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Feature/visualizer refactor #77

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merged 5 commits into from
Apr 15, 2024
Merged

Feature/visualizer refactor #77

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31407d6
renaming variables and modules
Jammy2211 Apr 9, 2024
b72a77e
Dataset1D uses Visualizer
Jammy2211 Apr 9, 2024
bd146e6
fix imports
Jammy2211 Apr 9, 2024
b39814b
refacted to use new visualize API
Jammy2211 Apr 9, 2024
93642b2
black
Jammy2211 Apr 9, 2024
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17 changes: 9 additions & 8 deletions autocti/charge_injection/imaging/readout_persistence.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,14 +3,14 @@

import autoarray as aa

class ReadoutPersistence:

class ReadoutPersistence:
def __init__(
self,
total_rows: Optional[int] = 10,
mean : Optional[float] = 5.0,
mean: Optional[float] = 5.0,
sigma: Optional[float] = 1.0,
rows_per_persistence_range: Optional[Tuple[int, int]] = (1, 10),
rows_per_persistence_range: Optional[Tuple[int, int]] = (1, 10),
seed: int = -1,
):
"""
Expand Down Expand Up @@ -53,7 +53,7 @@ def __init__(
self.rows_per_persistence_range = rows_per_persistence_range
self.seed = seed

def data_with_readout_persistence_from(self, data : aa.Array2D) -> aa.Array2D:
def data_with_readout_persistence_from(self, data: aa.Array2D) -> aa.Array2D:
"""
Returns the input data with readout persistence added to it.

Expand All @@ -73,7 +73,6 @@ def data_with_readout_persistence_from(self, data : aa.Array2D) -> aa.Array2D:
The input data with readout persistence added to it.
"""
for i in range(self.total_rows):

if self.seed == -1:
seed = np.random.randint(0, int(1e9))
else:
Expand All @@ -87,8 +86,10 @@ def data_with_readout_persistence_from(self, data : aa.Array2D) -> aa.Array2D:
row_value = np.random.normal(self.mean, self.sigma)

row_index = np.random.randint(0, data.shape[0])
row_range = np.random.randint(self.rows_per_persistence_range[0], self.rows_per_persistence_range[1])
row_range = np.random.randint(
self.rows_per_persistence_range[0], self.rows_per_persistence_range[1]
)

data[row_index:row_index+row_range] += row_value
data[row_index : row_index + row_range] += row_value

return data
return data
5 changes: 2 additions & 3 deletions autocti/charge_injection/imaging/simulator.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,7 +28,7 @@ def __init__(
read_noise: Optional[float] = None,
charge_noise: Optional[float] = None,
stray_light: Optional[Tuple[float, float]] = None,
readout_persistance : Optional[ReadoutPersistence] = None,
readout_persistance: Optional[ReadoutPersistence] = None,
flat_field_mode: bool = False,
noise_if_add_noise_false: float = 0.1,
noise_seed: int = -1,
Expand Down Expand Up @@ -59,7 +59,7 @@ def __init__(
self.read_noise = read_noise
self.charge_noise = charge_noise
self.stray_light = stray_light
self.readout_persistance = readout_persistance
self.readout_persistance = readout_persistance
self.flat_field_mode = flat_field_mode

self.ci_seed = ci_seed
Expand Down Expand Up @@ -242,7 +242,6 @@ def via_pre_cti_data_from(
post_cti_data = copy.copy(pre_cti_data)

if self.readout_persistance is not None:

post_cti_data = self.readout_persistance.data_with_readout_persistence_from(
data=post_cti_data
)
Expand Down
168 changes: 1 addition & 167 deletions autocti/charge_injection/model/analysis.py
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Original file line number Diff line number Diff line change
Expand Up @@ -26,6 +26,7 @@

class AnalysisImagingCI(AnalysisCTI):
Result = ResultImagingCI
Visualizer = VisualizerImagingCI

def __init__(
self,
Expand Down Expand Up @@ -297,170 +298,3 @@ def output_dataset(dataset, prefix):

if self.dataset_full is not None:
output_dataset(dataset=self.dataset_full, prefix="dataset_full")

def visualize_before_fit(self, paths: af.DirectoryPaths, model: af.Collection):
if conf.instance["visualize"]["plots"]["combined_only"]:
return

visualizer = VisualizerImagingCI(visualize_path=paths.image_path)

region_list = self.region_list_from(model=model)

