lightkurve.periodogram.LombScarglePeriodogram.from_lightcurve

static LombScarglePeriodogram.from_lightcurve(lc, minimum_frequency=None, maximum_frequency=None, minimum_period=None, maximum_period=None, frequency=None, period=None, nterms=1, nyquist_factor=1, oversample_factor=None, freq_unit=None, normalization='amplitude', ls_method='fast', **kwargs)[source]

Creates a Periodogram from a LightCurve using the Lomb-Scargle method.

By default, the periodogram will be created for a regular grid of frequencies from one frequency separation to the Nyquist frequency, where the frequency separation is determined as 1 / the time baseline.

The min frequency and/or max frequency (or max period and/or min period) can be passed to set custom limits for the frequency grid. Alternatively, the user can provide a custom regular grid using the frequency parameter or a custom regular grid of periods using the period parameter.

The sampling of the spectrum can be changed using the oversample_factor parameter. An oversampled spectrum (oversample_factor > 1) is useful for displaying the full details of the spectrum, allowing the frequencies and amplitudes to be measured directly from the plot itself, with no fitting required. This is recommended for most applications, with a value of 5 or 10. On the other hand, an oversample_factor of 1 means the spectrum is critically sampled, where every point in the spectrum is independent of the others. This may be used when Lorentzians are to be fitted to modes in the power spectrum, in cases where the mode lifetimes are shorter than the time-base of the data (which is sometimes the case for solar-like oscillations). An oversample_factor of 1 is suitable for these stars because the modes are usually fully resolved. That is, the power from each mode is spread over a range of frequencies due to damping. Hence, any small error from measuring mode frequencies by taking the maximum of the peak is negligible compared with the intrinsic linewidth of the modes.

The normalization parameter will normalize the spectrum to either power spectral density (“psd”) or amplitude (“amplitude”). Users doing asteroseismology on classical pulsators (e.g. delta Scutis) typically prefer normalization="amplitude" because “amplitude” has higher dynamic range (high and low peaks visible simultaneously), and we often want to read off amplitudes from the plot. If normalization="amplitude", the default value for oversample_factor is set to 5 and freq_unit is 1/day. Alternatively, users doing asteroseismology on solar-like oscillators tend to prefer normalization="psd" because power density has a scaled axis that depends on the length of the observing time, and is used when we are interested in noise levels (e.g. granulation) and are looking at damped oscillations. If normalization="psd", the default value for oversample_factor is set to 1 and freq_unit is set to microHz. Default values of freq_unit and oversample_factor can be overridden. See Appendix A of Kjeldsen & Bedding, 1995 for a full discussion of normalization and measurement of oscillation amplitudes (http://adsabs.harvard.edu/abs/1995A%26A…293…87K).

The parameter nterms controls how many Fourier terms are used in the model. Setting the Nyquist_factor to be greater than 1 will sample the space beyond the Nyquist frequency, which may introduce aliasing.

The freq_unit parameter allows a request for alternative units in frequency space. By default frequency is in (1/day) and power in (amplitude). Asteroseismologists for example may want frequency in (microHz) in which case they would pass freq_unit=u.microhertz.

By default this method uses the LombScargle ‘fast’ method, which assumes a regular grid. If a regular grid of periods (i.e. an irregular grid of frequencies) it will use the ‘slow’ method. If nterms > 1 is passed, it will use the ‘fastchi2’ method for regular grids, and ‘chi2’ for irregular grids.

Caution: this method assumes that the LightCurve’s time (lc.time) is given in units of days.

Parameters
lcLightCurve object

The LightCurve from which to compute the Periodogram.

minimum_frequencyfloat

If specified, use this minimum frequency rather than one over the time baseline.

maximum_frequencyfloat

If specified, use this maximum frequency rather than nyquist_factor times the nyquist frequency.

minimum_periodfloat

If specified, use 1./minium_period as the maximum frequency rather than nyquist_factor times the nyquist frequency.

maximum_periodfloat

If specified, use 1./maximum_period as the minimum frequency rather than one over the time baseline.

frequencyarray-like

The grid of frequencies to use. If given a unit, it is converted to units of freq_unit. If not, it is assumed to be in units of freq_unit. This over rides any set frequency limits.

periodarray-like

The grid of periods to use (as 1/period). If given a unit, it is converted to units of freq_unit. If not, it is assumed to be in units of 1/freq_unit. This overrides any set period limits.

ntermsint

Default 1. Number of terms to use in the Fourier fit.

nyquist_factorint

Default 1. The multiple of the average Nyquist frequency. Is overriden by maximum_frequency (or minimum period).

oversample_factorint

Default: None. The frequency spacing, determined by the time baseline of the lightcurve, is divided by this factor, oversampling the frequency space. This parameter is identical to the samples_per_peak parameter in astropy.LombScargle(). If normalization=’amplitude’, oversample_factor will be set to 5. If normalization=’psd’, it will be 1. These defaults can be overridden.

freq_unitastropy.units.core.CompositeUnit

Default: None. The desired frequency units for the Lomb Scargle periodogram. This implies that 1/freq_unit is the units for period. With default normalization (‘amplitude’), the freq_unit is set to 1/day, which can be overridden. ‘psd’ normalization will set freq_unit to microhertz.

normalization‘psd’ or ‘amplitude’

Default: 'amplitude'. The desired normalization of the spectrum. Can be either power spectral density ('psd') or amplitude ('amplitude').

ls_methodstr

Default: 'fast'. Passed to the method keyword of astropy.stats.LombScargle().

kwargsdict

Keyword arguments passed to astropy.stats.LombScargle()

Returns
PeriodogramPeriodogram object

Returns a Periodogram object extracted from the lightcurve.