minor style changes

lenstronomy/Analysis/kinematics_api.py

@@ -31,7 +31,8 @@ def __init__(self, z_lens, z_source, kwargs_model, kwargs_aperture, kwargs_seein
         :param z_source: redshift of source
         :param kwargs_model: model keyword arguments, needs 'lens_model_list', 'lens_light_model_list'
         :param kwargs_aperture: spectroscopic aperture keyword arguments, see lenstronomy.Galkin.aperture for options
-        :param kwargs_seeing: seeing condition of spectroscopic observation, corresponds to kwargs_psf in the GalKin module specified in lenstronomy.GalKin.psf
+        :param kwargs_seeing: seeing condition of spectroscopic observation, corresponds to kwargs_psf in the GalKin
+         module specified in lenstronomy.GalKin.psf
         :param cosmo: astropy.cosmology instance, if None then will be set to the default cosmology
         :param lens_model_kinematics_bool: bool list of length of the lens model. Only takes a subset of all the models
             as part of the kinematics computation (can be used to ignore substructure, shear etc that do not describe the
@@ -42,10 +43,13 @@ def __init__(self, z_lens, z_source, kwargs_model, kwargs_aperture, kwargs_seein
         :param multi_observations: bool, if True uses multi-observation to predict a set of different observations with
             the GalkinMultiObservation() class. kwargs_aperture and kwargs_seeing require to be lists of the individual
             observations.
-        :param anisotropy_model: type of stellar anisotropy model. See details in MamonLokasAnisotropy() class of lenstronomy.GalKin.anisotropy
-        :param analytic_kinematics: boolean, if True, used the analytic JAM modeling for a power-law profile on top of a Hernquist light profile
+        :param anisotropy_model: type of stellar anisotropy model. See details in MamonLokasAnisotropy() class of
+         lenstronomy.GalKin.anisotropy
+        :param analytic_kinematics: boolean, if True, used the analytic JAM modeling for a power-law profile on top of
+         a Hernquist light profile
          ATTENTION: This may not be accurate for your specific problem!
-        :param Hernquist_approx: bool, if True, uses a Hernquist light profile matched to the half light radius of the deflector light profile to compute the kinematics
+        :param Hernquist_approx: bool, if True, uses a Hernquist light profile matched to the half light radius of the
+         deflector light profile to compute the kinematics
         :param MGE_light: bool, if true performs the MGE for the light distribution
         :param MGE_mass: bool, if true performs the MGE for the mass distribution
         :param kwargs_numerics_galkin: numerical settings for the integrated line-of-sight velocity dispersion
@@ -76,7 +80,7 @@ def __init__(self, z_lens, z_source, kwargs_model, kwargs_aperture, kwargs_seein
 
         if kwargs_mge_mass is None:
             self._kwargs_mge_mass = {'n_comp': 20}
-        else :
+        else:
             self._kwargs_mge_mass = kwargs_mge_mass
 
         if kwargs_mge_light is None:

lenstronomy/LensModel/Profiles/epl.py

@@ -21,7 +21,7 @@ class EPL(LensProfileBase):
     with :math:`\\theta_{E}` is the (circularized) Einstein radius,
     :math:`\\gamma` is the negative power-law slope of the 3D mass distributions,
     :math:`q` is the minor/major axis ratio,
-    and :math:`x` and :math:`y` are defined in a coordinate sys- tem aligned with the major and minor axis of the lens.
+    and :math:`x` and :math:`y` are defined in a coordinate system aligned with the major and minor axis of the lens.
 
     In terms of eccentricities, this profile is defined as
 

lenstronomy/LensModel/Profiles/hernquist.py

@@ -20,9 +20,10 @@ class to compute the Hernquist 1990 model, which is in 3d:
     >>> cosmo = FlatLambdaCDM(H0=70, Om0=0.3, Ob0=0.05)
     >>> lens_cosmo = LensCosmo(z_lens=0.5, z_source=1.5, cosmo=cosmo)
 
-    Here we compute the angular scale of Rs on the sky (in arc seconds) and the deflection the normalization sigma0:
+    Here we compute the angular scale of Rs on the sky (in arc seconds) and the deflection the normalization sigma0 from
+    the total stellar mass in M_sol and Rs in [Mpc]:
 
-    >>> sigma0, rs_angle = lens_cosmo.hernquist_phys2angular(M=10**13, c=6)
+    >>> sigma0, rs_angle = lens_cosmo.hernquist_phys2angular(mass=10**11, rs=0.02)
 
     And here we perform the inverse calculation given Rs_angle and alpha_Rs to return the physical halo properties.
 

lenstronomy/PointSource/point_source.py

@@ -40,7 +40,8 @@ def __init__(self, point_source_type_list, lensModel=None, fixed_magnification_l
          to have a specified band/frame assigned to it
         :param point_source_frame_list: list of lists mirroring the structure of the image positions.
          Integers correspond to the i'th list entry of index_lens_model_list indicating in which frame/band the image is
-         appearing
+         appearing, e.g., four images and four cutouts, you can do [[0], [1], [2], [3]] when the frames
+         (ordered as the list) are in the same order as the point sources (indices)
         """
         if len(point_source_type_list) > 0:
             if index_lens_model_list is not None and point_source_frame_list is None:

lenstronomy/SimulationAPI/model_api.py

@@ -42,7 +42,7 @@ def __init__(self, lens_model_list=None, z_lens=None, z_source=None, lens_redshi
          models. If None, 'z_source' is used.
         :param tabulated_deflection_angles: a class that returns deflection angles given a set of (x, y) coordinates.
          Effectively a fixed lens model. See documentation in Profiles.numerical_alpha
-        :param observed_convention_index: a list of indicies that correspond to lens models where the center_x,center_y
+        :param observed_convention_index: a list of indices that correspond to lens models where the center_x,center_y
          values correspond to the observed (lensed positions), not the physical positions in space
         """
         if lens_model_list is None:

lenstronomy/SimulationAPI/observation_api.py

@@ -160,7 +160,7 @@ def __init__(self, pixel_scale, exposure_time, magnitude_zero_point, read_noise=
          'e-': (electrons assumed to be IID),
          'ADU': (analog-to-digital unit)
         :param background_noise: sqrt(variance of background) as a total contribution from readnoise,
-         sky brightness etc in units of the data_count_units (e- or ADU)
+         sky brightness etc. in units of the data_count_units (e- or ADU)
          If you set this parameter, it will use this value regardless of the values of read_noise, sky_brightness
         """
         Instrument.__init__(self, pixel_scale, read_noise, ccd_gain)  # read_noise and ccd_gain can be None