diff --git a/.github/workflows/linter.yml b/.github/workflows/linter.yml index 07f79e3b..466ef272 100644 --- a/.github/workflows/linter.yml +++ b/.github/workflows/linter.yml @@ -28,9 +28,7 @@ jobs: run: | ruff check --statistics *.py ruff check --statistics apps/ - ruff check --ignore D205 tests/ - name: Format run: | ruff format --check *.py ruff format --check apps/ - ruff format --check tests/ diff --git a/.github/workflows/run_test.yml b/.github/workflows/run_test.yml deleted file mode 100644 index e2e723f8..00000000 --- a/.github/workflows/run_test.yml +++ /dev/null @@ -1,29 +0,0 @@ -name: Sentinel - -on: - push: - branches: - - master - pull_request: - -jobs: - test-suite: - runs-on: ubuntu-latest - strategy: - matrix: - python-version: [3.11] - steps: - - uses: actions/checkout@v2 - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v2 - with: - python-version: ${{ matrix.python-version }} - - name: Install Python dependencies - run: | - cd tests/ - pip install --upgrade pip setuptools wheel - pip install -r requirements.txt - cd .. - - name: Run test suites - run: | - ./run_tests.sh --url ${{ secrets.APIURLDEV }} diff --git a/app.py b/app.py index 0e7c4e58..d73d768c 100644 --- a/app.py +++ b/app.py @@ -20,20 +20,15 @@ # import jpype import os -import yaml import diskcache + dash._dash_renderer._set_react_version("18.2.0") cache = diskcache.Cache("./cache") long_callback_manager = DiskcacheLongCallbackManager(cache) background_callback_manager = DiskcacheManager(cache) -args = yaml.load(open("config.yml"), yaml.Loader) - -APIURL = args["APIURL"] -LOCALAPI = args.get("LOCALAPI", False) - # bootstrap theme external_stylesheets = [ dbc.themes.SPACELAB, diff --git a/apps/api/__init__.py b/apps/api/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/apps/api/api.py b/apps/api/api.py deleted file mode 100644 index b987b5da..00000000 --- a/apps/api/api.py +++ /dev/null @@ -1,1719 +0,0 @@ -# Copyright 2020-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import dash_mantine_components as dmc -import numpy as np -import pandas as pd -import requests -from fink_science.ssoft.processor import ( - COLUMNS, - COLUMNS_HG, - COLUMNS_HG1G2, - COLUMNS_SHG1G2, - COLUMNS_SSHG1G2, -) -from fink_utils.xmatch.simbad import get_simbad_labels -from flask import Blueprint, Response, jsonify, request - -from app import APIURL - -from apps.api.utils import ( - download_euclid_data, - format_and_send_cutout, - perform_xmatch, - post_metadata, - retrieve_metadata, - retrieve_oid, - return_anomalous_objects_pdf, - return_bayestar_pdf, - return_explorer_pdf, - return_conesearch_pdf, - return_latests_pdf, - return_object_pdf, - return_random_pdf, - return_resolver_pdf, - return_sso_pdf, - return_ssocand_pdf, - return_ssoft_pdf, - return_statistics_pdf, - return_tracklet_pdf, - send_data, - upload_euclid_data, -) - -api_bp = Blueprint("api", __name__) - - -# Enable CORS for this blueprint only -@api_bp.after_request -def after_request(response): - response.headers.add("Access-Control-Allow-Origin", "*") - response.headers.add("Access-Control-Allow-Headers", "Content-Type,Authorization") - response.headers.add("Access-Control-Allow-Methods", "GET,PUT,POST,DELETE,OPTIONS") - return response - - -def layout(): - layout_ = dmc.MantineProvider( - dmc.Container( - dmc.Center( - style={"height": "100%", "width": "100%"}, - children=[ - dmc.Alert( - "The API documentation moved to https://fink-broker.readthedocs.io. This link will be soon removed.", - title="URL change", - radius="md", - ) - ], - ), - fluid=True, - className="home", - ) - ) - - layout_ = dmc.MantineProvider( - dmc.Container( - dmc.Center( - style={"height": "100%", "width": "100%"}, - children=[ - dmc.Card( - children=[ - dmc.Group( - [ - dmc.Text("The resource has moved", fw=500), - # dmc.Badge("On Sale", color="pink"), - ], - justify="space-between", - mt="md", - mb="xs", - ), - dmc.Text( - "The API documentation has moved and it is now integrated with all the Fink documentation to offer " - "a better experience.", - size="sm", - c="dimmed", - ), - dmc.Button( - dmc.Anchor( - "Go to API doc", - href="https://fink-broker.readthedocs.io/en/latest/services/search/getting_started/#quick-start-api", - target="_blank", - c="white", - ), - color="#15284F", - fullWidth=True, - mt="md", - radius="md", - ), - ], - withBorder=True, - shadow="sm", - radius="md", - w=350, - ) - ], - ), - fluid=True, - className="home", - ) - ) - - return layout_ - - -args_objects = [ - { - "name": "objectId", - "required": True, - "description": 'single ZTF Object ID, or a comma-separated list of object names, e.g. "ZTF19acmdpyr,ZTF21aaxtctv"', - }, - { - "name": "withupperlim", - "required": False, - "description": "If True, retrieve also upper limit measurements, and bad quality measurements. Use the column `d:tag` in your results: valid, upperlim, badquality.", - }, - { - "name": "withcutouts", - "required": False, - "description": "If True, retrieve also cutout data as 2D array. See also `cutout-kind`. More information on the original cutouts at https://irsa.ipac.caltech.edu/data/ZTF/docs/ztf_explanatory_supplement.pdf", - }, - { - "name": "cutout-kind", - "required": False, - "description": "`Science`, `Template`, or `Difference`. If not specified, returned all three.", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_explorer = [ - { - "name": "objectId", - "required": True, - "group": 0, - "description": "ZTF Object ID, or comma-separated list of Object IDs", - }, - { - "name": "ra", - "required": True, - "group": 1, - "description": "Right Ascension", - }, - { - "name": "dec", - "required": True, - "group": 1, - "description": "Declination", - }, - { - "name": "radius", - "required": True, - "group": 1, - "description": "Conesearch radius in arcsec. Maximum is 36,000 arcseconds (10 degrees).", - }, - { - "name": "startdate", - "required": False, - "group": None, - "description": "[Optional] Starting date in UTC, as either ISO string, JD or MJD.", - }, - { - "name": "stopdate", - "required": False, - "group": None, - "description": "[Optional] Stopping date in UTC, as either ISO string, JD or MJD.", - }, - { - "name": "window", - "required": False, - "group": None, - "description": "[Optional] Time window in days, may be used instead of stopdate", - }, - { - "name": "n", - "required": False, - "group": None, - "description": "Maximal number of alerts to return. Default is 1000.", - }, - { - "name": "output-format", - "required": False, - "group": None, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_conesearch = [ - { - "name": "ra", - "required": True, - "description": "Right Ascension", - }, - { - "name": "dec", - "required": True, - "description": "Declination", - }, - { - "name": "radius", - "required": True, - "description": "Conesearch radius in arcsec. Maximum is 36,000 arcseconds (10 degrees).", - }, - { - "name": "startdate", - "required": False, - "description": "[Optional] Starting date in UTC, as either ISO string, JD or MJD.", - }, - { - "name": "stopdate", - "required": False, - "description": "[Optional] Stopping date in UTC, as either ISO string, JD or MJD.", - }, - { - "name": "window", - "required": False, - "description": "[Optional] Time window in days, may be used instead of stopdate", - }, - { - "name": "n", - "required": False, - "description": "Maximal number of alerts to return. Default is 1000.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_latest = [ - { - "name": "class", - "required": True, - "description": "Fink derived class", - }, - { - "name": "n", - "required": False, - "description": "Last N alerts to transfer between stopping date and starting date. Default is 10, max is 1000.", - }, - { - "name": "startdate", - "required": False, - "description": "Starting date in UTC (iso, jd, or MJD). Default is 2019-11-01 00:00:00", - }, - { - "name": "stopdate", - "required": False, - "description": "Stopping date in UTC (iso, jd, or MJD). Default is now.", - }, - { - "name": "color", - "required": False, - "description": "If True, extract color information for the transient (default is False).", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_sso = [ - { - "name": "n_or_d", - "required": False, - "description": "IAU number of the object, or designation of the object IF the number does not exist yet. Example for numbers: 8467 (asteroid) or 10P (comet). Example for designations: 2010JO69 (asteroid) or C/2020V2 (comet). You can also give a list of object names (comma-separated).", - }, - { - "name": "withEphem", - "required": False, - "description": "Attach ephemerides provided by the Miriade service (https://ssp.imcce.fr/webservices/miriade/api/ephemcc/), as extra columns in the results.", - }, - { - "name": "withResiduals", - "required": False, - "description": "Return the residuals `obs - model` using the sHG1G2 phase curve model. Work only for a single object query (`n_or_d` cannot be a list).", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "withcutouts", - "required": False, - "description": "If True, retrieve also cutout data as 2D array. See also `cutout-kind`. More information on the original cutouts at https://irsa.ipac.caltech.edu/data/ZTF/docs/ztf_explanatory_supplement.pdf", - }, - { - "name": "cutout-kind", - "required": False, - "description": "`Science`[default], `Template`, or `Difference`", - }, - { - "name": "output-format", - "required": False, - "description": "Query output format among `json`[default], `csv`, `parquet`, `votable`", - }, -] - -args_tracklet = [ - { - "name": "date", - "required": False, - "description": "A date. Format: YYYY-MM-DD hh:mm:dd. You can use short versions like YYYY-MM-DD only, or YYYY-MM-DD hh.", - }, - { - "name": "id", - "required": False, - "description": "Tracklet ID, in the format TRCK_YYYYMMDD_HHMMSS_NN", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_cutouts = [ - { - "name": "objectId", - "required": True, - "description": "ZTF Object ID", - }, - { - "name": "kind", - "required": True, - "description": "Science, Template, or Difference. For output-format=array, you can also specify kind=All to get the 3 cutouts.", - }, - { - "name": "output-format", - "required": False, - "description": "PNG[default], FITS, array", - }, - { - "name": "candid", - "required": False, - "description": "Candidate ID of the alert belonging to the object with `objectId`. If not filled, the cutouts of the latest alert is returned", - }, - { - "name": "stretch", - "required": False, - "description": "Stretch function to be applied. Available: sigmoid[default], linear, sqrt, power, log.", - }, - { - "name": "colormap", - "required": False, - "description": "Valid matplotlib colormap name (see matplotlib.cm). Default is grayscale.", - }, - { - "name": "pmin", - "required": False, - "description": "The percentile value used to determine the pixel value of minimum cut level. Default is 0.5. No effect for sigmoid.", - }, - { - "name": "pmax", - "required": False, - "description": "The percentile value used to determine the pixel value of maximum cut level. Default is 99.5. No effect for sigmoid.", - }, - { - "name": "convolution_kernel", - "required": False, - "description": "Convolve the image with a kernel (gauss or box). Default is None (not specified).", - }, -] - -args_xmatch = [ - { - "name": "catalog", - "required": True, - "description": "External catalog as CSV", - }, - { - "name": "header", - "required": True, - "description": "Comma separated names of columns corresponding to RA, Dec, ID, Time[optional] in the input catalog.", - }, - { - "name": "radius", - "required": True, - "description": "Conesearch radius in arcsec. Maximum is 18,000 arcseconds (5 degrees).", - }, - { - "name": "window", - "required": False, - "description": "[Optional] Time window in days.", - }, -] - -args_bayestar = [ - { - "name": "bayestar", - "required": False, - "description": "LIGO/Virgo probability sky maps, as gzipped FITS (bayestar.fits.gz). Not compatible with `event_name`.", - }, - { - "name": "event_name", - "required": False, - "description": "If provided, directly query GraceDB with the `event_name`. Not compatible with the argument `bayestar`.", - }, - { - "name": "credible_level", - "required": True, - "description": "GW credible region threshold to look for. Note that the values in the resulting credible level map vary inversely with probability density: the most probable pixel is assigned to the credible level 0.0, and the least likely pixel is assigned the credible level 1.0.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet", - }, -] - -args_stats = [ - { - "name": "date", - "required": True, - "description": "Observing date. This can be either a given night (YYYYMMDD), month (YYYYMM), year (YYYY), or eveything (empty string)", - }, - { - "name": "columns", - "required": False, - "description": "Comma-separated data columns to transfer. Default is all columns.", - }, - { - "name": "schema", - "required": False, - "description": "If True, return just the schema of statistics table instead of actual data", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_random = [ - { - "name": "n", - "required": True, - "description": "Number of objects to return. Maximum is 16 for performance.", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "class", - "required": False, - "description": f"Fink derived class. Default is empty string, namely all classes are considered. See {APIURL}/api/v1/classes for more information", - }, - { - "name": "seed", - "required": False, - "description": "Seed number for random number generator. By default, the seed is not fixed.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_ssocand = [ - { - "name": "kind", - "required": True, - "description": "Choose to return orbital parameters (orbParams), or lightcurves (lightcurves)", - }, - { - "name": "ssoCandId", - "required": False, - "description": "[Optional] Trajectory ID if you know it. Otherwise do not specify to return all.", - }, - { - "name": "start_date", - "required": False, - "description": "[Optional] Start date in UTC YYYY-MM-DD. Only used for `kind=lightcurves`. Default is 2019-11-01.", - }, - { - "name": "stop_date", - "required": False, - "description": "[Optional] Stop date in UTC YYYY-MM-DD. Only used for `kind=lightcurves`. Default is today.", - }, - { - "name": "maxnumber", - "required": False, - "description": "Maximum number of entries (observations or orbital parameters) to retrieve. Default is 10,000.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_anomaly = [ - { - "name": "n", - "required": False, - "description": "Last N alerts to transfer between stop and start date (going from most recent to older alerts). Default is 10", - }, - { - "name": "start_date", - "required": False, - "description": "[Optional] Start date in UTC YYYY-MM-DD. Default is 2019-11-01.", - }, - { - "name": "stop_date", - "required": False, - "description": "[Optional] Stop date in UTC YYYY-MM-DD. Default is today.", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_ssoft = [ - { - "name": "sso_name", - "required": False, - "description": "Official name or provisional designation of the SSO.", - }, - { - "name": "sso_number", - "required": False, - "description": "IAU number of the SSO", - }, - { - "name": "schema", - "required": False, - "description": "If specified, return the schema of the table in json format.", - }, - { - "name": "flavor", - "required": False, - "description": "Data model among SSHG1G2, SHG1G2 (default), HG1G2, HG.", - }, - { - "name": "version", - "required": False, - "description": "Version of the SSOFT YYYY.MM. By default it uses the latest one. Starts at 2023.07", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_resolver = [ - { - "name": "resolver", - "required": True, - "description": "Resolver among: `simbad`, `ssodnet`, `tns`", - }, - { - "name": "name", - "required": True, - "description": "Object name to resolve", - }, - { - "name": "reverse", - "required": False, - "description": "If True, resolve ZTF* name. Default is False.", - }, - { - "name": "nmax", - "required": False, - "description": "Maximum number of match to return. Default is 10.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_euclidin = [ - { - "name": "EID", - "required": True, - "description": "ID from Euclid", - }, - { - "name": "pipeline", - "required": True, - "description": "`SSOPipe`, `streakdet`, `DL`", - }, - { - "name": "version", - "required": True, - "description": "Version of the processing", - }, - { - "name": "date", - "required": True, - "description": "Date of the processing", - }, - { - "name": "payload", - "required": True, - "description": "Data file", - }, - { - "name": "mode", - "required": False, - "description": "Execution mode among production[default], or sandbox. Choose sandbox if you just want to test the upload without touching the tables.", - }, -] - -args_eucliddata = [ - { - "name": "pipeline", - "required": True, - "description": "`SSOPipe`, `streakdet`, `DL`", - }, - { - "name": "dates", - "required": True, - "description": "Observation dates. It can be a single date (YYYYMMDD), and range (YYYYMMDD:YYYYMMDD), or any superset (e.g. YYYY)", - }, - { - "name": "columns", - "required": False, - "description": f"Comma-separated data columns to transfer. Default is all columns. See {APIURL}/api/v1/columns for more information.", - }, - { - "name": "mode", - "required": False, - "description": "Execution mode among production[default], or sandbox. Choose sandbox if you just want to connect to the test table.", - }, - { - "name": "output-format", - "required": False, - "description": "Output format among json[default], csv, parquet, votable", - }, -] - -args_metadata = [ - { - "name": "objectId", - "required": True, - "description": "ZTF object ID", - }, - { - "name": "internal_name", - "required": True, - "description": "Internal name to be given", - }, - { - "name": "username", - "required": True, - "description": "The username of the submitter", - }, - { - "name": "comments", - "required": False, - "description": "Any relevant comments for the object", - }, -] - - -@api_bp.route("/api/v1/objects", methods=["GET"]) -def return_object_arguments(): - """Obtain information about retrieving object data""" - if len(request.args) > 0: - # POST from query URL - return return_object(payload=request.args) - else: - return jsonify({"args": args_objects}) - - -@api_bp.route("/api/v1/objects", methods=["POST"]) -def return_object(payload=None): - """Retrieve object data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_objects if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdf = return_object_pdf(payload) - - # Error propagation - if isinstance(pdf, Response): - return pdf - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/explorer", methods=["GET"]) -def query_db_arguments(): - """Obtain information about querying the Fink database""" - if len(request.args) > 0: - # POST from query URL - return query_db(payload=request.args) - else: - return jsonify({"args": args_explorer}) - - -@api_bp.route("/api/v1/explorer", methods=["POST"]) -def query_db(payload=None): - """Query the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check the user specifies only one group - all_groups = [ - i["group"] - for i in args_explorer - if i["group"] is not None and i["name"] in payload - ] - if len(np.unique(all_groups)) > 1: - rep = { - "status": "error", - "text": "You need to set parameters from the same group\n", - } - return Response(str(rep), 400) - - # Check the user specifies all parameters within a group - if len(np.unique(all_groups)) == 1: - user_group = np.unique(all_groups)[0] - required_args = [i["name"] for i in args_explorer if i["group"] == user_group] - required = [i["required"] for i in args_explorer if i["group"] == user_group] - for required_arg, required_ in zip(required_args, required): - if (required_arg not in payload) and required_: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required for group {user_group}. