatSvOnj0re5imsMYGgOeffx7JyclISkrC8OHDMX78eEyZMoVrb9SoUSgoKPB8Dh8+7IifBEEQBEGUT+rXr4/ExETmRxWlsiUAsHLlSmzduhVutxvXX389OnbsKG3jxIkTOHHiBLdNvXr1EBVV8m48NzcXKSkpuOGGGzB//nyf15n6q9a8vDzP9vPnzyM2NhYZGRno1asXdxyrGDre2GasWbMGN910E/Lz8xEfH89tqyNbWNjjG2PZK145AV72pxGr+B6VJzaZmB07sWEiMUfJ0zYCADYmhZqOb4aKKsZDtCyCSiauCjIZq7w+MuMYEcl29Ne9IYoTMUdO+yZzr+jfaRk11IkYTbt2rcbREVEn7Xy3ZJRAnvLM+81mIaN+s/o6mRmvE4gYuiaDnImh+2Vm2cTQvfbaaz5/X7hwAdu2bcOSJUvwf//3f8pLgim/i7z11ls9S3+pEhcXh7i4OKG2R48eRUpKClq2bIl58+aVmlAVFhYiJCTEJ5VY/9vtdtvy02psM7Zt24aoqCjLBAuCIAiCIGwQZK9cn3jiCdPtb775Zqm3kjJIKXRutxvz58/Hp59+ipycHLhcLtSvXx/33XcfevfuzazLYpfc3Fy0a9cOdevWxTvvvIPQ0FDPvho1agAoKS+SlJSERx55BEOHDoXb7cbLL7+MxYsXY9euXahZsyaOHj2KDh064J133sE///lPAEB+fj7y8/OxefNmPProo/j+++8RExODunXrolq1akJjL168GPn5+UhOTkZ0dDRWrVqF4cOHIy0trdRMnEcgCwuzbADiBXhVMhZF4khEsvWs6lCpxIT5G178mMgTv8o5Fomz9O4rMr5TNaxEVUozP2X6lnXmtZ14OJnYRiN2MiTtIno8vH16dqb+FkEk9tRoS8RHJ2IBZe4vp+M87cSciowj629AFLrHHVLoZpWNQsdi//79SEpKUk6QFFboNE1Dt27d8M033+Daa69F8+bNoWkadu3ahbS0NHz66af4/PPPlZywYtmyZcjOzkZ2djZq165dyi8AaNy4MRYvXoxx48YhOTkZISEhuO6667BkyRLUrFkTQImsuWfPHhQWFnr6z5492ycx4ZZbbgHwd3FAkbHDw8Mxc+ZMPP3003C73UhMTMT48eMxePBg508GQRAEQRAeAlGHzh98/PHHphU0RBFW6ObNm4cnnngCX3zxBVJSUnz2rVy5EnfddRfeeOMNPPzww8rOXO6oxtA5GXejw3sSdGJxazP8GXsk8gStEktjp493fA+rYrsTypDM07aMoqnik45ZdX6RmDnV8byxE6NZVqqXlY/e24y+GZVuFXVa5U0Ab+k/mWvpZCxdWX2XeedYj1eO2l4BQNll3gYqrjQQCl3Tx5xR6Ha+VTYK3XXXXefzRlPTNOTn5+P48eOYOXMmBgwYoGRXWKFbuHAhnnvuuVKTOaAknm7kyJF4//33aUJHEARBEATBwLgAQUhICK644gq0b98ejRs3VrYrPKH76aefMHnyZOb+2267zfF1yQg+vDUIvZGJ7+Dt94cqIfLkqRKrJ6IIGtvyVArRDF8RZUPH7HzGQ12NYt0PMlmhIkqQMTNSVyAS5oYy+xjh3UtOxjLKZKGK2BGJ0RS1xetjPMciShBPmWNt86hqrayzzlnfEx2Z3weR+8yIjDoqEqsn8hthHJP5XQD7O5b4gPibB9a5Nutjdb7MfBPtazeTPCCUg1emoqSnp/vFrvCE7o8//uCW34iPj8fJkycdcYogCIIgCEKESyWGzi7CE7ri4mLuiguhoaG4ePGiI04RYjihFrCQySiVGZf3VGzcJqOCWSlOPF9Y43tjVR9K5ByIHIdKHCFLPeK1ZW0XuYZGJciYhSgyvkxcjw5P1VG5/jJtjD7xVB4rZVlkPBUVSuXescos97ZjFZ8mcj/buR5GtVLEF7vX3+rth9l1sqoKwLtnWNdURHE0jqOyLi/vvJVbZS6IMJZWM8PlcinPpaSyXNPS0hAZGWm633tNUoIgCIIgiDIhSOrQffbZZ8x9a9euxYwZM6C41gMAiSzXvn37Chn016KzlwOyWa7G7DLRGmNA6actszgoVlsncCrb1U7WpnE8Y1uz+m0yKoXM8fhDXXVaBVOxL4OIIssa1+lsYDv2RWNAZZRGJ66pSB9j7J53f5nVZYzY6WvEbnyXyPUwYnZerMZz4rfCyqZZXzvZ2ryMZVECkeXavP9LCI2wmeV6/hx+nlv2deh2796NUaNGYfHixfjXv/6FCRMmoG7dukq2hBU6mqgRBEEQBEHYJzc3F+np6fjvf/+L1NRUbN++Hc2aNbNlU3ktV8J5VOvQ6TihNOj79SrtALtSu0hGqb+zqZyoc+VE3SuVrD1ROyxbooqWmR2VFSlYvsiorSrIZDmz+or0EWnLOlaeAmzWxthO9Dw5nX0ocw95qzYA/94p6++lSPwma2yZ300Z35xQsmXeTqj8HvtDbQ+IQtfPIYUuw/8KXUFBAV566SXMmDEDSUlJmDRpEm6++WZHbCuv5UoQBEEQBBFogiXLdfLkyZg0aRJq1KiBhQsXonv37o7apwndJYTIk1ophSYTpn0SM9njqGR0GvtatfP2kRe3IhqnxOvjRMyeSlycjELDU0z0OlMiWZTGDDiVGDrv2EJvWyL+8869VVaoiuJgN1vP+H1hrZcpEnPIsyGq6vFgxYCK1PwTyW7UfytUYF1Dp+IIRc6T5/wzaj2K3JOivoog8h0Tyey180aDtV1k/WdCnpEjRyI6OhoNGzbEf//7X/z3v/81bffpp58q2acJHUEQBEEQwUuQZLk+/PDDlmVL7EATuksA49OVJ+v1f0/UZk+crKcu3lO9TByRlT2eEmRUBIzj8Z4eVdQXnVJZw16KhMxxGGE9FXv/zbLPyq4za6sSU2fmi9nfZuPKxC1ZjWc1Jms/S5GzE3tkhpUyxxtHx4nVMWRiAVVWbhAZR+Q+Yx2PyHHK9LWTFWzcZ/a9Z2EndlbknrFz7UT94PkWdKpckEzo5s+f71f7IX61ThAEQRAEQfgdUuguQXhrebKwUsW827BidMyeUq0ULZEYKpaPInZl4q949q0qxqs8qYsojUZfVFQxGZVCRtnirRVptC+ifjiR5agSrygTRyZzf7HGM/OJNQ6vxqTVtVOJ71KJOTXDKn5PJU7VuN+sDa+vlepk9h1nXV+WugeYvxmx8o0Fr4/oihQqqGRgB5JgSYrwNzShIwiCIAgieAmSV67+hiZ0lzBmWaKsp22R7EAjvPg1J+yzkMnAElHmjG1l4rtEjotll7fWokgcnEr8mNU4MmqeTHaryComKrFHxmMWOS6rNjKZlzz7rL9l7hURxZz1N09BVVHdrNQqbxu638YVIkSyKe3EfqnEj+rY+U3iKfj+ijlkKXOs8Xl2g0GFI6yhCd0lAOvLKDNhEPkhFH3FY7ZN5DUtaxyjLbMfT54vRpsiPhiRKcRr9Inlo+g+b3ivXvTz4nn904o9oXfiWoogM3m2mhzzfLO6f53+B0vklShrbJUHBydeO5shkwigMq5xqS/jNVQpTsz7LvOQeZ1t1Vfmesig8rBp516/VCZyLk2Dy+YaCXb7lwdoQkcQBEEQRPBCr1wB0NJf5Qq7S3+JYCcwV0cmyFvH+DQs8yqUN47KazrRc6Dio4hvRoUAEFcL/aXUGH0yU/WMOLl8mEhfEfVQxT5rHNY2sz5m2Lm/7LymM7a1owjz7PL8cOJ3xghPUVNR3UTGFX2Fy3vlLnLvOJXAYOWblQ0nFLtALP2V9NCLjiz9tf290WXit78ghY4gCIIgiKCFslxLoAndJYz+1HWwf7FnW8JcsT7esFQQmUQHVmkLmUQKFXhxSlYqCG9cVhyeTPA9r/yKHUSSIVh9jMuI8Wzwjp1l37jknIyPMrFnMoqdiF0reyKxTca2IudLdLv3eDz7rPvWqMzKxDY6Dev7ea5/kmUfXgkdloqnEnOmEgfJU7RFlWARXy+VuDgp6JUrACosTBAEQRAEEfRQDF05wukYurKOoVGJCRLxSSZj1bhdRHFg2VLJ9LWLnWxaER9E7evlJgB2yQmWbRH7Orw4ItZ19x6HtSSXyJiseCvecfgre1Y0I1JE0eb5ZnWPy2RRysQ2smJoVWJbZXwz22dlQ6SPjA2WLZVMcpnvC88Hp3+3vAlEDN31DzgTQ7d1IcXQEQRBEARBBAZ65QqAFLpyhb+yXEWyAnn7najBZDWumV0nxmPt5/lkJwZN5AlaRDF1MpPQW3HSYSklKufc6Qw90XuUZ8cpJcIJuyrX0kpFBqxjGGViQY21HWW+AzL3Ps++k3FkMqi8PXDymtr1kVWHUkW9doKAKHS9HFLoFpFCRxAEQRAEERAoy7UEmtBdpqg8BZfKVPyfQmAWl2WlFjitVhn3GW1413zjLdPDQtQHGd94+1htRWpX8WLE9H3+yCg2881KAVI9X8Yxra6HSoyT2TbRWDeeb2bbra6DMbNYxEcR5Uwk1tEq7tLsnLAyYz0KYyv2bwZrPKffHrDuQZn7TeTYrWzxfOAptPp3yqjUGv9WfWsQVNArVwCU5UoQBEEQBBH0kEJ3mSGqaMhgVOq8tznxBKgS02ZEZa1NER9EnthFzjXrPNlR0MwyGWUUKyMsZYNnyxjHw1McjT6KINrW7FyroJIpKWrDzB5vhRXRe0PkPhO5hjL+s+zy4rp4KqT3fhEllYeVSiXyeyOj1JmtvmJln+UDT23X4WX4Gwl6Zc6LS+GVqV1oQkcQBEEQRPCiaSUfuzaCHJrQXQbYzcAy7mM9aYrE9xi3m9U7U4k9YT058/qw7DqdhWZHEeL1tZOhKBqz5b3P6ryIKCc8Gx41KpM7jCky2cfGfcbVK0QysUXUIqt70sx/q9hDnk8iiMZQ8RQnoy3e+WKpU7w4QqvxZBBRNGVUcFZMm5ly5vm9hPhvrYovrPGIyw+a0BEEQRAEEbRQlmsJVIeuHOGvOnTeqNSsEu0jo4JZtZPFTpYba7/3Gri6eihqW8QXlXgokT524vqsxgTYKyyY9bFzDoyYqT1WiondGE4r5U+kr8h1EVVMZeLhZK4/73uposxZjSPzm2FEpY93P5FVK1h97XxveBmrKvcrK1Yu0JmrgahD1+reFxAWbq8O3cUL57D5k+eDug4dZbkSBEEQBEEEOfTK9TJDJrvNiFU2mErsFs8XlXgVXlujXavM0kSvWC47yiYLkZgzFeVUBZ4tozLGiusSUdtE7hnW8RhjkczGZtUuM2vLUmq8axayai3yzpdo3TbedTPakFG0VOKuZFQ3EZVdNKaRpwTy7Bv7yPyusa63WewZ67dORNG0+i6L/DbxtrPWGebFYQZKtfM3LnfJx66NYIcmdARBEARBBC9UWBgATeguO4xPcVZZaN7YebqTUfNY+0Sq2qu0FYH11KuihoggkuWoYl9F1bE6VpmsUDvxfTLnmtfXo5D8T4E1qmFmWbYiqxYY27KUQB1eJjErU5GnCMpkO8soWqL3mdkqBiylSSXuVub7I6IaGu8DmVg63jhWKqiZLavfR5V4Rad/A4nyD03oCIIgCIIIWijLtYSgmNDl5ORgwoQJWLlyJfLz81GrVi089NBDGD16NCIiIjztNm3ahJEjR2LLli1wuVxo3bo1Jk+ejKSkJKbtOXPmYMGCBdi6dStOnz6NkydPomrVqj5t6tWrh4MHD/pse/bZZ/Hyyy97/j506BAGDx6MlStXIjo6Gg8++CCmTp3q4195wPgUJ1Pnyir2SKaPjkwMXyCxyigzOz6VuCvj+ozGGmlmsJ7unYqHslJGzMYrFZ/EUPlksvnMFAdRdYqnhsgoGSyFmxfXabx2djImzWK1rFbjEEFGlWL5L6Mmi2CVJazaltVHBDvnmGVLxheZPoHOdi1TqLAwgCDJct29ezfcbjfeeust7Ny5E9OnT8fs2bPx3HPPedqcPn0aqampqFu3LjZs2IDVq1ejcuXKSE1NxYULF5i2CwsL0aVLFx9bZowfPx55eXmez/PPP+/ZV1xcjNtvvx1nzpzB6tWrsWjRInzyyScYPny4/YMnCIIgCIKwIGjr0E2ZMgWzZs3C/v37AQCbN29G69atcejQIdSpUwcA8PPPP6NFixbIzs5GgwYNuPaysrKQkpLCVOiefPJJPPnkk6Z9v/32W9xxxx04fPgwatWqBQBYtGgR0tLScOzYMWZNm6KiIhQV/f1Ue+rUKdSpU8evdeiMiGSJycQnsZCJPZOpxWblAy9z0QqRuCI7+LumnFlbo6LEUr9Ua31Z+cCrYeekyuKUCiY7nvc+0WxXb2SyKVWwup/K6nspghNZr7z72Ik6ejKZ9yJcCqpaIOrQ3XDnBEfq0G1YPCao69AFxStXMwoKClCtWjXP340aNUJcXBwyMjLw3HPPobi4GBkZGWjatCkSEhJsjzdp0iRMmDABderUwf3334//+7//87xOXbduHZo1a+aZzAFAamoqioqKsGXLFqSkpJjanDhxIsaNG2fbNzvI/ENo9Q+tyGst3o+o6KsdEZ+MtsxeB6mU1JDByn+nXwcZ+5qNowfbs8p8qIwjE3zPW5ZINDDce7txuTCR19wsv0UmATKTTdY9zwqSN4OVVCLS38xHq+8Lb1Im+tBh5gNrfO8HLdYrW95xWj0oml13ll2Re0Xkdb2TEzmR+8zqweGygLJcAQTJK1cj+/btw4wZMzBw4EDPtpiYGGRlZeG9995DdHQ0KlWqhKVLl+Kbb75BWJi9eesTTzyBRYsWYdWqVRgyZAheffVVDBo0yLM/Pz8f8fHxPn1iY2MRERGB/Px8pt1Ro0ahoKDA8zl8+LAtPwmCIAiCuDwJqEI3duxYS4Vq06ZNaNWqlefv3NxcdOnSBffffz/69+/v2X727Fk88sgjaNu2LRYuXIji4mJMnToVXbt2xaZNmxAdHa3s51NPPeX5/xYtWiA2Nhb33XcfJk2ahOrVqwMAXC5XqX6applu14mMjERkZCRzf3nDjuIkYsuOIqairjnxektE0RRpK6J6suzLBGiLHrO/1EnR15EitoDS5TFESndYKUsq9w7P31LHnGndx0oZ4iHy2lFGbWe+Ns/0tcmDNZ73uVBRqWSKN7O+LzLfYVYfuyEKKq/AdawKDF8OUJZrCQGd0A0ZMgS9evXitqlXr57n/3Nzc5GSkoLk5GTMmTPHp92CBQuQk5ODdevWISQkxLMtNjYWX3zxheU4Mtx4440AgOzsbFSvXh01atTAhg0bfNqcPHkSFy5cKKXcEQRBEAThIJTlCiDAE7q4uDjExcUJtT169ChSUlLQsmVLzJs3zzNp0yksLERISIiPIqb/7XY7u6bHtm3bAAA1a9YEACQnJ+PFF19EXl6eZ9uyZcsQGRmJli3tp7cHGtEnZ5EgfycC3M1iXKwW3BZ5glZRvKx85+2zG7DNwmhLZBFwYwwVL/bIOI6IGsJLhrBzPKJFj1XVVlZ/Y+yWdyyYxzdDvCAvrk8lflBUYRSJbeNtLxU3lmneVkWp88ao/LHg+ei0ciZaFsfu2wmjHREV8XJU4gg+QRFDl5ubi/bt26NOnTqYOnUqjh8/jvz8fJ/4tE6dOuHkyZMYPHgwdu3ahZ07d6Jv374ICwvzJCUcPXoUjRs3xsaNGz398vPzsX37dmRnZwMoyYzdvn07/vjjDwAlCQ/Tp0/H9u3bceDAAXz44Yd47LHH0K1bN9StWxcA0LlzZzRp0gS9e/fGtm3bkJmZiREjRuDRRx8N2mwZgiAIgggG9Feudj/BTlCULZk/fz769u1rus/b/eXLl2PcuHHYsWMHQkJCcN111+HFF1/0vCLNyclB/fr1sWrVKrRv3x4AO45v3rx5SEtLw9atWzFo0CDs3r0bRUVFSEhIQK9evfDMM8+gQoUKnvaHDh3CoEGDShUWlomR01Owy7JsCQu7JRXK+unRH2UqVJQAGSXIzC6rjVPn0UrRlBlPRH2zamOmoFhlLoqoLnbuTRHl1M71UCmX4RRWWae88a2O3Uw5ZY0jc3z7FyYBAKK2VzC1LWuPhT9+Q2SRKe9UXglE2ZLkLuMdKVuybsm/qWyJv0lLS0NaWpplu06dOqFTp07M/fXq1YNx/jp27FiMHTuW2ef666/H+vXrLceuW7cuvvrqK8t2BEEQBEEQThMUEzqi7DFTNGRUHNEnS/3pG/j7CdxOnJXME7NVGxmVQib+TuapW+S4VOpQGduqLOem/82rLWccz+irSuaiCKwCyoD1wvE8nFDmVFRcmRhE3nkyLsUmg5XfPOVMRNFmtUl8wPo7wLqWMvGWInF3IvegHXXd+P1zOibwUoWyXEugCR1BEARBEMGLWyv52LUR5NCEjrDEiQxCFglzQ73+klcNWIj4ZpW9KdJWZjwRmzKKgL7PToV4lrrn7YexfpqdDD9eDJ0Ro8piph6y1BCjCme33p0MKvXtrGKneLXrjPDuIavVGERq5Rn7yGRGs/qKIPJGwGiPd91Zx8M7DpHvp9X9I5MRz8s+JwgjNKEjCIIgCCJ4oaW/ANCEjlBAptK6VRvV+mAsX1h2zWJPrGo+edcWk6lIL9pGJhZIRs2TeYrXFRueQiQabyUTd2fcz2vDUw9FfDBut6pZaNbP6jhElFSeDdY5FomhsrJvprayxuOteWwVZ2lW79Doq9GmCLxzYLQv8r33R+ykTGybnd8xsz6k2hE6NKEjCIIgCCJoccGBpAhHPAksQVGH7nKhPNWh88bOk6CVeiBT88sJP7yxE++mojjIqAcyx6xyXlixcyq198wQ9UVG2RDJjLTaLtJG5BzwfHZCORGpR2altskomXaVclmcUpytMrztripiJ2NV5f66FAhEHbq2HcYiLMxmHbqL57Amc2xQ16ELipUiCIIgCIIgCDb0ypWwxI7aohIzJ7p+onFMnn3veDijXTvKk9PZtDpG5YGnRKg83Rtj54x14XyUDcjHP1qpEyJ11XixYEZUFEeRa2kV0ygTfyeDUU3yvh46Vpm7IveMTCyblX2Z+m0yiiOvr9U58LZldcwiWbRGn2Qyb0XuYx2V2pKXM4GoQ/f9999jypQp2LJlC/Ly8vDZZ5/hrrvusueETUihIwiCIAgieNEc+khw5swZXHvttXjjjTccOQQnoBi6ckR5jaFjYSe+xMyGTGyLlT2RGlkqsTROKHROqTkydcFYyCiBrPHtxPeJZCF6q6ss3/wVEyZqV0TVNY7HywplqV8q96RIrKbK8TiBSiydUzFoKuumyijMVjZErmUwKnWBiKG7KcWZGLrVq9Ri6FwuV7lQ6OiVK0EQBEEQQYtL0+CyqU3p/U+dOuWzPTIyEpGRkWZdyh2k0JUjgk2hcxonM8p4T/Uydcj86asZMtmzdupqlccMPNFYRpXjM1PD7Ki5KhmYvOtkRzU22lOJUzRiVoPRTga20Uez/Spxd06o1OXpTYMTvgSaQCh0N9+S7ohC98P340ptT09Px9ixY7l9SaEjCIIgCIIoRxw+fNhnIhos6hxAEzrCAVRqsKm0MYsnYT31Gv/mrfqg8lTP6itiV+WpWyYDVyQ2yErdU8l+lFEpzNp5FKVMc194MWEs+/rf3tecFZekj69n9Zr5JJJNq/tkZ7UEketipTTz1mNlXR9eX5XviROZpXpfs3NvdRy8OEWRcyx6zCJqqxO/gYQ5Tr5yrVy5ctDWoaMJHUEQBEEQwQut5QqAYujKFZdyDJ1MpppK3JIT2WAy9eh0jEqASAamRwkyqZHF8oXnL8snEexk4MrUFnMiS0/Glkpb3pq1KsduREZpNLJ/YRIAIGFuaKk+KhmrMlmaMrGArLFV7m8R/B1z5pSf5XU8fxCIGLpbbvq3IzF0368eL+z3X3/9hezsbADAddddh1deeQUpKSmoVq0a6tata8sXVWhCV44I9gmdSkC9zD9qdnxyyjbrHxDepEAl0YGFyFJGTkzSRILvWTZ5bVg2ReyLYCzAKzLBNo6r8spNBF6ihtW1tBOo791XdKIr8lpbZCLnRAKSiJ9OJSVZ2ZIJRRB9QAXslUEpbwRkQtd2jDMTujUThP3OyspCSkpKqe19+vTB/PnzbfmiCr1yJQiCIAgiaAnEShHt27dHedPDaEJHOIbMqxenimtaPf0mT9sIANiYFAojrL76663EB7aX6sMaR6Q4KU9NYAXzG8+X2TlgnR+VV3ssf8z62ikNIeKPiLJhPEaZIrEsH8wULd2undfyRszUXCfOqfGVvnc70QLGMuOZYUyukCmTw1KrzGyoKHNWyTa874uIOu1JwGrFV0O9bZkloRCELDShIwiCIAgieNG0ko9dG0EOTeiIMkFG0ZApjGr1hG6mzLH66uMmPmAjKYLzpC2jNMnEblmVx+CVLRHZbqUE8Y5ZRpmxik/kqZMyyhxLkTG7R61iv0TKY4jErclcD6t9etkVkXPBSgSRGVclwcnMFk+FNrMpM46ZvyLfE1G7Pvtb8ZNsgnE5r/KOy13ysWsj2AkJtAMEQRAEQRCEPUihI8oUmSd/7wKvgNxTOE89slLBzDJWrcYUie+zU/BXJvtUJgtRRm0xYlQgeL7ZKUbLU8ms1Cje8ciohlZteSVPRGKorMaViV9zGhWViuWvnexmkb48X0XvEbMYPStVjZexbPSJd68QitArVwA0oSMIgiAIIpihwsIAqA5duSLY69CJIKI8WD1J85bxcsI3nYP9iz3/r2e8surNmR2PMQbQrDgsCyfqdDld80vm2I3YqaMmYoulhoosTC9zL8qonywbvCXsWH1ExhHB6rulkhntVL070fECgUxsq0yNx0uRQNSha996tCN16LI2vVgmfvsLUugIgiAIgghanFzLNZihCR1RpvAyy0Tjrnj1u4x2RZ6K/64759sm0ST+jpXBaIz3M2urK3MiKoixFp5I3T4RlUcli9ZY441nn7VPpg6h0YZKHUJWO5G2Vv2tEI23VFk4Xr8vgNLZ2HaOS+R7KbPqg4pyLnrP8BR6O28AZHxTyT6+1JW5gEIxdAAoy5UgCIIgCCLooRi6csTlEEMnghOxJiqxTiwFwmyflS3vse3UnZKphefvGB07qxiIxBOxVi3wVmS898v4xlPoROKhjH1V1FCnsROrxWpjZ1UWb1QyVmXOrZVdkfqAVn1Z2wg+gYihS7l+FMJCbcbQFZ/Dqq0TKYaOIAiCIAgiEFAMXQk0oSMCiplyYueJ3Ij3E7oOKxbMWLPO26ZxTUojZuqCVR01mYr3MvXb/IWVjypxat59WPW5ePFlVjXljOuamsE7LqsMXpUsRzN46rCVHyoqEss3O6uyyJwLlftZJrNUJcvZuN17HyuOkFZ9IMoTNKEjCIIgCCJ40eBAUoQjngQUmtARAcVuxiFLXfFUZeesJMDKquX5KVpt3qytjEohkxUqWltMtY0RVlvvWDfWeecpZ8a2njYmGcRGe6y+KgqNN6y4Pp4NFbVVP0Yrn+zGd7