Merge pull request #283 from cta-observatory/show_run_summary

Remove show_run_summary + rename show_run_summary_tcu

src/osa/scripts/show_run_summary.py

@@ -1,30 +1,18 @@
 """
-Display summary of the observations for a given date.
-
-Show the run summary for a given date containing the number of subruns,
-the start and end time of the run and type pf the run: DATA, DRS4, PEDCALIB.
+Print out basic run summary for a given date with run numbers, type of runs,
+start and stop timestamps and elapsed times.
 """
 
 import argparse
-import logging
-import os
+import datetime
 from pathlib import Path
 
+import astropy.units as u
 import numpy as np
-from astropy import units as u
 from astropy.table import Table
-from astropy.time import Time
-from lstchain.scripts.lstchain_create_run_summary import (
-    get_list_of_files,
-    get_list_of_runs,
-    get_runs_and_subruns,
-    type_of_run,
-    read_counters,
-)
-
-from osa.utils.logging import myLogger
+from lstchain.scripts.lstchain_create_run_summary import get_list_of_files, get_list_of_runs
 
-log = myLogger(logging.getLogger(__name__))
+from osa.nightsummary.database import get_run_info_from_TCU
 
 parser = argparse.ArgumentParser(description="Create run summary file")
 
@@ -42,138 +30,60 @@
     default=Path("/fefs/aswg/data/real/R0"),
 )
 
-dtypes = {
-    "time_start": str,
-    "time_end": str,
-    "elapsed": u.quantity.Quantity,
-}
-
-
-def start_end_of_run_files_stat(r0_path: Path, run_number: int, num_files: int):
-    """
-    Get first timestamps from the last subrun.
-    Write down the reference Dragon module used, reference event_id.
-
-    Notes
-    -----
-    Start and end times are currently taken from the creation and last modification
-    time of the first and last file in the run. They are approximate and may be off
-    by a few seconds.
-
-    Parameters
-    ----------
-    r0_path : pathlib.Path
-        Directory that contains the R0 files
-    run_number : int
-        Number of the run
-    num_files : int
-        Number of the sequential files (subruns) of a given run
-
-    Returns
-    -------
-    end_timestamp
-    """
-
-    last_subrun = num_files - 1  # first subrun is 0
-    pattern_first_subrun = r0_path / f"LST-1.1.Run{run_number:05d}.0000.fits.fz"
-    pattern_last_subrun = r0_path / f"LST-1.1.Run{run_number:05d}.{last_subrun:04d}.fits.fz"
-    try:
-        # Get start and end times from the creation and last modification timestamps
-        # from the first and last file in the run
-        run_start = Time(os.path.getctime(pattern_first_subrun), format="unix")
-        run_end = Time(os.path.getmtime(pattern_last_subrun), format="unix")
-        elapsed_time = run_end - run_start
-
-        return dict(
-            time_start=run_start.iso,
-            time_end=run_end.iso,
-            elapsed=np.round(elapsed_time.to_value("min"), decimals=1),
-        )
-
-    except Exception as err:
-        log.error(f"Files {pattern_first_subrun} or {pattern_last_subrun} have error: {err}")
-
-        return dict(
-            time_start=None,
-            time_end=None,
-            elapsed=0.0,
-        )
+parser.add_argument(
+    "--tcu-db",
+    type=str,
+    help="Server of the TCU monitoring database",
+    default="lst101-int",
+)
 
 
 def main():
     """
-    Build an astropy Table with run summary information and write it
-    as ECSV file with the following information (one row per run):
-     - run_id
-     - number of subruns
-     - type of run (DRS4, CALI, DATA, CONF)
-     - start of the run
-     - dragon reference UCTS timestamp if available (-1 otherwise)
-     - dragon reference time source ("ucts" or "run_date")
-     - dragon_reference_module_id
-     - dragon_reference_module_index
-     - dragon_reference_counter
+    Get run metadata information from TCU monitoring
+    database and print out the run summary
     """
-
-    log.setLevel(logging.INFO)
-
     args = parser.parse_args()
 
+    tcu_db = args.tcu_db
     date_path = args.r0_path / args.date
-
     file_list = get_list_of_files(date_path)
-    runs = get_list_of_runs(file_list)
-    run_numbers, n_subruns = get_runs_and_subruns(runs)
-
-    reference_counters = [read_counters(date_path, run) for run in run_numbers]
-
-    run_types = [
-        type_of_run(date_path, run, counters)
-        for run, counters in zip(run_numbers, reference_counters)
-    ]
-
-    start_end_timestamps = [
-        start_end_of_run_files_stat(date_path, run, n_files)
-        for run, n_files in zip(run_numbers, n_subruns)
-    ]
-
-    run_summary = Table(
-        {
-            col: np.array([d[col] for d in start_end_timestamps], dtype=dtype)
-            for col, dtype in dtypes.items()
-        }
-    )
-
-    run_summary.add_column(run_numbers, name="run_id", index=0)
-    run_summary.add_column(n_subruns, name="n_subruns", index=1)
-    run_summary.add_column(run_types, name="run_type", index=2)
-
-    run_summary["elapsed"].unit = u.min
-
-    header = " Run summary "
-    print(f"{header.center(50, '*')}")
-    run_summary.pprint_all()
-    print("\n")
-
-    # Sum elapsed times:
-    obs_by_type = run_summary.group_by("run_type")
-    obs_by_type["number_of_runs"] = 1
-    total_obs_time = obs_by_type[
-        "run_type", "number_of_runs", "n_subruns", "elapsed"
-    ].groups.aggregate(np.sum)
-    total_obs_time["elapsed"].format = "7.1f"
-
-    header = " Observation time per run type "
-    print(f"{header.center(50, '*')}")
-    total_obs_time.pprint_all()
-    print("\n")
-
-    run_summary["number_of_runs"] = 1
-    total_obs = run_summary["number_of_runs", "n_subruns", "elapsed"].groups.aggregate(np.sum)
-    total_obs["elapsed"].format = "7.1f"
-    header = " Total observation time "
-    print(f"{header.center(50, '*')}")
-    total_obs.pprint_all()
+    all_runs = get_list_of_runs(file_list)
+    run_numbers = [x.run for x in all_runs]
+    run_numbers_array = np.unique(run_numbers)
+    run_numbers_array = run_numbers_array[run_numbers_array != 0]
+
+    list_info = []
+
+    for run in run_numbers_array:
+        run_info = get_run_info_from_TCU(int(run), tcu_server=tcu_db)
+        list_info.append(run_info)
+
+    if list_info:
+        table = Table(
+            np.array(list_info).T.tolist(),
+            names=("run", "type", "tstart", "tstop", "elapsed"),
+            dtype=(int, str, datetime.datetime, datetime.datetime, float),
+        )
+        table["elapsed"].unit = u.min
+        table["elapsed"].info.format = "3.1f"
+        print("\n")
+        table.pprint_all()
+
+        # Sum elapsed times:
+        obs_by_type = table.group_by("type")
+        obs_by_type["number_of_runs"] = 1
+        total_obs_time = obs_by_type["type", "number_of_runs", "elapsed"].groups.aggregate(np.sum)
+        total_obs_time["elapsed"].info.format = "7.0f"
+
+        print("\n")
+        header = " Observation time per run type "
+        print(f"{header.center(50, '*')}")
+        total_obs_time.pprint_all()
+        print("\n")
+
+    else:
+        print(f"No data found in {date_path}")
 
 
 if __name__ == "__main__":