def plot_error(self, spectrum, covariance_matrix=None, emin=None, emax=None, npts=100, autoscale=None, **kwargs):
if covariance_matrix is None: covariance_matrix = spectrum['covariance_matrix']
if emin is None and emax is None:
emin, emax=self.axes.get_xlim()
emin = emin*self.axes.energy_units_obj
emax = emax*self.axes.energy_units_obj
energies_units = logspace_units(emin, emax, npts)
dnde = self.get_dnde(spectrum, energies_units)
dnde_error = self.get_dnde_error(spectrum, covariance_matrix,energies_units)
energies, e2_dnde = self.axes.convert_points(energies_units, dnde)
energies, e2_dnde_error = self.axes.convert_points(energies_units, dnde_error)
# clip very small values, problems with log scale otherwise
low=e2_dnde-e2_dnde_error
low[low<1e-100]=1e-100
high=e2_dnde+e2_dnde_error
if autoscale is not None:
old_autoscale=self.axes.get_autoscale_on()
self.axes.autoscale(autoscale)
self.axes.fill_between(energies, low, high, **kwargs)
if autoscale is not None:
self.axes.autoscale(old_autoscale)
def plot(self,
spectrum,
emin=None,
emax=None,
npts=100,
autoscale=None,
**kwargs):
if emin is None and emax is None:
emin, emax = self.axes.get_xlim()
emin = emin * self.axes.energy_units_obj
emax = emax * self.axes.energy_units_obj
energies = logspace_units(emin, emax, npts)
dnde = self.get_dnde(spectrum, energies)
energies, e2_dnde = self.axes.convert_points(energies, dnde)
if autoscale is not None:
old_autoscale = self.axes.get_autoscale_on()
self.axes.autoscale(autoscale)
self.axes.plot(energies, e2_dnde, **kwargs)
if autoscale is not None:
self.axes.autoscale(old_autoscale)
def plot(self, spectrum, emin=None, emax=None, npts=100, autoscale=None, **kwargs):
if emin is None and emax is None:
emin, emax=self.axes.get_xlim()
emin = emin*self.axes.energy_units_obj
emax = emax*self.axes.energy_units_obj
energies = logspace_units(emin, emax, npts)
dnde = self.get_dnde(spectrum, energies)
energies, e2_dnde = self.axes.convert_points(energies, dnde)
if autoscale is not None:
old_autoscale=self.axes.get_autoscale_on()
self.axes.autoscale(autoscale)
self.axes.plot(energies, e2_dnde, **kwargs)
if autoscale is not None:
self.axes.autoscale(old_autoscale)
def plot_error(self,
spectrum,
covariance_matrix=None,
emin=None,
emax=None,
npts=100,
autoscale=None,
**kwargs):
if covariance_matrix is None:
covariance_matrix = spectrum['covariance_matrix']
if emin is None and emax is None:
emin, emax = self.axes.get_xlim()
emin = emin * self.axes.energy_units_obj
emax = emax * self.axes.energy_units_obj
energies_units = logspace_units(emin, emax, npts)
dnde = self.get_dnde(spectrum, energies_units)
dnde_error = self.get_dnde_error(spectrum, covariance_matrix,
energies_units)
energies, e2_dnde = self.axes.convert_points(energies_units, dnde)
energies, e2_dnde_error = self.axes.convert_points(
energies_units, dnde_error)
# clip very small values, problems with log scale otherwise
low = e2_dnde - e2_dnde_error
low[low < 1e-100] = 1e-100
high = e2_dnde + e2_dnde_error
if autoscale is not None:
old_autoscale = self.axes.get_autoscale_on()
self.axes.autoscale(autoscale)
self.axes.fill_between(energies, low, high, **kwargs)
if autoscale is not None:
self.axes.autoscale(old_autoscale)
