diff --git a/.github/workflows/apf.yaml b/.github/workflows/apf.yaml index 24aa29cd5..66394c1b8 100644 --- a/.github/workflows/apf.yaml +++ b/.github/workflows/apf.yaml @@ -150,7 +150,6 @@ jobs: TEST_BALTO_MODEL_PATH: "${{ secrets.TEST_BALTO_MODEL_PATH }}" TEST_BALTO_QUANTILES_PATH: "${{ secrets.TEST_BALTO_QUANTILES_PATH }}" TEST_MESSI_MODEL_PATH: "${{ secrets.TEST_MESSI_MODEL_PATH }}" - TEST_MESSI_HEADER_QUANTILES_PATH: "${{ secrets.TEST_MESSI_HEADER_QUANTILES_PATH }}" TEST_MESSI_FEATURE_QUANTILES_PATH: "${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }}" TEST_TORETTO_MODEL_PATH: "${{ secrets.TEST_TORETTO_MODEL_PATH }}" TEST_BARNEY_MODEL_PATH: "${{ secrets.TEST_BARNEY_MODEL_PATH }}" @@ -169,7 +168,6 @@ jobs: TEST_BALTO_MODEL_PATH: "${{ secrets.TEST_BALTO_MODEL_PATH }}" TEST_BALTO_QUANTILES_PATH: "${{ secrets.TEST_BALTO_QUANTILES_PATH }}" TEST_MESSI_MODEL_PATH: "${{ secrets.TEST_MESSI_MODEL_PATH }}" - TEST_MESSI_HEADER_QUANTILES_PATH: "${{ secrets.TEST_MESSI_HEADER_QUANTILES_PATH }}" TEST_MESSI_FEATURE_QUANTILES_PATH: "${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }}" TEST_TORETTO_MODEL_PATH: "${{ secrets.TEST_TORETTO_MODEL_PATH }}" TEST_BARNEY_MODEL_PATH: "${{ secrets.TEST_BARNEY_MODEL_PATH }}" diff --git a/.github/workflows/lc_classification_step.yaml b/.github/workflows/lc_classification_step.yaml index 0a08836e4..038b6c8ce 100644 --- a/.github/workflows/lc_classification_step.yaml +++ b/.github/workflows/lc_classification_step.yaml @@ -26,7 +26,6 @@ jobs: TEST_BALTO_MODEL_PATH: "${{ secrets.TEST_BALTO_MODEL_PATH }}" TEST_BALTO_QUANTILES_PATH: "${{ secrets.TEST_BALTO_QUANTILES_PATH }}" TEST_MESSI_MODEL_PATH: "${{ secrets.TEST_MESSI_MODEL_PATH }}" - TEST_MESSI_HEADER_QUANTILES_PATH: "${{ secrets.TEST_MESSI_HEADER_QUANTILES_PATH }}" TEST_MESSI_FEATURE_QUANTILES_PATH: "${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }}" TEST_TORETTO_MODEL_PATH: "${{ secrets.TEST_TORETTO_MODEL_PATH }}" TEST_MLP_MODEL_PATH: "${{ secrets.TEST_MLP_MODEL_PATH }}" @@ -47,19 +46,18 @@ jobs: test-folder: "tests/integration" secrets: GH_TOKEN: ${{ secrets.ADMIN_TOKEN }} - TEST_BALTO_MODEL_PATH: "${{ secrets.TEST_BALTO_MODEL_PATH }}" - TEST_BALTO_QUANTILES_PATH: "${{ secrets.TEST_BALTO_QUANTILES_PATH }}" - TEST_MESSI_MODEL_PATH: "${{ secrets.TEST_MESSI_MODEL_PATH }}" - TEST_MESSI_HEADER_QUANTILES_PATH: "${{ secrets.TEST_MESSI_HEADER_QUANTILES_PATH }}" - TEST_MESSI_FEATURE_QUANTILES_PATH: "${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }}" - TEST_TORETTO_MODEL_PATH: "${{ secrets.TEST_TORETTO_MODEL_PATH }}" - TEST_MLP_MODEL_PATH: "${{ secrets.TEST_MLP_MODEL_PATH }}" - TEST_ANOMALY_QUANTILES_PATH: "${{ secrets.TEST_ANOMALY_QUANTILES_PATH }}" - TEST_ANOMALY_MODEL_PATH: "${{ secrets.TEST_ANOMALY_MODEL_PATH }}" - TEST_MBAPPE_MODEL_PATH: "${{ secrets.TEST_MBAPPE_MODEL_PATH }}" - TEST_MBAPPE_FEATURES_QUANTILES_PATH: "${{ secrets.TEST_MBAPPE_FEATURES_QUANTILES_PATH }}" - TEST_MBAPPE_METADATA_QUANTILES_PATH: "${{ secrets.TEST_MBAPPE_METADATA_QUANTILES_PATH }}" - TEST_SQUIDWARD_MODEL_PATH: "${{ secrets.TEST_SQUIDWARD_MODEL_PATH }}" + TEST_BALTO_MODEL_PATH: ${{ secrets.TEST_BALTO_MODEL_PATH }} + TEST_BALTO_QUANTILES_PATH: ${{ secrets.TEST_BALTO_QUANTILES_PATH }} + TEST_MESSI_MODEL_PATH: ${{ secrets.TEST_MESSI_MODEL_PATH }} + TEST_MESSI_FEATURE_QUANTILES_PATH: ${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }} + TEST_TORETTO_MODEL_PATH: ${{ secrets.TEST_TORETTO_MODEL_PATH }} + TEST_MLP_MODEL_PATH: ${{ secrets.TEST_MLP_MODEL_PATH }} + TEST_ANOMALY_QUANTILES_PATH: ${{ secrets.TEST_ANOMALY_QUANTILES_PATH }} + TEST_ANOMALY_MODEL_PATH: ${{ secrets.TEST_ANOMALY_MODEL_PATH }} + TEST_MBAPPE_MODEL_PATH: ${{ secrets.TEST_MBAPPE_MODEL_PATH }} + TEST_MBAPPE_FEATURES_QUANTILES_PATH: ${{ secrets.TEST_MBAPPE_FEATURES_QUANTILES_PATH }} + TEST_MBAPPE_METADATA_QUANTILES_PATH: ${{ secrets.TEST_MBAPPE_METADATA_QUANTILES_PATH }} + TEST_SQUIDWARD_MODEL_PATH: ${{ secrets.TEST_SQUIDWARD_MODEL_PATH }} build-lc-classification-balto-dagger: uses: ./.github/workflows/template_build_with_dagger.yaml diff --git a/.github/workflows/poetry-tests-template.yaml b/.github/workflows/poetry-tests-template.yaml index 73f19abb4..d242903ca 100644 --- a/.github/workflows/poetry-tests-template.yaml +++ b/.github/workflows/poetry-tests-template.yaml @@ -43,21 +43,12 @@ on: TEST_MESSI_MODEL_PATH: required: false description: 'A path to a .pt file' - TEST_MESSI_HEADER_QUANTILES_PATH: - required: false - description: 'A path to the directory containing joblib files for messi' TEST_MESSI_FEATURE_QUANTILES_PATH: required: false description: 'A path to the directory containing joblib files for messi' TEST_TORETTO_MODEL_PATH: required: false description: 'A path to a .pkl file' - TEST_BARNEY_MODEL_PATH: - required: false - description: 'A path to a .pkl file' - TEST_NEW_BARNEY_MODEL_PATH: - required: false - description: 'A path to a .pkl file' TEST_MLP_MODEL_PATH: required: false description: 'A path to a .pkl file' @@ -87,18 +78,15 @@ jobs: TEST_BALTO_MODEL_PATH: ${{ secrets.TEST_BALTO_MODEL_PATH }} TEST_BALTO_QUANTILES_PATH: ${{ secrets.TEST_BALTO_QUANTILES_PATH }} TEST_MESSI_MODEL_PATH: ${{ secrets.TEST_MESSI_MODEL_PATH }} - TEST_MESSI_HEADER_QUANTILES_PATH: ${{ secrets.TEST_MESSI_HEADER_QUANTILES_PATH }} TEST_MESSI_FEATURE_QUANTILES_PATH: ${{ secrets.TEST_MESSI_FEATURE_QUANTILES_PATH }} TEST_TORETTO_MODEL_PATH: ${{ secrets.TEST_TORETTO_MODEL_PATH }} - TEST_BARNEY_MODEL_PATH: ${{ secrets.TEST_BARNEY_MODEL_PATH }} - TEST_NEW_BARNEY_MODEL_PATH: ${{ secrets.TEST_NEW_BARNEY_MODEL_PATH }} TEST_MLP_MODEL_PATH: ${{ secrets.TEST_MLP_MODEL_PATH }} TEST_ANOMALY_QUANTILES_PATH: ${{ secrets.TEST_ANOMALY_QUANTILES_PATH }} TEST_ANOMALY_MODEL_PATH: ${{ secrets.TEST_ANOMALY_MODEL_PATH }} - TEST_MBAPPE_MODEL_PATH: "${{ secrets.TEST_MBAPPE_MODEL_PATH }}" - TEST_MBAPPE_FEATURES_QUANTILES_PATH: "${{ secrets.TEST_MBAPPE_FEATURES_QUANTILES_PATH }}" - TEST_MBAPPE_METADATA_QUANTILES_PATH: "${{ secrets.TEST_MBAPPE_METADATA_QUANTILES_PATH }}" - TEST_SQUIDWARD_MODEL_PATH: "${{ secrets.TEST_SQUIDWARD_MODEL_PATH }}" + TEST_MBAPPE_MODEL_PATH: ${{ secrets.TEST_MBAPPE_MODEL_PATH }} + TEST_MBAPPE_FEATURES_QUANTILES_PATH: ${{ secrets.TEST_MBAPPE_FEATURES_QUANTILES_PATH }} + TEST_MBAPPE_METADATA_QUANTILES_PATH: ${{ secrets.TEST_MBAPPE_METADATA_QUANTILES_PATH }} + TEST_SQUIDWARD_MODEL_PATH: ${{ secrets.TEST_SQUIDWARD_MODEL_PATH }} steps: - name: Check out repository code uses: actions/checkout@v4 diff --git a/.github/workflows/stamp_classifier_step.yaml b/.github/workflows/stamp_classifier_step.yaml index ab3aacc72..9d9fbb2d5 100644 --- a/.github/workflows/stamp_classifier_step.yaml +++ b/.github/workflows/stamp_classifier_step.yaml @@ -41,7 +41,7 @@ jobs: secrets: GH_TOKEN: ${{ secrets.ADMIN_TOKEN }} - stamp_classifiier_step_integration: + stamp_classifier_step_integration: uses: ./.github/workflows/pip-tests-template.yaml with: base-folder: 'stamp_classifier_step' diff --git a/correction_step/tests/integration/conftest.py b/correction_step/tests/integration/conftest.py index cacb06ff9..19f3462f7 100644 --- a/correction_step/tests/integration/conftest.py +++ b/correction_step/tests/integration/conftest.py @@ -13,6 +13,12 @@ from tests.utils import atlas_extra_fields, lsst_extra_fields, ztf_extra_fields +@pytest.fixture(scope="session") +def docker_compose_command(): + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" + + @pytest.fixture(scope="session") def docker_compose_file(pytestconfig): return (pathlib.Path(pytestconfig.rootdir) / "tests/integration/docker-compose.yaml").absolute() diff --git a/early_classification_step/model/requirements.txt b/early_classification_step/model/requirements.txt index 5fb64ac94..9d1970a7f 100644 --- a/early_classification_step/model/requirements.txt +++ b/early_classification_step/model/requirements.txt @@ -1,7 +1,7 @@ ephem==3.7.7.0 absl-py==0.7.1 astor==0.8.0 -astropy==3.2.1 +astropy~=4.0 bleach==3.1.0 certifi==2019.6.16 chardet==3.0.4 diff --git a/early_classification_step/poetry.lock b/early_classification_step/poetry.lock index 9fd032e35..68d017fc0 100644 --- a/early_classification_step/poetry.lock +++ b/early_classification_step/poetry.lock @@ -109,39 +109,43 @@ test = ["coverage", "ipython", "objgraph", "pytest-astropy", "pytest-mpl", "pyte [[package]] name = "attrs" -version = "23.1.0" +version = "24.2.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.7" files = [ - {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"}, - {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"}, + {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"}, + {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"}, ] [package.dependencies] importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} [package.extras] -cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] -dev = ["attrs[docs,tests]", "pre-commit"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] -tests = ["attrs[tests-no-zope]", "zope-interface"] -tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] +tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] [[package]] name = "babel" -version = "2.12.1" +version = "2.14.0" description = "Internationalization utilities" optional = false python-versions = ">=3.7" files = [ - {file = "Babel-2.12.1-py3-none-any.whl", hash = "sha256:b4246fb7677d3b98f501a39d43396d3cafdc8eadb045f4a31be01863f655c610"}, - {file = "Babel-2.12.1.tar.gz", hash = "sha256:cc2d99999cd01d44420ae725a21c9e3711b3aadc7976d6147f622d8581963455"}, + {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"}, + {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"}, ] [package.dependencies] pytz = 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"sha256:177f9c9b0d45c47873b619f5b650346d632cdc35fb5e4d25058e09c9e581433d"}, + {file = "wheel-0.42.0.tar.gz", hash = "sha256:c45be39f7882c9d34243236f2d63cbd58039e360f85d0913425fbd7ceea617a8"}, ] [package.extras] -test = ["pytest (>=6.0.0)"] +test = ["pytest (>=6.0.0)", "setuptools (>=65)"] [[package]] name = "wrapt" diff --git a/early_classification_step/requirements.txt b/early_classification_step/requirements.txt index 560ded5f1..85395e5cb 100644 --- a/early_classification_step/requirements.txt +++ b/early_classification_step/requirements.txt @@ -1,2 +1,2 @@ apf-base==1.0.7 -git+https://git@github.com/alercebroker/db-plugins@2.1.4 +git+https://git@github.com/alercebroker/db-plugins@2.1.4 \ No newline at end of file diff --git a/early_classification_step/tests/integration/conftest.py b/early_classification_step/tests/integration/conftest.py index 804a4d2d1..dd03d1857 100644 --- a/early_classification_step/tests/integration/conftest.py +++ b/early_classification_step/tests/integration/conftest.py @@ -5,10 +5,8 @@ @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" @pytest.fixture(scope="session") diff --git a/feature_step/tests/integration/conftest.py b/feature_step/tests/integration/conftest.py index 05fb4e25f..2fb99fc3e 100644 --- a/feature_step/tests/integration/conftest.py +++ b/feature_step/tests/integration/conftest.py @@ -37,10 +37,8 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def is_responsive_kafka(url): diff --git a/lc_classification_step/lc_classification/core/step.py b/lc_classification_step/lc_classification/core/step.py index 812c7e333..31f692c3a 100644 --- a/lc_classification_step/lc_classification/core/step.py +++ b/lc_classification_step/lc_classification/core/step.py @@ -66,6 +66,9 @@ def __init__(self, config={}, level=logging.INFO, model=None, **step_args): self.step_parser: KafkaParser = get_class( config["STEP_PARSER_CLASS"] )() + self.min_detections = config.get("MIN_DETECTIONS", None) + if self.min_detections is not None: + self.min_detections = int(self.min_detections) def pre_produce(self, result: Tuple[OutputDTO, List[dict], DataFrame]): return self.step_parser.parse( @@ -149,6 +152,20 @@ def predict(self, model_input): self.log_data(model_input) raise e + def pre_execute(self, messages: List[dict]): + if self.min_detections is None: + return messages + + def has_enough_detections(message: dict) -> bool: + n_dets = len( + [True for det in message["detections"] if not det["forced"]] + ) + return n_dets >= self.min_detections + + filtered_messages = filter(has_enough_detections, messages) + filtered_messages = list(filtered_messages) + return filtered_messages + def execute(self, messages): """Run the classification. diff --git a/lc_classification_step/settings.py b/lc_classification_step/settings.py index c668a0ef4..e11c42ffc 100644 --- a/lc_classification_step/settings.py +++ b/lc_classification_step/settings.py @@ -159,4 +159,5 @@ def config(): os.getenv("LOG_CLASS_DISTRIBUTION", False) ), }, + "MIN_DETECTIONS": os.getenv("MIN_DETECTIONS", None), } diff --git a/lc_classification_step/tests/integration/conftest.py b/lc_classification_step/tests/integration/conftest.py index 0d635d1bc..ee80d65dc 100644 --- a/lc_classification_step/tests/integration/conftest.py +++ b/lc_classification_step/tests/integration/conftest.py @@ -34,11 +34,8 @@ def pytest_configure(config): @pytest.fixture(scope="session") def docker_compose_command(): - return ( - "docker compose" - if not os.getenv("COMPOSE", "v1") == "v1" - else "docker-compose" - ) + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" @pytest.fixture(scope="session") @@ -212,6 +209,7 @@ def set_env_variables( yield set_env_variables os.environ = env_copy + @pytest.fixture def env_variables_squidward(): env_copy = os.environ.copy() @@ -258,6 +256,7 @@ def set_env_variables( yield set_env_variables os.environ = env_copy + @pytest.fixture def env_variables_mbappe(): env_copy = os.environ.copy() @@ -304,6 +303,7 @@ def set_env_variables( yield set_env_variables os.environ = env_copy + @pytest.fixture def env_variables_elasticc(): env_copy = os.environ.copy() @@ -355,7 +355,12 @@ def set_env_variables( @pytest.fixture def produce_messages(): - def func(topic, force_empty_features=False, force_missing_features=False): + def func( + topic, + force_empty_features=False, + force_missing_features=False, + n_forced=5, + ): schema = load_schema(str(INPUT_SCHEMA_PATH)) schema_path = INPUT_SCHEMA_PATH _produce_messages( @@ -364,13 +369,19 @@ def func(topic, force_empty_features=False, force_missing_features=False): schema_path, force_empty_features, force_missing_features, + n_forced, ) return func def _produce_messages( - topic, SCHEMA, SCHEMA_PATH, force_empty_features, force_missing_features + topic, + SCHEMA, + SCHEMA_PATH, + force_empty_features, + force_missing_features, + n_forced: int, ): BANDS = ["g", "r"] producer = KafkaProducer( @@ -385,11 +396,16 @@ def _produce_messages( producer.set_key_field("oid") for message in messages: - for det in message["detections"]: + for i, det in enumerate(message["detections"]): det["oid"] = message["oid"] - det["candid"] = random.randint(0, 100000) + det["candid"] = str(random.randint(0, 100000)) det["extra_fields"] = generate_extra_fields() det["fid"] = random.choice(BANDS) + if i < n_forced: + det["forced"] = True + else: + det["forced"] = False + message["detections"][0]["new"] = True message["detections"][0]["has_stamp"] = True if topic == "features_ztf": diff --git a/lc_classification_step/tests/integration/test_step_mbappe.py b/lc_classification_step/tests/integration/test_step_mbappe.py index cb8c89163..8a9d4349c 100644 --- a/lc_classification_step/tests/integration/test_step_mbappe.py +++ b/lc_classification_step/tests/integration/test_step_mbappe.py @@ -3,6 +3,7 @@ from typing import Callable import pytest +from unittest import mock from apf.consumers import KafkaConsumer from lc_classification.core.step import LateClassifier @@ -25,7 +26,7 @@ def test_step_mbappe_result( "mbappe", "alerce_classifiers.mbappe.model.MbappeClassifier", { - "MODEL_PATH": os.getenv("TEST_MBAPPE_MODEL_PATH"), + "MODEL_PATH": os.getenv("TEST_MBAPPE_MODEL_PATH"), "FEATURE_QUANTILES_PATH": os.getenv( "TEST_MBAPPE_FEATURES_QUANTILES_PATH" ), @@ -67,7 +68,7 @@ def test_step_mbappe_no_features_result( "mbappe", "alerce_classifiers.mbappe.model.MbappeClassifier", { - "MODEL_PATH": os.getenv("TEST_MBAPPE_MODEL_PATH"), + "MODEL_PATH": os.getenv("TEST_MBAPPE_MODEL_PATH"), "FEATURE_QUANTILES_PATH": os.getenv( "TEST_MBAPPE_FEATURES_QUANTILES_PATH" ), @@ -78,7 +79,7 @@ def test_step_mbappe_no_features_result( }, ) - from settings import config + from settings import config kconsumer = kafka_consumer("mbappe") sconsumer = scribe_consumer("w_object_mbappe") @@ -94,3 +95,46 @@ def test_step_mbappe_no_features_result( command = json.loads(message["payload"]) assert_command_is_correct(command) sconsumer.commit() + + +@pytest.mark.ztf +def test_step_mbappe_min_detections( + kafka_service, + produce_messages, + env_variables_mbappe, + kafka_consumer: Callable[[str], KafkaConsumer], + scribe_consumer: Callable[[], KafkaConsumer], +): + + env_variables_mbappe( + "mbappe", + "alerce_classifiers.mbappe.model.MbappeClassifier", + { + "MODEL_PATH": os.getenv("TEST_MBAPPE_MODEL_PATH"), + "FEATURE_QUANTILES_PATH": os.getenv( + "TEST_MBAPPE_FEATURES_QUANTILES_PATH" + ), + "METADATA_QUANTILES_PATH": os.getenv( + "TEST_MBAPPE_METADATA_QUANTILES_PATH" + ), + "MAPPER_CLASS": "alerce_classifiers.mbappe.mapper.MbappeMapper", + "MIN_DETECTIONS": "6", + }, + ) + + from settings import config + + produce_messages("features_mbappe", n_forced=6) + step = LateClassifier(config=config()) + step.execute = mock.MagicMock() + step.start() + step.execute.assert_not_called() + + produce_messages("features_mbappe", n_forced=2) + kconsumer = kafka_consumer("mbappe") + step = LateClassifier(config=config()) + step.start() + + for message in kconsumer.consume(): + assert_ztf_object_is_correct(message) + kconsumer.commit() diff --git a/lc_classification_step/tests/integration/test_step_squidward.py b/lc_classification_step/tests/integration/test_step_squidward.py index 2879154a9..4627c5555 100644 --- a/lc_classification_step/tests/integration/test_step_squidward.py +++ b/lc_classification_step/tests/integration/test_step_squidward.py @@ -3,6 +3,7 @@ from typing import Callable import pytest +from unittest import mock from apf.consumers import KafkaConsumer from lc_classification.core.step import LateClassifier @@ -82,3 +83,40 @@ def test_step_squidward_no_features_result( command = json.loads(message["payload"]) assert_command_is_correct(command) sconsumer.commit() + + +@pytest.mark.ztf +def test_step_squidward_min_detections( + kafka_service, + produce_messages, + env_variables_squidward, + kafka_consumer: Callable[[str], KafkaConsumer], + scribe_consumer: Callable[[], KafkaConsumer], +): + + env_variables_squidward( + "squidward", + "alerce_classifiers.squidward.model.SquidwardFeaturesClassifier", + { + "MODEL_PATH": os.getenv("TEST_SQUIDWARD_MODEL_PATH"), + "MAPPER_CLASS": "alerce_classifiers.squidward.mapper.SquidwardMapper", + "MIN_DETECTIONS": "6", + }, + ) + + from settings import config + + produce_messages("features_squidward", n_forced=6) + step = LateClassifier(config=config()) + step.execute = mock.MagicMock() + step.start() + step.execute.assert_not_called() + + produce_messages("features_squidward", n_forced=2) + kconsumer = kafka_consumer("squidward") + step = LateClassifier(config=config()) + step.start() + + for message in kconsumer.consume(): + assert_ztf_object_is_correct(message) + kconsumer.commit() diff --git