dioph/periodicity

Useful tools for periodicity analysis in time series data.

periodicity's Issues

ValueError: Digital filter critical frequencies must be 0 < Wn < 1

I'm trying to execute your code below
from periodicity.gp import *
from lightkurve import search_lightcurvefile

lcs = search_lightcurvefile(target=9895037, quarter=[4,5]).download_all()
lc = lcs[0].PDCSAP_FLUX.normalize().append(lcs[1].PDCSAP_FLUX.normalize())
lc = lc.remove_nans().remove_outliers().bin(binsize=4)

t, x = lc.time, lc.flux
x = x - x.mean()

model = FastGPModeler(t, x)
model.prior = make_gaussian_prior(t, x)
model.minimize()
samples = model.mcmc(nwalkers=32, nsteps=5000, burn=500)

print('Median period: {:.2f}'.format(np.exp(np.median(samples[:, 4]))))

And it returns an error

ValueError Traceback (most recent call last)

in ()
10
11 model = FastGPModeler(t, x)
---> 12 model.prior = make_gaussian_prior(t, x)
13 model.minimize()
14 samples = model.mcmc(nwalkers=32, nsteps=5000, burn=500)

Figure out how to make prior function picklable

emcee's multiprocessing functionality requires the likelihood function to be picklable

AttributeError: Can't pickle local object 'make_gaussian_prior.<locals>.gaussian_prior'

Getting an error while working on AGN data

Hi, I wanted to incorporate this analysis in my work. While doing my analysis i am getting an error, which is as fellow:

siga = TSeries(t,y)
siga

---

AssertionError Traceback (most recent call last)
Cell In[28], line 1
----> 1 siga = TSeries(t,y)
2 siga

File /opt/anaconda3/envs/periodicity/lib/python3.8/site-packages/periodicity/core.py:472, in TSeries.init(self, time, values, assume_sorted)
470 raise ValueError("Input arrays have incompatible lengths.")
471 time = dict(time=time)
--> 472 super().init(data, time, fastpath=True)
473 if (
474 not assume_sorted
475 and not self.coords["time"]._data.array.is_monotonic_increasing
476 ):
477 self._array = self._array.sortby("time")

File /opt/anaconda3/envs/periodicity/lib/python3.8/site-packages/periodicity/core.py:58, in Signal.init(self, *args, **kwargs)
57 def init(self, *args, **kwargs):
---> 58 self._array = xr.DataArray(*args, **kwargs)

File /opt/anaconda3/envs/periodicity/lib/python3.8/site-packages/xarray/core/dataarray.py:400, in DataArray.init(self, data, coords, dims, name, attrs, indexes, fastpath)
398 assert dims is None
399 assert attrs is None
--> 400 assert indexes is not None
401 else:
402 # TODO: (benbovy - explicit indexes) remove
403 # once it becomes part of the public interface
404 if indexes is not None:

AssertionError:

Please help me to resolve this problem.

TypeError: 'Signal' object is not subscriptable

Hi,
When using Signal.find_peaks(), the line peaks = self[maxima] returns error TypeError: 'Signal' object is not subscriptable.
The context was :

gls = GLS(fmin=fmin, fmax=fmax)
pg = gls(x)
z= pg.val * Signal(y)  # y is an np array
z.find_peaks()

N.M.

Weird multiplication with a TimeSeries behaviour

While trying to multiply a Periodogram with coefficients y, I get different results :
Context :

gls = GLS(fmin=fmin, fmax=fmax)
pg = gls(x)
z= pg.val * y # y is an np array

I get results fine, but cannot do z.find_peaks() because z is a np array

So I switched to z= pg.val * Timeseries(time=periods, val=y)
This works (return a result), BUT z here is not equal to z in the first test.

I would assume it to gave same result, because of :

    def __mul__(self, other):
        result = self.copy()
        if isinstance(other, Signal):
            if len(self) != len(other):
                raise ValueError("Cannot multiply two Signals with different lengths.")
            result.val = self.val * other.val
        else:
            result.val = self.val * other
        return result

Am I missing something here ?

Some more infos :
pg.val and y are of size (7215,)