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - else: - user_group = None - - pdfs = return_explorer_pdf(payload, user_group) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/conesearch", methods=["GET"]) -def conesearch_arguments(): - """Obtain information about performing a conesearch in the Fink database""" - if len(request.args) > 0: - # POST from query URL - return conesearch(payload=request.args) - else: - return jsonify({"args": args_conesearch}) - - -@api_bp.route("/api/v1/conesearch", methods=["POST"]) -def conesearch(payload=None): - """Perform a conesearch in the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_conesearch if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdfs = return_conesearch_pdf(payload) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/latests", methods=["GET"]) -def latest_objects_arguments(): - """Obtain information about latest objects""" - if len(request.args) > 0: - # POST from query URL - return latest_objects(payload=request.args) - else: - return jsonify({"args": args_latest}) - - -@api_bp.route("/api/v1/latests", methods=["POST"]) -def latest_objects(payload=None): - """Get latest objects by class""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_latest if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdfs = return_latests_pdf(payload) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/classes", methods=["GET"]) -def class_arguments(): - """Obtain all Fink derived class""" - # TNS - tns_types = pd.read_csv("assets/tns_types.csv", header=None)[0].to_numpy() - tns_types = sorted(tns_types, key=lambda s: s.lower()) - tns_types = ["(TNS) " + x for x in tns_types] - - # SIMBAD - simbad_types = get_simbad_labels("old_and_new") - simbad_types = sorted(simbad_types, key=lambda s: s.lower()) - simbad_types = ["(SIMBAD) " + x for x in simbad_types] - - # Fink science modules - fink_types = pd.read_csv("assets/fink_types.csv", header=None)[0].to_numpy() - fink_types = sorted(fink_types, key=lambda s: s.lower()) - - types = { - "Fink classifiers": fink_types, - "TNS classified data": tns_types, - "Cross-match with SIMBAD (see http://simbad.u-strasbg.fr/simbad/sim-display?data=otypes)": simbad_types, - } - - return jsonify({"classnames": types}) - - -@api_bp.route("/api/v1/columns", methods=["GET"]) -def columns_arguments(): - """Obtain all alert fields available and their type""" - # ZTF candidate fields - r = requests.get( - "https://raw.githubusercontent.com/ZwickyTransientFacility/ztf-avro-alert/master/schema/candidate.avsc" - ) - tmp = pd.DataFrame.from_dict(r.json()) - ztf_candidate = tmp["fields"].apply(pd.Series) - ztf_candidate = ztf_candidate._append( - { - "name": "schemavsn", - "type": "string", - "doc": "schema version used", - }, - ignore_index=True, - ) - ztf_candidate = ztf_candidate._append( - { - "name": "publisher", - "type": "string", - "doc": "origin of alert packet", - }, - ignore_index=True, - ) - ztf_candidate = ztf_candidate._append( - { - "name": "objectId", - "type": "string", - "doc": "object identifier or name", - }, - ignore_index=True, - ) - - ztf_candidate = ztf_candidate._append( - { - "name": "fink_broker_version", - "type": "string", - "doc": "Fink broker (fink-broker) version used to process the data", - }, - ignore_index=True, - ) - - ztf_candidate = ztf_candidate._append( - { - "name": "fink_science_version", - "type": "string", - "doc": "Science modules (fink-science) version used to process the data", - }, - ignore_index=True, - ) - - ztf_cutouts = pd.DataFrame.from_dict( - [ - { - "name": "cutoutScience_stampData", - "type": "array", - "doc": "2D array from the Science cutout FITS", - }, - ], - ) - ztf_cutouts = ztf_cutouts._append( - { - "name": "cutoutTemplate_stampData", - "type": "array", - "doc": "2D array from the Template cutout FITS", - }, - ignore_index=True, - ) - ztf_cutouts = ztf_cutouts._append( - { - "name": "cutoutDifference_stampData", - "type": "array", - "doc": "2D array from the Difference cutout FITS", - }, - ignore_index=True, - ) - - # Science modules - fink_science = pd.DataFrame( - [ - { - "name": "cdsxmatch", - "type": "string", - "doc": "Object type of the closest source from SIMBAD database; if exists within 1 arcsec. See https://fink-portal.org/api/v1/classes", - }, - { - "name": "gcvs", - "type": "string", - "doc": "Object type of the closest source from GCVS catalog; if exists within 1 arcsec.", - }, - { - "name": "vsx", - "type": "string", - "doc": "Object type of the closest source from VSX catalog; if exists within 1 arcsec.", - }, - { - "name": "DR3Name", - "type": "string", - "doc": "Unique source designation of closest source from Gaia catalog; if exists within 1 arcsec.", - }, - { - "name": "Plx", - "type": "double", - "doc": "Absolute stellar parallax (in milli-arcsecond) of the closest source from Gaia catalog; if exists within 1 arcsec.", - }, - { - "name": "e_Plx", - "type": "double", - "doc": "Standard error of the stellar parallax (in milli-arcsecond) of the closest source from Gaia catalog; if exists within 1 arcsec.", - }, - { - "name": "x3hsp", - "type": "string", - "doc": "Counterpart (cross-match) to the 3HSP catalog if exists within 1 arcminute.", - }, - { - "name": "x4lac", - "type": "string", - "doc": "Counterpart (cross-match) to the 4LAC DR3 catalog if exists within 1 arcminute.", - }, - { - "name": "mangrove_HyperLEDA_name", - "type": "string", - "doc": "HyperLEDA source designation of closest source from Mangrove catalog; if exists within 1 arcmin.", - }, - { - "name": "mangrove_2MASS_name", - "type": "string", - "doc": "2MASS source designation of closest source from Mangrove catalog; if exists within 1 arcmin.", - }, - { - "name": "mangrove_lum_dist", - "type": "string", - "doc": "Luminosity distance of closest source from Mangrove catalog; if exists within 1 arcmin.", - }, - { - "name": "mangrove_ang_dist", - "type": "string", - "doc": "Angular distance of closest source from Mangrove catalog; if exists within 1 arcmin.", - }, - { - "name": "spicy_id", - "type": "string", - "doc": "Unique source designation of closest source from SPICY catalog; if exists within 1.2 arcsec.", - }, - { - "name": "spicy_class", - "type": "string", - "doc": "Class name of closest source from SPICY catalog; if exists within 1.2 arcsec.", - }, - { - "name": "mulens", - "type": "double", - "doc": "Probability score of an alert to be a microlensing event by [LIA](https://github.com/dgodinez77/LIA).", - }, - { - "name": "rf_snia_vs_nonia", - "type": "double", - "doc": "Probability of an alert to be a SNe Ia using a Random Forest Classifier (binary classification). Higher is better.", - }, - { - "name": "rf_kn_vs_nonkn", - "type": "double", - "doc": "Probability of an alert to be a Kilonova using a PCA & Random Forest Classifier (binary classification). Higher is better.", - }, - { - "name": "roid", - "type": "int", - "doc": "Determine if the alert is a potential Solar System object (experimental). 0: likely not SSO, 1: first appearance but likely not SSO, 2: candidate SSO, 3: found in MPC.", - }, - { - "name": "snn_sn_vs_all", - "type": "double", - "doc": "The probability of an alert to be a SNe vs. anything else (variable stars and other categories in the training) using SuperNNova", - }, - { - "name": "snn_snia_vs_nonia", - "type": "double", - "doc": "The probability of an alert to be a SN Ia vs. core-collapse SNe using SuperNNova", - }, - { - "name": "anomaly_score", - "type": "double", - "doc": "Probability of an alert to be anomalous (lower values mean more anomalous observations) based on lc_*", - }, - { - "name": "nalerthist", - "type": "int", - "doc": "Number of detections contained in each alert (current+history). Upper limits are not taken into account.", - }, - { - "name": "tracklet", - "type": "string", - "doc": "ID for fast moving objects, typically orbiting around the Earth. Of the format YYYY-MM-DD hh:mm:ss", - }, - { - "name": "lc_features_g", - "type": "string", - "doc": "Numerous light curve features for the g band (see https://github.com/astrolabsoftware/fink-science/tree/master/fink_science/ad_features). Stored as string of array.", - }, - { - "name": "lc_features_r", - "type": "string", - "doc": "Numerous light curve features for the r band (see https://github.com/astrolabsoftware/fink-science/tree/master/fink_science/ad_features). Stored as string of array.", - }, - { - "name": "jd_first_real_det", - "type": "double", - "doc": "First variation time at 5 sigma contained in the alert history", - }, - { - "name": "jdstarthist_dt", - "type": "double", - "doc": "Delta time between `jd_first_real_det` and the first variation time at 3 sigma (`jdstarthist`). If `jdstarthist_dt` > 30 days then the first variation time at 5 sigma is False (accurate for fast transient).", - }, - {"name": "mag_rate", "type": "double", "doc": "Magnitude rate (mag/day)"}, - { - "name": "sigma_rate", - "type": "double", - "doc": "Magnitude rate error estimation (mag/day)", - }, - { - "name": "lower_rate", - "type": "double", - "doc": "5% percentile of the magnitude rate sampling used for the error computation (`sigma_rate`)", - }, - { - "name": "upper_rate", - "type": "double", - "doc": "95% percentile of the magnitude rate sampling used for the error computation (`sigma_rate`)", - }, - { - "name": "delta_time", - "type": "double", - "doc": "Delta time between the the two measurement used for the magnitude rate `mag_rate`", - }, - { - "name": "from_upper", - "type": "boolean", - "doc": "If True, the magnitude rate `mag_rate` has been computed using the last upper limit and the current measurement.", - }, - { - "name": "tag", - "type": "string", - "doc": "Quality tag among `valid`, `badquality` (does not satisfy quality cuts), and `upper` (upper limit measurement). Only available if `withupperlim` is set to True.", - }, - { - "name": "tns", - "type": "string", - "doc": "TNS label, if it exists.", - }, - ], - ) - - fink_derived = pd.DataFrame( - [ - { - "name": "constellation", - "type": "string", - "doc": "Name of the constellation an alert on the sky is in", - }, - { - "name": "classification", - "type": "string", - "doc": "Fink inferred classification. See https://fink-portal.org/api/v1/classes", - }, - { - "name": "g-r", - "type": "double", - "doc": "Last g-r measurement for this object.", - }, - { - "name": "sigma(g-r)", - "type": "double", - "doc": "Error of last g-r measurement for this object.", - }, - { - "name": "rate(g-r)", - "type": "double", - "doc": "g-r change rate in mag/day (between last and previous g-r measurements).", - }, - { - "name": "sigma(rate(g-r))", - "type": "double", - "doc": "Error of g-r rate in mag/day (between last and previous g-r measurements).", - }, - { - "name": "rate", - "type": "double", - "doc": "Brightness change rate in mag/day (between last and previous measurement in this filter).", - }, - { - "name": "sigma(rate)", - "type": "double", - "doc": "Error of brightness change rate in mag/day (between last and previous measurement in this filter).", - }, - { - "name": "lastdate", - "type": "string", - "doc": "Human readable datetime for the alert (from the i:jd field).", - }, - { - "name": "firstdate", - "type": "string", - "doc": "Human readable datetime for the first detection of the object (from the i:jdstarthist field).", - }, - { - "name": "lapse", - "type": "double", - "doc": "Number of days between first and last detection.", - }, - ], - ) - - # Sort by name - ztf_candidate = ztf_candidate.sort_values("name") - fink_science = fink_science.sort_values("name") - fink_derived = fink_derived.sort_values("name") - - types = { - "ZTF original fields (i:)": { - i: {"type": j, "doc": k} - for i, j, k in zip( - ztf_candidate.name, ztf_candidate.type, ztf_candidate.doc - ) - }, - "ZTF original cutouts (b:)": { - i: {"type": j, "doc": k} - for i, j, k in zip(ztf_cutouts.name, ztf_cutouts.type, ztf_cutouts.doc) - }, - "Fink science module outputs (d:)": { - i: {"type": j, "doc": k} - for i, j, k in zip(fink_science.name, fink_science.type, fink_science.doc) - }, - "Fink on-the-fly added values (v:)": { - i: {"type": j, "doc": k} - for i, j, k in zip(fink_derived.name, fink_derived.type, fink_derived.doc) - }, - } - - return jsonify({"fields": types}) - - -@api_bp.route("/api/v1/sso", methods=["GET"]) -def return_sso_arguments(): - """Obtain information about retrieving Solar System Object data""" - if len(request.args) > 0: - # POST from query URL - return return_sso(payload=request.args) - else: - return jsonify({"args": args_sso}) - - -@api_bp.route("/api/v1/sso", methods=["POST"]) -def return_sso(payload=None): - """Retrieve Solar System Object data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - pdf = return_sso_pdf(payload) - - # Error propagation - if not isinstance(pdf, pd.DataFrame): - return pdf - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/ssocand", methods=["GET"]) -def return_ssocand_arguments(): - """Obtain information about retrieving candidate Solar System Object data""" - if len(request.args) > 0: - # POST from query URL - return return_ssocand(payload=request.args) - else: - return jsonify({"args": args_ssocand}) - - -@api_bp.route("/api/v1/ssocand", methods=["POST"]) -def return_ssocand(payload=None): - """Retrieve candidate Solar System Object data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_ssocand if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdf = return_ssocand_pdf(payload) - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/tracklet", methods=["GET"]) -def return_tracklet_arguments(): - """Obtain information about retrieving Tracklets""" - if len(request.args) > 0: - # POST from query URL - return return_tracklet(payload=request.args) - else: - return jsonify({"args": args_tracklet}) - - -@api_bp.route("/api/v1/tracklet", methods=["POST"]) -def return_tracklet(payload=None): - """Retrieve tracklet data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - pdf = return_tracklet_pdf(payload) - - # Error propagation - if isinstance(pdf, Response): - return pdf - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/cutouts", methods=["GET"]) -def cutouts_arguments(): - """Obtain information about cutouts service""" - if len(request.args) > 0: - # POST from query URL - return return_cutouts(payload=request.args) - else: - return jsonify({"args": args_cutouts}) - - -@api_bp.route("/api/v1/cutouts", methods=["POST"]) -def return_cutouts(payload=None): - """Retrieve cutout data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - assert payload["kind"] in ["Science", "Template", "Difference", "All"] - - return format_and_send_cutout(payload) - - -@api_bp.route("/api/v1/xmatch", methods=["GET"]) -def xmatch_arguments(): - """Obtain information about the xmatch service""" - if len(request.args) > 0: - # POST from query URL - return xmatch_user(payload=request.args) - else: - return jsonify({"args": args_xmatch}) - - -@api_bp.route("/api/v1/xmatch", methods=["POST"]) -def xmatch_user(payload=None): - """Xmatch with user uploaded catalog""" - # get payload from the JSON - if payload is None: - payload = request.json - - return perform_xmatch(payload) - - -@api_bp.route("/api/v1/bayestar", methods=["GET"]) -def query_bayestar_arguments(): - """Obtain information about inspecting a GW localization map""" - if len(request.args) > 0: - # POST from query URL - return query_bayestar(payload=request.args) - else: - return jsonify({"args": args_bayestar}) - - -@api_bp.route("/api/v1/bayestar", methods=["POST"]) -def query_bayestar(payload=None): - """Query the Fink database to find alerts inside a GW localization map""" - # get payload from the JSON - if payload is None: - payload = request.json - - pdfs = return_bayestar_pdf(payload) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/statistics", methods=["GET"]) -def query_statistics_arguments(): - """Obtain information about Fink statistics""" - if len(request.args) > 0: - # POST from query URL - return return_statistics(payload=request.args) - else: - return jsonify({"args": args_stats}) - - -@api_bp.route("/api/v1/statistics", methods=["POST"]) -def return_statistics(payload=None): - """Retrieve statistics about Fink data""" - # get payload from the JSON - if payload is None: - payload = request.json - - pdf = return_statistics_pdf(payload) - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/random", methods=["GET"]) -def return_random_arguments(): - """Obtain information about retrieving random object data""" - if len(request.args) > 0: - # POST from query URL - return return_random(payload=request.args) - else: - return jsonify({"args": args_random}) - - -@api_bp.route("/api/v1/random", methods=["POST"]) -def return_random(payload=None): - """Retrieve random object data from the Fink database""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_random if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdf = return_random_pdf(payload) - - # Error propagation - if isinstance(pdf, Response): - return pdf - - output_format = payload.get("output-format", "json") - return send_data(pdf, output_format) - - -@api_bp.route("/api/v1/anomaly", methods=["GET"]) -def anomalous_objects_arguments(): - """Obtain information about anomalous objects""" - if len(request.args) > 0: - # POST from query URL - return anomalous_objects(payload=request.args) - else: - return jsonify({"args": args_anomaly}) - - -@api_bp.route("/api/v1/anomaly", methods=["POST"]) -def anomalous_objects(payload=None): - """Get anomalous objects""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_anomaly if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdfs = return_anomalous_objects_pdf(payload) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/ssoft", methods=["GET"]) -def ssoft_arguments(): - """Obtain information about the Fink Flat Table""" - if len(request.args) > 0: - # POST from query URL - return ssoft_table(payload=request.args) - else: - return jsonify({"args": args_ssoft}) - - -@api_bp.route("/api/v1/ssoft", methods=["POST"]) -def ssoft_table(payload=None): - """Get the Fink Flat Table""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_ssoft if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - if "schema" in payload: - if "flavor" in payload: - flavor = payload["flavor"] - if flavor not in ["SSHG1G2", "SHG1G2", "HG1G2", "HG"]: - rep = { - "status": "error", - "text": "flavor needs to be in ['SSHG1G2', 'SHG1G2', 'HG1G2', 'HG']\n", - } - return Response(str(rep), 400) - elif flavor == "SSHG1G2": - ssoft_columns = {**COLUMNS, **COLUMNS_SSHG1G2} - elif flavor == "SHG1G2": - ssoft_columns = {**COLUMNS, **COLUMNS_SHG1G2} - elif flavor == "HG1G2": - ssoft_columns = {**COLUMNS, **COLUMNS_HG1G2} - elif flavor == "HG": - ssoft_columns = {**COLUMNS, **COLUMNS_HG} - else: - ssoft_columns = {**COLUMNS, **COLUMNS_SHG1G2} - # return the schema of the table - return jsonify({"args": ssoft_columns}) - - out = return_ssoft_pdf(payload) - - # Error propagation - if isinstance(out, Response): - return out - - if isinstance(out, pd.DataFrame): - output_format = payload.get("output-format", "json") - return send_data(out, output_format) - - # return the binary - return out - - -@api_bp.route("/api/v1/resolver", methods=["GET"]) -def resolver_arguments(): - """Obtain information about the resolver service""" - if len(request.args) > 0: - # POST from query URL - return resolver_table(payload=request.args) - else: - return jsonify({"args": args_resolver}) - - -@api_bp.route("/api/v1/resolver", methods=["POST"]) -def resolver_table(payload=None): - """Get information about an object name""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_resolver if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - pdfs = return_resolver_pdf(payload) - - # Error propagation - if isinstance(pdfs, Response): - return pdfs - - output_format = payload.get("output-format", "json") - return send_data(pdfs, output_format) - - -@api_bp.route("/api/v1/euclidin", methods=["GET"]) -def query_euclidin_arguments(): - """Obtain information about Euclid input files""" - if len(request.args) > 0: - # POST from query URL - return query_euclidin(payload=request.args) - else: - return jsonify({"args": args_euclidin}) - - -@api_bp.route("/api/v1/euclidin", methods=["POST"]) -def query_euclidin(payload=None): - """Upload Euclid data in Fink""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_euclidin if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - out = upload_euclid_data(payload) - - return out - - -@api_bp.route("/api/v1/eucliddata", methods=["GET"]) -def query_eucliddata_arguments(): - """Obtain information about Euclid stored data""" - if len(request.args) > 0: - # POST from query URL - return query_eucliddata(payload=request.args) - else: - return jsonify({"args": args_eucliddata}) - - -@api_bp.route("/api/v1/eucliddata", methods=["POST"]) -def query_eucliddata(payload=None): - """Download Euclid data in Fink""" - # get payload from the JSON - if payload is None: - payload = request.json - - # Check all required args are here - required_args = [i["name"] for i in args_eucliddata if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - out = download_euclid_data(payload) - - # Error propagation - if isinstance(out, Response): - return out - - output_format = payload.get("output-format", "json") - return send_data(out, output_format) - - -@api_bp.route("/api/v1/metadata", methods=["GET"]) -def metadata_arguments(): - """Obtain information about uploading metadata""" - if len(request.args) > 0: - # POST from query URL - return upload_metadata(payload=request.args) - else: - return jsonify({"args": args_metadata}) - - -@api_bp.route("/api/v1/metadata", methods=["POST"]) -def upload_metadata(payload=None): - """Upload metadata in Fink""" - # get payload from the JSON - if payload is None: - payload = request.json - - if len(payload) == 1 and "objectId" in payload: - # return the associated data - pdf = retrieve_metadata(payload["objectId"]) - out = send_data(pdf, "json") - elif len(payload) == 1 and "internal_name" in payload: - # return the associated data - pdf = retrieve_oid(payload["internal_name"], "internal_name") - out = send_data(pdf, "json") - elif len(payload) == 1 and "internal_name_encoded" in payload: - # return the associated data - pdf = retrieve_oid(payload["internal_name_encoded"], "internal_name_encoded") - out = send_data(pdf, "json") - else: - # Check all required args are here - required_args = [i["name"] for i in args_metadata if i["required"] is True] - for required_arg in required_args: - if required_arg not in payload: - rep = { - "status": "error", - "text": f"A value for `{required_arg}` is required. Use GET to check arguments.