a/lc_classification_step/tests/test_commons.py b/lc_classification_step/tests/test_commons.py index ac5e14ff1..ec8ed8029 100644 --- a/lc_classification_step/tests/test_commons.py +++ b/lc_classification_step/tests/test_commons.py @@ -37,6 +37,7 @@ def assert_command_is_correct(command): assert command["criteria"]["_id"] is not None assert not command["options"]["set_on_insert"] + def assert_score_command_is_correct(command): assert command["collection"] == "score" assert command["type"] == "insert" diff --git a/lc_classification_step/tests/unit/conftest.py b/lc_classification_step/tests/unit/conftest.py index fd5521585..ae84ff225 100644 --- a/lc_classification_step/tests/unit/conftest.py +++ b/lc_classification_step/tests/unit/conftest.py @@ -368,7 +368,7 @@ def test_model(factory, messages_ztf): # Test producer produces correct data calls = step.producer.mock_calls - assert len(calls) == len(messages_ztf) + 1 # beause call __del__ + assert len(calls) == len(messages_ztf) + 1 # because call __del__ for call in calls: if len(call.args) > 1: # because of __del__ obj = call.args[0] diff --git a/lc_classifier/lc_classifier/features/core/base.py b/lc_classifier/lc_classifier/features/core/base.py index 2853e963c..0c5e4d40f 100644 --- a/lc_classifier/lc_classifier/features/core/base.py +++ b/lc_classifier/lc_classifier/features/core/base.py @@ -1,3 +1,4 @@ +import pickle from dataclasses import dataclass from typing import List, Optional, Dict from abc import ABC, abstractmethod @@ -129,3 +130,9 @@ def query_ao_table(table: pd.DataFrame, name: str, check_unique: bool = True): return ans_df["value"].values[0] else: return ans_df + + +def save_astro_objects_batch(astro_objects: List[AstroObject], filename: str): + astro_objects_dicts = [ao.to_dict() for ao in astro_objects] + with open(filename, "wb") as f: + pickle.dump(astro_objects_dicts, f) diff --git a/lc_classifier/lc_classifier/utils.py b/lc_classifier/lc_classifier/utils.py index db54d234c..800569459 100644 --- a/lc_classifier/lc_classifier/utils.py +++ b/lc_classifier/lc_classifier/utils.py @@ -178,6 +178,7 @@ def create_astro_object( detections = detections[detection_keys].copy() detections["forced"] = False + forced_photometry = forced_photometry.copy() forced_photometry["candid"] = forced_photometry["oid"] + forced_photometry[ "pid" ].astype(str) diff --git a/libs/apf/apf/core/step.py b/libs/apf/apf/core/step.py index 62e42ef10..ea1fa6327 100644 --- a/libs/apf/apf/core/step.py +++ b/libs/apf/apf/core/step.py @@ -432,6 +432,9 @@ def start(self): self._pre_consume() for message in self.consumer.consume(): preprocessed_msg = self._pre_execute(message) + if len(preprocessed_msg) == 0: + logger.info("Message of len zero after pre_execute") + continue try: result = self.execute(preprocessed_msg) except Exception as error: diff --git a/libs/apf/poetry.lock b/libs/apf/poetry.lock index 2c7647bae..3940f5f3d 100644 --- a/libs/apf/poetry.lock +++ b/libs/apf/poetry.lock @@ -1,25 +1,26 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "attrs" -version = "23.1.0" +version = "24.2.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.7" files = [ - {file = "attrs-23.1.0-py3-none-any.whl", hash = "sha256:1f28b4522cdc2fb4256ac1a020c78acf9cba2c6b461ccd2c126f3aa8e8335d04"}, - {file = "attrs-23.1.0.tar.gz", hash = "sha256:6279836d581513a26f1bf235f9acd333bc9115683f14f7e8fae46c98fc50e015"}, + {file = "attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2"}, + {file = "attrs-24.2.0.tar.gz", hash = "sha256:5cfb1b9148b5b086569baec03f20d7b6bf3bcacc9a42bebf87ffaaca362f6346"}, ] [package.dependencies] importlib-metadata = {version = "*", markers = "python_version < \"3.8\""} [package.extras] -cov = ["attrs[tests]", "coverage[toml] (>=5.3)"] -dev = ["attrs[docs,tests]", "pre-commit"] -docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"] -tests = ["attrs[tests-no-zope]", "zope-interface"] -tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +benchmark = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-codspeed", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +cov = ["cloudpickle", "coverage[toml] (>=5.3)", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +dev = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pre-commit", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"] +tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"] +tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"] [[package]] name = "black" @@ -111,13 +112,13 @@ crt = ["awscrt (==0.16.9)"] [[package]] name = "certifi" -version = "2023.7.22" +version = "2024.7.4" description = "Python package for providing Mozilla's CA Bundle." optional = false python-versions = ">=3.6" files = [ - {file = "certifi-2023.7.22-py3-none-any.whl", hash = "sha256:92d6037539857d8206b8f6ae472e8b77db8058fec5937a1ef3f54304089edbb9"}, - {file = "certifi-2023.7.22.tar.gz", hash = "sha256:539cc1d13202e33ca466e88b2807e29f4c13049d6d87031a3c110744495cb082"}, + {file = "certifi-2024.7.4-py3-none-any.whl", hash = "sha256:c198e21b1289c2ab85ee4e67bb4b4ef3ead0892059901a8d5b622f24a1101e90"}, + {file = "certifi-2024.7.4.tar.gz", hash = "sha256:5a1e7645bc0ec61a09e26c36f6106dd4cf40c6db3a1fb6352b0244e7fb057c7b"}, ] [[package]] @@ -198,97 +199,112 @@ pycparser = "*" [[package]] name = "charset-normalizer" -version = "3.2.0" +version = "3.3.2" description = "The Real First Universal Charset Detector. 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readme = "README.md" packages = [{include = "apf"}] [tool.poetry.dependencies] -python = ">=3.7" +python = ">=3.7.1" click = ">=7.1.1" confluent-kafka = ">=1.4.0,<2.1.0" fastavro = ">=0.22.0,<=1.6.1" jinja2 = ">=2.10.0" -pandas = ">=0.24,<=2.0.1" +pandas = ">=1.2,<=2.2.1" +numpy = "<2.0.0" boto3 = "1.26.69" prometheus-client = "0.16.0" pyroscope-io = "0.8.4" diff --git a/libs/apf/tests/consumers/conftest.py b/libs/apf/tests/consumers/conftest.py index 437c5b8f9..37a48e0c5 100644 --- a/libs/apf/tests/consumers/conftest.py +++ b/libs/apf/tests/consumers/conftest.py @@ -1,5 +1,12 @@ from confluent_kafka.admin import AdminClient, NewTopic import pytest +import os + + +@pytest.fixture(scope="session") +def docker_compose_command(): + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def is_responsive_kafka(url): diff --git a/lightcurve-step/tests/integration/conftest.py b/lightcurve-step/tests/integration/conftest.py index d929cb968..1faf05e23 100644 --- a/lightcurve-step/tests/integration/conftest.py +++ b/lightcurve-step/tests/integration/conftest.py @@ -25,10 +25,8 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" @pytest.fixture diff --git a/magstats_step/tests/integration/conftest.py b/magstats_step/tests/integration/conftest.py index 30b772014..eec7c67b9 100644 --- a/magstats_step/tests/integration/conftest.py +++ b/magstats_step/tests/integration/conftest.py @@ -18,10 +18,8 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def is_responsive_kafka(url): diff --git a/metadata_step/poetry.lock b/metadata_step/poetry.lock index 48e7a1cd4..1d9238c3a 100644 --- a/metadata_step/poetry.lock +++ b/metadata_step/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. 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"meandec": 45.0, + "deltajd": 7.4, + "step_id_corr": "corr_bulk_0", }, ] diff --git a/metadata_step/tests/integration/conftest.py b/metadata_step/tests/integration/conftest.py index 14531c7e2..a039bc8db 100644 --- a/metadata_step/tests/integration/conftest.py +++ b/metadata_step/tests/integration/conftest.py @@ -5,17 +5,13 @@ @pytest.fixture(scope="session") def docker_compose_file(pytestconfig): - return os.path.join( - str(pytestconfig.rootdir), "tests/integration", "docker-compose.yaml" - ) + return os.path.join(str(pytestconfig.rootdir), "tests/integration", "docker-compose.yaml") @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def is_psql_responsive(ip, port): @@ -39,7 +35,5 @@ def is_psql_responsive(ip, port): def psql_service(docker_ip, docker_services): port = docker_services.port_for("postgres", 5432) server = f"{docker_ip}:{port}" - docker_services.wait_until_responsive( - timeout=30.0, pause=0.1, check=lambda: is_psql_responsive(server, port) - ) + docker_services.wait_until_responsive(timeout=30.0, pause=0.1, check=lambda: is_psql_responsive(server, port)) return server diff --git a/metadata_step/tests/integration/test_step.py b/metadata_step/tests/integration/test_step.py index 4730358cf..97008c4dd 100644 --- a/metadata_step/tests/integration/test_step.py +++ b/metadata_step/tests/integration/test_step.py @@ -10,9 +10,7 @@ def _populate_db(conn: PSQLConnection): with conn.session() as session: session.execute(insert(Object).values(object_mocks).on_conflict_do_nothing()) - session.execute( - insert(Detection).values(detection_mocks).on_conflict_do_nothing() - ) + session.execute(insert(Detection).values(detection_mocks).on_conflict_do_nothing()) session.execute(insert(Gaia_ztf).values(gaia_mocks).on_conflict_do_nothing()) session.execute(insert(Ps1_ztf).values(ps1_mocks).on_conflict_do_nothing()) session.commit() @@ -43,35 +41,32 @@ def test_step(psql_service): # assert insertion ss_result = session.execute(select(Ss_ztf).where(Ss_ztf.oid == "ZTF21waka")) ps1_result = session.execute( - select(Ps1_ztf) - .where(Ps1_ztf.oid == "ZTF21waka") - .where(Ps1_ztf.candid == 930930930) + select(Ps1_ztf).where(Ps1_ztf.oid == "ZTF21waka").where(Ps1_ztf.candid == 930930930) ) gaia_result = session.execute( - select(Gaia_ztf) - .where(Gaia_ztf.oid == "ZTF21waka") - .where(Gaia_ztf.candid == 930930930) + select(Gaia_ztf).where(Gaia_ztf.oid == "ZTF21waka").where(Gaia_ztf.candid == 930930930) ) ss_result = list(ss_result)[0][0].__dict__ ps1_result = list(ps1_result)[0][0].__dict__ gaia_result = list(gaia_result)[0][0].__dict__ - + assert ss_result["oid"] == "ZTF21waka" assert ss_result["candid"] == 930930930 assert ss_result["ssdistnr"] == 100 assert ps1_result["oid"] == "ZTF21waka" assert ps1_result["sgmag1"] == 100 - + assert gaia_result["neargaia"] == 100 # assert updating ps1_result = session.execute( - select(Ps1_ztf) - .where(Ps1_ztf.oid == "ZTF00llmn") - .where(Ps1_ztf.candid == 1234567890) + select(Ps1_ztf).where(Ps1_ztf.oid == "ZTF00llmn").where(Ps1_ztf.candid == 1234567890) ) ps1_result = list(ps1_result)[0][0].__dict__ assert ps1_result["oid"] == "ZTF00llmn" - assert ps1_result["unique1"] == False + + # This assertion is failing. I don't understand the + # expected behavior + assert ps1_result["unique1"] is False diff --git a/prv_candidates_step/tests/integration/conftest.py b/prv_candidates_step/tests/integration/conftest.py index 11fed22f2..b75b6360d 100644 --- a/prv_candidates_step/tests/integration/conftest.py +++ b/prv_candidates_step/tests/integration/conftest.py @@ -20,10 +20,8 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def is_responsive_kafka(url): diff --git a/reflector_step/tests/conftest.py b/reflector_step/tests/conftest.py index a020a2448..e04434648 100644 --- a/reflector_step/tests/conftest.py +++ b/reflector_step/tests/conftest.py @@ -3,6 +3,12 @@ from confluent_kafka.admin import AdminClient, NewTopic +@pytest.fixture(scope="session") +def docker_compose_command(): + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" + + @pytest.fixture(scope="session") def docker_compose_file(pytestconfig): try: diff --git a/s3_step/tests/conftest.py b/s3_step/tests/conftest.py index 2dc16b776..cd1efe67a 100644 --- a/s3_step/tests/conftest.py +++ b/s3_step/tests/conftest.py @@ -12,7 +12,7 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - version = os.getenv("COMPOSE", "v1") + version = os.getenv("COMPOSE", "v2") return "docker compose" if version == "v2" else "docker-compose" diff --git a/sorting_hat_step/sorting_hat_step/utils/wizard.py b/sorting_hat_step/sorting_hat_step/utils/wizard.py index 71ce087b4..82e5d723b 100644 --- a/sorting_hat_step/sorting_hat_step/utils/wizard.py +++ b/sorting_hat_step/sorting_hat_step/utils/wizard.py @@ -199,9 +199,9 @@ def generate_new_id(alerts: pd.DataFrame): count = 0 for oid, group in alerts_wo_aid.groupby("oid"): id_ = id_generator(group["ra"].iloc[0], group["dec"].iloc[0]) - alerts_wo_aid.loc[ - group.index, "aid" - ] = f"AL{time.strftime('%y')}{encode(id_)}" + alerts_wo_aid.loc[group.index, "aid"] = ( + f"AL{time.strftime('%y')}{encode(id_)}" + ) count += 1 logger.debug( diff --git a/sorting_hat_step/tests/integration/conftest.py b/sorting_hat_step/tests/integration/conftest.py index 76dd0d950..225112ee9 100644 --- a/sorting_hat_step/tests/integration/conftest.py +++ b/sorting_hat_step/tests/integration/conftest.py @@ -14,7 +14,5 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" diff --git a/stamp_classifier_step/pyproject.toml b/stamp_classifier_step/pyproject.toml index 95470cf86..42d27652d 100644 --- a/stamp_classifier_step/pyproject.toml +++ b/stamp_classifier_step/pyproject.toml @@ -16,7 +16,7 @@ url = "https://github.com/alercebroker/atlas_stamp_classifier" priority = "primary" [tool.poetry.dependencies] -python = ">=3.7,<3.9" +python = ">=3.8,<3.9" apf-base = { version = "<2.0" } atlas-stamp-classifier = {git = "ssh://git@github.com/alercebroker/atlas_stamp_classifier.git", rev = "main", optional = true } astropy = { version = "*", optional = true } @@ -64,14 +64,15 @@ werkzeug = {version = "*", optional = true } wrapt = {version = "*", optional = true } matplotlib = {version = "*", optional = true } click = {version = "*", optional = true } +wget = {version = "*", optional = true } [tool.poetry.group.dev.dependencies] black = "~=21.0" [tool.poetry.group.test.dependencies] pytest = "^7.3.1" -pytest-cov = "^4.1.0" -pytest-docker = "^1.0.1" +pytest-cov = "*" +pytest-docker = "*" [tool.poetry.group.atlas] optional = true diff --git a/stamp_classifier_step/requirements.txt b/stamp_classifier_step/requirements.txt index fa3eb7fb1..30b756bf2 100644 --- a/stamp_classifier_step/requirements.txt +++ b/stamp_classifier_step/requirements.txt @@ -1,10 +1,11 @@ atlas_stamp_classifier @ git+https://alerceadmin:${GH_TOKEN}@github.com/alercebroker/atlas_stamp_classifier.git@main apf_base<2.0 astropy -pandas +pandas<2.0 numpy +wget # Fixed versions to prevent clashes with tensorflow -protobuf==3.15.3 -grpcio==1.32 -Pygments==2.12 -Jinja2==3.0 +# protobuf==3.15.3 +# grpcio==1.32 +# Pygments==2.12 +# Jinja2==3.0 diff --git a/stamp_classifier_step/tests/integration/conftest.py b/stamp_classifier_step/tests/integration/conftest.py index 85a001c9a..0d18652e2 100644 --- a/stamp_classifier_step/tests/integration/conftest.py +++ b/stamp_classifier_step/tests/integration/conftest.py @@ -17,10 +17,8 @@ def docker_compose_file(pytestconfig): @pytest.fixture(scope="session") def docker_compose_command(): - v2 = False - if os.getenv("COMPOSE", "v1") == "v2": - v2 = True - return "docker compose" if v2 else "docker-compose" + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" def consume_messages() -> list: diff --git a/stamp_classifier_step/tests/integration/test_step.py b/stamp_classifier_step/tests/integration/test_step.py index b73455b72..eb05009dd 100644 --- a/stamp_classifier_step/tests/integration/test_step.py +++ b/stamp_classifier_step/tests/integration/test_step.py @@ -15,7 +15,8 @@ PRODUCER_SCHEMA_PATH = os.path.join(os.path.dirname(__file__), "test_schema.avsc") -SCRIBE_SCHEMA_PATH = os.path.join(os.path.dirname(__file__), "scribe.avsc") +SCRIBE_SCHEMA_PATH = os.path.join(os.path.dirname(__file__), "scribe.avsc") + def consume_messages(topic) -> List[dict]: config = { @@ -33,7 +34,7 @@ def consume_messages(topic) -> List[dict]: } consumer = KafkaConsumer(config) messages = [] - #if len(consumer.consumer.assignment()) == 0: + # if len(consumer.consumer.assignment()) == 0: # return messages for message in consumer.consume(): @@ -88,7 +89,7 @@ def test_atlas_step(): "PARAMS": { "bootstrap.servers": "localhost:9092", }, - "SCHEMA_PATH": SCRIBE_SCHEMA_PATH + "SCHEMA_PATH": SCRIBE_SCHEMA_PATH, } ) strategy = ATLASStrategy() diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/data/ZTF_ff_processed_to_final.py b/training/lc_classifier_ztf/ATAT_ALeRCE/data/ZTF_ff_processed_to_final.py index 4de8233e7..25c10b10f 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/data/ZTF_ff_processed_to_final.py +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/data/ZTF_ff_processed_to_final.py @@ -13,7 +13,7 @@ from src.partitions import get_partitions, ordered_partitions from src.processing import processing_lc from src.create_dataset import create_lc_h5py -from src.add_md_feat import add_metadata, add_features +from src.add_md_feat import add_metadata, add_features, compute_feature_quantiles def check_files(df_objid_label, dict_cols, dict_info, path_lcs_file, path_md_feat_file): @@ -223,7 +223,10 @@ def main( ####################################################################################################################################################### # Merge between light curves and partitions - num_folds = 5 + + # we will modify the training data for fold_0, + # so using other partitions will leak info + num_folds = 1 # 5 all_partitions = {} for fold in range(num_folds): all_partitions["fold_%s" % fold] = ordered_partitions( @@ -282,8 +285,11 @@ def main( dict_info["list_time_to_eval"], all_partitions, num_folds, + df_objid_label ) + compute_feature_quantiles(path_dataset, path_save_dataset, dict_info["list_time_to_eval"]) + dict_info.update( {"mapping_classes": mapping_to_int, "md_cols": md_cols, "feat_cols": feat_cols,} ) @@ -370,7 +376,7 @@ def main( # Astronomical objects and their labels df_objid_label = pd.read_parquet("{}/raw/data_231206/objects.parquet".format(ROOT)) df_objid_label = df_objid_label.reset_index() - df_objid_label = df_objid_label[[dict_cols["oid"], dict_cols["class"]]] + df_objid_label = df_objid_label[[dict_cols["oid"], dict_cols["class"], 'ra', 'dec']] main( path_lcs_file, diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/add_md_feat.py b/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/add_md_feat.py index 3fd71b80a..ff1b846b4 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/add_md_feat.py +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/add_md_feat.py @@ -72,7 +72,7 @@ def add_metadata( ].index.to_numpy() qt = QuantileTransformer( - n_quantiles=10000, random_state=0, output_distribution="normal" + n_quantiles=1000, random_state=0, output_distribution="uniform" ) qt.fit(df_metadata.iloc[aux_idx]) @@ -94,6 +94,7 @@ def add_features( list_times_to_eval, all_partitions, num_folds, + df_objid_label # used for periodic-other unbias ): for time_to_eval in list_times_to_eval: @@ -119,6 +120,52 @@ def add_features( df_feat[col] = df_feat[col] df_feat[col] = df_feat[col].replace([np.inf, -np.inf], -9999) + # manage bias Periodic-Other + # we will modify the training data for fold_0, + # so using other partitions will leak info + assert num_folds == 1 + + training_partition = "training_0" + labels = all_partitions['fold_0'] + po_tp = labels[ + (labels["alerceclass"] == "Periodic-Other") + & (labels["partition"] == training_partition) + ] + + training_po_oids = list(set([oid.split('_')[0] for oid in po_tp['oid'].values])) + del po_tp + po_tp_coords = df_objid_label[df_objid_label["oid"].isin(training_po_oids)] + southern = po_tp_coords["dec"] < -20 + + n_not_to_be_replaced = ((~southern).astype(float).sum()) / (54 - (-20)) * (28 - 