import autofit as af
from autolens.model.galaxy import galaxy_model as gm
from autolens.pipeline.phase import phase_imaging, phase_extensions
from autolens.pipeline import pipeline
from autolens.pipeline import tagging as tag
from autolens.model.profiles import light_profiles as lp
from autolens.model.profiles import mass_profiles as mp

# In this pipeline, we'll perform a basic analysis which initializes a lens model (the lens's light, mass and source's \
# light) and then fits the source galaxy using an inversion. This pipeline uses three phases:

# Phase 1:

# Description: Initializes and subtracts the lens light model.
# Lens Light: EllipticalSersic + EllipticalExponential
# Lens Mass: None
# Source Light: None
# Previous Pipelines: None
# Prior Passing: None
# Notes: None

# Phase 2:

# Description: Initializes the lens mass model and source light profile, using the lens subtracted image from phase 1.
# Lens Light: None
# Lens Mass: EllipitcalIsothermal + ExternalShear
# Source Light: EllipticalSersic
# Previous Pipelines: None
# Prior Passing: None
# Notes: Uses the lens light subtracted image from phase 1

# Phase 3:

# Description: Refine the lens light and mass models and source light profile, using priors from the previous 2 phases.
# Lens Light: EllipticalSersic + EllipticalExponential
# Lens Mass: EllipitcalIsothermal + ExternalShear
# Source Light: EllipticalSersic
# Previous Pipelines: None
# Prior Passing: Lens light (variable -> phase 1), lens mass and source (variable -> phase 2)
# Notes: None

def make_pipeline(
        pl_align_bulge_disk_centre=False, pl_align_bulge_disk_axis_ratio=False, pl_align_bulge_disk_phi=False,
        phase_folders=None, tag_phases=True,
        redshift_lens=0.5, redshift_source=1.0,
        sub_grid_size=2, bin_up_factor=None, positions_threshold=None, inner_mask_radii=None, interp_pixel_scale=None):

    ### SETUP PIPELINE AND PHASE NAMES, TAGS AND PATHS ###

    # We setup the pipeline name using the tagging module. In this case, the pipeline name is tagged according to
    # whether certain components of the lens light's bulge-disk model are aligned.

    pipeline_name = 'pipeline_init__lens_sersic_exp_sie_shear_source_sersic'

    pipeline_name = tag.pipeline_name_from_name_and_settings(
        pipeline_name=pipeline_name,
        align_bulge_disk_centre=pl_align_bulge_disk_centre,
        align_bulge_disk_axis_ratio=pl_align_bulge_disk_axis_ratio,
        align_bulge_disk_phi=pl_align_bulge_disk_phi)

    phase_folders.append(pipeline_name)

    ### PHASE 1 ###

    # In phase 1, we will fit only the lens galaxy's light, where we:

    # 1) Set our priors on the lens galaxy (y,x) centre such that we assume the image is centred around the lens galaxy.
    # 2) Use a circular mask which includes the lens and source galaxy light.

    class BulgeDiskPhase(phase_imaging.LensPlanePhase):

        def pass_priors(self, results):

            if pl_align_bulge_disk_centre:
                self.lens_galaxies.lens.bulge.centre = self.lens_galaxies.lens.disk.centre

            if pl_align_bulge_disk_axis_ratio:
                self.lens_galaxies.lens.bulge.axis_ratio = self.lens_galaxies.lens.disk.axis_ratio

            if pl_align_bulge_disk_phi:
                self.lens_galaxies.lens.bulge.phi = self.lens_galaxies.lens.disk.phi

    phase1 = BulgeDiskPhase(
        phase_name='phase_1_lens_sersic_exp', phase_folders=phase_folders, tag_phases=tag_phases,
        lens_galaxies=dict(
            lens=gm.GalaxyModel(
                redshift=redshift_lens,
                bulge=lp.EllipticalSersic,
                disk=lp.EllipticalExponential)),
        sub_grid_size=sub_grid_size, bin_up_factor=bin_up_factor,
        optimizer_class=af.MultiNest)

    # You'll see these lines throughout all of the example pipelines. They are used to make MultiNest sample the \
    # non-linear parameter space faster (if you haven't already, checkout the tutorial '' in howtolens/chapter_2).

    phase1.optimizer.const_efficiency_mode = True
    phase1.optimizer.n_live_points = 40
    phase1.optimizer.sampling_efficiency = 0.3

