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Merged
Jammy2211 merged 5 commits into from
Sep 24, 2019
Merged

Feature/phase #120

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5c83717
attempted to separate fitting logic from phase logic
rhayes777 Sep 23, 2019
88438cc
fixes
rhayes777 Sep 23, 2019
052cce8
using real masks
rhayes777 Sep 23, 2019
067779e
no need to apply the to 2d function as it doesn't actually do anythin…
rhayes777 Sep 23, 2019
d88a217
fixed tests
rhayes777 Sep 23, 2019
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303 changes: 152 additions & 151 deletions autolens/pipeline/phase/phase_data.py
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Original file line number Diff line number Diff line change
Expand Up @@ -23,54 +23,23 @@ def isinstance_or_prior(obj, cls):
return False


class PhaseData(AbstractPhase):
galaxies = af.PhaseProperty("galaxies")

class MetaDataFit:
def __init__(
self,
phase_name,
phase_tag,
phase_folders=tuple(),
galaxies=None,
optimizer_class=af.MultiNest,
cosmology=cosmo.Planck15,
sub_size=2,
signal_to_noise_limit=None,
positions_threshold=None,
mask_function=None,
inner_mask_radii=None,
pixel_scale_interpolation_grid=None,
pixel_scale_binned_cluster_grid=None,
inversion_uses_border=True,
inversion_pixel_limit=None,
auto_link_priors=False,
self,
variable,
sub_size=2,
signal_to_noise_limit=None,
positions_threshold=None,
mask_function=None,
inner_mask_radii=None,
pixel_scale_interpolation_grid=None,
pixel_scale_binned_cluster_grid=None,
inversion_uses_border=True,
inversion_pixel_limit=None,
is_hyper_phase=False
):

"""

A phase in an lens pipeline. Uses the set non_linear optimizer to try to fit models and hyper_galaxies
passed to it.

Parameters
----------
optimizer_class: class
The class of a non_linear optimizer
sub_size: int
The side length of the subgrid
pixel_scale_binned_cluster_grid : float or None
If *True*, the hyper_galaxies image used to generate the cluster'grids weight map will be binned
up to this higher pixel scale to speed up the KMeans clustering algorithm. \
"""

super(PhaseData, self).__init__(
phase_name=phase_name,
phase_tag=phase_tag,
phase_folders=phase_folders,
optimizer_class=optimizer_class,
cosmology=cosmology,
auto_link_priors=auto_link_priors,
)

self.is_hyper_phase = is_hyper_phase
self.variable = variable
self.sub_size = sub_size
self.signal_to_noise_limit = signal_to_noise_limit
self.positions_threshold = positions_threshold
Expand All @@ -79,24 +48,93 @@ def __init__(
self.pixel_scale_interpolation_grid = pixel_scale_interpolation_grid
self.pixel_scale_binned_cluster_grid = pixel_scale_binned_cluster_grid
self.inversion_uses_border = inversion_uses_border

self.inversion_pixel_limit = (
inversion_pixel_limit
or af.conf.instance.general.get(
"inversion", "inversion_pixel_limit_overall", int
)
inversion_pixel_limit or
af.conf.instance.general.get(
"inversion",
"inversion_pixel_limit_overall",
int
)
)
self.hyper_noise_map_max = af.conf.instance.general.get(
"hyper", "hyper_noise_map_max", float
)

self.galaxies = galaxies or []
def setup_phase_mask(self, data, mask):

self.is_hyper_phase = False
if self.mask_function is not None:
mask = self.mask_function(image=data.image, sub_size=self.sub_size)
elif mask is None and self.mask_function is None:
mask = default_mask_function(image=data.image)

if mask.sub_size != self.sub_size:
mask = mask.new_mask_with_new_sub_size(sub_size=self.sub_size)

if self.inner_mask_radii is not None:
inner_mask = msk.Mask.circular(
shape=mask.shape,
pixel_scale=mask.pixel_scale,
radius_arcsec=self.inner_mask_radii,
sub_size=self.sub_size,
invert=True,
)
mask = mask + inner_mask

return mask

def check_positions(self, positions):

if self.positions_threshold is not None and positions is None:
raise exc.PhaseException(
"You have specified for a phase to use positions, but not input positions to the "
"pipeline when you ran it."
)

def pixel_scale_binned_grid_from_mask(
self,
mask
):

if self.pixel_scale_binned_cluster_grid is None:

pixel_scale_binned_cluster_grid = mask.pixel_scale

else:

pixel_scale_binned_cluster_grid = self.pixel_scale_binned_cluster_grid

if pixel_scale_binned_cluster_grid > mask.pixel_scale:

bin_up_factor = int(
self.pixel_scale_binned_cluster_grid / mask.pixel_scale
)

else:

bin_up_factor = 1

binned_mask = mask.binned_up_mask_from_mask(bin_up_factor=bin_up_factor)

while binned_mask.pixels_in_mask < self.inversion_pixel_limit:

if bin_up_factor == 1:
raise exc.DataException(
f"The pixelization {self.pixelization} uses a KMeans clustering algorithm which uses "
f"a hyper model image to adapt the pixelization. This hyper model image must have "
f"more pixels than inversion pixels. Current, the inversion_pixel_limit exceeds the "
f"data-points in the image.\n\n To rectify this image, manually set the inversion "
f"pixel limit in the pipeline phases or change the inversion_pixel_limit_overall "
f"parameter in general.ini "
)

bin_up_factor -= 1
binned_mask = mask.binned_up_mask_from_mask(bin_up_factor=bin_up_factor)

return mask.pixel_scale * bin_up_factor

@property
def pixelization(self):
for galaxy in self.galaxies:
for galaxy in self.variable.galaxies:
if galaxy.pixelization is not None:
if isinstance(galaxy.pixelization, af.PriorModel):
return galaxy.pixelization.cls
Expand All @@ -105,12 +143,67 @@ def pixelization(self):