HOv0z2sQ5P/fRHHKxM5irrevF8ErFvVOr1Y7ebRU3YhLJcAVCWK0EQBEEQRNBDCh1R7hHJelPJ9LNSTlRqj3n3sRNfIxNjVFZZwVZtZY7TbD1bo12Z2EOjDZUVIszsG+3InHOr+DunskNZShbPJ6OCKnOOdVhrLZv1EVnH2KqGnMz3keUHbx/Pvp3MW6IMcANwOWAjyKEJHUEQBEEQQQtluZYQFBO6nJwcTJgwAStXrkR+fj5q1aqFhx56CKNHj0ZERISn3aZNmzBy5Ehs2bIFLpcLrVu3xuTJk5GUlMS0PWfOHCxYsABbt27F6dOncfLkSVStWtWzPysrCykpKaZ9N27ciNatWwMAXK7SjwezZs3CwIED1Q6a8CCShWbMZhVRaFjj2Ik98/6bF/sF+PrMUy7MxhWBp7bIqIfGtjJxhMZxZeKgZFYxYNkXUXOduO6842Eds7cNzzk2xGixYgMB9j0jooYZ4xNlYuhkzrXMfWalFvLuZyfiRe36TxCBJihi6Hbv3g2324233noLO3fuxPTp0zF79mw899xznjanT59Gamoq6tatiw0bNmD16tWoXLkyUlNTceHCBabtwsJCdOnSxceWN23atEFeXp7Pp3///qhXrx5atWrl03bevHk+7fr06ePMCSAIgiAIwhw9KcLuJ8gJ2pUipkyZglmzZmH//v0AgM2bN6N169Y4dOgQ6tSpAwD4+eef0aJFC2RnZ6NBgwZce7oSZ1TojFy4cAG1a9fGkCFDMGbMGM92l8uFzz77DHfddZfyMdFKEWLYrXcm+lRvprqwsidl4qHstJWJPRJRw1hqjkicmkx2qAxWKqTKOeDZt4p1Y9kBxI5T5hyrKIAyiMZKipwLmftMxQ87Wbx21DYRFZxi6NgEYqWIDk1GICw00roDh4vFRcj8ZWpQrxQRFAqdGQUFBahWrZrn70aNGiEuLg4ZGRk4f/48zp49i4yMDDRt2hQJCQmOjfvll1/ixIkTSEtLK7VvyJAhiIuLQ+vWrTF79my43fwoy6KiIpw6dcrnQxAEQRAEIUtQxNAZ2bdvH2bMmIFp06Z5tsXExCArKwvdu3fHhAkTAABXX301li5dirAw5w4zIyMDqampHhVQZ8KECejQoQOio6ORmZmJ4cOH48SJE3j++eeZtiZOnIhx48Y55tvlglNPx1Z2ePXCWG29n+6t1DVeLBjrb5G1KUXqnhlt8Hy1UkrMlA+Wgqnb2L8wCQCQMDdU2G+RDE/WigG8encisFQb3goUIhm3RmRqpFndXyo18sxsWcUyml1/lYxUKwVNpdajiB0ns8WJAEF16AAEWKEbO3YsXC4X97N582afPrm5uejSpQvuv/9+9O/f37P97NmzeOSRR9C2bVusX78ea9asQdOmTdG1a1ecPXvWEX+PHDmCpUuXol+/fqX2Pf/880hOTkZSUhKGDx+O8ePHY8qUKVx7o0aNQkFBgedz+PBhR/wkCIIgiMsGt0OfICegCt2QIUPQq1cvbpt69ep5/j83NxcpKSlITk7GnDlzfNotWLAAOTk5WLduHUJCQjzbYmNj8cUXX1iOI8K8efNQvXp1dOvWzbLtjTfeiFOnTuG3335DfHy8aZvIyEhERtp770+UIBNDJWtL1Z5KW6vjMK436w1rVQPvzEhWbTc7vqpUy098YDtzHysDUyZjVUdFHROJneSpSaL3isz9JRITKBJv6UTWpnEcM5VS9H72xqrmn4xvZn2t6hqKxGYSRHkmoBO6uLg4xMXFCbU9evQoUlJS0LJlS8ybN88zadMpLCxESEiIT/kQ/W+rWDYRNE3DvHnz8PDDDyM83DphYdu2bYiKiuImWBDOYfXjzCvDYNbGap9VKQeztvo+zwSrlXXZEjv/kIhMAo2ITAJZvvm8DrYYU+QfdpV/yI2+2Q2+17cZX7WzJgf+womHA8D6daZIUoxMORGWfeN2nl2ZiZ3IcnEyk2aayAUHVIeuhKBIisjNzUX79u1Rp04dTJ06FcePH0d+fj7y8/M9bTp16oSTJ09i8ODB2LVrF3bu3Im+ffsiLCzMU0fu6NGjaNy4MTZu3Ojpl5+fj+3btyM7OxtASWbs9u3b8ccff/j4sHLlShw4cMD0devixYvx9ttvY8eOHdi3bx/mzp2L0aNHY8CAAaTAEQRBEIQ/obIlAIIkKWLZsmXIzs5GdnY2ateu7bNPr7rSuHFjLF68GOPGjUNycjJCQkJw3XXXYcmSJahZsyaAkpIje/bsQWFhoaf/7NmzfRITbrnlFgAlr1e9M1kzMjLQpk0bXHPNNaX8Cw8Px8yZM/H000/D7XYjMTER48ePx+DBgx07B4QcMuoBq49ZAoJMAWPjeLwgeSv1QeQ1sFVRWjOfWNvNFDYrpUSlSDEPq+vk3UYkuJ9lhxfcL+oj7/4SsSuqBPGO3Vic2E55FJnzJlPE2Xjv+CjBDFVXxifj61+Z5A6CCHaCYkKXlpZmWibESKdOndCpUyfm/nr16sFYdm/s2LEYO3aspe0FCxYw93Xp0gVdunSxtEEQBEEQhMO4NcBlU2Fzk0JHEOUKGaXGSqUwK8NgVFnsKE5myolezoOXNGBlT2QckeWh7IzLimkTWdDdKsbRbtkRVn8VBU3k2J1MQDDbd7B/MQAgart5O5HzpRLbZvSNV1aEdW963w8qsa0yhZit+hBBDJUtARAkMXQEQRAEQRAEG1LoiMsWmVgaZhkRhxft9i606z0e629vX6yyBL3hLUPFQkXRYPXhFaP1h3IiUyJE1S5rm0g5ESMyPiYKZhTz7MkUlvZXCR9jaRiR82ZlV6QYMXEp4ERSQ/ArdDShIwiCIAgieKFXrgBoQkcQtrL2jOgxcEDpODgZZcOOKsLL2rRS/HixhirniakWtmpTqo9HobHIdvTOjORlNZr19W7Din+UKZAsgowKKjOuVUybSsyhTB06ox8yds18Y113J5VhgriUoQkdQRAEQRDBi1uD7VemlOVKEMGPSuV7lrrjrcrJxE6pxFmxbPDi++yoK6xxeDZYfc2WixJdmom3CoVMpqTKag8q8WN/Zy7L17uTUYtVsk91WMut8XyRUXd5bfyBE0ucEUGE5i752LUR5FCWK0EQBEEQRJBDCh1B/A9erJCV+iVSg0sk+5QFb41KGdXNmElYartFxiRvHLPjYdW7M65qYIZRZZFZAcNOdrAZrLFFsnWjtlfw6WNnJQoZFUykRp6KTyylzmxlFSv1W6Y+pNkxqNQUJC5BKCkCAE3oCIIgCIIIZiiGDgDg0oxrYREB49SpU6hSpQraozvCXOGBdofwwolaXDpmqo7oyg0q8Wq8NixE+srULmNtN1N1nFBodMxW3rC6ljKrJNiJCXO6Phyrj896qQzlSj9Peh1Eb5tW96ZTdf1YiqwRymAt31zULiALX6CgoACVK1f261j6v5kdrxqIsJBI6w4cLrqLsOLo7DLx21+QQkcQBEEQRPBCr1wB0ISOIISwyiiUUXfMVBJR9YNXg03Ud5592f7e+0XWZTVuNzsGo3pnPDciCo3eN2Eu+xyJxNmxzg8v7s6Oasu6D+ysyuAdp2is5affi7y1g61UY6dUatGaggRRCg0OTOgc8SSgUJYrQRAEQRBEkEMKHUHYwMmYKp4do4Lj3YaVMWonJowXqyVSu86JmmWseC+R2DOeemnlk1lcn3FslUxllg3AepUEkSxq43bjeLI+idoTqdvIUql551qHasoRltArVwA0oSMIgiAIIphxuwHYLAzsDv7CwjShIwgHsKvMWdWs49VrM6odrBpzPDs8pVE0fsxOHB6vLSvuy6yNTOyZSg0zFfVLpfaaneMRUdus6g3KZFN7q2w6VvbNFGcWpMwRhBg0oSMIgiAIInihV64AqA5duYLq0F2ayMQcycRDHexfDODv2mEifVTq0JWK1XNQMfFWd1hZjrzadVZ9dfQ6a8DfGZ0idc7srEWqUkeNVUOOlw1sZcup4+HZNdpm3TNOxZoS5ZeA1KGLewRhIRG2bF10n8eKE/8J6jp0lOVKEARBEAQR5NArV4LwMyr1u1hrt3r3STTEKRnj78z6iK7gYLZSgFXGp4wSqLdVWUPUG9GVNRIfYMeT2TkOUT+tbLGui379ZfrylFSr8yRyDpysR0cQjkBLfwGgCR1BlAtES3aY9eG9ljNi9Y+x2cTCaFdlGSyRch+idq0C7gF+0L1VaRjeuZcpxCxTukV0AiwynsjrTavj4CXSiC7R5d3G6CtBOImmuaFp9rJU7fYvD9ArV4IgCIIgiCCHFDqCKIdILcnVqkQx4ZX1sLJfqjSIlyoj+ppOpo0dpYs3jg7r9TDPB/2YRV65iiQXWClzIsWCZYo5y7xCtjq3PLXXjhJMEH5B0+y/Mr0E8kNpQkcQBEEQRPCiORBDRxM6giCcwI4SZFRMVMqLiBSclSk5obL0l5UN3vJnVoWZeWPLLHvmpPKkl50B/i6lwvJRZnkt498iSTGi+3m+EQQRWGhCRxAEQRBE8OJ2Ay6bSQ2XQFIETegIohwjon4Y1RtWVqoZMkViRft6b9ML+pqVDREdR0ckq1Ila9MYNygSb8dDtK13QWhR5YyHzL1CEJcU9MoVAGW5EgRBEARBBD2k0BHEJYJKwVcR5YfVR8Ruwlz5vjqsTEwnVTJArVaaSPFeGR/MsotFfbKznBbFwxGXAprbDc3mK9dLoQ4dTegIgiAIgghe6JUrAJrQEcQli51abyJ11VSWzJKpq2ZEpe6dWVyhTF04YxsdmQxilm9m9lTUNlLVCIIAaEJHEARBEEQw49YAFyl0NKEjiEsUOyoPbxUD49+8emcibY2w1EI7qyXwUKmRJ2LPym+RGnkq4xHEZYemAbBbtiT4J3SU5UoQBEEQBBHkkEJHEAQXK9VLRmmSUducWF1CZLUEFXVSBZlafzKrfZAyR1zuaG4Nms1XrtoloNDRhI4gCIIgiOBFc8P+K1cqW0IQxCWIv+O7zGzpbfWabMYVL4ztVH1TaWulKHrbtOojEvOmkkVLEETZM3PmTEyZMgV5eXlo2rQpXn31Vdx8880B8YVi6AiCIAiCCFo0t+bIR5YPPvgATz75JEaPHo1t27bh5ptvxm233YZDhw754SitcWmXwovjS4RTp06hSpUqaI/uCHOFB9odgvAbMpmxMvY8Ky4YFC5v28Y2Rl/0+DUzO3agbFTicuCidgFZ+AIFBQWoXLmyX8dy8t9MFb9vuOEGXH/99Zg1a5Zn2zXXXIO77roLEydOtOWPCvTKtRyhz60v4oLtotcEUZ4pvngOAKBpF0pt0/HeJ2qvuOh/3yFDX2/bxjZGX4qL/m5rtGMHs2MmiEuNiyi5v8tSK3Li30zd71OnTvlsj4yMRGRkZKn258+fx5YtWzBy5Eif7Z07d8batQEKmdCIcsPhw4f19UvoQx/60Ic+9Anaz+HDh/3+b+bZs2e1GjVqOOZzpUqVSm1LT083Hfvo0aMaAG3NmjU+21988UXt6quv9vuxm0EKXTmiVq1aOHz4MGJiYuByuTzbT506hTp16uDw4cN+l7CJ0tD5Dyx0/gMHnfvAEoznX9M0nD59GrVq1fL7WFFRUThw4ADOnz/viD1N03z+7QVgqs55Y2xvZqOsoAldOSIkJAS1a9dm7q9cuXLQfKkvRej8BxY6/4GDzn1gCbbzX6VKlTIbKyoqClFRUWU2nk5cXBxCQ0ORn5/vs/3YsWOIj48vc38AynIlCIIgCIKQIiIiAi1btsTy5ct9ti9fvhxt2rRh9PIvpNARBEEQBEFI8vTTT6N3795o1aoVkpOTMWfOHBw6dAgDBw4MiD80oQsCIiMjkZ6ebvkun/APdP4DC53/wEHnPrDQ+S/f9OzZE7///jvGjx+PvLw8NGvWDN988w0SEhIC4g/VoSMIgiAIgghyKIaOIAiCIAgiyKEJHUEQBEEQRJBDEzqCIAiCIIgghyZ0BEEQBEEQQQ5N6PzI2LFj4XK5fD41atTw2d+4cWNUrFgRsbGx6NixIzZs2GBp95NPPkGTJk0QGRmJJk2a4LPPPpMa93LBH+d/586duPfee1GvXj24XC68+uqrpu1mzpyJ+vXrIyoqCi1btsQPP/zg5KEFBYE6/3T/++fcv/3227j55psRGxvr6bNx48ZS7ejeD9z5p3v/8oYmdH6madOmyMvL83x+/vlnz76rr74ab7zxBn7++WesXr0a9erVQ+fOnXH8+HGmvXXr1qFnz57o3bs3fvzxR/Tu3Rs9evQo9WPAG/dywunzX1hYiMTERLz88svMH8oPPvgATz75JEaPHo1t27bh5ptvxm233YZDhw45fnzlnUCcf6txLxecPvdZWVl44IEHsGrVKqxbtw5169ZF586dcfToUU8buvf/JhDn32pc4hInICvIXiakp6dr1157rXD7goICDYC2YsUKZpsePXpoXbp08dmWmpqq9erVS3ncSxV/nH9vEhIStOnTp5fa/s9//lMbOHCgz7bGjRtrI0eOFPblUiBQ55/uf/+fe03TtIsXL2oxMTHaf//7X882uvdLCNT5p3v/8oYUOj+zd+9e1KpVC/Xr10evXr2wf/9+03bnz5/HnDlzUKVKFVx77bVMe+vWrUPnzp19tqWmpmLt2rVK417qOH3+rTh//jy2bNlS6hp17ty51DW6HCjr8y877qWMv899YWEhLly4gGrVqnns0L3/N2V9/mXHJS49aELnR2644Qa88847WLp0Kd5++23k5+ejTZs2+P333z1tvvrqK1SqVAlRUVGYPn06li9fjri4OKbN/Pz8Ugv/xsfH+ywQLDLu5YA/zr8VJ06cQHFxseU1uhwIxPkXHfdSpyzO/ciRI3HVVVehY8eOAOje9yYQ5190XOISJtAS4eXEX3/9pcXHx2vTpk3z2bZ3715t3bp12iOPPKLVq1dP++2335g2wsPDtQULFvhse++997TIyEipcS9HnDj/3pi98jt69KgGQFu7dq3P9hdeeEFr1KiR7WMIZsri/IuOe7nh9LmfNGmSFhsbq/3444+ebXTvsymL8y86LnHpQgpdGVKxYkU0b94ce/fu9dnWsGFD3HjjjcjIyEBYWBgyMjKYNmrUqFHqaffYsWOlnoqtxr0cceL8WxEXF4fQ0FDpa3Q5UBbnX3Tcyw0nz/3UqVPx0ksvYdmyZWjRooVnO937bMri/IuOS1y60ISuDCkqKsKuXbtQs2ZNZhtN01BUVMTcn5ycjOXLl/tsW7ZsGdq0aWNr3MsBJ86/FREREWjZsmWpa7R8+XLuNbocKIvzrzrupY5T537KlCmYMGEClixZglatWvnso3ufTVmcf9VxiUuIgOqDlzjDhw/XsrKytP3792vr16/X7rjjDi0mJkbLycnR/vrrL23UqFHaunXrtJycHG3Lli1av379tMjISG3Hjh0eG7179/bJEFuzZo0WGhqqvfzyy9quXbu0l19+WQsLC9PWr18vNO7lhD/Of1FRkbZt2zZt27ZtWs2aNbURI0Zo27Zt0/bu3etps2jRIi08PFzLyMjQfvnlF+3JJ5/UKlasSOe/jM4/3f/+OfeTJk3SIiIitI8//ljLy8vzfE6fPu1pQ/d+CYE6/3TvX97QhM6P9OzZU6tZs6YWHh6u1apVS7vnnnu0nTt3apqmaWfPntXuvvturVatWlpERIRWs2ZNrVu3btrGjRt9bLRr107r06ePz7aPPvpIa9SokRYeHq41btxY++STT4THvZzwx/k/cOCABqDUp127dj793nzzTS0hIUGLiIjQrr/+eu27777z9+GWOwJ1/un+98+5T0hIMD336enpPv3o3g/c+ad7//LGpWmaVraaIEEQBEEQBOEkFENHEARBEAQR5NCEjiAIgiAIIsihCR1BEARBEESQQxM6giAIgiCIIIcmdARBEARBEEEOTegIgiAIgiCCHJrQEQRBEARBBDk0oSMIgiAIgghyaEJHEJcJLpcLn3/+uXD7rKwsuFwu/Pnnn37zKZiQPX8qjB07Fi6XCy6XC6+++mqZ+5OWluYZ39/HShCEs9CEjiCCHO9/hMPCwlC3bl08/vjjOHnypE+7vLw83HbbbY6OPXbsWCQlJQm3P3LkCCIiItC4cWNH/SgL/HH+zGjatCny8vIwYMAAv49l5LXXXkNeXl6Zj0sQhH1oQkcQlwBdunRBXl4ecnJyMHfuXCxevBiDBg3yaVOjRg1ERkYGyMMS5s+fjx49eqCwsBBr1qwJqC+ylNX5CwsLQ40aNVChQgW/j2WkSpUqqFGjRpmPSxCEfWhCRxCXAJGRkahRowZq166Nzp07o2fPnli2bJlPG+NrtLVr1yIpKQlRUVFo1aoVPv/8c7hcLmzfvt2n35YtW9CqVStUqFABbdq0wZ49ewCUTM7GjRuHH3/80aMQzp8/n+mjpmmYN28eevfujQcffBAZGRk++8+fP48hQ4agZs2aiIqKQr169TBx4kTP/j///BMDBgxAfHw8oqKi0KxZM3z11Vc+x3PLLbcgOjoaderUwbBhw3DmzBnP/nr16uGll17CI488gpiYGNStWxdz5swRHt94/n7++WfceuutiI6ORvXq1TFgwAD89ddfnv1paWm46667MHXqVNSsWRPVq1fH4MGDceHCBeY5YrF3717ccsstiIqKQpMmTbB8+fJSbY4ePYqePXsiNjYW1atXR/fu3ZGTk+PZf/HiRQwbNgxVq1ZF9erV8eyzz6JPnz646667pP0hCKL8QRM6grjE2L9/P5YsWYLw8HBmm9OnT+POO+9E8+bNsXXrVkyYMAHPPvusadvRo0dj2rRp2Lx5M8LCwvDII48AAHr27Inhw4d7XhHm5eWhZ8+ezDFXrVqFwsJCdOzYEb1798aHH36I06dPe/a//vrr+PLLL/Hhhx9iz549eO+991CvXj0AgNvtxm233Ya1a9fivffewy+//IKXX34ZoaGhAEomV6mpqbjnnnvw008/4YMPPsDq1asxZMgQHx+mTZuGVq1aYdu2bRg0aBAef/xx7N6923J8I4WFhejSpQtiY2OxadMmfPTRR1ixYkWp8VatWoV9+/Zh1apV+O9//4v58+dzJ71muN1u3HPPPQgNDcX69esxe/bsUteqsLAQKSkpqFSpEr7//nusXr0alSpVQpcuXXD+/HkAwKRJk/D+++9j3rx5WLNmDU6dOkVxcgRxKaERBBHU9OnTRwsNDdUqVqyoRUVFaQA0ANorr7zi0w6A9tlnn2mapmmzZs3Sqlevrp09e9az/+2339YAaNu2bdM0TdNWrVqlAdBWrFjhafP1119rADz90tPTtWuvvVbIzwcffFB78sknPX9fe+212ttvv+35e+jQodqtt96qud3uUn2XLl2qhYSEaHv27DG13bt3b23AgAE+23744QctJCTE42tCQoL20EMPefa73W7tyiuv1GbNmmU5vqb5nr85c+ZosbGx2l9//eXZ//XXX2shISFafn6+pmkl1yUhIUG7ePGip83999+v9ezZ09S+ppmfz6VLl2qhoaHa4cOHPdu+/fZbH38yMjK0Ro0a+fheVFSkRUdHa0uXLtU0TdPi4+O1KVOmePZfvHhRq1u3rta9e3fusRIEERyQQkcQlwApKSnYvn07NmzYgKFDhyI1NRVDhw5ltt+zZw9atGiBqKgoz7Z//vOfpm1btGjh+f+aNWsCAI4dOybl359//olPP/0UDz30kGfbQw89hP/85z+ev9PS0rB9+3Y0atQIw4YN83llvH37dtSuXRtXX321qf0tW7Zg/vz5qFSpkueTmpoKt9uNAwcOmB6Ly+VCjRo1PMfCG9/Irl27cO2116JixYqebW3btoXb7fa8kgZKEhx0FREoOX+y527Xrl2oW7cuateu7dmWnJxc6vizs7MRExPjOf5q1arh3Llz2LdvHwoKCvDbb7/5XOPQ0FC0bNlSyheCIMovYYF2gCAI+1SsWBENGzYEUPLqMCUlBePGjcOECRNM22uaBpfLVWqbGd6vbvU+brdbyr8FCxbg3LlzuOGGG3zGc7vd+OWXX9CkSRNcf/31OHDgAL799lusWLECPXr0QMeOHfHxxx8jOjqaa9/tduOxxx7DsGHDSu2rW7eu6bHox6MfC298I2bnz9umyHiimF0X49hutxstW7bE+++/X6rtFVdcwez3/+3dXSizbxwH8K8dLGltDszLiRwojIRMOTDEgTNCGJlIIq0VZQfLy4nXVk7kZO1ECUneSpYDeUtJ3JiwHcxbkjRxIsn8D/Rfz8zrP8/fM8/3U9fJrmv377q7av363dd97bU1JyLfwwod0Q/U2toKo9GIs7OzF/ujo6Oxvb2Nu7s792fr6+ufjiMWi/Hw8PDuOLPZjMbGRgiC4G5bW1vIzMz0qNJJpVIUFxfDZDJhZGQEY2NjcDqdiI+Px+npKWw224vXT0pKwu7uLiIjI72aWCz+8P28Fv85hUIBQRA8XrpYWVmBSCR6tYr4XykUChwfH3us5erqqseYpKQk2O12BAcHe92/TCaDTCZDSEgI1tbW3N95eHjA5ubml86ViL4PEzqiHygjIwOxsbHo6Oh4sb+0tBQulws1NTXY29uDxWKB0WgE4F3FeUtERAQcDgcEQcDl5aVHgvgvQRCwsbGB6upqxMXFeTS1Wo2BgQHc39+jt7cXw8PD2N/fh81mw+joKEJDQxEYGIj09HSoVCoUFBRgbm7OXUmbnZ0FAOj1eqyurqK+vh6CIMBut2NqaurNx87PvRX/ubKyMvj7+6OiogJWqxXz8/PQarUoLy9HSEjIh2N+RHZ2NqKioqDRaLC1tYWlpSUYDAa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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ - "# Example 1: Histogram of i-band PSF magnitudes\n", - "#plt.figure(figsize=(7,5))\n", - "#plt.hist(object_cat_ecdfs['i_psfMag'], bins=50, color='steelblue', alpha=0.7)\n", - "#plt.xlabel(\"i-band PSF Magnitude\")\n", - "#plt.ylabel(\"Number of Objects\")\n", - "#plt.title(\"Distribution of i-band PSF Magnitudes\")\n", - "#plt.show()\n", - "\n", - "# Example 2: 2D histogram of sky coordinates (RA vs Dec)\n", - "plt.figure(figsize=(7,5))\n", + "plt.figure(figsize=(7, 5))\n", "plt.hist2d(object_cat_ecdfs['coord_ra'], object_cat_ecdfs['coord_dec'],\n", " bins=200, cmap='viridis')\n", "plt.colorbar(label=\"Number of Objects\")\n", @@ -1356,79 +411,76 @@ ] }, { - "cell_type": "code", - "execution_count": null, - "id": "5af580e6-8611-4c83-b4ac-d924905fcec2", - "metadata": { - "execution": { - "execution_failed": "2025-09-16T17:06:28.151Z", - "iopub.execute_input": "2025-09-16T17:05:09.111140Z", - "iopub.status.busy": "2025-09-16T17:05:09.110835Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting float[pyarrow] to object dtype.