    ### PHASE 2 ###

    # In phase 2, we will fit the lens galaxy's mass and source galaxy's light, where we:

    # 1) Use a lens-subtracted image generated by subtracting model lens galaxy image from phase 1.
    # 2) Initialize the priors on the centre of the lens galaxy's mass-profile by linking them to those inferred for \
    #    the bulge of the light profile in phase 1.
    # 3) Have the option to use an annular mask removing the central light, if the inner_mask_radii parametr is input.

    class LensSubtractedPhase(phase_imaging.LensSourcePlanePhase):

        def pass_priors(self, results):

            ## Lens Light Sersic -> Sersic, Exp -> Exp ##

            self.lens_galaxies.lens.bulge = results.from_phase('phase_1_lens_sersic_exp').\
                constant.lens_galaxies.lens.bulge

            self.lens_galaxies.lens.disk = results.from_phase('phase_1_lens_sersic_exp').\
                constant.lens_galaxies.lens.disk

            ## Lens Mass, Move centre priors to centre of lens light ###

            self.lens_galaxies.lens.mass.centre = results.from_phase('phase_1_lens_sersic_exp').\
                variable_absolute(a=0.1).lens_galaxies.lens.bulge.centre

    phase2 = LensSubtractedPhase(
        phase_name='phase_2_lens_sie_shear_source_sersic', phase_folders=phase_folders, tag_phases=tag_phases,
        lens_galaxies=dict(
            lens=gm.GalaxyModel(
                redshift=redshift_lens,
                bulge=lp.EllipticalSersic,
                disk=lp.EllipticalExponential,
                mass=mp.EllipticalIsothermal,
                shear=mp.ExternalShear)),
        source_galaxies=dict(
            source=gm.GalaxyModel(
                redshift=redshift_source,
                light=lp.EllipticalSersic)),
        sub_grid_size=sub_grid_size, bin_up_factor=bin_up_factor, positions_threshold=positions_threshold,
        inner_mask_radii=inner_mask_radii, interp_pixel_scale=interp_pixel_scale,
        optimizer_class=af.MultiNest)

    phase2.optimizer.const_efficiency_mode = False
    phase2.optimizer.n_live_points = 50
    phase2.optimizer.sampling_efficiency = 0.3

    ### PHASE 3 ###

    # In phase 3, we will fit simultaneously the lens and source galaxies, where we:

    # 1) Initialize the lens's light, mass, shear and source's light using the results of phases 1 and 2.
    # 2) Use a circular mask, to fully capture the lens and source light.

    class LensSourcePhase(phase_imaging.LensSourcePlanePhase):

        def pass_priors(self, results):

            ## Lens Light, Sersic -> Sersic ###

            self.lens_galaxies.lens.bulge = results.from_phase('phase_1_lens_sersic_exp').\
                variable.lens_galaxies.lens.bulge

            self.lens_galaxies.lens.disk = results.from_phase('phase_1_lens_sersic_exp').\
                variable.lens_galaxies.lens.disk

            ## Lens Mass, SIE -> SIE, Shear -> Shear ###

            self.lens_galaxies.lens.mass = results.from_phase('phase_2_lens_sie_shear_source_sersic').\
                variable.lens_galaxies.lens.mass

            self.lens_galaxies.lens.shear = results.from_phase('phase_2_lens_sie_shear_source_sersic').\
                variable.lens_galaxies.lens.shear

            ### Source Light, Sersic -> Sersic, Exp -> Exp ###

            self.source_galaxies.source = results.from_phase('phase_2_lens_sie_shear_source_sersic').\
                variable.source_galaxies.source

    phase3 = LensSourcePhase(
        phase_name='phase_3_lens_sersic_exp_sie_shear_source_sersic', phase_folders=phase_folders, tag_phases=tag_phases,
        lens_galaxies=dict(
            lens=gm.GalaxyModel(
                redshift=redshift_lens,
                bulge=lp.EllipticalSersic,
                disk=lp.EllipticalExponential,
                mass=mp.EllipticalIsothermal,
                shear=mp.ExternalShear)),
        source_galaxies=dict(
            source=gm.GalaxyModel(
                redshift=redshift_source,
                light=lp.EllipticalSersic)),
        sub_grid_size=sub_grid_size, bin_up_factor=bin_up_factor, positions_threshold=positions_threshold,
        interp_pixel_scale=interp_pixel_scale,
        optimizer_class=af.MultiNest)

    phase3.optimizer.const_efficiency_mode = True
    phase3.optimizer.n_live_points = 75
    phase3.optimizer.sampling_efficiency = 0.3

    return pipeline.PipelineImaging(pipeline_name, phase1, phase2, phase3)