20) + n_not_to_be_replaced = int(np.ceil(n_not_to_be_replaced)) + + southern_po_oids = po_tp_coords[southern]["oid"].values + northern_po_oids = po_tp_coords[~southern]["oid"].values + + np.random.seed(0) + southern_not_to_be_replaced = np.random.choice( + southern_po_oids, size=n_not_to_be_replaced, replace=False + ) + not_to_be_replaced = np.concatenate([northern_po_oids, southern_not_to_be_replaced]) + to_be_replaced = list(set(training_po_oids) - set(not_to_be_replaced)) + + tbr_feature_mask = df_feat["oid"].isin(to_be_replaced) + n_replacement_needed = tbr_feature_mask.astype(int).sum() + replacement_coords = ( + df_feat[df_feat["oid"].isin(not_to_be_replaced)][ + [f"Coordinate_{x}" for x in "xyz"] + ] + .sample(n_replacement_needed, replace=True) + .values + ) + df_feat = df_feat.set_index("oid") + df_feat.loc[ + to_be_replaced, [f"Coordinate_{x}" for x in "xyz"] + ] = replacement_coords + df_feat = df_feat.reset_index() + + feat_cols = df_feat.columns if dict_info["type_windows"] == "windows": @@ -144,29 +191,6 @@ def add_features( df_feat.index.names = ["SNID"] df_feat = df_feat.filter(items=All_SNID_h5.astype(str), axis=0) - for fold in range(num_folds): - name_used = "fold_{}".format(fold) - aux_pd = all_partitions["fold_{}".format(fold)] - aux_idx = aux_pd[ - aux_pd["partition"] == "training_{}".format(fold) - ].index.to_numpy() - - qt = QuantileTransformer( - n_quantiles=10000, random_state=0, output_distribution="normal" - ) - qt.fit(df_feat.iloc[aux_idx]) - - os.makedirs( - "{}/quantiles/features/{}_days".format(path_save_dataset, time_to_eval), - exist_ok=True, - ) - dump( - qt, - "{}/quantiles/features/{}_days/{}.joblib".format( - path_save_dataset, time_to_eval, name_used - ), - ) - add_cols_h5py( df_feat, path_save_dataset, @@ -323,3 +347,26 @@ def add_features_QT_as_MLP( ) return list(df_feat.columns) + + +def compute_feature_quantiles(dataset_path, path_save_dataset, list_time_to_eval): + h5_file = h5py.File(dataset_path) + + all_features = [] + for time in list_time_to_eval: + all_features.append(h5_file[f"extracted_feat_{time}"][h5_file["training_0"]]) + + h5_file.close() + all_features = np.concatenate(all_features, axis=0) + qt = QuantileTransformer( + n_quantiles=1000, random_state=0, output_distribution="uniform" + ) + qt.fit(all_features) + os.makedirs( + f"{path_save_dataset}/quantiles/features", + exist_ok=True, + ) + dump( + qt, + f"{path_save_dataset}/quantiles/features/fold_0.joblib" + ) \ No newline at end of file diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/processing.py b/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/processing.py index 064cd1ec7..5d31bfcd8 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/processing.py +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/data/src/processing.py @@ -1,5 +1,6 @@ import pandas as pd import numpy as np +from tqdm import tqdm import copy import glob @@ -252,9 +253,8 @@ def processing_lc(path_lcs_file, dict_cols, dict_info, df_objid_label): df_final = [] path_lcs_chunks = glob.glob("{}/lightcurves*".format(path_lcs_file)) - for i, path_chunk in enumerate(path_lcs_chunks): - print("Processing chunk {}".format(i)) - + for path_chunk in tqdm(path_lcs_chunks, "processing lc chunks"): + # Lightcurves df_chunk = pd.read_parquet("{}".format(path_chunk)) df_chunk = df_chunk[ diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/inference_ztf.py b/training/lc_classifier_ztf/ATAT_ALeRCE/inference_ztf.py index ebe7d2ba7..87c517b6d 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/inference_ztf.py +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/inference_ztf.py @@ -209,10 +209,7 @@ def get_predictions( if config_used["general"]["use_features"]: extracted_feat = dict() for time_eval in config_used["general"]["list_time_to_eval"]: - last_time = config_used["general"]["list_time_to_eval"][-1] - path_QT = "./{}/quantiles/features/{}_days/fold_{}.joblib".format( - data_root, last_time, partition_used - ) + path_QT = f"./{data_root}/quantiles/features/fold_{partition_used}.joblib" extracted_feat_aux = h5_file.get("extracted_feat_{}".format(time_eval))[:][ these_idx ] @@ -355,7 +352,7 @@ def get_predictions( "list_eval_time": [8, 16, 32, 64, 128, 256, 512, 1024, 2048], }, "ztf_ff": { - "path_exp": "results/ZTF_ff/LC_MD_FEAT/ireyes_test_6/MTA", + "path_exp": "results/ZTF_ff/LC_MD_FEAT/ireyes_test_7/MTA", "data_root": "data/datasets/ZTF_ff/final/LC_MD_FEAT_240627_windows_200_12", "list_eval_time": [16, 32, 64, 128, 256, 512, 1024, 2048], }, diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/notebooks/vis_results/ATAT_results_windows_v3.ipynb b/training/lc_classifier_ztf/ATAT_ALeRCE/notebooks/vis_results/ATAT_results_windows_v3.ipynb index d2b6751d2..2eee4609e 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/notebooks/vis_results/ATAT_results_windows_v3.ipynb +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/notebooks/vis_results/ATAT_results_windows_v3.ipynb @@ -64,7 +64,7 @@ "outputs": [], "source": [ "path_data = './data/datasets/ZTF_ff/final/LC_MD_FEAT_240627_windows_200_12'\n", - "path_results = './results/ZTF_ff/LC_MD_FEAT/ireyes_test_6/MTA'\n", + "path_results = './results/ZTF_ff/LC_MD_FEAT/ireyes_test_7/MTA'\n", "time_to_eval = 2048\n", "\n", "order_classes = ['SNIa', # yes\n", @@ -1216,118 +1216,118 @@ " b'ZTF23abcvqkd_3', b'ZTF23abcvqkd_4', b'ZTF23abcvqkd_5'],\n", " dtype=object),\n", " 'y_test': tensor([10, 10, 10, ..., 4, 4, 4]),\n", - " 'list_y_pred': {'test_16': array([ 2, 10, 10, ..., 16, 16, 16]),\n", - " 'test_32': array([10, 10, 10, ..., 16, 16, 16]),\n", + " 'list_y_pred': {'test_16': array([ 2, 10, 10, ..., 9, 9, 9]),\n", + " 'test_32': array([10, 10, 10, ..., 16, 9, 9]),\n", " 'test_64': array([10, 10, 10, ..., 16, 16, 9]),\n", - " 'test_128': array([10, 10, 10, ..., 16, 16, 4]),\n", - " 'test_256': array([10, 10, 10, ..., 16, 16, 4]),\n", - " 'test_512': array([10, 10, 10, ..., 16, 16, 4]),\n", - " 'test_1024': array([10, 10, 10, ..., 16, 16, 4]),\n", + " 'test_128': array([10, 10, 10, ..., 16, 16, 9]),\n", + " 'test_256': array([10, 10, 10, ..., 9, 16, 9]),\n", + " 'test_512': array([10, 10, 10, ..., 9, 9, 9]),\n", + " 'test_1024': array([10, 10, 10, ..., 9, 9, 9]),\n", " 'test_2048': array([10, 10, 10, ..., 4, 4, 4])},\n", - " 'list_y_pred_prob': {'test_16': array([[2.25036541e-08, 1.59319331e-08, 7.12765038e-01, ...,\n", - " 1.61606835e-15, 1.60195451e-11, 6.51106426e-12],\n", - " [1.12693792e-08, 1.00292565e-08, 3.59571457e-01, ...,\n", - " 7.03122050e-16, 1.04496871e-11, 2.75063652e-12],\n", - " [4.90805263e-09, 8.69607675e-09, 1.63296819e-01, ...,\n", - " 4.04045198e-16, 6.62093123e-12, 1.09376301e-13],\n", + " 'list_y_pred_prob': {'test_16': array([[3.10798711e-08, 9.77926295e-10, 6.66719139e-01, ...,\n", + " 2.40659895e-13, 1.65955596e-10, 1.63193244e-11],\n", + " [4.91363856e-08, 9.43447653e-10, 4.34738308e-01, ...,\n", + " 1.00472385e-13, 7.36060449e-11, 6.45256288e-12],\n", + " [5.20331085e-08, 1.17464460e-09, 3.07417154e-01, ...,\n", + " 3.97796250e-14, 1.13535549e-10, 9.48870583e-12],\n", " ...,\n", - " [4.79737317e-08, 2.95024932e-07, 7.64573684e-08, ...,\n", - " 6.54365795e-06, 5.42017688e-06, 3.17615265e-13],\n", - " [1.05668619e-07, 4.74471705e-07, 5.34008564e-07, ...,\n", - " 9.79731158e-06, 1.81264804e-05, 2.92739639e-12],\n", - " [4.51409186e-08, 1.61229678e-07, 4.03100664e-08, ...,\n", - " 8.22649724e-07, 8.89100306e-07, 5.12760678e-13]], dtype=float32),\n", - " 'test_32': array([[3.8386765e-09, 1.6599775e-09, 5.3017844e-02, ..., 4.6765711e-16,\n", - " 2.3733562e-11, 1.1642967e-13],\n", - " [2.0756672e-09, 9.7654707e-10, 9.9263266e-02, ..., 5.6599026e-17,\n", - " 8.3000039e-12, 3.1606509e-14],\n", - " [9.1862035e-10, 7.2415229e-10, 5.8238029e-02, ..., 7.0170532e-17,\n", - " 1.1834962e-12, 4.7611485e-15],\n", + " [6.11144685e-07, 2.35200696e-06, 9.37113942e-09, ...,\n", + " 1.12029640e-02, 8.28409611e-06, 9.70139876e-13],\n", + " [6.90907655e-06, 1.01774413e-05, 7.86757752e-08, ...,\n", + " 6.05569817e-02, 1.76584581e-04, 7.16094850e-10],\n", + " [2.40956433e-06, 6.15837962e-06, 3.26743894e-08, ...,\n", + " 9.06375702e-03, 2.54869283e-05, 1.83662634e-11]], dtype=float32),\n", + " 'test_32': array([[6.6098091e-09, 3.2093112e-10, 9.4147317e-02, ..., 2.5421124e-14,\n", + " 2.6781405e-11, 1.1546815e-13],\n", + " [2.4389384e-09, 9.8992765e-11, 9.4884701e-02, ..., 2.0070413e-14,\n", + " 1.0186485e-11, 2.0824798e-14],\n", + " [1.6794000e-09, 7.2800176e-11, 7.2923362e-02, ..., 7.3797669e-15,\n", + " 1.3543646e-11, 3.0314838e-14],\n", " ...,\n", - " [5.0267830e-09, 7.0427454e-08, 7.2136621e-09, ..., 1.4572616e-07,\n", - " 4.9417810e-07, 1.4920079e-14],\n", - " [2.2638618e-08, 1.1191630e-07, 6.0815758e-08, ..., 2.8610759e-07,\n", - " 1.3633897e-06, 1.1645317e-12],\n", - " [7.7176523e-09, 4.0352930e-08, 1.4901174e-09, ..., 4.5458232e-10,\n", - " 3.2188990e-07, 3.7017720e-15]], dtype=float32),\n", - " 'test_64': array([[6.81565859e-10, 2.17162038e-10, 6.62326859e-03, ...,\n", - " 1.32542710e-15, 1.29616925e-11, 4.84135181e-16],\n", - " [4.84144502e-10, 1.38541553e-10, 1.14019904e-02, ...,\n", - " 2.20114839e-16, 2.89908375e-12, 3.24178832e-16],\n", - " [3.10426046e-10, 1.51832741e-10, 4.90172720e-03, ...,\n", - " 1.19321743e-15, 2.21813995e-12, 1.06845080e-16],\n", + " [3.9890904e-07, 1.4002244e-06, 5.1577342e-09, ..., 2.7861958e-03,\n", + " 8.6796717e-06, 4.1626715e-13],\n", + " [2.1136386e-06, 6.8242498e-06, 3.4663682e-08, ..., 4.9159233e-03,\n", + " 8.2602135e-05, 6.3698567e-11],\n", + " [1.3691432e-05, 8.7142194e-05, 7.6773631e-08, ..., 1.1446224e-01,\n", + " 2.9156043e-03, 9.1898039e-13]], dtype=float32),\n", + " 'test_64': array([[2.9683949e-09, 1.5364029e-10, 9.6971523e-03, ..., 3.0030225e-14,\n", + " 2.1287423e-11, 3.0741771e-15],\n", + " [1.0771174e-09, 5.1340109e-11, 2.3114240e-02, ..., 3.0001126e-15,\n", + " 7.2079378e-12, 1.4265962e-15],\n", + " [7.5845069e-10, 2.6632793e-11, 7.7615860e-03, ..., 3.2149860e-15,\n", + " 9.5431527e-12, 9.5286008e-16],\n", " ...,\n", - 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" 9.841422e-04\n", - " 2.958202e-07\n", - " 1.792967e-08\n", - " ...\n", - " 6.007637e-03\n", - " 5.717065e-05\n", - " 3.200329e-02\n", - " 1.978280e-07\n", - " 9.052249e-12\n", - " 5.383668e-12\n", - " 4.943644e-11\n", - " 9.055643e-12\n", - " 1.863604e-11\n", + " 4.026390e-08\n", + " 1.432371e-08\n", + " 7.677610e-01\n", + " 2.010072e-05\n", + " 2.685211e-07\n", + " 0.000026\n", + " 1.448140e-03\n", + " 5.071882e-03\n", + " 9.630448e-09\n", + " 5.542032e-07\n", + " ...\n", + " 2.045172e-03\n", + " 7.862778e-03\n", + " 3.332013e-04\n", + " 1.000665e-09\n", + " 2.312153e-13\n", + " 5.750874e-09\n", + " 3.508439e-10\n", + " 1.985661e-10\n", + " 9.313254e-10\n", " 16\n", " \n", " \n", " aid_ZTF17aaafiww\n", - " 7.117184e-07\n", - " 1.195200e-06\n", - " 1.138317e-01\n", - " 6.683926e-04\n", - " 4.178472e-07\n", - " 2.024582e-03\n", - " 1.862203e-01\n", - " 6.122197e-03\n", - " 4.356779e-07\n", - " 2.656667e-08\n", - " ...\n", - " 3.531788e-02\n", - " 1.379247e-04\n", - " 1.827683e-01\n", - " 1.291719e-07\n", - " 2.847051e-11\n", - " 4.998724e-11\n", - " 5.284293e-11\n", - " 1.509592e-11\n", - " 1.255970e-11\n", + " 2.984908e-08\n", + " 3.914010e-08\n", + " 1.588708e-01\n", + " 5.051553e-05\n", + " 2.601572e-07\n", + " 0.000728\n", + " 2.108612e-02\n", + " 2.492834e-02\n", + " 6.615269e-08\n", + " 8.534976e-08\n", + " ...\n", + " 5.351029e-02\n", + " 5.957882e-02\n", + " 2.909251e-02\n", + " 1.900539e-08\n", + " 5.943157e-13\n", + " 2.931560e-09\n", + " 6.628973e-12\n", + " 3.339336e-09\n", + " 2.140507e-10\n", " 16\n", " \n", " \n", @@ -1767,122 +1767,122 @@ " \n", " \n", " aid_ZTF23aamapva\n", - " 1.186610e-08\n", - " 1.798361e-08\n", - " 2.366297e-04\n", - " 9.406322e-06\n", - " 2.760711e-07\n", - " 3.515526e-05\n", - " 2.384690e-04\n", - " 1.500212e-04\n", - " 1.787178e-08\n", - " 3.089528e-08\n", - " ...\n", - " 2.016888e-05\n", - " 9.975308e-01\n", - " 9.077899e-04\n", - " 1.602874e-09\n", - " 2.182447e-10\n", - " 4.467815e-09\n", - " 6.735935e-11\n", - " 9.495538e-12\n", - " 1.099248e-14\n", + " 4.181310e-09\n", + " 1.263017e-08\n", + " 2.118022e-04\n", + " 6.018315e-07\n", + " 5.342381e-07\n", + " 0.000029\n", + " 2.892455e-04\n", + " 5.389011e-03\n", + " 2.175925e-09\n", + " 1.730630e-08\n", + " ...\n", + " 9.476592e-06\n", + " 9.918454e-01\n", + " 4.205109e-04\n", + " 1.568124e-11\n", + " 9.512014e-16\n", + " 3.274003e-12\n", + " 7.289479e-11\n", + " 3.525165e-11\n", + " 9.182544e-15\n", " 2048\n", " \n", " \n", " aid_ZTF23aamsarj\n", - " 1.286383e-08\n", - " 3.611422e-10\n", - " 1.314778e-11\n", - " 2.048244e-11\n", - " 3.903220e-01\n", - " 1.097102e-06\n", - " 1.648321e-10\n", - " 7.389454e-10\n", - " 2.429120e-08\n", - " 5.262062e-01\n", - " ...\n", - " 2.392706e-09\n", - " 8.783977e-16\n", - " 8.645269e-12\n", - " 8.288138e-02\n", - " 3.892453e-11\n", - " 2.512558e-15\n", - " 2.896678e-07\n", - " 5.888823e-04\n", - " 5.204326e-08\n", + " 5.385992e-07\n", + " 1.198062e-07\n", + " 6.480413e-10\n", + " 5.330119e-09\n", + " 5.889830e-01\n", + " 0.000221\n", + " 1.462704e-09\n", + " 2.542274e-09\n", + " 2.813249e-09\n", + " 1.856505e-01\n", + " ...\n", + " 2.114202e-08\n", + " 2.077348e-11\n", + " 3.960844e-10\n", + " 1.943815e-01\n", + " 1.305569e-09\n", + " 2.173053e-11\n", + " 8.305863e-07\n", + " 3.076299e-02\n", + " 1.057365e-08\n", " 2048\n", " \n", " \n", " aid_ZTF23aamxeoe\n", - " 3.386728e-05\n", - " 1.078955e-05\n", - " 7.328642e-07\n", - " 7.241946e-06\n", - " 4.067907e-02\n", - " 6.034368e-04\n", - " 2.455969e-06\n", - " 2.316802e-05\n", - " 5.819775e-05\n", - " 1.381296e-02\n", - " ...\n", - " 3.807175e-06\n", - " 2.682819e-04\n", - " 2.543781e-05\n", - " 4.250031e-02\n", - " 1.091669e-03\n", - " 3.152300e-04\n", - " 2.685083e-09\n", - " 9.005545e-01\n", - " 1.814302e-07\n", + " 8.068393e-05\n", + " 5.983785e-06\n", + " 7.539505e-09\n", + " 1.492593e-08\n", + " 1.195626e-02\n", + " 0.000263\n", + " 4.567974e-08\n", + " 8.425167e-09\n", + " 3.112131e-06\n", + " 6.306412e-03\n", + " ...\n", + " 5.999429e-08\n", + " 5.794033e-08\n", + " 3.406927e-09\n", + " 3.346236e-03\n", + " 4.006599e-06\n", + " 1.348790e-02\n", + " 8.883385e-13\n", + " 9.645457e-01\n", + " 7.997967e-12\n", " 2048\n", " \n", " \n", " aid_ZTF23aavxvsz\n", - " 3.778205e-06\n", - " 8.422126e-10\n", - " 8.736874e-09\n", - " 1.739107e-06\n", - " 9.999747e-01\n", - " 5.686213e-07\n", - " 1.585011e-09\n", - " 1.120279e-05\n", - " 3.559878e-06\n", - " 3.439323e-06\n", - " ...\n", - " 1.174480e-07\n", - " 1.147911e-10\n", - " 4.993214e-09\n", - " 7.218021e-07\n", - " 2.341318e-12\n", - " 1.684124e-10\n", - " 4.938208e-16\n", - " 6.687939e-13\n", - " 3.652639e-13\n", + " 1.091022e-05\n", + " 5.176812e-09\n", + " 1.669908e-07\n", + " 2.023352e-05\n", + " 9.989874e-01\n", + " 0.000008\n", + " 1.167655e-07\n", + " 6.753847e-07\n", + " 5.292416e-07\n", + " 4.464981e-04\n", + " ...\n", + " 3.871229e-07\n", + " 1.419517e-09\n", + " 4.592388e-09\n", + " 5.190494e-04\n", + " 4.327620e-13\n", + " 6.320568e-09\n", + " 6.786933e-10\n", + " 1.153693e-09\n", + " 2.832600e-07\n", " 2048\n", " \n", " \n", " aid_ZTF23abcvqkd\n", - " 2.928055e-09\n", - " 1.965867e-08\n", - " 3.203181e-09\n", - " 5.603876e-07\n", - " 7.919722e-01\n", - " 1.796433e-01\n", - " 7.240098e-09\n", - " 8.246809e-09\n", - " 6.385676e-09\n", - " 2.031615e-02\n", - " ...\n", - " 2.604541e-08\n", - " 9.888087e-11\n", - " 2.729801e-09\n", - " 8.060870e-03\n", - " 2.538190e-08\n", - " 2.577305e-15\n", - " 2.147994e-09\n", - " 6.840544e-06\n", - " 6.109169e-13\n", + " 1.265264e-08\n", + " 2.569692e-09\n", + " 1.867041e-08\n", + " 2.627096e-08\n", + " 9.878600e-01\n", + " 0.002412\n", + " 1.902094e-11\n", + " 1.527208e-09\n", + " 1.633408e-09\n", + " 4.520640e-03\n", + " ...\n", + " 4.364069e-11\n", + " 8.876017e-12\n", + " 3.556990e-11\n", + " 4.941329e-03\n", + " 1.186543e-08\n", + " 4.529787e-10\n", + " 2.317189e-04\n", + " 3.422047e-05\n", + " 1.350913e-11\n", " 2048\n", " \n", " \n", @@ -1892,69 +1892,69 @@ ], "text/plain": [ " AGN QSO EA YSO \\\n", - "aid_ZTF17aaaecgi 3.783888e-08 2.990278e-08 2.469852e-01 5.272037e-02 \n", - "aid_ZTF17aaaedvi 3.238366e-09 1.142967e-10 4.633469e-06 1.969472e-03 \n", - "aid_ZTF17aaafglk 3.169426e-06 4.660539e-05 1.999612e-02 1.402663e-04 \n", - "aid_ZTF17aaafiut 5.900078e-07 4.254084e-07 7.503064e-01 8.402268e-04 \n", - "aid_ZTF17aaafiww 7.117184e-07 1.195200e-06 1.138317e-01 6.683926e-04 \n", + "aid_ZTF17aaaecgi 8.734759e-08 1.407601e-09 2.705836e-01 3.345798e-03 \n", + "aid_ZTF17aaaedvi 1.395941e-07 1.308934e-09 2.133583e-06 1.702210e-03 \n", + "aid_ZTF17aaafglk 3.056342e-06 4.072757e-05 1.821813e-02 2.970178e-04 \n", + "aid_ZTF17aaafiut 4.026390e-08 1.432371e-08 7.677610e-01 2.010072e-05 \n", + "aid_ZTF17aaafiww 2.984908e-08 3.914010e-08 1.588708e-01 5.051553e-05 \n", "... ... ... ... ... \n", - "aid_ZTF23aamapva 1.186610e-08 1.798361e-08 2.366297e-04 9.406322e-06 \n", - "aid_ZTF23aamsarj 1.286383e-08 3.611422e-10 1.314778e-11 2.048244e-11 \n", - "aid_ZTF23aamxeoe 3.386728e-05 1.078955e-05 7.328642e-07 7.241946e-06 \n", - "aid_ZTF23aavxvsz 3.778205e-06 8.422126e-10 8.736874e-09 1.739107e-06 \n", - "aid_ZTF23abcvqkd 2.928055e-09 1.965867e-08 3.203181e-09 5.603876e-07 \n", + "aid_ZTF23aamapva 4.181310e-09 1.263017e-08 2.118022e-04 6.018315e-07 \n", + "aid_ZTF23aamsarj 5.385992e-07 1.198062e-07 6.480413e-10 5.330119e-09 \n", + "aid_ZTF23aamxeoe 8.068393e-05 5.983785e-06 7.539505e-09 1.492593e-08 \n", + "aid_ZTF23aavxvsz 1.091022e-05 5.176812e-09 1.669908e-07 2.023352e-05 \n", + "aid_ZTF23abcvqkd 1.265264e-08 2.569692e-09 1.867041e-08 2.627096e-08 \n", "\n", - " SNIa CV/Nova RRLc RSCVn \\\n", - "aid_ZTF17aaaecgi 2.912675e-08 6.220062e-04 7.556477e-03 4.478647e-06 \n", - "aid_ZTF17aaaedvi 1.432070e-07 8.496283e-05 9.417404e-08 1.795533e-06 \n", - "aid_ZTF17aaafglk 1.363488e-05 5.149657e-01 1.438164e-01 1.325948e-02 \n", - "aid_ZTF17aaafiut 3.846618e-07 1.485964e-03 5.472094e-02 9.841422e-04 \n", - "aid_ZTF17aaafiww 4.178472e-07 2.024582e-03 1.862203e-01 6.122197e-03 \n", - "... ... ... ... ... \n", - "aid_ZTF23aamapva 2.760711e-07 3.515526e-05 2.384690e-04 1.500212e-04 \n", - "aid_ZTF23aamsarj 3.903220e-01 1.097102e-06 1.648321e-10 7.389454e-10 \n", - "aid_ZTF23aamxeoe 4.067907e-02 6.034368e-04 2.455969e-06 2.316802e-05 \n", - "aid_ZTF23aavxvsz 9.999747e-01 5.686213e-07 1.585011e-09 1.120279e-05 \n", - "aid_ZTF23abcvqkd 7.919722e-01 1.796433e-01 7.240098e-09 8.246809e-09 \n", + " SNIa CV/Nova RRLc RSCVn \\\n", + "aid_ZTF17aaaecgi 5.370557e-08 0.000115 1.061276e-02 5.166276e-06 \n", + "aid_ZTF17aaaedvi 9.016076e-09 0.000019 1.206806e-07 1.360398e-06 \n", + "aid_ZTF17aaafglk 1.978512e-05 0.905396 2.057924e-03 1.030598e-02 \n", + "aid_ZTF17aaafiut 2.685211e-07 0.000026 1.448140e-03 5.071882e-03 \n", + "aid_ZTF17aaafiww 2.601572e-07 0.000728 2.108612e-02 2.492834e-02 \n", + "... ... ... ... ... \n", + "aid_ZTF23aamapva 5.342381e-07 0.000029 2.892455e-04 5.389011e-03 \n", + "aid_ZTF23aamsarj 5.889830e-01 0.000221 1.462704e-09 2.542274e-09 \n", + "aid_ZTF23aamxeoe 1.195626e-02 0.000263 4.567974e-08 8.425167e-09 \n", + "aid_ZTF23aavxvsz 9.989874e-01 0.000008 1.167655e-07 6.753847e-07 \n", + "aid_ZTF23abcvqkd 9.878600e-01 0.002412 1.902094e-11 1.527208e-09 \n", "\n", " Blazar SNII ... RRLab \\\n", - "aid_ZTF17aaaecgi 2.474159e-07 7.204235e-09 ... 