\n", - " warnings.warn(\n", - "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/dask/dataframe/dask_expr/_collection.py:1435: UserWarning: Dask currently has limited support for converting pandas extension dtypes to arrays. Converting float[pyarrow] to object dtype.\n", - " warnings.warn(\n" - ] - } - ], + "cell_type": "markdown", + "id": "047c6cc8-a1a8-496e-b4a9-7ea57dee6e1c", + "metadata": {}, "source": [ - "# Example 1: Histogram of i-band PSF magnitudes\n", - "plt.figure(figsize=(7,5))\n", - "plt.hist(object_cat_ecdfs['r_psfMag'], bins=50, color='steelblue', alpha=0.7)\n", - "plt.xlabel(\"i-band PSF Magnitude\")\n", - "plt.ylabel(\"Number of Objects\")\n", - "plt.title(\"Distribution of i-band PSF Magnitudes\")\n", - "plt.show()" + "#### 2.1.3 Queries" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "050ef751-3f6d-4805-a6ba-c2f0bf0c5ae8", + "cell_type": "markdown", + "id": "caa8e632-e7df-4190-8516-7cfc68884e2b", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "It is possible to filter LSDB catalogs using the `.query()` method. \n", + "The query expression is written as a string and follows the same syntax as [Pandas `.query()`](https://pandas.pydata.org/docs/reference/api/pandas.DataFrame.query.html), which supports a subset of Python expressions for filtering DataFrames." + ] }, { "cell_type": "markdown", - "id": "5a9cce35-0fe0-46ee-846e-eaf7755e731d", + "id": "070f40be-94d7-4fe3-aa31-d6dd91c28362", "metadata": {}, "source": [ - "Optional: uncomment the following cell and press \"tab\" to browse more availabe methods." + "Select only objects with an **r-band PSF magnitude between 16 and 24**" ] }, { "cell_type": "code", "execution_count": null, - "id": "2c19a686-c4ce-49bc-836e-d5becc7f8b7b", + "id": "5d8e6e4d-784f-4442-a52f-73a51de1b915", "metadata": {}, "outputs": [], "source": [ - "# object_cat." + "object_cat_mag_range = object_cat.query(\"r_psfMag > 16 and r_psfMag < 24\")\n", + "object_cat_mag_range" + ] + }, + { + "cell_type": "markdown", + "id": "6a0a329c-7be5-4b0a-b47d-033621f9dc3c", + "metadata": {}, + "source": [ + "Use the `.head()` method to quickly inspect a few rows to check that the query worked as expected." ] }, { "cell_type": "code", "execution_count": null, - "id": "cb4cdfab-33b6-4f81-b9ac-d5bf459d5740", + "id": "2205b723-4fe7-484b-b996-8857b3142936", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "object_cat_mag_range.head(10)" + ] + }, + { + "cell_type": "markdown", + "id": "5a9cce35-0fe0-46ee-846e-eaf7755e731d", + "metadata": {}, + "source": [ + "Optional: uncomment the following cell and press \"tab\" to browse more availabe methods." + ] }, { "cell_type": "code", "execution_count": null, - "id": "4ffbca13-0c91-4ce9-a23d-ed4b84c851b4", + "id": "2c19a686-c4ce-49bc-836e-d5becc7f8b7b", "metadata": {}, "outputs": [], - "source": [] + "source": [ + "# object_cat." + ] }, { "cell_type": "markdown", @@ -1456,17 +508,9 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": null, "id": "ce101fd1-06bb-4b3b-8f32-7c128079cbb0", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:51:06.294000Z", - "iopub.status.busy": "2025-09-16T13:51:06.293722Z", - "iopub.status.idle": "2025-09-16T13:51:07.843316Z", - "shell.execute_reply": "2025-09-16T13:51:07.842785Z", - "shell.execute_reply.started": "2025-09-16T13:51:06.293978Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_lite = lsdb.open_catalog(base_path / \"object_collection_lite\")" @@ -1482,102 +526,10 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "cf587923-8b43-47fa-af57-6bdce6062035", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T13:38:54.127686Z", - "iopub.status.busy": "2025-09-16T13:38:54.127386Z", - "iopub.status.idle": "2025-09-16T13:38:54.133255Z", - "shell.execute_reply": "2025-09-16T13:38:54.132466Z", - "shell.execute_reply.started": "2025-09-16T13:38:54.127663Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['tract',\n", - " 'patch',\n", - " 'z_psfFlux',\n", - " 'z_psfFluxErr',\n", - " 'z_kronRad',\n", - " 'z_kronFlux',\n", - " 'z_kronFluxErr',\n", - " 'u_psfFlux',\n", - " 'u_psfFluxErr',\n", - " 'u_kronRad',\n", - " 'u_kronFlux',\n", - " 'u_kronFluxErr',\n", - " 'g_psfFlux',\n", - " 'g_psfFluxErr',\n", - " 'g_kronRad',\n", - " 'g_kronFlux',\n", - " 'g_kronFluxErr',\n", - " 'r_psfFlux',\n", - " 'r_psfFluxErr',\n", - " 'r_kronRad',\n", - " 'r_kronFlux',\n", - " 'r_kronFluxErr',\n", - " 'i_psfFlux',\n", - " 'i_psfFluxErr',\n", - " 'i_kronRad',\n", - " 'i_kronFlux',\n", - " 'i_kronFluxErr',\n", - " 'y_psfFlux',\n", - " 'y_psfFluxErr',\n", - " 'y_kronRad',\n", - " 'y_kronFlux',\n", - " 'y_kronFluxErr',\n", - " 'parentObjectId',\n", - " 'coord_ra',\n", - " 'coord_dec',\n", - " 'coord_raErr',\n", - " 'coord_decErr',\n", - " 'refBand',\n", - " 'x',\n", - " 'y',\n", - " 'xErr',\n", - " 'yErr',\n", - " 'refFwhm',\n", - " 'shape_xx',\n", - " 'shape_yy',\n", - " 'shape_xy',\n", - " 'detect_isIsolated',\n", - " 'shape_flag',\n", - " 'objectId',\n", - " 'u_psfMag',\n", - " 'u_psfMagErr',\n", - " 'u_kronMag',\n", - " 'u_kronMagErr',\n", - " 'g_psfMag',\n", - " 'g_psfMagErr',\n", - " 'g_kronMag',\n", - " 'g_kronMagErr',\n", - " 'r_psfMag',\n", - " 'r_psfMagErr',\n", - " 'r_kronMag',\n", - " 'r_kronMagErr',\n", - " 'i_psfMag',\n", - " 'i_psfMagErr',\n", - " 'i_kronMag',\n", - " 'i_kronMagErr',\n", - " 'z_psfMag',\n", - " 'z_psfMagErr',\n", - " 'z_kronMag',\n", - " 'z_kronMagErr',\n", - " 'y_psfMag',\n", - " 'y_psfMagErr',\n", - " 'y_kronMag',\n", - " 'y_kronMagErr',\n", - " 'objectForcedSource']" - ] - }, - "execution_count": 13, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_lite.all_columns" ] @@ -1592,17 +544,9 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:19:02.130305Z", - "iopub.status.busy": "2025-09-16T15:19:02.129984Z", - "iopub.status.idle": "2025-09-16T15:19:04.617665Z", - "shell.execute_reply": "2025-09-16T15:19:04.616953Z", - "shell.execute_reply.started": "2025-09-16T15:19:02.130278Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "dia_object_cat = lsdb.open_catalog(base_path / \"dia_object_collection\")" @@ -1610,138 +554,10 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": null, "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:19:04.618807Z", - "iopub.status.busy": "2025-09-16T15:19:04.618596Z", - "iopub.status.idle": "2025-09-16T15:19:04.632750Z", - "shell.execute_reply": "2025-09-16T15:19:04.632097Z", - "shell.execute_reply.started": "2025-09-16T15:19:04.618788Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog dia_object_lc:
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decdiaObjectIdnDiaSourcesraradecMjdTaitractdiaObjectForcedSourcediaSource
npartitions=208
Order: 6, Pixel: 130double[pyarrow]int64[pyarrow]int64[pyarrow]double[pyarrow]double[pyarrow]int64[pyarrow]nested<band: [string], coord_dec: [double], co...nested<band: [string], centroid_flag: [bool], ...
Order: 6, Pixel: 136........................
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Order: 11, Pixel: 36833621........................
Order: 7, Pixel: 143884........................
\n", - "
8 out of 140 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " dec diaObjectId nDiaSources ra radecMjdTai tract diaObjectForcedSource diaSource\n", - "npartitions=208 \n", - "9147936743096320 double[pyarrow] int64[pyarrow] int64[pyarrow] double[pyarrow] double[pyarrow] int64[pyarrow] nested nested\n", - "9570149208162304 ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "dia_object_cat" ] @@ -1756,17 +572,9 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": null, "id": "e8dd3508-9aff-4157-a911-d555128c9a37", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:19:04.633550Z", - "iopub.status.busy": "2025-09-16T15:19:04.633334Z", - "iopub.status.idle": "2025-09-16T15:19:04.837954Z", - "shell.execute_reply": "2025-09-16T15:19:04.837238Z", - "shell.execute_reply.started": "2025-09-16T15:19:04.633518Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "pz_cat = lsdb.open_catalog(base_path / \"object_photoz\")" @@ -1782,859 +590,10 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": null, "id": "6cfe9c30-21dc-4b22-8ae0-d0552ecdcef3", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:19:04.839108Z", - "iopub.status.busy": "2025-09-16T15:19:04.838890Z", - "iopub.status.idle": "2025-09-16T15:19:04.909614Z", - "shell.execute_reply": "2025-09-16T15:19:04.908926Z", - "shell.execute_reply.started": "2025-09-16T15:19:04.839088Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog object_photoz:
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coord_deccoord_rag_cModelMagg_cModelMagErrg_gaap1p0Magg_gaap1p0MagErrg_gaap3p0Magg_gaap3p0MagErrg_kronMagg_kronMagErrg_psfMagg_psfMagErrg_sersicMagg_sersicMagErri_cModelMagi_cModelMagErri_gaap1p0Magi_gaap1p0MagErri_gaap3p0Magi_gaap3p0MagErri_kronMagi_kronMagErri_psfMagi_psfMagErri_sersicMagi_sersicMagErrobjectIdr_cModelMagr_cModelMagErrr_gaap1p0Magr_gaap1p0MagErrr_gaap3p0Magr_gaap3p0MagErrr_kronMagr_kronMagErrr_psfMagr_psfMagErrr_sersicMagr_sersicMagErru_cModelMagu_cModelMagErru_gaap1p0Magu_gaap1p0MagErru_gaap3p0Magu_gaap3p0MagErru_kronMagu_kronMagErru_psfMagu_psfMagErru_sersicMagu_sersicMagErry_cModelMagy_cModelMagErry_gaap1p0Magy_gaap1p0MagErry_gaap3p0Magy_gaap3p0MagErry_kronMagy_kronMagErry_psfMagy_psfMagErry_sersicMagy_sersicMagErrz_cModelMagz_cModelMagErrz_gaap1p0Magz_gaap1p0MagErrz_gaap3p0Magz_gaap3p0MagErrz_kronMagz_kronMagErrz_psfMagz_psfMagErrz_sersicMagz_sersicMagErrlephare_z_medianlephare_z_meanlephare_z_modelephare_z_err95_lowlephare_z_err95_highlephare_z_err68_lowlephare_z_err68_highknn_z_medianknn_z_modeknn_z_err95_lowknn_z_err95_highknn_z_err68_lowknn_z_err68_hightpz_z_mediantpz_z_meantpz_z_modetpz_z_err95_lowtpz_z_err95_hightpz_z_err68_lowtpz_z_err68_highcmnn_z_mediancmnn_z_meancmnn_z_modecmnn_z_err95_lowcmnn_z_err95_highcmnn_z_err68_lowcmnn_z_err68_highgpz_z_mediangpz_z_meangpz_z_modegpz_z_err95_lowgpz_z_err95_highgpz_z_err68_lowgpz_z_err68_highbpz_z_medianbpz_z_meanbpz_z_modebpz_z_err95_lowbpz_z_err95_highbpz_z_err68_lowbpz_z_err68_highdnf_z_mediandnf_z_meandnf_z_modednf_z_err95_lowdnf_z_err95_highdnf_z_err68_lowdnf_z_err68_highfzboost_z_medianfzboost_z_meanfzboost_z_modefzboost_z_err95_lowfzboost_z_err95_highfzboost_z_err68_lowfzboost_z_err68_high
npartitions=4
Order: 3, Pixel: 2double[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]int64[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]
Order: 5, Pixel: 4471......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 2, Pixel: 80......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 0, Pixel: 8......................................................................................................................................................................................................................................................................................................................................................................................................
