bec_widgets.widgets.plots.image.image_processor

Classes

ImageProcessor	Class for processing the image data.
ImageStats	Container to store stats of an image.
ProcessingConfig	!!! abstract "Usage Documentation"

Module Contents

class ImageProcessor(parent=None, config: ProcessingConfig = None)

Bases: qtpy.QtCore.QObject

Class for processing the image data.

FFT(data: numpy.ndarray) → numpy.ndarray

Perform FFT on the data.

Parameters:

data (np.ndarray) – The data to be processed.

Returns:

The processed data.

Return type:

np.ndarray

log(data: numpy.ndarray) → numpy.ndarray

Perform log on the data.

Parameters:

data (np.ndarray) – The data to be processed.

Returns:

The processed data.

Return type:

np.ndarray

process_image(data: numpy.ndarray) → numpy.ndarray

Core processing logic without threading overhead.

rotation(data: numpy.ndarray, rotate_90: int) → numpy.ndarray

Rotate the data by 90 degrees n times.

Parameters:

• data (np.ndarray) – The data to be processed.

• rotate_90 (int) – The number of 90 degree rotations.

Returns:

The processed data.

Return type:

np.ndarray

set_config(config: ProcessingConfig)

Set the configuration of the processor.

Parameters:

config (ProcessingConfig) – The configuration of the processor.

transpose(data: numpy.ndarray) → numpy.ndarray

Transpose the data.

Parameters:

data (np.ndarray) – The data to be processed.

Returns:

The processed data.

Return type:

np.ndarray

update_image_stats(data: numpy.ndarray) → None

Get the statistics of the image data.

Parameters:

data (np.ndarray) – The image data.

config = None

image_processed

class ImageStats

Container to store stats of an image.

classmethod from_data(data: numpy.ndarray) → ImageStats

Get the statistics of the image data.

Parameters:

data (np.ndarray) – The image data.

Returns:

The statistics of the image data.

Return type:

ImageStats

maximum: float

mean: float

minimum: float

std: float

class ProcessingConfig(/, **data: Any)

Bases: pydantic.BaseModel

!!! abstract “Usage Documentation”

[Models](../concepts/models.md)

A base class for creating Pydantic models.

__class_vars__

The names of the class variables defined on the model.

__private_attributes__

Metadata about the private attributes of the model.

__signature__

The synthesized __init__ [Signature][inspect.Signature] of the model.

__pydantic_complete__

Whether model building is completed, or if there are still undefined fields.

__pydantic_core_schema__

The core schema of the model.

__pydantic_custom_init__

Whether the model has a custom __init__ function.

__pydantic_decorators__

Metadata containing the decorators defined on the model. This replaces Model.__validators__ and Model.__root_validators__ from Pydantic V1.

__pydantic_generic_metadata__

Metadata for generic models; contains data used for a similar purpose to __args__, __origin__, __parameters__ in typing-module generics. May eventually be replaced by these.

__pydantic_parent_namespace__

Parent namespace of the model, used for automatic rebuilding of models.

__pydantic_post_init__

The name of the post-init method for the model, if defined.

__pydantic_root_model__

Whether the model is a [RootModel][pydantic.root_model.RootModel].

__pydantic_serializer__

The pydantic-core SchemaSerializer used to dump instances of the model.

__pydantic_validator__

The pydantic-core SchemaValidator used to validate instances of the model.

__pydantic_fields__

A dictionary of field names and their corresponding [FieldInfo][pydantic.fields.FieldInfo] objects.

__pydantic_computed_fields__

A dictionary of computed field names and their corresponding [ComputedFieldInfo][pydantic.fields.ComputedFieldInfo] objects.

__pydantic_extra__

A dictionary containing extra values, if [extra][pydantic.config.ConfigDict.extra] is set to ‘allow’.

__pydantic_fields_set__

The names of fields explicitly set during instantiation.

__pydantic_private__

Values of private attributes set on the model instance.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

fft: bool = None

log: bool = None

model_config: dict

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

num_rotation_90: int = None

stats: ImageStats = None

transpose: bool = None