The top Readme file should provide an Index of the all the tutorial notebooks with a brief description of what that notebook demonstrate. This will allow a user to quickly find out what they need instead of having to browse through them. Some of the notebook names can be made more descriptive as well.

Creating this as an issue to discuss this addition and track commits.

I am trying to test with an elliptical-NFW and shear lens as follows. The initial error was KeyError: 'alpha_Rs' when I used 'theta_Rs' instead of 'alpha_Rs'. After I change the key in the dictionary kwargs_lens_init, the error became KeyError: 'e1'.
The same error occurs if I change 'gamma1' and 'gamma2' to 'e1' and 'e2' respectively.
I believe it may be some mistake of parameter naming? Can someone point it out if otherwise?

KeyError Traceback (most recent call last)
in
6
7 start_time = time.time()
----> 8 chain_list_pso = fitting_seq.fit_sequence(fitting_kwargs_list)
9 kwargs_result = fitting_seq.best_fit()
10 end_time = time.time()

~\AppData\Roaming\Python\Python38\site-packages\lenstronomy\Workflow\fitting_sequence.py in fit_sequence(self, fitting_list)
78
79 elif fitting_type == 'PSO':
---> 80 kwargs_result, chain, param = self.pso(**kwargs)
81 self._updateManager.update_param_state(**kwargs_result)
82 chain_list.append([fitting_type, chain, param])

~\AppData\Roaming\Python\Python38\site-packages\lenstronomy\Workflow\fitting_sequence.py in pso(self, n_particles, n_iterations, sigma_scale, print_key, threadCount)
250 param_class = self.param_class
251 kwargs_temp = self._updateManager.parameter_state
--> 252 init_pos = param_class.kwargs2args(**kwargs_temp)
253 kwargs_sigma = self._updateManager.sigma_kwargs
254 sigma_start = param_class.kwargs2args(**kwargs_sigma)

~\AppData\Roaming\Python\Python38\site-packages\lenstronomy\Sampling\parameters.py in kwargs2args(self, kwargs_lens, kwargs_source, kwargs_lens_light, kwargs_ps, kwargs_special, kwargs_extinction)
312 """
313
--> 314 args = self.lensParams.setParams(kwargs_lens)
315 args += self.souceParams.setParams(kwargs_source)
316 args += self.lensLightParams.setParams(kwargs_lens_light)

~\AppData\Roaming\Python\Python38\site-packages\lenstronomy\LensModel\lens_param.py in setParams(self, kwargs_list)
115 # pass
116 else:
--> 117 args.append(kwargs[name])
118 return args
119

KeyError: 'e1'

Hi Simon,

I am playing around using your example quad model. The first thing this does is create a mock dataset, however lenstronomy.Util.simulation_util does not exist in the installed package nor anywhere in the documentation. Has this not been implemented yet?

Cheers,
Hannah

direct links to google colab or any other free online Jupyter server could enhance the visibility and usability of the notebooks without the need to download them and having lenstronomy installed locally.
What we would need to change in all the notebooks is that the installation of lenstronomy (and potentially other software) need to be done in the notebook itself with

!pip install lenstronomy

One way to not double install lenstronomy if operated in the current form is to have a condition:

try:
import lenstronomy
except:
!pip install lenstronomy

There is a minor error in the simulation_api notebook 13/14/15 where SimAPI() calls kwargs_numerics as a parameter although SimAPI does not take this parameter, rather SimAPI.image_model_class() seems to take this. Also, running that cell of code after moving kwargs_numerics to the image_model_class() gives a TypeError in SimulationAPI.data_api in .init() that gives the error that .init() got an unexpected keyword argument psf_model.

At "from lenstronomy.LensModel.Util.decouple_multi_plane_util import *" in the modeling_with_decoupled_multiplane.ipynb, ERROR RAISED:"No module named 'lenstronomy.LensModel.Util.decouple_multi_plane_util'", Could you help me with it?