\n", - "
130 out of 130 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_ra g_cModelMag g_cModelMagErr g_gaap1p0Mag g_gaap1p0MagErr g_gaap3p0Mag g_gaap3p0MagErr g_kronMag g_kronMagErr g_psfMag g_psfMagErr g_sersicMag g_sersicMagErr i_cModelMag i_cModelMagErr i_gaap1p0Mag i_gaap1p0MagErr i_gaap3p0Mag i_gaap3p0MagErr i_kronMag i_kronMagErr i_psfMag i_psfMagErr i_sersicMag i_sersicMagErr objectId r_cModelMag r_cModelMagErr r_gaap1p0Mag r_gaap1p0MagErr r_gaap3p0Mag r_gaap3p0MagErr r_kronMag r_kronMagErr r_psfMag r_psfMagErr r_sersicMag r_sersicMagErr u_cModelMag u_cModelMagErr u_gaap1p0Mag u_gaap1p0MagErr u_gaap3p0Mag u_gaap3p0MagErr u_kronMag u_kronMagErr u_psfMag u_psfMagErr u_sersicMag u_sersicMagErr y_cModelMag y_cModelMagErr y_gaap1p0Mag y_gaap1p0MagErr y_gaap3p0Mag y_gaap3p0MagErr y_kronMag y_kronMagErr y_psfMag y_psfMagErr y_sersicMag y_sersicMagErr z_cModelMag z_cModelMagErr z_gaap1p0Mag z_gaap1p0MagErr z_gaap3p0Mag z_gaap3p0MagErr z_kronMag z_kronMagErr z_psfMag z_psfMagErr z_sersicMag z_sersicMagErr lephare_z_median lephare_z_mean lephare_z_mode lephare_z_err95_low lephare_z_err95_high lephare_z_err68_low lephare_z_err68_high knn_z_median knn_z_mode knn_z_err95_low knn_z_err95_high knn_z_err68_low knn_z_err68_high tpz_z_median tpz_z_mean tpz_z_mode tpz_z_err95_low tpz_z_err95_high tpz_z_err68_low tpz_z_err68_high cmnn_z_median cmnn_z_mean cmnn_z_mode cmnn_z_err95_low cmnn_z_err95_high cmnn_z_err68_low cmnn_z_err68_high gpz_z_median gpz_z_mean gpz_z_mode gpz_z_err95_low gpz_z_err95_high gpz_z_err68_low gpz_z_err68_high bpz_z_median bpz_z_mean bpz_z_mode bpz_z_err95_low bpz_z_err95_high bpz_z_err68_low bpz_z_err68_high dnf_z_median dnf_z_mean dnf_z_mode dnf_z_err95_low dnf_z_err95_high dnf_z_err68_low dnf_z_err68_high fzboost_z_median fzboost_z_mean fzboost_z_mode fzboost_z_err95_low fzboost_z_err95_high fzboost_z_err68_low fzboost_z_err68_high\n", - "npartitions=4 \n", - "9007199254740992 double[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] int64[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow]\n", - "1258474620873342976 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "1441151880758558720 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2305843009213693952 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2594073385365405696 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 23, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "pz_cat" ] @@ -2642,15 +601,7 @@ { "cell_type": "markdown", "id": "97342caa-6d08-4e1f-bafe-80056c928632", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:19:04.910420Z", - "iopub.status.busy": "2025-09-16T15:19:04.910210Z", - "iopub.status.idle": "2025-09-16T15:19:04.913031Z", - "shell.execute_reply": "2025-09-16T15:19:04.912399Z", - "shell.execute_reply.started": "2025-09-16T15:19:04.910402Z" - } - }, + "metadata": {}, "source": [ "## 3. Sky partitions" ] @@ -2671,77 +622,23 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": null, "id": "035604c1-816d-4e1e-ad95-061b04249e4f", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:27:06.829115Z", - "iopub.status.busy": "2025-09-16T15:27:06.828843Z", - "iopub.status.idle": "2025-09-16T15:27:07.145752Z", - "shell.execute_reply": "2025-09-16T15:27:07.145099Z", - "shell.execute_reply.started": "2025-09-16T15:27:06.829094Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/hats/inspection/visualize_catalog.py:303: UserWarning: This plot contains HEALPix pixels smaller than a pixel of the plot. Some values may be lost\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ "fig = object_cat.plot_pixels(plot_title=\"Object Cat Sky Partition Map\")" ] }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "68bcaa43-c76d-4445-b101-54fc382c7399", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-16T15:27:32.206844Z", - "iopub.status.busy": "2025-09-16T15:27:32.206567Z", - "iopub.status.idle": "2025-09-16T15:27:32.532728Z", - "shell.execute_reply": "2025-09-16T15:27:32.532243Z", - "shell.execute_reply.started": "2025-09-16T15:27:32.206824Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ "fig = pz_cat.plot_pixels(plot_title=\"Photo-z Cat Sky Partition Map\")" ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "6fe57fd1-8e5c-4986-ac1f-8fa8e0fac896", - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { From d040a6677c8f055bcb8e421d307b1b22fd8cdcd0 Mon Sep 17 00:00:00 2001 From: MelissaGraham Date: Thu, 18 Sep 2025 01:06:11 +0000 Subject: [PATCH 4/8] updates --- .../102_5_LSDB_data_access.ipynb | 225 +++++++++++++----- 1 file changed, 159 insertions(+), 66 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 4d7ac06e..552751d0 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -22,7 +22,7 @@ "Data Release: Data Preview 1
\n", "Container Size: Large
\n", "LSST Science Pipelines version: Release r29.2.0
\n", - "Last verified to run: 2025-09-09
\n", + "Last verified to run: 2025-09-17
\n", "Repository: github.com/lsst/tutorial-notebooks
" ] }, @@ -33,7 +33,7 @@ "source": [ "**Learning objective:** How to access Rubin data in LSDB format.\n", "\n", - "**LSST data products:** `Object`, `DIAObject`\n", + "**LSST data products:** `Object`, `DiaObject`\n", "\n", "**Packages:** `lsdb`\n", "\n", @@ -55,28 +55,28 @@ "source": [ "## 1. Introduction\n", "\n", - "[LSDB](https://docs.lsdb.io/) (Large Scale Database) is an open-source Python framework that enables fast all-sky cross-matching, bulk application of user-defined functions, \n", - " and simplified analysis of time-domain (light curve) data.\n", + "[LSDB](https://docs.lsdb.io/) (Large Scale Database) is an open-source Python framework that enables fast all-sky cross-matching, bulk application of user-defined functions, and simplified analysis of time-domain (light curve) data.\n", "It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format ([HEALPix](https://healpix.sourceforge.io/documentation.php)-sharded [Parquet](https://parquet.apache.org/docs/)) to efficiently perform spatial operations.\n", "\n", - "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial (e.g., Gaia).\n", + "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial, but **only the DP1 dataset is available in the RSP**.\n", + "Find the full list of LSDB-hosted datasets at [data.lsdb.io](https://data.lsdb.io/).\n", "\n", "**Note:** This notebook is intended only as a simple tutorial on LSDB DP1 catalogs.\n", - "For more detailed examples and advanced use cases, see the full set of LSDB tutorials at [LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html). \n", + "For more detailed examples and advanced use cases, see the full set of LSDB tutorials at [LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html).\n", "\n", "**References:**\n", "\n", - "- Descriptions of LSDB-formatted Data Preview 1 (DP1) data: [https://data.lsdb.io/](https://data.lsdb.io/ )\n", + "- Descriptions of LSDB-formatted Data Preview 1 (DP1) data: [https://data.lsdb.io/](https://data.lsdb.io/)\n", "- LSDB documentation: [docs.lsdb.io](https://docs.lsdb.io/en/latest/index.html)\n", "- [Working with Rubin Data using LSDB](https://docs.lsdb.io/en/latest/tutorial_toc/toc_rubin.html)\n", "- [LSDB hackathon at the Rubin Community Workshop 2025](https://github.com/lincc-frameworks/RCW_Hackathon_2025_LSDB/tree/main)\n", "\n", - "**Related tutorials:** The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. \n", + "**Related tutorials:** The 200-level tutorials on the `Object` and `DiaObject` catalogs. The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. \n", "\n", "### 1.1. Import packages\n", "\n", - "Import the [LSDB package](https://github.com/astronomy-commons/lsdb/) to work with LSDB-formatted files, [`upath`](https://github.com/fsspec/universal_pathlib) for handling local and remote file paths uniformly , and `matplotlib.pyplot` for visualization." + "Import the [LSDB package](https://github.com/astronomy-commons/lsdb/) to work with LSDB-formatted files, [`upath`](https://github.com/fsspec/universal_pathlib) for handling local and remote file paths uniformly, and `matplotlib.pyplot` for visualization." ] }, { @@ -87,67 +87,52 @@ "outputs": [], "source": [ "import lsdb\n", + "\n", + "import astropy.units as u\n", + "from astropy.coordinates import SkyCoord\n", "from upath import UPath\n", "import matplotlib.pyplot as plt" ] }, { "cell_type": "markdown", - "id": "5305936d-dd18-4ceb-b6bf-c362f7e268d0", + "id": "ae66b0eb-3fb6-4e26-be2b-acc9eaafa2f3", "metadata": {}, "source": [ - "## 2. Accessing catalogs" + "Set the base path to the LSDB-formatted DP1 data in the RSP." ] }, { - "cell_type": "markdown", - "id": "dbe24ce4-ca74-4edb-8a33-a0689cefe8eb", + "cell_type": "code", + "execution_count": null, + "id": "98b33f9b-914a-4184-8765-66c96e9c2cef", "metadata": {}, + "outputs": [], "source": [ - "The `lsdb` read-only catalogs at the `data.lsst.cloud` Rubin Science Platform are located at `/rubin/lsdb_data`, and they consist of `Object`, `DIAObject` and photometric redshift (photo-z) catalogs:\n", - "- `dia_object_collection`\n", - "- `object_collection` \n", - "- `object_collection_lite` \n", - "- `object_photoz`\n", - "\n", - "The schemas for `dia_object_collection`, `object_collection`, and `object_collection_lite` with column names, units, and descriptions can be checked at the [Data Preview 1 (DP1) schema website](https://sdm-schemas.lsst.io/dp1.html) via the `Object` and `DiaObject` tables.\n", - "\n", - "\n", - "The `lsdb` read-only catalogs at the `data.lsst.cloud` Rubin Science Platform are located at `/rubin/lsdb_data`, and they consist of `Object`, `DIAObject`, and photometric redshift (photo-z) catalogs:\n", - "\n", - "- `dia_object_collection` \n", - "- `object_collection` \n", - "- `object_collection_lite` \n", - "- `object_photoz` \n", - "\n", - "The **`dia_object_collection`, `object_collection`, and `object_collection_lite`** catalogs have columns that match the [Data Preview 1 (DP1) schema](https://sdm-schemas.lsst.io/dp1.html) for the `Object` and `DiaObject` tables, with some additional convenience columns:\n", - "\n", - "- `psfMag`, `scienceMag` — fluxes already converted to magnitudes \n", - "- `psfMagErr`, `scienceMagErr` — corresponding uncertainties \n", - "\n", - "The `object_photoz` table follows a naming pattern of `{pz_algorithm_name}_z_{point_estimate_type}` \n", - "where:\n", - "\n", - "- `pz_algorithm_name ∈ ['fzboost', 'knn', 'gpz', 'bpz', 'cmnn', 'dnf', 'tpz', 'lephare']` \n", - "- `point_estimate_type ∈ ['mode', 'mean', 'median', 'err68high', 'err68low', 'err95high', 'err95low']` " + "base_path = UPath(\"/rubin/lsdb_data\")" ] }, { "cell_type": "markdown", - "id": "d7f22845-3128-4d62-8bbf-b0afec98ee75", + "id": "5305936d-dd18-4ceb-b6bf-c362f7e268d0", "metadata": {}, "source": [ - "Set the base path." + "## 2. Access the LSDB DP1 catalogs" ] }, { - "cell_type": "code", - "execution_count": null, - "id": "14c81508-8944-493d-b7f0-b4f5a2622e18", + "cell_type": "markdown", + "id": "dbe24ce4-ca74-4edb-8a33-a0689cefe8eb", "metadata": {}, - "outputs": [], "source": [ - "base_path = UPath(\"/rubin/lsdb_data\")" + "The four LSDB DP1 read-only catalogs available in the Rubin Science Platform at `data.lsst.cloud` are located in the directory `/rubin/lsdb_data`, and their names are:\n", + "\n", + "- `object_collection`: the `Object` table\n", + "- `object_collection_lite`: a limited number of columns from the `Object` table\n", + "- `dia_object_collection`: the `DiaObject` table\n", + "- `object_photoz`: photometric redshift (photo-z) estimates for galaxies\n", + "\n", + "Note that the `object_photoz` catalog was not part of the DP1 release (see Section 2.3, below)." ] }, { @@ -155,7 +140,11 @@ "id": "1d77f3c2-3e21-462e-bb61-23a66ecdfdc0", "metadata": {}, "source": [ - "### 2.1. Object catalog" + "### 2.1. object_collection\n", + "\n", + "This LSDB-formatted file is the same as the DP1 `Object` table but with additional columns, `_psfMag` and `_psfMagErr`, which are the corresponding `_psfFlux` columns converted to magnitudes (for each filter, ``, in $ugrizy$).\n", + "\n", + "[Schema browser for the DP1 Object table](https://sdm-schemas.lsst.io/dp1.html#Object)." ] }, { @@ -163,7 +152,7 @@ "id": "05a9db77-bcdc-4c83-8c12-cf3c83dc4c95", "metadata": {}, "source": [ - "#### 2.1.1 Load and display the catalog" + "#### 2.1.1. Load and display the catalog" ] }, { @@ -203,7 +192,7 @@ "id": "acdce8d8-9727-4ea2-880b-afbfe0fa7d83", "metadata": {}, "source": [ - "#### 2.1.2 Columns" + "#### 2.1.2. Show column names" ] }, { @@ -211,7 +200,7 @@ "id": "4d29b2c6-7576-4df7-a03d-b2c20e955679", "metadata": {}, "source": [ - "Display the 42 loaded columns." + "Display the subset of 42 columns that are lazily loaded by default." ] }, { @@ -235,13 +224,33 @@ { "cell_type": "code", "execution_count": null, - "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", + "id": "bcf956b0-8d59-445d-bd9b-ba0914d78c4b", "metadata": {}, "outputs": [], "source": [ "# object_cat.all_columns" ] }, + { + "cell_type": "markdown", + "id": "6199446b-7723-49cd-a6de-ab750165458c", + "metadata": {}, + "source": [ + "Show only the additional columns in the LSDB catalog that contains the PSF fluxes converted to magnitudes." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", + "metadata": {}, + "outputs": [], + "source": [ + "for col in object_cat.all_columns:\n", + " if col.find('psfMag') > 0:\n", + " print(col)" + ] + }, { "cell_type": "markdown", "id": "7e026aec-03d7-496d-9fdb-3ac317558732", @@ -323,7 +332,7 @@ "id": "5a6394d7-ecc3-4f90-9269-dfad81b2872e", "metadata": {}, "source": [ - "#### 2.1.3 Cone searchs" + "#### 2.1.3. Execute a cone search" ] }, { @@ -331,7 +340,7 @@ "id": "d5021222-fc50-4f94-8095-c68e3afd39ff", "metadata": {}, "source": [ - "Cone searchs are supported and defined by a center (`ra`, `dec`), in degrees, and a radius `r`, in arcseconds.\n", + "Cone searches are supported and defined by a center (`ra`, `dec`), in degrees, and a radius `r`, in arcseconds.\n", "Execute a cone search on the object catalog using the coordinates (in degrees) of the Extended Chandra Deep Field South DP1 target field, with a radius of 0.1 deg." ] }, @@ -410,12 +419,20 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "6cd4aa4c-f3ea-4a19-bd7d-22c9f789f640", + "metadata": {}, + "source": [ + "> **Figure 1:** A 2-dimensional distribution (heatmap) of the number of objects across the sky, as returned by the cone search centered on the ECDFS field." + ] + }, { "cell_type": "markdown", "id": "047c6cc8-a1a8-496e-b4a9-7ea57dee6e1c", "metadata": {}, "source": [ - "#### 2.1.3 Queries" + "#### 2.1.4. Execute a query on column values" ] }, { @@ -487,7 +504,7 @@ "id": "1c52944d-f33f-4d72-9bc3-3430fe26b113", "metadata": {}, "source": [ - "### 2.2. Lite object catalog" + "### 2.2. object_collection_lite" ] }, { @@ -495,7 +512,7 @@ "id": "83cd7f51-81cb-4ae4-b36b-fa43d3ddb61a", "metadata": {}, "source": [ - "The `object_collection_lite` LSDB catalog is a reduced version of the `Object` catalog in `object_collection`. It contains 74 commonly used columns that provide basic object properties, including object identifiers, sky coordinates with uncertainties, basic shape measurements, flags, and PSF- and Kron-based fluxes and magnitudes (with uncertainties) across the six Legacy Survey of Space and Time (LSST) bands (`u`, `g`, `r`, `i`, `z`, and `y`)." + "The `object_collection_lite` LSDB catalog is a reduced version of the `Object` catalog in `object_collection`. It contains 74 commonly used columns that provide basic object properties, including object identifiers, sky coordinates with uncertainties, basic shape measurements, flags, and PSF- and Kron-based fluxes and magnitudes (with uncertainties) across the six Legacy Survey of Space and Time (LSST) bands ($ugrizy$)." ] }, { @@ -503,7 +520,7 @@ "id": "06d11db7-9188-4534-bd18-3a2ebc6eea2d", "metadata": {}, "source": [ - "Get the catalog" + "Get the catalog." ] }, { @@ -516,12 +533,30 @@ "object_cat_lite = lsdb.open_catalog(base_path / \"object_collection_lite\")" ] }, + { + "cell_type": "markdown", + "id": "841d33a4-cc73-441a-b256-5b7b2ead89b1", + "metadata": {}, + "source": [ + "The same 42 default columns are loaded lazily for the `object_collection_lite` as for the `object_collecation` catalog." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "57ef8891-4567-4d75-9611-0d07eb0acd28", + "metadata": {}, + "outputs": [], + "source": [ + "object_cat_lite" + ] + }, { "cell_type": "markdown", "id": "9d4c3445-81da-4ea6-9831-e709874ea5c6", "metadata": {}, "source": [ - "Display all the columns." + "Option to display all 74 of the columns." ] }, { @@ -531,7 +566,7 @@ "metadata": {}, "outputs": [], "source": [ - "object_cat_lite.all_columns" + "# object_cat_lite.all_columns" ] }, { @@ -539,7 +574,11 @@ "id": "73764ef6-ebb6-4b7f-bfd5-d7c5e1a51302", "metadata": {}, "source": [ - "### 2.2 Dia Object catalog" + "### 2.3. dia_object_collection\n", + "\n", + "This LSDB-formatted file is the same as the DP1 `DiaObject` table.\n", + "\n", + "[Schema browser for the DP1 DiaObject table](https://sdm-schemas.lsst.io/dp1.html#DiaObject)." ] }, { @@ -567,7 +606,19 @@ "id": "a4e7a75f-07e7-443e-b5c0-ac92db031f00", "metadata": {}, "source": [ - "### 2.3 Phot-z catalog" + "### 2.4. object_photoz\n", + "\n", + "As documented in the SIT-Com tech note \"Initial studies of photometric redshifts with LSSTComCam from DP1\" ([SITCOMTN-154](https://sitcomtn-154.lsst.io/)), members of the Rubin Commissioning Science Unit for photometric redshifts have generated photo-z estimates for every galaxy in DP1.