Updated bad samples for April 20, 2026 release

.github/workflows/ci-test.yml

@@ -16,7 +16,7 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.12", "3.14"]
 
     steps:
     - uses: actions/checkout@v4
@@ -29,6 +29,7 @@ jobs:
         python -m pip install --upgrade pip
         python -m pip install pytest pytest-astropy
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
+        pip install .
     - name: Test with pytest
       run: |
         pytest --remote-data -svv nuclockutils

NEWS.rst

@@ -0,0 +1,4 @@
+nuclockutils 0.4.dev5+g48a3009ec.d20260324 (2026-03-24)
+=======================================================
+
+No significant changes.

README.rst

@@ -19,7 +19,6 @@ Installation
 
     $ git clone https://github.com/matteobachetti/nustar-clock-utils
     $ cd nustar-clock-utils
-    $ pip install -r requirements.txt
     $ pip install .
 
 Usage

docs/index.rst

@@ -11,7 +11,6 @@ Installation
 
     $ git clone https://github.com/matteobachetti/nustar-clock-utils
     $ cd nustar-clock-utils
-    $ pip install -r requirements.txt
     $ pip install .
 
 Usage

nuclockutils/__init__.py

@@ -1,5 +1,14 @@
 # Licensed under a 3-clause BSD style license - see LICENSE.rst
 
+# Time constants (all in seconds unless noted)
+SECONDS_PER_DAY = 86400
+HALF_DAY_SECONDS = 43200  # Minimum GTI duration for valid processing
+SECONDS_PER_MONTH = SECONDS_PER_DAY * 30
+SECONDS_PER_YEAR = SECONDS_PER_DAY * 365.25
+
+# Mission timeline constants (MET values)
+# MET when science operations began (end of commissioning phase)
+SCIENCE_START_MET = 77674700
 
 from .nustarclock import *
 from .utils import *

nuclockutils/barycorr.py

@@ -14,7 +14,7 @@
 import nuclockutils
 from .utils import filter_with_region, high_precision_keyword_read
 from .nustarclock import interpolate_clock_function
-
+from . import SECONDS_PER_DAY
 
 class OrbitalFunctions():
     lat_fun = None
@@ -29,7 +29,7 @@ def get_orbital_functions(orbfile):
     orbtable = Table.read(orbfile)
     mjdref = high_precision_keyword_read(orbtable.meta, 'MJDREF')
 
-    times = Time(np.array(orbtable['TIME'] / 86400 + mjdref), format='mjd')
+    times = Time(np.array(orbtable['TIME'] / SECONDS_PER_DAY + mjdref), format='mjd')
     if 'GEODETIC' in orbtable.colnames:
         geod = np.array(orbtable['GEODETIC'])
         lat, lon, alt = geod[:, 0] * u.deg, geod[:, 1] * u.deg, geod[:,
@@ -82,8 +82,8 @@ def get_barycentric_correction(orbfile, parfile, dt=5, ephem='DE421'):
         mjdref = high_precision_keyword_read(hdul[1].header, 'MJDREF')
 
     knots = no.X.get_knots()
-    mjds = np.arange(knots[1], knots[-2], dt / 86400)
-    mets = (mjds - mjdref) * 86400
+    mjds = np.arange(knots[1], knots[-2], dt / SECONDS_PER_DAY)
+    mets = (mjds - mjdref) * SECONDS_PER_DAY
 
     obs, scale = 'nustar', "tt"
     toalist = [None] * len(mjds)

nuclockutils/clean_clock/app.py

@@ -19,7 +19,7 @@
 
 from nuclockutils.nustarclock import load_temptable, load_freq_changes, \
     load_and_flag_clock_table, find_good_time_intervals, calculate_stats, \
-    eliminate_trends_in_residuals
+    eliminate_trends_in_residuals, _BAD_POINTS_FILE, FIXED_CONTROL_POINTS
 
 import dash
 from dash import dcc
@@ -64,7 +64,7 @@ def recalc(outfile='save_all.pickle'):
     met_start = clock_offset_table['met'][0]
     met_stop = clock_offset_table['met'][-1] + 30
     clock_jump_times = \
-        np.array([77469000, 78708320, 79657575, 81043985, 82055671, 293346772,
+        np.array([77469000, 78708320, 79657575, 81043985, 82055671, 293346772, 305080000,
                   392200784, 394825882, 395304135, 407914525, 408299422])
     clock_jump_times += 30 #  Sum 30 seconds to avoid to exclude these points
                            #  from previous interval
@@ -80,7 +80,7 @@ def recalc(outfile='save_all.pickle'):
 