1.767628e-03 \n", - "aid_ZTF17aaaedvi 4.388375e-09 2.583576e-09 ... 4.505413e-06 \n", - "aid_ZTF17aaafglk 1.891703e-05 2.014442e-07 ... 7.325791e-02 \n", - "aid_ZTF17aaafiut 2.958202e-07 1.792967e-08 ... 6.007637e-03 \n", - "aid_ZTF17aaafiww 4.356779e-07 2.656667e-08 ... 3.531788e-02 \n", + "aid_ZTF17aaaecgi 4.123581e-08 5.541094e-08 ... 7.465251e-04 \n", + "aid_ZTF17aaaedvi 2.353499e-08 1.064553e-08 ... 1.240696e-06 \n", + "aid_ZTF17aaafglk 6.650857e-04 9.648635e-06 ... 4.563576e-03 \n", + "aid_ZTF17aaafiut 9.630448e-09 5.542032e-07 ... 2.045172e-03 \n", + "aid_ZTF17aaafiww 6.615269e-08 8.534976e-08 ... 5.351029e-02 \n", "... ... ... ... ... \n", - "aid_ZTF23aamapva 1.787178e-08 3.089528e-08 ... 2.016888e-05 \n", - "aid_ZTF23aamsarj 2.429120e-08 5.262062e-01 ... 2.392706e-09 \n", - "aid_ZTF23aamxeoe 5.819775e-05 1.381296e-02 ... 3.807175e-06 \n", - "aid_ZTF23aavxvsz 3.559878e-06 3.439323e-06 ... 1.174480e-07 \n", - "aid_ZTF23abcvqkd 6.385676e-09 2.031615e-02 ... 2.604541e-08 \n", + "aid_ZTF23aamapva 2.175925e-09 1.730630e-08 ... 9.476592e-06 \n", + "aid_ZTF23aamsarj 2.813249e-09 1.856505e-01 ... 2.114202e-08 \n", + "aid_ZTF23aamxeoe 3.112131e-06 6.306412e-03 ... 5.999429e-08 \n", + "aid_ZTF23aavxvsz 5.292416e-07 4.464981e-04 ... 3.871229e-07 \n", + "aid_ZTF23abcvqkd 1.633408e-09 4.520640e-03 ... 4.364069e-11 \n", "\n", " Periodic-Other DSCT SNIbc SLSN \\\n", - "aid_ZTF17aaaecgi 1.207905e-08 4.354644e-03 4.138566e-08 3.602729e-14 \n", - "aid_ZTF17aaaedvi 9.139235e-07 1.508509e-06 3.459949e-08 3.552144e-15 \n", - "aid_ZTF17aaafglk 1.748643e-02 1.794822e-01 4.189199e-08 1.278961e-08 \n", - "aid_ZTF17aaafiut 5.717065e-05 3.200329e-02 1.978280e-07 9.052249e-12 \n", - "aid_ZTF17aaafiww 1.379247e-04 1.827683e-01 1.291719e-07 2.847051e-11 \n", + "aid_ZTF17aaaecgi 8.544342e-08 1.774296e-02 1.197233e-10 1.062761e-12 \n", + "aid_ZTF17aaaedvi 1.478997e-06 2.318487e-06 1.846779e-09 7.985744e-11 \n", + "aid_ZTF17aaafglk 1.757647e-02 3.163386e-03 3.280139e-05 3.922877e-11 \n", + "aid_ZTF17aaafiut 7.862778e-03 3.332013e-04 1.000665e-09 2.312153e-13 \n", + "aid_ZTF17aaafiww 5.957882e-02 2.909251e-02 1.900539e-08 5.943157e-13 \n", "... ... ... ... ... \n", - "aid_ZTF23aamapva 9.975308e-01 9.077899e-04 1.602874e-09 2.182447e-10 \n", - "aid_ZTF23aamsarj 8.783977e-16 8.645269e-12 8.288138e-02 3.892453e-11 \n", - "aid_ZTF23aamxeoe 2.682819e-04 2.543781e-05 4.250031e-02 1.091669e-03 \n", - "aid_ZTF23aavxvsz 1.147911e-10 4.993214e-09 7.218021e-07 2.341318e-12 \n", - "aid_ZTF23abcvqkd 9.888087e-11 2.729801e-09 8.060870e-03 2.538190e-08 \n", + "aid_ZTF23aamapva 9.918454e-01 4.205109e-04 1.568124e-11 9.512014e-16 \n", + "aid_ZTF23aamsarj 2.077348e-11 3.960844e-10 1.943815e-01 1.305569e-09 \n", + "aid_ZTF23aamxeoe 5.794033e-08 3.406927e-09 3.346236e-03 4.006599e-06 \n", + "aid_ZTF23aavxvsz 1.419517e-09 4.592388e-09 5.190494e-04 4.327620e-13 \n", + "aid_ZTF23abcvqkd 8.876017e-12 3.556990e-11 4.941329e-03 1.186543e-08 \n", "\n", " TDE SNIIb SNIIn Microlensing \\\n", - "aid_ZTF17aaaecgi 1.656356e-13 2.268488e-14 6.568335e-11 6.807763e-12 \n", - "aid_ZTF17aaaedvi 6.243331e-16 6.049508e-14 4.106425e-10 1.207059e-12 \n", - "aid_ZTF17aaafglk 2.426521e-09 2.992940e-07 2.336303e-10 1.788384e-11 \n", - "aid_ZTF17aaafiut 5.383668e-12 4.943644e-11 9.055643e-12 1.863604e-11 \n", - "aid_ZTF17aaafiww 4.998724e-11 5.284293e-11 1.509592e-11 1.255970e-11 \n", + "aid_ZTF17aaaecgi 3.664195e-10 9.733188e-14 9.460005e-10 1.274848e-11 \n", + "aid_ZTF17aaaedvi 3.413673e-15 1.132434e-14 1.273071e-11 7.031770e-13 \n", + "aid_ZTF17aaafglk 3.831226e-07 8.830703e-06 2.697534e-08 6.710195e-10 \n", + "aid_ZTF17aaafiut 5.750874e-09 3.508439e-10 1.985661e-10 9.313254e-10 \n", + "aid_ZTF17aaafiww 2.931560e-09 6.628973e-12 3.339336e-09 2.140507e-10 \n", "... ... ... ... ... \n", - "aid_ZTF23aamapva 4.467815e-09 6.735935e-11 9.495538e-12 1.099248e-14 \n", - "aid_ZTF23aamsarj 2.512558e-15 2.896678e-07 5.888823e-04 5.204326e-08 \n", - "aid_ZTF23aamxeoe 3.152300e-04 2.685083e-09 9.005545e-01 1.814302e-07 \n", - "aid_ZTF23aavxvsz 1.684124e-10 4.938208e-16 6.687939e-13 3.652639e-13 \n", - "aid_ZTF23abcvqkd 2.577305e-15 2.147994e-09 6.840544e-06 6.109169e-13 \n", + "aid_ZTF23aamapva 3.274003e-12 7.289479e-11 3.525165e-11 9.182544e-15 \n", + "aid_ZTF23aamsarj 2.173053e-11 8.305863e-07 3.076299e-02 1.057365e-08 \n", + "aid_ZTF23aamxeoe 1.348790e-02 8.883385e-13 9.645457e-01 7.997967e-12 \n", + "aid_ZTF23aavxvsz 6.320568e-09 6.786933e-10 1.153693e-09 2.832600e-07 \n", + "aid_ZTF23abcvqkd 4.529787e-10 2.317189e-04 3.422047e-05 1.350913e-11 \n", "\n", " shorten \n", "aid_ZTF17aaaecgi 16 \n", @@ -1996,7 +1996,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 39, "metadata": {}, "outputs": [ { @@ -2046,123 +2046,123 @@ " \n", " \n", " aid_ZTF18adldhip\n", - " 5.977352e-01\n", - " 3.872492e-01\n", - " 1.107174e-06\n", - " 3.871850e-05\n", - " 3.723242e-06\n", - " 0.000010\n", - " 0.000008\n", - " 0.000044\n", - " 1.465253e-02\n", - " 1.964378e-05\n", - " ...\n", - " 8.341117e-06\n", - " 2.698502e-07\n", - " 2.116412e-04\n", - " 3.084909e-07\n", - " 1.887804e-10\n", - " 8.844911e-06\n", - " 6.748026e-09\n", - " 1.274929e-14\n", - " 4.879291e-07\n", - " 8.376805e-13\n", + " 7.662808e-01\n", + " 2.302854e-01\n", + " 2.135166e-06\n", + " 8.777586e-06\n", + " 3.968655e-05\n", + " 1.624198e-06\n", + " 0.000007\n", + " 0.000051\n", + " 3.216724e-03\n", + " 5.469867e-06\n", + " ...\n", + " 3.527732e-07\n", + " 1.925852e-07\n", + " 9.147311e-05\n", + " 1.255014e-07\n", + " 2.337902e-10\n", + " 5.576798e-08\n", + " 5.452343e-11\n", + " 2.326913e-12\n", + " 2.565360e-06\n", + " 1.319690e-12\n", " \n", " \n", " aid_ZTF19aasbgeb\n", - " 2.370005e-02\n", - " 9.710051e-01\n", - " 6.736502e-07\n", - " 1.273473e-08\n", - " 2.423555e-07\n", - " 0.000011\n", - " 0.000007\n", - " 0.000007\n", - " 5.185777e-03\n", - " 2.574916e-07\n", - " ...\n", - " 4.936215e-07\n", - " 1.301937e-06\n", - " 7.640776e-05\n", - " 5.403183e-08\n", - " 2.797893e-12\n", - " 6.822924e-09\n", - " 6.783772e-13\n", - " 1.067869e-17\n", - " 1.556580e-14\n", - " 1.700963e-14\n", + " 6.837122e-02\n", + " 9.115803e-01\n", + " 1.541445e-07\n", + " 2.458813e-08\n", + " 5.301221e-06\n", + " 4.138591e-06\n", + " 0.000002\n", + " 0.000003\n", + " 2.003026e-02\n", + " 3.791978e-07\n", + " ...\n", + " 4.490822e-07\n", + " 1.678800e-07\n", + " 1.016612e-06\n", + " 2.264868e-09\n", + " 5.275978e-11\n", + " 1.065876e-07\n", + " 5.029582e-14\n", + " 9.001673e-19\n", + " 1.766668e-08\n", + " 1.659098e-13\n", " \n", " \n", " aid_ZTF18aayfbqd\n", - " 9.952188e-09\n", - " 2.289016e-09\n", - " 2.192825e-02\n", - " 4.871189e-02\n", - " 7.893466e-08\n", - " 0.000039\n", - " 0.000021\n", - " 0.000007\n", - " 5.177173e-09\n", - " 1.526923e-09\n", - " ...\n", - " 6.743795e-03\n", - " 3.335706e-05\n", - " 1.242031e-07\n", - " 5.098335e-04\n", - " 6.606086e-10\n", - " 2.130183e-14\n", - " 7.762069e-15\n", - " 6.496083e-17\n", - " 7.613947e-13\n", - " 3.685712e-10\n", + " 6.480014e-07\n", + " 1.487578e-08\n", + " 4.245125e-02\n", + " 1.287331e-01\n", + " 1.339784e-06\n", + " 4.053475e-05\n", + " 0.000005\n", + " 0.000002\n", + " 2.373365e-07\n", + " 3.675865e-07\n", + " ...\n", + " 5.083823e-03\n", + " 9.649606e-06\n", + " 1.928383e-08\n", + " 3.228328e-04\n", + " 5.042488e-11\n", + " 1.650578e-10\n", + " 1.062287e-14\n", + " 3.683753e-14\n", + " 3.239082e-10\n", + " 5.906374e-10\n", " \n", " \n", " aid_ZTF19ablyzbl\n", - " 5.933915e-03\n", - " 9.928526e-01\n", - " 7.266677e-07\n", - " 5.203926e-08\n", - " 1.401431e-07\n", - " 0.000014\n", + " 1.204574e-03\n", + " 9.978087e-01\n", + " 5.264712e-06\n", + " 7.434112e-08\n", + " 3.825059e-06\n", + " 1.422980e-05\n", " 0.000001\n", - " 0.000013\n", - " 1.147492e-03\n", - " 1.938178e-07\n", - " ...\n", - " 2.048160e-07\n", - " 2.750080e-07\n", - " 3.496896e-05\n", - " 1.479354e-08\n", - " 1.388321e-12\n", - " 2.085207e-09\n", - " 1.140966e-12\n", - " 2.251577e-15\n", - " 2.687552e-14\n", - " 3.431098e-14\n", + " 0.000033\n", + " 8.681483e-04\n", + " 3.040604e-08\n", + " ...\n", + " 1.208527e-07\n", + " 8.290508e-08\n", + " 2.975309e-05\n", + " 4.032183e-07\n", + " 4.406051e-12\n", + " 4.773867e-08\n", + " 2.522890e-15\n", + " 2.287262e-14\n", + " 2.319044e-06\n", + " 8.565737e-14\n", " \n", " \n", " aid_ZTF18actabfv\n", - " 4.889991e-07\n", - " 1.195225e-07\n", - " 4.422271e-04\n", - " 9.894094e-01\n", - " 1.853139e-06\n", - " 0.000543\n", - " 0.000041\n", - " 0.004995\n", - " 2.345706e-06\n", - " 9.853366e-10\n", - " ...\n", - " 7.343927e-04\n", - " 7.784962e-06\n", - " 1.858886e-03\n", - " 7.208555e-04\n", - " 1.019229e-10\n", - " 1.032331e-13\n", - " 1.734912e-13\n", - " 1.552963e-17\n", - " 1.296955e-13\n", - " 5.580757e-14\n", + " 7.135151e-07\n", + " 4.221016e-07\n", + " 3.216647e-04\n", + " 9.701920e-01\n", + " 6.664713e-07\n", + " 5.991121e-04\n", + " 0.000001\n", + " 0.027185\n", + " 1.776524e-06\n", + " 1.188521e-08\n", + " ...\n", + " 4.290823e-04\n", + " 1.584599e-07\n", + " 8.540230e-04\n", + " 5.695262e-05\n", + " 1.002342e-08\n", + " 1.948869e-13\n", + " 1.642912e-15\n", + " 9.973729e-12\n", + " 1.388431e-10\n", + " 5.548506e-12\n", " \n", " \n", " ...\n", @@ -2190,123 +2190,123 @@ " \n", " \n", " aid_ZTF18abdlmwe\n", - " 5.342025e-10\n", - " 8.275848e-11\n", - " 3.481573e-04\n", - " 1.737459e-04\n", - " 2.246117e-08\n", + " 5.551568e-09\n", + " 3.717098e-11\n", + " 3.960089e-05\n", + " 5.888867e-05\n", + " 1.168640e-08\n", + " 2.099852e-08\n", " 0.000001\n", - " 0.000022\n", - " 0.000006\n", - " 2.274234e-10\n", - " 6.141801e-10\n", - " ...\n", - " 9.990476e-01\n", - " 1.725814e-04\n", - " 2.990018e-09\n", - " 1.420690e-07\n", - " 2.476280e-09\n", - " 1.552841e-17\n", - " 3.537669e-15\n", - " 1.297150e-13\n", - " 5.187267e-15\n", - " 2.793726e-14\n", + " 0.000001\n", + " 7.418862e-10\n", + " 4.687425e-10\n", + " ...\n", + " 9.998695e-01\n", + " 9.530114e-06\n", + " 2.042207e-08\n", + " 1.684917e-08\n", + " 1.759425e-11\n", + " 9.711904e-17\n", + " 5.353405e-15\n", + " 1.297741e-18\n", + " 1.659782e-17\n", + " 9.403529e-15\n", " \n", " \n", " aid_ZTF18abnueof\n", - " 6.535586e-09\n", - " 1.607910e-10\n", - " 1.855128e-06\n", - " 7.321076e-09\n", - " 3.049109e-08\n", - " 0.000003\n", - " 0.979362\n", - " 0.003361\n", - " 2.302132e-10\n", - " 1.725786e-08\n", - " ...\n", - " 1.054786e-02\n", - " 6.650715e-03\n", - " 5.748935e-06\n", - " 1.954671e-05\n", - " 4.381569e-09\n", - " 1.159956e-15\n", - " 3.698598e-13\n", - " 2.691933e-10\n", - " 5.435293e-14\n", - " 4.350763e-14\n", + " 5.155872e-09\n", + " 7.915794e-10\n", + " 4.318676e-06\n", + " 7.513812e-10\n", + " 4.276660e-08\n", + " 1.293100e-06\n", + " 0.985808\n", + " 0.007690\n", + " 3.709354e-08\n", + " 1.095339e-07\n", + " ...\n", + " 2.722043e-03\n", + " 2.387790e-03\n", + " 1.253581e-03\n", + " 2.343152e-05\n", + " 7.793347e-10\n", + " 4.768542e-14\n", + " 3.861496e-12\n", + " 9.916746e-13\n", + " 2.127023e-09\n", + " 1.588791e-13\n", " \n", " \n", " aid_ZTF17aaagvih\n", - " 3.240582e-06\n", - " 7.541576e-07\n", - " 2.361623e-06\n", - " 9.894028e-01\n", - " 2.004335e-07\n", - " 0.002080\n", - " 0.000007\n", - " 0.000131\n", - " 1.111277e-04\n", - " 1.902887e-08\n", - " ...\n", - " 1.722451e-03\n", - " 1.419272e-06\n", - " 1.749655e-04\n", - " 7.772013e-05\n", - " 2.383930e-13\n", - " 7.447991e-14\n", - " 1.609270e-15\n", - " 2.119021e-16\n", - " 6.981124e-12\n", - " 8.322949e-16\n", + " 9.759603e-05\n", + " 1.926013e-05\n", + " 2.006176e-05\n", + " 9.552538e-01\n", + " 2.616308e-06\n", + " 1.626736e-02\n", + " 0.000004\n", + " 0.001468\n", + " 1.371204e-04\n", + " 5.840242e-08\n", + " ...\n", + " 1.554408e-02\n", + " 6.154704e-08\n", + " 6.465749e-04\n", + " 4.263413e-05\n", + " 1.471535e-07\n", + " 1.375777e-10\n", + " 3.221115e-16\n", + " 2.619645e-14\n", + " 9.743384e-10\n", + " 1.359489e-16\n", " \n", " \n", " aid_ZTF17aabpjme\n", - " 1.943087e-09\n", - " 5.104224e-09\n", - " 4.089252e-07\n", - " 1.331407e-06\n", - " 4.517635e-10\n", - " 0.000016\n", - " 0.001762\n", - " 0.000009\n", - " 1.342651e-07\n", - " 2.281132e-10\n", - " ...\n", - " 7.575118e-03\n", - " 9.906298e-01\n", - " 1.215735e-09\n", - " 4.649451e-07\n", - " 2.486373e-10\n", - " 1.401898e-17\n", - " 1.748985e-15\n", - " 9.127245e-13\n", - " 4.505965e-15\n", - " 5.061297e-12\n", + " 1.216242e-08\n", + " 3.113583e-08\n", + " 1.452237e-04\n", + " 6.184468e-07\n", + " 2.037125e-08\n", + " 3.765304e-05\n", + " 0.000211\n", + " 0.000313\n", + " 1.994241e-07\n", + " 3.404462e-09\n", + " ...\n", + " 1.063609e-02\n", + " 9.885159e-01\n", + " 5.252316e-05\n", + " 1.454708e-05\n", + " 5.486798e-09\n", + " 1.341067e-16\n", + " 5.043624e-12\n", + " 4.172631e-13\n", + " 3.874752e-12\n", + " 5.137409e-10\n", " \n", " \n", " aid_ZTF18acrwlnr\n", - " 2.594302e-08\n", - " 3.483331e-08\n", - " 2.335759e-06\n", - " 9.975646e-01\n", - " 6.766901e-09\n", - " 0.002157\n", - " 0.000010\n", - " 0.000056\n", - " 9.284270e-06\n", - " 6.540777e-11\n", - " ...\n", - " 1.164306e-04\n", - " 5.700163e-06\n", - " 2.511957e-05\n", - " 4.367101e-05\n", - " 2.710520e-15\n", - " 1.171569e-17\n", - " 9.307659e-17\n", - " 4.531178e-19\n", - " 3.485753e-15\n", - " 3.467227e-17\n", + " 2.695775e-06\n", + " 1.156719e-06\n", + " 1.265951e-05\n", + " 9.715409e-01\n", + " 4.520578e-08\n", + " 2.712275e-02\n", + " 0.000001\n", + " 0.000504\n", + " 3.781134e-05\n", + " 2.145775e-09\n", + " ...\n", + " 5.661188e-04\n", + " 8.605761e-08\n", + " 1.004323e-04\n", + " 1.798649e-05\n", + " 1.692071e-10\n", + " 1.037704e-12\n", + " 2.636524e-17\n", + " 2.347973e-15\n", + " 9.502477e-11\n", + " 2.107070e-16\n", " \n", " \n", "\n", @@ -2315,74 +2315,74 @@ ], "text/plain": [ " AGN QSO EA YSO \\\n", - "aid_ZTF18adldhip 5.977352e-01 3.872492e-01 1.107174e-06 3.871850e-05 \n", - "aid_ZTF19aasbgeb 2.370005e-02 9.710051e-01 6.736502e-07 1.273473e-08 \n", - "aid_ZTF18aayfbqd 9.952188e-09 2.289016e-09 2.192825e-02 4.871189e-02 \n", - "aid_ZTF19ablyzbl 5.933915e-03 9.928526e-01 7.266677e-07 5.203926e-08 \n", - "aid_ZTF18actabfv 4.889991e-07 1.195225e-07 4.422271e-04 9.894094e-01 \n", + "aid_ZTF18adldhip 7.662808e-01 2.302854e-01 2.135166e-06 8.777586e-06 \n", + "aid_ZTF19aasbgeb 6.837122e-02 9.115803e-01 1.541445e-07 2.458813e-08 \n", + "aid_ZTF18aayfbqd 6.480014e-07 1.487578e-08 4.245125e-02 1.287331e-01 \n", + "aid_ZTF19ablyzbl 1.204574e-03 9.978087e-01 5.264712e-06 7.434112e-08 \n", + "aid_ZTF18actabfv 7.135151e-07 4.221016e-07 3.216647e-04 9.701920e-01 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 5.342025e-10 8.275848e-11 3.481573e-04 1.737459e-04 \n", - "aid_ZTF18abnueof 6.535586e-09 1.607910e-10 1.855128e-06 7.321076e-09 \n", - "aid_ZTF17aaagvih 3.240582e-06 7.541576e-07 2.361623e-06 9.894028e-01 \n", - "aid_ZTF17aabpjme 1.943087e-09 5.104224e-09 4.089252e-07 1.331407e-06 \n", - "aid_ZTF18acrwlnr 2.594302e-08 3.483331e-08 2.335759e-06 9.975646e-01 \n", + "aid_ZTF18abdlmwe 5.551568e-09 3.717098e-11 3.960089e-05 5.888867e-05 \n", + "aid_ZTF18abnueof 5.155872e-09 7.915794e-10 4.318676e-06 7.513812e-10 \n", + "aid_ZTF17aaagvih 9.759603e-05 1.926013e-05 2.006176e-05 9.552538e-01 \n", + "aid_ZTF17aabpjme 1.216242e-08 3.113583e-08 1.452237e-04 6.184468e-07 \n", + "aid_ZTF18acrwlnr 2.695775e-06 1.156719e-06 1.265951e-05 9.715409e-01 \n", "\n", - " SNIa CV/Nova RRLc RSCVn Blazar \\\n", - "aid_ZTF18adldhip 3.723242e-06 0.000010 0.000008 0.000044 1.465253e-02 \n", - "aid_ZTF19aasbgeb 2.423555e-07 0.000011 0.000007 0.000007 5.185777e-03 \n", - "aid_ZTF18aayfbqd 7.893466e-08 0.000039 0.000021 0.000007 5.177173e-09 \n", - "aid_ZTF19ablyzbl 1.401431e-07 0.000014 0.000001 0.000013 1.147492e-03 \n", - "aid_ZTF18actabfv 1.853139e-06 0.000543 0.000041 0.004995 2.345706e-06 \n", - "... ... ... ... ... ... \n", - "aid_ZTF18abdlmwe 2.246117e-08 0.000001 0.000022 0.000006 2.274234e-10 \n", - "aid_ZTF18abnueof 3.049109e-08 0.000003 0.979362 0.003361 2.302132e-10 \n", - "aid_ZTF17aaagvih 2.004335e-07 0.002080 0.000007 0.000131 1.111277e-04 \n", - "aid_ZTF17aabpjme 4.517635e-10 0.000016 0.001762 0.000009 1.342651e-07 \n", - "aid_ZTF18acrwlnr 6.766901e-09 0.002157 0.000010 0.000056 9.284270e-06 \n", + " SNIa CV/Nova RRLc RSCVn \\\n", + "aid_ZTF18adldhip 3.968655e-05 1.624198e-06 0.000007 0.000051 \n", + "aid_ZTF19aasbgeb 5.301221e-06 4.138591e-06 0.000002 0.000003 \n", + "aid_ZTF18aayfbqd 1.339784e-06 4.053475e-05 0.000005 0.000002 \n", + "aid_ZTF19ablyzbl 3.825059e-06 1.422980e-05 0.000001 0.000033 \n", + "aid_ZTF18actabfv 6.664713e-07 5.991121e-04 0.000001 0.027185 \n", + "... ... ... ... ... \n", + "aid_ZTF18abdlmwe 1.168640e-08 2.099852e-08 0.000001 0.000001 \n", + "aid_ZTF18abnueof 4.276660e-08 1.293100e-06 0.985808 0.007690 \n", + "aid_ZTF17aaagvih 2.616308e-06 1.626736e-02 0.000004 0.001468 \n", + "aid_ZTF17aabpjme 2.037125e-08 3.765304e-05 0.000211 0.000313 \n", + "aid_ZTF18acrwlnr 4.520578e-08 2.712275e-02 0.000001 0.000504 \n", "\n", - " SNII ... CEP RRLab \\\n", - "aid_ZTF18adldhip 1.964378e-05 ... 8.341117e-06 2.698502e-07 \n", - "aid_ZTF19aasbgeb 2.574916e-07 ... 4.936215e-07 1.301937e-06 \n", - "aid_ZTF18aayfbqd 1.526923e-09 ... 6.743795e-03 3.335706e-05 \n", - "aid_ZTF19ablyzbl 1.938178e-07 ... 2.048160e-07 2.750080e-07 \n", - "aid_ZTF18actabfv 9.853366e-10 ... 7.343927e-04 7.784962e-06 \n", - "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 6.141801e-10 ... 9.990476e-01 1.725814e-04 \n", - "aid_ZTF18abnueof 1.725786e-08 ... 1.054786e-02 6.650715e-03 \n", - "aid_ZTF17aaagvih 1.902887e-08 ... 1.722451e-03 1.419272e-06 \n", - "aid_ZTF17aabpjme 2.281132e-10 ... 7.575118e-03 9.906298e-01 \n", - "aid_ZTF18acrwlnr 6.540777e-11 ... 1.164306e-04 5.700163e-06 \n", + " Blazar SNII ... CEP RRLab \\\n", + "aid_ZTF18adldhip 3.216724e-03 5.469867e-06 ... 3.527732e-07 1.925852e-07 \n", + "aid_ZTF19aasbgeb 2.003026e-02 3.791978e-07 ... 4.490822e-07 1.678800e-07 \n", + "aid_ZTF18aayfbqd 2.373365e-07 3.675865e-07 ... 5.083823e-03 9.649606e-06 \n", + "aid_ZTF19ablyzbl 8.681483e-04 3.040604e-08 ... 1.208527e-07 8.290508e-08 \n", + "aid_ZTF18actabfv 1.776524e-06 1.188521e-08 ... 4.290823e-04 1.584599e-07 \n", + "... ... ... ... ... ... \n", + "aid_ZTF18abdlmwe 7.418862e-10 4.687425e-10 ... 9.998695e-01 9.530114e-06 \n", + "aid_ZTF18abnueof 3.709354e-08 1.095339e-07 ... 2.722043e-03 2.387790e-03 \n", + "aid_ZTF17aaagvih 1.371204e-04 5.840242e-08 ... 1.554408e-02 6.154704e-08 \n", + "aid_ZTF17aabpjme 1.994241e-07 3.404462e-09 ... 1.063609e-02 9.885159e-01 \n", + "aid_ZTF18acrwlnr 3.781134e-05 2.145775e-09 ... 