if conf.instance["visualize"]["plots"]["dataset"]["fpr_non_uniformity"]:
region_list += ["fpr_non_uniformity"]

visualizer.visualize_dataset(dataset=self.dataset)
visualizer.visualize_dataset_regions(
dataset=self.dataset, region_list=region_list
)

if self.dataset_full is not None:
visualizer.visualize_dataset(
dataset=self.dataset_full, folder_suffix="_full"
)
visualizer.visualize_dataset_regions(
dataset=self.dataset_full,
region_list=region_list,
folder_suffix="_full",
)

def visualize_before_fit_combined(
self, analyses, paths: af.DirectoryPaths, model: af.Collection
):
if analyses is None:
return

visualizer = VisualizerImagingCI(visualize_path=paths.image_path)

region_list = self.region_list_from(model=model)

if conf.instance["visualize"]["plots"]["dataset"]["fpr_non_uniformity"]:
region_list += ["fpr_non_uniformity"]

dataset_list = [analysis.dataset for analysis in analyses]
fpr_value_list = [dataset.fpr_value for dataset in dataset_list]

dataset_list = self.in_ascending_fpr_order_from(
quantity_list=dataset_list,
fpr_value_list=fpr_value_list,
)

visualizer.visualize_dataset_combined(
dataset_list=dataset_list,
)

visualizer.visualize_dataset_regions_combined(
dataset_list=dataset_list,
region_list=region_list,
)

if self.dataset_full is not None:
dataset_full_list = [analysis.dataset_full for analysis in analyses]

dataset_full_list = self.in_ascending_fpr_order_from(
quantity_list=dataset_full_list,
fpr_value_list=fpr_value_list,
)

visualizer.visualize_dataset_combined(
dataset_list=dataset_full_list,
folder_suffix="_full",
filename_suffix="_full",
)
visualizer.visualize_dataset_regions_combined(
dataset_list=dataset_full_list,
region_list=region_list,
folder_suffix="_full",
filename_suffix="_full",
)

def visualize(
self,
paths: af.DirectoryPaths,
instance: af.ModelInstance,
during_analysis: bool,
):
if conf.instance["visualize"]["plots"]["combined_only"]:
return

fit = self.fit_via_instance_from(instance=instance)
region_list = self.region_list_from(model=instance)

visualizer = VisualizerImagingCI(visualize_path=paths.image_path)
visualizer.visualize_fit(fit=fit, during_analysis=during_analysis)
visualizer.visualize_fit_1d_regions(
fit=fit, during_analysis=during_analysis, region_list=region_list
)

if self.dataset_full is not None:
fit_full = self.fit_via_instance_and_dataset_from(
instance=instance, dataset=self.dataset_full
)

visualizer.visualize_fit(
fit=fit_full, during_analysis=during_analysis, folder_suffix="_full"
)
visualizer.visualize_fit_1d_regions(
fit=fit_full,
during_analysis=during_analysis,
region_list=region_list,
folder_suffix="_full",
)

def visualize_combined(
self,
analyses: List["AnalysisImagingCI"],
paths: af.DirectoryPaths,
instance: af.ModelInstance,
during_analysis: bool,
):
if analyses is None:
return

fit_list = [
analysis.fit_via_instance_from(instance=instance) for analysis in analyses
]

fpr_value_list = [fit.dataset.fpr_value for fit in fit_list]

fit_list = self.in_ascending_fpr_order_from(
quantity_list=fit_list,
fpr_value_list=fpr_value_list,
)

region_list = self.region_list_from(model=instance)

visualizer = VisualizerImagingCI(visualize_path=paths.image_path)
visualizer.visualize_fit_combined(
fit_list=fit_list, during_analysis=during_analysis
)
visualizer.visualize_fit_1d_regions_combined(
fit_list=fit_list,
region_list=region_list,
during_analysis=during_analysis,
)

if self.dataset_full is not None:
fit_full_list = [
analysis.fit_via_instance_and_dataset_from(
instance=instance, dataset=analysis.dataset_full
)
for analysis in analyses
]

fit_full_list = self.in_ascending_fpr_order_from(
quantity_list=fit_full_list,
fpr_value_list=fpr_value_list,
)

visualizer.visualize_fit_combined(
fit_list=fit_full_list,
during_analysis=during_analysis,
folder_suffix="_full",
)
visualizer.visualize_fit_1d_regions_combined(
fit_list=fit_full_list,
region_list=region_list,
during_analysis=during_analysis,
folder_suffix="_full",
)
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