     table_new = eliminate_trends_in_residuals(
         table_new, clock_offset_table_corr, gtis,
-        fixed_control_points=np.arange(291e6, 295e6, 86400))
+        fixed_control_points=FIXED_CONTROL_POINTS)
 
     mets = np.array(table_new['met'])
     start = mets[0]
@@ -100,6 +100,7 @@ def recalc(outfile='save_all.pickle'):
         np.array(
             clock_offset_table['offset'] - table_new['temp_corr'][tempcorr_idx]
         )
+
     clock_residuals_detrend = np.array(
         clock_offset_table['offset'] - table_new['temp_corr_detrend'][tempcorr_idx])
 
@@ -219,7 +220,7 @@ def plot_dash(all_data, table_new, gti, all_nustar_obs,
         'text': text[bad],
         'mode': 'markers',
         'name': f'Bad clock offset measurements',
-        'marker': {'color': 'grey', 'symbol': "x-dot", 'size': 3}
+        'marker': {'color': 'grey', 'symbol': "x-dot", 'size': 5}
     }), 1, 1)
 
     all_data_bad = all_data[bad]
@@ -232,7 +233,7 @@ def plot_dash(all_data, table_new, gti, all_nustar_obs,
             'text': text[bad],
             'mode': 'markers',
             'showlegend': False,
-            'marker': {'color': 'grey', 'symbol': "x-dot", 'size': 3}
+            'marker': {'color': 'grey', 'symbol': "x-dot", 'size': 5}
          }), row, 1)
 
     for station, color in zip(['MLD', 'SNG', 'UHI'], ['blue', 'red', 'orange']):
@@ -244,7 +245,7 @@ def plot_dash(all_data, table_new, gti, all_nustar_obs,
             'hovertemplate': hovertemplate,
             'text': text[good],
             'mode': 'markers',
-            'marker': {'color': color, 'size': 3},
+            'marker': {'color': color, 'size': 5},
             'name': f'Clock offset - {station}'
         }), 1, 1)
         for ydata, row in zip(['residual', 'residual_detrend'], [2, 3]):
@@ -255,7 +256,7 @@ def plot_dash(all_data, table_new, gti, all_nustar_obs,
                 'text': text[good],
                 'showlegend': False,
                 'mode': 'markers',
-                'marker': {'color': color, 'size': 3}
+                'marker': {'color': color, 'size': 5}
             }), row, 1)
 
     # bad_intervals = [[0, 77.767e6]]
@@ -270,20 +271,23 @@ def plot_dash(all_data, table_new, gti, all_nustar_obs,
             continue
         if bti[0] > all_data['met'][-1]:
             continue
-        shapes.append(dict(type="rect",
+        shapes.append(
+            dict(
+                type="rect",
                 # x-reference is assigned to the x-values
                 xref="x",
                 # y-reference is assigned to the plot paper [0,1]
                 yref="paper",
-                x0=max(bti[0], all_data['met'][0]),
+                x0=float(max(bti[0], all_data["met"][0])),
                 y0=0,
-                x1=min(bti[1], all_data['met'][-1]),
+                x1=float(min(bti[1], all_data["met"][-1])),
                 y1=1,
                 fillcolor="LightSalmon",
                 opacity=0.5,
                 layer="below",
                 line_width=0,
-            ))
+            )
+        )
 
     if axis_ranges is not None:
         if 'xaxis.range[0]' in axis_ranges:
@@ -414,8 +418,8 @@ def stored_analysis(file):
         html.Div(
             className="three columns div-for-charts bg-grey",
             children=[
-            dcc.Graph(id='temperature-time-series'),
-            dcc.Graph(id='temperature-gradient-time-series'),
+            dcc.Graph(mathjax=True, id='temperature-time-series'),
+            dcc.Graph(mathjax=True, id='temperature-gradient-time-series'),
             ]
         ),
         html.Div(id='dummy', style={'display': 'none'}),
@@ -515,20 +519,25 @@ def refresh_output(n_cl_refresh, n_cl_bad, n_cl_good, n_cl_recalc, selectedData)
 
