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.github/workflows/lightkurve-tests.yml

@@ -42,7 +42,7 @@ jobs:
           - name: "3.11"
             python-version: "3.11"
             pytest-command: ./poetry/bin/poetry run pytest
-          - name: "3.12-remote-data"
+          - name: "3.12"
             python-version: "3.12"
             pytest-command: ./poetry/bin/poetry run pytest
           - name: "3.13"

CHANGES.rst

@@ -1,4 +1,9 @@
-2.5.2dev  (unreleased)
+2.6.1dev
+=====================
+- Update search URL for query_solar_system_objects [#1556]
+- Fixed search result sort order for the cases involving TESS sectors 99 and 100, etc. [#1558]
+
+2.6.0 (2026-04-16)
 =====================
 - Patch for changes to astroquery 0.4.11. Search results using GAIA DR2 now case insensitive. Integer searches converted to string. [#1511]
 - Added Folded lightcurve reader to open data saved with ``lk.FoldedLightCurve.to_fits()`` [#1488]
@@ -7,8 +12,18 @@
 - Include MOM_CENTR1 and MOM_CENTR2, if it exists, when saving fits files [#1488]
 - Fixed bugs in ``bin`` for ``flux_err`` column. Improved ``bin`` performance. [#1499]
 - Updated search result sort order [#1384]
+- When reading in data saved with to_fits, change meta.flux_origin to reflect origin [#1371]
 - Convert flux and flux_err to Quantity objects when using ``select_flux`` [#1513]
 - Fixed bugs in ``FoldedLightCurve`` objects with normalized phase to support pickle / dill [#1529]
+- Added support in ``read_generic_lightcurve()`` for FITS Standard reference time keywords like [M]JDREF [#1535]
+- Capped pandas version at <3.0.0 for breaking changes [#1534]
+- Added ability to download 20-s CBV products for TESS [#1537]
+- Changed search so that it longer emits ERROR log message when the search result is empty [#1540]
+- Fixed search by exact match for TICs with fewer than 9 digits, avoiding the extra 
+  fallback cone search [#1541]
+- Modified how SAP_QUALITY is treated when reading/writing TESS and Kepler data [#1538]
+- Added ability to use nifty-ls for periodograms [#1550]
+- Added new tutorial for read_generic_lightcurve [#1542]
 
 2.5.1  (2025-05-20)
 =====================

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "lightkurve"
-version = "2.5.2dev"
+version = "2.6.1dev"
 description = "A friendly package for Kepler & TESS time series analysis in Python."
 license = "MIT"
 authors = ["Geert Barentsen <hello@geert.io>", "TESS Science Support Center <tesshelp@bigbang.gsfc.nasa.gov>"]
@@ -36,7 +36,7 @@ beautifulsoup4 = ">=4.6.0"
 requests = ">=2.22.0"
 urllib3 = { version = ">=1.23", python = ">=3.8,<4.0" }  # necessary to make requests work on py310
 tqdm = ">=4.25.0"
-pandas = ">=1.3.6"
+pandas = ">=1.3.6, <3.0.0"
 uncertainties = ">=3.1.4"
 patsy = ">=0.5.0"
 fbpca = ">=1.0"
@@ -81,6 +81,7 @@ mistune = "<2.0.0"  # Workaround for #1162 (not a true dependency)
 # See https://github.com/python-poetry/poetry/issues/9293
 docutils = "!=0.21"
 lxml-html-clean = "^0.4.2"
+ipython = ">=7.0"
 
 [build-system]
 requires = ["poetry-core"]

src/lightkurve/correctors/cbvcorrector.py

@@ -96,7 +96,7 @@ class CBVCorrector(RegressionCorrector):
     """
 
     def __init__(self, lc, interpolate_cbvs=False, extrapolate_cbvs=False, do_not_load_cbvs=False,
-        cbv_dir=None):
+        cbv_dir=None, fast_cadence=False):
         """Constructor
 
         This constructor will retrieve all relevant CBVs from MAST and then
@@ -120,6 +120,8 @@ def __init__(self, lc, interpolate_cbvs=False, extrapolate_cbvs=False, do_not_lo
         cbv_dir : str
             Path to specific directory holding TESS CBVs. If this is None, will query
             MAST by default.
+        fast_cadence : bool
+            If True, then the 20-s fast cadence CBV file will be loaded 
         """
         if not isinstance(lc, LightCurve):
             raise Exception('<lc> must be a LightCurve class')
@@ -129,6 +131,11 @@ def __init__(self, lc, interpolate_cbvs=False, extrapolate_cbvs=False, do_not_lo
 
         if extrapolate_cbvs and (extrapolate_cbvs != interpolate_cbvs):
             raise Exception('interpolate_cbvs must be True if extrapolate_cbvs is True')
+
+        # Check if the lightkurve has 20-s cadence.
+        if hasattr(lc, 'filename'):
+            if 'fast' in lc.filename:
+                fast_cadence = True
 
