Replace 10**9 by straxen.units.s

straxen/analyses/bokeh_waveform_plot.py

@@ -727,7 +727,7 @@ def _make_event_title(event, run_id, width=1600):
     """
     start = event["time"]
     date = np.datetime_as_string(start.astype("<M8[ns]"), unit="s")
-    start_ns = start - (start // 10**9) * 10**9
+    start_ns = start - (start // straxen.units.s) * straxen.units.s
     end = strax.endtime(event)
     end_ns = end - start + start_ns
     event_number = event["event_number"]

straxen/config/protocols.py

@@ -315,5 +315,5 @@ def get_run_start(run_id):
     )
     start_time = doc["start"]
     start_time_unix = start_time.replace(tzinfo=pytz.utc).timestamp()
-    start_time_unix = np.int64(start_time_unix) * 10**9
+    start_time_unix = np.int64(start_time_unix) * straxen.units.s
     return start_time_unix

straxen/holoviews/holoviews_tpc_event_display.py

@@ -165,7 +165,7 @@ def _pmt_pattern_callback(self, event_index, top_pmt_array=True, pattern_ops=imm
         s2_plot = pmt_array.plot_pmt_array(
             self._s2,
             label="S2",
-            logz=True,  # TODO make me optional?
+            logz=True,  # TODO: make me optional?
             **pattern_ops,
         )
         s2_point = hv.Points(
@@ -178,7 +178,7 @@ def _pmt_pattern_callback(self, event_index, top_pmt_array=True, pattern_ops=imm
             alt_s2_plot = pmt_array.plot_pmt_array(
                 self._alt_s2,
                 label="alt. S2",
-                logz=True,  # TODO make me optional?
+                logz=True,  # TODO: make me optional?
                 **pattern_ops,
             )
             alt_s2_point = hv.Points(

straxen/holoviews_utils.py

@@ -433,7 +433,7 @@ def _make_title(self, ind):
         """Function which creates title test in markdown format."""
         start = self.df_event_time.loc[ind, "time"]
         date = np.datetime_as_string(start.astype("<M8[ns]"), unit="s")
-        start_ns = start - (start // 10**9) * 10**9
+        start_ns = start - (start // straxen.units.s) * straxen.units.s
         end = self.df_event_time.loc[ind, "endtime"]
         end_ns = end - start + start_ns
         return "".join(

straxen/misc.py

@@ -228,11 +228,11 @@ def get_start_end(self):
         start, start_ns = self._convert_to_datetime(self._start_widget, time_zone)
         start = start.astimezone(tz=pytz.UTC)
         start = start.timestamp()
-        start = int(start * 10**9) + start_ns
+        start = int(start * straxen.units.s) + start_ns
         end, end_ns = self._convert_to_datetime(self._end_widget, time_zone)
         end = end.astimezone(tz=pytz.UTC)
         end = end.timestamp()
-        end = int(end * 10**9) + end_ns
+        end = int(end * straxen.units.s) + end_ns
 
         if start > end:
             warnings.warn("Start time is larger than endtime are you sure you wanted this?")

straxen/plugins/gps_syncing/gps_syncing.py

@@ -15,7 +15,7 @@ class GpsSync(strax.OverlapWindowPlugin):
     1. Finds the TTL GPS pulses coming into the AM from the gps
     module and their pairs coming from the module for the
     correspondent run.
-      2. Corrects the timestamp of all events by linearly interpolating
+    2. Corrects the timestamp of all events by linearly interpolating
     between the previous and next sync pulses.
 
     """
@@ -51,7 +51,7 @@ class GpsSync(strax.OverlapWindowPlugin):
     def get_window_size(self):
         # Use a large window to ensure that multiple GPS pulses are found
         # within the current chunk. Specified window is in nanoseconds.
-        return int(120 * 10**9)
+        return int(120 * straxen.units.s)
 
     def setup(self):
         # Load GPS-module pulses
@@ -101,8 +101,8 @@ def match_gps_pulses_with_truth(gps_pulse_time, gps_truth_time, vicinity):
 
         """
         _gps_pulses = np.zeros(len(gps_pulse_time), strax.time_fields)
-        _gps_pulses["time"] = gps_pulse_time - int(vicinity * 10**9)
-        _gps_pulses["endtime"] = gps_pulse_time + int(vicinity * 10**9)
+        _gps_pulses["time"] = gps_pulse_time - int(vicinity * straxen.units.s)
+        _gps_pulses["endtime"] = gps_pulse_time + int(vicinity * straxen.units.s)
 
         _gps_truth = np.zeros(len(gps_truth_time), strax.time_fields)
         _gps_truth["time"] = gps_truth_time

straxen/scada.py

@@ -190,7 +190,7 @@ def get_scada_values(
         df = df.tz_localize(tz="UTC")
         df.index.rename("time UTC", inplace=True)
 
-        if (end // 10**9) > now.astype(np.int64):
+        if (end // straxen.units.s) > now.astype(np.int64):
             df.loc[now:, :] = np.nan
 
         return df
@@ -240,20 +240,20 @@ def _get_and_check_start_end(self, run_id, start, end, time_selection_kwargs):
             )
 
         now = np.datetime64("now")
-        if (end // 10**9) > now.astype(np.int64):
+        if (end // straxen.units.s) > now.astype(np.int64):
             mes = (
                 "You are asking for an endtime which is in the future,"
                 " I may be written by a physicist, but I am neither self-"
                 "aware nor can I predict the future like they can. You "
-                f"asked for the endtime: {end // 10**9} but current utc "
+                f"asked for the endtime: {end // straxen.units.s} but current utc "
                 f"time is {now.astype(np.int64)}. I will return for the values for the "
                 "corresponding times as nans instead."
             )
             warnings.warn(mes)
 