         if who_triggered == 'recalculate-button':
             log.info("Recalculating all")
+
+            for file in ['save_all.pickle', 'dump.hdf5', 'all_data_res.pkl', 'rolling_data.pkl']:
+
+                if os.path.exists(file):
+                    log.info(f"Removing file {file}")
+                    os.unlink(file)
+
             stored_analysis.cache_clear()
-            # cache.delete_memoized(stored_analysis, 'save_all.pickle')
-            if os.path.exists('save_all.pickle'):
-                os.unlink('save_all.pickle')
+
         elif who_triggered == 'actually-good-data-button' and len(NEW_BAD_POINTS) > 0:
             log.info("Removing point(s) from bad clock offset database")
             ALL_BAD_POINTS = eliminate_array_from_array(
                 ALL_BAD_POINTS, NEW_BAD_POINTS)
-            np.savetxt('BAD_POINTS_DB.dat', ALL_BAD_POINTS, fmt='%d')
+            np.savetxt(_BAD_POINTS_FILE, ALL_BAD_POINTS, fmt='%d')
         elif who_triggered == 'bad-data-button' and len(NEW_BAD_POINTS) > 0:
             log.info("Adding point(s) to bad clock offset database")
             ALL_BAD_POINTS = merge_and_sort_arrays(
                 ALL_BAD_POINTS, NEW_BAD_POINTS)
-            np.savetxt('BAD_POINTS_DB.dat', ALL_BAD_POINTS, fmt='%d')
+            np.savetxt(_BAD_POINTS_FILE, ALL_BAD_POINTS, fmt='%d')
         else:
             log.info("Refreshing plot")
             CURRENT_AXES = default_axes()
@@ -550,39 +559,32 @@ def display_selected_data(selectedData):
 
 
     def create_temperature_timeseries(x, y, axis_type='linear'):
-        return {
-            'data': [dict(
-                x=x,
-                y=y,
-                mode='lines'
-            )],
-            'layout': {
-                'height': 300,
-                'yaxis': {'title': 'TCXO Temperature',
-                    'type': 'linear' if axis_type == 'Linear' else 'log'},
-                'xaxis': {'title': 'met', 'showgrid': False,
-                'margin':{'t': 20}}
-
-            }
-        }
+        import plotly.graph_objects as go
+        fig = go.Figure()
+        fig.add_trace(go.Scattergl(x=np.asarray(x, dtype=float),
+                                   y=np.asarray(y, dtype=float), mode="lines"))
+        fig.update_layout(
+            height=300,
+            margin=dict(t=20, b=50, l=60, r=20),
+        )
+        fig.update_xaxes(title_text="MET (s)", showgrid=False)
+        fig.update_yaxes(title_text="TCXO Temperature (°C)",
+                         type="linear" if axis_type == "linear" else "log")
+        return fig
 
 
     def create_temperature_gradient_timeseries(x, y, axis_type='linear'):
-        return {
-            'data': [dict(
-                x=x,
-                y=y,
-                mode='lines'
-            )],
-            'layout': {
-                'height': 300,
-                'yaxis': {'title': 'TCXO Temp Gradient',
-                    'type': 'linear'},
-                'xaxis': {'title': 'met', 'showgrid': False,
-                'margin':{'t': 20}}
-
-            }
-        }
+        import plotly.graph_objects as go
+        fig = go.Figure()
+        fig.add_trace(go.Scattergl(x=np.asarray(x, dtype=float),
+                                   y=np.asarray(y, dtype=float) * 1e3, mode="lines"))
+        fig.update_layout(
+            height=300,
+            margin=dict(t=20, b=50, l=60, r=20),
+        )
+        fig.update_xaxes(title_text="MET (s)", showgrid=False)
+        fig.update_yaxes(title_text=r"TCXO Temp Gradient (1e-3 °C/s)", type="linear")
+        return fig
 