\n", + "\n", + "The `object_photoz` table follows a naming pattern of `{pz_algorithm_name}_z_{point_estimate_type}` \n", + "where:\n", + "\n", + "- `pz_algorithm_name ∈ ['fzboost', 'knn', 'gpz', 'bpz', 'cmnn', 'dnf', 'tpz', 'lephare']` \n", + "- `point_estimate_type ∈ ['mode', 'mean', 'median', 'err68high', 'err68low', 'err95high', 'err95low']`\n", + "\n", + "As mentioned in Section 1, use of the `object_photoz` table is demonstrated in more detail in the 300-level tutorials.\n", + "\n", + "Load the photo-z table." ] }, { @@ -603,7 +654,7 @@ "id": "97342caa-6d08-4e1f-bafe-80056c928632", "metadata": {}, "source": [ - "## 3. Sky partitions" + "## 3. Visualize the LSDB sky partitions" ] }, { @@ -617,7 +668,9 @@ "\n", "The `plot_pixels` method of a catalog object visualizes these partitions.\n", "The result is not a science-driven sky coverage map but a display of the polygonal partition boundaries.\n", - "Pixel colors represent pixel sizes, with smaller pixels corresponding to regions of higher source density." + "Pixel colors represent pixel sizes, with smaller pixels corresponding to regions of higher source density.\n", + "\n", + "> **Warning:** the following code cell produces a `UserWarning` about small HEALPix pixels, which is OK to ignore. The seven DP1 fields are relatively small on the sky to start with, and their partitions even smaller -- but still the locations of all seven fields appear." ] }, { @@ -627,17 +680,57 @@ "metadata": {}, "outputs": [], "source": [ - "fig = object_cat.plot_pixels(plot_title=\"Object Cat Sky Partition Map\")" + "fig = object_cat.plot_pixels(plot_title=\"Object Sky Partition Map\")" + ] + }, + { + "cell_type": "markdown", + "id": "575511ae-fb65-4f6f-9c02-01f40790ef0c", + "metadata": {}, + "source": [ + "> **Figure 2:** An all-sky map showing the HEALPix partitions for the LSDB-formatted `object_collection` catalog." + ] + }, + { + "cell_type": "markdown", + "id": "4fd38417-3800-4c80-b2d7-c917cd70239c", + "metadata": {}, + "source": [ + "Define a field of view (fov) and center in order to zoom-in on the partitions for the `object_collection` catalog, and re-create the plot. \n", + "\n", + "> **Warning:** The same `UserWarning` will show about small HEALPix pixels." ] }, { "cell_type": "code", "execution_count": null, - "id": "68bcaa43-c76d-4445-b101-54fc382c7399", + "id": "e25035eb-b54d-4bf7-96ae-c974a1db28a5", "metadata": {}, "outputs": [], "source": [ - "fig = pz_cat.plot_pixels(plot_title=\"Photo-z Cat Sky Partition Map\")" + "fov = (100 * u.deg, 120 * u.deg)\n", + "center = SkyCoord(70 * u.deg, -30 * u.deg)\n", + "fig = object_cat.plot_pixels(fov=fov, center=center,\n", + " plot_title=\"Object Sky Partition Map\")" + ] + }, + { + "cell_type": "markdown", + "id": "f7809a09-56b9-46a5-8701-194877f095ef", + "metadata": {}, + "source": [ + "> **Figure 3:** A zoomed-in version of Figure 2." + ] + }, + { + "cell_type": "markdown", + "id": "8e433068-ad9d-4545-bbcb-0f26a574b83a", + "metadata": {}, + "source": [ + "## 4. Learn more about LSDB\n", + "\n", + "As mentioned in Section 1, this notebook is intended only as a simple tutorial on LSDB DP1 catalogs.\n", + "For more detailed examples and advanced use cases, see [the full set of LSDB tutorials](https://docs.lsdb.io/en/latest/tutorials.html).\n" ] } ], From 691bc676f66b5fd3861fa0be212d14ac8eff9b5d Mon Sep 17 00:00:00 2001 From: plazas Date: Thu, 18 Sep 2025 13:40:02 +0000 Subject: [PATCH 5/8] Display nested columns and additional columns --- .../102_5_LSDB_data_access.ipynb | 3934 ++++++++++++++++- 1 file changed, 3856 insertions(+), 78 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 552751d0..6f597df2 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -22,7 +22,7 @@ "Data Release: Data Preview 1
\n", "Container Size: Large
\n", "LSST Science Pipelines version: Release r29.2.0
\n", - "Last verified to run: 2025-09-17
\n", + "Last verified to run: 2025-09-18
\n", "Repository: github.com/lsst/tutorial-notebooks
" ] }, @@ -81,9 +81,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "id": "963c1141-196b-49c1-8db0-019f3a22c6ad", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:15.831594Z", + "iopub.status.busy": "2025-09-18T12:54:15.831249Z", + "iopub.status.idle": "2025-09-18T12:54:15.834630Z", + "shell.execute_reply": "2025-09-18T12:54:15.834145Z", + "shell.execute_reply.started": "2025-09-18T12:54:15.831559Z" + } + }, "outputs": [], "source": [ "import lsdb\n", @@ -104,9 +112,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "98b33f9b-914a-4184-8765-66c96e9c2cef", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:15.835560Z", + "iopub.status.busy": "2025-09-18T12:54:15.835359Z", + "iopub.status.idle": "2025-09-18T12:54:15.866997Z", + "shell.execute_reply": "2025-09-18T12:54:15.866461Z", + "shell.execute_reply.started": "2025-09-18T12:54:15.835523Z" + } + }, "outputs": [], "source": [ "base_path = UPath(\"/rubin/lsdb_data\")" @@ -144,7 +160,9 @@ "\n", "This LSDB-formatted file is the same as the DP1 `Object` table but with additional columns, `_psfMag` and `_psfMagErr`, which are the corresponding `_psfFlux` columns converted to magnitudes (for each filter, ``, in $ugrizy$).\n", "\n", - "[Schema browser for the DP1 Object table](https://sdm-schemas.lsst.io/dp1.html#Object)." + "[Schema browser for the DP1 Object table](https://sdm-schemas.lsst.io/dp1.html#Object).\n", + "\n", + "Nested columns also have additional columns such as `psfMag` and `psfMagErr` (see section 2.1.2 below)." ] }, { @@ -157,9 +175,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 30, "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:15.867567Z", + "iopub.status.busy": "2025-09-18T12:54:15.867376Z", + "iopub.status.idle": "2025-09-18T12:54:18.495281Z", + "shell.execute_reply": "2025-09-18T12:54:18.494756Z", + "shell.execute_reply.started": "2025-09-18T12:54:15.867528Z" + } + }, "outputs": [], "source": [ "object_cat = lsdb.open_catalog(base_path / \"object_collection\")" @@ -167,10 +193,376 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 31, "id": "c6626b82-07b8-4a06-80dc-96aa78fe1dbe", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.496003Z", + "iopub.status.busy": "2025-09-18T12:54:18.495798Z", + "iopub.status.idle": "2025-09-18T12:54:18.526922Z", + "shell.execute_reply": "2025-09-18T12:54:18.526438Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.495987Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", + "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=389 \n", + "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 31, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat" ] @@ -205,10 +597,38 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 32, "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.528199Z", + "iopub.status.busy": "2025-09-18T12:54:18.528004Z", + "iopub.status.idle": "2025-09-18T12:54:18.549325Z", + "shell.execute_reply": "2025-09-18T12:54:18.548837Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.528183Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", + " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", + " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", + " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", + " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", + " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", + " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", + " 'objectForcedSource'],\n", + " dtype='object')" + ] + }, + "execution_count": 32, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat.columns" ] @@ -218,14 +638,22 @@ "id": "d251a7d0-620a-45d6-aa32-4cc3138f70e6", "metadata": {}, "source": [ - "Optional: uncomment the cell below to display the names of all the 1304 columns from the `Object` catalog." + "Optional: uncomment the cell below to display the names of a larger subset of the 1304 columns from the `Object` catalog." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 68, "id": "bcf956b0-8d59-445d-bd9b-ba0914d78c4b", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T13:13:43.452051Z", + "iopub.status.busy": "2025-09-18T13:13:43.451736Z", + "iopub.status.idle": "2025-09-18T13:13:43.454712Z", + "shell.execute_reply": "2025-09-18T13:13:43.454141Z", + "shell.execute_reply.started": "2025-09-18T13:13:43.452030Z" + } + }, "outputs": [], "source": [ "# object_cat.all_columns" @@ -241,10 +669,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 59, "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:56:41.537674Z", + "iopub.status.busy": "2025-09-18T12:56:41.537360Z", + "iopub.status.idle": "2025-09-18T12:56:41.542172Z", + "shell.execute_reply": "2025-09-18T12:56:41.541643Z", + "shell.execute_reply.started": "2025-09-18T12:56:41.537652Z" + } + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "u_psfMag\n", + "u_psfMagErr\n", + "g_psfMag\n", + "g_psfMagErr\n", + "r_psfMag\n", + "r_psfMagErr\n", + "i_psfMag\n", + "i_psfMagErr\n", + "z_psfMag\n", + "z_psfMagErr\n", + "y_psfMag\n", + "y_psfMagErr\n" + ] + } + ], "source": [ "for col in object_cat.all_columns:\n", " if col.find('psfMag') > 0:\n", @@ -261,10 +716,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 35, "id": "c27232da-4cfd-423d-a17e-cb4e69499b12", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.592782Z", + "iopub.status.busy": "2025-09-18T12:54:18.592572Z", + "iopub.status.idle": "2025-09-18T12:54:18.619694Z", + "shell.execute_reply": "2025-09-18T12:54:18.619219Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.592764Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['objectForcedSource']" + ] + }, + "execution_count": 35, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat.nested_columns" ] @@ -274,15 +748,61 @@ "id": "63faee7e-3de1-4612-a94b-6248ec63f16d", "metadata": {}, "source": [ - "Display the fields in the nested column." + "Display the fields in the nested column.\n", + "Note the additional columns `psfMag` and `psfMagErr`." ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 36, "id": "3678573c-8f9a-4076-8c3b-f5e2cbb7a2c7", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.620262Z", + "iopub.status.busy": "2025-09-18T12:54:18.620087Z", + "iopub.status.idle": "2025-09-18T12:54:18.639860Z", + "shell.execute_reply": "2025-09-18T12:54:18.639408Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.620247Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['coord_ra',\n", + " 'coord_dec',\n", + " 'visit',\n", + " 'detector',\n", + " 'band',\n", + " 'psfFlux',\n", + " 'psfFluxErr',\n", + " 'psfFlux_flag',\n", + " 'psfDiffFlux',\n", + " 'psfDiffFluxErr',\n", + " 'psfDiffFlux_flag',\n", + " 'pixelFlags_bad',\n", + " 'pixelFlags_cr',\n", + " 'pixelFlags_crCenter',\n", + " 'pixelFlags_edge',\n", + " 'pixelFlags_interpolated',\n", + " 'pixelFlags_interpolatedCenter',\n", + " 'pixelFlags_nodata',\n", + " 'pixelFlags_saturated',\n", + " 'pixelFlags_saturatedCenter',\n", + " 'pixelFlags_suspect',\n", + " 'pixelFlags_suspectCenter',\n", + " 'invalidPsfFlag',\n", + " 'forcedSourceId',\n", + " 'psfMag',\n", + " 'psfMagErr',\n", + " 'midpointMjdTai']" + ] + }, + "execution_count": 36, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat[\"objectForcedSource\"].nest.fields" ] @@ -297,9 +817,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 37, "id": "af22e340-5692-4864-8ca6-4d5a665e7178", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.640488Z", + "iopub.status.busy": "2025-09-18T12:54:18.640317Z", + "iopub.status.idle": "2025-09-18T12:54:18.659432Z", + "shell.execute_reply": "2025-09-18T12:54:18.658990Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.640473Z" + } + }, "outputs": [], "source": [ "use_columns = ['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr',\n", @@ -308,9 +836,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 38, "id": "bf5d271e-3968-4583-b743-47cdab5e5561", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:18.660123Z", + "iopub.status.busy": "2025-09-18T12:54:18.659930Z", + "iopub.status.idle": "2025-09-18T12:54:21.071463Z", + "shell.execute_reply": "2025-09-18T12:54:21.070835Z", + "shell.execute_reply.started": "2025-09-18T12:54:18.660102Z" + } + }, "outputs": [], "source": [ "object_cat_selected_columns = lsdb.open_catalog(base_path / \"object_collection\",\n", @@ -319,10 +855,31 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 39, "id": "6a6eda41-db4f-43d1-b769-c4df1a1c6e84", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:21.072340Z", + "iopub.status.busy": "2025-09-18T12:54:21.072131Z", + "iopub.status.idle": "2025-09-18T12:54:21.075925Z", + "shell.execute_reply": "2025-09-18T12:54:21.075442Z", + "shell.execute_reply.started": "2025-09-18T12:54:21.072322Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr'],\n", + " dtype='object')" + ] + }, + "execution_count": 39, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat_selected_columns.columns" ] @@ -346,9 +903,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 40, "id": "bffa951f-f910-4103-837d-e095ef63db41", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:21.076651Z", + "iopub.status.busy": "2025-09-18T12:54:21.076425Z", + "iopub.status.idle": "2025-09-18T12:54:21.097076Z", + "shell.execute_reply": "2025-09-18T12:54:21.096615Z", + "shell.execute_reply.started": "2025-09-18T12:54:21.076633Z" + } + }, "outputs": [], "source": [ "ra_ecdfs = 53.16\n", @@ -357,9 +922,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 41, "id": "5a5d8111-6c2e-4c76-a939-447a9cd7b96f", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:21.098798Z", + "iopub.status.busy": "2025-09-18T12:54:21.098585Z", + "iopub.status.idle": "2025-09-18T12:54:22.339200Z", + "shell.execute_reply": "2025-09-18T12:54:22.338677Z", + "shell.execute_reply.started": "2025-09-18T12:54:21.098782Z" + } + }, "outputs": [], "source": [ "object_cat_ecdfs = object_cat.cone_search(ra=ra_ecdfs, dec=dec_ecdfs,\n", @@ -376,20 +949,414 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 42, "id": "d3b6022c-7e0b-4c52-a178-fe0c35f6ada3", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:22.339926Z", + "iopub.status.busy": "2025-09-18T12:54:22.339723Z", + "iopub.status.idle": "2025-09-18T12:54:22.365551Z", + "shell.execute_reply": "2025-09-18T12:54:22.365058Z", + "shell.execute_reply.started": "2025-09-18T12:54:22.339902Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=8
Order: 9, Pixel: 2299851double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 9, Pixel: 2299854..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2299876..............................................................................................................................
Order: 9, Pixel: 2299878..............................................................................................................................
\n", + "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=8 \n", + "2528712916652261376 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "2528716215187144704 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2528742603466211328 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2528743702977839104 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: search_points, 5 expressions\n", + "Expr=MapPartitions(search_points)" + ] + }, + "execution_count": 42, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat_ecdfs" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 43, "id": "21c7d923-dec5-4c75-bfd6-4602864420ec", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:22.366266Z", + "iopub.status.busy": "2025-09-18T12:54:22.366087Z", + "iopub.status.idle": "2025-09-18T12:54:22.378060Z", + "shell.execute_reply": "2025-09-18T12:54:22.377496Z", + "shell.execute_reply.started": "2025-09-18T12:54:22.366250Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", + " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", + " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", + " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", + " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", + " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", + " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", + " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", + " 'objectForcedSource'],\n", + " dtype='object')" + ] + }, + "execution_count": 43, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat_ecdfs.columns" ] @@ -404,10 +1371,29 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 44, "id": "f7dafb69-0a7b-4091-9bfa-3c43460744bf", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:22.378768Z", + "iopub.status.busy": "2025-09-18T12:54:22.378559Z", + "iopub.status.idle": "2025-09-18T12:54:43.553570Z", + "shell.execute_reply": "2025-09-18T12:54:43.553002Z", + "shell.execute_reply.started": "2025-09-18T12:54:22.378751Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
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lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", + "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=389 \n", + "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: lambda, 4 expressions\n", + "Expr=MapPartitions(lambda)" + ] + 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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1126386.055018...0.09095260641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1138826.060315...0.12807860641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1131546.062188...0.04767560641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1111466.062607...0.08525660641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.0998626.062018...0.0055360641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1078426.064204...0.13739260641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1083536.065384...0.16849360641.047911
+4 rows............
