Merge pull request lenstronomy#576 from sibirrer/main

ready for release 1.11.6 with docstrings updated

HISTORY.rst

@@ -358,4 +358,14 @@ History
 1.11.5 (2023-09-28)
 +++++++++++++++++++
 * bug fix in findOverlap function
-* bug fix in luminosity-0weighted celocity dispersion calculation
+* bug fix in luminosity-0weighted velocity dispersion calculation
+
+1.11.6 (2024-01-24)
++++++++++++++++++++
+* bug fix with partial kwargs in kwargs_tracer mode
+* stability and documentation improvements
+* name change from GNFW -> PSEUDO_DPL
+* improved plotting of point sources and caustics on top of pixelated images
+* RADIAL_INTERPOL lens profile
+* improved description of how to add new lenses
+* Debug findOverlap parantheses of image_util.py

docs/lenstronomy.LensModel.Profiles.rst

@@ -20,6 +20,14 @@ lenstronomy.LensModel.Profiles.base\_profile module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.blank\_plane module
+--------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.blank_plane
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.chameleon module
 -----------------------------------------------
 
@@ -180,6 +188,14 @@ lenstronomy.LensModel.Profiles.epl module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.epl\_boxydisky module
+----------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.epl_boxydisky
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.epl\_numba module
 ------------------------------------------------
 
@@ -244,10 +260,10 @@ lenstronomy.LensModel.Profiles.gaussian\_potential module
    :undoc-members:
    :show-inheritance:
 
-lenstronomy.LensModel.Profiles.general\_nfw module
---------------------------------------------------
+lenstronomy.LensModel.Profiles.gnfw module
+------------------------------------------
 
-.. automodule:: lenstronomy.LensModel.Profiles.general_nfw
+.. automodule:: lenstronomy.LensModel.Profiles.gnfw
    :members:
    :undoc-members:
    :show-inheritance:
@@ -316,6 +332,14 @@ lenstronomy.LensModel.Profiles.nfw module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.nfw\_core\_truncated module
+----------------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.nfw_core_truncated
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.nfw\_ellipse module
 --------------------------------------------------
 
@@ -340,6 +364,14 @@ lenstronomy.LensModel.Profiles.nfw\_mass\_concentration module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.nfw\_mass\_concentration\_ellipse module
+-----------------------------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.nfw_mass_concentration_ellipse
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.nfw\_vir\_trunc module
 -----------------------------------------------------
 
@@ -404,6 +436,22 @@ lenstronomy.LensModel.Profiles.point\_mass module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.pseudo\_double\_powerlaw module
+--------------------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.pseudo_double_powerlaw
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
+lenstronomy.LensModel.Profiles.radial\_interpolated module
+----------------------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.radial_interpolated
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.sersic module
 --------------------------------------------
 
@@ -516,6 +564,14 @@ lenstronomy.LensModel.Profiles.spp module
    :undoc-members:
    :show-inheritance:
 
+lenstronomy.LensModel.Profiles.synthesis module
+-----------------------------------------------
+
+.. automodule:: lenstronomy.LensModel.Profiles.synthesis
+   :members:
+   :undoc-members:
+   :show-inheritance:
+
 lenstronomy.LensModel.Profiles.tnfw module
 ------------------------------------------
 

lenstronomy/Analysis/kinematics_api.py

@@ -52,15 +52,15 @@ def __init__(
             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 cosmo: astropy.cosmology instance, if None then will be set to the
+        :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
             main deflector potential
         :param light_model_kinematics_bool: bool list of length of the light model. Only
             takes a subset of all the models as part of the kinematics computation (can
-            be used to ignore light components that do not describe the main deflector
+            be used to ignore light components that do not describe the main deflector)
         :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
@@ -69,7 +69,7 @@ def __init__(
             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!
+            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

lenstronomy/LensModel/MultiPlane/multi_plane.py

@@ -50,13 +50,13 @@ def __init__(
         :param ignore_observed_positions: bool, if True, will ignore the conversion between observed to physical
          position of deflectors
         :param z_source_convention: float, redshift of a source to define the reduced deflection angles of the lens
-        models. If None, 'z_source' is used.
+         models. If None, 'z_source' is used.
         :param z_lens_convention: float, redshift of a lens plane to define the
-        effective time-delay distance. Only needed if distance ratios are
-        sampled. If None, the first lens redshift is used.
+         effective time-delay distance. Only needed if distance ratios are
+         sampled. If None, the first lens redshift is used.
         :param kwargs_synthesis: keyword arguments for the 'SYNTHESIS' lens model, if applicable
         :param distance_ratio_sampling: bool, if True, will use sampled
-        distance ratios to update T_ij value in multi-lens plane computation.
+         distance ratios to update T_ij value in multi-lens plane computation.
         """
 