5.661188e-04 8.605761e-08 \n", "\n", " Periodic-Other DSCT SNIbc SLSN \\\n", - "aid_ZTF18adldhip 2.116412e-04 3.084909e-07 1.887804e-10 8.844911e-06 \n", - "aid_ZTF19aasbgeb 7.640776e-05 5.403183e-08 2.797893e-12 6.822924e-09 \n", - "aid_ZTF18aayfbqd 1.242031e-07 5.098335e-04 6.606086e-10 2.130183e-14 \n", - "aid_ZTF19ablyzbl 3.496896e-05 1.479354e-08 1.388321e-12 2.085207e-09 \n", - "aid_ZTF18actabfv 1.858886e-03 7.208555e-04 1.019229e-10 1.032331e-13 \n", + "aid_ZTF18adldhip 9.147311e-05 1.255014e-07 2.337902e-10 5.576798e-08 \n", + "aid_ZTF19aasbgeb 1.016612e-06 2.264868e-09 5.275978e-11 1.065876e-07 \n", + "aid_ZTF18aayfbqd 1.928383e-08 3.228328e-04 5.042488e-11 1.650578e-10 \n", + "aid_ZTF19ablyzbl 2.975309e-05 4.032183e-07 4.406051e-12 4.773867e-08 \n", + "aid_ZTF18actabfv 8.540230e-04 5.695262e-05 1.002342e-08 1.948869e-13 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 2.990018e-09 1.420690e-07 2.476280e-09 1.552841e-17 \n", - "aid_ZTF18abnueof 5.748935e-06 1.954671e-05 4.381569e-09 1.159956e-15 \n", - "aid_ZTF17aaagvih 1.749655e-04 7.772013e-05 2.383930e-13 7.447991e-14 \n", - "aid_ZTF17aabpjme 1.215735e-09 4.649451e-07 2.486373e-10 1.401898e-17 \n", - "aid_ZTF18acrwlnr 2.511957e-05 4.367101e-05 2.710520e-15 1.171569e-17 \n", + "aid_ZTF18abdlmwe 2.042207e-08 1.684917e-08 1.759425e-11 9.711904e-17 \n", + "aid_ZTF18abnueof 1.253581e-03 2.343152e-05 7.793347e-10 4.768542e-14 \n", + "aid_ZTF17aaagvih 6.465749e-04 4.263413e-05 1.471535e-07 1.375777e-10 \n", + "aid_ZTF17aabpjme 5.252316e-05 1.454708e-05 5.486798e-09 1.341067e-16 \n", + "aid_ZTF18acrwlnr 1.004323e-04 1.798649e-05 1.692071e-10 1.037704e-12 \n", "\n", " TDE SNIIb SNIIn Microlensing \n", - "aid_ZTF18adldhip 6.748026e-09 1.274929e-14 4.879291e-07 8.376805e-13 \n", - "aid_ZTF19aasbgeb 6.783772e-13 1.067869e-17 1.556580e-14 1.700963e-14 \n", - "aid_ZTF18aayfbqd 7.762069e-15 6.496083e-17 7.613947e-13 3.685712e-10 \n", - "aid_ZTF19ablyzbl 1.140966e-12 2.251577e-15 2.687552e-14 3.431098e-14 \n", - "aid_ZTF18actabfv 1.734912e-13 1.552963e-17 1.296955e-13 5.580757e-14 \n", + "aid_ZTF18adldhip 5.452343e-11 2.326913e-12 2.565360e-06 1.319690e-12 \n", + "aid_ZTF19aasbgeb 5.029582e-14 9.001673e-19 1.766668e-08 1.659098e-13 \n", + "aid_ZTF18aayfbqd 1.062287e-14 3.683753e-14 3.239082e-10 5.906374e-10 \n", + "aid_ZTF19ablyzbl 2.522890e-15 2.287262e-14 2.319044e-06 8.565737e-14 \n", + "aid_ZTF18actabfv 1.642912e-15 9.973729e-12 1.388431e-10 5.548506e-12 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 3.537669e-15 1.297150e-13 5.187267e-15 2.793726e-14 \n", - "aid_ZTF18abnueof 3.698598e-13 2.691933e-10 5.435293e-14 4.350763e-14 \n", - "aid_ZTF17aaagvih 1.609270e-15 2.119021e-16 6.981124e-12 8.322949e-16 \n", - "aid_ZTF17aabpjme 1.748985e-15 9.127245e-13 4.505965e-15 5.061297e-12 \n", - "aid_ZTF18acrwlnr 9.307659e-17 4.531178e-19 3.485753e-15 3.467227e-17 \n", + "aid_ZTF18abdlmwe 5.353405e-15 1.297741e-18 1.659782e-17 9.403529e-15 \n", + "aid_ZTF18abnueof 3.861496e-12 9.916746e-13 2.127023e-09 1.588791e-13 \n", + "aid_ZTF17aaagvih 3.221115e-16 2.619645e-14 9.743384e-10 1.359489e-16 \n", + "aid_ZTF17aabpjme 5.043624e-12 4.172631e-13 3.874752e-12 5.137409e-10 \n", + "aid_ZTF18acrwlnr 2.636524e-17 2.347973e-15 9.502477e-11 2.107070e-16 \n", "\n", "[8346 rows x 22 columns]" ] }, - "execution_count": 21, + "execution_count": 39, "metadata": {}, "output_type": "execute_result" } @@ -2395,7 +2395,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 40, "metadata": {}, "outputs": [ { @@ -2445,123 +2445,123 @@ " \n", " \n", " aid_ZTF18adldhip\n", - " 5.977352e-01\n", - " 3.872492e-01\n", - " 1.107174e-06\n", - " 3.871850e-05\n", - " 3.723242e-06\n", - " 0.000010\n", - " 0.000008\n", - " 0.000044\n", - " 1.465253e-02\n", - " 1.964378e-05\n", - " ...\n", - " 8.341117e-06\n", - " 2.698502e-07\n", - " 2.116412e-04\n", - " 3.084909e-07\n", - " 1.887804e-10\n", - " 8.844911e-06\n", - " 6.748026e-09\n", - " 1.274929e-14\n", - " 4.879291e-07\n", - " 8.376805e-13\n", + " 7.662808e-01\n", + " 2.302854e-01\n", + " 2.135166e-06\n", + " 8.777586e-06\n", + " 3.968655e-05\n", + " 1.624198e-06\n", + " 0.000007\n", + " 0.000051\n", + " 3.216724e-03\n", + " 5.469867e-06\n", + " ...\n", + " 3.527732e-07\n", + " 1.925852e-07\n", + " 9.147311e-05\n", + " 1.255014e-07\n", + " 2.337902e-10\n", + " 5.576798e-08\n", + " 5.452343e-11\n", + " 2.326913e-12\n", + " 2.565360e-06\n", + " 1.319690e-12\n", " \n", " \n", " aid_ZTF19aasbgeb\n", - " 2.370005e-02\n", - " 9.710051e-01\n", - " 6.736502e-07\n", - " 1.273473e-08\n", - " 2.423555e-07\n", - " 0.000011\n", - " 0.000007\n", - " 0.000007\n", - " 5.185777e-03\n", - " 2.574916e-07\n", - " ...\n", - " 4.936215e-07\n", - " 1.301937e-06\n", - " 7.640776e-05\n", - " 5.403183e-08\n", - " 2.797893e-12\n", - " 6.822924e-09\n", - " 6.783772e-13\n", - " 1.067869e-17\n", - " 1.556580e-14\n", - " 1.700963e-14\n", + " 6.837122e-02\n", + " 9.115803e-01\n", + " 1.541445e-07\n", + " 2.458813e-08\n", + " 5.301221e-06\n", + " 4.138591e-06\n", + " 0.000002\n", + " 0.000003\n", + " 2.003026e-02\n", + " 3.791978e-07\n", + " ...\n", + " 4.490822e-07\n", + " 1.678800e-07\n", + " 1.016612e-06\n", + " 2.264868e-09\n", + " 5.275978e-11\n", + " 1.065876e-07\n", + " 5.029582e-14\n", + " 9.001673e-19\n", + " 1.766668e-08\n", + " 1.659098e-13\n", " \n", " \n", " aid_ZTF18aayfbqd\n", - " 9.952188e-09\n", - " 2.289016e-09\n", - " 2.192825e-02\n", - " 4.871189e-02\n", - " 7.893466e-08\n", - " 0.000039\n", - " 0.000021\n", - " 0.000007\n", - " 5.177173e-09\n", - " 1.526923e-09\n", - " ...\n", - " 6.743795e-03\n", - " 3.335706e-05\n", - " 1.242031e-07\n", - " 5.098335e-04\n", - " 6.606086e-10\n", - " 2.130183e-14\n", - " 7.762069e-15\n", - " 6.496083e-17\n", - " 7.613947e-13\n", - " 3.685712e-10\n", + " 6.480014e-07\n", + " 1.487578e-08\n", + " 4.245125e-02\n", + " 1.287331e-01\n", + " 1.339784e-06\n", + " 4.053475e-05\n", + " 0.000005\n", + " 0.000002\n", + " 2.373365e-07\n", + " 3.675865e-07\n", + " ...\n", + " 5.083823e-03\n", + " 9.649606e-06\n", + " 1.928383e-08\n", + " 3.228328e-04\n", + " 5.042488e-11\n", + " 1.650578e-10\n", + " 1.062287e-14\n", + " 3.683753e-14\n", + " 3.239082e-10\n", + " 5.906374e-10\n", " \n", " \n", " aid_ZTF19ablyzbl\n", - " 5.933915e-03\n", - " 9.928526e-01\n", - " 7.266677e-07\n", - " 5.203926e-08\n", - " 1.401431e-07\n", - " 0.000014\n", + " 1.204574e-03\n", + " 9.978087e-01\n", + " 5.264712e-06\n", + " 7.434112e-08\n", + " 3.825059e-06\n", + " 1.422980e-05\n", " 0.000001\n", - " 0.000013\n", - " 1.147492e-03\n", - " 1.938178e-07\n", - " ...\n", - " 2.048160e-07\n", - " 2.750080e-07\n", - " 3.496896e-05\n", - " 1.479354e-08\n", - " 1.388321e-12\n", - " 2.085207e-09\n", - " 1.140966e-12\n", - " 2.251577e-15\n", - " 2.687552e-14\n", - " 3.431098e-14\n", + " 0.000033\n", + " 8.681483e-04\n", + " 3.040604e-08\n", + " ...\n", + " 1.208527e-07\n", + " 8.290508e-08\n", + " 2.975309e-05\n", + " 4.032183e-07\n", + " 4.406051e-12\n", + " 4.773867e-08\n", + " 2.522890e-15\n", + " 2.287262e-14\n", + " 2.319044e-06\n", + " 8.565737e-14\n", " \n", " \n", " aid_ZTF18actabfv\n", - " 4.889991e-07\n", - " 1.195225e-07\n", - " 4.422271e-04\n", - " 9.894094e-01\n", - " 1.853139e-06\n", - " 0.000543\n", - " 0.000041\n", - " 0.004995\n", - " 2.345706e-06\n", - " 9.853366e-10\n", - " ...\n", - " 7.343927e-04\n", - " 7.784962e-06\n", - " 1.858886e-03\n", - " 7.208555e-04\n", - " 1.019229e-10\n", - " 1.032331e-13\n", - " 1.734912e-13\n", - " 1.552963e-17\n", - " 1.296955e-13\n", - " 5.580757e-14\n", + " 7.135151e-07\n", + " 4.221016e-07\n", + " 3.216647e-04\n", + " 9.701920e-01\n", + " 6.664713e-07\n", + " 5.991121e-04\n", + " 0.000001\n", + " 0.027185\n", + " 1.776524e-06\n", + " 1.188521e-08\n", + " ...\n", + " 4.290823e-04\n", + " 1.584599e-07\n", + " 8.540230e-04\n", + " 5.695262e-05\n", + " 1.002342e-08\n", + " 1.948869e-13\n", + " 1.642912e-15\n", + " 9.973729e-12\n", + " 1.388431e-10\n", + " 5.548506e-12\n", " \n", " \n", " ...\n", @@ -2589,123 +2589,123 @@ " \n", " \n", " aid_ZTF18abdlmwe\n", - " 5.342025e-10\n", - " 8.275848e-11\n", - " 3.481573e-04\n", - " 1.737459e-04\n", - " 2.246117e-08\n", + " 5.551568e-09\n", + " 3.717098e-11\n", + " 3.960089e-05\n", + " 5.888867e-05\n", + " 1.168640e-08\n", + " 2.099852e-08\n", + " 0.000001\n", " 0.000001\n", - " 0.000022\n", - " 0.000006\n", - " 2.274234e-10\n", - " 6.141801e-10\n", - " ...\n", - " 9.990476e-01\n", - " 1.725814e-04\n", - " 2.990018e-09\n", - " 1.420690e-07\n", - " 2.476280e-09\n", - " 1.552841e-17\n", - " 3.537669e-15\n", - " 1.297150e-13\n", - " 5.187267e-15\n", - " 2.793726e-14\n", + " 7.418862e-10\n", + " 4.687425e-10\n", + " ...\n", + " 9.998695e-01\n", + " 9.530114e-06\n", + " 2.042207e-08\n", + " 1.684917e-08\n", + " 1.759425e-11\n", + " 9.711904e-17\n", + " 5.353405e-15\n", + " 1.297741e-18\n", + " 1.659782e-17\n", + " 9.403529e-15\n", " \n", " \n", " aid_ZTF18abnueof\n", - " 6.535586e-09\n", - " 1.607910e-10\n", - " 1.855128e-06\n", - " 7.321076e-09\n", - " 3.049109e-08\n", - " 0.000003\n", - " 0.979362\n", - " 0.003361\n", - " 2.302132e-10\n", - " 1.725786e-08\n", - " ...\n", - " 1.054786e-02\n", - " 6.650715e-03\n", - " 5.748935e-06\n", - " 1.954671e-05\n", - " 4.381569e-09\n", - " 1.159956e-15\n", - " 3.698598e-13\n", - " 2.691933e-10\n", - " 5.435293e-14\n", - " 4.350763e-14\n", + " 5.155872e-09\n", + " 7.915794e-10\n", + " 4.318676e-06\n", + " 7.513812e-10\n", + " 4.276660e-08\n", + " 1.293100e-06\n", + " 0.985808\n", + " 0.007690\n", + " 3.709354e-08\n", + " 1.095339e-07\n", + " ...\n", + " 2.722043e-03\n", + " 2.387790e-03\n", + " 1.253581e-03\n", + " 2.343152e-05\n", + " 7.793347e-10\n", + " 4.768542e-14\n", + " 3.861496e-12\n", + " 9.916746e-13\n", + " 2.127023e-09\n", + " 1.588791e-13\n", " \n", " \n", " aid_ZTF17aaagvih\n", - " 3.240582e-06\n", - " 7.541576e-07\n", - " 2.361623e-06\n", - " 9.894028e-01\n", - " 2.004335e-07\n", - " 0.002080\n", - " 0.000007\n", - " 0.000131\n", - " 1.111277e-04\n", - " 1.902887e-08\n", - " ...\n", - " 1.722451e-03\n", - " 1.419272e-06\n", - " 1.749655e-04\n", - " 7.772013e-05\n", - " 2.383930e-13\n", - " 7.447991e-14\n", - " 1.609270e-15\n", - " 2.119021e-16\n", - " 6.981124e-12\n", - " 8.322949e-16\n", + " 9.759603e-05\n", + " 1.926013e-05\n", + " 2.006176e-05\n", + " 9.552538e-01\n", + " 2.616308e-06\n", + " 1.626736e-02\n", + " 0.000004\n", + " 0.001468\n", + " 1.371204e-04\n", + " 5.840242e-08\n", + " ...\n", + " 1.554408e-02\n", + " 6.154704e-08\n", + " 6.465749e-04\n", + " 4.263413e-05\n", + " 1.471535e-07\n", + " 1.375777e-10\n", + " 3.221115e-16\n", + " 2.619645e-14\n", + " 9.743384e-10\n", + " 1.359489e-16\n", " \n", " \n", " aid_ZTF17aabpjme\n", - " 1.943087e-09\n", - " 5.104224e-09\n", - " 4.089252e-07\n", - " 1.331407e-06\n", - " 4.517635e-10\n", - " 0.000016\n", - " 0.001762\n", - " 0.000009\n", - " 1.342651e-07\n", - " 2.281132e-10\n", - " ...\n", - " 7.575118e-03\n", - " 9.906298e-01\n", - " 1.215735e-09\n", - " 4.649451e-07\n", - " 2.486373e-10\n", - " 1.401898e-17\n", - " 1.748985e-15\n", - " 9.127245e-13\n", - " 4.505965e-15\n", - " 5.061297e-12\n", + " 1.216242e-08\n", + " 3.113583e-08\n", + " 1.452237e-04\n", + " 6.184468e-07\n", + " 2.037125e-08\n", + " 3.765304e-05\n", + " 0.000211\n", + " 0.000313\n", + " 1.994241e-07\n", + " 3.404462e-09\n", + " ...\n", + " 1.063609e-02\n", + " 9.885159e-01\n", + " 5.252316e-05\n", + " 1.454708e-05\n", + " 5.486798e-09\n", + " 1.341067e-16\n", + " 5.043624e-12\n", + " 4.172631e-13\n", + " 3.874752e-12\n", + " 5.137409e-10\n", " \n", " \n", " aid_ZTF18acrwlnr\n", - " 2.594302e-08\n", - " 3.483331e-08\n", - " 2.335759e-06\n", - " 9.975646e-01\n", - " 6.766901e-09\n", - " 0.002157\n", - " 0.000010\n", - " 0.000056\n", - " 9.284270e-06\n", - " 6.540777e-11\n", - " ...\n", - " 1.164306e-04\n", - " 5.700163e-06\n", - " 2.511957e-05\n", - " 4.367101e-05\n", - " 2.710520e-15\n", - " 1.171569e-17\n", - " 9.307659e-17\n", - " 4.531178e-19\n", - " 3.485753e-15\n", - " 3.467227e-17\n", + " 2.695775e-06\n", + " 1.156719e-06\n", + " 1.265951e-05\n", + " 9.715409e-01\n", + " 4.520578e-08\n", + " 2.712275e-02\n", + " 0.000001\n", + " 0.000504\n", + " 3.781134e-05\n", + " 2.145775e-09\n", + " ...\n", + " 5.661188e-04\n", + " 8.605761e-08\n", + " 1.004323e-04\n", + " 1.798649e-05\n", + " 1.692071e-10\n", + " 1.037704e-12\n", + " 2.636524e-17\n", + " 2.347973e-15\n", + " 9.502477e-11\n", + " 2.107070e-16\n", " \n", " \n", "\n", @@ -2714,74 +2714,74 @@ ], "text/plain": [ " AGN QSO EA YSO \\\n", - "aid_ZTF18adldhip 5.977352e-01 3.872492e-01 1.107174e-06 3.871850e-05 \n", - "aid_ZTF19aasbgeb 2.370005e-02 9.710051e-01 6.736502e-07 1.273473e-08 \n", - "aid_ZTF18aayfbqd 9.952188e-09 2.289016e-09 2.192825e-02 4.871189e-02 \n", - "aid_ZTF19ablyzbl 5.933915e-03 9.928526e-01 7.266677e-07 5.203926e-08 \n", - "aid_ZTF18actabfv 4.889991e-07 1.195225e-07 4.422271e-04 9.894094e-01 \n", + "aid_ZTF18adldhip 7.662808e-01 2.302854e-01 2.135166e-06 8.777586e-06 \n", + "aid_ZTF19aasbgeb 6.837122e-02 9.115803e-01 1.541445e-07 2.458813e-08 \n", + "aid_ZTF18aayfbqd 6.480014e-07 1.487578e-08 4.245125e-02 1.287331e-01 \n", + "aid_ZTF19ablyzbl 1.204574e-03 9.978087e-01 5.264712e-06 7.434112e-08 \n", + "aid_ZTF18actabfv 7.135151e-07 4.221016e-07 3.216647e-04 9.701920e-01 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 5.342025e-10 8.275848e-11 3.481573e-04 1.737459e-04 \n", - "aid_ZTF18abnueof 6.535586e-09 1.607910e-10 1.855128e-06 7.321076e-09 \n", - "aid_ZTF17aaagvih 3.240582e-06 7.541576e-07 2.361623e-06 9.894028e-01 \n", - "aid_ZTF17aabpjme 1.943087e-09 5.104224e-09 4.089252e-07 1.331407e-06 \n", - "aid_ZTF18acrwlnr 2.594302e-08 3.483331e-08 2.335759e-06 9.975646e-01 \n", + "aid_ZTF18abdlmwe 5.551568e-09 3.717098e-11 3.960089e-05 5.888867e-05 \n", + "aid_ZTF18abnueof 5.155872e-09 7.915794e-10 4.318676e-06 7.513812e-10 \n", + "aid_ZTF17aaagvih 9.759603e-05 1.926013e-05 2.006176e-05 9.552538e-01 \n", + "aid_ZTF17aabpjme 1.216242e-08 3.113583e-08 1.452237e-04 6.184468e-07 \n", + "aid_ZTF18acrwlnr 2.695775e-06 1.156719e-06 1.265951e-05 9.715409e-01 \n", "\n", - " SNIa CV/Nova RRLc RSCVn Blazar \\\n", - "aid_ZTF18adldhip 3.723242e-06 0.000010 0.000008 0.000044 1.465253e-02 \n", - "aid_ZTF19aasbgeb 2.423555e-07 0.000011 0.000007 0.000007 5.185777e-03 \n", - "aid_ZTF18aayfbqd 7.893466e-08 0.000039 0.000021 0.000007 5.177173e-09 \n", - "aid_ZTF19ablyzbl 1.401431e-07 0.000014 0.000001 0.000013 1.147492e-03 \n", - "aid_ZTF18actabfv 1.853139e-06 0.000543 0.000041 0.004995 2.345706e-06 \n", - "... ... ... ... ... ... \n", - "aid_ZTF18abdlmwe 2.246117e-08 0.000001 0.000022 0.000006 2.274234e-10 \n", - "aid_ZTF18abnueof 3.049109e-08 0.000003 0.979362 0.003361 2.302132e-10 \n", - "aid_ZTF17aaagvih 2.004335e-07 0.002080 0.000007 0.000131 1.111277e-04 \n", - "aid_ZTF17aabpjme 4.517635e-10 0.000016 0.001762 0.000009 1.342651e-07 \n", - "aid_ZTF18acrwlnr 6.766901e-09 0.002157 0.000010 0.000056 9.284270e-06 \n", + " SNIa CV/Nova RRLc RSCVn \\\n", + "aid_ZTF18adldhip 3.968655e-05 1.624198e-06 0.000007 0.000051 \n", + "aid_ZTF19aasbgeb 5.301221e-06 4.138591e-06 0.000002 0.000003 \n", + "aid_ZTF18aayfbqd 1.339784e-06 4.053475e-05 0.000005 0.000002 \n", + "aid_ZTF19ablyzbl 3.825059e-06 1.422980e-05 0.000001 0.000033 \n", + "aid_ZTF18actabfv 6.664713e-07 5.991121e-04 0.000001 0.027185 \n", + "... ... ... ... ... \n", + "aid_ZTF18abdlmwe 1.168640e-08 2.099852e-08 0.000001 0.000001 \n", + "aid_ZTF18abnueof 4.276660e-08 1.293100e-06 0.985808 0.007690 \n", + "aid_ZTF17aaagvih 2.616308e-06 1.626736e-02 0.000004 0.001468 \n", + "aid_ZTF17aabpjme 2.037125e-08 3.765304e-05 0.000211 0.000313 \n", + "aid_ZTF18acrwlnr 4.520578e-08 2.712275e-02 0.000001 0.000504 \n", "\n", - " SNII ... CEP RRLab \\\n", - "aid_ZTF18adldhip 1.964378e-05 ... 8.341117e-06 2.698502e-07 \n", - "aid_ZTF19aasbgeb 2.574916e-07 ... 4.936215e-07 1.301937e-06 \n", - "aid_ZTF18aayfbqd 1.526923e-09 ... 6.743795e-03 3.335706e-05 \n", - "aid_ZTF19ablyzbl 1.938178e-07 ... 2.048160e-07 2.750080e-07 \n", - "aid_ZTF18actabfv 9.853366e-10 ... 7.343927e-04 7.784962e-06 \n", - "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 6.141801e-10 ... 9.990476e-01 1.725814e-04 \n", - "aid_ZTF18abnueof 1.725786e-08 ... 1.054786e-02 6.650715e-03 \n", - "aid_ZTF17aaagvih 1.902887e-08 ... 1.722451e-03 1.419272e-06 \n", - "aid_ZTF17aabpjme 2.281132e-10 ... 7.575118e-03 9.906298e-01 \n", - "aid_ZTF18acrwlnr 6.540777e-11 ... 1.164306e-04 5.700163e-06 \n", + " Blazar SNII ... CEP RRLab \\\n", + "aid_ZTF18adldhip 3.216724e-03 5.469867e-06 ... 3.527732e-07 1.925852e-07 \n", + "aid_ZTF19aasbgeb 2.003026e-02 3.791978e-07 ... 4.490822e-07 1.678800e-07 \n", + "aid_ZTF18aayfbqd 2.373365e-07 3.675865e-07 ... 5.083823e-03 9.649606e-06 \n", + "aid_ZTF19ablyzbl 8.681483e-04 3.040604e-08 ... 1.208527e-07 8.290508e-08 \n", + "aid_ZTF18actabfv 1.776524e-06 1.188521e-08 ... 4.290823e-04 1.584599e-07 \n", + "... ... ... ... ... ... \n", + "aid_ZTF18abdlmwe 7.418862e-10 4.687425e-10 ... 9.998695e-01 9.530114e-06 \n", + "aid_ZTF18abnueof 3.709354e-08 1.095339e-07 ... 2.722043e-03 2.387790e-03 \n", + "aid_ZTF17aaagvih 1.371204e-04 5.840242e-08 ... 1.554408e-02 6.154704e-08 \n", + "aid_ZTF17aabpjme 1.994241e-07 3.404462e-09 ... 1.063609e-02 9.885159e-01 \n", + "aid_ZTF18acrwlnr 3.781134e-05 2.145775e-09 ... 5.661188e-04 8.605761e-08 \n", "\n", " Periodic-Other DSCT SNIbc SLSN \\\n", - "aid_ZTF18adldhip 2.116412e-04 3.084909e-07 1.887804e-10 8.844911e-06 \n", - "aid_ZTF19aasbgeb 7.640776e-05 5.403183e-08 2.797893e-12 6.822924e-09 \n", - "aid_ZTF18aayfbqd 1.242031e-07 5.098335e-04 6.606086e-10 2.130183e-14 \n", - "aid_ZTF19ablyzbl 3.496896e-05 1.479354e-08 1.388321e-12 2.085207e-09 \n", - "aid_ZTF18actabfv 1.858886e-03 7.208555e-04 1.019229e-10 1.032331e-13 \n", + "aid_ZTF18adldhip 9.147311e-05 1.255014e-07 2.337902e-10 5.576798e-08 \n", + "aid_ZTF19aasbgeb 1.016612e-06 2.264868e-09 5.275978e-11 1.065876e-07 \n", + "aid_ZTF18aayfbqd 1.928383e-08 3.228328e-04 5.042488e-11 1.650578e-10 \n", + "aid_ZTF19ablyzbl 2.975309e-05 4.032183e-07 4.406051e-12 4.773867e-08 \n", + "aid_ZTF18actabfv 8.540230e-04 5.695262e-05 1.002342e-08 1.948869e-13 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 2.990018e-09 1.420690e-07 2.476280e-09 1.552841e-17 \n", - "aid_ZTF18abnueof 5.748935e-06 1.954671e-05 4.381569e-09 1.159956e-15 \n", - "aid_ZTF17aaagvih 1.749655e-04 7.772013e-05 2.383930e-13 7.447991e-14 \n", - "aid_ZTF17aabpjme 1.215735e-09 4.649451e-07 2.486373e-10 1.401898e-17 \n", - "aid_ZTF18acrwlnr 2.511957e-05 4.367101e-05 2.710520e-15 1.171569e-17 \n", + "aid_ZTF18abdlmwe 2.042207e-08 1.684917e-08 1.759425e-11 9.711904e-17 \n", + "aid_ZTF18abnueof 1.253581e-03 2.343152e-05 7.793347e-10 4.768542e-14 \n", + "aid_ZTF17aaagvih 6.465749e-04 4.263413e-05 1.471535e-07 1.375777e-10 \n", + "aid_ZTF17aabpjme 5.252316e-05 1.454708e-05 5.486798e-09 1.341067e-16 \n", + "aid_ZTF18acrwlnr 1.004323e-04 1.798649e-05 1.692071e-10 1.037704e-12 \n", "\n", " TDE SNIIb SNIIn Microlensing \n", - "aid_ZTF18adldhip 6.748026e-09 1.274929e-14 4.879291e-07 8.376805e-13 \n", - "aid_ZTF19aasbgeb 6.783772e-13 1.067869e-17 1.556580e-14 1.700963e-14 \n", - "aid_ZTF18aayfbqd 7.762069e-15 6.496083e-17 7.613947e-13 3.685712e-10 \n", - "aid_ZTF19ablyzbl 1.140966e-12 2.251577e-15 2.687552e-14 3.431098e-14 \n", - "aid_ZTF18actabfv 1.734912e-13 1.552963e-17 1.296955e-13 5.580757e-14 \n", + "aid_ZTF18adldhip 5.452343e-11 2.326913e-12 2.565360e-06 1.319690e-12 \n", + "aid_ZTF19aasbgeb 5.029582e-14 9.001673e-19 1.766668e-08 1.659098e-13 \n", + "aid_ZTF18aayfbqd 1.062287e-14 3.683753e-14 3.239082e-10 5.906374e-10 \n", + "aid_ZTF19ablyzbl 2.522890e-15 2.287262e-14 2.319044e-06 8.565737e-14 \n", + "aid_ZTF18actabfv 1.642912e-15 9.973729e-12 1.388431e-10 5.548506e-12 \n", "... ... ... ... ... \n", - "aid_ZTF18abdlmwe 3.537669e-15 1.297150e-13 5.187267e-15 2.793726e-14 \n", - "aid_ZTF18abnueof 3.698598e-13 2.691933e-10 5.435293e-14 4.350763e-14 \n", - "aid_ZTF17aaagvih 1.609270e-15 2.119021e-16 6.981124e-12 8.322949e-16 \n", - "aid_ZTF17aabpjme 1.748985e-15 9.127245e-13 4.505965e-15 5.061297e-12 \n", - "aid_ZTF18acrwlnr 9.307659e-17 4.531178e-19 3.485753e-15 3.467227e-17 \n", + "aid_ZTF18abdlmwe 5.353405e-15 1.297741e-18 1.659782e-17 9.403529e-15 \n", + "aid_ZTF18abnueof 3.861496e-12 9.916746e-13 2.127023e-09 1.588791e-13 \n", + "aid_ZTF17aaagvih 3.221115e-16 2.619645e-14 