         # Chop start/end time if precision is higher then seconds level.
-        start = (start // 10**9) * 10**9
-        end = (end // 10**9) * 10**9
+        start = (start // straxen.units.s) * straxen.units.s
+        end = (end // straxen.units.s) * straxen.units.s
 
         return int(start), int(end), now
 
@@ -302,9 +302,11 @@ def _query_single_parameter(
         if query_type_lab:
             # In the lab case we get interpolated data without nans so the df can be set
             # accordingly.
-            seconds = np.arange(start, end + 1, 10**9 * every_nth_value)
+            seconds = np.arange(start, end + 1, straxen.units.s * every_nth_value)
         else:
-            seconds = np.arange(start, end + 1, 10**9)  # +1 to make sure endtime is included
+            seconds = np.arange(
+                start, end + 1, straxen.units.s
+            )  # +1 to make sure endtime is included
 
         df = pd.DataFrame()
         df.loc[:, "time"] = seconds
@@ -319,7 +321,7 @@ def _query_single_parameter(
             # This is only needed in case of raw data since here it can
             # happen that the user queries a range without any data.
             temp_df = self._query(
-                query, self.SCLastValue_URL, end=(start // 10**9) + 1
+                query, self.SCLastValue_URL, end=(start // straxen.units.s) + 1
             )  # +1 since it is end before exclusive
 
             # Store value as first value in our df
@@ -328,7 +330,7 @@ def _query_single_parameter(
         else:
             offset = 0
 
-        one_year_in_ns = int(24 * 3600 * 360 * 10**9)
+        one_year_in_ns = int(24 * 3600 * 360 * straxen.units.s)
         starts = np.arange(start + offset, end, one_year_in_ns)
         if len(starts):
             ends = starts + one_year_in_ns
@@ -401,8 +403,8 @@ def _query_data_per_year(
             temp_df = self._query(
                 query,
                 self.SCData_URL,
-                start=(start // 10**9),
-                end=(end // 10**9),
+                start=(start // straxen.units.s),
+                end=(end // straxen.units.s),
                 query_type_lab=query_type_lab,
                 seconds_interval=seconds_interval,
                 raise_error_message=False,  # No valid value in query range...
@@ -411,12 +413,12 @@ def _query_data_per_year(
                 # In case WebInterface does not return any data, e.g. if query range too small
                 break
 
-            times = (temp_df["timestampseconds"].values * 10**9).astype("<M8[ns]")
+            times = (temp_df["timestampseconds"].values * straxen.units.s).astype("<M8[ns]")
             result_dataframe.loc[times, parameter_name] = temp_df.loc[:, "value"].values
-            endtime = temp_df["timestampseconds"].values[-1].astype(np.int64) * 10**9
+            endtime = temp_df["timestampseconds"].values[-1].astype(np.int64) * straxen.units.s
             start = endtime  # Next query should start at the last time seen.
             ntries += 1
-            if not (len(temp_df) == 35000 and endtime != end // 10**9):
+            if not (len(temp_df) == 35000 and endtime != end // straxen.units.s):
                 # Max query are 35000 values, if end is reached the
                 # length of the dataframe is either smaller or the last
                 # time value is equivalent to queried range.

straxen/scripts/ajax.py

@@ -41,8 +41,7 @@
     # this many seconds ago to e.g. allow for saving et cetera
     "wait_after_processing": 12 * 3600,  # s
     # Remove high level plugins if the run is this old
-    # TODO
-    # change the value to a different one
+    # TODO: change the value to a different one
     "remove_high_level_data": 365 * 24 * 3600,  # s
     # Minimum time for restarting ajax to check for new stuff to clean (essentially the
     # timeout)

straxen/scripts/bootstrax.py

@@ -1333,7 +1333,7 @@ def run_strax(
         log.info(f"Starting strax to make {run_id} with input dir {input_dir}")
 
         if targets == strax.to_str_tuple("led_calibration"):
-            # TODO, still true?
+            # TODO: still true?
             # timeout *= 5
             pass
 

straxen/storage/rucio_remote.py

@@ -212,7 +212,7 @@ def _saver(self, dirname, metadata, **kwargs):
 
 @export
 class RucioSaver(strax.Saver):
-    """TODO Saves data to rucio if you are the production user."""
+    """TODO: Saves data to rucio if you are the production user."""
 
     def __init__(self, *args, **kwargs):
         raise NotImplementedError

tests/plugins/peak_building.py

@@ -27,7 +27,7 @@ def test_sum_wf(self: PluginTestCase):
     np.testing.assert_array_almost_equal(
         peaks["area_fraction_top"],
         np.sum(peaks["data_top"], axis=1) / np.sum(peaks["data"], axis=1),
-        # TODO rather high tolerance is needed to pass the test -> possible bug?
+        # TODO: rather high tolerance is needed to pass the test -> possible bug?
         decimal=4,
     )
 
@@ -56,7 +56,7 @@ def test_saturation_correction(self: PluginTestCase):
         records=records["records"], start=np.min(rr["time"]), end=np.max(strax.endtime(rr))
     )
     assert len(peaklets)
-    # TODO add more tests to see if results make sense
+    # TODO: add more tests to see if results make sense
 
 
 @PluginTestAccumulator.register("test_tight_coincidence")

tests/test_scada.py

@@ -13,7 +13,7 @@ def setUp(self):
         self.start = 1609682275000000000
         # Add micro-second to check if query does not fail if inquery precsion > SC precision
         self.start += 10**6
-        self.end = self.start + 5 * 10**9
+        self.end = self.start + 5 * straxen.units.s
 
     def test_wrong_querries(self):
         parameters = {"SomeParameter": "XE1T.CTPC.Board06.Chan011.VMon"}