\n", - } - return Response(str(rep), 400) - - out = post_metadata(payload) - - return out diff --git a/apps/api/utils.py b/apps/api/utils.py deleted file mode 100644 index 6a8d3545..00000000 --- a/apps/api/utils.py +++ /dev/null @@ -1,2134 +0,0 @@ -# Copyright 2022-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import datetime -import json -import gzip -import io - -import astropy.units as u -import healpy as hp -import numpy as np -import pandas as pd -import requests -import yaml - -from astropy.coordinates import SkyCoord -from astropy.io import fits, votable -from astropy.table import Table -from astropy.time import Time, TimeDelta -from flask import Response, send_file, jsonify -from matplotlib import cm -from PIL import Image - -from app import APIURL -from apps.client import connect_to_hbase_table -from apps.euclid.utils import ( - add_columns, - check_header, - compute_rowkey, - load_euclid_header, -) -from apps.plotting import legacy_normalizer, sigmoid_normalizer -from apps.utils import ( - convert_datatype, - convolve, - format_hbase_output, - hbase_to_dict, - hbase_type_converter, - isoify_time, -) -from apps.sso.utils import resolve_sso_name, resolve_sso_name_to_ssnamenr -from fink_utils.sso.utils import get_miriade_data -from fink_utils.sso.spins import func_hg1g2_with_spin, estimate_sso_params - - -def return_object_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/objects - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/objects - - Return - ---------- - out: pandas dataframe - """ - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if "," in payload["objectId"]: - # multi-objects search - splitids = payload["objectId"].split(",") - objectids = [f"key:key:{i.strip()}" for i in splitids] - else: - # single object search - objectids = ["key:key:{}".format(payload["objectId"])] - - if "withcutouts" in payload and str(payload["withcutouts"]) == "True": - withcutouts = True - else: - withcutouts = False - - if "withupperlim" in payload and str(payload["withupperlim"]) == "True": - withupperlim = True - else: - withupperlim = False - - if cols == "*": - truncated = False - else: - truncated = True - - client = connect_to_hbase_table("ztf") - - # Get data from the main table - results = {} - for to_evaluate in objectids: - result = client.scan( - "", - to_evaluate, - cols, - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - - pdf = format_hbase_output( - results, - schema_client, - group_alerts=False, - truncated=truncated, - ) - - if withcutouts: - # Default `None` returns all 3 cutouts - cutout_kind = payload.get("cutout-kind", "All") - - def download_cutout(objectId, candid, kind): - r = requests.post( - "{}/api/v1/cutouts".format(APIURL), - json={ - "objectId": objectId, - "candid": candid, - "kind": kind, - "output-format": "array", - }, - ) - if r.status_code == 200: - data = json.loads(r.content) - else: - # TODO: different return based on `kind`? - return [] - - if kind != "All": - return data["b:cutout{}_stampData".format(kind)] - else: - return [ - data["b:cutout{}_stampData".format(k)] - for k in ["Science", "Template", "Difference"] - ] - - if cutout_kind == "All": - cols = [ - "b:cutoutScience_stampData", - "b:cutoutTemplate_stampData", - "b:cutoutDifference_stampData", - ] - pdf[cols] = pdf[["i:objectId", "i:candid"]].apply( - lambda x: pd.Series(download_cutout(x.iloc[0], x.iloc[1], cutout_kind)), - axis=1, - ) - else: - colname = "b:cutout{}_stampData".format(cutout_kind) - pdf[colname] = pdf[["i:objectId", "i:candid"]].apply( - lambda x: pd.Series( - [download_cutout(x.iloc[0], x.iloc[1], cutout_kind)] - ), - axis=1, - ) - - if withupperlim: - clientU = connect_to_hbase_table("ztf.upper") - # upper limits - resultsU = {} - for to_evaluate in objectids: - resultU = clientU.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - resultsU.update(resultU) - - # bad quality - clientUV = connect_to_hbase_table("ztf.uppervalid") - resultsUP = {} - for to_evaluate in objectids: - resultUP = clientUV.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - resultsUP.update(resultUP) - - pdfU = pd.DataFrame.from_dict(hbase_to_dict(resultsU), orient="index") - pdfUP = pd.DataFrame.from_dict(hbase_to_dict(resultsUP), orient="index") - - pdf["d:tag"] = "valid" - pdfU["d:tag"] = "upperlim" - pdfUP["d:tag"] = "badquality" - - if "i:jd" in pdfUP.columns: - # workaround -- see https://github.com/astrolabsoftware/fink-science-portal/issues/216 - mask = np.array( - [ - False if float(i) in pdf["i:jd"].to_numpy() else True - for i in pdfUP["i:jd"].to_numpy() - ] - ) - pdfUP = pdfUP[mask] - - # Hacky way to avoid converting concatenated column to float - pdfU["i:candid"] = -1 # None - pdfUP["i:candid"] = -1 # None - - pdf_ = pd.concat((pdf, pdfU, pdfUP), axis=0) - - # replace - if "i:jd" in pdf_.columns: - pdf_["i:jd"] = pdf_["i:jd"].astype(float) - pdf = pdf_.sort_values("i:jd", ascending=False) - else: - pdf = pdf_ - - clientU.close() - clientUV.close() - - client.close() - - return pdf - - -def return_explorer_pdf(payload: dict, user_group: int) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/explorer - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/explorer - - Return - ---------- - out: pandas dataframe - """ - truncated = False - - if "startdate" in payload: - jd_start = Time(isoify_time(payload["startdate"])).jd - else: - jd_start = Time("2019-11-01 00:00:00").jd - - if "stopdate" in payload: - jd_stop = Time(isoify_time(payload["stopdate"])).jd - elif "window" in payload and "startdate" in payload: - window = float(payload["window"]) - jd_stop = jd_start + window - else: - jd_stop = Time.now().jd - - n = int(payload.get("n", 1000)) - - if user_group == 0: - # objectId search - client = connect_to_hbase_table("ztf") - results = {} - for oid in payload["objectId"].split(","): - # objectId search - to_evaluate = f"key:key:{oid.strip()}" - result = client.scan( - "", - to_evaluate, - "*", - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - elif user_group == 1: - # Conesearch with optional date range - client = connect_to_hbase_table("ztf.pixel128") - client.setLimit(n) - - # Interpret user input - ra, dec = payload["ra"], payload["dec"] - radius = payload["radius"] - - if float(radius) > 18000.0: - rep = { - "status": "error", - "text": "`radius` cannot be bigger than 18,000 arcseconds (5 degrees).\n", - } - return Response(str(rep), 400) - - try: - if "h" in str(ra): - coord = SkyCoord(ra, dec, frame="icrs") - elif ":" in str(ra) or " " in str(ra): - coord = SkyCoord(ra, dec, frame="icrs", unit=(u.hourangle, u.deg)) - else: - coord = SkyCoord(ra, dec, frame="icrs", unit="deg") - except ValueError as e: - rep = { - "status": "error", - "text": e, - } - return Response(str(rep), 400) - - ra = coord.ra.deg - dec = coord.dec.deg - radius_deg = float(radius) / 3600.0 - - # angle to vec conversion - vec = hp.ang2vec(np.pi / 2.0 - np.pi / 180.0 * dec, np.pi / 180.0 * ra) - - # Send request - nside = 128 - - pixs = hp.query_disc( - nside, - vec, - np.pi / 180 * radius_deg, - inclusive=True, - ) - - # Filter by time - if "startdate" in payload: - client.setRangeScan(True) - results = {} - for pix in pixs: - to_search = f"key:key:{pix}_{jd_start},key:key:{pix}_{jd_stop}" - result = client.scan( - "", - to_search, - "*", - 0, - True, - True, - ) - results.update(result) - client.setRangeScan(False) - else: - results = {} - for pix in pixs: - to_search = f"key:key:{pix}_" - result = client.scan( - "", - to_search, - "*", - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - truncated = True - else: - # Plain date search - client = connect_to_hbase_table("ztf.jd") - - # Limit the time window to 3 hours days - if jd_stop - jd_start > 3 / 24: - jd_stop = jd_start + 3 / 24 - - # Send the request. RangeScan. - client.setRangeScan(True) - client.setLimit(n) - to_evaluate = f"key:key:{jd_start},key:key:{jd_stop}" - results = client.scan( - "", - to_evaluate, - "*", - 0, - True, - True, - ) - schema_client = client.schema() - - client.close() - - pdfs = format_hbase_output( - results, - schema_client, - truncated=truncated, - group_alerts=True, - extract_color=False, - ) - - # For conesearch, sort by distance - if (user_group == 1) and (len(pdfs) > 0): - sep = coord.separation( - SkyCoord( - pdfs["i:ra"], - pdfs["i:dec"], - unit="deg", - ), - ).deg - - pdfs["v:separation_degree"] = sep - pdfs = pdfs.sort_values("v:separation_degree", ascending=True) - - mask = pdfs["v:separation_degree"] > radius_deg - pdfs = pdfs[~mask] - - return pdfs - - -def return_conesearch_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/conesearch - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/conesearch - - Return - ---------- - out: pandas dataframe - """ - if "startdate" in payload: - jd_start = Time(isoify_time(payload["startdate"])).jd - else: - jd_start = Time("2019-11-01 00:00:00").jd - - if "stopdate" in payload: - jd_stop = Time(isoify_time(payload["stopdate"])).jd - elif "window" in payload and "startdate" in payload: - window = float(payload["window"]) - jd_stop = jd_start + window - else: - jd_stop = Time.now().jd - - n = int(payload.get("n", 1000)) - - # Conesearch with optional date range - client = connect_to_hbase_table("ztf.pixel128") - client.setLimit(n) - - # Interpret user input - ra, dec = payload["ra"], payload["dec"] - radius = payload["radius"] - - if float(radius) > 18000.0: - rep = { - "status": "error", - "text": "`radius` cannot be bigger than 18,000 arcseconds (5 degrees).\n", - } - return Response(str(rep), 400) - - try: - if "h" in str(ra): - coord = SkyCoord(ra, dec, frame="icrs") - elif ":" in str(ra) or " " in str(ra): - coord = SkyCoord(ra, dec, frame="icrs", unit=(u.hourangle, u.deg)) - else: - coord = SkyCoord(ra, dec, frame="icrs", unit="deg") - except ValueError as e: - rep = { - "status": "error", - "text": e, - } - return Response(str(rep), 400) - - ra = coord.ra.deg - dec = coord.dec.deg - radius_deg = float(radius) / 3600.0 - - # angle to vec conversion - vec = hp.ang2vec(np.pi / 2.0 - np.pi / 180.0 * dec, np.pi / 180.0 * ra) - - # Send request - nside = 128 - - pixs = hp.query_disc( - nside, - vec, - np.pi / 180 * radius_deg, - inclusive=True, - ) - - # Filter by time - if "startdate" in payload: - client.setRangeScan(True) - results = {} - for pix in pixs: - to_search = f"key:key:{pix}_{jd_start},key:key:{pix}_{jd_stop}" - result = client.scan( - "", - to_search, - "*", - 0, - True, - True, - ) - results.update(result) - client.setRangeScan(False) - else: - results = {} - for pix in pixs: - to_search = f"key:key:{pix}_" - result = client.scan( - "", - to_search, - "*", - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - - client.close() - - pdfs = format_hbase_output( - results, - schema_client, - truncated=True, - group_alerts=True, - extract_color=False, - ) - - # For conesearch, sort by distance - if len(pdfs) > 0: - sep = coord.separation( - SkyCoord( - pdfs["i:ra"], - pdfs["i:dec"], - unit="deg", - ), - ).deg - - pdfs["v:separation_degree"] = sep - pdfs = pdfs.sort_values("v:separation_degree", ascending=True) - - mask = pdfs["v:separation_degree"] > radius_deg - pdfs = pdfs[~mask] - - return pdfs - - -def return_latests_pdf(payload: dict, return_raw: bool = False) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/latests - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/latests - return_raw: bool - If True, return the HBase output, else pandas DataFrame. Default is False. - - Return - ---------- - out: pandas dataframe - """ - if "n" not in payload: - nalerts = 10 - else: - nalerts = int(payload["n"]) - - if "startdate" not in payload: - # start of the Fink operations - jd_start = Time("2019-11-01 00:00:00").jd - else: - jd_start = Time(payload["startdate"]).jd - - if "stopdate" not in payload: - jd_stop = Time.now().jd - else: - jd_stop = Time(payload["stopdate"]).jd - - if "color" not in payload: - color = False - else: - color = True - - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if cols == "*": - truncated = False - else: - truncated = True - - # Search for latest alerts for a specific class - tns_classes = pd.read_csv("assets/tns_types.csv", header=None)[0].to_numpy() - is_tns = payload["class"].startswith("(TNS)") and ( - payload["class"].split("(TNS) ")[1] in tns_classes - ) - if is_tns: - client = connect_to_hbase_table("ztf.tns") - classname = payload["class"].split("(TNS) ")[1] - client.setLimit(nalerts) - client.setRangeScan(True) - client.setReversed(True) - - results = client.scan( - "", - f"key:key:{classname}_{jd_start},key:key:{classname}_{jd_stop}", - cols, - 0, - True, - True, - ) - schema_client = client.schema() - group_alerts = True - elif payload["class"].startswith("(SIMBAD)") or payload["class"] != "allclasses": - if payload["class"].startswith("(SIMBAD)"): - classname = payload["class"].split("(SIMBAD) ")[1] - else: - classname = payload["class"] - - client = connect_to_hbase_table("ztf.class") - - client.setLimit(nalerts) - client.setRangeScan(True) - client.setReversed(True) - - results = client.scan( - "", - f"key:key:{classname}_{jd_start},key:key:{classname}_{jd_stop}", - cols, - 0, - False, - False, - ) - schema_client = client.schema() - group_alerts = False - elif payload["class"] == "allclasses": - client = connect_to_hbase_table("ztf.jd") - client.setLimit(nalerts) - client.setRangeScan(True) - client.setReversed(True) - - to_evaluate = f"key:key:{jd_start},key:key:{jd_stop}" - results = client.scan( - "", - to_evaluate, - cols, - 0, - True, - True, - ) - schema_client = client.schema() - group_alerts = False - - client.close() - - if return_raw: - return results - - # We want to return alerts - # color computation is disabled - pdfs = format_hbase_output( - results, - schema_client, - group_alerts=group_alerts, - extract_color=color, - truncated=truncated, - with_constellation=True, - ) - - return pdfs - - -def return_sso_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/sso - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/sso - - Return - ---------- - out: pandas dataframe - """ - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if cols == "*": - truncated = False - else: - truncated = True - - with_ephem, with_residuals, with_cutouts = False, False, False - if "withResiduals" in payload and ( - payload["withResiduals"] == "True" or payload["withResiduals"] is True - ): - with_residuals = True - with_ephem = True - if "withEphem" in payload and ( - payload["withEphem"] == "True" or payload["withEphem"] is True - ): - with_ephem = True - if "withcutouts" in payload and ( - payload["withcutouts"] == "True" or payload["withcutouts"] is True - ): - with_cutouts = True - - n_or_d = str(payload["n_or_d"]) - - if "," in n_or_d: - ids = n_or_d.replace(" ", "").split(",") - multiple_objects = True - else: - ids = [n_or_d.replace(" ", "")] - multiple_objects = False - - # We cannot do multi-object and phase curve computation - if multiple_objects and with_residuals: - rep = { - "status": "error", - "text": "You cannot request residuals for a list object names.\n", - } - return Response(str(rep), 400) - - # Get all ssnamenrs - ssnamenrs = [] - ssnamenr_to_sso_name = {} - ssnamenr_to_sso_number = {} - for id_ in ids: - if id_.startswith("C/"): - start = id_[0:6] - stop = id_[6:] - r = requests.get( - "https://api.ssodnet.imcce.fr/quaero/1/sso?q={} {}&type=Comet".format( - start, stop - ) - ) - if r.status_code == 200 and r.json() != []: - sso_name = r.json()["data"][0]["name"] - else: - sso_name = id_ - sso_number = None - elif id_.endswith("P"): - sso_name = id_ - sso_number = None - else: - # resolve the name of asteroids using rocks - sso_name, sso_number = resolve_sso_name(id_) - - if not isinstance(sso_number, int) and not isinstance(sso_name, str): - rep = { - "status": "error", - "text": "{} is not a valid name or number according to quaero.\n".format( - n_or_d - ), - } - return Response(str(rep), 400) - - # search all ssnamenr corresponding quaero -> ssnamenr - if isinstance(sso_name, str): - new_ssnamenrs = resolve_sso_name_to_ssnamenr(sso_name) - ssnamenrs = np.concatenate((ssnamenrs, new_ssnamenrs)) - else: - new_ssnamenrs = resolve_sso_name_to_ssnamenr(sso_number) - ssnamenrs = np.concatenate((ssnamenrs, new_ssnamenrs)) - - for ssnamenr_ in new_ssnamenrs: - ssnamenr_to_sso_name[ssnamenr_] = sso_name - ssnamenr_to_sso_number[ssnamenr_] = sso_number - - # Get data from the main table - client = connect_to_hbase_table("ztf.ssnamenr") - results = {} - for to_evaluate in ssnamenrs: - result = client.scan( - "", - f"key:key:{to_evaluate}_", - cols, - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - - # reset the limit in case it has been changed above - client.close() - - pdf = format_hbase_output( - results, - schema_client, - group_alerts=False, - truncated=truncated, - extract_color=False, - ) - - # Propagate name and number - pdf["sso_name"] = pdf["i:ssnamenr"].apply(lambda x: ssnamenr_to_sso_name[x]) - pdf["sso_number"] = pdf["i:ssnamenr"].apply(lambda x: ssnamenr_to_sso_number[x]) - - if with_cutouts: - # Extract cutouts - cutout_kind = payload.get("cutout-kind", "Science") - if cutout_kind not in ["Science", "Template", "Difference"]: - rep = { - "status": "error", - "text": "`cutout-kind` must be `Science`, `Difference`, or `Template`.\n", - } - return Response(str(rep), 400) - - colname = "b:cutout{}_stampData".format(cutout_kind) - - # get all cutouts - cutouts = [] - for result in results.values(): - r = requests.post( - f"{APIURL}/api/v1/cutouts", - json={ - "objectId": result["i:objectId"], - "candid": result["i:candid"], - "kind": cutout_kind, - "output-format": "array", - }, - ) - if r.status_code == 200: - # the result should be unique (based on candid) - cutouts.append(json.loads(r.content)[colname]) - else: - rep = { - "status": "error", - "text": r.content, - } - return Response(str(rep), r.status_code) - - pdf[colname] = cutouts - - if with_ephem: - # We should probably add a timeout - # and try/except in case of miriade shutdown - pdf = get_miriade_data(pdf, sso_colname="sso_name") - if "i:magpsf_red" not in pdf.columns: - rep = { - "status": "error", - "text": "We could not obtain the ephemerides information. Check Miriade availabilities.", - } - return Response(str(rep), 400) - - if with_residuals: - # get phase curve parameters using - # the sHG1G2 model - - # Phase angle, in radians - phase = np.deg2rad(pdf["Phase"].values) - - # Required for sHG1G2 - ra = np.deg2rad(pdf["i:ra"].values) - dec = np.deg2rad(pdf["i:dec"].values) - - outdic = estimate_sso_params( - magpsf_red=pdf["i:magpsf_red"].to_numpy(), - sigmapsf=pdf["i:sigmapsf"].to_numpy(), - phase=phase, - filters=pdf["i:fid"].to_numpy(), - ra=ra, - dec=dec, - p0=[15.0, 0.15, 0.15, 0.8, np.pi, 0.0], - bounds=( - [0, 0, 0, 3e-1, 0, -np.pi / 2], - [30, 1, 1, 1, 2 * np.pi, np.pi / 2], - ), - model="SHG1G2", - normalise_to_V=False, - ) - - # check if fit converged else return NaN - if outdic["fit"] != 0: - pdf["residuals_shg1g2"] = np.nan - else: - # per filter construction of the residual - pdf["residuals_shg1g2"] = 0.0 - for filt in np.unique(pdf["i:fid"]): - cond = pdf["i:fid"] == filt - model = func_hg1g2_with_spin( - [phase[cond], ra[cond], dec[cond]], - outdic["H_{}".format(filt)], - outdic["G1_{}".format(filt)], - outdic["G2_{}".format(filt)], - outdic["R"], - np.deg2rad(outdic["alpha0"]), - np.deg2rad(outdic["delta0"]), - ) - pdf.loc[cond, "residuals_shg1g2"] = ( - pdf.loc[cond, "i:magpsf_red"] - model - ) - - return pdf - - -def return_ssocand_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/ssocand - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/ssocand - - Return - ---------- - out: pandas dataframe - """ - if "ssoCandId" in payload: - trajectory_id = str(payload["ssoCandId"]) - else: - trajectory_id = None - - if "maxnumber" in payload: - maxnumber = payload["maxnumber"] - else: - maxnumber = 10000 - - payload_name = payload["kind"] - - if payload_name == "orbParams": - gen_client = connect_to_hbase_table("ztf.orb_cand") - - if trajectory_id is not None: - to_evaluate = f"key:key:cand_{trajectory_id}" - else: - to_evaluate = "key:key:cand_" - elif payload_name == "lightcurves": - gen_client = connect_to_hbase_table("ztf.sso_cand") - - if "start_date" in payload: - start_date = Time(payload["start_date"], format="iso").jd - else: - start_date = Time("2019-11-01", format="iso").jd - - if "stop_date" in payload: - stop_date = Time(payload["stop_date"], format="iso").jd - else: - stop_date = Time.now().jd - - gen_client.setRangeScan(True) - gen_client.setLimit(maxnumber) - - if trajectory_id is not None: - gen_client.setEvaluation(f"ssoCandId.equals('{trajectory_id}')") - - to_evaluate = f"key:key:{start_date}_,key:key:{stop_date}_" - - results = gen_client.