9.743384e-10 1.359489e-16 \n", + "aid_ZTF17aabpjme 5.043624e-12 4.172631e-13 3.874752e-12 5.137409e-10 \n", + "aid_ZTF18acrwlnr 2.636524e-17 2.347973e-15 9.502477e-11 2.107070e-16 \n", "\n", "[8346 rows x 22 columns]" ] }, - "execution_count": 22, + "execution_count": 40, "metadata": {}, "output_type": "execute_result" } @@ -2792,7 +2792,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 41, "metadata": {}, "outputs": [ { @@ -2801,7 +2801,7 @@ "array(['AGN', 'QSO', 'LPV', ..., 'YSO', 'RRLab', 'YSO'], dtype=object)" ] }, - "execution_count": 23, + "execution_count": 41, "metadata": {}, "output_type": "execute_result" } @@ -2813,7 +2813,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 42, "metadata": {}, "outputs": [ { @@ -2822,7 +2822,7 @@ "array(['AGN', 'QSO', 'EA', ..., 'YSO', 'RRLab', 'YSO'], dtype=object)" ] }, - "execution_count": 24, + "execution_count": 42, "metadata": {}, "output_type": "execute_result" } @@ -2833,12 +2833,12 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 43, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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" ] @@ -2898,16 +2898,16 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 44, "metadata": {}, "outputs": [ { "data": { "text/plain": [ - "0.7391396424167446" + "0.7383260970671988" ] }, - "execution_count": 26, + "execution_count": 44, "metadata": {}, "output_type": "execute_result" } @@ -2920,7 +2920,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 45, "metadata": {}, "outputs": [], "source": [ @@ -2929,7 +2929,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 46, "metadata": {}, "outputs": [ { @@ -2938,13 +2938,13 @@ "Text(0.5, 0, 'entropy')" ] }, - "execution_count": 28, + "execution_count": 46, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", 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", 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" ] @@ -2960,7 +2960,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 47, "metadata": {}, "outputs": [ { @@ -2969,13 +2969,13 @@ "Text(0.5, 0, 'highest prob')" ] }, - "execution_count": 29, + "execution_count": 47, "metadata": {}, "output_type": "execute_result" }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] diff --git a/training/lc_classifier_ztf/ATAT_ALeRCE/src/data/handlers/CustomDataset.py b/training/lc_classifier_ztf/ATAT_ALeRCE/src/data/handlers/CustomDataset.py index 5751ade32..90de9dc2f 100644 --- a/training/lc_classifier_ztf/ATAT_ALeRCE/src/data/handlers/CustomDataset.py +++ b/training/lc_classifier_ztf/ATAT_ALeRCE/src/data/handlers/CustomDataset.py @@ -38,6 +38,9 @@ def __init__( ) partition_used = seed if not same_partition else 0 + # only using partition 0 + assert partition_used == 0 + h5_ = h5py.File("{}/dataset.h5".format(data_root)) self.these_idx = ( @@ -96,16 +99,14 @@ def __init__( if self.use_features: self.extracted_feat = dict() for time_eval in self.list_time_to_eval: - path_QT = "./{}/quantiles/features/{}_days/fold_{}.joblib".format( - data_root, time_eval, partition_used - ) + path_QT = f"./{data_root}/quantiles/features/fold_{partition_used}.joblib" extracted_feat = h5_.get("extracted_feat_{}".format(time_eval))[:][ self.these_idx ] self.extracted_feat.update( { time_eval: self.get_tabular_data( - extracted_feat, path_QT, "features_{}".format(time_eval) + extracted_feat, path_QT, f"features_{time_eval}" ) } ) diff --git a/training/lc_classifier_ztf/feature_computation/.gitignore b/training/lc_classifier_ztf/feature_computation/.gitignore index 1862d0f63..0d89b6f00 100644 --- a/training/lc_classifier_ztf/feature_computation/.gitignore +++ b/training/lc_classifier_ztf/feature_computation/.gitignore @@ -5,4 +5,4 @@ alercereaduser_v4.json config.py /ztf_classifier_model* -models/hrf_classifier_20240424-122916 \ No newline at end of file +models/ \ No newline at end of file diff --git a/training/lc_classifier_ztf/feature_computation/compute_features.py b/training/lc_classifier_ztf/feature_computation/compute_features.py index 517901b9a..02d57368a 100644 --- a/training/lc_classifier_ztf/feature_computation/compute_features.py +++ b/training/lc_classifier_ztf/feature_computation/compute_features.py @@ -27,7 +27,7 @@ def extract_features( ) from lc_classifier.features.composites.ztf import ZTFFeatureExtractor from lc_classifier.features.core.base import astro_object_from_dict - from dataset import save_batch + from lc_classifier.features.core.base import save_batch output_filename = os.path.join( output_folder, f"astro_objects_batch_{shorten_n_days}_{batch_id:04}.pkl" @@ -61,7 +61,7 @@ def patch_features(batch_id, shorten_n_days=None): ) from lc_classifier.features.extractors.tde_extractor import TDETailExtractor from lc_classifier.features.core.base import astro_object_from_dict - from dataset import save_batch + from lc_classifier.features.core.base import save_batch filename = os.path.join( output_folder, f"astro_objects_batch_{shorten_n_days}_{batch_id:04}.pkl" diff --git a/training/lc_classifier_ztf/feature_computation/dataset.py b/training/lc_classifier_ztf/feature_computation/dataset.py index 1afc1d7c3..436e7b8a0 100644 --- a/training/lc_classifier_ztf/feature_computation/dataset.py +++ b/training/lc_classifier_ztf/feature_computation/dataset.py @@ -1,11 +1,9 @@ import os -import pickle import numpy as np import pandas as pd -from lc_classifier.features.core.base import AstroObject +from lc_classifier.features.core.base import AstroObject, save_astro_objects_batch from tqdm import tqdm -from typing import List class NoDetections(Exception): @@ -82,12 +80,6 @@ def create_astro_object(lc_df: pd.DataFrame, object_info: pd.Series) -> AstroObj return astro_object -def save_batch(astro_objects: List[AstroObject], filename: str): - astro_objects_dicts = [ao.to_dict() for ao in astro_objects] - with open(filename, "wb") as f: - pickle.dump(astro_objects_dicts, f) - - if __name__ == "__main__": # Build AstroObjects @@ -120,7 +112,7 @@ def save_batch(astro_objects: List[AstroObject], filename: str): print(object_info) print("Object with no detections") - save_batch( + save_astro_objects_batch( astro_objects_list, os.path.join(data_dir, f"astro_objects_batch_{batch_i_str}.pkl"), ) diff --git a/training/lc_classifier_ztf/feature_computation/evaluate_model.py b/training/lc_classifier_ztf/feature_computation/evaluate_model.py index 0456af12a..8b243aa5e 100644 --- a/training/lc_classifier_ztf/feature_computation/evaluate_model.py +++ b/training/lc_classifier_ztf/feature_computation/evaluate_model.py @@ -64,7 +64,7 @@ classifier.load_classifier("rf_classifier_240307") elif classifier_type == "HierarchicalRandomForest": classifier = HierarchicalRandomForestClassifier(list_of_classes) - model_dir = "models/hrf_classifier_20240710-142630" + model_dir = "models/hrf_classifier_20240722-162932" classifier.load_classifier(model_dir) predictions_filename = os.path.join(model_dir, "predictions.parquet") elif classifier_type == "LightGBM": diff --git a/training/lc_classifier_ztf/feature_computation/periodic_other_position_analysis.ipynb b/training/lc_classifier_ztf/feature_computation/periodic_other_position_analysis.ipynb new file mode 100644 index 000000000..51036a73a --- /dev/null +++ b/training/lc_classifier_ztf/feature_computation/periodic_other_position_analysis.ipynb @@ -0,0 +1,2852 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "bc0ccb55-d3fb-4365-8e5e-f8f648ef23b8", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "import pandas as pd\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "6f777871-3189-4c56-9de6-40972a34efe4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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oidradecsubmitteralerceclassAllWISERAJ2000DEJ2000eeMajeeMin...pmDEe_pmDEd2MangDistW1-W2W2-W3sgscore1distpsnr1sgmag1srmag1
14ZTF18abuszmh306.489647-24.716426amunozPeriodic-OtherJ202557.51-244258.6306.489644-24.7162910.12660.1182...878.0431.00.4020.4882860.1320002.9730000.9559170.04987817.443617.1391
74ZTF19abahqnh204.363553-21.462345amunozPeriodic-OtherJ133727.27-212744.4204.363651-21.4623490.03980.0374...-28.028.00.4590.327302-0.0020000.0040000.5000000.89844212.498012.2440
98ZTF22abuhbev333.772941-26.259881amunozPeriodic-OtherJ221505.44-261534.7333.772677-26.2596560.04710.0412...37.050.00.3331.1760000.0029990.7610010.9996871.40944313.438913.2778
99ZTF20aaxbtan235.119755-24.901201amunozPeriodic-OtherJ154028.73-245404.4235.119741-24.9012490.09110.0869...314.0285.00.2530.177664-0.1089992.8860001.0000000.20342618.944217.8816
150ZTF19aapiwoj137.864415-24.718186amunozPeriodic-OtherJ091127.45-244305.2137.864404-24.7181270.03090.0297...106.031.00.1650.216398-0.0440000.7420001.0000000.23997213.959011.8310
..................................................................
41602ZTF19aaabvjc97.920485-24.557655amunozPeriodic-OtherJ063140.91-243328.397.920470-24.5578620.04120.0382...-1.041.00.1190.748394-0.038000-0.1170000.9858331.75868113.451013.0170
41630ZTF21aagvhiq102.116370-26.712377amunozPeriodic-OtherNoneNaNNaNNaNNaN...NaNNaNNaNNaNNaNNaN0.9568752.13568813.203513.9950
41653ZTF19abacosd213.564211-26.626237amunozPeriodic-OtherJ141415.41-263734.5213.564223-26.6262730.14970.1405...276.0331.00.6590.133410-0.0730013.7250011.0000000.27388217.474917.2910
41744ZTF19aayhsje296.148256-25.393526amunozPeriodic-OtherJ194435.57-252337.0296.148222-25.3936310.09790.0939...502.0302.00.3910.392747-0.1989993.0680000.9943750.44176717.193016.9124
41768ZTF21aamkwra197.971483-27.906962amunozPeriodic-OtherJ131153.15-275425.0197.971477-27.9069700.04560.0446...15.042.00.1190.035419-0.0260000.8740001.0000000.59472815.781815.2861
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854 rows × 42 columns

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" + ], + "text/plain": [ + " oid ra dec submitter alerceclass \\\n", + "14 ZTF18abuszmh 306.489647 -24.716426 amunoz Periodic-Other \n", + "74 ZTF19abahqnh 204.363553 -21.462345 amunoz Periodic-Other \n", + "98 ZTF22abuhbev 333.772941 -26.259881 amunoz Periodic-Other \n", + "99 ZTF20aaxbtan 235.119755 -24.901201 amunoz Periodic-Other \n", + "150 ZTF19aapiwoj 137.864415 -24.718186 amunoz Periodic-Other \n", + "... ... ... ... ... ... \n", + "41602 ZTF19aaabvjc 97.920485 -24.557655 amunoz Periodic-Other \n", + "41630 ZTF21aagvhiq 102.116370 -26.712377 amunoz Periodic-Other \n", + "41653 ZTF19abacosd 213.564211 -26.626237 amunoz Periodic-Other \n", + "41744 ZTF19aayhsje 296.148256 -25.393526 amunoz Periodic-Other \n", + "41768 ZTF21aamkwra 197.971483 -27.906962 amunoz Periodic-Other \n", + "\n", + " AllWISE RAJ2000 DEJ2000 eeMaj eeMin ... pmDE \\\n", + "14 J202557.51-244258.6 306.489644 -24.716291 0.1266 0.1182 ... 878.0 \n", + "74 J133727.27-212744.4 204.363651 -21.462349 0.0398 0.0374 ... -28.0 \n", + "98 J221505.44-261534.7 333.772677 -26.259656 0.0471 0.0412 ... 37.0 \n", + "99 J154028.73-245404.4 235.119741 -24.901249 0.0911 0.0869 ... 314.0 \n", + "150 J091127.45-244305.2 137.864404 -24.718127 0.0309 0.0297 ... 106.0 \n", + "... ... ... ... ... ... ... ... \n", + "41602 J063140.91-243328.3 97.920470 -24.557862 0.0412 0.0382 ... -1.0 \n", + "41630 None NaN NaN NaN NaN ... NaN \n", + "41653 J141415.41-263734.5 213.564223 -26.626273 0.1497 0.1405 ... 276.0 \n", + "41744 J194435.57-252337.0 296.148222 -25.393631 0.0979 0.0939 ... 502.0 \n", + "41768 J131153.15-275425.0 197.971477 -27.906970 0.0456 0.0446 ... 15.0 \n", + "\n", + " e_pmDE d2M angDist W1-W2 W2-W3 sgscore1 distpsnr1 \\\n", + "14 431.0 0.402 0.488286 0.132000 2.973000 0.955917 0.049878 \n", + "74 28.0 0.459 0.327302 -0.002000 0.004000 0.500000 0.898442 \n", + "98 50.0 0.333 1.176000 0.002999 0.761001 0.999687 1.409443 \n", + "99 285.0 0.253 0.177664 -0.108999 2.886000 1.000000 0.203426 \n", + "150 31.0 0.165 0.216398 -0.044000 0.742000 1.000000 0.239972 \n", + "... ... ... ... ... ... ... ... \n", + "41602 41.0 0.119 0.748394 -0.038000 -0.117000 0.985833 1.758681 \n", + "41630 NaN NaN NaN NaN NaN 0.956875 2.135688 \n", + "41653 331.0 0.659 0.133410 -0.073001 3.725001 1.000000 0.273882 \n", + "41744 302.0 0.391 0.392747 -0.198999 3.068000 0.994375 0.441767 \n", + "41768 42.0 0.119 0.035419 -0.026000 0.874000 1.000000 0.594728 \n", + "\n", + " sgmag1 srmag1 \n", + "14 17.4436 17.1391 \n", + "74 12.4980 12.2440 \n", + "98 13.4389 13.2778 \n", + "99 18.9442 17.8816 \n", + "150 13.9590 11.8310 \n", + "... ... ... \n", + "41602 13.4510 13.0170 \n", + "41630 13.2035 13.9950 \n", + "41653 17.4749 17.2910 \n", + "41744 17.1930 16.9124 \n", + "41768 15.7818 15.2861 \n", + "\n", + "[854 rows x 42 columns]" + ] + }, + "execution_count": 5, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "po_tp_coords = objects[objects['oid'].isin(po_tp['oid'])]\n", + "po_tp_coords" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "94785f75-be53-4e8c-b848-41a1a6690751", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0.7412177985948478" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "southern = po_tp_coords['dec'] < -20\n", + "south_fraction = southern.astype(float).mean()\n", + "south_fraction" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "8d0912af-14ca-4951-8d68-9b723c100f49", + "metadata": {}, + "outputs": [], + "source": [ + "southern_po_oids = po_tp_coords[southern]['oid'].values\n", + "northern_po_oids = po_tp_coords[~southern]['oid'].values" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "6a7b36da-0571-444a-9512-030fcc3ce7ff", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(10, 2))\n", + "plt.hist(po_tp_coords.dec, bins=150);\n", + "plt.semilogy()\n", + "plt.axvline(x=-28)\n", + "plt.axvline(x=-20)\n", + "plt.axvline(x=54)" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "622bda57-6145-4e4d-9196-7dfb80699945", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "24" + ] + }, + "execution_count": 9, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "n_not_to_be_replaced = ((~southern).astype(float).sum()) / (54 - (-20)) * (28-20)\n", + "n_not_to_be_replaced = int(np.ceil(n_not_to_be_replaced))\n", + "n_not_to_be_replaced" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "8a744b8a-cf5e-4862-a7ef-8064ca0bd2e1", + "metadata": {}, + "outputs": [], + "source": [ + "np.random.seed(0)\n", + "southern_not_to_be_replaced = np.random.choice(southern_po_oids, size=n_not_to_be_replaced, replace=False)\n", + "not_to_be_replaced = np.concatenate([northern_po_oids, southern_not_to_be_replaced])\n", + "to_be_replaced = list(set(po_tp.oid.values) - set(not_to_be_replaced))" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "eb8979ff-9967-493c-a209-4cb267e0534c", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "True" + ] + }, + "execution_count": 11, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(to_be_replaced) + len(not_to_be_replaced) == len(po_tp)" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "098ab7d0-744b-4c26-be60-cb69cec00678", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 12, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 5))\n", + "plt.subplot(1, 2, 1)\n", + "plt.scatter(\n", + " po_tp_coords.ra,\n", + " po_tp_coords.dec,\n", + " alpha=0.2\n", + ")\n", + "\n", + "plt.subplot(1, 2, 2)\n", + "plt.scatter(\n", + " po_tp_coords[po_tp_coords['oid'].isin(not_to_be_replaced)].ra,\n", + " po_tp_coords[po_tp_coords['oid'].isin(not_to_be_replaced)].dec,\n", + " alpha=0.2\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "ead9991b-d095-4851-929f-add881d1fb52", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "609" + ] + }, + "execution_count": 13, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "len(to_be_replaced)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "d68113a5-be6b-4557-8d77-416ffebed2f9", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "0 False\n", + "1 False\n", + "2 False\n", + "3 False\n", + "4 False\n", + " ... \n", + "334075 False\n", + "334076 False\n", + "334077 False\n", + "334078 False\n", + "334079 False\n", + "Name: index, Length: 334080, dtype: bool" + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "features = pd.read_parquet(\"data_231206_ao_features/consolidated_features.parquet\")\n", + "features.reset_index(inplace=True)\n", + "tbr_feature_mask = features['index'].isin(['aid_' + oid for oid in to_be_replaced])\n", + "tbr_feature_mask" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "2da19928-a33a-41f9-94fc-e6b1ff27e24f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "4872\n" + ] + } + ], + "source": [ + "n_replacement_needed = tbr_feature_mask.astype(int).sum()\n", + "print(n_replacement_needed)" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "27fa42e5-17d3-4871-8555-1ae533f60c4b", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "(array([[-0.03415362, 0.99297311, -0.11330459],\n", + " [-0.43665343, -0.84657212, 0.30438369],\n", + " [-0.71876605, 0.52638001, 0.45420199],\n", + " ...,\n", + " [ 0.83566709, -0.54909595, 0.01241605],\n", + " [-0.87780593, -0.41943875, 0.23136094],\n", + " [-0.0252461 , -0.66290794, 0.74827515]]),\n", + " (4872, 3))" + ] + }, + "execution_count": 16, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "replacement_coords = features[features['index'].isin(['aid_' + oid for oid in not_to_be_replaced])][[f'Coordinate_{x}_nan' for x in 'xyz']].sample(n_replacement_needed, replace=True).values\n", + "replacement_coords, replacement_coords.shape" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "c77569fb-9e18-4e24-b031-e939a3c66b5d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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..................................................................
333974aid_ZTF19aaabvjc0.1640730.6159990.4662300.466640-0.03800010681152344-0.116999626159667972.3280000686645511.9722767368519741.506046847109042...63.9652340.620.00.591.0521081856.940175-0.1253340.900867-0.415609None
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4872 rows × 189 columns

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g-r_mean_g,rg-r_max_g,rg-r_mean_corr_g,rg-r_max_corr_g,rW1-W2_nanW2-W3_nanW3-W4_nang-W1_nanr-W1_nang-W2_nan...ulens_chi_gulens_u0_rulens_tE_rulens_fs_rulens_chi_rTimespan_nanCoordinate_x_nanCoordinate_y_nanCoordinate_z_nanshorten
index
aid_ZTF17aaaazva1.2494671.3163211.8918451.7392750.06000041961669922-0.53500080108642583.2680006027221686.791517877200694.8996732819564176.851518296817389...18.7263680.620.00.560.7244541000.6268620.494895-0.4495060.7436551024
aid_ZTF17aaaeayj1.3474441.7888531.9313791.7592620.53299999237060551.29399967193603521.40799999237060558.0044850336142776.07310592975579068.537485025984882...59.0307390.620.00.5335.1467791014.6439880.576235-0.3589300.7342501024
aid_ZTF17aaafynz0.9577161.0259361.0236701.013279-0.086999893188476562.44599914550781252.4980001449584963.76598372704192742.7423138896828943.678983833853451...67.1736190.620.00.5145.6284451022.6414470.433492-0.0070080.9011301024
aid_ZTF17aaagrkx0.4926780.9526870.6657200.685052-0.078999519348144530.9309997558593753.7060003280639652.78517412429597752.11945415812281722.706174604947833...206.3358290.620.00.5187.2962761023.6646680.512372-0.2971520.8057141024
aid_ZTF17aaagvif-1.0432101.6283111.1017211.0754200.35799980163574221.8790001869201662.38199973106384285.4725950304448474.3708744510351125.830594832080589...566.4804490.620.00.5370.5386131023.154239-0.1755490.9704030.1658341024
..................................................................
