Add a new filter for Blazar and BLLac

fink_filters/filter_blazar/filter.py

@@ -0,0 +1,70 @@
+# Copyright 2023 AstroLab Software
+# Author: Julien Peloton
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+from pyspark.sql.functions import pandas_udf, PandasUDFType
+from pyspark.sql.types import BooleanType
+
+from fink_filters.tester import spark_unit_tests
+
+import pandas as pd
+
+from typing import Any
+
+@pandas_udf(BooleanType(), PandasUDFType.SCALAR)
+def blazar(cdsxmatch: Any) -> pd.Series:
+    """ Return alerts identified as Blazar or BLLac by the xmatch module.
+
+    Parameters
+    ----------
+    cdsxmatch: Spark DataFrame Column
+        Column containing the cross-match values
+
+    Returns
+    ----------
+    out: pandas.Series of bool
+        Return a Pandas DataFrame with the appropriate flag:
+        false for bad alert, and true for good alert.
+
+    Examples
+    ----------
+    >>> from fink_utils.spark.utils import apply_user_defined_filter
+    >>> df = spark.read.format('parquet').load('datatest')
+    >>> f = 'fink_filters.filter_blazar.filter.blazar'
+    >>> df = apply_user_defined_filter(df, f)
+    >>> print(df.count())
+    10
+
+    >>> df.groupby('cdsxmatch').count().show()
+    +----------------+-----+
+    |       cdsxmatch|count|
+    +----------------+-----+
+    |Blazar_Candidate|    3|
+    |           BLLac|    4|
+    |          Blazar|    3|
+    +----------------+-----+
+
+    """
+    # Include new taxonomy
+    classes = ['Blazar', 'Blazar_Candidate', 'BLLac', 'BLLac_Candidate']
+    mask = cdsxmatch.isin(classes)
+
+    return pd.Series(mask)
+
+
+if __name__ == "__main__":
+    """ Execute the test suite """
+
+    # Run the test suite
+    globs = globals()
+    spark_unit_tests(globs)