tree wide: way too many changes, im sorry
This commit is contained in:
@@ -17,6 +17,10 @@ from astropy.time.formats import TimeFromEpoch
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log = logging.getLogger(__name__)
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class LightkurveWarning(Warning):
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"""Class for all Lightkurve warnings."""
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pass
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class TimeBKJD(TimeFromEpoch):
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name = 'bkjd'
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unit = 1.0
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@@ -402,6 +406,14 @@ class TessQualityFlags(QualityFlags):
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32768: "Insufficient Targets for Error Correction Exclude",
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}
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def validate_method(method, supported_methods):
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method = method.lower()
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if method in supported_methods:
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return method
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raise ValueError(
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"method '{}' is not supported; "
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"must be one of {}".format(method, supported_methods)
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)
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def _is_dict_like(data1):
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return hasattr(data1, "keys") and callable(getattr(data1, "keys"))
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@@ -879,6 +891,195 @@ class LightCurve(TimeSeries):
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return flatten_lc, trend_lc
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return flatten_lc
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def to_periodogram(self, method="lombscargle", **kwargs):
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supported_methods = ["ls", "bls", "lombscargle", "boxleastsquares"]
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method = validate_method(method.replace(" ", ""), supported_methods)
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if method in ["bls", "boxleastsquares"]:
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from .MinimalPeriodogram import BoxLeastSquaresPeriodogram
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return BoxLeastSquaresPeriodogram.from_lightcurve(lc=self, **kwargs)
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else:
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from .MinimalPeriodogram import LombScarglePeriodogram
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return LombScarglePeriodogram.from_lightcurve(lc=self, **kwargs)
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def fold(
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self,
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period=None,
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epoch_time=None,
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epoch_phase=0,
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wrap_phase=None,
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normalize_phase=False,
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):
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# Lightkurve v1.x assumed that `period` was given in days if no unit
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# was specified. We maintain this behavior for backwards-compatibility.
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if period is not None and not isinstance(period, Quantity):
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period *= u.day
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if epoch_time is not None and not isinstance(epoch_time, Time):
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epoch_time = Time(
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epoch_time, format=self.time.format, scale=self.time.scale
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)
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if (
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epoch_phase is not None
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and not isinstance(epoch_phase, Quantity)
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and not normalize_phase
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):
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epoch_phase *= u.day
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if wrap_phase is not None and not isinstance(wrap_phase, Quantity):
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wrap_phase *= u.day
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# Warn if `epoch_time` appears to use the wrong format
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if epoch_time is not None and epoch_time.value > 2450000:
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if self.time.format == "bkjd":
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warnings.warn(
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"`epoch_time` appears to be given in JD, "
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"however the light curve time uses BKJD "
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"(i.e. JD - 2454833).",
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LightkurveWarning,
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)
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elif self.time.format == "btjd":
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warnings.warn(
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"`epoch_time` appears to be given in JD, "
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"however the light curve time uses BTJD "
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"(i.e. JD - 2457000).",
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LightkurveWarning,
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)
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ts = super().fold(
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period=period,
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epoch_time=epoch_time,
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epoch_phase=epoch_phase,
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wrap_phase=wrap_phase,
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normalize_phase=normalize_phase,
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)
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# The folded time would pass the `TimeSeries` validation check if
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# `normalize_phase=True`, so creating a `FoldedLightCurve` object
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# requires the following three-step workaround:
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# 1. Give the folded light curve a valid time column again
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with ts._delay_required_column_checks():
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folded_time = ts.time.copy()
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ts.remove_column("time")
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ts.add_column(self.time, name="time", index=0)
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# 2. Create the folded object
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lc = FoldedLightCurve(data=ts)
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# 3. Restore the folded time
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with lc._delay_required_column_checks():
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lc.remove_column("time")
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lc.add_column(folded_time, name="time", index=0)
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# Add extra column and meta data specific to FoldedLightCurve
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lc.add_column(
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self.time.copy(), name="time_original", index=len(self._required_columns)
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)
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lc.meta["PERIOD"] = period
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lc.meta["EPOCH_TIME"] = epoch_time
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lc.meta["EPOCH_PHASE"] = epoch_phase
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lc.meta["WRAP_PHASE"] = wrap_phase
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lc.meta["NORMALIZE_PHASE"] = normalize_phase
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lc.sort("time")
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return lc
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def normalize(self, unit="unscaled"):
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validate_method(unit, ["unscaled", "percent", "ppt", "ppm"])
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median_flux = np.nanmedian(self.flux)
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std_flux = np.nanstd(self.flux)
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# If the median flux is within half a standard deviation from zero, the
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# light curve is likely zero-centered and normalization makes no sense.
