def calculate_empirical_rms(spec, test=False):
fl = spec.flux.value
wv = spec.wavelength.value
min_cond = ltu.is_local_minima(fl)
max_cond = ltu.is_local_maxima(fl)
min_local_inds = np.where(min_cond)[0]
max_local_inds = np.where(max_cond)[0]
interpolated_max = interp1d(wv[max_local_inds],
fl[max_local_inds],
kind='linear',
bounds_error=False,
fill_value=0)
interpolated_min = interp1d(wv[min_local_inds],
fl[min_local_inds],
kind='linear',
bounds_error=False,
fill_value=0)
# these are the envelopes
fl_max = interpolated_max(wv)
fl_min = interpolated_min(wv)
# take the mid value
fl_mid = 0.5 * (fl_max + fl_min) # reference flux
# the idea here is that these will be the intrinsic rms per pixel (both are the same though)
max_mean_diff = np.abs(fl_mid - fl_max)
min_mean_diff = np.abs(fl_mid - fl_min)
sigma = 0.5 * (
max_mean_diff + min_mean_diff
) # anyways these two differences are the same by definition
if test:
# fluxes
wv_mins = wv[min_local_inds]
wv_maxs = wv[max_local_inds]
plt.figure()
plt.plot(wv, fl, drawstyle='steps-mid')
plt.plot(wv_mins,
fl[min_local_inds],
marker='o',
color='r',
label='Local minimum')
plt.plot(wv_maxs,
fl[max_local_inds],
marker='o',
color='green',
label='Local maximum')
plt.plot(wv, fl_mid, color='black', label='flux_mid')
# sigmas
plt.plot(wv, sigma, marker='o-', color='pink', label='Empirical sigma')
plt.plot(wv, spec.sig.value, color='yellow', label='Original sigma')
plt.legend()
plt.show()
return XSpectrum1D.from_tuple((wv, fl, sigma))
def test_is_local_minima_maxima():
a = np.ones(100)
#adding local minima/maxima by hand
ind_lmin = [14, 50, 75] # these should be in increasing order for the assert later
ind_lmax = [25, 60, 90]
a[ind_lmin] = 0. # local minima
a[ind_lmax] = 2. # local maxima
a_lmin = ltu.is_local_minima(a)
a_lmax = ltu.is_local_maxima(a)
assert all(np.where(a_lmin)[0] == ind_lmin)
assert all(np.where(a_lmax)[0] == ind_lmax)
def test_is_local_minima_maxima():
a = np.ones(100)
#adding local minima/maxima by hand
ind_lmin = [14, 50, 75] # these should be in increasing order for the assert later
ind_lmax = [25, 60, 90]
a[ind_lmin] = 0. # local minima
a[ind_lmax] = 2. # local maxima
a_lmin = ltu.is_local_minima(a)
a_lmax = ltu.is_local_maxima(a)
assert all(np.where(a_lmin)[0] == ind_lmin)
assert all(np.where(a_lmax)[0] == ind_lmax)
def is_local_maxima(a):
"""For a given array a, returns true for local maxima"""
return ltu.is_local_maxima(a)
def is_local_maxima(a):
"""For a given array a, returns true for local maxima"""
return ltu.is_local_maxima(a)