def view_eep_fit(self, mass, feh, plot_fit=True, order=5, p0=None, plot_p0=False):
import holoviews as hv
hv.extension('bokeh')
subdf = self.df.xs((mass, feh), level=('initial_mass', 'initial_feh'))
ds = hv.Dataset(subdf)
pts = hv.Points(ds, kdims=['age', 'eep'], vdims=['phase', 'interpolated']).options(tools=['hover'], width=800, height=400, marker='+')
primary_eeps = self.primary_eeps
primary_ages = [subdf.loc[e].age for e in primary_eeps if e < subdf.eep.max()]
from isochrones.eep import eep_fn, eep_jac, eep_fn_p0
from scipy.optimize import curve_fit
if p0 is None:
p0 = eep_fn_p0(subdf.age.values, subdf.eep.values, order=order)
m = subdf.eep < 808
if plot_fit:
pfit, _ = curve_fit(partial(eep_fn, order=order), subdf.age.values[m], subdf.eep.values[m], p0, jac=partial(eep_jac, order=order))
fit = hv.Points([(a, eep_fn(a, *pfit)) for a in subdf.age])
if plot_p0:
p0_fit = hv.Points([(a, eep_fn(a, *p0)) for a in subdf.age])
olay = pts * hv.Points([(a, e) for a, e in zip(primary_ages, primary_eeps)]).options(size=8)
if plot_fit:
olay = olay * fit
if plot_p0:
olay = olay * p0_fit
return olay
def view_eep_fit(self,
mass,
feh,
plot_fit=True,
order=5,
p0=None,
plot_p0=False):
import holoviews as hv
hv.extension('bokeh')
subdf = self.df.xs((mass, feh), level=('initial_mass', 'initial_feh'))
ds = hv.Dataset(subdf)
pts = hv.Points(ds,
kdims=['age', 'eep'],
vdims=['phase',
'interpolated']).options(tools=['hover'],
width=800,
height=400,
marker='+')
primary_eeps = self.primary_eeps
primary_ages = [
subdf.loc[e].age for e in primary_eeps if e < subdf.eep.max()
]
from isochrones.eep import eep_fn, eep_jac, eep_fn_p0
from scipy.optimize import curve_fit
if p0 is None:
p0 = eep_fn_p0(subdf.age.values, subdf.eep.values, order=order)
m = subdf.eep < 808
if plot_fit:
pfit, _ = curve_fit(partial(eep_fn, order=order),
subdf.age.values[m],
subdf.eep.values[m],
p0,
jac=partial(eep_jac, order=order))
fit = hv.Points([(a, eep_fn(a, *pfit)) for a in subdf.age])
if plot_p0:
p0_fit = hv.Points([(a, eep_fn(a, *p0)) for a in subdf.age])
olay = pts * hv.Points([
(a, e) for a, e in zip(primary_ages, primary_eeps)
]).options(size=8)
if plot_fit:
olay = olay * fit
if plot_p0:
olay = olay * p0_fit
return olay
def get_eep_fit(self, mass, age, feh, approx=False):
eep_fn_pars = self.approx_eep_interp([feh, mass], 'all')
eep = eep_fn(age, *eep_fn_pars)
if approx:
return eep
else:
i, _ = searchsorted(self.primary_eeps_arr, eep)
try:
return polyval(self.eep_interps[i-1]([feh, mass], 'all'), age)
except IndexError:
if age > eep_fn_pars[-2]:
return polyval(self.eep_interps[-1]([feh, mass], 'all'), age) # assume you're in last bit
else:
logging.warning('EEP conversion failed for mass={}, age={}, feh={} (approx eep = {}). Returning nan.'.format(mass, age, feh, eep))
return np.nan
def get_eep_fit(self, mass, age, feh, approx=False):
eep_fn_pars = self.approx_eep_interp([feh, mass], 'all')
eep = eep_fn(age, *eep_fn_pars)
if approx:
return eep
else:
i, _ = searchsorted(self.primary_eeps_arr, eep)
try:
return polyval(self.eep_interps[i - 1]([feh, mass], 'all'),
age)
except IndexError:
if age > eep_fn_pars[-2]:
return polyval(self.eep_interps[-1]([feh, mass], 'all'),
age) # assume you're in last bit
else:
getLogger().warning(
'EEP conversion failed for mass={}, age={}, feh={} (approx eep = {}). Returning nan.'
.format(mass, age, feh, eep))
return np.nan