Plotting a Light Curve

We can now look at plotting another kind of data: light curves. Through this, we will see some of the customisation options that are available through plot().

The first step is to fetch some light curve data. For this, we introduce another system: the white dwarf pulsar, AR Sco.

from AstroToolkit.Tools import query

lightcurve_data = query(kind="lightcurve",source=6050296829033196032,survey="ztf")
lightcurve_data.showdata()

.kind:       lightcurve
.survey:     ztf
.source:     6050296829033196032
.pos:        [245.44701332846378, -22.886218247040002]
.identifier: J162147.28-225310.39
.figure:     None
.dataname:   J162147.28-225310.39_6050296829033196032_ztf_ATKlightcurve.fits
.plotname:   J162147.28-225310.39_6050296829033196032_ztf_ATKlightcurve.html
.trace:      start -> extracted pos from source query, assumed [2016, 0] -> ztf: [2019, 0] -> ztf query performed -> [2000,0] -> end

.data:
    band: g
        ra:      [245.447071  245.4470765 245.447069  ... 245.4471056 245.4470825 245.4470859]
        dec:     [-22.8864202 -22.8864231 -22.8864182 ... -22.8865103 -22.8865078 -22.8865203]
        mjd:     [58235.38073661 58235.44304301 58246.36157061 ... 60524.18209167 60527.19084229 60529.19070857]
        mag:     [16.7012329 14.7080278 16.4311085 ... 15.7799644 14.800931  16.0791607]
        mag_err: [0.02124788 0.019023   0.02014201 ... 0.01882575 0.01893662 0.01923533]

    band: r
        ra:      [245.4470594 245.4470709 245.4470644 ... 245.4471027 245.4470833 245.4470933]
        dec:     [-22.8864405 -22.8864381 -22.8864126 ... -22.8865397 -22.8865631 -22.8865343]
        mjd:     [58218.40971316 58218.47173164 58246.40244004 ... 60504.26994093 60510.25643771 60527.15762767]
        mag:     [15.6002302 15.0777416 14.619998  ... 15.7173185 14.579071  15.1474562]
        mag_err: [0.01373806 0.01352318 0.01368265 ... 0.01386647 0.01370837 0.01352345]

    band: i
        ra:      None
        dec:     None
        mjd:     None
        mag:     None
        mag_err: None

    Available Methods: .bin(), .crop(), .exportplot(), .plot(), .savedata(), .saveplot(), .showdata(), .showplot(), .sigmaclip()

The attributes of the resulting LightcurveStruct are all familiar. We do have some new methods (bin(), crop() and sigmaclip()), but we won’t look at those here.

Let’s now plot our light curve, skipping plot():

lightcurve_data.showplot()

Note: No plot was found. One will be generated with a default configuration.
Plotting lightcurve data...
Saving plot to local storage: J092444.48+080151.00_587316166180416640_ztf_ATKlightcurve.html

This looks a little bland, and the bands all merge together. We can pass some additional arguments to plot() to add some colour:

lightcurve_data.plot(bands=["g","r","i"],colours=["green","red","blue"])
lightcurve_data.showplot()

Note: i-band data is missing since AR Sco has no i-band photometry in ZTF.

That looks better. However, the options that we can pass to plot() are not purely stylistic. LightcurveStructs support three kinds of plotting: “lightcurve” (as seen above), “powspec”, and “phasefold”. The latter two utilise the Lomb-Scargle periodogram to perform time series analysis.

Let’s try generating a power spectrum:

lightcurve_data.plot(kind="powspec").showplot()

and a phase folded light curve:

lightcurve_data.plot(kind="phasefold").showplot()

Additional plotting options are available depending on the kind of data being plotted, and the way in which it is being plotted (e.g. the lightcurve/powspec/phasefold plots above). As an example, we could bin the phase-folded light curve and shift it slightly to the right to better align it with our phase axis:

lightcurve_data.plot(kind="phasefold",bins=100,shift=0.115)

For a full description of available parameters, see each data structure’s documentation.

Note: The code used in this tutorial can be executed using:

from AstroToolkit.Examples import lightcurve_plotting