Minor style fixes

skyllh/analyses/i3/publicdata_ps/detsigyield.py

@@ -197,10 +197,10 @@ def _create_hist(
                 E2=energy_bin_edges_upper)
             h_phi *= to_internal_flux_unit_factor
 
-            # Sum over the enegry bins for each sin_dec row.
+            # Sum over the energy bins for each sin_dec row.
             h = np.sum(aeff*h_phi, axis=1)
 
-            # make sure h is greater than 0 everywhere
+            # Make sure `h` is greater than 0 everywhere.
             min_h = np.min(h[h>0])
             return np.where(h==0, min_h*1e-10, h)
 

skyllh/analyses/i3/publicdata_ps/signal_generator.py

@@ -615,7 +615,6 @@ def __init__(
                 f'Its current type is {classname(time_flux_profile)}!')
 
         self.livetime = livetime
-        self._livetime = livetime
         self._time_flux_profile = time_flux_profile
 
     @property

skyllh/analyses/i3/publicdata_ps/time_integrated_ps.py

@@ -52,7 +52,6 @@
 from skyllh.core.minimizers.iminuit import (
     IMinuitMinimizerImpl,
 )
-
 from skyllh.core.model import (
     DetectorModel,
 )
@@ -192,7 +191,7 @@ def create_analysis(
         Minimizer implementation to be used. Supported options are ``"LBFGS"``
         (L-BFG-S minimizer used from the :mod:`scipy.optimize` module),
         ``"minuit"`` (Minuit minimizer used by the :mod:`iminuit` module), 
-        or "crs" (global CRS minimizer by nlopt, not gradient based).
+        or ``"crs"`` (global CRS minimizer by nlopt, not gradient based).
         Default: "LBFGS".
     minimizer_max_rep : int
         In case the minimization process did not converge at the first time
@@ -245,7 +244,8 @@ def create_analysis(
 
     # Create the minimizer instance.
     if minimizer_impl == "LBFGS":
-        minimizer = Minimizer(LBFGSMinimizerImpl(cfg=cfg))
+        minimizer = Minimizer(LBFGSMinimizerImpl(cfg=cfg),
+                              max_repetitions=minimizer_max_rep)
     elif minimizer_impl == "minuit":
         minimizer = Minimizer(IMinuitMinimizerImpl(cfg=cfg, ftol=1e-8), 
                               max_repetitions=minimizer_max_rep)
@@ -255,7 +255,8 @@ def create_analysis(
             CRSMinimizerImpl,
         )
 
-        minimizer = Minimizer(CRSMinimizerImpl(cfg=cfg, ftol=1e-8))
+        minimizer = Minimizer(CRSMinimizerImpl(cfg=cfg, ftol=1e-8),
+                              max_repetitions=minimizer_max_rep)
     else:
         raise NameError(
             f"Minimizer implementation `{minimizer_impl}` is not supported "

skyllh/core/flux_model.py

@@ -520,7 +520,6 @@ def get_integral(
         return integral
 
 
-
 class PowerLawEnergyFluxProfile(
         EnergyFluxProfile,
 ):
@@ -980,7 +979,6 @@ def crit_log10_energy_upper(self, v):
 class FunctionEnergyFluxProfile(
         EnergyFluxProfile):
     r"""Energy flux profile for a callable function with energy as argument.
-
     """
     def __init__(
             self,
@@ -1039,7 +1037,6 @@ class EpeakFunctionEnergyProfile(
     r"""Energy flux profile for a callable function with energy as argument where 
     Epeak (assuming a peaked spectrum, this is the peak's energy) and the scaling 
     will be optimized.  
-
     """
     def __init__(
             self,
@@ -1072,38 +1069,33 @@ def __init__(
         # method.
         self.param_names = ('e_peak')
 
-
     @property
     def e_peak(self):
         """The e_peak parameter of the function.
         """
         return self._e_peak
 
-
     @e_peak.setter
     def e_peak(self, e):
         e = float_cast(
             e,
             'Property e must be castable to type float!')
         self._e_peak = e
 
-
     @property
     def e_peak_orig(self):
         """The original peak energy of the original distribution. The shift will 
         be relative to this energy
         """
         return self._e_peak_orig
 
-
     @e_peak_orig.setter
     def e_peak_orig(self, e):
         e = float_cast(
             e,
             'Property e must be castable to type float!')
         self._e_peak_orig = e
 
-
     def __call__(
             self,
             E,
@@ -1141,7 +1133,6 @@ def __call__(
         # avoid really small values    
         return np.where(value >= max_flux*1e-100, value, max_flux*1e-100)
 
-
     def get_integral(
             self,
             E1,
@@ -1199,10 +1190,8 @@ def get_integral(
             # used to be an issue using the spline integrate self.function.integrate)
             integral[i] = tmp_int if tmp_int >= 0. else 0.
 
-
         return integral
 
-
     @property
     def math_function_str(self):
         """(read-only) The string representation of the mathematical function of

skyllh/core/parameters.py

@@ -54,7 +54,6 @@ def make_linear_parameter_grid_1d(
     grid = np.arange(low, high+delta, delta)
     return ParameterGrid(name, grid, delta)
 
-
 def make_logarithmic_parameter_grid_1d(
         name,
         low,
@@ -307,7 +306,6 @@ def as_linear_grid(self, delta):
 
         return grid
 
-
     def as_logarithmic_grid(self, delta):
         """Creates a ParameterGrid instance with a linear grid with constant
         grid value distances delta.

skyllh/core/utils/coords.py

@@ -1,7 +1,6 @@
 # -*- coding: utf-8 -*-
 
 import numpy as np
-from astropy.coordinates import SkyCoord
 
 from astropy.coordinates import (
     SkyCoord,
@@ -199,4 +198,3 @@ def angular_separation(ra1, dec1, ra2, dec2, psi_floor=None):
         psi = np.where(psi < psi_floor, psi_floor, psi)
 
     return psi
-