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - - schema_client = gen_client.schema() - gen_client.close() - - if results.isEmpty(): - return pd.DataFrame({}) - - # Construct the dataframe - pdf = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - - if "key:time" in pdf.columns: - pdf = pdf.drop(columns=["key:time"]) - - # Type conversion - for col in pdf.columns: - pdf[col] = convert_datatype( - pdf[col], - hbase_type_converter[schema_client.type(col)], - ) - - return pdf - - -def return_tracklet_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/tracklet - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/tracklet - - Return - ---------- - out: pandas dataframe - """ - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if cols == "*": - truncated = False - else: - truncated = True - - if "id" in payload: - payload_name = payload["id"] - elif "date" in payload: - designation = payload["date"] - payload_name = "TRCK_" + designation.replace("-", "").replace(":", "").replace( - " ", "_" - ) - else: - rep = { - "status": "error", - "text": "You need to specify a date at the format YYYY-MM-DD hh:mm:ss\n", - } - return Response(str(rep), 400) - - # Note the trailing _ - to_evaluate = f"key:key:{payload_name}" - - client = connect_to_hbase_table("ztf.tracklet") - results = client.scan( - "", - to_evaluate, - cols, - 0, - True, - True, - ) - - schema_client = client.schema() - - # reset the limit in case it has been changed above - client.close() - - pdf = format_hbase_output( - results, - schema_client, - group_alerts=False, - truncated=truncated, - extract_color=False, - ) - - return pdf - - -def format_and_send_cutout(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and jsonify it - - Data is from /api/v1/cutouts - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/cutouts - - Return - ---------- - out: pandas dataframe - """ - output_format = payload.get("output-format", "PNG") - - # default stretch is sigmoid - if "stretch" in payload: - stretch = payload["stretch"] - else: - stretch = "sigmoid" - - if payload["kind"] == "All" and payload["output-format"] != "array": - # TODO: error 400 - pass - - # default name based on parameters - filename = "{}_{}".format( - payload["objectId"], - payload["kind"], - ) - - if output_format == "PNG": - filename = filename + ".png" - elif output_format == "JPEG": - filename = filename + ".jpg" - elif output_format == "FITS": - filename = filename + ".fits" - - # Query the Database (object query) - client = connect_to_hbase_table("ztf.cutouts") - results = client.scan( - "", - "key:key:{}".format(payload["objectId"]), - "d:hdfs_path,i:jd,i:candid,i:objectId", - 0, - False, - False, - ) - - # Format the results - schema_client = client.schema() - client.close() - - pdf = format_hbase_output( - results, - schema_client, - group_alerts=False, - truncated=True, - extract_color=False, - ) - - json_payload = {} - # Extract only the alert of interest - if "candid" in payload: - mask = pdf["i:candid"].astype(str) == str(payload["candid"]) - json_payload.update({"candid": str(payload["candid"])}) - pos_target = np.where(mask)[0][0] - else: - # pdf has been sorted in `format_hbase_output` - pdf = pdf.iloc[0:1] - pos_target = 0 - - json_payload.update( - { - "hdfsPath": pdf["d:hdfs_path"].to_numpy()[pos_target].split("8020")[1], - "kind": payload["kind"], - "objectId": pdf["i:objectId"].to_numpy()[pos_target], - } - ) - - if pdf.empty: - return send_file( - io.BytesIO(), - mimetype="image/png", - as_attachment=True, - download_name=filename, - ) - # Extract cutouts - if output_format == "FITS": - json_payload.update({"return_type": "FITS"}) - r0 = requests.post("http://localhost:24001/api/v1/cutouts", json=json_payload) - cutout = io.BytesIO(r0.content) - elif output_format in ["PNG", "array"]: - json_payload.update({"return_type": "array"}) - r0 = requests.post("http://localhost:24001/api/v1/cutouts", json=json_payload) - cutout = json.loads(r0.content) - - # send the FITS file - if output_format == "FITS": - return send_file( - cutout, - mimetype="application/octet-stream", - as_attachment=True, - download_name=filename, - ) - # send the array - elif output_format == "array": - if payload["kind"] != "All": - return jsonify({"b:cutout{}_stampData".format(payload["kind"]): cutout[0]}) - else: - out = { - "b:cutoutScience_stampData": cutout[0], - "b:cutoutTemplate_stampData": cutout[1], - "b:cutoutDifference_stampData": cutout[2], - } - return jsonify(out) - - array = np.nan_to_num(np.array(cutout[0], dtype=float)) - if stretch == "sigmoid": - array = sigmoid_normalizer(array, 0, 1) - elif stretch is not None: - pmin = 0.5 - if "pmin" in payload: - pmin = float(payload["pmin"]) - pmax = 99.5 - if "pmax" in payload: - pmax = float(payload["pmax"]) - array = legacy_normalizer(array, stretch=stretch, pmin=pmin, pmax=pmax) - - if "convolution_kernel" in payload: - assert payload["convolution_kernel"] in ["gauss", "box"] - array = convolve(array, smooth=1, kernel=payload["convolution_kernel"]) - - # colormap - if "colormap" in payload: - colormap = getattr(cm, payload["colormap"]) - else: - colormap = lambda x: x # noqa: E731 - array = np.uint8(colormap(array) * 255) - - # Convert to PNG - data = Image.fromarray(array) - datab = io.BytesIO() - data.save(datab, format="PNG") - datab.seek(0) - return send_file( - datab, mimetype="image/png", as_attachment=True, download_name=filename - ) - - -def perform_xmatch(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and jsonify it - - Data is from /api/v1/xmatch - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/xmatch - - Return - ---------- - out: pandas dataframe - """ - df = pd.read_csv(io.StringIO(payload["catalog"])) - - radius = float(payload["radius"]) - if radius > 18000.0: - rep = { - "status": "error", - "text": "`radius` cannot be bigger than 18,000 arcseconds (5 degrees).\n", - } - return Response(str(rep), 400) - - header = payload["header"] - - header = [i.strip() for i in header.split(",")] - if len(header) == 3: - raname, decname, idname = header - elif len(header) == 4: - raname, decname, idname, timename = header - else: - rep = { - "status": "error", - "text": "Header should contain 3 or 4 entries from your catalog. E.g. RA,DEC,ID or RA,DEC,ID,Time\n", - } - return Response(str(rep), 400) - - if "window" in payload: - window_days = payload["window"] - else: - window_days = None - - # Fink columns of interest - colnames = [ - "i:objectId", - "i:ra", - "i:dec", - "i:jd", - "d:cdsxmatch", - "i:ndethist", - ] - - colnames_added_values = [ - "d:cdsxmatch", - "d:roid", - "d:mulens_class_1", - "d:mulens_class_2", - "d:snn_snia_vs_nonia", - "d:snn_sn_vs_all", - "d:rf_snia_vs_nonia", - "i:ndethist", - "i:drb", - "i:classtar", - "d:rf_kn_vs_nonkn", - "i:jdstarthist", - ] - - unique_cols = np.unique(colnames + colnames_added_values).tolist() - - # check units - ra0 = df[raname].to_numpy()[0] - if "h" in str(ra0): - coords = [ - SkyCoord(ra, dec, frame="icrs") - for ra, dec in zip(df[raname].to_numpy(), df[decname].to_numpy()) - ] - elif ":" in str(ra0) or " " in str(ra0): - coords = [ - SkyCoord(ra, dec, frame="icrs", unit=(u.hourangle, u.deg)) - for ra, dec in zip(df[raname].to_numpy(), df[decname].to_numpy()) - ] - else: - coords = [ - SkyCoord(ra, dec, frame="icrs", unit="deg") - for ra, dec in zip(df[raname].to_numpy(), df[decname].to_numpy()) - ] - ras = [coord.ra.deg for coord in coords] - decs = [coord.dec.deg for coord in coords] - ids = df[idname].to_numpy() - - if len(header) == 4: - times = df[timename].to_numpy() - else: - times = np.zeros_like(ras) - - pdfs = pd.DataFrame(columns=unique_cols + [idname] + ["v:classification"]) - for oid, ra, dec, time_start in zip(ids, ras, decs, times): - if len(header) == 4: - payload_data = { - "ra": ra, - "dec": dec, - "radius": radius, - "startdate_conesearch": time_start, - "window_days_conesearch": window_days, - } - else: - payload_data = { - "ra": ra, - "dec": dec, - "radius": radius, - } - r = requests.post( - f"{APIURL}/api/v1/explorer", - json=payload_data, - ) - pdf = pd.read_json(io.BytesIO(r.content)) - - # Loop over results and construct the dataframe - if not pdf.empty: - pdf[idname] = [oid] * len(pdf) - if "d:rf_kn_vs_nonkn" not in pdf.columns: - pdf["d:rf_kn_vs_nonkn"] = np.zeros(len(pdf), dtype=float) - pdfs = pd.concat((pdfs, pdf), ignore_index=True) - - # Final join - join_df = pdfs.merge(df, on=idname) - - # reorganise columns order - no_duplicate = np.where(pdfs.columns != idname)[0] - cols = list(df.columns) + list(pdfs.columns[no_duplicate]) - join_df = join_df[cols] - - return join_df.to_json(orient="records") - - -def return_bayestar_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and jsonify it - - Data is from /api/v1/bayestar - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/bayestar - - Return - ---------- - out: pandas dataframe - """ - # boundaries in day - n_day_min = 1 - n_day_max = 6 - - # Interpret user input - if "bayestar" in payload: - bayestar_data = payload["bayestar"] - elif "event_name" in payload: - r = requests.get( - "https://gracedb.ligo.org/api/superevents/{}/files/bayestar.fits.gz".format( - payload["event_name"] - ) - ) - if r.status_code == 200: - bayestar_data = str(r.content) - else: - return pd.DataFrame([{"status": r.content}]) - credible_level_threshold = float(payload["credible_level"]) - - with gzip.open(io.BytesIO(eval(bayestar_data)), "rb") as f: - with fits.open(io.BytesIO(f.read())) as hdul: - data = hdul[1].data - header = hdul[1].header - - hpx = data["PROB"] - if header["ORDERING"] == "NESTED": - hpx = hp.reorder(hpx, n2r=True) - - i = np.flipud(np.argsort(hpx)) - sorted_credible_levels = np.cumsum(hpx[i]) - credible_levels = np.empty_like(sorted_credible_levels) - credible_levels[i] = sorted_credible_levels - - # TODO: use that to define the max skyfrac (in conjunction with level) - # npix = len(hpx) - # nside = hp.npix2nside(npix) - # skyfrac = np.sum(credible_levels <= 0.1) * hp.nside2pixarea(nside, degrees=True) - - credible_levels_128 = hp.ud_grade(credible_levels, 128) - - pixs = np.where(credible_levels_128 <= credible_level_threshold)[0] - - # make a condition as well on the number of pixels? - # print(len(pixs), pixs) - - # For the future: we could set clientP128.setRangeScan(True) - # and pass directly the time boundaries here instead of - # grouping by later. - - # 1 day before the event, to 6 days after the event - jdstart = Time(header["DATE-OBS"]).jd - n_day_min - jdend = jdstart + n_day_max - - client = connect_to_hbase_table("ztf.pixel128") - client.setRangeScan(True) - results = {} - for pix in pixs: - to_search = f"key:key:{pix}_{jdstart},key:key:{pix}_{jdend}" - result = client.scan( - "", - to_search, - "*", - 0, - True, - True, - ) - results.update(result) - - schema_client = client.schema() - client.close() - - pdfs = format_hbase_output( - results, - schema_client, - truncated=True, - group_alerts=True, - extract_color=False, - ) - - if pdfs.empty: - return pdfs - - pdfs["v:jdstartgw"] = Time(header["DATE-OBS"]).jd - - # remove alerts with clear wrong jdstarthist - mask = (pdfs["i:jd"] - pdfs["i:jdstarthist"]) <= n_day_max - - return pdfs[mask] - - -def return_statistics_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and jsonify it - - Data is from /api/v1/statistics - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/statistics - - Return - ---------- - out: pandas dataframe - """ - if "columns" in payload: - cols = payload["columns"] - else: - cols = "*" - - client = connect_to_hbase_table("statistics_class") - if "schema" in payload and str(payload["schema"]) == "True": - schema = client.schema() - results = list(schema.columnNames()) - pdf = pd.DataFrame({"schema": results}) - else: - payload_date = payload["date"] - - to_evaluate = f"key:key:ztf_{payload_date}" - results = client.scan( - "", - to_evaluate, - cols, - 0, - True, - True, - ) - pdf = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - - # See https://github.com/astrolabsoftware/fink-science-portal/issues/579 - pdf = pdf.replace(regex={r"^\x00.*$": 0}) - - client.close() - - return pdf - - -def send_data(pdf, output_format): - """ """ - if output_format == "json": - return pdf.to_json(orient="records") - elif output_format == "csv": - return pdf.to_csv(index=False) - elif output_format == "votable": - f = io.BytesIO() - table = Table.from_pandas(pdf) - vt = votable.from_table(table) - votable.writeto(vt, f) - f.seek(0) - return f.read() - elif output_format == "parquet": - f = io.BytesIO() - pdf.to_parquet(f) - f.seek(0) - return f.read() - - rep = { - "status": "error", - "text": f"Output format `{output_format}` is not supported. Choose among json, csv, or parquet\n", - } - return Response(str(rep), 400) - - -def return_random_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/random - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/random - - Return - ---------- - out: pandas dataframe - """ - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if "class" in payload and str(payload["class"]) != "": - classsearch = True - else: - classsearch = False - - if cols == "*": - truncated = False - else: - truncated = True - - if int(payload["n"]) > 16: - number = 16 - else: - number = int(payload["n"]) - - seed = payload.get("seed") - if seed is not None: - np.random.seed(int(payload["seed"])) - - # logic - client = connect_to_hbase_table("ztf.jd") - results = [] - client.setLimit(1000) - client.setRangeScan(True) - - jd_low = Time("2019-11-02 03:00:00.0").jd - jd_high = Time.now().jd - - # 1 month - delta_min = 43200 - delta_jd = TimeDelta(delta_min * 60, format="sec").jd - while len(results) == 0: - jdstart = np.random.uniform(jd_low, jd_high) - jdstop = jdstart + delta_jd - - if classsearch: - payload_data = { - "class": payload["class"], - "n": number, - "startdate": Time(jdstart, format="jd").iso, - "stopdate": Time(jdstop, format="jd").iso, - "columns": "", - "output-format": "json", - } - results = return_latests_pdf(payload_data, return_raw=True) - else: - results = client.scan( - "", - f"key:key:{jdstart},key:key:{jdstop}", - "", - 0, - False, - False, - ) - - oids = list(dict(results).keys()) - oids = np.array([i.split("_")[-1] for i in oids]) - - index_oid = np.random.randint(0, len(oids), number) - oid = oids[index_oid] - client.close() - - client = connect_to_hbase_table("ztf") - client.setLimit(2000) - # Get data from the main table - results = {} - for oid_ in oid: - result = client.scan( - "", - f"key:key:{oid_}", - f"{cols}", - 0, - False, - False, - ) - results.update(result) - - pdf = format_hbase_output( - results, - client.schema(), - group_alerts=False, - truncated=truncated, - ) - - client.close() - - return pdf - - -def return_anomalous_objects_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/anomaly - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/anomaly - - Return - ---------- - out: pandas dataframe - """ - if "n" not in payload: - nalerts = 10 - else: - nalerts = int(payload["n"]) - - if "start_date" not in payload: - # start of the Fink operations - jd_start = Time("2019-11-01 00:00:00").jd - else: - jd_start = Time(payload["start_date"]).jd - - if "stop_date" not in payload: - jd_stop = Time.now().jd - else: - # allow to get unique day - jd_stop = Time(payload["stop_date"]).jd + 1 - - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - if cols == "*": - truncated = False - else: - truncated = True - - client = connect_to_hbase_table("ztf.anomaly") - client.setLimit(nalerts) - client.setRangeScan(True) - client.setReversed(True) - - to_evaluate = f"key:key:{jd_start},key:key:{jd_stop}" - results = client.scan( - "", - to_evaluate, - cols, - 0, - True, - True, - ) - schema_client = client.schema() - client.close() - - # We want to return alerts - # color computation is disabled - pdfs = format_hbase_output( - results, - schema_client, - group_alerts=False, - extract_color=False, - truncated=truncated, - with_constellation=True, - ) - - return pdfs - - -def return_ssoft_pdf(payload: dict) -> pd.DataFrame: - """Send the Fink Flat Table - - Data is from /api/v1/ssoft - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/ssoft - - Return - ---------- - out: pandas dataframe - """ - if "version" in payload: - version = payload["version"] - - # version needs YYYY.MM - yyyymm = version.split(".") - if (len(yyyymm[0]) != 4) or (len(yyyymm[1]) != 2): - rep = { - "status": "error", - "text": "version needs to be YYYY.MM\n", - } - return Response(str(rep), 400) - if version < "2023.07": - rep = { - "status": "error", - "text": "version starts on 2023.07\n", - } - return Response(str(rep), 400) - else: - now = datetime.datetime.now() - version = f"{now.year}.{now.month:02d}" - - if "flavor" in payload: - flavor = payload["flavor"] - if flavor not in ["SSHG1G2", "SHG1G2", "HG1G2", "HG"]: - rep = { - "status": "error", - "text": "flavor needs to be in ['SSHG1G2', 'SHG1G2', 'HG1G2', 'HG']\n", - } - return Response(str(rep), 400) - else: - flavor = "SHG1G2" - - input_args = yaml.load(open("config_datatransfer.yml"), yaml.Loader) - r = requests.get( - "{}/SSOFT/ssoft_{}_{}.parquet?op=OPEN&user.name={}&namenoderpcaddress={}".format( - input_args["WEBHDFS"], - flavor, - version, - input_args["USER"], - input_args["NAMENODE"], - ), - ) - - if payload.get("output-format", "parquet") != "parquet": - return pd.read_parquet(io.BytesIO(r.content)) - - if "sso_name" in payload: - pdf = pd.read_parquet(io.BytesIO(r.content)) - mask = pdf["sso_name"] == pdf["sso_name"] - pdf = pdf[mask] - pdf = pdf[pdf["sso_name"].astype("str") == payload["sso_name"]] - return pdf - elif "sso_number" in payload: - pdf = pd.read_parquet(io.BytesIO(r.content)) - mask = pdf["sso_number"] == pdf["sso_number"] - pdf = pdf[mask] - pdf = pdf[pdf["sso_number"].astype("int") == int(payload["sso_number"])] - return pdf - - # return blob - return io.BytesIO(r.content) - - -def return_resolver_pdf(payload: dict) -> pd.DataFrame: - """Extract data returned by HBase and format it in a Pandas dataframe - - Data is from /api/v1/resolver - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/resolver - - Return - ---------- - out: pandas dataframe - """ - resolver = payload["resolver"] - name = payload["name"] - if "nmax" in payload: - nmax = payload["nmax"] - else: - nmax = 10 - - reverse = False - if "reverse" in payload: - if payload["reverse"] is True: - reverse = True - - if resolver == "tns": - client = connect_to_hbase_table("ztf.tns_resolver") - client.setLimit(nmax) - if name == "": - # return the full table - results = client.scan( - "", - "", - "*", - 0, - False, - False, - ) - elif reverse: - # Prefix search on second part of the key which is `fullname_internalname` - to_evaluate = f"key:key:_{name}:substring" - results = client.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - else: - # indices are case-insensitive - to_evaluate = f"key:key:{name.lower()}" - results = client.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - - # Restore default limits - client.close() - - pdfs = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - elif resolver == "simbad": - client = connect_to_hbase_table("ztf") - if reverse: - to_evaluate = f"key:key:{name}" - client.setLimit(nmax) - results = client.scan( - "", - to_evaluate, - "i:objectId,d:cdsxmatch,i:ra,i:dec,i:candid,i:jd", - 0, - False, - False, - ) - client.close() - pdfs = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - else: - r = requests.get( - f"http://cds.unistra.fr/cgi-bin/nph-sesame/-oxp/~S?{name}", - ) - - check = pd.read_xml(io.BytesIO(r.content)) - if "Resolver" in check.columns: - pdfs = pd.read_xml(io.BytesIO(r.content), xpath=".