         # We do not want any NaNs
         lc = lc.remove_nans()
@@ -151,7 +158,7 @@ def __init__(self, lc, interpolate_cbvs=False, extrapolate_cbvs=False, do_not_lo
                 # For TESS we load multiple CBV types
                 # Single-Scale
                 cbvs.append(load_tess_cbvs(cbv_dir=cbv_dir,sector=self.lc.sector,
-                    camera=self.lc.camera, ccd=self.lc.ccd, cbv_type='SingleScale'))
+                    camera=self.lc.camera, ccd=self.lc.ccd, cbv_type='SingleScale', fast_cadence=fast_cadence))
 
                 # Multi-Scale
                 # Although there has always been 3 bands, there could be more,
@@ -162,15 +169,15 @@ def __init__(self, lc, interpolate_cbvs=False, extrapolate_cbvs=False, do_not_lo
                     iBand += 1
                     cbvObj = load_tess_cbvs(cbv_dir=cbv_dir,sector=self.lc.sector,
                         camera=self.lc.camera, ccd=self.lc.ccd, cbv_type='MultiScale',
-                        band=iBand)
+                        band=iBand, fast_cadence=fast_cadence)
                     if (cbvObj.band == iBand):
                         cbvs.append(cbvObj)
                     else:
                         moreData = False
 
                 # Spike
                 cbvs.append(load_tess_cbvs(cbv_dir=cbv_dir,sector=self.lc.sector,
-                    camera=self.lc.camera, ccd=self.lc.ccd, cbv_type='Spike'))
+                    camera=self.lc.camera, ccd=self.lc.ccd, cbv_type='Spike', fast_cadence=fast_cadence))
 
             else:
                 raise ValueError('Unknown mission type')
@@ -1837,7 +1844,7 @@ def download_tess_cbvs(*args, **kwargs):
 
 
 def load_tess_cbvs(cbv_dir=None,sector=None, camera=None,
-        ccd=None, cbv_type='SingleScale', band=None):
+        ccd=None, cbv_type='SingleScale', band=None, fast_cadence=False):
     """Loads TESS cotrending basis vectors, either from a directory of 
     CBV files already saved locally if cbv_dir is passed, or else 
     will retrieve the relevant files programmatically from MAST. 
@@ -1863,6 +1870,8 @@ def load_tess_cbvs(cbv_dir=None,sector=None, camera=None,
         'SingleScale' or 'MultiScale' or 'Spike'
     band : int
         Multi-scale band number
+    fast_cadence : bool
+        'True' to get 20-s cadence CBVs. If False, defaults to the 2-min CBV file. 
 
     Returns
     -------
@@ -1934,7 +1943,10 @@ def load_tess_cbvs(cbv_dir=None,sector=None, camera=None,
 
         else:
             curlBaseUrl = 'https://archive.stsci.edu/missions/tess/download_scripts/sector/tesscurl_sector_'
-            curlEndUrl = '_cbv.sh'
+            if fast_cadence:
+                curlEndUrl = '_fast-cbv.sh'
+            else:
+                curlEndUrl = '_cbv.sh'
             curlUrl = curlBaseUrl + str(sector) + curlEndUrl
 
             # This is the string to search for in the curl script file

src/lightkurve/io/generic.py

@@ -99,12 +99,29 @@ def read_generic_lightcurve(
             log.debug("Ignoring {} rows with NaN times".format(np.sum(nans)))
         tab = tab[~nans]
 