\n", + "10 rows x 42 columns" + ], + "text/plain": [ + " coord_dec coord_decErr coord_ra coord_raErr \\\n", + "_healpix_29 \n", + "9195875808926578 6.055018 0.000014 38.112638 0.000027 \n", + "9195883532105479 6.060315 0.000014 38.113882 0.000016 \n", + "9195884147047980 6.059977 0.000077 38.110133 0.000113 \n", + "9195885212200071 6.062188 0.000008 38.113154 0.000008 \n", + "9195885679351887 6.062607 0.000014 38.111146 0.000017 \n", + "9195895412822106 6.063319 0.000142 38.117222 0.00025 \n", + "9195975821955136 6.062018 0.000002 38.099862 0.000002 \n", + "9195977793920544 6.064204 0.000033 38.107842 0.000027 \n", + "9195978049796578 6.065086 0.000003 38.109232 0.000005 \n", + "9195978078224513 6.065384 0.000017 38.108353 0.000019 \n", + "\n", + " g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr \\\n", + "_healpix_29 \n", + "9195875808926578 1274.516846 97.626991 23.636637 0.08333 \n", + "9195883532105479 89.467979 75.252007 26.52083 1.329962 \n", + "9195884147047980 550.610413 76.316589 24.54789 0.151462 \n", + "9195885212200071 1776.998657 77.35807 23.275782 0.047295 \n", + "9195885679351887 890.506226 76.1539 24.025908 0.093077 \n", + "9195895412822106 613.264221 96.621689 24.430882 0.172498 \n", + "9195975821955136 20678.574219 98.712624 20.611198 0.005183 \n", + "9195977793920544 716.549133 75.797112 24.261885 0.115281 \n", + "9195978049796578 5265.098633 80.913536 22.096483 0.016687 \n", + "9195978078224513 806.570007 76.026337 24.133394 0.102645 \n", + "\n", + " i_psfFlux i_psfFluxErr ... y_psfFlux y_psfFluxErr \\\n", + "_healpix_29 ... \n", + "9195875808926578 ... \n", + "9195883532105479 ... \n", + "9195884147047980 ... \n", + "9195885212200071 ... \n", + "9195885679351887 ... \n", + "9195895412822106 ... \n", + "9195975821955136 93029.984375 400.546143 ... \n", + "9195977793920544 1638.996582 288.262207 ... \n", + "9195978049796578 16507.730469 303.508453 ... \n", + "9195978078224513 1609.817871 287.098694 ... \n", + "\n", + " y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr \\\n", + "_healpix_29 \n", + "9195875808926578 0.253183 \n", + "9195883532105479 0.253343 \n", + "9195884147047980 1.393253 \n", + "9195885212200071 0.13731 \n", + "9195885679351887 0.249914 \n", + "9195895412822106 2.553389 \n", + "9195975821955136 0.029594 \n", + "9195977793920544 0.585919 \n", + "9195978049796578 0.060191 \n", + "9195978078224513 0.314163 \n", + "\n", + " z_psfMag z_psfMagErr \\\n", + "_healpix_29 \n", + "9195875808926578 \n", + "9195883532105479 \n", + "9195884147047980 \n", + "9195885212200071 \n", + "9195885679351887 \n", + "9195895412822106 \n", + "9195975821955136 \n", + "9195977793920544 \n", + "9195978049796578 \n", + "9195978078224513 \n", + "\n", + " objectForcedSource \n", + "_healpix_29 \n", + "9195875808926578 [{coord_ra: 38.112638, coord_dec: 6.055018, vi... \n", + "9195883532105479 [{coord_ra: 38.113882, coord_dec: 6.060315, vi... \n", + "9195884147047980 [{coord_ra: 38.110133, coord_dec: 6.059977, vi... \n", + "9195885212200071 [{coord_ra: 38.113154, coord_dec: 6.062188, vi... \n", + "9195885679351887 [{coord_ra: 38.111146, coord_dec: 6.062607, vi... \n", + "9195895412822106 [{coord_ra: 38.117222, coord_dec: 6.063319, vi... \n", + "9195975821955136 [{coord_ra: 38.099862, coord_dec: 6.062018, vi... \n", + "9195977793920544 [{coord_ra: 38.107842, coord_dec: 6.064204, vi... \n", + "9195978049796578 [{coord_ra: 38.109232, coord_dec: 6.065086, vi... \n", + "9195978078224513 [{coord_ra: 38.108353, coord_dec: 6.065384, vi... \n", + "\n", + "[10 rows x 42 columns]" + ] + }, + "execution_count": 46, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat_mag_range.head(10)" ] @@ -491,9 +2706,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 47, "id": "2c19a686-c4ce-49bc-836e-d5becc7f8b7b", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:44.074114Z", + "iopub.status.busy": "2025-09-18T12:54:44.073830Z", + "iopub.status.idle": "2025-09-18T12:54:44.077078Z", + "shell.execute_reply": "2025-09-18T12:54:44.076387Z", + "shell.execute_reply.started": "2025-09-18T12:54:44.074085Z" + } + }, "outputs": [], "source": [ "# object_cat." @@ -525,9 +2748,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "id": "ce101fd1-06bb-4b3b-8f32-7c128079cbb0", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:44.077878Z", + "iopub.status.busy": "2025-09-18T12:54:44.077666Z", + "iopub.status.idle": "2025-09-18T12:54:46.022196Z", + "shell.execute_reply": "2025-09-18T12:54:46.021596Z", + "shell.execute_reply.started": "2025-09-18T12:54:44.077860Z" + } + }, "outputs": [], "source": [ "object_cat_lite = lsdb.open_catalog(base_path / \"object_collection_lite\")" @@ -543,10 +2774,376 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 49, "id": "57ef8891-4567-4d75-9611-0d07eb0acd28", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:46.022994Z", + "iopub.status.busy": "2025-09-18T12:54:46.022781Z", + "iopub.status.idle": "2025-09-18T12:54:46.054386Z", + "shell.execute_reply": "2025-09-18T12:54:46.053869Z", + "shell.execute_reply.started": "2025-09-18T12:54:46.022977Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<band: [string], coord_dec: [double], co...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", + "
42 out of 74 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", + "npartitions=389 \n", + "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", + "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 49, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "object_cat_lite" ] @@ -561,9 +3158,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 50, "id": "cf587923-8b43-47fa-af57-6bdce6062035", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:46.055104Z", + "iopub.status.busy": "2025-09-18T12:54:46.054914Z", + "iopub.status.idle": "2025-09-18T12:54:46.062999Z", + "shell.execute_reply": "2025-09-18T12:54:46.062556Z", + "shell.execute_reply.started": "2025-09-18T12:54:46.055088Z" + } + }, "outputs": [], "source": [ "# object_cat_lite.all_columns" @@ -583,20 +3188,282 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 51, "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:46.063636Z", + "iopub.status.busy": "2025-09-18T12:54:46.063447Z", + "iopub.status.idle": "2025-09-18T12:54:48.171783Z", + "shell.execute_reply": "2025-09-18T12:54:48.171234Z", + "shell.execute_reply.started": "2025-09-18T12:54:46.063621Z" + } + }, "outputs": [], "source": [ "dia_object_cat = lsdb.open_catalog(base_path / \"dia_object_collection\")" ] }, + { + "cell_type": "markdown", + "id": "41897f53-eb64-44a3-af2c-9953fbb2beef", + "metadata": {}, + "source": [ + "Check which columns are nested." + ] + }, { "cell_type": "code", - "execution_count": null, - "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", + "execution_count": 69, + "id": "7b3b8279-4823-4103-a354-7a555bab06ae", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T13:25:29.193354Z", + "iopub.status.busy": "2025-09-18T13:25:29.193010Z", + "iopub.status.idle": "2025-09-18T13:25:29.198442Z", + "shell.execute_reply": "2025-09-18T13:25:29.197986Z", + "shell.execute_reply.started": "2025-09-18T13:25:29.193332Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['diaObjectForcedSource', 'diaSource']" + ] + }, + "execution_count": 69, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dia_object_cat.nested_columns" + ] + }, + { + "cell_type": "markdown", + "id": "093979e4-4bb1-49cd-900c-0a25fa349a9e", "metadata": {}, - "outputs": [], + "source": [ + "Display the fields in the `diaSource` nested column.\n", + "Note the additional columns such as `psfMag`, `psfMagErr`, `scienceMag` and `scienceMagErr`." + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "e8581870-76c5-4f78-8d77-8de6a3526ea7", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T13:32:24.685530Z", + "iopub.status.busy": "2025-09-18T13:32:24.685242Z", + "iopub.status.idle": "2025-09-18T13:32:24.691015Z", + "shell.execute_reply": "2025-09-18T13:32:24.690421Z", + "shell.execute_reply.started": "2025-09-18T13:32:24.685510Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "['band',\n", + " 'centroid_flag',\n", + " 'coord_dec',\n", + " 'coord_ra',\n", + " 'dec',\n", + " 'decErr',\n", + " 'diaSourceId',\n", + " 'forced_PsfFlux_flag',\n", + " 'forced_PsfFlux_flag_edge',\n", + " 'forced_PsfFlux_flag_noGoodPixels',\n", + " 'midpointMjdTai',\n", + " 'pixelFlags',\n", + " 'pixelFlags_bad',\n", + " 'pixelFlags_cr',\n", + " 'pixelFlags_crCenter',\n", + " 'pixelFlags_edge',\n", + " 'pixelFlags_interpolated',\n", + " 'pixelFlags_interpolatedCenter',\n", + " 'pixelFlags_nodata',\n", + " 'pixelFlags_nodataCenter',\n", + " 'pixelFlags_offimage',\n", + " 'pixelFlags_saturated',\n", + " 'pixelFlags_saturatedCenter',\n", + " 'pixelFlags_streak',\n", + " 'pixelFlags_streakCenter',\n", + " 'pixelFlags_suspect',\n", + " 'pixelFlags_suspectCenter',\n", + " 'psfFlux',\n", + " 'psfFlux_flag',\n", + " 'psfFlux_flag_edge',\n", + " 'psfFlux_flag_noGoodPixels',\n", + " 'psfFluxErr',\n", + " 'psfMag',\n", + " 'psfMagErr',\n", + " 'ra',\n", + " 'raErr',\n", + " 'reliability',\n", + " 'scienceFlux',\n", + " 'scienceFluxErr',\n", + " 'scienceMag',\n", + " 'scienceMagErr',\n", + " 'shape_flag',\n", + " 'shape_flag_no_pixels',\n", + " 'shape_flag_not_contained',\n", + " 'shape_flag_parent_source',\n", + " 'snr',\n", + " 'trail_flag_edge',\n", + " 'visit',\n", + " 'x',\n", + " 'xErr',\n", + " 'y',\n", + " 'yErr']" + ] + }, + "execution_count": 72, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "dia_object_cat[\"diaSource\"].nest.fields" + ] + }, + { + "cell_type": "code", + "execution_count": 52, + "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:48.172504Z", + "iopub.status.busy": "2025-09-18T12:54:48.172313Z", + "iopub.status.idle": "2025-09-18T12:54:48.184344Z", + "shell.execute_reply": "2025-09-18T12:54:48.183877Z", + "shell.execute_reply.started": "2025-09-18T12:54:48.172486Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog dia_object_lc:
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decdiaObjectIdnDiaSourcesraradecMjdTaitractdiaObjectForcedSourcediaSource
npartitions=208
Order: 6, Pixel: 130double[pyarrow]int64[pyarrow]int64[pyarrow]double[pyarrow]double[pyarrow]int64[pyarrow]nested<band: [string], coord_dec: [double], co...nested<band: [string], centroid_flag: [bool], ...
Order: 6, Pixel: 136........................
...........................
Order: 11, Pixel: 36833621........................
Order: 7, Pixel: 143884........................
\n", + "
8 out of 140 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " dec diaObjectId nDiaSources ra radecMjdTai tract diaObjectForcedSource diaSource\n", + "npartitions=208 \n", + "9147936743096320 double[pyarrow] int64[pyarrow] int64[pyarrow] double[pyarrow] double[pyarrow] int64[pyarrow] nested nested\n", + "9570149208162304 ... ... ... ... ... ... ... ...\n", + "... ... ... ... ... ... ... ... ...\n", + "2531234096814751744 ... ... ... ... ... ... ... ...\n", + "2531251689000796160 ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 52, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "dia_object_cat" ] @@ -623,9 +3490,17 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 53, "id": "e8dd3508-9aff-4157-a911-d555128c9a37", - "metadata": {}, + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:48.184967Z", + "iopub.status.busy": "2025-09-18T12:54:48.184792Z", + "iopub.status.idle": "2025-09-18T12:54:48.290568Z", + "shell.execute_reply": "2025-09-18T12:54:48.290029Z", + "shell.execute_reply.started": "2025-09-18T12:54:48.184953Z" + } + }, "outputs": [], "source": [ "pz_cat = lsdb.open_catalog(base_path / \"object_photoz\")" @@ -641,10 +3516,859 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 54, "id": "6cfe9c30-21dc-4b22-8ae0-d0552ecdcef3", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:48.291273Z", + "iopub.status.busy": "2025-09-18T12:54:48.291075Z", + "iopub.status.idle": "2025-09-18T12:54:48.349839Z", + "shell.execute_reply": "2025-09-18T12:54:48.349301Z", + "shell.execute_reply.started": "2025-09-18T12:54:48.291256Z" + } + }, + "outputs": [ + { + "data": { + "text/html": [ + "
lsdb Catalog object_photoz:
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npartitions=4
Order: 3, Pixel: 2double[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]int64[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]
Order: 5, Pixel: 4471......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 2, Pixel: 80......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 0, Pixel: 8......................................................................................................................................................................................................................................................................................................................................................................................................
\n", + "
130 out of 130 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" + ], + "text/plain": [ + "Dask NestedFrame Structure:\n", + " coord_dec coord_ra g_cModelMag g_cModelMagErr g_gaap1p0Mag g_gaap1p0MagErr g_gaap3p0Mag g_gaap3p0MagErr g_kronMag g_kronMagErr g_psfMag g_psfMagErr g_sersicMag g_sersicMagErr i_cModelMag i_cModelMagErr i_gaap1p0Mag i_gaap1p0MagErr i_gaap3p0Mag i_gaap3p0MagErr i_kronMag i_kronMagErr i_psfMag i_psfMagErr i_sersicMag i_sersicMagErr objectId r_cModelMag r_cModelMagErr r_gaap1p0Mag r_gaap1p0MagErr r_gaap3p0Mag r_gaap3p0MagErr r_kronMag r_kronMagErr r_psfMag r_psfMagErr r_sersicMag r_sersicMagErr u_cModelMag u_cModelMagErr u_gaap1p0Mag u_gaap1p0MagErr u_gaap3p0Mag u_gaap3p0MagErr u_kronMag u_kronMagErr u_psfMag u_psfMagErr u_sersicMag u_sersicMagErr y_cModelMag y_cModelMagErr y_gaap1p0Mag y_gaap1p0MagErr y_gaap3p0Mag y_gaap3p0MagErr y_kronMag y_kronMagErr y_psfMag y_psfMagErr y_sersicMag y_sersicMagErr z_cModelMag z_cModelMagErr z_gaap1p0Mag z_gaap1p0MagErr z_gaap3p0Mag z_gaap3p0MagErr z_kronMag z_kronMagErr z_psfMag z_psfMagErr z_sersicMag z_sersicMagErr lephare_z_median lephare_z_mean lephare_z_mode lephare_z_err95_low lephare_z_err95_high lephare_z_err68_low lephare_z_err68_high knn_z_median knn_z_mode knn_z_err95_low knn_z_err95_high knn_z_err68_low knn_z_err68_high tpz_z_median tpz_z_mean tpz_z_mode tpz_z_err95_low tpz_z_err95_high tpz_z_err68_low tpz_z_err68_high cmnn_z_median cmnn_z_mean cmnn_z_mode cmnn_z_err95_low cmnn_z_err95_high cmnn_z_err68_low cmnn_z_err68_high gpz_z_median gpz_z_mean gpz_z_mode gpz_z_err95_low gpz_z_err95_high gpz_z_err68_low gpz_z_err68_high bpz_z_median bpz_z_mean bpz_z_mode bpz_z_err95_low bpz_z_err95_high bpz_z_err68_low bpz_z_err68_high dnf_z_median dnf_z_mean dnf_z_mode dnf_z_err95_low dnf_z_err95_high dnf_z_err68_low dnf_z_err68_high fzboost_z_median fzboost_z_mean fzboost_z_mode fzboost_z_err95_low fzboost_z_err95_high fzboost_z_err68_low fzboost_z_err68_high\n", + "npartitions=4 \n", + "9007199254740992 double[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] int64[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow]\n", + "1258474620873342976 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "1441151880758558720 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2305843009213693952 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "2594073385365405696 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", + "Dask Name: nestedframe, 3 expressions\n", + "Expr=MapPartitions(NestedFrame)" + ] + }, + "execution_count": 54, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ "pz_cat" ] @@ -675,10 +4399,37 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 55, "id": "035604c1-816d-4e1e-ad95-061b04249e4f", - "metadata": {}, - "outputs": [], + "metadata": { + "execution": { + "iopub.execute_input": "2025-09-18T12:54:48.350558Z", + "iopub.status.busy": "2025-09-18T12:54:48.350358Z", + "iopub.status.idle": "2025-09-18T12:54:48.661192Z", + "shell.execute_reply": "2025-09-18T12:54:48.660545Z", + "shell.execute_reply.started": "2025-09-18T12:54:48.350525Z" + } + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/hats/inspection/visualize_catalog.py:303: UserWarning: This plot contains HEALPix pixels smaller than a pixel of the plot. Some values may be lost\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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", 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Some values may be lost\n", + " warnings.warn(\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ "fov = (100 * u.deg, 120 * u.deg)\n", "center = SkyCoord(70 * u.deg, -30 * u.deg)\n", From e11f74ddcb2c8f907454bc56a4f6b739799372a7 Mon Sep 17 00:00:00 2001 From: plazas Date: Thu, 18 Sep 2025 13:42:01 +0000 Subject: [PATCH 6/8] Clear outputs --- .../102_5_LSDB_data_access.ipynb | 3898 +---------------- 1 file changed, 80 insertions(+), 3818 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 6f597df2..91b09dc3 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -81,17 +81,9 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": null, "id": "963c1141-196b-49c1-8db0-019f3a22c6ad", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:15.831594Z", - "iopub.status.busy": "2025-09-18T12:54:15.831249Z", - "iopub.status.idle": "2025-09-18T12:54:15.834630Z", - "shell.execute_reply": "2025-09-18T12:54:15.834145Z", - "shell.execute_reply.started": "2025-09-18T12:54:15.831559Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "import lsdb\n", @@ -112,17 +104,9 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": null, "id": "98b33f9b-914a-4184-8765-66c96e9c2cef", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:15.835560Z", - "iopub.status.busy": "2025-09-18T12:54:15.835359Z", - "iopub.status.idle": "2025-09-18T12:54:15.866997Z", - "shell.execute_reply": "2025-09-18T12:54:15.866461Z", - "shell.execute_reply.started": "2025-09-18T12:54:15.835523Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "base_path = UPath(\"/rubin/lsdb_data\")" @@ -175,17 +159,9 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": null, "id": "8acbb5a9-c485-4852-8f02-4d481df259c4", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:15.867567Z", - "iopub.status.busy": "2025-09-18T12:54:15.867376Z", - "iopub.status.idle": "2025-09-18T12:54:18.495281Z", - "shell.execute_reply": "2025-09-18T12:54:18.494756Z", - "shell.execute_reply.started": "2025-09-18T12:54:15.867528Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat = lsdb.open_catalog(base_path / \"object_collection\")" @@ -193,376 +169,10 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "id": "c6626b82-07b8-4a06-80dc-96aa78fe1dbe", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.496003Z", - "iopub.status.busy": "2025-09-18T12:54:18.495798Z", - "iopub.status.idle": "2025-09-18T12:54:18.526922Z", - "shell.execute_reply": "2025-09-18T12:54:18.526438Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.495987Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog object_lc:
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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<coord_ra: [double], coord_dec: [double]...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", - "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=389 \n", - "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat" ] @@ -597,38 +207,10 @@ }, { "cell_type": "code", - "execution_count": 32, + "execution_count": null, "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.528199Z", - "iopub.status.busy": "2025-09-18T12:54:18.528004Z", - "iopub.status.idle": "2025-09-18T12:54:18.549325Z", - "shell.execute_reply": "2025-09-18T12:54:18.548837Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.528183Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", - " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", - " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", - " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", - " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", - " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", - " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", - " 'objectForcedSource'],\n", - " dtype='object')" - ] - }, - "execution_count": 32, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat.columns" ] @@ -643,17 +225,9 @@ }, { "cell_type": "code", - "execution_count": 68, + "execution_count": null, "id": "bcf956b0-8d59-445d-bd9b-ba0914d78c4b", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T13:13:43.452051Z", - "iopub.status.busy": "2025-09-18T13:13:43.451736Z", - "iopub.status.idle": "2025-09-18T13:13:43.454712Z", - "shell.execute_reply": "2025-09-18T13:13:43.454141Z", - "shell.execute_reply.started": "2025-09-18T13:13:43.452030Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# object_cat.all_columns" @@ -669,37 +243,10 @@ }, { "cell_type": "code", - "execution_count": 59, + "execution_count": null, "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:56:41.537674Z", - "iopub.status.busy": "2025-09-18T12:56:41.537360Z", - "iopub.status.idle": "2025-09-18T12:56:41.542172Z", - "shell.execute_reply": "2025-09-18T12:56:41.541643Z", - "shell.execute_reply.started": "2025-09-18T12:56:41.537652Z" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "u_psfMag\n", - "u_psfMagErr\n", - "g_psfMag\n", - "g_psfMagErr\n", - "r_psfMag\n", - "r_psfMagErr\n", - "i_psfMag\n", - "i_psfMagErr\n", - "z_psfMag\n", - "z_psfMagErr\n", - "y_psfMag\n", - "y_psfMagErr\n" - ] - } - ], + "metadata": {}, + "outputs": [], "source": [ "for col in object_cat.all_columns:\n", " if col.find('psfMag') > 0:\n", @@ -716,29 +263,10 @@ }, { "cell_type": "code", - "execution_count": 35, + "execution_count": null, "id": "c27232da-4cfd-423d-a17e-cb4e69499b12", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.592782Z", - "iopub.status.busy": "2025-09-18T12:54:18.592572Z", - "iopub.status.idle": "2025-09-18T12:54:18.619694Z", - "shell.execute_reply": "2025-09-18T12:54:18.619219Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.592764Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['objectForcedSource']" - ] - }, - "execution_count": 35, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat.nested_columns" ] @@ -754,55 +282,10 @@ }, { "cell_type": "code", - "execution_count": 36, + "execution_count": null, "id": "3678573c-8f9a-4076-8c3b-f5e2cbb7a2c7", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.620262Z", - "iopub.status.busy": "2025-09-18T12:54:18.620087Z", - "iopub.status.idle": "2025-09-18T12:54:18.639860Z", - "shell.execute_reply": "2025-09-18T12:54:18.639408Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.620247Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['coord_ra',\n", - " 'coord_dec',\n", - " 'visit',\n", - " 'detector',\n", - " 'band',\n", - " 'psfFlux',\n", - " 'psfFluxErr',\n", - " 'psfFlux_flag',\n", - " 'psfDiffFlux',\n", - " 'psfDiffFluxErr',\n", - " 'psfDiffFlux_flag',\n", - " 'pixelFlags_bad',\n", - " 'pixelFlags_cr',\n", - " 'pixelFlags_crCenter',\n", - " 'pixelFlags_edge',\n", - " 'pixelFlags_interpolated',\n", - " 'pixelFlags_interpolatedCenter',\n", - " 'pixelFlags_nodata',\n", - " 'pixelFlags_saturated',\n", - " 'pixelFlags_saturatedCenter',\n", - " 'pixelFlags_suspect',\n", - " 'pixelFlags_suspectCenter',\n", - " 'invalidPsfFlag',\n", - " 'forcedSourceId',\n", - " 'psfMag',\n", - " 'psfMagErr',\n", - " 'midpointMjdTai']" - ] - }, - "execution_count": 36, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat[\"objectForcedSource\"].nest.fields" ] @@ -817,17 +300,9 @@ }, { "cell_type": "code", - "execution_count": 37, + "execution_count": null, "id": "af22e340-5692-4864-8ca6-4d5a665e7178", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.640488Z", - "iopub.status.busy": "2025-09-18T12:54:18.640317Z", - "iopub.status.idle": "2025-09-18T12:54:18.659432Z", - "shell.execute_reply": "2025-09-18T12:54:18.658990Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.640473Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "use_columns = ['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr',\n", @@ -836,17 +311,9 @@ }, { "cell_type": "code", - "execution_count": 38, + "execution_count": null, "id": "bf5d271e-3968-4583-b743-47cdab5e5561", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:18.660123Z", - "iopub.status.busy": "2025-09-18T12:54:18.659930Z", - "iopub.status.idle": "2025-09-18T12:54:21.071463Z", - "shell.execute_reply": "2025-09-18T12:54:21.070835Z", - "shell.execute_reply.started": "2025-09-18T12:54:18.660102Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_selected_columns = lsdb.open_catalog(base_path / \"object_collection\",\n", @@ -855,31 +322,10 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": null, "id": "6a6eda41-db4f-43d1-b769-c4df1a1c6e84", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:21.072340Z", - "iopub.status.busy": "2025-09-18T12:54:21.072131Z", - "iopub.status.idle": "2025-09-18T12:54:21.075925Z", - "shell.execute_reply": "2025-09-18T12:54:21.075442Z", - "shell.execute_reply.started": "2025-09-18T12:54:21.072322Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr'],\n", - " dtype='object')" - ] - }, - "execution_count": 39, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_selected_columns.columns" ] @@ -903,17 +349,9 @@ }, { "cell_type": "code", - "execution_count": 40, + "execution_count": null, "id": "bffa951f-f910-4103-837d-e095ef63db41", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:21.076651Z", - "iopub.status.busy": "2025-09-18T12:54:21.076425Z", - "iopub.status.idle": "2025-09-18T12:54:21.097076Z", - "shell.execute_reply": "2025-09-18T12:54:21.096615Z", - "shell.execute_reply.started": "2025-09-18T12:54:21.076633Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "ra_ecdfs = 53.16\n", @@ -922,17 +360,9 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": null, "id": "5a5d8111-6c2e-4c76-a939-447a9cd7b96f", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:21.098798Z", - "iopub.status.busy": "2025-09-18T12:54:21.098585Z", - "iopub.status.idle": "2025-09-18T12:54:22.339200Z", - "shell.execute_reply": "2025-09-18T12:54:22.338677Z", - "shell.execute_reply.started": "2025-09-18T12:54:21.098782Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_ecdfs = object_cat.cone_search(ra=ra_ecdfs, dec=dec_ecdfs,\n", @@ -949,414 +379,20 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": null, "id": "d3b6022c-7e0b-4c52-a178-fe0c35f6ada3", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:22.339926Z", - "iopub.status.busy": "2025-09-18T12:54:22.339723Z", - "iopub.status.idle": "2025-09-18T12:54:22.365551Z", - "shell.execute_reply": "2025-09-18T12:54:22.365058Z", - "shell.execute_reply.started": "2025-09-18T12:54:22.339902Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
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Order: 9, Pixel: 2299854..............................................................................................................................