aid_ZTF22abyiisu0.3824420.2212950.1849730.126016nannannannannannan...111.4747690.620.00.5230.71015243.9469290.914842-0.1831940.359866None
aid_ZTF23aacgchk-0.456579-0.2569270.042352-0.060017-0.0120000839233398440.77600002288818363.63899993896484380.88117720769776750.83882522594035610.8691771237744277...435.5477740.620.00.5252.3285821868.906361-0.8427310.333456-0.422625None
aid_ZTF23aaqniyk0.3545710.2916080.4059220.3692240.230999946594238283.78299999237060551.76499938964843754.7914515462750244.3855295858251965.022451492869262...12.3812570.620.00.582.76030587.945095-0.058707-0.9827320.175472None
aid_ZTF23aaxadel0.7980460.9032120.5563590.743472nannannannannannan...49.3244940.620.00.5152.854089917.7143390.8943300.0582850.443595None
aid_ZTF23abccimv0.4692210.0819160.3986630.1871370.078000068664550782.5409994125366212.92000007629394532.65563456134628242.25697178821434362.733634630010833...110.5020300.620.00.5235.247593284.2877720.2447240.969174-0.028502None
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334080 rows × 188 columns

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"aid_ZTF22abyiisu 0.126016 nan \n", + "aid_ZTF23aacgchk -0.060017 -0.012000083923339844 \n", + "aid_ZTF23aaqniyk 0.369224 0.23099994659423828 \n", + "aid_ZTF23aaxadel 0.743472 nan \n", + "aid_ZTF23abccimv 0.187137 0.07800006866455078 \n", + "\n", + " W2-W3_nan W3-W4_nan g-W1_nan \\\n", + "index \n", + "aid_ZTF17aaaazva -0.5350008010864258 3.268000602722168 6.79151787720069 \n", + "aid_ZTF17aaaeayj 1.2939996719360352 1.4079999923706055 8.004485033614277 \n", + "aid_ZTF17aaafynz 2.4459991455078125 2.498000144958496 3.7659837270419274 \n", + "aid_ZTF17aaagrkx 0.930999755859375 3.706000328063965 2.7851741242959775 \n", + "aid_ZTF17aaagvif 1.879000186920166 2.3819997310638428 5.472595030444847 \n", + "... ... ... ... \n", + "aid_ZTF22abyiisu nan nan nan \n", + "aid_ZTF23aacgchk 0.7760000228881836 3.6389999389648438 0.8811772076977675 \n", + "aid_ZTF23aaqniyk 3.7829999923706055 1.7649993896484375 4.791451546275024 \n", + "aid_ZTF23aaxadel nan nan nan \n", + "aid_ZTF23abccimv 2.540999412536621 2.9200000762939453 2.6556345613462824 \n", + "\n", + " r-W1_nan g-W2_nan ... ulens_chi_g \\\n", + "index ... \n", + "aid_ZTF17aaaazva 4.899673281956417 6.851518296817389 ... 18.726368 \n", + "aid_ZTF17aaaeayj 6.0731059297557906 8.537485025984882 ... 59.030739 \n", + "aid_ZTF17aaafynz 2.742313889682894 3.678983833853451 ... 67.173619 \n", + "aid_ZTF17aaagrkx 2.1194541581228172 2.706174604947833 ... 206.335829 \n", + "aid_ZTF17aaagvif 4.370874451035112 5.830594832080589 ... 566.480449 \n", + "... ... ... ... ... \n", + "aid_ZTF22abyiisu nan nan ... 111.474769 \n", + "aid_ZTF23aacgchk 0.8388252259403561 0.8691771237744277 ... 435.547774 \n", + "aid_ZTF23aaqniyk 4.385529585825196 5.022451492869262 ... 12.381257 \n", + "aid_ZTF23aaxadel nan nan ... 49.324494 \n", + "aid_ZTF23abccimv 2.2569717882143436 2.733634630010833 ... 110.502030 \n", + "\n", + " ulens_u0_r ulens_tE_r ulens_fs_r ulens_chi_r Timespan_nan \\\n", + "index \n", + "aid_ZTF17aaaazva 0.6 20.0 0.5 60.724454 1000.626862 \n", + "aid_ZTF17aaaeayj 0.6 20.0 0.5 335.146779 1014.643988 \n", + "aid_ZTF17aaafynz 0.6 20.0 0.5 145.628445 1022.641447 \n", + "aid_ZTF17aaagrkx 0.6 20.0 0.5 187.296276 1023.664668 \n", + "aid_ZTF17aaagvif 0.6 20.0 0.5 370.538613 1023.154239 \n", + "... ... ... ... ... ... \n", + "aid_ZTF22abyiisu 0.6 20.0 0.5 230.710152 43.946929 \n", + "aid_ZTF23aacgchk 0.6 20.0 0.5 252.328582 1868.906361 \n", + "aid_ZTF23aaqniyk 0.6 20.0 0.5 82.760305 87.945095 \n", + "aid_ZTF23aaxadel 0.6 20.0 0.5 152.854089 917.714339 \n", + "aid_ZTF23abccimv 0.6 20.0 0.5 235.247593 284.287772 \n", + "\n", + " Coordinate_x_nan Coordinate_y_nan Coordinate_z_nan \\\n", + "index \n", + "aid_ZTF17aaaazva 0.494895 -0.449506 0.743655 \n", + "aid_ZTF17aaaeayj 0.576235 -0.358930 0.734250 \n", + "aid_ZTF17aaafynz 0.433492 -0.007008 0.901130 \n", + "aid_ZTF17aaagrkx 0.512372 -0.297152 0.805714 \n", + "aid_ZTF17aaagvif -0.175549 0.970403 0.165834 \n", + "... ... ... ... \n", + "aid_ZTF22abyiisu 0.914842 -0.183194 0.359866 \n", + "aid_ZTF23aacgchk -0.842731 0.333456 -0.422625 \n", + "aid_ZTF23aaqniyk -0.058707 -0.982732 0.175472 \n", + "aid_ZTF23aaxadel 0.894330 0.058285 0.443595 \n", + "aid_ZTF23abccimv 0.244724 0.969174 -0.028502 \n", + "\n", + " shorten \n", + "index \n", + "aid_ZTF17aaaazva 1024 \n", + "aid_ZTF17aaaeayj 1024 \n", + "aid_ZTF17aaafynz 1024 \n", + "aid_ZTF17aaagrkx 1024 \n", + "aid_ZTF17aaagvif 1024 \n", + "... ... \n", + "aid_ZTF22abyiisu None \n", + "aid_ZTF23aacgchk None \n", + "aid_ZTF23aaqniyk None \n", + "aid_ZTF23aaxadel None \n", + "aid_ZTF23abccimv None \n", + "\n", + "[334080 rows x 188 columns]" + ] + }, + "execution_count": 18, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "features.set_index('index', inplace=True)\n", + "features" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "093944fb-3da8-472c-9e0a-dd3a9f521859", + "metadata": {}, + "outputs": [], + "source": [ + "features.loc[['aid_' + oid for oid in to_be_replaced], [f'Coordinate_{x}_nan' for x in 'xyz']] = replacement_coords" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "6c85f64f-9e5a-4380-9a50-27171b75133f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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g-r_mean_g,rg-r_max_g,rg-r_mean_corr_g,rg-r_max_corr_g,rW1-W2_nanW2-W3_nanW3-W4_nang-W1_nanr-W1_nang-W2_nan...ulens_chi_gulens_u0_rulens_tE_rulens_fs_rulens_chi_rTimespan_nanCoordinate_x_nanCoordinate_y_nanCoordinate_z_nanshorten
index
aid_ZTF17aaaazva1.2494671.3163211.8918451.7392750.06000041961669922-0.53500080108642583.2680006027221686.791517877200694.8996732819564176.851518296817389...18.7263680.620.00.560.7244541000.6268620.494895-0.4495060.7436551024
aid_ZTF17aaaeayj1.3474441.7888531.9313791.7592620.53299999237060551.29399967193603521.40799999237060558.0044850336142776.07310592975579068.537485025984882...59.0307390.620.00.5335.1467791014.6439880.576235-0.3589300.7342501024
aid_ZTF17aaafynz0.9577161.0259361.0236701.013279-0.086999893188476562.44599914550781252.4980001449584963.76598372704192742.7423138896828943.678983833853451...67.1736190.620.00.5145.6284451022.6414470.433492-0.0070080.9011301024
aid_ZTF17aaagrkx0.4926780.9526870.6657200.685052-0.078999519348144530.9309997558593753.7060003280639652.78517412429597752.11945415812281722.706174604947833...206.3358290.620.00.5187.2962761023.6646680.512372-0.2971520.8057141024
aid_ZTF17aaagvif-1.0432101.6283111.1017211.0754200.35799980163574221.8790001869201662.38199973106384285.4725950304448474.3708744510351125.830594832080589...566.4804490.620.00.5370.5386131023.154239-0.1755490.9704030.1658341024
..................................................................
aid_ZTF22abyiisu0.3824420.2212950.1849730.126016nannannannannannan...111.4747690.620.00.5230.71015243.9469290.914842-0.1831940.359866None
aid_ZTF23aacgchk-0.456579-0.2569270.042352-0.060017-0.0120000839233398440.77600002288818363.63899993896484380.88117720769776750.83882522594035610.8691771237744277...435.5477740.620.00.5252.3285821868.906361-0.8427310.333456-0.422625None
aid_ZTF23aaqniyk0.3545710.2916080.4059220.3692240.230999946594238283.78299999237060551.76499938964843754.7914515462750244.3855295858251965.022451492869262...12.3812570.620.00.582.76030587.945095-0.058707-0.9827320.175472None
aid_ZTF23aaxadel0.7980460.9032120.5563590.743472nannannannannannan...49.3244940.620.00.5152.854089917.7143390.8943300.0582850.443595None
aid_ZTF23abccimv0.4692210.0819160.3986630.1871370.078000068664550782.5409994125366212.92000007629394532.65563456134628242.25697178821434362.733634630010833...110.5020300.620.00.5235.247593284.2877720.2447240.969174-0.028502None
\n", + "

334080 rows × 188 columns

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" + ], + "text/plain": [ + " g-r_mean_g,r g-r_max_g,r g-r_mean_corr_g,r \\\n", + "index \n", + "aid_ZTF17aaaazva 1.249467 1.316321 1.891845 \n", + "aid_ZTF17aaaeayj 1.347444 1.788853 1.931379 \n", + "aid_ZTF17aaafynz 0.957716 1.025936 1.023670 \n", + "aid_ZTF17aaagrkx 0.492678 0.952687 0.665720 \n", + "aid_ZTF17aaagvif -1.043210 1.628311 1.101721 \n", + "... ... ... ... \n", + "aid_ZTF22abyiisu 0.382442 0.221295 0.184973 \n", + "aid_ZTF23aacgchk -0.456579 -0.256927 0.042352 \n", + "aid_ZTF23aaqniyk 0.354571 0.291608 0.405922 \n", + "aid_ZTF23aaxadel 0.798046 0.903212 0.556359 \n", + "aid_ZTF23abccimv 0.469221 0.081916 0.398663 \n", + "\n", + " g-r_max_corr_g,r W1-W2_nan \\\n", + "index \n", + "aid_ZTF17aaaazva 1.739275 0.06000041961669922 \n", + "aid_ZTF17aaaeayj 1.759262 0.5329999923706055 \n", + "aid_ZTF17aaafynz 1.013279 -0.08699989318847656 \n", + "aid_ZTF17aaagrkx 0.685052 -0.07899951934814453 \n", + "aid_ZTF17aaagvif 1.075420 0.3579998016357422 \n", + "... ... ... \n", + "aid_ZTF22abyiisu 0.126016 nan \n", + "aid_ZTF23aacgchk -0.060017 -0.012000083923339844 \n", + "aid_ZTF23aaqniyk 0.369224 0.23099994659423828 \n", + "aid_ZTF23aaxadel 0.743472 nan \n", + "aid_ZTF23abccimv 0.187137 0.07800006866455078 \n", + "\n", + " W2-W3_nan W3-W4_nan g-W1_nan \\\n", + "index \n", + "aid_ZTF17aaaazva -0.5350008010864258 3.268000602722168 6.79151787720069 \n", + "aid_ZTF17aaaeayj 1.2939996719360352 1.4079999923706055 8.004485033614277 \n", + "aid_ZTF17aaafynz 2.4459991455078125 2.498000144958496 3.7659837270419274 \n", + "aid_ZTF17aaagrkx 0.930999755859375 3.706000328063965 2.7851741242959775 \n", + "aid_ZTF17aaagvif 1.879000186920166 2.3819997310638428 5.472595030444847 \n", + "... ... ... ... \n", + "aid_ZTF22abyiisu nan nan nan \n", + "aid_ZTF23aacgchk 0.7760000228881836 3.6389999389648438 0.8811772076977675 \n", + "aid_ZTF23aaqniyk 3.7829999923706055 1.7649993896484375 4.791451546275024 \n", + "aid_ZTF23aaxadel nan nan nan \n", + "aid_ZTF23abccimv 2.540999412536621 2.9200000762939453 2.6556345613462824 \n", + "\n", + " r-W1_nan g-W2_nan ... ulens_chi_g \\\n", + "index ... \n", + "aid_ZTF17aaaazva 4.899673281956417 6.851518296817389 ... 18.726368 \n", + "aid_ZTF17aaaeayj 6.0731059297557906 8.537485025984882 ... 59.030739 \n", + "aid_ZTF17aaafynz 2.742313889682894 3.678983833853451 ... 67.173619 \n", + "aid_ZTF17aaagrkx 2.1194541581228172 2.706174604947833 ... 206.335829 \n", + "aid_ZTF17aaagvif 4.370874451035112 5.830594832080589 ... 566.480449 \n", + "... ... ... ... ... \n", + "aid_ZTF22abyiisu nan nan ... 111.474769 \n", + "aid_ZTF23aacgchk 0.8388252259403561 0.8691771237744277 ... 435.547774 \n", + "aid_ZTF23aaqniyk 4.385529585825196 5.022451492869262 ... 12.381257 \n", + "aid_ZTF23aaxadel nan nan ... 49.324494 \n", + "aid_ZTF23abccimv 2.2569717882143436 2.733634630010833 ... 110.502030 \n", + "\n", + " ulens_u0_r ulens_tE_r ulens_fs_r ulens_chi_r Timespan_nan \\\n", + "index \n", + "aid_ZTF17aaaazva 0.6 20.0 0.5 60.724454 1000.626862 \n", + "aid_ZTF17aaaeayj 0.6 20.0 0.5 335.146779 1014.643988 \n", + "aid_ZTF17aaafynz 0.6 20.0 0.5 145.628445 1022.641447 \n", + "aid_ZTF17aaagrkx 0.6 20.0 0.5 187.296276 1023.664668 \n", + "aid_ZTF17aaagvif 0.6 20.0 0.5 370.538613 1023.154239 \n", + "... ... ... ... ... ... \n", + "aid_ZTF22abyiisu 0.6 20.0 0.5 230.710152 43.946929 \n", + "aid_ZTF23aacgchk 0.6 20.0 0.5 252.328582 1868.906361 \n", + "aid_ZTF23aaqniyk 0.6 20.0 0.5 82.760305 87.945095 \n", + "aid_ZTF23aaxadel 0.6 20.0 0.5 152.854089 917.714339 \n", + "aid_ZTF23abccimv 0.6 20.0 0.5 235.247593 284.287772 \n", + "\n", + " Coordinate_x_nan Coordinate_y_nan Coordinate_z_nan \\\n", + "index \n", + "aid_ZTF17aaaazva 0.494895 -0.449506 0.743655 \n", + "aid_ZTF17aaaeayj 0.576235 -0.358930 0.734250 \n", + "aid_ZTF17aaafynz 0.433492 -0.007008 0.901130 \n", + "aid_ZTF17aaagrkx 0.512372 -0.297152 0.805714 \n", + "aid_ZTF17aaagvif -0.175549 0.970403 0.165834 \n", + "... ... ... ... \n", + "aid_ZTF22abyiisu 0.914842 -0.183194 0.359866 \n", + "aid_ZTF23aacgchk -0.842731 0.333456 -0.422625 \n", + "aid_ZTF23aaqniyk -0.058707 -0.982732 0.175472 \n", + "aid_ZTF23aaxadel 0.894330 0.058285 0.443595 \n", + "aid_ZTF23abccimv 0.244724 0.969174 -0.028502 \n", + "\n", + " shorten \n", + "index \n", + "aid_ZTF17aaaazva 1024 \n", + "aid_ZTF17aaaeayj 1024 \n", + "aid_ZTF17aaafynz 1024 \n", + "aid_ZTF17aaagrkx 1024 \n", + "aid_ZTF17aaagvif 1024 \n", + "... ... \n", + "aid_ZTF22abyiisu None \n", + "aid_ZTF23aacgchk None \n", + "aid_ZTF23aaqniyk None \n", + "aid_ZTF23aaxadel None \n", + "aid_ZTF23abccimv None \n", + "\n", + "[334080 rows x 188 columns]" + ] + }, + "execution_count": 20, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "features" + ] + }, + { + "cell_type": "code", + "execution_count": 21, + "id": "989d3978-5bf2-4237-8ddb-7841aee22620", + "metadata": {}, + "outputs": [], + "source": [ + "%matplotlib widget" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "id": "d3445c02-e860-48da-a94d-f6c113c8313f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 22, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "404ead0933c7426faa2f7fa28ac5c2d0", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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", 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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = plt.figure().add_subplot(projection='3d')\n", + "ax.scatter(\n", + " features.loc[['aid_' + oid for oid in to_be_replaced]]['Coordinate_x_nan'],\n", + " features.loc[['aid_' + oid for oid in to_be_replaced]]['Coordinate_y_nan'],\n", + " features.loc[['aid_' + oid for oid in to_be_replaced]]['Coordinate_z_nan']\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "0fea2023-eaa9-41a5-8798-ee3a180d56da", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 23, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f1124baa7b7240949fae5f209d122830", + "version_major": 2, + "version_minor": 0 + }, + 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", 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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "ax = plt.figure().add_subplot(projection='3d')\n", + "ax.scatter(\n", + " features.loc[['aid_' + oid for oid in not_to_be_replaced]]['Coordinate_x_nan'],\n", + " features.loc[['aid_' + oid for oid in not_to_be_replaced]]['Coordinate_y_nan'],\n", + " features.loc[['aid_' + oid for oid in not_to_be_replaced]]['Coordinate_z_nan']\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "e8c7a137-a412-46f3-8c13-df4d64cf43b2", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 24, + "metadata": {}, + "output_type": "execute_result" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "2cedbea6d60a43928d563028dd3a61bf", + "version_major": 2, + "version_minor": 0 + }, + "image/png": 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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "sample = features.sample(1000)\n", + "ax = plt.figure().add_subplot(projection='3d')\n", + "ax.scatter(\n", + " sample['Coordinate_x_nan'],\n", + " sample['Coordinate_y_nan'],\n", + " sample['Coordinate_z_nan'],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "523e5e4a-90d7-4bc8-ab11-b3d6cf2bae75", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/training/lc_classifier_ztf/feature_computation/training.py b/training/lc_classifier_ztf/feature_computation/training.py index dd2b453c7..54733f0c7 100644 --- a/training/lc_classifier_ztf/feature_computation/training.py +++ b/training/lc_classifier_ztf/feature_computation/training.py @@ -1,4 +1,5 @@ import os +import numpy as np import pandas as pd import time from alerce_classifiers.classifiers.mlp import MLPClassifier @@ -23,6 +24,46 @@ if __name__ == "__main__": features = pd.read_parquet("data_231206_ao_features/consolidated_features.parquet") labels = pd.read_parquet("data_231206/partitions.parquet") + objects = pd.read_parquet( + "data_231206/objects_with_wise_20240105.parquet" + ) # to get RA/DEC + + # manage bias of Periodic-Other towards southern sky + training_partition = "training_0" + po_tp = labels[ + (labels["alerceclass"] == "Periodic-Other") + & (labels["partition"] == training_partition) + ] + po_tp_coords = objects[objects["oid"].isin(po_tp["oid"])] + southern = po_tp_coords["dec"] < -20 + + n_not_to_be_replaced = ((~southern).astype(float).sum()) / (54 - (-20)) * (28 - 20) + n_not_to_be_replaced = int(np.ceil(n_not_to_be_replaced)) + + southern_po_oids = po_tp_coords[southern]["oid"].values + northern_po_oids = po_tp_coords[~southern]["oid"].values + + np.random.seed(0) + southern_not_to_be_replaced = np.random.choice( + southern_po_oids, size=n_not_to_be_replaced, replace=False + ) + not_to_be_replaced = np.concatenate([northern_po_oids, southern_not_to_be_replaced]) + to_be_replaced = list(set(po_tp.oid.values) - set(not_to_be_replaced)) + + features.reset_index(inplace=True) + tbr_feature_mask = features["index"].isin(["aid_" + oid for oid in to_be_replaced]) + n_replacement_needed = tbr_feature_mask.astype(int).sum() + replacement_coords = ( + features[features["index"].isin(["aid_" + oid for oid in not_to_be_replaced])][ + [f"Coordinate_{x}_nan" for x in "xyz"] + ] + .sample(n_replacement_needed, replace=True) + .values + ) + features.set_index("index", inplace=True) + features.loc[ + ["aid_" + oid for oid in to_be_replaced], [f"Coordinate_{x}_nan" for x in "xyz"] + ] = replacement_coords # support for shortened lightcurves features.index = ( diff --git a/training/lc_classifier_ztf/feature_computation/which_column_to_use.ipynb b/training/lc_classifier_ztf/feature_computation/which_column_to_use.ipynb new file mode 100644 index 000000000..8ca01600f --- /dev/null +++ b/training/lc_classifier_ztf/feature_computation/which_column_to_use.ipynb @@ -0,0 +1,1307 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 6, + "id": "49445105-659d-4b45-a49a-e2d8439f13b6", + "metadata": {}, + "outputs": [], + "source": [ + "import sqlalchemy as sa\n", + "import requests\n", + "import pandas as pd\n", + "import os\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 69, + "id": "60dc272e-3344-49af-8185-1bb04d6c265b", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " oid candid mjd fid pid \\\n", + "0 ZTF18aavoomb 503315013715010004 58257.315012 2 503315013715 \n", + "1 ZTF18aavoomb 503356783715015005 58257.356782 2 503356783715 \n", + "2 ZTF18aavoomb 514374363715015003 58268.374363 2 514374363715 \n", + "3 ZTF18aavoomb 524271413715010002 58278.271412 2 524271413715 \n", + "4 ZTF18aavoomb 527209783715015013 58281.209780 2 527209783715 \n", + "... ... ... ... ... ... \n", + "1209 ZTF21acceboj 1796336925615015000 59550.336921 2 1796336925615 \n", + "1210 ZTF21acceboj 1796337391415015019 59550.337396 2 1796337391415 \n", + "1211 ZTF21acceboj 1870169955615015001 59624.169954 2 1870169955615 \n", + "1212 ZTF21acceboj 1873147335615015001 59627.147338 2 1873147335615 \n", + "1213 ZTF21acceboj 1882135765615015001 59636.135764 2 1882135765615 \n", + "\n", + " diffmaglim isdiffpos nid ra dec ... sigmagapbig \\\n", + "0 20.405800 -1 503 240.645156 5.740859 ... 0.0633 \n", + "1 20.490700 1 503 240.645233 5.740790 ... 0.0854 \n", + "2 19.249200 1 514 240.645160 5.740850 ... 0.1288 \n", + "3 20.413221 -1 524 240.645135 5.740913 ... 0.0774 \n", + "4 20.645897 1 527 240.645155 5.740854 ... 0.0297 \n", + "... ... ... ... ... ... ... ... \n", + "1209 20.480295 1 1796 79.087644 -13.477760 ... 0.0480 \n", + "1210 20.401945 1 1796 79.087643 -13.477791 ... 0.0522 \n", + "1211 19.547693 1 1870 79.087639 -13.477712 ... 0.3668 \n", + "1212 19.500300 1 1873 79.087541 -13.477598 ... 0.8670 \n", + "1213 20.118727 1 1882 79.087663 -13.477771 ... 0.4920 \n", + "\n", + " rfid magpsf_corr sigmapsf_corr sigmapsf_corr_ext corrected \\\n", + "0 NaN 17.445303 100.000000 0.016360 True \n", + "1 NaN 16.792156 100.000000 0.009637 True \n", + "2 NaN 16.551277 0.018581 0.020983 True \n", + "3 481120237.0 17.337175 100.000000 0.015342 True \n", + "4 481120237.0 16.412691 100.000000 0.007246 True \n", + "... ... ... ... ... ... \n", + "1209 305120256.0 17.222464 0.002194 0.035514 True \n", + "1210 356120214.0 NaN NaN NaN False \n", + "1211 305120256.0 18.107824 100.000000 0.054231 True \n", + "1212 NaN 18.134502 100.000000 0.062755 True \n", + "1213 305120256.0 18.160744 100.000000 0.035231 True \n", + "\n", + " dubious parent_candid has_stamp step_id_corr \n", + "0 False 5.272098e+17 False bulk_1.0.0 \n", + "1 False 5.272098e+17 False bulk_1.0.0 \n", + "2 False 5.432915e+17 False bulk_1.0.0 \n", + "3 False 5.432915e+17 False bulk_1.0.0 \n", + "4 False 5.432915e+17 False bulk_1.0.0 \n", + "... ... ... ... ... \n", + "1209 True NaN True correction_1.0.6 \n", + "1210 False NaN True correction_1.0.6 \n", + "1211 True NaN True correction_1.0.6 \n", + "1212 True 1.882136e+18 False correction_1.0.6 \n", + "1213 True NaN True correction_1.0.6 \n", + "\n", + "[1214 rows x 30 columns]\n", + "Index(['oid', 'candid', 'mjd', 'fid', 'pid', 'diffmaglim', 'isdiffpos', 'nid',\n", + " 'ra', 'dec', 'magpsf', 'sigmapsf', 'magap', 'sigmagap', 'distnr', 'rb',\n", + " 'rbversion', 'drb', 'drbversion', 'magapbig', 'sigmagapbig', 'rfid',\n", + " 'magpsf_corr', 'sigmapsf_corr', 'sigmapsf_corr_ext', 'corrected',\n", + " 'dubious', 'parent_candid', 'has_stamp', 'step_id_corr'],\n", + " dtype='object')\n", + " pid oid mjd fid ra dec \\\n", + "0 2557554073715 ZTF18aavoomb 60311.554074 2 240.645133 5.740907 \n", + "1 2557556583715 ZTF18aavoomb 60311.556586 2 240.645164 5.740918 \n", + "2 2557561593715 ZTF18aavoomb 60311.561597 2 240.645160 5.740947 \n", + "3 2557564103715 ZTF18aavoomb 60311.564109 2 240.645151 5.740882 \n", + "4 2560554893715 ZTF18aavoomb 60314.554896 2 240.645170 5.740882 \n", + ".. ... ... ... ... ... ... \n", + "74 2717294653715 ZTF18aavoomb 60471.294653 2 240.645198 5.740855 \n", + "75 2715412473715 ZTF18aavoomb 60469.412477 2 240.645198 5.740855 \n", + "76 2715338223715 ZTF18aavoomb 60469.338229 1 240.645198 5.740855 \n", + "77 2731341783715 ZTF18aavoomb 60485.341782 2 240.645198 5.740855 \n", + "78 2729273413715 ZTF18aavoomb 60483.273414 2 240.645198 5.740855 \n", + "\n", + " e_ra e_dec mag e_mag ... diffmaglim programid procstatus \\\n", + "0 None None 18.661386 0.051368 ... 19.797100 1 0 \n", + "1 None None 18.700552 0.050587 ... 19.837200 1 0 \n", + "2 None None 18.573282 0.035769 ... 19.923300 1 0 \n", + "3 None None 18.599634 0.040498 ... 19.972700 1 0 \n", + "4 None None 18.357758 0.034819 ... 19.831100 1 0 \n", + ".. ... ... ... ... ... ... ... ... \n", + "74 None None 18.617392 0.026919 ... 20.507000 1 0 \n", + "75 None None 18.597378 0.030984 ... 20.271700 1 0 \n", + "76 None None 18.228188 0.016722 ... 20.620300 1 0 \n", + "77 None None 17.969757 0.029868 ... 19.835800 1 0 \n", + "78 None None 18.610371 0.057062 ... 19.665701 1 0 \n", + "\n", + " distnr ranr decnr magnr sigmagnr chinr sharpnr \n", + "0 0.105198 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "1 0.033612 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "2 0.137655 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "3 0.105623 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "4 0.099407 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + ".. ... ... ... ... ... ... ... \n", + "74 0.233803 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "75 0.233803 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "76 0.223260 240.645172 5.740908 17.142000 0.018 0.767 -0.045 \n", + "77 0.233803 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "78 0.233803 240.645157 5.740909 17.019001 0.015 0.512 -0.012 \n", + "\n", + "[79 rows x 42 columns]\n", + "Index(['pid', 'oid', 'mjd', 'fid', 'ra', 'dec', 'e_ra', 'e_dec', 'mag',\n", + " 'e_mag', 'mag_corr', 'e_mag_corr', 'e_mag_corr_ext', 'isdiffpos',\n", + " 'corrected', 'dubious', 'parent_candid', 'has_stamp', 'field', 'rcid',\n", + " 'rfid', 'sciinpseeing', 'scibckgnd', 'scisigpix', 'magzpsci',\n", + " 'magzpsciunc', 'magzpscirms', 'clrcoeff', 'clrcounc', 'exptime',\n", + " 'adpctdif1', 'adpctdif2', 'diffmaglim', 'programid', 'procstatus',\n", + " 'distnr', 'ranr', 'decnr', 'magnr', 'sigmagnr', 'chinr', 'sharpnr'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "url = \"https://raw.githubusercontent.com/alercebroker/usecases/master/alercereaduser_v4.json\"\n", + "params = requests.get(url).json()[\"params\"]\n", + "\n", + "engine = sa.create_engine(\n", + " f\"postgresql+psycopg2://{params['user']}:{params['password']}@{params['host']}/{params['dbname']}\"\n", + ")\n", + "engine.begin()\n", + "\n", + "oids = [\"ZTF19aaxqrku\", \"ZTF18aavoomb\", \"ZTF18acwyopw\" ,\"ZTF21acceboj\", \"ZTF21aanrvaz\"]\n", + "oids = [f\"'{oid}'\" for oid in oids]\n", + "\n", + "query_detections = f\"\"\"\n", + "SELECT * FROM detection\n", + "WHERE oid in ({','.join(oids)});\n", + "\"\"\"\n", + "detections = pd.read_sql_query(query_detections, con=engine)\n", + "print(detections)\n", + "print(detections.columns)\n", + "\n", + "\n", + "\n", + "query_forced_photometry = f\"\"\"\n", + "SELECT * FROM forced_photometry\n", + "WHERE oid in ({','.join(oids)});\n", + "\"\"\"\n", + "forced_photometry = pd.read_sql_query(query_forced_photometry, con=engine)\n", + "print(forced_photometry)\n", + "print(forced_photometry.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 70, + "id": "0beee064-95a1-492c-a2b6-2f164e9f6c0d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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oidcandidmjdfidpiddiffmaglimisdiffposnidradec...sigmagapbigrfidmagpsf_corrsigmapsf_corrsigmapsf_corr_extcorrecteddubiousparent_candidhas_stampstep_id_corr
0ZTF18aavoomb50331501371501000458257.315012250331501371520.405800-1503240.6451565.740859...0.0633NaN17.445303100.0000000.016360TrueFalse5.272098e+17Falsebulk_1.0.0
1ZTF18aavoomb50335678371501500558257.356782250335678371520.4907001503240.6452335.740790...0.0854NaN16.792156100.0000000.009637TrueFalse5.272098e+17Falsebulk_1.0.0
2ZTF18aavoomb51437436371501500358268.374363251437436371519.2492001514240.6451605.740850...0.1288NaN16.5512770.0185810.020983TrueFalse5.432915e+17Falsebulk_1.0.0
3ZTF18aavoomb52427141371501000258278.271412252427141371520.413221-1524240.6451355.740913...0.0774481120237.017.337175100.0000000.015342TrueFalse5.432915e+17Falsebulk_1.0.0
4ZTF18aavoomb52720978371501501358281.209780252720978371520.6458971527240.6451555.740854...0.0297481120237.016.412691100.0000000.007246TrueFalse5.432915e+17Falsebulk_1.0.0
..................................................................