//Resolver") - else: - pdfs = pd.DataFrame() - elif resolver == "ssodnet": - if reverse: - # ZTF alerts -> ssnmanenr - client = connect_to_hbase_table("ztf") - to_evaluate = f"key:key:{name}" - client.setLimit(nmax) - results = client.scan( - "", - to_evaluate, - "i:objectId,i:ssnamenr", - 0, - False, - False, - ) - client.close() - pdfs = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - - # ssnmanenr -> MPC name & number - if not pdfs.empty: - client = connect_to_hbase_table("ztf.sso_resolver") - ssnamenrs = np.unique(pdfs["i:ssnamenr"].to_numpy()) - results = {} - for ssnamenr in ssnamenrs: - result = client.scan( - "", - f"i:ssnamenr:{ssnamenr}:exact", - "i:number,i:name,i:ssnamenr", - 0, - False, - False, - ) - results.update(result) - client.close() - pdfs = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - else: - # MPC -> ssnamenr - # keys follow the pattern - - client = connect_to_hbase_table("ztf.sso_resolver") - - if nmax == 1: - # Prefix with internal marker - to_evaluate = f"key:key:{name.lower()}-" - elif nmax > 1: - # This enables e.g. autocompletion tasks - client.setLimit(nmax) - to_evaluate = f"key:key:{name.lower()}" - - results = client.scan( - "", - to_evaluate, - "i:ssnamenr,i:name,i:number", - 0, - False, - False, - ) - client.close() - pdfs = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - - return pdfs - - -def upload_euclid_data(payload: dict) -> pd.DataFrame: - """Upload Euclid data - - Data is from /api/v1/euclidin - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/euclidin - - Return - ---------- - out: pandas dataframe - """ - # Interpret user input - data = payload["payload"] - pipeline_name = payload["pipeline"].lower() - - # Read data into pandas DataFrame - pdf = pd.read_csv(io.BytesIO(eval(data)), header=0, sep=" ", index_col=False) - - # Add Fink defined columns - pdf = add_columns( - pdf, - pipeline_name, - payload["version"], - payload["date"], - payload["EID"], - ) - - # Load official headers for HBase - header = load_euclid_header(pipeline_name) - euclid_header = header.keys() - - msg = check_header(pdf, list(euclid_header)) - if msg != "ok": - return Response(msg, 400) - - # Push data in the HBase table - mode = payload.get("mode", "production") - if mode == "production": - table = "euclid.in" - elif mode == "sandbox": - table = "euclid.test" - client = connect_to_hbase_table(table, schema_name=f"schema_{pipeline_name}") - - for index, row in pdf.iterrows(): - # Compute the row key - rowkey = compute_rowkey(row, index) - - # Compute the payload - out = [f"d:{name}:{value}" for name, value in row.items()] - - client.put( - rowkey, - out, - ) - client.close() - - return Response( - "{} - {} - {} - {} - Uploaded!".format( - payload["EID"], - payload["pipeline"], - payload["version"], - payload["date"], - ), - 200, - ) - - -def download_euclid_data(payload: dict) -> pd.DataFrame: - """Download Euclid data - - Data is from /api/v1/eucliddata - - Parameters - ---------- - payload: dict - See https://fink-portal.org/api/v1/eucliddata - - Return - ---------- - out: pandas dataframe - """ - # Interpret user input - pipeline = payload["pipeline"].lower() - - if "columns" in payload: - cols = payload["columns"].replace(" ", "") - else: - cols = "*" - - # Push data in the HBase table - mode = payload.get("mode", "production") - if mode == "production": - table = "euclid.in" - elif mode == "sandbox": - table = "euclid.test" - - client = connect_to_hbase_table(table, schema_name=f"schema_{pipeline}") - - # TODO: put a regex instead? - if ":" in payload["dates"]: - start, stop = payload["dates"].split(":") - to_evaluate = f"key:key:{pipeline}_{start},key:key:{pipeline}_{stop}" - client.setRangeScan(True) - elif payload["dates"].replace(" ", "") == "*": - to_evaluate = f"key:key:{pipeline}" - else: - start = payload["dates"] - to_evaluate = f"key:key:{pipeline}_{start}" - - results = client.scan( - "", - to_evaluate, - cols, - 0, - False, - False, - ) - - pdf = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - - # Remove hbase specific fields - if "key:key" in pdf.columns: - pdf = pdf.drop(columns=["key:key"]) - if "key:time" in pdf.columns: - pdf = pdf.drop(columns=["key:time"]) - - # Type conversion - schema = client.schema() - for col in pdf.columns: - pdf[col] = convert_datatype( - pdf[col], - hbase_type_converter[schema.type(col)], - ) - - client.close() - - return pdf - - -def post_metadata(payload: dict) -> Response: - """Upload metadata in Fink""" - client = connect_to_hbase_table("ztf.metadata") - encoded = payload["internal_name"].replace(" ", "") - client.put( - payload["objectId"].strip(), - [ - "d:internal_name:{}".format(payload["internal_name"]), - f"d:internal_name_encoded:{encoded}", - "d:comments:{}".format(payload["comments"]), - "d:username:{}".format(payload["username"]), - ], - ) - client.close() - - return Response( - "Thanks {} - You can visit {}/{}".format( - payload["username"], - APIURL, - encoded, - ), - 200, - ) - - -def retrieve_metadata(objectId: str) -> pd.DataFrame: - """Retrieve metadata in Fink given a ZTF object ID""" - client = connect_to_hbase_table("ztf.metadata") - to_evaluate = f"key:key:{objectId}" - results = client.scan( - "", - to_evaluate, - "*", - 0, - False, - False, - ) - pdf = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - client.close() - return pdf - - -def retrieve_oid(metaname: str, field: str) -> pd.DataFrame: - """Retrieve a ZTF object ID given metadata in Fink""" - client = connect_to_hbase_table("ztf.metadata") - to_evaluate = f"d:{field}:{metaname}:exact" - results = client.scan( - "", - to_evaluate, - "*", - 0, - True, - True, - ) - pdf = pd.DataFrame.from_dict(hbase_to_dict(results), orient="index") - client.close() - - return pdf diff --git a/apps/cards.py b/apps/cards.py index 231c8aaf..6ae03f81 100644 --- a/apps/cards.py +++ b/apps/cards.py @@ -24,7 +24,7 @@ from dash_iconify import DashIconify from fink_utils.photometry.utils import is_source_behind -from app import APIURL, app +from app import app from apps.plotting import all_radio_options from apps.utils import ( class_colors, @@ -36,6 +36,11 @@ simbad_types, ) +from apps.utils import extract_configuration + +args = extract_configuration("config.yml") +APIURL = args["APIURL"] + lc_help = r""" ##### Difference magnitude diff --git a/apps/client.py b/apps/client.py deleted file mode 100644 index 1f2efcca..00000000 --- a/apps/client.py +++ /dev/null @@ -1,155 +0,0 @@ -# Copyright 2023 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import os - -import jpype -import jpype.imports -import numpy as np -import yaml - -from apps import __file__ as apps_loc - - -def initialise_jvm(path=None): - """Start a JVM - - Parameters - ---------- - path: str, optional - Path to the HBase client. Default is relative to apps/ - """ - if not jpype.isJVMStarted(): - if path is None: - path = os.path.dirname(apps_loc) + "/../bin/FinkBrowser.exe.jar" - jarpath = f"-Djava.class.path={path}" - jpype.startJVM(jpype.getDefaultJVMPath(), "-ea", jarpath, convertStrings=True) - - jpype.attachThreadToJVM() - - -def connect_to_hbase_table( - tablename: str, - schema_name=None, - nlimit=10000, - setphysicalrepo=False, - config_path=None, -): - """Return a client connected to a HBase table - - Parameters - ---------- - tablename: str - The name of the table - schema_name: str, optional - Name of the rowkey in the table containing the schema. Default is given by the config file. - nlimit: int, optional - Maximum number of objects to return. Default is 10000 - setphysicalrepo: bool, optional - If True, store cutouts queried on disk ("/tmp/Lomikel/HBaseClientBinaryDataRepository") - Needs client 02.01+. Default is False - config_path: str, optional - Path to the config file. Default is None (relative to the apps/ folder) - """ - initialise_jvm() - - if config_path is None: - config_path = os.path.dirname(apps_loc) + "/../config.yml" - args = yaml.load( - open(config_path), - yaml.Loader, - ) - - import com.Lomikel.HBaser - from com.astrolabsoftware.FinkBrowser.Utils import Init - - Init.init() - - client = com.Lomikel.HBaser.HBaseClient(args["HBASEIP"], args["ZOOPORT"]) - - if schema_name is None: - schema_name = args["SCHEMAVER"] - client.connect(tablename, schema_name) - if setphysicalrepo: - import com.Lomikel.HBaser.FilesBinaryDataRepository - - client.setRepository(com.Lomikel.HBaser.FilesBinaryDataRepository()) - client.setLimit(nlimit) - - return client - - -def create_or_update_hbase_table( - tablename: str, - families: list, - schema_name: str, - schema: dict, - create=False, - config_path=None, -): - """Create or update a table in HBase - - By default (create=False), it will only update the schema of the table - otherwise it will create the table in HBase and push the schema. The schema - has a rowkey `schema`. - - Currently accepts only a single family name - - Parameters - ---------- - tablename: str - The name of the table - families: list - List of family names, e.g. ['d'] - schema_name: str - Rowkey value for the schema - schema: dict - Dictionary with column names (keys) and column types (values) - create: bool - If true, create the table. Default is False (only update schema) - config_path: str, optional - Path to the config file. Default is None (relative to the apps/ folder) - """ - if len(np.unique(families)) != 1: - raise NotImplementedError("`create_hbase_table` only accepts one family name") - - initialise_jvm() - - if config_path is None: - config_path = os.path.dirname(apps_loc) + "/../config.yml" - args = yaml.load( - open(config_path), - yaml.Loader, - ) - - import com.Lomikel.HBaser - from com.astrolabsoftware.FinkBrowser.Utils import Init - - Init.init() - - client = com.Lomikel.HBaser.HBaseClient(args["HBASEIP"], args["ZOOPORT"]) - - if create: - # Create the table and connect without schema - client.create(tablename, families) - client.connect(tablename) - else: - # Connect by ignoring the current schema - client.connect(tablename, None) - - # Push the schema - out = [f"{families[0]}:{colname}:{coltype}" for colname, coltype in schema.items()] - client.put(schema_name, out) - - client.close() diff --git a/apps/gw.py b/apps/gw.py index 8d857de8..f094ed32 100644 --- a/apps/gw.py +++ b/apps/gw.py @@ -32,7 +32,7 @@ from dash_iconify import DashIconify from mocpy import MOC -from app import APIURL, app +from app import app from apps.utils import ( class_colors, convert_jd, @@ -40,9 +40,14 @@ markdownify_objectid, request_api, simbad_types, + extract_configuration, ) +args = extract_configuration("config.yml") +APIURL = args["APIURL"] + + def extract_moc(fn, credible_level): """ """ payload = urlopen(fn).read() @@ -125,7 +130,7 @@ def query_bayestar(submit, credible_level, superevent_name, searchurl): return "error" pdf = request_api( - "/api/v1/bayestar", + "/api/v1/skymap", json={ "bayestar": str(data), "credible_level": float(credible_level), diff --git a/apps/query_cluster.py b/apps/query_cluster.py index f26a9325..f3bec24a 100644 --- a/apps/query_cluster.py +++ b/apps/query_cluster.py @@ -26,7 +26,7 @@ from dash_iconify import DashIconify from fink_utils.xmatch.simbad import get_simbad_labels -from app import APIURL, app +from app import app from apps.mining.utils import ( estimate_size_gb_elasticc, estimate_size_gb_ztf, @@ -34,6 +34,10 @@ upload_file_hdfs, ) from apps.utils import request_api +from apps.utils import extract_configuration + +args = extract_configuration("config.yml") +APIURL = args["APIURL"] simbad_types = get_simbad_labels("old_and_new") simbad_types = sorted(simbad_types, key=lambda s: s.lower()) @@ -253,7 +257,7 @@ def display_filter_tab(trans_datasource): description = [ "One condition per line (SQL syntax), ending with semi-colon. See ", dmc.Anchor( - "here", href=f"{APIURL}/api/v1/columns", size="xs", target="_blank" + "here", href=f"{APIURL}/api/v1/schema", size="xs", target="_blank" ), " (and also ", dmc.Anchor( diff --git a/apps/sso/cards.py b/apps/sso/cards.py index 2e4fdce4..d6307974 100644 --- a/apps/sso/cards.py +++ b/apps/sso/cards.py @@ -20,10 +20,15 @@ from dash import Input, Output, dcc, html from dash_iconify import DashIconify -from app import APIURL, app +from app import app from apps.utils import convert_mpc_type, help_popover, query_mpc from astropy.time import Time +from apps.utils import extract_configuration + +args = extract_configuration("config.yml") +APIURL = args["APIURL"] + AU_TO_M = 149597870700 diff --git a/apps/sso/utils.py b/apps/sso/utils.py index 5d316438..43f7041d 100644 --- a/apps/sso/utils.py +++ b/apps/sso/utils.py @@ -33,7 +33,7 @@ def resolve_sso_name_to_ssnamenr(sso_name): """ # search all ssnamenr corresponding quaero -> ssnamenr r = requests.post( - "https://fink-portal.org/api/v1/resolver", + "https://api.fink-portal.org/api/v1/resolver", json={"resolver": "ssodnet", "name": sso_name, "nmax": 1}, ) if r.status_code != 200: diff --git a/apps/statistics.py b/apps/statistics.py index 598b0f35..42f0713d 100644 --- a/apps/statistics.py +++ b/apps/statistics.py @@ -83,12 +83,13 @@ you can do all of these yourself using the REST API. Here is an example using Python: ```python +import io import requests import pandas as pd # get stats for all the year 2021 r = requests.post( - 'https://fink-portal.org/api/v1/statistics', + 'https://api.fink-portal.org/api/v1/statistics', json={{ 'date': '2021', 'output-format': 'json' @@ -96,7 +97,7 @@ ) # Format output in a DataFrame -pdf = pd.read_json(r.content) +pdf = pd.read_json(io.BytesIO(r.content)) ``` Note `date` can be either a given night (YYYYMMDD), month (YYYYMM), year (YYYY), or eveything (empty string). @@ -365,6 +366,7 @@ def generate_col_list(): "/api/v1/statistics", json={ "output-format": "json", + "date": "", "schema": True, }, ) diff --git a/apps/summary.py b/apps/summary.py index f0d7ac6b..92b499d8 100644 --- a/apps/summary.py +++ b/apps/summary.py @@ -683,7 +683,7 @@ def store_release_photometry(n_clicks, object_data): ], ) def make_qrcode(path): - qrdata = f"https://fink-portal.org/{path[1:]}" + qrdata = f"https://api.fink-portal.org/{path[1:]}" qrimg = generate_qr(qrdata) return html.Img(src="data:image/png;base64, " + pil_to_b64(qrimg)) diff --git a/apps/utils.py b/apps/utils.py index 3b31621c..8c6e6e2d 100644 --- a/apps/utils.py +++ b/apps/utils.py @@ -13,6 +13,7 @@ # See the License for the specific language governing permissions and # limitations under the License. import base64 +import yaml import gzip import io @@ -34,18 +35,13 @@ from qrcode.image.styledpil import StyledPilImage from qrcode.image.styles.moduledrawers import RoundedModuleDrawer -import apps.api -from app import APIURL, LOCALAPI, server - # TODO: split these UI snippets into separate file?.. import dash_bootstrap_components as dbc import dash_mantine_components as dmc from dash import html # Access local or remove API endpoint -from json import loads as json_loads -from flask import Response simbad_types = get_simbad_labels("old_and_new") simbad_types = sorted(simbad_types, key=lambda s: s.lower()) @@ -871,58 +867,31 @@ def get_first_value(pdf, colname, default=None): def request_api(endpoint, json=None, output="pandas", method="POST", **kwargs): """Output is one of 'pandas' (default), 'raw' or 'json'""" - if LOCALAPI: - # Use local API - urls = server.url_map.bind("") - func_name = urls.match(endpoint, method) - if len(func_name) == 2 and func_name[0].startswith("api."): - func = getattr(apps.api.api, func_name[0].split(".")[1]) - - if method == "GET": - # No args?.. - res = func() - else: - res = func(json) - if isinstance(res, Response): - if res.direct_passthrough: - res.make_sequence() - result = res.get_data() - else: - result = res - - if output == "json": - return json_loads(result) - elif output == "raw": - return result - else: - return pd.read_json(result, **kwargs) - else: - return None - else: - # Use remote API - if method == "POST": - r = requests.post( - f"{APIURL}{endpoint}", - json=json, - ) - elif method == "GET": - # No args?.. - r = requests.get( - f"{APIURL}{endpoint}", - ) + args = extract_configuration("config.yml") + APIURL = args["APIURL"] + if method == "POST": + r = requests.post( + f"{APIURL}{endpoint}", + json=json, + ) + elif method == "GET": + # No args?.. + r = requests.get( + f"{APIURL}{endpoint}", + ) - if output == "json": - if r.status_code != 200: - return [] - return r.json() - elif output == "raw": - if r.status_code != 200: - return io.BytesIO() - return io.BytesIO(r.content) - else: - if r.status_code != 200: - return pd.DataFrame() - return pd.read_json(io.BytesIO(r.content), **kwargs) + if output == "json": + if r.status_code != 200: + return [] + return r.json() + elif output == "raw": + if r.status_code != 200: + return io.BytesIO() + return io.BytesIO(r.content) + else: + if r.status_code != 200: + return pd.DataFrame() + return pd.read_json(io.BytesIO(r.content), **kwargs) def loading(item): @@ -1146,3 +1115,24 @@ def create_button_for_external_conesearch( ) return button + + +def extract_configuration(filename): + """Extract user defined configuration + + Parameters + ---------- + filename: str + Full path to the `config.yml` file. + + Returns + ------- + out: dict + Dictionary with user defined values. + """ + config = yaml.load(open("config.yml"), yaml.Loader) + if config["HOST"].endswith(".org"): + config["SITEURL"] = "https://" + config["HOST"] + else: + config["SITEURL"] = "http://" + config["HOST"] + ":" + str(config["PORT"]) + return config diff --git a/assets/spark_ztf_transfer.py b/assets/spark_ztf_transfer.py index 774f0584..5261c780 100644 --- a/assets/spark_ztf_transfer.py +++ b/assets/spark_ztf_transfer.py @@ -294,7 +294,7 @@ def check_path_exist(dateToCheck): out: bool """ r = requests.post( - 'https://fink-portal.org/api/v1/statistics', + 'https://api.fink-portal.org/api/v1/statistics', json={ 'date': '{}{}{}'.format(*dateToCheck.split('-')), 'columns': 'basic:sci', diff --git a/config.yml b/config.yml index 264e9dd5..0955f011 100644 --- a/config.yml +++ b/config.yml @@ -1,7 +1,3 @@ -APIURL: http://localhost -IP: http://localhost +APIURL: https://api.fink-portal.org +HOST: localhost PORT: 24000 -HBASEIP: localhost -ZOOPORT: 2181 -SCHEMAVER: schema_2.2_2.0.0 -tablename: test_sp diff --git a/index.py b/index.py index 3721a3ac..26a17e15 100644 --- a/index.py +++ b/index.py @@ -37,10 +37,8 @@ from app import server from app import app -from app import APIURL from apps import summary, about, statistics, query_cluster, gw -from apps.api import api from apps.utils import markdownify_objectid, class_colors, simbad_types from apps.utils import isoify_time @@ -48,6 +46,7 @@ from apps.utils import retrieve_oid_from_metaname from apps.utils import help_popover from apps.utils import request_api +from apps.utils import extract_configuration from apps.plotting import draw_cutouts_quickview, draw_lightcurve_preview from apps.cards import card_search_result from apps.parse import parse_query @@ -57,6 +56,8 @@ import urllib +config_args = extract_configuration("config.yml") + tns_types = pd.read_csv("assets/tns_types.csv", header=None)[0].to_numpy() tns_types = sorted(tns_types, key=lambda s: s.lower()) @@ -196,10 +197,10 @@ - i:ndethist: Number of spatially coincident detections falling within 1.5 arcsec going back to the beginning of the survey; only detections that fell on the same field and readout-channel ID where the input candidate was observed are counted. All raw detections down to a photometric S/N of ~ 3 are included. - v:lapse: number of days between the first and last spatially coincident detections. -You can also add more columns using the dropdown button above the result table. Full documentation of all available fields can be found at {}/api/v1/columns. +You can also add more columns using the dropdown button above the result table. Full documentation of all available fields can be found at {}/api/v1/schema. The button `Sky Map` will open a popup with embedded Aladin sky map showing the positions of the search results on the sky. -""".format(APIURL) +""".format(config_args["APIURL"]) # Smart search field quick_fields = [ @@ -636,7 +637,7 @@ def display_table_results(table): 2. Table of results The dropdown is shown only if the table is non-empty. """ - pdf = request_api("/api/v1/columns", method="GET") + pdf = request_api("/api/v1/schema", method="GET") fink_fields = [ "d:" + i for i in pdf.loc["Fink science module outputs (d:)"]["fields"].keys() @@ -825,7 +826,9 @@ def display_skymap(data, columns, is_open): link = '{}' titles = [ link.format( - APIURL, i.split("]")[0].split("[")[1], i.split("]")[0].split("[")[1] + config_args["SITEURL"], + i.split("]")[0].split("[")[1], + i.split("]")[0].split("[")[1], ) for i in pdf["i:objectId"].to_numpy() ] @@ -1991,8 +1994,6 @@ def display_page(pathname, searchurl): ) if pathname == "/about": return about.layout, "home" - elif pathname == "/api": - return api.layout(), "home" elif pathname == "/stats": return statistics.layout(), "home_light" elif pathname == "/download": @@ -2010,18 +2011,8 @@ def display_page(pathname, searchurl): return layout, "home" -# register the API -try: - from apps.api.api import api_bp - - server.register_blueprint(api_bp, url_prefix="/") - server.config["JSONIFY_PRETTYPRINT_REGULAR"] = True - server.config["JSON_SORT_KEYS"] = False -except ImportError: - print("API not yet registered") +server.config["JSONIFY_PRETTYPRINT_REGULAR"] = True +server.config["JSON_SORT_KEYS"] = False if __name__ == "__main__": - import yaml - - input_args = yaml.load(open("config.yml"), yaml.Loader) - app.run_server(input_args["IP"], debug=True, port=input_args["PORT"]) + app.run_server(config_args["HOST"], debug=True, port=config_args["PORT"]) diff --git a/tests/api_anomaly_test.py b/tests/api_anomaly_test.py deleted file mode 100644 index 5ad3df39..00000000 --- a/tests/api_anomaly_test.py +++ /dev/null @@ -1,168 +0,0 @@ -# Copyright 2023 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -from astropy.io import votable - -import io -import sys -import json - -APIURL = sys.argv[1] - - -def anomalysearch( - n=10, start_date=None, stop_date=None, output_format="json", cols=None -): - """Perform a search for anomaly""" - payload = {"n": n, "output-format": output_format} - - if start_date is not None: - payload.update({"start_date": start_date, "stop_date": stop_date}) - - if cols is not None: - payload.update({"columns": cols}) - - r = requests.post("{}/api/v1/anomaly".