components
Submodules
Package Contents
Classes
This class is an abstracted for all other classes, providing initialization function with a name |
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An object of this class represents 1 image (Multiple images have not been considered or investigated yet). |
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An object of this class represents the video dataset. |
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An object of this class represents the Parameter. |
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This object is used to represent the model for data processing in the experiment |
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This class represents Datasets that are mapped from other datasets using a given model |
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This object represents a pipeline |
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This object represents the run structure |
- class components.Storage(name)
This class is an abstracted for all other classes, providing initialization function with a name and store function to generate an HDF5 file
- Parameters
name (str) – the name of the instant
- set_storage_path(self, path)
set the storage path where you want to store the HDF5 file
Attention
please always use “/” in path string instead of “”
- Parameters
path (str) – _description_
- is_overwritable(self)
- store_HDF5(self, root=None)
- store_json(self, root=None)
- store(self, format=None, root=None)
- __str__(self)
rewrite the built-in method to modify the behaviors of print() for this instance to make the print result more readable
before:
>>>print(run1)
<run.Run object at 0x0000022AA45715A0>
after:
>>>print(run1)
‘run1’
here, the string ‘run1’ is the name of this instance
- __repr__(self)
rewrite the built-in method to modify the behaviors of print() for a list of instances to make the print result more readable
before:
>>>print(run1.pipelines)
[<pipeline.Pipeline object at 0x0000022AA45715A0>, <pipeline.Pipeline object at 0x0000022AA4gd1s0>]
after:
>>>print(run1.pipelines)
[‘pipe1’, ‘pipe2’]
here, the strings ‘pipe1’ and ‘pipe2’ are the names of this instance
- show(self)
use the method to show the detailed information about this instance, for example all attributes and names. It should return a string like this:
Examples
>> msmtrun.show()
#### pipelines ####
[‘aa’, ‘bb’, ‘cc’]
#### parameters ####
[‘dd’, ‘ee’, ‘ff’]
#### attributes ####
‘author’ : ‘who’
‘author’ : ‘derGeraet’
‘pmanager’ : ‘tcorneli’
‘targettmp’ : 70
‘targetrps’ : 2
‘oil’ : ‘PA06’
- add_attrs_dict(self, dict)
Add a flat Dictionary of key values as a set of attributes.
- dictstr
The Dictionary consists of Key Value pairs, with the keys being the names of the attribute and the value being the value assigned to the attribute
- encode(self, object)
encode anything as a string Parameters: ———- object: Any
an object which can be an instance of any class
- object_string: str
an encoded string, maybe very long if the original object is large
- Parameters
object (Any) –
- Return type
str
- decode(self, object_string)
decode a string as its original form Parameters: ———– object_string: str
an encoded string
- object: object
this is a instance of its original class, you can check its type with type()
- Parameters
object_string (str) –
- Return type
Storage.decode.object
- class components.Dataset_Image(name)
Bases:
Storage
An object of this class represents 1 image (Multiple images have not been considered or investigated yet).
The user only needs to provide the path of the image, this class will read it using the pillow lib
- Parameters
name (str) – the name of the dataset
Examples
ataset1 = Dataset_Image(‘image_dataset_1’)
dataset1.data = “/test/test_rig_1.jpg”
- property data(self)
- output_file(self)
this function is designed to export image
- class components.Dataset_Video(name)
Bases:
Storage
An object of this class represents the video dataset.
- Parameters
name (str) – the name of the dataset
Examples
dataset1 = Dataset_Video(‘video_dataset_1’)
ataset1.data = r”C:/UsersAdministrator/Videos/Captures/test_meeting _recording.mp4”
dataset1.data = “C:/Users/Administrator/Videos/Captures/test_meeting _recording.mp4”
dataset1.attrs[‘timestamp’] = ‘2022-06-13 11:22:11’
dataset1.set_storage_path(‘test/test_ut_video.h5’)
dataset1.store()
- property data(self)
- output_file(self, path_output)
this function is designed to convert the binary format data into the original format
- Parameters
path_output (str) – the path of output
- convert_pics(self, path_output)
this function is to convert the video file into frame segmentations
- Parameters
path_output (str) – the path of output
- class components.Parameter(name)
Bases:
Storage
An object of this class represents the Parameter.
- Parameters
name (str) – the name of the parameter
Examples
para1 = Parameter(‘para1’)
para1.attrs[‘value’] = 1 para1.attrs[‘units’] = ‘cm’
para1.attrs[‘variable’] = ‘-’
para1.attrs[‘origin’] = ‘this’
- class components.Model(name)
Bases:
Storage
This object is used to represent the model for data processing in the experiment
- Parameters
name (str) – the name of the model
Examples
model = Model(‘model1’)
model.add([parameter1, parameter2])
- class components.Instrument(name)
Bases:
Storage
This class represents Datasets that are mapped from other datasets using a given model
This can be used to convert the input of a sensor to its actual physical data using the given model, for example polynomials or lookup tables.
- Parameters
name (str) – the name of the instrument
Examples
instrument = Instrument(‘instrument1’)
instrument.add([model1, model2])
- class components.Pipeline(name)
Bases:
Storage
This object represents a pipeline
This name of pipeline should contain the following information:
<measured/derived>/<capa>/<raw/scaled>
- Parameters
name (str) – the name of the pipeline
Examples
pipeline1 = Pipeline(‘measured/capa1/raw’)
pipeline1.attrs[‘variable’] = ‘voltage’
pipeline1.attrs[‘units’] = ‘volts’
pipeline1.attrs[‘origin’] = ‘this’
pipeline.add([dataset1, dataset2])
pipeline.add([instrument1, insturment2])
- add(self, list_obj)
add (multi) dataset(s) and instrument(s) into model
- Parameters
list_obj (List[Instrument | Dataset]) – a list of Instrument or Dataset object(s)
- Raises
TypeError – raised when the element of list_obj is not the type of Instrument or Dataset
AssertionError – raised when list_obj is not a list or it is empty