         if z_source_convention is None:

lenstronomy/LensModel/Profiles/base_profile.py

@@ -10,13 +10,15 @@ class LensProfileBase(object):
     1. make a new python file in this folder
     2. create a class inheriting this class; YourModel(LensProfileBase)
     3. write new definitions following the same input and output conventions as this base class
-        function(x, y, <other parameters>)
-        derivatives(x, y, <other parameters>)
-        hessian(x, y, <other parameters>)
+    - function(x, y, <other parameters>)
+    - derivatives(x, y, <other parameters>)
+    - hessian(x, y, <other parameters>)
     4. set the variables for sampling the new profile
+
         param_names = ["param1", "param2", ...]
         lower_limit_default = {"param1": value, "param2: value, ...}
         upper_limit_default = {"param1": value, "param2: value, ...}
+
     5. give the new profile a meaningful name and add it in the LensModel.profile_list_base class
     6. write test functions in the test/test_LensModel/test_Profiles folder with a new file with test_<profile name>.py
 

lenstronomy/LensModel/Profiles/epl_boxydisky.py

@@ -25,8 +25,8 @@ class EPL_BOXYDISKY(LensProfileBase):
     :param center_x: center of distortion
     :param center_y: center of distortion
     :param a4_a: Strength of the deviation of multipole order 4 of the elliptical isodensity contours,
-    which is translated into the multipole strength from the MULTIPOLE class through a rescaling by theta_E / sqrt(q).
-    Profile is disky when a4_a>0 and boxy when a4_a<0.
+     which is translated into the multipole strength from the MULTIPOLE class through a rescaling by theta_E / sqrt(q).
+     Profile is disky when a4_a>0 and boxy when a4_a<0.
     """
 
     param_names = ["theta_E", "gamma", "e1", "e2", "center_x", "center_y", "a4_a"]

lenstronomy/LensModel/Profiles/gnfw.py

@@ -13,16 +13,16 @@ class GNFW(LensProfileBase):
     This class computes the lensing quantities of a generalized NFW profile:
 
     .. math::
-    \rho(r) = \frac{\rho_{\rm s}} { (r/r_{\rm s}})^{\gamma_{\rm in}} * (1 + r/r_{\rm
-    s})^{3 - {\gamma_{\rm in}}}
+        \\rho(r) = \\frac{\\rho_{\\rm s}} { (r/r_{\\rm s}})^{\\gamma_{\\rm in}} * (1 + r/r_{\\rm
+        s})^{3 - {\\gamma_{\\rm in}}}
 
     This class uses the normalization parameter `kappa_s` defined as:
 
     .. math::
-    kappas_{\rm s} = \frac{\rho_{\rm s} r_{\rm s}}{\Sigma_{\rm crit}}
+        kappas_{\\rm s} = \\frac{\\rho_{\\rm s} r_{\\rm s}}{\\Sigma_{\\rm crit}}
 
-    Some expressions are obtained from Keeton 2001 (
-    https://ui.adsabs.harvard.edu/abs/2001astro.ph..2341K/abstract). See and cite the
+    Some expressions are obtained from Keeton 2001
+    https://ui.adsabs.harvard.edu/abs/2001astro.ph..2341K/abstract. See and cite the
     references therein.
     """
 
@@ -46,8 +46,9 @@ class GNFW(LensProfileBase):
 
     def __init__(self, trapezoidal_integration=False, integration_steps=1000):
         """
+
         :param trapezoidal_integrate: bool, if True, the numerical integral is performed
-            with the trapezoidal rule, otherwise with scipy.integrate.quad
+         with the trapezoidal rule, otherwise with ~scipy.integrate.quad
         :param integration_steps: number of steps in the trapezoidal integral
         """
         super(GNFW, self).__init__()

lenstronomy/LensModel/Profiles/synthesis.py

@@ -12,12 +12,12 @@ class SynthesisProfile(LensProfileBase):
     """A general class which describes a linear sum of many simple profiles to
     approximate a target profile.
 