+        # Set default reference time value to 0.0
+        reference_time_value = 0.0
+
         # Prepare a special time column
         if not time_format:
+            # Check for the Kepler and TESS special cases
             if hdulist[ext].header.get("BJDREFI") == 2454833: # Kepler specific
                 time_format = "bkjd"
             elif hdulist[ext].header.get("BJDREFI") == 2457000: # TESS specific
                 time_format = "btjd"
+            # Work through options from the FITS Standard  v4.0 Section 9.2.2
+            elif ("MJDREFI" in hdulist[ext].header) and ("MJDREFF" in hdulist[ext].header):  # Check if MJDREFI and MJDREFF set
+                time_format = "mjd"
+                reference_time_value = hdulist[ext].header.get("MJDREFI") + hdulist[ext].header.get("MJDREFF")
+            elif "MJDREF" in hdulist[ext].header:  # Check if MJDREF set
+                time_format = "mjd"
+                reference_time_value = hdulist[ext].header.get("MJDREF")
+            elif ("JDREFI" in hdulist[ext].header) and ("JDREFF" in hdulist[ext].header):  # Check if JDREFI and JDREFF set
+                time_format = "jd"
+                reference_time_value = hdulist[ext].header.get("JDREFI") + hdulist[ext].header.get("JDREFF")
+            elif "JDREF" in hdulist[ext].header:  # Check if JDREF set
+                time_format = "jd"
+                reference_time_value = hdulist[ext].header.get("JDREF")
             # make compatible with normalized light curves without absolute start sime (see #1502) 
             elif hdulist[ext].header.get("TIMESYS") == "local":
                 try:
@@ -115,14 +132,19 @@ def read_generic_lightcurve(
                     tab.remove_column("time")
                 except:
                     raise KeyError(f"Unclear unit for local time system: TUNIT1 must be astropy.unit value.")            # Error handling for invalid astropy.unit value or if the TUNIT1 keyword is missing from header         
-
+            # Check for nonstandard, format-flavored values of TIMESYS
             elif hdulist[ext].header.get("TIMESYS") == "mjd":
                 time_format = 'mjd'
             elif hdulist[ext].header.get("TIMESYS") == "jd":
                 time_format = 'jd'
+            # Raise error if reference time (or related variants) not found
             else:
-                raise ValueError(f"Input file has unclear time format: {filename}")
+                raise ValueError(f"No reference time found in {filename}. Pass in a common time_format manually, or edit the FITS header.")
         if 'time' not in locals():
+            if (tab["time"].unit is not None) and (tab["time"].unit != u.d) and (type(tab["time"].unit) is not u.UnrecognizedUnit):
+                # If time column is in a recognized unit other than days...
+                tab["time"] = tab["time"].to(u.d, copy=False) # ...convert to days.
+            tab["time"] += reference_time_value  # Add reference time to the time column values
             time = Time(
                 tab["time"].data,
                 scale=hdulist[ext].header.get("TIMESYS", "tdb").lower(),
@@ -156,7 +178,15 @@ def read_generic_lightcurve(
         tab.meta["RA"] = hdulist[0].header.get("RA_OBJ")
         tab.meta["DEC"] = hdulist[0].header.get("DEC_OBJ")
         tab.meta["FILENAME"] = filename
-        tab.meta["FLUX_ORIGIN"] = flux_column
+        # issue 1371 - 
+        # When reading in a file saved with to_fits, the flux source is not known
+        # We could save the flux_origin keyword, but that is an incomplete story, 
+        # as we don't know if other manipulation (like detrending) also occurred
+        # So, we populate the 'FLUX_ORIGIN' meta data with 'to_fits' to contain that ambiguity 
+        if ("CREATOR" in hdulist[0].header) and (hdulist[0].header["CREATOR"] == 'lightkurve.LightCurve.to_fits()'):
+            tab.meta["FLUX_ORIGIN"] = "lightkurve.LightCurve.to_fits()"
+        else:
+            tab.meta["FLUX_ORIGIN"] = flux_column
 
         return LightCurve(time=time, data=tab)
     finally:

src/lightkurve/io/kepler.py

@@ -4,6 +4,8 @@
 
 from .generic import read_generic_lightcurve
 
+import numpy as np
+
 
 def read_kepler_lightcurve(
     filename, flux_column="pdcsap_flux", quality_bitmask="default"
@@ -38,6 +40,11 @@ def read_kepler_lightcurve(
         time_format="bkjd",
     )
 
+    #RAH - To allow generic lightcurves to be read by Kepler read we need to add this work around
+    if "sap_quality" not in lc.columns:
+        lc['sap_quality'] = np.zeros(len(lc['time']), dtype=int)
+
+
     # Filter out poor-quality data
     # NOTE: Unfortunately Astropy Table masking does not yet work for columns
     # that are Quantity objects, so for now we remove poor-quality data instead

src/lightkurve/io/tess.py

@@ -4,6 +4,8 @@
 
 from .generic import read_generic_lightcurve
 
+import numpy as np
+
 
 def read_tess_lightcurve(
     filename, flux_column="pdcsap_flux", quality_bitmask="default", time_format="btjd",
@@ -32,6 +34,10 @@ def read_tess_lightcurve(
     """
     lc = read_generic_lightcurve(filename, flux_column=flux_column, time_format=time_format)
 
+    #RAH - To allow generic lightcurves to be read by TESS read we need to add this work around
+    if "quality" not in lc.columns:
+        lc['quality'] = np.zeros(len(lc['time']), dtype=int)
+
     # Filter out poor-quality data
     # NOTE: Unfortunately Astropy Table masking does not yet work for columns
     # that are Quantity objects, so for now we remove poor-quality data instead