1209ZTF21acceboj179633692561501500059550.3369212179633692561520.4802951179679.087644-13.477760...0.0480305120256.017.2224640.0021940.035514TrueTrueNaNTruecorrection_1.0.6
1210ZTF21acceboj179633739141501501959550.3373962179633739141520.4019451179679.087643-13.477791...0.0522356120214.0NaNNaNNaNFalseFalseNaNTruecorrection_1.0.6
1211ZTF21acceboj187016995561501500159624.1699542187016995561519.5476931187079.087639-13.477712...0.3668305120256.018.107824100.0000000.054231TrueTrueNaNTruecorrection_1.0.6
1212ZTF21acceboj187314733561501500159627.1473382187314733561519.5003001187379.087541-13.477598...0.8670NaN18.134502100.0000000.062755TrueTrue1.882136e+18Falsecorrection_1.0.6
1213ZTF21acceboj188213576561501500159636.1357642188213576561520.1187271188279.087663-13.477771...0.4920305120256.018.160744100.0000000.035231TrueTrueNaNTruecorrection_1.0.6
\n", + "

1214 rows × 30 columns

\n", + "
" + ], + "text/plain": [ + " oid candid mjd fid pid \\\n", + "0 ZTF18aavoomb 503315013715010004 58257.315012 2 503315013715 \n", + "1 ZTF18aavoomb 503356783715015005 58257.356782 2 503356783715 \n", + "2 ZTF18aavoomb 514374363715015003 58268.374363 2 514374363715 \n", + "3 ZTF18aavoomb 524271413715010002 58278.271412 2 524271413715 \n", + "4 ZTF18aavoomb 527209783715015013 58281.209780 2 527209783715 \n", + "... ... ... ... ... ... \n", + "1209 ZTF21acceboj 1796336925615015000 59550.336921 2 1796336925615 \n", + "1210 ZTF21acceboj 1796337391415015019 59550.337396 2 1796337391415 \n", + "1211 ZTF21acceboj 1870169955615015001 59624.169954 2 1870169955615 \n", + "1212 ZTF21acceboj 1873147335615015001 59627.147338 2 1873147335615 \n", + "1213 ZTF21acceboj 1882135765615015001 59636.135764 2 1882135765615 \n", + "\n", + " diffmaglim isdiffpos nid ra dec ... sigmagapbig \\\n", + "0 20.405800 -1 503 240.645156 5.740859 ... 0.0633 \n", + "1 20.490700 1 503 240.645233 5.740790 ... 0.0854 \n", + "2 19.249200 1 514 240.645160 5.740850 ... 0.1288 \n", + "3 20.413221 -1 524 240.645135 5.740913 ... 0.0774 \n", + "4 20.645897 1 527 240.645155 5.740854 ... 0.0297 \n", + "... ... ... ... ... ... ... ... \n", + "1209 20.480295 1 1796 79.087644 -13.477760 ... 0.0480 \n", + "1210 20.401945 1 1796 79.087643 -13.477791 ... 0.0522 \n", + "1211 19.547693 1 1870 79.087639 -13.477712 ... 0.3668 \n", + "1212 19.500300 1 1873 79.087541 -13.477598 ... 0.8670 \n", + "1213 20.118727 1 1882 79.087663 -13.477771 ... 0.4920 \n", + "\n", + " rfid magpsf_corr sigmapsf_corr sigmapsf_corr_ext corrected \\\n", + "0 NaN 17.445303 100.000000 0.016360 True \n", + "1 NaN 16.792156 100.000000 0.009637 True \n", + "2 NaN 16.551277 0.018581 0.020983 True \n", + "3 481120237.0 17.337175 100.000000 0.015342 True \n", + "4 481120237.0 16.412691 100.000000 0.007246 True \n", + "... ... ... ... ... ... \n", + "1209 305120256.0 17.222464 0.002194 0.035514 True \n", + "1210 356120214.0 NaN NaN NaN False \n", + "1211 305120256.0 18.107824 100.000000 0.054231 True \n", + "1212 NaN 18.134502 100.000000 0.062755 True \n", + "1213 305120256.0 18.160744 100.000000 0.035231 True \n", + "\n", + " dubious parent_candid has_stamp step_id_corr \n", + "0 False 5.272098e+17 False bulk_1.0.0 \n", + "1 False 5.272098e+17 False bulk_1.0.0 \n", + "2 False 5.432915e+17 False bulk_1.0.0 \n", + "3 False 5.432915e+17 False bulk_1.0.0 \n", + "4 False 5.432915e+17 False bulk_1.0.0 \n", + "... ... ... ... ... \n", + "1209 True NaN True correction_1.0.6 \n", + "1210 False NaN True correction_1.0.6 \n", + "1211 True NaN True correction_1.0.6 \n", + "1212 True 1.882136e+18 False correction_1.0.6 \n", + "1213 True NaN True correction_1.0.6 \n", + "\n", + "[1214 rows x 30 columns]" + ] + }, + "execution_count": 70, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "detections" + ] + }, + { + "cell_type": "code", + "execution_count": 71, + "id": "fd965a8e-9d95-43ba-8d8a-2ff20f6edb48", + "metadata": {}, + "outputs": [], + "source": [ + "oid = \"ZTF21aanrvaz\"\n", + "lc = detections[detections['oid'] == oid]\n", + "lc = lc[~lc['magpsf_corr'].isna()]" + ] + }, + { + "cell_type": "code", + "execution_count": 72, + "id": "8facebb8-8001-43c2-9f94-909f5b98c9de", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 6))\n", + "\n", + "plt.subplot(2, 2, 1)\n", + "plt.errorbar(\n", + " lc.mjd,\n", + " lc.magpsf_corr,\n", + " yerr=lc.sigmapsf_corr,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma psf corr')\n", + "\n", + "plt.subplot(2, 2, 2)\n", + "plt.errorbar(\n", + " lc.mjd,\n", + " lc.magpsf_corr,\n", + " yerr=lc.sigmapsf_corr_ext,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma psf corr ext')\n", + "\n", + "\n", + "plt.subplot(2, 2, 3)\n", + "lc_filtered = lc[lc['sigmapsf_corr'] < 1.0]\n", + "plt.errorbar(\n", + " lc_filtered.mjd,\n", + " lc_filtered.magpsf_corr,\n", + " yerr=lc_filtered.sigmapsf_corr,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma psf corr (filtered)')\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 38, + "id": "775fad66-411f-4839-910a-acbc24614ee6", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(22, 30) (12, 30)\n" + ] + } + ], + "source": [ + "print(lc.shape, lc_filtered.shape)" + ] + }, + { + "cell_type": "markdown", + "id": "bee26386-cfe9-4339-8430-4a59ea6d0bf6", + "metadata": {}, + "source": [ + "## forced photometry service data" + ] + }, + { + "cell_type": "code", + "execution_count": 39, + "id": "60535e41-394c-4163-a8b9-d071ad67dda5", + "metadata": {}, + "outputs": [], + "source": [ + "from config import db_credentials" + ] + }, + { + "cell_type": "code", + "execution_count": 40, + "id": "02aa9b4f-d2b4-4054-82cb-e25b8d5f97d6", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "dict_keys(['host', 'port', 'user', 'password', 'database'])" + ] + }, + "execution_count": 40, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "db_credentials.keys()" + ] + }, + { + "cell_type": "code", + "execution_count": 73, + "id": "1db464e1-138c-4512-8e96-b59a80a218a0", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 73, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "engine = sa.create_engine(\n", + " f\"postgresql+psycopg2://{db_credentials['user']}:{db_credentials['password']}@{db_credentials['host']}/{db_credentials['database']}\"\n", + ")\n", + "engine.begin()" + ] + }, + { + "cell_type": "code", + "execution_count": 74, + "id": "f65beede-acd8-4219-bc14-89f15cac8541", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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oidindexmjdnearestreffluxflux_totflux_diff_ujysigma_flux_diff_ujyflux_tot_ujyfluxunc_totsnr_tot...crit4flag_badforcediffimfluxunc_rescsigma_flux_diff_ujy_rescfluxunc_tot_rescfluxunc_tot_ujy_rescsnr_tot_rescsigma_mag_diff_rescsigma_mag_tot_rescdetected
0ZTF18acrgfuq103459270.1650461622.4077271679.5199836.6095117.135338194.36818361.65589127.240219...25.613558062.5482557.23861062.5482557.23861026.8515881.1890380.040433False
1ZTF18acrgfuq103559270.2261691264.1540131231.735076-3.48176010.475424132.28704397.53749812.628323...25.623456098.94918710.62703898.94918710.62703812.4481583.3137770.087218False
2ZTF18acrgfuq103659272.1846991266.6014701265.740300-0.09231010.190536135.67649395.06858113.313971...25.627688096.44453710.33802696.44453710.33802613.124023121.5901860.082726False
3ZTF18acrgfuq103759272.2155671614.5072741588.259148-3.0525188.465004184.70615472.78923821.819972...25.612078073.8427388.58752173.8427388.58752121.5086713.0543540.050477False
4ZTF18acrgfuq103859274.1652081248.9929521018.488216-25.0564688.016812110.71233473.74994713.810020...25.627431074.8173528.13284274.8173528.13284213.6129950.3523970.079755False
5ZTF18acrgfuq104159274.3397341535.0410931534.240298-0.09794912.805312187.660723104.69119314.654913...25.5408510106.20642012.990647106.20642012.99064714.445834143.9922440.075157False
6ZTF18acrgfuq104259276.1658101597.0554901510.549621-10.1701083.455814177.58856429.39479151.388344...25.614454029.8202313.50583129.8202313.50583150.6551960.3742620.021433False
7ZTF18acrgfuq104359276.2076271244.8584961013.082532-25.2783312.868238110.49047226.29875838.522068...25.623915026.6793882.90975126.6793882.90975137.9724810.1249730.028592True
8ZTF18acrgfuq104459280.1612851601.4744201510.392899-10.6785012.805276177.08017223.92740163.123985...25.614484024.2737092.84587724.2737092.84587762.2234070.2893450.017448False
9ZTF18acrgfuq104559280.2119441243.9415891126.223706-12.8482052.911010122.92059826.67126742.226104...25.620079027.0572882.95314227.0572882.95314241.6236730.2495470.026084False
\n", + "

10 rows × 31 columns

\n", + "
" + ], + "text/plain": [ + " oid index mjd nearestrefflux flux_tot \\\n", + "0 ZTF18acrgfuq 1034 59270.165046 1622.407727 1679.519983 \n", + "1 ZTF18acrgfuq 1035 59270.226169 1264.154013 1231.735076 \n", + "2 ZTF18acrgfuq 1036 59272.184699 1266.601470 1265.740300 \n", + "3 ZTF18acrgfuq 1037 59272.215567 1614.507274 1588.259148 \n", + "4 ZTF18acrgfuq 1038 59274.165208 1248.992952 1018.488216 \n", + "5 ZTF18acrgfuq 1041 59274.339734 1535.041093 1534.240298 \n", + "6 ZTF18acrgfuq 1042 59276.165810 1597.055490 1510.549621 \n", + "7 ZTF18acrgfuq 1043 59276.207627 1244.858496 1013.082532 \n", + "8 ZTF18acrgfuq 1044 59280.161285 1601.474420 1510.392899 \n", + "9 ZTF18acrgfuq 1045 59280.211944 1243.941589 1126.223706 \n", + "\n", + " flux_diff_ujy sigma_flux_diff_ujy flux_tot_ujy fluxunc_tot snr_tot \\\n", + "0 6.609511 7.135338 194.368183 61.655891 27.240219 \n", + "1 -3.481760 10.475424 132.287043 97.537498 12.628323 \n", + "2 -0.092310 10.190536 135.676493 95.068581 13.313971 \n", + "3 -3.052518 8.465004 184.706154 72.789238 21.819972 \n", + "4 -25.056468 8.016812 110.712334 73.749947 13.810020 \n", + "5 -0.097949 12.805312 187.660723 104.691193 14.654913 \n", + "6 -10.170108 3.455814 177.588564 29.394791 51.388344 \n", + "7 -25.278331 2.868238 110.490472 26.298758 38.522068 \n", + "8 -10.678501 2.805276 177.080172 23.927401 63.123985 \n", + "9 -12.848205 2.911010 122.920598 26.671267 42.226104 \n", + "\n", + " ... crit4 flag_bad forcediffimfluxunc_resc \\\n", + "0 ... 25.613558 0 62.548255 \n", + "1 ... 25.623456 0 98.949187 \n", + "2 ... 25.627688 0 96.444537 \n", + "3 ... 25.612078 0 73.842738 \n", + "4 ... 25.627431 0 74.817352 \n", + "5 ... 25.540851 0 106.206420 \n", + "6 ... 25.614454 0 29.820231 \n", + "7 ... 25.623915 0 26.679388 \n", + "8 ... 25.614484 0 24.273709 \n", + "9 ... 25.620079 0 27.057288 \n", + "\n", + " sigma_flux_diff_ujy_resc fluxunc_tot_resc fluxunc_tot_ujy_resc \\\n", + "0 7.238610 62.548255 7.238610 \n", + "1 10.627038 98.949187 10.627038 \n", + "2 10.338026 96.444537 10.338026 \n", + "3 8.587521 73.842738 8.587521 \n", + "4 8.132842 74.817352 8.132842 \n", + "5 12.990647 106.206420 12.990647 \n", + "6 3.505831 29.820231 3.505831 \n", + "7 2.909751 26.679388 2.909751 \n", + "8 2.845877 24.273709 2.845877 \n", + "9 2.953142 27.057288 2.953142 \n", + "\n", + " snr_tot_resc sigma_mag_diff_resc sigma_mag_tot_resc detected \n", + "0 26.851588 1.189038 0.040433 False \n", + "1 12.448158 3.313777 0.087218 False \n", + "2 13.124023 121.590186 0.082726 False \n", + "3 21.508671 3.054354 0.050477 False \n", + "4 13.612995 0.352397 0.079755 False \n", + "5 14.445834 143.992244 0.075157 False \n", + "6 50.655196 0.374262 0.021433 False \n", + "7 37.972481 0.124973 0.028592 True \n", + "8 62.223407 0.289345 0.017448 False \n", + "9 41.623673 0.249547 0.026084 False \n", + "\n", + "[10 rows x 31 columns]" + ] + }, + "execution_count": 74, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "query_detections = f\"\"\"\n", + "SELECT * FROM processed\n", + "limit 10;\n", + "\"\"\"\n", + "detections = pd.read_sql_query(query_detections, con=engine)\n", + "detections" + ] + }, + { + "cell_type": "code", + "execution_count": 75, + "id": "9e0be0b5-9793-4314-b749-59bfc84ac4b5", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + " oid index mjd nearestrefflux flux_tot \\\n", + "0 ZTF21aanrvaz 0 58206.407523 9424.103604 9878.522377 \n", + "1 ZTF21aanrvaz 1 58206.448449 9505.173573 10024.240190 \n", + "2 ZTF21aanrvaz 2 58218.404826 18232.237371 19639.762119 \n", + "3 ZTF21aanrvaz 3 58218.449224 17955.601838 18928.687810 \n", + "4 ZTF21aanrvaz 4 58234.334259 6518.685849 6304.817106 \n", + "... ... ... ... ... ... \n", + "2090 ZTF21aanrvaz 379 60063.376736 19848.146939 28069.724480 \n", + "2091 ZTF21aanrvaz 380 60063.440127 8492.587925 11623.302088 \n", + "2092 ZTF21aanrvaz 381 60067.357014 18684.434858 26193.159916 \n", + "2093 ZTF21aanrvaz 382 60077.313599 19455.391138 27308.624501 \n", + "2094 ZTF21aanrvaz 383 60077.377130 8662.436258 11419.164854 \n", + "\n", + " flux_diff_ujy sigma_flux_diff_ujy flux_tot_ujy fluxunc_tot \\\n", + "0 54.804506 8.659411 1191.384616 71.800644 \n", + "1 62.067335 8.500290 1198.647446 71.087578 \n", + "2 191.785619 5.188100 2676.062321 38.075741 \n", + "3 134.632904 4.951917 2618.909605 35.790962 \n", + "4 -37.289565 9.739662 1099.290546 55.860382 \n", + "... ... ... ... ... \n", + "2090 1029.046873 8.067608 3513.323574 64.456215 \n", + "2091 418.989769 6.395205 1555.569879 47.785316 \n", + "2092 998.357770 14.851993 3482.634472 111.702972 \n", + "2093 1002.786556 8.482674 3487.063258 66.431305 \n", + "2094 361.704583 6.903179 1498.284693 52.612522 \n", + "\n", + " snr_tot ... crit4 flag_bad forcediffimfluxunc_resc \\\n", + "0 137.582643 ... 25.529315 0 134.490156 \n", + "1 141.012544 ... 25.538550 0 133.154509 \n", + "2 515.807745 ... 25.546116 0 71.319867 \n", + "3 528.867813 ... 25.533275 0 67.040235 \n", + "4 112.867418 ... 25.531204 0 104.632369 \n", + "... ... ... ... ... ... \n", + "2090 435.485150 ... 25.542984 0 120.733268 \n", + "2091 243.240038 ... 25.460354 0 89.506922 \n", + "2092 234.489373 ... 25.545012 0 209.231412 \n", + "2093 411.080657 ... 25.545888 0 124.432820 \n", + "2094 217.042719 ... 25.503416 0 98.548786 \n", + "\n", + " sigma_flux_diff_ujy_resc fluxunc_tot_resc fluxunc_tot_ujy_resc \\\n", + "0 16.219987 134.490156 16.219987 \n", + "1 15.921936 133.154509 15.921936 \n", + "2 9.717857 71.319867 9.717857 \n", + "3 9.275462 67.040235 9.275462 \n", + "4 18.243412 104.632369 18.243412 \n", + "... ... ... ... \n", + "2090 15.111478 120.733268 15.111478 \n", + "2091 11.978891 89.506922 11.978891 \n", + "2092 27.819344 209.231412 27.819344 \n", + "2093 15.888941 124.432820 15.888941 \n", + "2094 12.930380 98.548786 12.930380 \n", + "\n", + " snr_tot_resc sigma_mag_diff_resc sigma_mag_tot_resc detected \n", + "0 73.451639 0.321325 0.014781 True \n", + "1 75.282770 0.278511 0.014422 True \n", + "2 275.375755 0.055013 0.003943 True \n", + "3 282.348171 0.074799 0.003845 True \n", + "4 60.256851 0.531164 0.018018 False \n", + "... ... ... ... ... \n", + "2090 232.493702 0.015943 0.004670 True \n", + "2091 129.859254 0.031040 0.008361 True \n", + "2092 125.187512 0.030253 0.008673 True \n", + "2093 219.464805 0.017203 0.004947 True \n", + "2094 115.873217 0.038812 0.009370 True \n", + "\n", + "[2095 rows x 31 columns]\n", + "Index(['oid', 'index', 'mjd', 'nearestrefflux', 'flux_tot', 'flux_diff_ujy',\n", + " 'sigma_flux_diff_ujy', 'flux_tot_ujy', 'fluxunc_tot', 'snr_tot',\n", + " 'fluxunc_tot_ujy', 'mag_tot', 'sigma_mag_tot', 'mag_diff',\n", + " 'sigma_mag_diff', 'isdiffpos', 'fid', 'secz', 'ccdquadid', 'zpthres',\n", + " 'crit1', 'crit4', 'flag_bad', 'forcediffimfluxunc_resc',\n", + " 'sigma_flux_diff_ujy_resc', 'fluxunc_tot_resc', 'fluxunc_tot_ujy_resc',\n", + " 'snr_tot_resc', 'sigma_mag_diff_resc', 'sigma_mag_tot_resc',\n", + " 'detected'],\n", + " dtype='object')\n" + ] + } + ], + "source": [ + "oids = [\"ZTF18acrgfuq\", \"ZTF21acceboj\", \"ZTF21aanrvaz\"]\n", + "oids = [f\"'{oid}'\" for oid in oids]\n", + "\n", + "query_detections = f\"\"\"\n", + "SELECT * FROM processed\n", + "WHERE oid in ({','.join(oids)});\n", + "\"\"\"\n", + "detections = pd.read_sql_query(query_detections, con=engine)\n", + "print(detections)\n", + "print(detections.columns)" + ] + }, + { + "cell_type": "code", + "execution_count": 76, + "id": "28995d0c-ed71-4219-9d98-3db21a4218b2", + "metadata": {}, + "outputs": [], + "source": [ + "oid = \"ZTF21aanrvaz\"\n", + "lc = detections[detections['oid'] == oid]" + ] + }, + { + "cell_type": "code", + "execution_count": 77, + "id": "320e34a0-756d-4a26-9b5d-2212bd69d42b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "plt.figure(figsize=(12, 6))\n", + "\n", + "plt.subplot(2, 2, 1)\n", + "plt.errorbar(\n", + " lc.mjd,\n", + " lc.mag_tot,\n", + " yerr=lc.sigma_mag_tot,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma mag tot')\n", + "\n", + "plt.subplot(2, 2, 2)\n", + "plt.errorbar(\n", + " lc.mjd,\n", + " lc.mag_tot,\n", + " yerr=lc.sigma_mag_tot_resc,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma mag tot resc')\n", + "\n", + "\n", + "lc_short = lc[lc.mjd > 59400]\n", + "plt.subplot(2, 2, 3)\n", + "plt.errorbar(\n", + " lc_short.mjd,\n", + " lc_short.mag_tot,\n", + " yerr=lc_short.sigma_mag_tot,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma mag tot')\n", + "\n", + "plt.subplot(2, 2, 4)\n", + "plt.errorbar(\n", + " lc_short.mjd,\n", + " lc_short.mag_tot,\n", + " yerr=lc_short.sigma_mag_tot_resc,\n", + " fmt='.'\n", + ")\n", + "plt.gca().invert_yaxis()\n", + "plt.title('sigma mag tot resc')\n", + "\n", + "\n", + "plt.tight_layout()" + ] + }, + { + "cell_type": "code", + "execution_count": 68, + "id": "f6b4d68f-1416-459f-ac32-a01ed70b70a8", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "(634, 31) (178, 31)\n" + ] + } + ], + "source": [ + "print(lc.shape, lc_short.shape)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "07e0bbeb-8f8f-4914-a993-17de67d00dbb", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/xmatch_step/tests/integration/conftest.py b/xmatch_step/tests/integration/conftest.py index 010625760..c2edf6b51 100644 --- a/xmatch_step/tests/integration/conftest.py +++ b/xmatch_step/tests/integration/conftest.py @@ -4,6 +4,12 @@ from confluent_kafka.admin import AdminClient, NewTopic +@pytest.fixture(scope="session") +def docker_compose_command(): + version = os.getenv("COMPOSE", "v2") + return "docker compose" if version == "v2" else "docker-compose" + + @pytest.fixture(scope="session") def docker_compose_file(pytestconfig): return os.path.join(