 
     @app.callback(
@@ -615,6 +617,7 @@ def main(args=None):
     global FREQFILE
     global MODELVERSION
     import argparse
+    import logging
     description = ('Clean clock offset measurements with an handy web '
                    'interface.')
     parser = argparse.ArgumentParser(description=description)
@@ -630,6 +633,8 @@ def main(args=None):
                              "file in the auxil/directory "
                              "or the tp_tcxo*.csv file)")
     parser.add_argument("--temperature-model-version", default=None, help="Temperature model version")
+    parser.add_argument("--devel", action='store_true', help="Enable development mode")
+    parser.add_argument("--debug", action='store_true', help="Enable debug logging")
     args = parser.parse_args(args)
     if args.temperature_file is not None:
         TEMPFILE = args.temperature_file
@@ -639,14 +644,16 @@ def main(args=None):
         FREQFILE = args.frequency_file
     if args.temperature_model_version is not None:
         MODELVERSION = args.temperature_model_version
+    if args.debug:
+        log.setLevel(logging.DEBUG)
 
     print("Creating app")
     app = create_app()
     try:
-        app.run(debug=True)
+        app.run(debug=args.devel, use_reloader=False)
     except Exception as e:
         # Compatibility with old versions
-        app.run_server(debug=True)
+        app.run_server(debug=args.devel, use_reloader=False)
 
 
 
@@ -657,4 +664,4 @@ def main(args=None):
     FREQFILE = os.path.join(datadir, 'sample_freq.dat')
     TEMPFILE = os.path.join(datadir, 'tcxo_tmp_sample.csv')
 
-    main()
+    main()

nuclockutils/data/BAD_POINTS_DB.dat

@@ -1694,3 +1694,4 @@
 512698376
 512839329
 513133512
+513704513

nuclockutils/diagnostics/bary_and_fold_all.py

@@ -17,7 +17,7 @@
     get_ephemeris_from_parfile
 from .compare_pulses import main as main_compare_pulses
 from nuclockutils.barycorr import main_barycorr as nubarycorr
-from nuclockutils.utils import high_precision_keyword_read
+from nuclockutils.utils import high_precision_keyword_read, SECONDS_PER_DAY
 
 
 def mkdir(folder):
@@ -40,7 +40,7 @@ def get_observing_mjd(fname):
         log.error(f"{fname} might be corrupted")
         return None
 
-    return np.array([tstart, tstop]) / 86400 + mjdref
+    return np.array([tstart, tstop]) / SECONDS_PER_DAY + mjdref
 
 
 def fold_file_to_ephemeris(fname, parfile, emin=None, emax=None,
@@ -61,7 +61,7 @@ def fold_file_to_ephemeris(fname, parfile, emin=None, emax=None,
         good = good & (events.energy < emax)
 
     times = events.time[good]
-    event_mjds = times / 86400 + events.mjdref
+    event_mjds = times / SECONDS_PER_DAY + events.mjdref
     phase = correction_fun(event_mjds)
 
     t = calculate_profile_from_phase(phase, nbin=nbin)

nuclockutils/diagnostics/compare_clock_files.py

@@ -3,17 +3,17 @@
 import numpy as np
 from astropy.table import Table
 import matplotlib.pyplot as plt
-from nuclockutils.nustarclock import interpolate_clock_function
+from nuclockutils.nustarclock import interpolate_clock_function, SECONDS_PER_DAY
 
 
 def get_todays_met():
     t = Time.now()
-    met = (t.mjd - 55197.00076601852) * 86400
+    met = (t.mjd - 55197.00076601852) * SECONDS_PER_DAY
     return met
 
 def get_launch_met():
     t = Time('2012-06-12')
-    met = (t.mjd - 55197.00076601852) * 86400
+    met = (t.mjd - 55197.00076601852) * SECONDS_PER_DAY
     return met
 
 

nuclockutils/diagnostics/compare_pulses.py

@@ -7,6 +7,7 @@
 from uncertainties import ufloat
 from astropy import log
 from statsmodels.robust import mad
+from nuclockutils.utils import SECONDS_PER_DAY
 
 from .fftfit import fftfit
 
@@ -33,7 +34,7 @@ def format_profile_and_get_phase(file, template=None):
     fddot = 0
     if 'F2' in table.meta:
         fddot = table.meta['F2']
-    delta_t = (mjd - pepoch) * 86400
+    delta_t = (mjd - pepoch) * SECONDS_PER_DAY
     f0 = freq + fdot * delta_t + 0.5 * fddot * delta_t ** 2
 
     period_ms = 1 / f0 * 1000