@property
def uses_cluster_inversion(self):
if self.galaxies:
for galaxy in self.galaxies:
if self.variable.galaxies:
for galaxy in self.variable.galaxies:
if isinstance_or_prior(galaxy.pixelization, pix.VoronoiBrightnessImage):
return True
return False

def preload_pixelization_grids_of_planes_from_results(self, results):

if self.is_hyper_phase:
return None

if (
results is not None
and results.last is not None
and hasattr(results.last, "hyper_combined")
and self.pixelization is not None
):
if self.pixelization.__class__ is results.last.pixelization.__class__:
return (
results.last.hyper_combined.most_likely_pixelization_grids_of_planes
)
return None


class PhaseData(AbstractPhase):
galaxies = af.PhaseProperty("galaxies")

def __init__(
self,
phase_name,
phase_tag,
phase_folders=tuple(),
galaxies=None,
optimizer_class=af.MultiNest,
cosmology=cosmo.Planck15,
auto_link_priors=False,
):

"""

A phase in an lens pipeline. Uses the set non_linear optimizer to try to fit models and hyper_galaxies
passed to it.

Parameters
----------
optimizer_class: class
The class of a non_linear optimizer
"""

super(PhaseData, self).__init__(
phase_name=phase_name,
phase_tag=phase_tag,
phase_folders=phase_folders,
optimizer_class=optimizer_class,
cosmology=cosmology,
auto_link_priors=auto_link_priors,
)
self.galaxies = galaxies or []

self.is_hyper_phase = False

def run(self, data, results=None, mask=None, positions=None):
"""
Run this phase.
Expand Down Expand Up @@ -164,98 +257,6 @@ def make_analysis(self, data, results=None, mask=None, positions=None):
"""
raise NotImplementedError()

def setup_phase_mask(self, data, mask):

if self.mask_function is not None:
mask = self.mask_function(image=data.image, sub_size=self.sub_size)
elif mask is None and self.mask_function is None:
mask = default_mask_function(image=data.image)

if mask.sub_size != self.sub_size:
mask = mask.new_mask_with_new_sub_size(sub_size=self.sub_size)

if self.inner_mask_radii is not None:
inner_mask = msk.Mask.circular(
shape=mask.shape,
pixel_scale=mask.pixel_scale,
radius_arcsec=self.inner_mask_radii,
sub_size=self.sub_size,
invert=True,
)
mask = mask + inner_mask

return mask

def check_positions(self, positions):

if self.positions_threshold is not None and positions is None:
raise exc.PhaseException(
"You have specified for a phase to use positions, but not input positions to the "
"pipeline when you ran it."
)

def pixel_scale_binned_grid_from_mask(self, mask):

pixel_scale_binned_grid = None

if self.uses_cluster_inversion:

if self.pixel_scale_binned_cluster_grid is None:

pixel_scale_binned_cluster_grid = mask.pixel_scale

else:

pixel_scale_binned_cluster_grid = self.pixel_scale_binned_cluster_grid

if pixel_scale_binned_cluster_grid > mask.pixel_scale:

bin_up_factor = int(
self.pixel_scale_binned_cluster_grid / mask.pixel_scale
)

else:

bin_up_factor = 1

binned_mask = mask.binned_up_mask_from_mask(bin_up_factor=bin_up_factor)

while binned_mask.pixels_in_mask < self.inversion_pixel_limit:

if bin_up_factor == 1:
raise exc.DataException(
f"The pixelization {self.pixelization} uses a KMeans clustering algorithm which uses "
f"a hyper model image to adapt the pixelization. This hyper model image must have "
f"more pixels than inversion pixels. Current, the inversion_pixel_limit exceeds the "
f"data-points in the image.\n\n To rectify this image, manually set the inversion "
f"pixel limit in the pipeline phases or change the inversion_pixel_limit_overall "
f"parameter in general.ini "
)

bin_up_factor -= 1
binned_mask = mask.binned_up_mask_from_mask(bin_up_factor=bin_up_factor)

pixel_scale_binned_grid = mask.pixel_scale * bin_up_factor

return pixel_scale_binned_grid

def preload_pixelization_grids_of_planes_from_results(self, results):

if self.is_hyper_phase:
return None

if (
results is not None
and results.last is not None
and hasattr(results.last, "hyper_combined")
and self.pixelization is not None
):
if self.pixelization.__class__ is results.last.pixelization.__class__:
return (
results.last.hyper_combined.most_likely_pixelization_grids_of_planes
)
return None

def extend_with_inversion_phase(self):
return phase_extensions.InversionPhase(phase=self)

Expand All @@ -268,8 +269,8 @@ def lens_data(self):
def check_positions_trace_within_threshold_via_tracer(self, tracer):

if (
self.lens_data.positions is not None
and self.lens_data.positions_threshold is not None
self.lens_data.positions is not None
and self.lens_data.positions_threshold is not None
):

traced_positions_of_planes = tracer.traced_positions_of_planes_from_positions(
Expand All @@ -282,7 +283,7 @@ def check_positions_trace_within_threshold_via_tracer(self, tracer):
)

if not fit.maximum_separation_within_threshold(
self.lens_data.positions_threshold
self.lens_data.positions_threshold
):
raise exc.RayTracingException

Expand Down
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