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - elif output_format == "votable": - vt = votable.parse(io.BytesIO(r.content)) - pdf = vt.get_first_table().to_table().to_pandas() - - return pdf - - -def test_simple_anomaly() -> None: - """ - Examples - -------- - >>> test_simple_anomaly() - """ - pdf = anomalysearch() - - assert not pdf.empty - - assert len(pdf) == 10, len(pdf) - - assert np.all(pdf["d:anomaly_score"].to_numpy() < 0) - - -def test_anomaly_and_date() -> None: - """ - Examples - -------- - >>> test_anomaly_and_date() - """ - pdf = anomalysearch(start_date="2023-01-25", stop_date="2023-01-25") - - assert not pdf.empty - - assert len(pdf) == 10, len(pdf) - - assert "ZTF23aaaatwl" in pdf["i:objectId"].to_numpy() - - -def test_anomaly_and_cols_with_sort() -> None: - """ - Examples - -------- - >>> test_anomaly_and_cols_with_sort() - """ - pdf = anomalysearch(cols="i:jd,i:objectId") - - assert not pdf.empty - - assert len(pdf.columns) == 2, len(pdf.columns) - - assert "i:jd" in pdf.columns - assert "i:objectId" in pdf.columns - assert "v:classifation" not in pdf.columns - - -def test_query_url() -> None: - """ - Examples - -------- - >>> test_query_url() - """ - pdf1 = anomalysearch() - - url = "{}/api/v1/anomaly?n=10&output-format=json".format(APIURL) - r = requests.get(url) - pdf2 = pd.read_json(io.BytesIO(r.content)) - - # subset of cols to avoid type issues - cols = ["d:anomaly_score"] - - isclose = np.isclose(pdf1[cols], pdf2[cols]) - assert np.all(isclose) - - -def test_various_outputs() -> None: - """ - Examples - -------- - >>> test_various_outputs() - """ - pdf1 = anomalysearch(output_format="json") - - for fmt in ["csv", "parquet", "votable"]: - pdf2 = anomalysearch(output_format=fmt) - - # subset of cols to avoid type issues - cols1 = ["d:anomaly_score"] - - # https://docs.astropy.org/en/stable/io/votable/api_exceptions.html#w02-x-attribute-y-is-invalid-must-be-a-standard-xml-id - cols2 = cols1 if fmt != "votable" else ["d_anomaly_score"] - - isclose = np.isclose(pdf1[cols1], pdf2[cols2]) - assert np.all(isclose), fmt - - -def test_feature_array() -> None: - """ - Examples - -------- - >>> test_feature_array() - """ - pdf = anomalysearch() - - a_feature = pdf["d:lc_features_g"].to_numpy()[0] - assert isinstance(a_feature, str), a_feature - - for col in ["d:lc_features_g", "d:lc_features_r"]: - pdf[col] = pdf[col].apply(lambda x: json.loads(x)) - - a_feature = pdf["d:lc_features_g"].to_numpy()[0] - assert isinstance(a_feature, list), a_feature - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_bayestar_test.py b/tests/api_bayestar_test.py deleted file mode 100644 index 5f30dd39..00000000 --- a/tests/api_bayestar_test.py +++ /dev/null @@ -1,88 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - -import io -import sys - -APIURL = sys.argv[1] - - -def bayestartest( - bayestar="bayestar.fits.gz", event_name="", credible_level=0.1, output_format="json" -): - """Perform a GW search in the Science Portal using the Fink REST API""" - if event_name != "": - payload = { - "event_name": event_name, - "credible_level": credible_level, - "output-format": output_format, - } - else: - data = open(bayestar, "rb").read() - payload = { - "bayestar": str(data), - "credible_level": credible_level, - "output-format": output_format, - } - - r = requests.post("{}/api/v1/bayestar".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - pdf = pd.read_json(io.BytesIO(r.content)) - - return pdf - - -def test_bayestar() -> None: - """ - Examples - -------- - >>> test_bayestar() - """ - pdf = bayestartest() - - assert len(pdf) == 14, len(pdf) - - a = ( - pdf.groupby("d:classification") - .count() - .sort_values("i:objectId", ascending=False)["i:objectId"] - .to_dict() - ) - - assert a["Unknown"] == 4, a - - -def test_name_bayestar() -> None: - """ - Examples - -------- - >>> test_name_bayestar() - """ - pdf1 = bayestartest(event_name="S200219ac") - pdf2 = bayestartest() - - assert pdf1.equals(pdf2) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_classsearch_test.py b/tests/api_classsearch_test.py deleted file mode 100644 index 2675e527..00000000 --- a/tests/api_classsearch_test.py +++ /dev/null @@ -1,210 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -from astropy.io import votable - -import io -import sys - -APIURL = sys.argv[1] - - -def classsearch( - myclass="Early SN Ia candidate", - n=10, - startdate=None, - stopdate=None, - output_format="json", - cols=None, -): - """Perform a class search in the Science Portal using the Fink REST API""" - payload = {"class": myclass, "n": n, "output-format": output_format} - - if startdate is not None: - payload.update({"startdate": startdate, "stopdate": stopdate}) - - if cols is not None: - payload.update({"columns": cols}) - - r = requests.post("{}/api/v1/latests".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - elif output_format == "votable": - vt = votable.parse(io.BytesIO(r.content)) - pdf = vt.get_first_table().to_table().to_pandas() - - return pdf - - -def test_simple_classsearch() -> None: - """ - Examples - -------- - >>> test_simple_classsearch() - """ - pdf = classsearch() - - assert not pdf.empty - - assert len(pdf) == 10, len(pdf) - - assert np.all(pdf["v:classification"].to_numpy() == "Early SN Ia candidate") - - -def test_simbad_classsearch() -> None: - """ - Examples - -------- - >>> test_simbad_classsearch() - """ - pdf = classsearch(myclass="(SIMBAD) QSO") - - assert not pdf.empty - - assert len(pdf) == 10, len(pdf) - - assert np.all(pdf["v:classification"].to_numpy() == "QSO") - - -# def test_tns_classsearch() -> None: -# """ -# Examples -# --------- -# >>> test_tns_classsearch() -# """ -# pdf = classsearch(myclass='(TNS) SN Ia', n=100) -# -# assert not pdf.empty -# -# # 9 instead of 10 because we group by objectId, -# # and among the 10 first alerts, there are 2 with the same objectId -# assert len(pdf) == 9, len(pdf) -# -# # print(pdf['i:fid'].to_numpy()) -# assert np.all(pdf['i:fid'].to_numpy() > 0) - - -def test_classsearch_and_date() -> None: - """ - Examples - -------- - >>> test_classsearch_and_date() - """ - pdf = classsearch(startdate="2021-11-01", stopdate="2021-12-01") - - assert not pdf.empty - - assert len(pdf) == 10, len(pdf) - - assert np.all(pdf["v:classification"].to_numpy() == "Early SN Ia candidate") - - assert np.all(pdf["v:lastdate"].to_numpy() < "2021-12-01") - - assert np.all(pdf["v:lastdate"].to_numpy() >= "2021-11-01") - - -def test_classsearch_and_cols_with_sort() -> None: - """ - Examples - -------- - >>> test_classsearch_and_cols_with_sort() - """ - pdf = classsearch(cols="i:jd,i:objectId") - - assert not pdf.empty - - assert len(pdf.columns) == 2, len(pdf.columns) - - assert "i:jd" in pdf.columns - assert "i:objectId" in pdf.columns - assert "v:classifation" not in pdf.columns - - -def test_classsearch_and_cols_without_sort() -> None: - """ - Examples - -------- - >>> test_classsearch_and_cols_without_sort() - """ - pdf = classsearch(cols="i:objectId") - - assert not pdf.empty - - assert len(pdf.columns) == 1, len(pdf.columns) - - assert "i:objectId" in pdf.columns - - -def test_query_url() -> None: - """ - Examples - -------- - >>> test_query_url() - """ - pdf1 = classsearch() - - url = ( - "{}/api/v1/latests?class=Early SN Ia candidate&n=10&output-format=json".format( - APIURL - ) - ) - r = requests.get(url) - pdf2 = pd.read_json(io.BytesIO(r.content)) - - # subset of cols to avoid type issues - cols = ["i:ra", "i:dec"] - - isclose = np.isclose(pdf1[cols], pdf2[cols]) - assert np.all(isclose) - - -def test_various_outputs() -> None: - """ - Examples - -------- - >>> test_various_outputs() - """ - pdf1 = classsearch(output_format="json") - - for fmt in ["csv", "parquet", "votable"]: - pdf2 = classsearch(output_format=fmt) - - # subset of cols to avoid type issues - cols1 = ["i:ra", "i:dec"] - - # https://docs.astropy.org/en/stable/io/votable/api_exceptions.html#w02-x-attribute-y-is-invalid-must-be-a-standard-xml-id - cols2 = cols1 if fmt != "votable" else ["i_ra", "i_dec"] - - isclose = np.isclose(pdf1[cols1], pdf2[cols2]) - assert np.all(isclose), fmt - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_columns_test.py b/tests/api_columns_test.py deleted file mode 100644 index d32ea7b2..00000000 --- a/tests/api_columns_test.py +++ /dev/null @@ -1,219 +0,0 @@ -# Copyright 2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - -import io -import sys - -APIURL = sys.argv[1] - - -def get_fields_per_family(): - """Get fields exposed in /api/v1/columns""" - r = requests.get("{}/api/v1/columns".format(APIURL)) - - assert r.status_code == 200, r.content - - schema = r.json() - - categories = schema["fields"].keys() - - dic = {} - for i in ["i:", "d:", "b:", "v:"]: - for category in categories: - if i in category: - dic[i] = list(schema["fields"][category].keys()) - - return dic - - -def check_recent_columns(columns, objectId): - """Check the alert columns correspond to what is defined in /api/v1/columns""" - fields_per_family = get_fields_per_family() - - for family in fields_per_family.keys(): - definition = fields_per_family[family] - obtained = [ - i.split(family)[1] - for i in columns - if i.startswith(family) and ("t2_" not in i) - ] - - outside_obtained = [i for i in definition if i not in obtained] - assert len(outside_obtained) == 0, ( - "Not in obtained fields", - family, - outside_obtained, - objectId, - ) - - # `spicy_name` was introduced by mistake instead of `spicy_class` for 2024/02/01 - outside_definition = [ - i for i in obtained if (i not in definition) and (i != "spicy_name") - ] - assert len(outside_definition) == 0, ( - "Not in defined fields", - family, - outside_definition, - objectId, - ) - - -def check_old_columns(columns, objectId): - """Check the alert columns correspond to what is defined in /api/v1/columns""" - fields_per_family = get_fields_per_family() - - for family in fields_per_family.keys(): - definition = fields_per_family[family] - obtained = [ - i.split(family)[1] - for i in columns - if i.startswith(family) and ("t2_" not in i) - ] - - # Only d: has changed - if family != "d:": - outside_obtained = [i for i in definition if i not in obtained] - assert len(outside_obtained) == 0, ( - "Not in obtained fields", - family, - outside_obtained, - objectId, - ) - - # `spicy_name` was introduced by mistake instead of `spicy_class` for 2024/02/01 - outside_definition = [ - i for i in obtained if (i not in definition) and (i != "spicy_name") - ] - assert len(outside_definition) == 0, ( - "Not in defined fields", - family, - outside_definition, - objectId, - ) - else: - recent_cols = [ - "DR3Name", - "Plx", - "anomaly_score", - "delta_time", - "e_Plx", - "from_upper", - "gcvs", - "jd_first_real_det", - "jdstarthist_dt", - "lc_features_g", - "lc_features_r", - "lower_rate", - "mag_rate", - "mangrove_2MASS_name", - "mangrove_HyperLEDA_name", - "mangrove_ang_dist", - "mangrove_lum_dist", - "sigma_rate", - "spicy_class", - "spicy_id", - "upper_rate", - "vsx", - "x3hsp", - "x4lac", - ] - - outside_obtained = [i for i in definition if i not in obtained] - outside_obtained_ = [i for i in outside_obtained if i not in recent_cols] - assert len(outside_obtained_) == 0, ( - "Not in obtained fields", - family, - outside_obtained_, - objectId, - ) - - # `spicy_name` was introduced by mistake instead of `spicy_class` for 2024/02/01 - outside_definition = [ - i for i in obtained if (i not in definition) and (i != "spicy_name") - ] - assert len(outside_definition) == 0, ( - "Not in defined fields", - family, - outside_definition, - objectId, - ) - - -def test_recent_object() -> None: - """Supposed to fail if apps/api/api.py@columns_arguments is not updated correctly - - Examples - -------- - >>> test_recent_object() - """ - r = requests.post( - "{}/api/v1/latests".format(APIURL), - json={"class": "EB*", "n": 1, "columns": "i:objectId"}, - ) - - assert r.status_code == 200, r.content - - objectId = r.json()[0]["i:objectId"] - r2 = requests.post( - "{}/api/v1/objects".format(APIURL), - json={ - "objectId": objectId, - "columns": "*", - "output-format": "json", - "withupperlim": True, - "withcutouts": True, - }, - ) - - assert r2.status_code == 200, r2.content - - pdf = pd.read_json(io.BytesIO(r2.content)) - - check_recent_columns(pdf.columns, objectId) - - -def test_old_object() -> None: - """ - Examples - -------- - >>> test_old_object() - """ - objectId = "ZTF21abfmbix" - r = requests.post( - "{}/api/v1/objects".format(APIURL), - json={ - "objectId": objectId, - "columns": "*", - "output-format": "json", - "withupperlim": True, - "withcutouts": True, - }, - ) - - assert r.status_code == 200, r.content - - pdf = pd.read_json(io.BytesIO(r.content)) - - check_old_columns(pdf.columns, objectId) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_conesearch_test.py b/tests/api_conesearch_test.py deleted file mode 100644 index 5aa417a1..00000000 --- a/tests/api_conesearch_test.py +++ /dev/null @@ -1,211 +0,0 @@ -# Copyright 2022-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -from astropy.coordinates import SkyCoord -from astropy.io import votable - -import io -import sys - -APIURL = sys.argv[1] - - -def conesearch( - ra="193.8217409", - dec="2.8973184", - radius="5", - startdate=None, - window=None, - output_format="json", -): - """Perform a conesearch in the Science Portal using the Fink REST API""" - payload = {"ra": ra, "dec": dec, "radius": radius, "output-format": output_format} - - if startdate is not None: - payload.update({"startdate": startdate, "window": window}) - - r = requests.post("{}/api/v1/conesearch".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - elif output_format == "votable": - vt = votable.parse(io.BytesIO(r.content)) - pdf = vt.get_first_table().to_table().to_pandas() - - return pdf - - -def test_simple_conesearch() -> None: - """ - Examples - -------- - >>> test_simple_conesearch() - """ - ra0 = 193.8217 - dec0 = 2.897 - radius = 5 - - pdf = conesearch(ra=ra0, dec=dec0, radius=radius) - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 1 - - # Check the candidate is found no further away than the radius - coord0 = SkyCoord(ra0, dec0, unit="deg") - coord1 = SkyCoord(pdf["i:ra"].to_numpy()[0], pdf["i:dec"].to_numpy()[0], unit="deg") - - sep = coord0.separation(coord1).degree * 3600 - - assert sep <= 5, sep - - -def test_conesearch_with_dates() -> None: - """ - Examples - -------- - >>> test_conesearch_with_dates() - """ - # at this date, one object - pdf1 = conesearch( - ra="175.3242473", - dec="36.5429392", - radius="5", - startdate="2021-11-03 10:00:00", - window="1", - ) - - # at this date, a new object appeared - pdf2 = conesearch( - ra="175.3242473", - dec="36.5429392", - radius="5", - startdate="2021-11-05 10:00:00", - window="1", - ) - - assert pdf1.empty - assert not pdf2.empty - - # One object found - assert len(pdf2) == 1 - - -def test_bad_radius_conesearch() -> None: - """ - Examples - -------- - >>> test_bad_radius_conesearch() - """ - payload = { - "ra": "175.3242473", - "dec": "36.5429392", - "radius": 36000, - "output_format": "json", - } - - r = requests.post("{}/api/v1/conesearch".format(APIURL), json=payload) - - msg = { - "status": "error", - "text": "`radius` cannot be bigger than 18,000 arcseconds (5 degrees).\n", - } - assert r.text == str(msg) - - -def test_empty_conesearch() -> None: - """ - Examples - -------- - >>> test_empty_conesearch() - """ - pdf = conesearch(ra=0, dec=0, radius=1) - - assert pdf.empty - - -def test_coordinates() -> None: - """ - Examples - -------- - >>> test_coordinates() - """ - pdf1 = conesearch(ra=193.822, dec=2.89732) - pdf2 = conesearch(ra="193d49m18.267s", dec="2d53m50.35s") - pdf3 = conesearch(ra="12h55m17.218s", dec="+02d53m50.35s") - pdf4 = conesearch(ra="12 55 17.218", dec="+02 53 50.35") - pdf5 = conesearch(ra="12:55:17.218", dec="02:53:50.35") - - magpsf = pdf1["i:magpsf"].to_numpy() - for pdf in [pdf2, pdf3, pdf4, pdf5]: - assert np.all(pdf["i:magpsf"].to_numpy() == magpsf) - - -def test_bad_request() -> None: - """ - Examples - -------- - >>> test_bad_request() - """ - payload = {"ra": "kfdlkj", "dec": "lkfdjf", "radius": 5, "output_format": "json"} - - r = requests.post("{}/api/v1/conesearch".format(APIURL), json=payload) - - msg = { - "status": "error", - "text": ValueError("Invalid character at col 0 in angle 'kfdlkj'"), - } - assert r.text == str(msg), r.text - - -def test_various_outputs() -> None: - """ - Examples - -------- - >>> test_various_outputs() - """ - pdf1 = conesearch(output_format="json") - - for fmt in ["csv", "parquet", "votable"]: - pdf2 = conesearch(output_format=fmt) - - # subset of cols to avoid type issues - cols1 = ["i:ra", "i:dec"] - - # https://docs.astropy.org/en/stable/io/votable/api_exceptions.html#w02-x-attribute-y-is-invalid-must-be-a-standard-xml-id - cols2 = cols1 if fmt != "votable" else ["i_ra", "i_dec"] - - isclose = np.isclose(pdf1[cols1], pdf2[cols2]) - assert np.all(isclose), fmt - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_cutouts_test.py b/tests/api_cutouts_test.py deleted file mode 100644 index 8cf4aae4..00000000 --- a/tests/api_cutouts_test.py +++ /dev/null @@ -1,196 +0,0 @@ -# Copyright 2022-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import numpy as np - -from astropy.io import fits - -from PIL import Image - -import io -import sys - -APIURL = sys.argv[1] - - -def cutouttest( - objectId="ZTF21aaxtctv", - kind="Science", - stretch="sigmoid", - colormap="viridis", - pmin=0.5, - pmax=99.5, - convolution_kernel=None, - output_format="PNG", - candid=None, -): - """Perform a cutout search in the Science Portal using the Fink REST API""" - payload = { - "objectId": objectId, - "kind": kind, # Science, Template, Difference - "stretch": stretch, # sigmoid[default], linear, sqrt, power, log, asinh - "colormap": colormap, # Valid matplotlib colormap name (see matplotlib.cm). Default is grayscale. - "pmin": pmin, # The percentile value used to determine the pixel value of minimum cut level. Default is 0.5. No effect for sigmoid. - "pmax": pmax, # The percentile value used to determine the pixel value of maximum cut level. Default is 99.5. No effect for sigmoid. - "output-format": output_format, - } - - if candid is not None: - payload.update({"candid": candid}) - - # Convolve the image with a kernel (gauss or box). Default is None (not specified). - if convolution_kernel is not None: - payload.update({"convolution_kernel": convolution_kernel}) - - r = requests.post("{}/api/v1/cutouts".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "PNG": - # Format output in a DataFrame - data = Image.open(io.BytesIO(r.content)) - elif output_format == "FITS": - data = fits.open(io.BytesIO(r.content), ignore_missing_simple=True) - elif output_format == "array": - data = r.json()["b:cutout{}_stampData".format(kind)] - - return data - - -def test_png_cutout() -> None: - """ - Examples - -------- - >>> test_png_cutout() - """ - data = cutouttest() - - assert data.format == "PNG" - assert data.size == (63, 63) - - -def test_fits_cutout() -> None: - """ - Examples - -------- - >>> test_fits_cutout() - """ - data = cutouttest(output_format="FITS") - - assert len(data) == 1 - assert np.shape(data[0].data) == (63, 63) - - -def test_array_cutout() -> None: - """ - Examples - -------- - >>> test_array_cutout() - """ - data = cutouttest(output_format="array") - - assert np.shape(data) == (63, 63), data - assert isinstance(data, list) - - -def test_kind_cutout() -> None: - """ - Examples - -------- - >>> test_kind_cutout() - """ - data1 = cutouttest(kind="Science", output_format="array") - data2 = cutouttest(kind="Template", output_format="array") - data3 = cutouttest(kind="Difference", output_format="array") - - assert data1 != data2 - assert data2 != data3 - - -def test_pvalues_cutout() -> None: - """ - Examples - -------- - >>> test_pvalues_cutout() - """ - # pmin and pmax have no effect if stretch = sigmoid - data1 = cutouttest() - data2 = cutouttest(pmin=0.1, pmax=0.5) - - assert data1.getextrema() == data2.getextrema() - - # pmin and pmax have an effect otherwise - data1 = cutouttest() - data2 = cutouttest(pmin=0.1, pmax=0.5, stretch="linear") - - assert data1.getextrema() != data2.getextrema() - - -def test_stretch_cutout() -> None: - """ - Examples - -------- - >>> test_stretch_cutout() - """ - # pmin and pmax have no effect if stretch = sigmoid - data1 = cutouttest(stretch="sigmoid") - - for stretch in ["linear", "sqrt", "power", "log"]: - data2 = cutouttest(stretch=stretch) - assert data1.getextrema() != data2.getextrema() - - -def test_colormap_cutout() -> None: - """ - Examples - -------- - >>> test_colormap_cutout() - """ - data1 = cutouttest() - data2 = cutouttest(colormap="Greys") - - assert data1.getextrema() != data2.getextrema() - - -def test_convolution_kernel_cutout() -> None: - """ - Examples - -------- - >>> test_convolution_kernel_cutout() - """ - data1 = cutouttest() - data2 = cutouttest(convolution_kernel="gauss") - - assert data1.getextrema() != data2.getextrema() - - -def test_candid_cutout() -> None: - """ - Examples - -------- - >>> test_candid_cutout() - """ - data1 = cutouttest() - data2 = cutouttest(candid="1622215345315015012") - - assert data1.getextrema() != data2.getextrema() - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_datesearch_test.py b/tests/api_datesearch_test.py deleted file mode 100644 index ff5c9a4e..00000000 --- a/tests/api_datesearch_test.py +++ /dev/null @@ -1,80 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -import io -import sys - -APIURL = sys.argv[1] - - -def datesearch( - startdate="2021-07-01 05:59:37.000", window=1 / 24 / 60, output_format="json" -): - """Perform a date search in the Science Portal using the Fink REST API""" - payload = {"startdate": startdate, "window": window, "output-format": output_format} - - r = requests.post("{}/api/v1/explorer".