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Order: 9, Pixel: 2299876..............................................................................................................................
Order: 9, Pixel: 2299878..............................................................................................................................
\n", - "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=8 \n", - "2528712916652261376 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "2528716215187144704 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2528742603466211328 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2528743702977839104 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: search_points, 5 expressions\n", - "Expr=MapPartitions(search_points)" - ] - }, - "execution_count": 42, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_ecdfs" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": null, "id": "21c7d923-dec5-4c75-bfd6-4602864420ec", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:22.366266Z", - "iopub.status.busy": "2025-09-18T12:54:22.366087Z", - "iopub.status.idle": "2025-09-18T12:54:22.378060Z", - "shell.execute_reply": "2025-09-18T12:54:22.377496Z", - "shell.execute_reply.started": "2025-09-18T12:54:22.366250Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "Index(['coord_dec', 'coord_decErr', 'coord_ra', 'coord_raErr', 'g_psfFlux',\n", - " 'g_psfFluxErr', 'g_psfMag', 'g_psfMagErr', 'i_psfFlux', 'i_psfFluxErr',\n", - " 'i_psfMag', 'i_psfMagErr', 'objectId', 'patch', 'r_psfFlux',\n", - " 'r_psfFluxErr', 'r_psfMag', 'r_psfMagErr', 'refBand', 'refFwhm',\n", - " 'shape_flag', 'shape_xx', 'shape_xy', 'shape_yy', 'tract', 'u_psfFlux',\n", - " 'u_psfFluxErr', 'u_psfMag', 'u_psfMagErr', 'x', 'xErr', 'y',\n", - " 'y_psfFlux', 'y_psfFluxErr', 'y_psfMag', 'y_psfMagErr', 'yErr',\n", - " 'z_psfFlux', 'z_psfFluxErr', 'z_psfMag', 'z_psfMagErr',\n", - " 'objectForcedSource'],\n", - " dtype='object')" - ] - }, - "execution_count": 43, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_ecdfs.columns" ] @@ -1371,29 +407,10 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": null, "id": "f7dafb69-0a7b-4091-9bfa-3c43460744bf", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:22.378768Z", - "iopub.status.busy": "2025-09-18T12:54:22.378559Z", - "iopub.status.idle": "2025-09-18T12:54:43.553570Z", - "shell.execute_reply": "2025-09-18T12:54:43.553002Z", - "shell.execute_reply.started": "2025-09-18T12:54:22.378751Z" - } - }, - "outputs": [ - { - "data": { - "image/png": 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", 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lsdb Catalog object_lc:
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Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", - "
42 out of 1304 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=389 \n", - "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: lambda, 4 expressions\n", - "Expr=MapPartitions(lambda)" - ] - }, - "execution_count": 45, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_mag_range = object_cat.query(\"r_psfMag > 16 and r_psfMag < 24\")\n", "object_cat_mag_range" @@ -1825,873 +476,10 @@ }, { "cell_type": "code", - 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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1126386.055018...0.09095260641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1138826.060315...0.12807860641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1131546.062188...0.04767560641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
38.1111466.062607...0.08525660641.047911
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coord_racoord_dec...psfMagErrmidpointMjdTai
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"shell.execute_reply": "2025-09-18T12:54:44.076387Z", - "shell.execute_reply.started": "2025-09-18T12:54:44.074085Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# object_cat." @@ -2748,17 +528,9 @@ }, { "cell_type": "code", - "execution_count": 48, + "execution_count": null, "id": "ce101fd1-06bb-4b3b-8f32-7c128079cbb0", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:44.077878Z", - "iopub.status.busy": "2025-09-18T12:54:44.077666Z", - "iopub.status.idle": "2025-09-18T12:54:46.022196Z", - "shell.execute_reply": "2025-09-18T12:54:46.021596Z", - "shell.execute_reply.started": "2025-09-18T12:54:44.077860Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "object_cat_lite = lsdb.open_catalog(base_path / \"object_collection_lite\")" @@ -2774,376 +546,10 @@ }, { "cell_type": "code", - "execution_count": 49, + "execution_count": null, "id": "57ef8891-4567-4d75-9611-0d07eb0acd28", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:46.022994Z", - 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coord_deccoord_decErrcoord_racoord_raErrg_psfFluxg_psfFluxErrg_psfMagg_psfMagErri_psfFluxi_psfFluxErri_psfMagi_psfMagErrobjectIdpatchr_psfFluxr_psfFluxErrr_psfMagr_psfMagErrrefBandrefFwhmshape_flagshape_xxshape_xyshape_yytractu_psfFluxu_psfFluxErru_psfMagu_psfMagErrxxErryy_psfFluxy_psfFluxErry_psfMagy_psfMagErryErrz_psfFluxz_psfFluxErrz_psfMagz_psfMagErrobjectForcedSource
npartitions=389
Order: 6, Pixel: 130double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]string[pyarrow]float[pyarrow]bool[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]int64[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]float[pyarrow]nested<band: [string], coord_dec: [double], co...
Order: 8, Pixel: 2176..............................................................................................................................
.................................................................................................................................
Order: 9, Pixel: 2302101..............................................................................................................................
Order: 7, Pixel: 143884..............................................................................................................................
\n", - "
42 out of 74 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " coord_dec coord_decErr coord_ra coord_raErr g_psfFlux g_psfFluxErr g_psfMag g_psfMagErr i_psfFlux i_psfFluxErr i_psfMag i_psfMagErr objectId patch r_psfFlux r_psfFluxErr r_psfMag r_psfMagErr refBand refFwhm shape_flag shape_xx shape_xy shape_yy tract u_psfFlux u_psfFluxErr u_psfMag u_psfMagErr x xErr y y_psfFlux y_psfFluxErr y_psfMag y_psfMagErr yErr z_psfFlux z_psfFluxErr z_psfMag z_psfMagErr objectForcedSource\n", - "npartitions=389 \n", - "9147936743096320 double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] string[pyarrow] float[pyarrow] bool[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] int64[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] float[pyarrow] nested\n", - "9570149208162304 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "object_cat_lite" ] @@ -3158,17 +564,9 @@ }, { "cell_type": "code", - "execution_count": 50, + "execution_count": null, "id": "cf587923-8b43-47fa-af57-6bdce6062035", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:46.055104Z", - "iopub.status.busy": "2025-09-18T12:54:46.054914Z", - "iopub.status.idle": "2025-09-18T12:54:46.062999Z", - "shell.execute_reply": "2025-09-18T12:54:46.062556Z", - "shell.execute_reply.started": "2025-09-18T12:54:46.055088Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "# object_cat_lite.all_columns" @@ -3188,17 +586,9 @@ }, { "cell_type": "code", - "execution_count": 51, + "execution_count": null, "id": "a99dd0ea-6206-494d-bf92-2ea5cf53a1af", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:46.063636Z", - "iopub.status.busy": "2025-09-18T12:54:46.063447Z", - "iopub.status.idle": "2025-09-18T12:54:48.171783Z", - "shell.execute_reply": "2025-09-18T12:54:48.171234Z", - "shell.execute_reply.started": "2025-09-18T12:54:46.063621Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "dia_object_cat = lsdb.open_catalog(base_path / \"dia_object_collection\")" @@ -3214,29 +604,10 @@ }, { "cell_type": "code", - "execution_count": 69, + "execution_count": null, "id": "7b3b8279-4823-4103-a354-7a555bab06ae", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T13:25:29.193354Z", - "iopub.status.busy": "2025-09-18T13:25:29.193010Z", - "iopub.status.idle": "2025-09-18T13:25:29.198442Z", - "shell.execute_reply": "2025-09-18T13:25:29.197986Z", - "shell.execute_reply.started": "2025-09-18T13:25:29.193332Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['diaObjectForcedSource', 'diaSource']" - ] - }, - "execution_count": 69, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "dia_object_cat.nested_columns" ] @@ -3252,218 +623,20 @@ }, { "cell_type": "code", - "execution_count": 72, + "execution_count": null, "id": "e8581870-76c5-4f78-8d77-8de6a3526ea7", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T13:32:24.685530Z", - "iopub.status.busy": "2025-09-18T13:32:24.685242Z", - "iopub.status.idle": "2025-09-18T13:32:24.691015Z", - "shell.execute_reply": "2025-09-18T13:32:24.690421Z", - "shell.execute_reply.started": "2025-09-18T13:32:24.685510Z" - } - }, - "outputs": [ - { - "data": { - "text/plain": [ - "['band',\n", - " 'centroid_flag',\n", - " 'coord_dec',\n", - " 'coord_ra',\n", - " 'dec',\n", - " 'decErr',\n", - " 'diaSourceId',\n", - " 'forced_PsfFlux_flag',\n", - " 'forced_PsfFlux_flag_edge',\n", - " 'forced_PsfFlux_flag_noGoodPixels',\n", - " 'midpointMjdTai',\n", - " 'pixelFlags',\n", - " 'pixelFlags_bad',\n", - " 'pixelFlags_cr',\n", - " 'pixelFlags_crCenter',\n", - " 'pixelFlags_edge',\n", - " 'pixelFlags_interpolated',\n", - " 'pixelFlags_interpolatedCenter',\n", - " 'pixelFlags_nodata',\n", - " 'pixelFlags_nodataCenter',\n", - " 'pixelFlags_offimage',\n", - " 'pixelFlags_saturated',\n", - " 'pixelFlags_saturatedCenter',\n", - " 'pixelFlags_streak',\n", - " 'pixelFlags_streakCenter',\n", - " 'pixelFlags_suspect',\n", - " 'pixelFlags_suspectCenter',\n", - " 'psfFlux',\n", - " 'psfFlux_flag',\n", - " 'psfFlux_flag_edge',\n", - " 'psfFlux_flag_noGoodPixels',\n", - " 'psfFluxErr',\n", - " 'psfMag',\n", - " 'psfMagErr',\n", - " 'ra',\n", - " 'raErr',\n", - " 'reliability',\n", - " 'scienceFlux',\n", - " 'scienceFluxErr',\n", - " 'scienceMag',\n", - " 'scienceMagErr',\n", - " 'shape_flag',\n", - " 'shape_flag_no_pixels',\n", - " 'shape_flag_not_contained',\n", - " 'shape_flag_parent_source',\n", - " 'snr',\n", - " 'trail_flag_edge',\n", - " 'visit',\n", - " 'x',\n", - " 'xErr',\n", - " 'y',\n", - " 'yErr']" - ] - }, - "execution_count": 72, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "dia_object_cat[\"diaSource\"].nest.fields" ] }, { "cell_type": "code", - "execution_count": 52, + "execution_count": null, "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:48.172504Z", - "iopub.status.busy": "2025-09-18T12:54:48.172313Z", - "iopub.status.idle": "2025-09-18T12:54:48.184344Z", - "shell.execute_reply": "2025-09-18T12:54:48.183877Z", - "shell.execute_reply.started": "2025-09-18T12:54:48.172486Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog dia_object_lc:
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decdiaObjectIdnDiaSourcesraradecMjdTaitractdiaObjectForcedSourcediaSource
npartitions=208
Order: 6, Pixel: 130double[pyarrow]int64[pyarrow]int64[pyarrow]double[pyarrow]double[pyarrow]int64[pyarrow]nested<band: [string], coord_dec: [double], co...nested<band: [string], centroid_flag: [bool], ...
Order: 6, Pixel: 136........................
...........................
Order: 11, Pixel: 36833621........................
Order: 7, Pixel: 143884........................
\n", - "
8 out of 140 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
" - ], - "text/plain": [ - "Dask NestedFrame Structure:\n", - " dec diaObjectId nDiaSources ra radecMjdTai tract diaObjectForcedSource diaSource\n", - "npartitions=208 \n", - "9147936743096320 double[pyarrow] int64[pyarrow] int64[pyarrow] double[pyarrow] double[pyarrow] int64[pyarrow] nested nested\n", - "9570149208162304 ... ... ... ... ... ... ... ...\n", - "... ... ... ... ... ... ... ... ...\n", - "2531234096814751744 ... ... ... ... ... ... ... ...\n", - "2531251689000796160 ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 52, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "dia_object_cat" ] @@ -3490,17 +663,9 @@ }, { "cell_type": "code", - "execution_count": 53, + "execution_count": null, "id": "e8dd3508-9aff-4157-a911-d555128c9a37", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:48.184967Z", - "iopub.status.busy": "2025-09-18T12:54:48.184792Z", - "iopub.status.idle": "2025-09-18T12:54:48.290568Z", - "shell.execute_reply": "2025-09-18T12:54:48.290029Z", - "shell.execute_reply.started": "2025-09-18T12:54:48.184953Z" - } - }, + "metadata": {}, "outputs": [], "source": [ "pz_cat = lsdb.open_catalog(base_path / \"object_photoz\")" @@ -3516,859 +681,10 @@ }, { "cell_type": "code", - "execution_count": 54, + "execution_count": null, "id": "6cfe9c30-21dc-4b22-8ae0-d0552ecdcef3", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:48.291273Z", - "iopub.status.busy": "2025-09-18T12:54:48.291075Z", - "iopub.status.idle": "2025-09-18T12:54:48.349839Z", - "shell.execute_reply": "2025-09-18T12:54:48.349301Z", - "shell.execute_reply.started": "2025-09-18T12:54:48.291256Z" - } - }, - "outputs": [ - { - "data": { - "text/html": [ - "
lsdb Catalog object_photoz:
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npartitions=4
Order: 3, Pixel: 2double[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]int64[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]float[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]double[pyarrow]
Order: 5, Pixel: 4471......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 2, Pixel: 80......................................................................................................................................................................................................................................................................................................................................................................................................
Order: 0, Pixel: 8......................................................................................................................................................................................................................................................................................................................................................................................................