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if (median_flux == 0) or (
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np.isfinite(std_flux) and (np.abs(median_flux) < 0.5 * std_flux)
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):
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warnings.warn(
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"The light curve appears to be zero-centered "
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"(median={:.2e} +/- {:.2e}); `normalize()` will divide "
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"the light curve by a value close to zero, which is "
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"probably not what you want."
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"".format(median_flux, std_flux),
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LightkurveWarning,
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)
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# If the median flux is negative, normalization will invert the light
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# curve and makes no sense.
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if median_flux < 0:
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warnings.warn(
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"The light curve has a negative median flux ({:.2e});"
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" `normalize()` will therefore divide by a negative "
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"number and invert the light curve, which is probably"
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"not what you want".format(median_flux),
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LightkurveWarning,
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)
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# Create a new light curve instance and normalize its values
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lc = self.copy()
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lc.flux = lc.flux / median_flux
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lc.flux_err = lc.flux_err / median_flux
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if not lc.flux.unit:
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lc.flux *= u.dimensionless_unscaled
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if not lc.flux_err.unit:
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lc.flux_err *= u.dimensionless_unscaled
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# Set the desired relative (dimensionless) units
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if unit == "percent":
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lc.flux = lc.flux.to(u.percent)
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lc.flux_err = lc.flux_err.to(u.percent)
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elif unit in ("ppt", "ppm"):
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lc.flux = lc.flux.to(unit)
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lc.flux_err = lc.flux_err.to(unit)
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lc.meta["NORMALIZED"] = True
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return lc
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def remove_nans(self, column: str = "flux"):
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return self[~np.isnan(self[column])] # This will return a sliced copy
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class FoldedLightCurve(LightCurve):
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@property
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def phase(self):
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"""Alias for `LightCurve.time`."""
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return self.time
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@property
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def cycle(self):
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cycle_epoch_start = self.epoch_time - self.period / 2
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result = np.asarray(np.floor(((self.time_original - cycle_epoch_start) / self.period).value), dtype=int)
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result = result - result.min()
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return result
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@property
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def odd_mask(self):
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return self.cycle % 2 == 1
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@property
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def even_mask(self):
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return ~self.odd_mask
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def _set_xlabel(self, kwargs):
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if "xlabel" not in kwargs:
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kwargs["xlabel"] = "Phase"
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if isinstance(self.time, TimeDelta):
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kwargs["xlabel"] += f" [{self.time.format.upper()}]"
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return kwargs
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def plot(self, **kwargs):
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kwargs = self._set_xlabel(kwargs)
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return super(FoldedLightCurve, self).plot(**kwargs)
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def scatter(self, **kwargs):
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kwargs = self._set_xlabel(kwargs)
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return super(FoldedLightCurve, self).scatter(**kwargs)
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def errorbar(self, **kwargs):
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kwargs = self._set_xlabel(kwargs)
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return super(FoldedLightCurve, self).errorbar(**kwargs)
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def plot_river(self, **kwargs):
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ax = super(FoldedLightCurve, self).plot_river(
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period=self.period, epoch_time=self.epoch_time, **kwargs
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)
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return ax
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class KeplerLightCurve(LightCurve):
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"""Subclass of :class:`LightCurve <lightkurve.lightcurve.LightCurve>`
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to represent data from NASA's Kepler and K2 mission."""
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@@ -1418,3 +1619,5 @@ try:
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except registry.IORegistryError as exc:
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print(exc)
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pass # necessary to enable autoreload during debugging
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