-    Example: Mimic an NFW profile with many CSE profiles. In this case, you could use LensModel(['SYNTHESIS'],kwargs_synthesis=kwargs_synthesis) with
-    kwargs_synthesis={'target_lens_model': 'NFW',
-                    'component_lens_model': 'CSE',
-                   'kwargs_list': kwargs_list,
-                   'lin_fit_hyperparams':{'lower_log_bound':-6, 'upper_log_bound':3, 'num_r_evals':100, 'sigma':0.01} (default values)
-                   }
+    Example: Mimic an NFW profile with many CSE profiles. In this case, you could use LensModel(['SYNTHESIS'],
+    kwargs_synthesis=kwargs_synthesis)
+    with
+    kwargs_synthesis={'target_lens_model': 'NFW', 'component_lens_model': 'CSE', 'kwargs_list': kwargs_list,
+    'lin_fit_hyperparams':{'lower_log_bound':-6, 'upper_log_bound':3, 'num_r_evals':100, 'sigma':0.01} (default values)
+    }
     where kwargs_list would be a list of input CSE kwargs (where the amplitude will be re-adjusted).
     """
 

lenstronomy/LensModel/lens_model.py

@@ -57,9 +57,9 @@ def __init__(
         :param z_interp_stop: (only in multi-plane with cosmo_interp=True); maximum redshift for distance interpolation
          This number should be higher or equal the maximum of the source redshift and/or the z_source_convention
         :param num_z_interp: (only in multi-plane with cosmo_interp=True); number of redshift bins for interpolating
-        distances
+         distances
         :param distance_ratio_sampling: bool, if True, will use sampled
-        distance ratios to update T_ij value in multi-lens plane computation.
+         distance ratios to update T_ij value in multi-lens plane computation.
         """
         self.lens_model_list = lens_model_list
         self.z_lens = z_lens

lenstronomy/Sampling/special_param.py

@@ -192,7 +192,7 @@ class SpecialParam(object):
     """Class that handles special parameters that are not directly part of a specific
     model component.
 
-    These includes cosmology relevant parameters, astrometric errors and overall scaling
+    These include cosmology relevant parameters, astrometric errors and overall scaling
     parameters.
     """
 
@@ -235,9 +235,11 @@ def __init__(
          Warning: this is only defined for pixel-based source modelling (e.g. 'SLIT_STARLETS' light profile)
         :param kinematic_sampling: bool, if True, samples the kinematic parameters b_ani, incli, with cosmography
          D_dt (overrides _D_dt_sampling) and Dd
-        :param distance_ratio_sampling: bool, if True, the distance ratios will be sampled. Only applicable for multi-plane case, will turn-off Ddt_sampling by default as Ddt will be sampled as a ratio with a fiducial value in this option.
+        :param distance_ratio_sampling: bool, if True, the distance ratios will be sampled.
+         Only applicable for multi-plane case, will turn-off Ddt_sampling by default as Ddt will be sampled as a
+         ratio with a fiducial value in this option.
         :param num_lens_planes: integer, number of lens planes when `distance_ratio_sampling` is True
-        sampled
+         sampled
         """
         self._num_lens_planes = num_lens_planes
         self._distance_ratio_sampling = DistanceRatioFactorsAB(

lenstronomy/__init__.py

@@ -1,6 +1,6 @@
 __author__ = "lenstronomy developers"
 __email__ = "lenstronomy-dev@googlegroups.com"
-__version__ = "1.11.5"
+__version__ = "1.11.6"
 __credits__ = "ETH Zurich, UCLA, Stanford, Stony Brook"
 
 from .Util.package_util import short, laconic

setup.py

@@ -75,13 +75,13 @@ def run_tests(self):
 
 setup(
     name="lenstronomy",
-    version="1.11.5",
+    version="1.11.6",
     description="Strong lens modeling package.",
     long_description=desc,
     author="lenstronomy developers",
     author_email="lenstronomy-dev@googlegroups.com",
     url="https://github.com/lenstronomy/lenstronomy",
-    download_url="https://github.com/lenstronomy/lenstronomy/archive/1.11.5.tar.gz",
+    download_url="https://github.com/lenstronomy/lenstronomy/archive/1.11.6.tar.gz",
     packages=find_packages(PACKAGE_PATH, "test"),
     package_dir={"lenstronomy": "lenstronomy"},
     include_package_data=True,