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_simple_datesearch() -> None: - """ - Examples - -------- - >>> test_simple_datesearch() - """ - pdf = datesearch() - - assert not pdf.empty - - assert len(pdf) == 407, len(pdf) - - assert (np.max(pdf["i:jd"]) - np.min(pdf["i:jd"])) <= 1 - - -def test_bad_datesearch() -> None: - """ - Examples - -------- - >>> test_bad_datesearch() - """ - pdf1 = datesearch("2021-07-01 05:59:37.000", window=3 / 24) - - # The window is rounded to 3 hours so results should be equal - pdf2 = datesearch("2021-07-01 05:59:37.000", window=1) - - assert len(pdf1) == len(pdf2), "{} != {}".format(len(pdf1), len(pdf2)) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_euclidsso_test.py b/tests/api_euclidsso_test.py deleted file mode 100644 index 9c69a4dc..00000000 --- a/tests/api_euclidsso_test.py +++ /dev/null @@ -1,150 +0,0 @@ -# Copyright 2023 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - - -import io -import sys - -APIURL = sys.argv[1] - - -def push_euclid(fn="old_ssopipe.txt"): - """Push Euclid SSO data""" - data = open(fn, "rb").read() - - r = requests.post( - "{}/api/v1/euclidin".format(APIURL), - json={ - "EID": "6565656", - "pipeline": "ssopipe", - "version": "1.0", - "date": "19881103", - "payload": str(data), - "mode": "sandbox", - }, - ) - - assert r.status_code == 200, r.content - - return r.content - - -def pull_euclid( - pipeline="ssopipe", dates="20210101", columns="*", output_format="json" -): - """Pull Euclid data""" - payload = { - "pipeline": pipeline, - "dates": dates, - "columns": columns, - "mode": "sandbox", - "output-format": output_format, - } - - r = requests.post("{}/api/v1/eucliddata".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_euclid_push() -> None: - """ - Examples - -------- - >>> test_euclid_push() - """ - msg = push_euclid() - - # Not empty - assert msg == b"6565656 - ssopipe - 1.0 - 19881103 - Uploaded!", msg - - -def test_euclid_single_date() -> None: - """ - Examples - -------- - >>> test_euclid_single_date() - """ - pdf = pull_euclid(dates="20210101") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 2798, len(pdf) - - -def test_euclid_range_date() -> None: - """ - Examples - -------- - >>> test_euclid_range_date() - """ - pdf = pull_euclid(dates="20210101:20210102") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 2798, len(pdf) - - -def test_euclid_all_date() -> None: - """ - Examples - -------- - >>> test_euclid_all_date() - """ - pdf = pull_euclid(dates="*") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 2798, len(pdf) - - -def test_euclid_columns() -> None: - """ - Examples - -------- - >>> test_euclid_columns() - """ - pdf = pull_euclid(dates="20210101", columns="d:INDEX") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf.columns) == 1, pdf.columns - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_performance_test.py b/tests/api_performance_test.py deleted file mode 100644 index 2dad5669..00000000 --- a/tests/api_performance_test.py +++ /dev/null @@ -1,80 +0,0 @@ -# Copyright 2022-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import time - -import io -import sys - -APIURL = sys.argv[1] - - -def classsearch( - myclass="Solar System MPC", - n=100000, - startdate="2022-03-03", - stopdate="2022-03-04", - output_format="json", - columns="*", -): - """Perform a heavy class search in the Science Portal using the Fink REST API""" - payload = { - "class": myclass, - "n": n, - "columns": columns, - "output-format": output_format, - } - - if startdate is not None: - payload.update({"startdate": startdate, "stopdate": stopdate}) - - r = requests.post("{}/api/v1/latests".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_heavy_classsearch() -> None: - """ - Examples - -------- - >>> test_heavy_classsearch() - """ - t0 = time.time() - classsearch(columns="i:objectId,i:magpsf,i:jd,d:rf_snia_vs_nonia") - dt = time.time() - t0 - - # less than 45 seconds to get 21,000 objects - assert dt < 45, "Spent {} seconds in querying for MPC objects -- too long!".format( - dt - ) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_random_object_test.py b/tests/api_random_object_test.py deleted file mode 100644 index 8ef911b9..00000000 --- a/tests/api_random_object_test.py +++ /dev/null @@ -1,129 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -import io -import sys - -APIURL = sys.argv[1] - - -def get_an_object( - number=1, output_format="json", columns="*", object_class="", seed=None -): - """Query an object from the Science Portal using the Fink REST API""" - payload = { - "n": number, - "columns": columns, - "output-format": output_format, - } - - if object_class != "": - payload.update({"class": object_class}) - - if seed is not None: - payload.update({"seed": int(seed)}) - - r = requests.post("{}/api/v1/random".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_single_object() -> None: - """ - Examples - -------- - >>> test_single_object() - """ - pdf = get_an_object(number=1) - - assert not pdf.empty - - -def test_multiple_objects() -> None: - """ - Examples - -------- - >>> test_multiple_objects() - """ - pdf = get_an_object(number=3) - nobjects = len(pdf.groupby("i:objectId").count()) - - assert nobjects == 3, nobjects - - -def test_seed() -> None: - """ - Examples - -------- - >>> test_seed() - """ - pdf1 = get_an_object(number=1, seed=54859) - pdf2 = get_an_object(number=1, seed=54859) - - oid1 = np.unique(pdf1["i:objectId"].to_numpy()) - oid2 = np.unique(pdf2["i:objectId"].to_numpy()) - - assert oid1 == oid2 - - pdf1 = get_an_object(number=1) - pdf2 = get_an_object(number=1) - - oid1 = np.unique(pdf1["i:objectId"].to_numpy()) - oid2 = np.unique(pdf2["i:objectId"].to_numpy()) - - assert oid1 != oid2 - - -def test_column_selection() -> None: - """ - Examples - -------- - >>> test_column_selection() - """ - pdf = get_an_object(number=1, columns="i:jd,i:magpsf") - - assert len(pdf.columns) == 2, "I count {} columns".format(len(pdf.columns)) - - -def test_class() -> None: - """ - Examples - -------- - >>> test_class() - """ - pdf = get_an_object(number=3, object_class="Solar System MPC") - - assert np.all([i == "Solar System MPC" for i in pdf["v:classification"].to_numpy()]) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_resolver_test.py b/tests/api_resolver_test.py deleted file mode 100644 index a3ff8bbb..00000000 --- a/tests/api_resolver_test.py +++ /dev/null @@ -1,258 +0,0 @@ -# Copyright 2023 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - -from astropy.io import votable - -import io -import sys - -APIURL = sys.argv[1] - - -def resolver(resolver="", name="", nmax=None, reverse=None, output_format="json"): - """Perform a conesearch in the Science Portal using the Fink REST API""" - payload = {"resolver": resolver, "name": name, "output-format": output_format} - - if reverse is not None: - payload.update( - { - "reverse": True, - } - ) - - if nmax is not None: - payload.update( - { - "nmax": nmax, - } - ) - - r = requests.post("{}/api/v1/resolver".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - elif output_format == "votable": - vt = votable.parse(io.BytesIO(r.content)) - pdf = vt.get_first_table().to_table().to_pandas() - - return pdf - - -def test_tns_fulltable() -> None: - """ - Examples - -------- - >>> test_tns_fulltable() - """ - pdf = resolver(resolver="tns", name="", nmax=100000) - - # Not empty - assert not pdf.empty - - # More than the default 10,000 limitation - assert len(pdf) > 10000 - - -def test_tns_resolver() -> None: - """ - Examples - -------- - >>> test_tns_resolver() - """ - pdf = resolver(resolver="tns", name="SN 2023") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 10 - - cols = [ - "d:declination", - "d:fullname", - "d:internalname", - "d:ra", - "d:type", - "d:redshift", - ] - for col in cols: - assert col in pdf.columns, col - - -def test_tns_lower_case() -> None: - """ - Examples - -------- - >>> test_tns_lower_case() - """ - pdf = resolver(resolver="tns", name="sn 2023") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 10 - - -def test_reverse_tns_resolver() -> None: - """ - Examples - -------- - >>> test_reverse_tns_resolver() - """ - pdf = resolver(resolver="tns", name="ZTF23aaaahln", reverse=True) - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 1 - - assert pdf["d:fullname"].to_numpy()[0] == "SN 2023Q", pdf.columns - - -def test_nmax() -> None: - """ - Examples - -------- - >>> test_nmax() - """ - pdf = resolver(resolver="tns", name="SN 2023", nmax=20) - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 20 - - -def test_simbad_resolver() -> None: - """ - Examples - -------- - >>> test_simbad_resolver() - """ - pdf = resolver(resolver="simbad", name="Markarian 2") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 1 - - assert pdf["oname"].to_numpy()[0].replace(" ", "") == "Mrk2", pdf[ - "oname" - ].to_numpy()[0] - - cols = [ - "name", - "oid", - "oname", - "otype", - "jpos", - "jradeg", - "jdedeg", - "refPos", - "MType", - "nrefs", - ] - for col in cols: - assert col in pdf.columns, [col, pdf.columns] - - -def test_reverse_simbad_resolver() -> None: - """ - Examples - -------- - >>> test_reverse_simbad_resolver() - """ - pdf = resolver(resolver="simbad", name="ZTF18aabfjoi", reverse=True) - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 5, len(pdf) - - assert pdf["d:cdsxmatch"].to_numpy()[0] == "GinGroup", pdf["d:cdsxmatch"].to_numpy() - - -def test_ssodnet_resolver() -> None: - """ - Examples - -------- - >>> test_ssodnet_resolver() - """ - pdf = resolver(resolver="ssodnet", name="624188") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 4, pdf - - assert "2002MA06" in pdf["i:ssnamenr"].to_numpy(), pdf - - -def test_ssodnet_lower_case() -> None: - """ - Examples - -------- - >>> test_ssodnet_lower_case() - """ - pdf = resolver(resolver="ssodnet", name="julienpeloton") - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 1, pdf - - assert "Julienpeloton" in pdf["i:name"].to_numpy(), pdf - - -def test_reverse_ssodnet_resolver() -> None: - """ - Examples - -------- - >>> test_reverse_ssodnet_resolver() - """ - pdf = resolver(resolver="ssodnet", name="ZTF23aabccya", reverse=True) - - # Not empty - assert not pdf.empty - - # One object found - assert len(pdf) == 3, len(pdf) - - assert "Julienpeloton" in pdf["i:name"].to_numpy(), pdf - assert 33803 in pdf["i:number"].to_numpy(), pdf - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_single_object_test.py b/tests/api_single_object_test.py deleted file mode 100644 index 480481fd..00000000 --- a/tests/api_single_object_test.py +++ /dev/null @@ -1,224 +0,0 @@ -# Copyright 2022-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -import io -import sys - -APIURL = sys.argv[1] - -# Implement random name generator -OID = "ZTF21abfmbix" - - -def get_an_object( - oid="ZTF21abfmbix", - output_format="json", - columns="*", - withupperlim=False, - withcutouts=False, - cutout_kind=None, -): - """Query an object from the Science Portal using the Fink REST API""" - payload = { - "objectId": oid, - "columns": columns, - "output-format": output_format, - "withupperlim": withupperlim, - "withcutouts": withcutouts, - } - - if cutout_kind is not None: - payload.update({"cutout-kind": cutout_kind}) - - r = requests.post("{}/api/v1/objects".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_single_object() -> None: - """ - Examples - -------- - >>> test_single_object() - """ - pdf = get_an_object(oid=OID) - - assert not pdf.empty - - -def test_single_object_csv() -> None: - """ - Examples - -------- - >>> test_single_object_csv() - """ - pdf = get_an_object(oid=OID, output_format="csv") - - assert not pdf.empty - - -def test_single_object_parquet() -> None: - """ - Examples - -------- - >>> test_single_object_parquet() - """ - pdf = get_an_object(oid=OID, output_format="parquet") - - assert not pdf.empty - - -def test_column_selection() -> None: - """ - Examples - -------- - >>> test_column_selection() - """ - pdf = get_an_object(oid=OID, columns="i:jd,i:magpsf") - - assert len(pdf.columns) == 2, "I count {} columns".format(len(pdf.columns)) - - -def test_column_length() -> None: - """ - Examples - -------- - >>> test_column_length() - """ - pdf = get_an_object(oid=OID) - - assert len(pdf.columns) == 129, "I count {} columns".format(len(pdf.columns)) - - -def test_withupperlim() -> None: - """ - Examples - -------- - >>> test_withupperlim() - """ - pdf = get_an_object(oid=OID, withupperlim=True) - assert "d:tag" in pdf.columns - - -def test_withcutouts() -> None: - """ - Examples - -------- - >>> test_withcutouts() - """ - pdf = get_an_object(oid=OID, withcutouts=True) - - assert isinstance(pdf["b:cutoutScience_stampData"].to_numpy()[0], list) - assert isinstance(pdf["b:cutoutTemplate_stampData"].to_numpy()[0], list) - assert isinstance(pdf["b:cutoutDifference_stampData"].to_numpy()[0], list) - - -def test_withcutouts_single_field() -> None: - """ - Examples - -------- - >>> test_withcutouts_single_field() - """ - pdf = get_an_object(oid=OID, withcutouts=True, cutout_kind="Science") - - assert isinstance(pdf["b:cutoutScience_stampData"].to_numpy()[0], list) - assert "b:cutoutTemplate_stampData" not in pdf.columns - - -def test_formatting() -> None: - """ - Examples - -------- - >>> test_formatting() - """ - pdf = get_an_object(oid=OID) - - # stupid python cast... - assert isinstance(pdf["i:fid"].to_numpy()[0], np.int64), type( - pdf["i:fid"].to_numpy()[0] - ) - assert isinstance(pdf["i:magpsf"].to_numpy()[0], np.double), type( - pdf["i:magpsf"].to_numpy()[0] - ) - - -def test_misc() -> None: - """ - Examples - -------- - >>> test_misc() - """ - pdf = get_an_object(oid=OID) - assert np.all(pdf["i:fid"].to_numpy() > 0) - assert np.all(pdf["i:magpsf"].to_numpy() > 6) - - -def test_bad_request() -> None: - """ - Examples - -------- - >>> test_bad_request() - """ - pdf = get_an_object(oid="ldfksjflkdsjf") - - assert pdf.empty - - -def test_multiple_objects() -> None: - """ - Examples - -------- - >>> test_multiple_objects() - """ - OIDS_ = ["ZTF21abfmbix", "ZTF21aaxtctv", "ZTF21abfaohe"] - OIDS = ",".join(OIDS_) - pdf = get_an_object(oid=OIDS) - - n_oids = len(np.unique(pdf.groupby("i:objectId").count()["i:ra"])) - assert n_oids == 3 - - n_oids_single = 0 - len_object = 0 - for oid in OIDS_: - pdf_ = get_an_object(oid=oid) - n_oid = len(np.unique(pdf_.groupby("i:objectId").count()["i:ra"])) - n_oids_single += n_oid - len_object += len(pdf_) - - assert n_oids == n_oids_single, "{} is not equal to {}".format( - n_oids, n_oids_single - ) - assert len_object == len(pdf), "{} is not equal to {}".format(len_object, len(pdf)) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_sso_test.py b/tests/api_sso_test.py deleted file mode 100644 index 8b380f91..00000000 --- a/tests/api_sso_test.py +++ /dev/null @@ -1,263 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -import io -import sys - -APIURL = sys.argv[1] - - -def ssosearch( - n_or_d="8467", - withEphem=False, - withCutouts=False, - withResiduals=False, - cutout_kind=None, - columns="*", - output_format="json", - expected_status=200, -): - """Perform a sso search in the Science Portal using the Fink REST API""" - payload = { - "n_or_d": n_or_d, - "withEphem": withEphem, - "withcutouts": withCutouts, - "withResiduals": withResiduals, - "columns": columns, - "output-format": output_format, - } - - if cutout_kind is not None: - payload.update({"cutout-kind": cutout_kind}) - - r = requests.post("{}/api/v1/sso".format(APIURL), json=payload) - - assert r.status_code == expected_status, r.content - - if r.status_code == 200: - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - else: - pdf = pd.DataFrame() - - return pdf - - -def test_simple_ssosearch() -> None: - """ - Examples - -------- - >>> test_simple_ssosearch() - """ - pdf = ssosearch() - - assert not pdf.empty - - assert np.all(pdf["i:ssnamenr"].to_numpy() > 0) - - assert np.all(pdf["d:roid"].to_numpy() == 3) - - assert len(pdf.groupby("i:ssnamenr").count()) == 1 - - -def test_ephem() -> None: - """ - Examples - -------- - >>> test_ephem() - """ - names = [ - "8467", - "BenoitCarry", - "JulienPeloton", - "Phaethon", - 3200, - "Lucretia", - 269, - 323137, - ] - for name in names: - pdf = ssosearch(n_or_d=name, withEphem=True) - - assert not pdf.empty - - assert "Phase" in pdf.columns - - assert "SDSS:g" in pdf.columns - - -def test_residuals() -> None: - """ - Examples - -------- - >>> test_residuals() - """ - pdf = ssosearch(withResiduals=True) - - assert not pdf.empty - - assert "residuals_shg1g2" in pdf.columns, list(pdf.columns) - - pdf = ssosearch("33803,8467", withResiduals=True, expected_status=400) - - assert pdf.empty - - pdf = ssosearch("323137", withResiduals=True) - - assert not pdf.empty - - assert np.isnan(pdf["residuals_shg1g2"].to_numpy()[0]) - - -def test_comet() -> None: - """ - Examples - -------- - >>> test_comet() - """ - pdf = ssosearch(n_or_d="10P", withEphem=True) - - assert not pdf.empty - - assert "Phase" in pdf.columns - - assert "SDSS:g" not in pdf.columns - - -def test_temp_designation() -> None: - """ - Examples - -------- - >>> test_temp_designation() - """ - pdf_ephem = ssosearch(n_or_d="2010 JO69", withEphem=True) - - assert not pdf_ephem.empty - - assert "Phase" in pdf_ephem.columns - - assert "SDSS:g" in pdf_ephem.columns - - -def test_multiple_sso_names() -> None: - """ - Examples - -------- - >>> test_multiple_sso_names() - """ - pdf = ssosearch(n_or_d="624188") - - assert len(pdf["sso_name"].unique()) == 1, pdf["sso_name"].unique() - assert len(pdf["i:ssnamenr"].unique()) == 3, pdf["i:ssnamenr"].unique() - - # however we do not want Rubin & Rubincam - pdf = ssosearch(n_or_d="Rubin") - - assert len(pdf["sso_name"].unique()) == 1, pdf["sso_name"].unique() - assert len(pdf["i:ssnamenr"].unique()) == 1, pdf["i:ssnamenr"].unique() - - -def test_bad_request() -> None: - """ - Examples - -------- - >>> test_bad_request() - """ - pdf = ssosearch(n_or_d="kdflsjffld", expected_status=400) - - assert pdf.empty - - -def test_multiple_ssosearch() -> None: - """ - Examples - -------- - >>> test_multiple_ssosearch() - """ - pdf = ssosearch(n_or_d="8467,10P") - - assert not pdf.empty - - assert len(pdf.groupby("i:ssnamenr").count()) == 2 - - assert len(pdf.groupby("sso_name").count()) == 2 - - -def test_with_ephem_multiple_ssosearch() -> None: - """ - Examples - -------- - >>> test_with_ephem_multiple_ssosearch() - """ - pdf = ssosearch(n_or_d="8467,1922", withEphem=True) - - assert len(pdf.groupby("i:ssnamenr").count()) == 2 - assert len(pdf.groupby("sso_name").count()) == 2 - assert len(pdf.groupby("sso_number").count()) == 2 - - assert 8467 in np.unique(pdf["i:ssnamenr"].to_numpy()) - assert 1922 in np.unique(pdf["i:ssnamenr"].to_numpy()) - - pdf1 = ssosearch(n_or_d="8467", withEphem=True) - pdf2 = ssosearch(n_or_d="1922", withEphem=True) - - assert len(pdf) == len(pdf1) + len(pdf2) - - m1 = pdf["i:ssnamenr"] == 8467 - assert len(pdf[m1].to_numpy()) == len(pdf1.to_numpy()), ( - pdf[m1].to_numpy(), - pdf1.to_numpy(), - ) - - m2 = pdf["i:ssnamenr"] == 1922 - assert len(pdf[m2].to_numpy()) == len(pdf2.to_numpy()), ( - pdf[m2].to_numpy(), - pdf2.to_numpy(), - ) - - -def test_withcutouts() -> None: - """ - Examples - -------- - >>> test_withcutouts() - """ - pdf = ssosearch(withCutouts=True) - - assert "b:cutoutScience_stampData" in pdf.columns - assert isinstance(pdf["b:cutoutScience_stampData"].to_numpy()[0], list), pdf[ - "b:cutoutScience_stampData" - ] - - pdf = ssosearch(withCutouts=True, cutout_kind="Template") - - assert "b:cutoutTemplate_stampData" in pdf.columns - assert isinstance(pdf["b:cutoutTemplate_stampData"].to_numpy()[0], list) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_ssocand_test.py b/tests/api_ssocand_test.py deleted file mode 100644 index accb29b7..00000000 --- a/tests/api_ssocand_test.py +++ /dev/null @@ -1,140 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -from astropy.time import Time - -import io -import sys - -APIURL = sys.argv[1] - - -def ssocandsearch( - kind="orbParams", - trajectory_id=None, - start_date=None, - stop_date=None, - maxnumber=None, - output_format="json", -): - """Perform a sso candidate search in the Science Portal using the Fink REST API""" - payload = {"kind": kind, "output-format": output_format} - - if trajectory_id is not None: - payload.update({"ssoCandId": trajectory_id}) - if start_date is not None: - payload.update({"start_date": start_date}) - if stop_date is not None: - payload.update({"stop_date": stop_date}) - if maxnumber is not None: - payload.update({"maxnumber": maxnumber}) - - r = requests.post("{}/api/v1/ssocand".