[SSOFT] add yearly processing for ephemerides

fink_utils/sso/ssoft.py

@@ -18,6 +18,8 @@
 from pyspark.sql import SparkSession
 import pyspark.sql.functions as F
 
+from astropy.time import Time
+
 from fink_utils.tester import spark_unit_tests
 
 COLUMNS = {
@@ -475,16 +477,27 @@ def join_aggregated_sso_data(df_prev, df_new, on="ssnamenr", output_filename=Non
 
 
 def aggregate_ztf_sso_data(
-    year, month, prefix_path="archive/science", output_filename=None
+    year,
+    month=None,
+    stop_previous_month=False,
+    prefix_path="archive/science",
+    output_filename=None,
 ):
     """Aggregate ZTF SSO data in Fink
 
     Parameters
     ----------
     year: str
         Year date in format YYYY.
-    month: str
-        Month date in format MM.
+    month: str, optional
+        Month date in format MM. Default is None, in
+        which case `year` only will be considered.
+    stop_previous_month: bool, optional
+        If True, load data only until previous month.
+        To use only with month=None, to reconstruct
+        data from the current year.
+    prefix_path: str, optional
+        Prefix path on HDFS. Default is archive/science
     output_filename: str, optional
         If given, save data on HDFS. Cannot overwrite. Default is None.
 
@@ -496,9 +509,18 @@ def aggregate_ztf_sso_data(
     Examples
     --------
     >>> path = "fink_utils/test_data/benoit_julien_2025/science"
+
+    Check monthly aggregation
     >>> df_agg = aggregate_ztf_sso_data(year=2025, month=1, prefix_path=path)
     >>> assert df_agg.count() == 1, df_agg.count()
 
+    >>> out = df_agg.collect()
+    >>> assert len(out[0]["cfid"]) == 3, len(out[0]["cfid"])
+
+    Check yearly aggregation
+    >>> df_agg = aggregate_ztf_sso_data(year=2025, prefix_path=path)
+    >>> assert df_agg.count() == 1, df_agg.count()
+
     >>> out = df_agg.collect()
     >>> assert len(out[0]["cfid"]) == 3, len(out[0]["cfid"])
     """
@@ -513,11 +535,20 @@ def aggregate_ztf_sso_data(
         "candidate.jd",
     ]
 
-    df = (
-        spark.read.format("parquet")
-        .option("basePath", prefix_path)
-        .load("{}/year={}/month={}".format(prefix_path, year, month))
-    )
+    if month is not None:
+        path = "{}/year={}/month={}".format(prefix_path, year, month)
+    else:
+        path = "{}/year={}".format(prefix_path, year)
+
+    df = spark.read.format("parquet").option("basePath", prefix_path).load(path)
+
+    if month is None and stop_previous_month:
+        prevdate = retrieve_last_date_of_previous_month(datetime.datetime.today())
+        # take the last hour of the last day
+        prevdate = prevdate.replace(hour=23)
+        jd0 = Time(prevdate, format="datetime").jd
+        df = df.filter(df["candidate.jd"] <= jd0)
+
     df_agg = (
         df.select(cols0 + cols)
         .filter(F.col("roid") == 3)

fink_utils/sso/utils.py

@@ -26,10 +26,12 @@
 import astropy.units as u
 
 from scipy import signal
+from line_profiler import profile
 
 from fink_utils.tester import regular_unit_tests
 
 
+@profile
 def query_miriade(
     ident,
     jd,
@@ -129,6 +131,7 @@ def query_miriade(
     return ephem
 
 
+@profile
 def query_miriade_ephemcc(
     ident,
     jd,
@@ -236,6 +239,7 @@ def query_miriade_ephemcc(
     return ephem
 
 
+@profile
 def get_miriade_data(
     pdf,
     sso_colname="i:ssnamenr",