\n", - "
130 out of 130 available columns in the catalog have been loaded lazily, meaning no data has been read, only the catalog schema
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"npartitions=4 \n", - "9007199254740992 double[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] int64[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] float[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow] double[pyarrow]\n", - "1258474620873342976 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "1441151880758558720 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2305843009213693952 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "2594073385365405696 ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ... ...\n", - "Dask Name: nestedframe, 3 expressions\n", - "Expr=MapPartitions(NestedFrame)" - ] - }, - "execution_count": 54, - "metadata": {}, - "output_type": "execute_result" - } - ], + "metadata": {}, + "outputs": [], "source": [ "pz_cat" ] @@ -4399,37 +715,10 @@ }, { "cell_type": "code", - "execution_count": 55, + "execution_count": null, "id": "035604c1-816d-4e1e-ad95-061b04249e4f", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:48.350558Z", - "iopub.status.busy": "2025-09-18T12:54:48.350358Z", - "iopub.status.idle": "2025-09-18T12:54:48.661192Z", - "shell.execute_reply": "2025-09-18T12:54:48.660545Z", - "shell.execute_reply.started": "2025-09-18T12:54:48.350525Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/hats/inspection/visualize_catalog.py:303: UserWarning: This plot contains HEALPix pixels smaller than a pixel of the plot. Some values may be lost\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ "fig = object_cat.plot_pixels(plot_title=\"Object Sky Partition Map\")" ] @@ -4454,37 +743,10 @@ }, { "cell_type": "code", - "execution_count": 56, + "execution_count": null, "id": "e25035eb-b54d-4bf7-96ae-c974a1db28a5", - "metadata": { - "execution": { - "iopub.execute_input": "2025-09-18T12:54:48.661968Z", - "iopub.status.busy": "2025-09-18T12:54:48.661755Z", - "iopub.status.idle": "2025-09-18T12:54:48.988090Z", - "shell.execute_reply": "2025-09-18T12:54:48.987562Z", - "shell.execute_reply.started": "2025-09-18T12:54:48.661950Z" - } - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/opt/lsst/software/stack/conda/envs/lsst-scipipe-10.1.0/lib/python3.12/site-packages/hats/inspection/visualize_catalog.py:303: UserWarning: This plot contains HEALPix pixels smaller than a pixel of the plot. Some values may be lost\n", - " warnings.warn(\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "metadata": {}, + "outputs": [], "source": [ "fov = (100 * u.deg, 120 * u.deg)\n", "center = SkyCoord(70 * u.deg, -30 * u.deg)\n", From 5d9e76ec7724a825bdc9c0c05c9092ff89980c2d Mon Sep 17 00:00:00 2001 From: MelissaGraham Date: Fri, 19 Sep 2025 01:12:29 +0000 Subject: [PATCH 7/8] guidance for light curves --- .../102_5_LSDB_data_access.ipynb | 471 ++++++++++++++++-- 1 file changed, 419 insertions(+), 52 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 91b09dc3..2ebdcd20 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -72,7 +72,7 @@ "- [Working with Rubin Data using LSDB](https://docs.lsdb.io/en/latest/tutorial_toc/toc_rubin.html)\n", "- [LSDB hackathon at the Rubin Community Workshop 2025](https://github.com/lincc-frameworks/RCW_Hackathon_2025_LSDB/tree/main)\n", "\n", - "**Related tutorials:** The 200-level tutorials on the `Object` and `DiaObject` catalogs. The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. \n", + "**Related tutorials:** The 200-level tutorials on the `Object`, `DiaObject`, `DiaSource`, `ForcedSource`, and `ForcedSourceOnDiaObject` catalogs. The 300-level tutorial on how to access photometric redshifts in LSDB-formatted files. \n", "\n", "### 1.1. Import packages\n", "\n", @@ -91,7 +91,29 @@ "import astropy.units as u\n", "from astropy.coordinates import SkyCoord\n", "from upath import UPath\n", - "import matplotlib.pyplot as plt" + "import matplotlib.pyplot as plt\n", + "from lsst.utils.plotting import (get_multiband_plot_colors,\n", + " get_multiband_plot_symbols)" + ] + }, + { + "cell_type": "markdown", + "id": "7bd13ae9-8729-4047-839a-fe525fcbb3b4", + "metadata": {}, + "source": [ + "Define the filter names, colors, and symbols to use when plotting." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "403ff4d4-6bd7-4ef2-82e3-baba66cb272f", + "metadata": {}, + "outputs": [], + "source": [ + "filter_names = ['u', 'g', 'r', 'i', 'z', 'y']\n", + "filter_colors = get_multiband_plot_colors()\n", + "filter_symbols = get_multiband_plot_symbols()" ] }, { @@ -191,103 +213,85 @@ }, { "cell_type": "markdown", - "id": "acdce8d8-9727-4ea2-880b-afbfe0fa7d83", + "id": "5c7fe272-c73f-4ac0-86ab-c025cffbc96e", "metadata": {}, "source": [ - "#### 2.1.2. Show column names" - ] - }, - { - "cell_type": "markdown", - "id": "4d29b2c6-7576-4df7-a03d-b2c20e955679", - "metadata": {}, - "source": [ - "Display the subset of 42 columns that are lazily loaded by default." + "Optional: uncomment the following cell and press \"tab\" to browse the available methods on an LSDB catalog like `object_cat`." ] }, { "cell_type": "code", "execution_count": null, - "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", + "id": "38ac69e3-2bae-4da3-9581-f916660e87d8", "metadata": {}, "outputs": [], "source": [ - "object_cat.columns" + "# object_cat." ] }, { "cell_type": "markdown", - "id": "d251a7d0-620a-45d6-aa32-4cc3138f70e6", - "metadata": {}, - "source": [ - "Optional: uncomment the cell below to display the names of a larger subset of the 1304 columns from the `Object` catalog." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bcf956b0-8d59-445d-bd9b-ba0914d78c4b", + "id": "acdce8d8-9727-4ea2-880b-afbfe0fa7d83", "metadata": {}, - "outputs": [], "source": [ - "# object_cat.all_columns" + "#### 2.1.2. Show column names" ] }, { "cell_type": "markdown", - "id": "6199446b-7723-49cd-a6de-ab750165458c", + "id": "4d29b2c6-7576-4df7-a03d-b2c20e955679", "metadata": {}, "source": [ - "Show only the additional columns in the LSDB catalog that contains the PSF fluxes converted to magnitudes." + "Display the subset of 42 columns that are lazily loaded by default." ] }, { "cell_type": "code", "execution_count": null, - "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", + "id": "0565e62f-79a9-4122-a4a1-5371f62b9673", "metadata": {}, "outputs": [], "source": [ - "for col in object_cat.all_columns:\n", - " if col.find('psfMag') > 0:\n", - " print(col)" + "object_cat.columns" ] }, { "cell_type": "markdown", - "id": "7e026aec-03d7-496d-9fdb-3ac317558732", + "id": "d251a7d0-620a-45d6-aa32-4cc3138f70e6", "metadata": {}, "source": [ - "Check which columns are [nested](https://docs.lsdb.io/en/latest/tutorials/pre_executed/nestedframe.html)." + "Optional: uncomment the cell below to display the names of a larger subset of the 1304 columns from the `Object` catalog." ] }, { "cell_type": "code", "execution_count": null, - "id": "c27232da-4cfd-423d-a17e-cb4e69499b12", + "id": "bcf956b0-8d59-445d-bd9b-ba0914d78c4b", "metadata": {}, "outputs": [], "source": [ - "object_cat.nested_columns" + "# object_cat.all_columns" ] }, { "cell_type": "markdown", - "id": "63faee7e-3de1-4612-a94b-6248ec63f16d", + "id": "6199446b-7723-49cd-a6de-ab750165458c", "metadata": {}, "source": [ - "Display the fields in the nested column.\n", - "Note the additional columns `psfMag` and `psfMagErr`." + "Search for column names that contain a string, such as `psfMag` (i.e., the columns that contain the PSF fluxes converted to magnitudes)." ] }, { "cell_type": "code", "execution_count": null, - "id": "3678573c-8f9a-4076-8c3b-f5e2cbb7a2c7", + "id": "47f08ae7-2945-4db4-8094-cbecfd7ff4f1", "metadata": {}, "outputs": [], "source": [ - "object_cat[\"objectForcedSource\"].nest.fields" + "search_string = 'psfMag'\n", + "for col in object_cat.all_columns:\n", + " if col.find(search_string) > 0:\n", + " print(col)" ] }, { @@ -387,6 +391,16 @@ "object_cat_ecdfs" ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "4c0fd158-9adf-420d-bb18-c63116841187", + "metadata": {}, + "outputs": [], + "source": [ + "object_cat_ecdfs.head(3)" + ] + }, { "cell_type": "code", "execution_count": null, @@ -452,7 +466,7 @@ "id": "070f40be-94d7-4fe3-aa31-d6dd91c28362", "metadata": {}, "source": [ - "Select only objects with an **r-band PSF magnitude between 16 and 24**" + "Select only objects with an $r$-band PSF magnitude between 16 and 24 mag." ] }, { @@ -481,7 +495,7 @@ "metadata": {}, "outputs": [], "source": [ - "object_cat_mag_range.head(10)" + "object_cat_mag_range.head(3)" ] }, { @@ -489,7 +503,24 @@ "id": "5a9cce35-0fe0-46ee-846e-eaf7755e731d", "metadata": {}, "source": [ - "Optional: uncomment the following cell and press \"tab\" to browse more availabe methods." + "#### 2.1.5. Access nested light curves\n", + "\n", + "Some LSDB catalogs have \"nested\" columns.\n", + "These are columns which, instead of containing an array of data, contain a table.\n", + "\n", + "The LSDB documentation contains more information on working with \n", + "[nested columns](https://docs.lsdb.io/en/latest/tutorials/pre_executed/nestedframe.html)\n", + "and\n", + "[time series data](https://docs.lsdb.io/en/latest/tutorials/pre_executed/timeseries.html)\n", + "in LSDB format.\n", + "\n", + "In the `object_collection` catalog, forced photometry is available in a nested column named `objectForcedSource`.\n", + "\n", + "The fields in `objectForcedSource` are a subset of the DP1 `ForcedSource` table columns, plus two additional columns: `psfMag` and `psfMagErr`, the `psfFlux` and `psfFluxErr` columns converted to magnitudes.\n", + "\n", + "[Schema browser for the DP1 ForcedSource table](https://sdm-schemas.lsst.io/dp1.html#ForcedSource).\n", + "\n", + "Discover which columns are nested." ] }, { @@ -499,7 +530,157 @@ "metadata": {}, "outputs": [], "source": [ - "# object_cat." + "object_cat.nested_columns" + ] + }, + { + "cell_type": "markdown", + "id": "c86f70ad-95e4-4a7c-8683-b71bac9d43bb", + "metadata": {}, + "source": [ + "Option to display the fields in the nested column." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "37015469-d91a-4e80-83f4-8156db51a708", + "metadata": {}, + "outputs": [], + "source": [ + "# object_cat[\"objectForcedSource\"].nest.fields" + ] + }, + { + "cell_type": "markdown", + "id": "70894fbe-fc8a-4d35-9e27-8c47a0d7e68a", + "metadata": {}, + "source": [ + "##### Extract and plot a light curve for a random object\n", + "\n", + "Select a random object from the ECDFS field by its `objectId`.\n", + "The ECDFS field had many visits over multiple weeks, so the forced photometry light curve for any random object in ECDFS will have many light curve points." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "58d5f215-9316-491d-b581-ba21882e21ae", + "metadata": {}, + "outputs": [], + "source": [ + "random_object = object_cat.query(\"objectId == 611253698252788430\")" + ] + }, + { + "cell_type": "markdown", + "id": "ddbdfd91-d173-48f9-b74c-fe4752efe7c6", + "metadata": {}, + "source": [ + "Option to show the row of the `object_cat` for this random object." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5267b6cb-5a55-4940-8b16-391a1afd7012", + "metadata": {}, + "outputs": [], + "source": [ + "# random_object.head(1)" + ] + }, + { + "cell_type": "markdown", + "id": "b9f5cf20-3452-4d16-8bce-960709b02774", + "metadata": {}, + "source": [ + "Extract just the `objectForcedSource` for this random object, use the `compute` method to convert it to a Pandas DataFrame (`df`), and extract the light curve (`lc`)." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "4a1d72e6-4d9d-407d-862d-066d1f04d531", + "metadata": {}, + "outputs": [], + "source": [ + "random_object_fs = random_object['objectForcedSource']\n", + "random_object_df = random_object_fs.compute()\n", + "random_object_lc = random_object_df.iloc[0]" + ] + }, + { + "cell_type": "markdown", + "id": "1981c517-1b63-4f11-b132-8563e0496f3c", + "metadata": {}, + "source": [ + "Option to display the light curve as a table." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "b1b7717f-6b91-4715-b142-fa2b58b7e6d6", + "metadata": {}, + "outputs": [], + "source": [ + "# random_object_lc" + ] + }, + { + "cell_type": "markdown", + "id": "37e33694-bec0-4956-b333-7f247dad3bd8", + "metadata": {}, + "source": [ + "Plot the forced photometry light curve for this random object." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "284977a6-d7b6-42e8-85bd-ca5d49458d67", + "metadata": {}, + "outputs": [], + "source": [ + "fig = plt.figure(figsize=(6, 4))\n", + "for f, filt in enumerate(filter_names):\n", + " tx = (random_object_lc['band'] == filt)\n", + " plt.plot(random_object_lc['midpointMjdTai'][tx], random_object_lc['psfMag'][tx],\n", + " filter_symbols[filt], ms=5, mew=0, alpha=0.5, color=filter_colors[filt], label=filt)\n", + "plt.ylim([20, 14])\n", + "plt.legend(loc='lower left', ncol=3)\n", + "plt.xlabel('MJD')\n", + "plt.ylabel('PSF Magnitude')\n", + "plt.title('Nested Forced Photometry Light Curve')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "1e175297-3fa8-4097-a506-ba858a5fcf9c", + "metadata": {}, + "source": [ + "> **Figure 2:** The forced photometry light curve of a random object in the ECDFS field, extracted from a nested column" + ] + }, + { + "cell_type": "markdown", + "id": "cd3cc621-499f-47c4-964c-abf28c28c18d", + "metadata": {}, + "source": [ + "Clean up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "df96e347-836c-47f5-9fb3-226123db5f94", + "metadata": {}, + "outputs": [], + "source": [ + "del object_cat_selected_columns, object_cat_ecdfs, object_cat_mag_range\n", + "del random_object, random_object_fs, random_object_df, random_object_lc" ] }, { @@ -572,6 +753,24 @@ "# object_cat_lite.all_columns" ] }, + { + "cell_type": "markdown", + "id": "3e0a2e7d-7220-43e1-93ca-6da23dd50aac", + "metadata": {}, + "source": [ + "Clean up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "fcfd6a52-d696-4f3f-9fcb-60932d2514a0", + "metadata": {}, + "outputs": [], + "source": [ + "del object_cat_lite" + ] + }, { "cell_type": "markdown", "id": "73764ef6-ebb6-4b7f-bfd5-d7c5e1a51302", @@ -599,6 +798,8 @@ "id": "41897f53-eb64-44a3-af2c-9953fbb2beef", "metadata": {}, "source": [ + "#### 2.3.1. Access nested light curves\n", + "\n", "Check which columns are nested." ] }, @@ -617,8 +818,19 @@ "id": "093979e4-4bb1-49cd-900c-0a25fa349a9e", "metadata": {}, "source": [ - "Display the fields in the `diaSource` nested column.\n", - "Note the additional columns such as `psfMag`, `psfMagErr`, `scienceMag` and `scienceMagErr`." + "The fields in these nested columns are the mostly same as the DP1 `DiaSource` and `ForcedSourceOnDiaObject` tables.\n", + "\n", + "[Schema browser for the DP1 DiaSource table](https://sdm-schemas.lsst.io/dp1.html#DiaSource).\n", + "\n", + "[Schema browser for the DP1 ForcedSourceOnDiaObject table](https://sdm-schemas.lsst.io/dp1.html#ForcedSourceOnDiaObject).\n", + "\n", + "There are four additional fields:\n", + "* `psfMag` and `psfMagErr` (in both nested columns)\n", + "* `scienceMag` and `scienceMagErr` (in the `diaSource` nested column only)\n", + "\n", + "> **Warning:** For both nested columns, the `psfMag` column has been calculated from the `psfFlux` column, but they are not the same: in the `DiaSource` table `psfFlux` is the PSF fit flux in the difference image, but in the `ForcedSourceOnDiaObject` table `psfFlux` is the PSF forced photometry flux in the direct (or science) image. Fluxes measured on a difference image will be negative when the object is brighter in the template image than in the direct (science) image, and so typically, difference-image fluxes are not converted to magnitudes.\n", + "\n", + "Option to display the fields in the nested columns." ] }, { @@ -628,17 +840,136 @@ "metadata": {}, "outputs": [], "source": [ - "dia_object_cat[\"diaSource\"].nest.fields" + "# dia_object_cat[\"diaSource\"].nest.fields" ] }, { "cell_type": "code", "execution_count": null, - "id": "34af0c99-36d7-43f1-82e7-942c2adb6f8a", + "id": "46ffc205-7409-4793-b77f-d26a7d81eaa0", "metadata": {}, "outputs": [], "source": [ - "dia_object_cat" + "# dia_object_cat[\"diaObjectForcedSource\"].nest.fields" + ] + }, + { + "cell_type": "markdown", + "id": "c0ee650b-35e8-4611-8af2-b881d64fb8a8", + "metadata": {}, + "source": [ + "##### Extract and plot a light curve for a random object\n", + "\n", + "A known supernova (SN) occurred in the ECDFS field.\n", + "\n", + "Select this known SN by its `diaObjectId`." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8aebcb94-9d2c-4aa4-95a9-e968041db6e7", + "metadata": {}, + "outputs": [], + "source": [ + "known_sn = dia_object_cat.query(\"diaObjectId == 611255759837069401\")" + ] + }, + { + "cell_type": "markdown", + "id": "aa2ce552-fafa-4654-a066-0669b705a339", + "metadata": {}, + "source": [ + "Extract the light curve from the `diaSource` and `diaObjectForcedSource` columns." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3950b89d-6481-41d4-9f6d-ac3979cb8821", + "metadata": {}, + "outputs": [], + "source": [ + "known_sn_ds = known_sn['diaSource']\n", + "known_sn_ds_df = known_sn_ds.compute()\n", + "known_sn_ds_lc = known_sn_ds_df.iloc[0]\n", + "\n", + "known_sn_fs = known_sn['diaObjectForcedSource']\n", + "known_sn_fs_df = known_sn_fs.compute()\n", + "known_sn_fs_lc = known_sn_fs_df.iloc[0]" + ] + }, + { + "cell_type": "markdown", + "id": "4b8532bd-88bf-4b15-929d-94686ce43a21", + "metadata": {}, + "source": [ + "Compare light curves that use the forced difference-image flux, the detected difference-image flux, and the detected difference-image flux converted to a magnitude.\n", + "\n", + "This will illustrate why **it is recommended to use forced photometry fluxes for difference-image light curves**." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "407157eb-e93e-444f-a24d-31583e971e41", + "metadata": {}, + "outputs": [], + "source": [ + "fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(6, 8))\n", + "for f, filt in enumerate(filter_names):\n", + " tx1 = (known_sn_fs_lc['band'] == filt)\n", + " tx2 = (known_sn_ds_lc['band'] == filt)\n", + " ax1.plot(known_sn_fs_lc['midpointMjdTai'][tx1]-60000, known_sn_fs_lc['psfDiffFlux'][tx1],\n", + " filter_symbols[filt], ms=5, mew=0, alpha=0.5, color=filter_colors[filt], label=filt)\n", + " ax2.plot(known_sn_ds_lc['midpointMjdTai'][tx2]-60000, known_sn_ds_lc['psfFlux'][tx2],\n", + " filter_symbols[filt], ms=5, mew=0, alpha=0.5, color=filter_colors[filt], label=filt)\n", + " ax3.plot(known_sn_ds_lc['midpointMjdTai'][tx2]-60000, known_sn_ds_lc['psfMag'][tx2],\n", + " filter_symbols[filt], ms=5, mew=0, alpha=0.5, color=filter_colors[filt], label=filt)\n", + " del tx1, tx2\n", + "ax1.set_xlim([620, 660])\n", + "ax2.set_xlim([620, 660])\n", + "ax3.set_xlim([620, 660])\n", + "ax1.set_ylim([-10000, 10000])\n", + "ax2.set_ylim([-10000, 10000])\n", + "ax3.set_ylim([23.7, 21.3])\n", + "ax1.set_xlabel('MJD-60000')\n", + "ax2.set_xlabel('MJD-60000')\n", + "ax3.set_xlabel('MJD-60000')\n", + "ax1.set_ylabel('forced PSF Diff Flux')\n", + "ax2.set_ylabel('diaSource PSF Flux')\n", + "ax3.set_ylabel('diaSource PSF Mag')\n", + "ax2.legend(loc='upper right', ncol=2)\n", + "plt.tight_layout()\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3810c49f-1a03-4da5-b92f-710507599711", + "metadata": {}, + "source": [ + "> **Figure 3:** Top: the forced PSF photometry on the difference image has light curve points from every observation. Middle: the `diaSource` PSF-fit photometry only has light curve points when the SN was detected with a signal-to-noise ratio $>$ 5, positive or negative, in the difference image. Some epochs are missing, when the difference flux was near 0. Bottom: converting difference-image fluxes to magnitudes means the observations where the difference-image flux is negative are lost." + ] + }, + { + "cell_type": "markdown", + "id": "571e5f98-7b13-4d32-a921-c0a4650404dc", + "metadata": {}, + "source": [ + "Clean up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "84e71038-1ad7-4a6e-9654-2449aacfeaa8", + "metadata": {}, + "outputs": [], + "source": [ + "del dia_object_cat, known_sn\n", + "del known_sn_ds, known_sn_ds_df, known_sn_ds_lc\n", + "del known_sn_fs, known_sn_fs_df, known_sn_fs_lc" ] }, { @@ -689,6 +1020,24 @@ "pz_cat" ] }, + { + "cell_type": "markdown", + "id": "1566cb0e-b3bc-44c6-a740-f729dadea778", + "metadata": {}, + "source": [ + "Clean up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "5060f005-d8ef-4b16-ab8d-b6740b5f7d31", + "metadata": {}, + "outputs": [], + "source": [ + "del pz_cat" + ] + }, { "cell_type": "markdown", "id": "97342caa-6d08-4e1f-bafe-80056c928632", @@ -728,7 +1077,7 @@ "id": "575511ae-fb65-4f6f-9c02-01f40790ef0c", "metadata": {}, "source": [ - "> **Figure 2:** An all-sky map showing the HEALPix partitions for the LSDB-formatted `object_collection` catalog." + "> **Figure 4:** An all-sky map showing the HEALPix partitions for the LSDB-formatted `object_collection` catalog." ] }, { @@ -759,7 +1108,25 @@ "id": "f7809a09-56b9-46a5-8701-194877f095ef", "metadata": {}, "source": [ - "> **Figure 3:** A zoomed-in version of Figure 2." + "> **Figure 5:** A zoomed-in version of Figure 2." + ] + }, + { + "cell_type": "markdown", + "id": "09cf4e7e-bf8b-48c9-a21e-10c93b5e98c5", + "metadata": {}, + "source": [ + "Clean up." + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "877639bd-e316-4808-ad96-f3279705b5bf", + "metadata": {}, + "outputs": [], + "source": [ + "del object_cat" ] }, { From 93c82ba8f6e2598e345baa5dd20417e7e16ea747 Mon Sep 17 00:00:00 2001 From: plazas Date: Fri, 19 Sep 2025 14:28:49 +0000 Subject: [PATCH 8/8] Update notebook --- .../102_Catalog_access/102_5_LSDB_data_access.ipynb | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb index 2ebdcd20..8757c29c 100644 --- a/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb +++ b/DP1/100_How_to_Use_RSP_Tools/102_Catalog_access/102_5_LSDB_data_access.ipynb @@ -22,7 +22,7 @@ "Data Release: Data Preview 1
\n", "Container Size: Large
\n", "LSST Science Pipelines version: Release r29.2.0
\n", - "Last verified to run: 2025-09-18
\n", + "Last verified to run: 2025-09-19
\n", "Repository: github.com/lsst/tutorial-notebooks
" ] }, @@ -33,7 +33,7 @@ "source": [ "**Learning objective:** How to access Rubin data in LSDB format.\n", "\n", - "**LSST data products:** `Object`, `DiaObject`\n", + "**LSST data products:** `Object`, `DiaObject`, `DiaSource`, `ForcedSource`, and `ForcedSourceOnDiaObject`\n", "\n", "**Packages:** `lsdb`\n", "\n", @@ -59,7 +59,7 @@ "It operates on data stored in the [HATS](https://hats.readthedocs.io/) data format that provides an efficient, spatially-indexed format for storing catalog data.\n", "Built on top of [Dask](https://docs.dask.org/), LSDB uses the [HATS](https://hats.readthedocs.io/) (Hierarchical Adaptive Tiling Scheme) data format ([HEALPix](https://healpix.sourceforge.io/documentation.php)-sharded [Parquet](https://parquet.apache.org/docs/)) to efficiently perform spatial operations.\n", "\n", - "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial, but **only the DP1 dataset is available in the RSP**.\n", + "LSDB also hosts many other datasets stored in the HATS format, beyond the DP1 catalogs shown in this tutorial, but **only the DP1 dataset is available in the Rubin Science Platform (RSP)**.\n", "Find the full list of LSDB-hosted datasets at [data.lsdb.io](https://data.lsdb.io/).\n", "\n", "**Note:** This notebook is intended only as a simple tutorial on LSDB DP1 catalogs.\n",