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_orbparam() -> None: - """ - Examples - -------- - >>> test_orbparam() - """ - pdf = ssocandsearch() - - assert not pdf.empty - - assert len(pdf) >= 327 - - assert "d:a" in pdf.columns - - -def test_lightcurves() -> None: - """ - Examples - -------- - >>> test_lightcurves() - """ - pdf = ssocandsearch(kind="lightcurves") - - assert not pdf.empty - - assert "d:magpsf" in pdf.columns - - -def test_lightcurves_max() -> None: - """ - Examples - -------- - >>> test_lightcurves_max() - """ - pdf = ssocandsearch(kind="lightcurves") - - assert len(pdf) == 10000, len(pdf) - - pdf2 = ssocandsearch(kind="lightcurves", maxnumber=20000) - - assert len(pdf2) > 10000, len(pdf2) - - -def test_lightcurves_traj() -> None: - """ - Examples - -------- - >>> test_lightcurves_traj() - """ - pdf = ssocandsearch(kind="lightcurves", trajectory_id="FF20230725aaaacgw") - - assert "d:ssoCandId" in pdf.columns - - nobjects = len(np.unique(pdf["d:ssoCandId"])) - assert nobjects == 1, "Expecting 1 object, but found {}".format(nobjects) - - -def test_time_boundaries() -> None: - """ - Examples - -------- - >>> test_time_boundaries() - """ - pdf = ssocandsearch( - kind="lightcurves", start_date="2023-01-01", stop_date="2023-12-31" - ) - - assert not pdf.empty - - assert np.all(pdf["d:jd"].to_numpy() >= Time("2023-01-01", format="iso").jd) - assert np.all(pdf["d:jd"].to_numpy() <= Time("2023-12-31", format="iso").jd) - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_ssoft_test.py b/tests/api_ssoft_test.py deleted file mode 100644 index 095e785c..00000000 --- a/tests/api_ssoft_test.py +++ /dev/null @@ -1,188 +0,0 @@ -# Copyright 2023-2024 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import datetime - -import pandas as pd - -import io -import sys - -APIURL = sys.argv[1] - - -def ssoftsearch( - version=None, - flavor=None, - sso_number=None, - sso_name=None, - schema=None, - output_format="parquet", -): - """Perform a sso search in the Science Portal using the Fink REST API""" - payload = {"output-format": output_format} - - if version is not None: - payload.update( - { - "version": version, - } - ) - - if flavor is not None: - payload.update( - { - "flavor": flavor, - } - ) - - if sso_number is not None: - payload.update( - { - "sso_number": sso_number, - } - ) - - if sso_name is not None: - payload.update( - { - "sso_name": sso_name, - } - ) - - if schema is not None: - payload.update( - { - "schema": True, - } - ) - - r = requests.post("{}/api/v1/ssoft".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def default_ssoft() -> None: - """ - Examples - -------- - >>> default_ssoft() - """ - pdf = ssoftsearch() - - assert not pdf.empty - - now = datetime.datetime.now() - current_date = "{}.{:02d}".format(now.year, now.month) - - assert pdf["version"].to_numpy()[0] == current_date - - assert "alpha0" in pdf.columns - - -def previous_ssoft() -> None: - """ - Examples - -------- - >>> previous_ssoft() - """ - pdf = ssoftsearch(version="2023.07") - - assert not pdf.empty - - -def test_ids() -> None: - """ - Examples - -------- - >>> test_ids() - """ - pdf = ssoftsearch(sso_number="33803") - - assert len(pdf) == 1 - - pdf = ssoftsearch(sso_name="Benoitcarry") - - assert len(pdf) == 1 - - -def test_schema() -> None: - """ - Examples - -------- - >>> test_schema() - """ - pdf = ssoftsearch(flavor="SHG1G2") - - schema = ssoftsearch(schema=True, flavor="SHG1G2", output_format="json") - - # check columns - not_in_pdf = [i for i in set(schema["args"].keys()) if i not in set(pdf.columns)] - not_in_schema = [i for i in set(pdf.columns) if i not in set(schema["args"].keys())] - - assert not_in_pdf == [], not_in_pdf - assert not_in_schema == [], not_in_schema - - msg = "Found {} entries in the DataFrame and {} entries in the schema.".format( - len(pdf.columns), len(schema) - ) - assert set(schema["args"].keys()) == set(pdf.columns), msg - - -def compare_schema() -> None: - """ - Examples - -------- - >>> compare_schema() - """ - schema1 = ssoftsearch(schema=True, flavor="SSHG1G2", output_format="json") - - # get the schema - r = requests.get("{}/api/v1/ssoft?schema&flavor=SSHG1G2".format(APIURL)) - schema2 = r.json() - - keys1 = set(schema1["args"].keys()) - keys2 = set(schema2["args"].keys()) - assert keys1 == keys2, [keys1, keys2] - - -def check_sshg1g2() -> None: - """ - Examples - -------- - >>> check_sshg1g2() - """ - pdf = ssoftsearch(flavor="SSHG1G2") - - assert "period" in pdf.columns - assert "a_b_00" in pdf.columns - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_stats_test.py b/tests/api_stats_test.py deleted file mode 100644 index 80fdefbd..00000000 --- a/tests/api_stats_test.py +++ /dev/null @@ -1,95 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - -import io -import sys - -APIURL = sys.argv[1] - - -def statstest(date="2021", columns="*", output_format="json"): - """Perform a stats search in the Science Portal using the Fink REST API""" - payload = { - "date": date, - "columns": columns, - "output-format": output_format, - } - - r = requests.post("{}/api/v1/statistics".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_stats() -> None: - """ - Examples - -------- - >>> test_stats() - """ - pdf = statstest() - - # Number of observation days in 2021 - assert len(pdf) == 254, len(pdf) - - -def test_a_day() -> None: - """ - Examples - -------- - >>> test_a_day() - """ - pdf = statstest(date="20211103") - - assert len(pdf) == 1 - - assert len(pdf.columns) == 131 - - assert "basic:sci" in pdf.columns - assert "basic:raw" in pdf.columns - - assert pdf["basic:raw"].to_numpy()[0] == 346644 - - -def test_cols() -> None: - """ - Examples - -------- - >>> test_cols() - """ - pdf = statstest(columns="basic:exposures,class:Solar System MPC") - - assert not pdf.empty - - assert len(pdf.columns) == 2 + 2, pdf.columns - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_tracklet_test.py b/tests/api_tracklet_test.py deleted file mode 100644 index 3da3289d..00000000 --- a/tests/api_tracklet_test.py +++ /dev/null @@ -1,91 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd -import numpy as np - -from astropy.time import Time - -import io -import sys - -APIURL = sys.argv[1] - - -def trackletsearch(date="2021-08-10", columns="*", output_format="json"): - """Perform a tracklet search in the Science Portal using the Fink REST API""" - payload = {"date": date, "columns": columns, "output-format": output_format} - - r = requests.post("{}/api/v1/tracklet".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - if output_format == "json": - # Format output in a DataFrame - pdf = pd.read_json(io.BytesIO(r.content)) - elif output_format == "csv": - pdf = pd.read_csv(io.BytesIO(r.content)) - elif output_format == "parquet": - pdf = pd.read_parquet(io.BytesIO(r.content)) - - return pdf - - -def test_simple_trackletsearch() -> None: - """ - Examples - -------- - >>> test_simple_trackletsearch() - """ - pdf = trackletsearch() - - assert not pdf.empty - - assert np.all(pdf["d:tracklet"].to_numpy() != "") - - assert np.all([i.startswith("TRCK") for i in pdf["d:tracklet"].to_numpy()]) - - -def test_fulldate() -> None: - """ - Examples - -------- - >>> test_fulldate() - """ - pdf = trackletsearch(date="2021-10-22 09:19:49") - jd0 = Time("2021-10-22 09:19:49").jd - - assert np.all( - [np.round(i, 3) == np.round(jd0, 3) for i in pdf["i:jd"].to_numpy()] - ), (jd0, pdf["i:jd"].to_numpy()) - - -def test_single_tracklet() -> None: - """ - Examples - -------- - >>> test_single_tracklet() - """ - pdf = trackletsearch(date="2021-10-22 09:19:49 00") - - assert np.all(pdf["d:tracklet"].to_numpy() == "TRCK_20211022_091949_00") - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/api_xmatch_test.py b/tests/api_xmatch_test.py deleted file mode 100644 index 9a5f671b..00000000 --- a/tests/api_xmatch_test.py +++ /dev/null @@ -1,61 +0,0 @@ -# Copyright 2022 AstroLab Software -# Author: Julien Peloton -# -# Licensed under the Apache License, Version 2.0 (the "License"); -# you may not use this file except in compliance with the License. -# You may obtain a copy of the License at -# -# http://www.apache.org/licenses/LICENSE-2.0 -# -# Unless required by applicable law or agreed to in writing, software -# distributed under the License is distributed on an "AS IS" BASIS, -# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -# See the License for the specific language governing permissions and -# limitations under the License. -import requests -import pandas as pd - -import io -import sys - -APIURL = sys.argv[1] - - -def xmatchtest(catalog="mycatalog.csv", header="RA,Dec,ID,Time", radius=1.5, window=7): - """Perform a xmatch search in the Science Portal using the Fink REST API""" - payload = { - "catalog": open(catalog).read(), - "header": header, - "radius": radius, # in arcsecond - "window": window, # in days - } - - r = requests.post("{}/api/v1/xmatch".format(APIURL), json=payload) - - assert r.status_code == 200, r.content - - pdf = pd.read_json(io.BytesIO(r.content)) - - return pdf - - -def test_xmatch() -> None: - """ - - Examples - -------- - >>> test_xmatch() - """ - pdf = xmatchtest() - - assert len(pdf) == 1, len(pdf) - - assert pdf["ID"].to_numpy()[0] == "AnObjectMatching" - - -if __name__ == "__main__": - """ Execute the test suite """ - import sys - import doctest - - sys.exit(doctest.testmod()[0]) diff --git a/tests/bayestar.fits.gz b/tests/bayestar.fits.gz deleted file mode 100644 index 5883adb1..00000000 Binary files a/tests/bayestar.fits.gz and /dev/null differ diff --git a/tests/mycatalog.csv b/tests/mycatalog.csv deleted file mode 100644 index 5ad1c932..00000000 --- a/tests/mycatalog.csv +++ /dev/null @@ -1,8 +0,0 @@ -ID,Time,RA,Dec,otherproperty -210430A,2021-04-30 10:42:10,57.185,45.080,toto -210422A,2021-04-22 17:47:10,21.077,42.100,tutu -210421B,2021-04-21 10:54:44,270.817,56.828,tutu -210421A,2021-04-21 00:27:30,104.882,4.928,toto -210420B,2021-04-20 18:34:37,254.313,42.558,foo -210419C,2021-04-19 23:27:49,212.969,36.011,bar -AnObjectMatching,2019-10-29 01:25:35.999,271.3914265,45.2545134,foo diff --git a/tests/old_ssopipe.txt b/tests/old_ssopipe.txt deleted file mode 100644 index cf4f2e7c..00000000 --- a/tests/old_ssopipe.txt +++ /dev/null @@ -1,2799 +0,0 @@ -INDEX RA DEC PROP_MOT N_DET CATALOG X_WORLD Y_WORLD ERRA_WORLD ERRB_WORLD FLUX_AUTO FLUXERR_AUTO MAG_AUTO MAGERR_AUTO ELONGATION ELLIPTICITY MJD -0 7.678199583795886 -21.23647516734966 4.078818560515706 4 D1_ObsId03_purged.txt 7.678199583795885 -21.236475167349656 3.265579380240524e-07 2.1048177245575062e-07 56860.0 281.6098327636719 19.262983322143555 0.005378618836402893 1.7200441360473633 0.4186195731163025 59215.25069444445 -1 7.6784768631923965 -21.236274746839204 4.078818560515706 4 D2_ObsId03_purged.txt 7.6784768631923965 -21.236274746839204 3.248530333621602e-07 2.090550452749085e-07 56539.71875 279.5437316894531 19.269115447998047 0.005369402468204497 1.7110624313354492 0.41556775569915766 59215.26265046285 -2 7.678761367062062 -21.23607344297273 4.078818560515706 4 D3_ObsId03_purged.txt 7.678761367062062 -21.23607344297273 3.254286298215448e-07 2.1164642305393497e-07 56069.78125 279.10595703125 19.278177261352536 0.005405925679951905 1.7230046987533567 0.419618546962738 59215.27460648171 -3 7.679028148833312 -21.23588301021517 4.078818560515706 4 D4_ObsId03_purged.txt 7.679028148833311 -21.23588301021517 3.344958088291605e-07 2.1292986218668375e-07 55827.58203125 278.3727111816406 19.28287696838379 0.00541511457413435 1.7233257293701172 0.41972666978836054 59215.2865625 -0 7.72277500199734 -21.22508377571373 9.592444438085035 4 D1_ObsId03_purged.txt 7.72277500199734 -21.22508377571373 7.56291342440818e-07 2.508659235900268e-07 47966.74609375 303.64654541015625 19.447649002075195 0.006874765735119581 3.9377629756927486 0.7460486888885498 59215.25069444445 -1 7.723292329851062 -21.22450802505028 9.592444438085035 4 D2_ObsId03_purged.txt 7.723292329851063 -21.22450802505028 7.530396146648856e-07 2.6435247946210444e-07 47759.1875 303.4143981933594 19.45235824584961 0.0068993642926216125 3.743240833282471 0.732851803302765 59215.26265046285 -2 7.723824518846129 -21.223909802426288 9.592444438085035 4 D3_ObsId03_purged.txt 7.723824518846129 -21.223909802426288 7.4595686783141e-07 2.527971787458228e-07 47952.10546875 302.31524658203125 19.447980880737305 0.006846714299172163 3.833229303359985 0.7391233444213867 59215.27460648171 -3 7.7243160924142495 -21.223300512202808 9.592444438085035 4 D4_ObsId03_purged.txt 7.7243160924142495 -21.223300512202808 7.815584126547037e-07 2.828581102676253e-07 47969.80859375 311.7782592773437 19.44758033752441 0.007058422546833754 3.6334786415100098 0.7247816324234008 59215.2865625 -0 7.700494104522271 -21.23755803842811 6.485048936440475 4 D1_ObsId03_purged.txt 7.700494104522271 -21.23755803842811 5.932541853326256e-07 3.594712723042904e-07 33360.87109375 251.42333984375 19.84190559387207 0.008184610866010189 2.721115827560425 0.6325036883354187 59215.25069444445 -1 7.699942612222969 -21.23751027086032 6.485048936440475 4 D2_ObsId03_purged.txt 7.699942612222969 -21.23751027086032 6.040582434252428e-07 3.789587879055034e-07 33727.203125 259.909912109375 19.830049514770508 0.008368976414203644 2.5898096561431885 0.6138712167739868 59215.26265046285 -2 7.699403396587267 -21.2374542294054 6.485048936440475 4 D3_ObsId03_purged.txt 7.699403396587267 -21.2374542294054 6.063671662559501e-07 3.719978280969372e-07 32724.45703125 258.8399353027344 19.862817764282223 0.00858991127461195 2.630627155303955 0.6198625564575195 59215.27460648171 -3 7.698836058456616 -21.237397741441413 6.485048936440475 4 D4_ObsId03_purged.txt 7.698836058456615 -21.23739774144141 6.054270897948301e-07 3.831785022612167e-07 33353.75 255.54327392578125 19.842138290405277 0.008320503868162632 2.5558857917785645 0.6087461709976196 59215.2865625 -0 7.718759919947623 -21.23013178339209 8.69029095469069 4 D1_ObsId03_purged.txt 7.7187599199476224 -21.23013178339209 5.387599912864971e-07 2.3168966833964083e-07 67559.9296875 332.06787109375 19.075777053833008 0.005337863694876432 3.19057846069336 0.6865772008895874 59215.25069444445 -1 7.719469949077177 -21.22993913661082 8.69029095469069 4 D2_ObsId03_purged.txt 7.719469949077178 -21.22993913661082 5.483889822244238e-07 2.2597109250455105e-07 67047.625 330.0729675292969 19.084041595458984 0.005346337798982859 3.261217832565308 0.6933660507202148 59215.26265046285 -2 7.720195318125986 -21.229725301090667 8.69029095469069 4 D3_ObsId03_purged.txt 7.7201953181259855 -21.229725301090667 5.462614467433013e-07 2.257212514678031e-07 66904.4765625 332.513427734375 19.086360931396484 0.005397390574216843 3.3016226291656494 0.6971186399459839 59215.27460648171 -3 7.720879638472521 -21.22950388074799 8.69029095469069 4 D4_ObsId03_purged.txt 7.720879638472522 -21.22950388074799 5.444895236905722e-07 2.3719607611383253e-07 67871.7109375 334.77542114257807 19.070777893066406 0.005356666166335344 3.1809864044189453 0.6856321096420288 59215.2865625 -0 7.717476890774319 -21.23144329741296 2.0424790741689702 4 D1_ObsId03_purged.txt 7.717476890774319 -21.23144329741296 2.654124386936019e-07 2.158739960123057e-07 45496.3125 244.25408935546875 19.505058288574215 0.005830361507833004 1.3870640993118286 0.2790527939796448 59215.25069444445 -1 7.717540905839686 -21.23130880760436 2.0424790741689702 4 D2_ObsId03_purged.txt 7.717540905839686 -21.23130880760436 2.80049818002226e-07 2.3504622959080734e-07 45678.86328125 245.1166534423828 19.50071144104004 0.005827568005770445 1.335694432258606 0.251325786113739 59215.26265046285 -2 7.717622381324198 -21.23115416737813 2.0424790741689702 4 D3_ObsId03_purged.txt 7.717622381324198 -21.231154167378126 2.7460021101433085e-07 2.281425537375981e-07 45434.50390625 243.7333221435547 19.506534576416012 0.005825845059007406 1.360180139541626 0.26480329036712646 59215.27460648171 -3 7.7176629486696 -21.230991019484367 2.0424790741689702 4 D4_ObsId03_purged.txt 7.717662948669599 -21.230991019484367 2.6566655719761917e-07 2.176367956963077e-07 45160.8828125 243.24011230468753 19.513093948364254 0.005849282722920179 1.354525804519653 0.2617343068122864 59215.2865625 -0 7.7134304979556925 -21.245446445905856 2.9511895417323037 3 D1_ObsId03_purged.txt 7.7134304979556925 -21.245446445905852 2.4533801479265094e-07 1.8159666126393859e-07 69981.484375 293.8099060058594 19.03754234313965 0.0045594568364322186 1.7070573568344116 0.41419661045074463 59215.25069444445 -1 7.7134051741590275 -21.24521519575755 2.9511895417323037 3 D2_ObsId03_purged.txt 7.7134051741590275 -21.24521519575755 2.549000441831595e-07 1.9058097677771002e-07 69975.40625 294.5832214355469 19.037635803222656 0.0045718546025455 1.6830304861068723 0.4058337211608887 59215.26265046285 -2 7.713407395786516 -21.24497695763829 2.9511895417323037 3 D3_ObsId03_purged.txt 7.713407395786515 -21.244976957638286 2.638509783992049e-07 2.0023881575070845e-07 70633.90625 297.5479736328125 19.0274658203125 0.00457481574267149 1.6372116804122925 0.3892054557800293 59215.27460648171 -0 7.681860639756485 -21.27056892153881 2.0662962041122337 4 D1_ObsId03_purged.txt 7.681860639756483 -21.27056892153881 2.1520118309581449e-07 1.9701563758189883e-07 69613.75 290.57049560546875 19.043262481689453 0.004533006343990564 1.1921828985214231 0.16120249032974243 59215.25069444445 -1 7.681664060451383 -21.270547392620628 2.0662962041122337 4 D2_ObsId03_purged.txt 7.681664060451382 -21.270547392620628 2.168645494293742e-07 1.860729952340989e-07 69589.1171875 289.437744140625 19.04364585876465 0.004516933113336563 1.230956792831421 0.1876238584518433 59215.26265046285 -2 7.681504272176391 -21.270553846556624 2.0662962041122337 4 D3_ObsId03_purged.txt 7.68150427217639 -21.270553846556624 2.1348166967527507e-07 1.8688399450184082e-07 69121.8046875 289.0152893066406 19.05096244812012 0.00454083364456892 1.228786826133728 0.1861891746520996 59215.27460648171 -3 7.68132678845777 -21.270554139858834 2.0662962041122337 4 D4_ObsId03_purged.txt 7.68132678845777 -21.270554139858834 2.09876390044883e-07 1.9470950007871576e-07 69230.546875 288.583984375 19.049255371093754 0.0045269355177879325 1.176834225654602 0.15026265382766724 59215.2865625 -0 7.74693132024097 -21.245163360816523 1.4341908528245486 4 D1_ObsId03_purged.txt 7.74693132024097 -21.245163360816523 3.0312943977151013e-07 2.2366350549418715e-07 30590.759765625 203.14538574218753 19.936023712158203 0.007211847230792045 1.3997936248779297 0.28560900688171387 59215.25069444445 -1 7.746935168114649 -21.24530116931766 1.4341908528245486 4 D2_ObsId03_purged.txt 7.74693516811465 -21.245301169317656 3.0439781539826077e-07 2.4271375309581344e-07 31013.6015625 205.8195037841797 19.921119689941406 0.007207159884274007 1.3278390169143677 0.24689662456512448 59215.26265046285 -2 7.746979606491126 -21.24542642977949 1.4341908528245486 4 D3_ObsId03_purged.txt 7.746979606491126 -21.24542642977949 3.119224629699602e-07 2.381472228307757e-07 30981.982421875 204.68795776367188 19.92222595214844 0.00717485137283802 1.3700921535491943 0.27012205123901367 59215.27460648171 -3 7.746999429377067 -21.24549367319341 1.4341908528245486 4 D4_ObsId03_purged.txt 7.746999429377067 -21.24549367319341 3.102994980963558e-07 2.442484685616364e-07 30986.51171875 206.62767028808597 19.922067642211918 0.007241784594953059 1.3346352577209473 0.25073158740997314 59215.2865625 -0 7.734902203065896 -21.252666707625085 5.130405229197209 4 D1_ObsId03_purged.txt 7.734902203065896 -21.252666707625085 3.243121113882808e-07 1.939931877359413e-07 77399.1953125 321.449462890625 18.928157806396484 0.004510306753218174 1.98478639125824 0.4961674213409424 59215.25069444445 -1 7.735206148353921 -21.25241628170519 5.130405229197209 4 D2_ObsId03_purged.txt 7.735206148353922 -21.25241628170519 3.170519846662501e-07 1.8307937921235862e-07 77819.90625 323.5157775878906 18.922273635864254 0.004514758940786123 2.005076646804809 0.5012660026550293 59215.26265046285 -2 7.735553130262263 -21.252160580229106 5.130405229197209 4 D3_ObsId03_purged.txt 7.735553130262263 -21.252160580229106 3.187810477811581e-07 1.7982144129291558e-07 78339.4453125 325.003662109375 18.915048599243164 0.004505443852394819 2.0201821327209473 0.5049951076507568 59215.27460648171 -3 7.735882869340387 -21.251850888064247 5.130405229197209 4 D4_ObsId03_purged.txt 7.735882869340387 -21.251850888064247 4.7547675308123877e-07 1.851955602205635e-07 79242.515625 333.42877197265625 18.902603149414062 0.004569562617689371 2.299190044403076 0.5650642514228821 59215.2865625 -0 7.755596437026758 -21.245304194674205 5.08055816051564 4 D1_ObsId03_purged.txt 7.755596437026757 -21.245304194674205 4.858275133301504e-07 2.1930547688953086e-07 40576.390625 251.47244262695312 19.62931632995605 0.006730492226779461 2.5656814575195312 0.6102399826049805 59215.25069444445 -1 7.755756718153133 -21.24570130782972 5.08055816051564 4 D2_ObsId03_purged.txt 7.755756718153132 -21.24570130782972 4.6986559709694125e-07 2.1638116720623657e-07 39698.87890625 247.1550445556641 19.653053283691406 0.0067611574195325375 2.5137126445770264 0.6021820306777954 59215.26265046285 -2 7.75595807540593 -21.24608711882752 5.08055816051564 4 D3_ObsId03_purged.txt 7.755958075405929 -21.24608711882752 4.831627506973746e-07 2.2541884447946361e-07 40292.05078125 250.55401611328125 19.636951446533203 0.006753234192728996 2.49251127243042 0.5987981557846069 59215.27460648171 -3 7.756138768644835 -21.24640032639817 5.08055816051564 4 D4_ObsId03_purged.txt 7.756138768644835 -21.246400326398167 4.7544290282530715e-07 2.0795576460841403e-07 39950.515625 248.3232269287109 19.64619445800781 0.006750326603651048 2.5904252529144287 0.6139630079269409 59215.2865625 -0 7.733120180289504 -21.255673162571966 6.971779687017654 4 D1_ObsId03_purged.txt 7.733120180289502 -21.255673162571966 4.409806422245311e-07 1.7253221074042813e-07 70157.03125 314.8622741699219 19.034822463989254 0.0048739295452833176 3.078470468521118 0.6751633882522583 59215.25069444445 -1 7.733357773939996 -21.25618842855205 6.971779687017654 4 D2_ObsId03_purged.txt 7.733357773939997 -21.25618842855205 4.3908448787988164e-07 1.8597037865220045e-07 69878.34375 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