nanopyx.methods.srrf.SRRF_workflow

 1from ..workflow import Workflow
 2from ...core.transform import Radiality, CRShiftAndMagnify
 3
 4
 5import numpy as np
 6
 7
 8def SRRF(
 9    image,
10    magnification=5,
11    ringRadius=0.5,
12    border=0,
13    radialityPositivityConstraint=True,
14    doIntensityWeighting=True,
15    _force_run_type=None,
16):
17    """
18    Perform SRRF (Super-Resolution Radial Fluctuations) analysis on a single image.
19
20    Args:
21        image (numpy.ndarray): The input image for SRRF analysis.
22        magnification (int, optional): Magnification factor (default is 5).
23        ringRadius (float, optional): Radius of the ring for radiality analysis (default is 0.5).
24        border (int, optional): Border parameter for radiality analysis (default is 0).
25        radialityPositivityConstraint (bool, optional): Enable radiality positivity constraint (default is True).
26        doIntensityWeighting (bool, optional): Enable intensity weighting (default is True).
27        _force_run_type (str, optional): Force a specific run type for the analysis (default is None).
28
29    Returns:
30        numpy.ndarray: The result of SRRF analysis, typically representing super-resolved structures.
31
32    Example:
33        result = SRRF(image, magnification=5, ringRadius=0.5, border=0, radialityPositivityConstraint=True, doIntensityWeighting=True)
34
35    Note:
36        - SRRF (Super-Resolution Radial Fluctuations) is a method for super-resolution microscopy.
37        - This function sets up a workflow to perform SRRF analysis on the input image.
38        - The workflow includes CRShiftAndMagnify and Radiality as steps and can be customized with various parameters.
39        - The result is typically a numpy array representing super-resolved structures.
40
41    See Also:
42        - CRShiftAndMagnify: A step that performs coordinate transformation and magnification.
43        - Radiality: A step that calculates radiality for super-resolution analysis.
44        - Workflow: The class used to define and run analysis workflows.
45    """
46
47    _SRRF = Workflow(
48        (CRShiftAndMagnify(verbose=False), (image, 0, 0, magnification, magnification), {}),
49        (
50            Radiality(verbose=False),
51            (image, "PREV_RETURN_VALUE_0_0"),
52            {
53                "magnification": magnification,
54                "ringRadius": ringRadius,
55                "border": border,
56                "radialityPositivityConstraint": radialityPositivityConstraint,
57                "doIntensityWeighting": doIntensityWeighting,
58            },
59        ),
60    )
61
62    return _SRRF.calculate(_force_run_type=_force_run_type)
def SRRF( image, magnification=5, ringRadius=0.5, border=0, radialityPositivityConstraint=True, doIntensityWeighting=True, _force_run_type=None):
 9def SRRF(
10    image,
11    magnification=5,
12    ringRadius=0.5,
13    border=0,
14    radialityPositivityConstraint=True,
15    doIntensityWeighting=True,
16    _force_run_type=None,
17):
18    """
19    Perform SRRF (Super-Resolution Radial Fluctuations) analysis on a single image.
20
21    Args:
22        image (numpy.ndarray): The input image for SRRF analysis.
23        magnification (int, optional): Magnification factor (default is 5).
24        ringRadius (float, optional): Radius of the ring for radiality analysis (default is 0.5).
25        border (int, optional): Border parameter for radiality analysis (default is 0).
26        radialityPositivityConstraint (bool, optional): Enable radiality positivity constraint (default is True).
27        doIntensityWeighting (bool, optional): Enable intensity weighting (default is True).
28        _force_run_type (str, optional): Force a specific run type for the analysis (default is None).
29
30    Returns:
31        numpy.ndarray: The result of SRRF analysis, typically representing super-resolved structures.
32
33    Example:
34        result = SRRF(image, magnification=5, ringRadius=0.5, border=0, radialityPositivityConstraint=True, doIntensityWeighting=True)
35
36    Note:
37        - SRRF (Super-Resolution Radial Fluctuations) is a method for super-resolution microscopy.
38        - This function sets up a workflow to perform SRRF analysis on the input image.
39        - The workflow includes CRShiftAndMagnify and Radiality as steps and can be customized with various parameters.
40        - The result is typically a numpy array representing super-resolved structures.
41
42    See Also:
43        - CRShiftAndMagnify: A step that performs coordinate transformation and magnification.
44        - Radiality: A step that calculates radiality for super-resolution analysis.
45        - Workflow: The class used to define and run analysis workflows.
46    """
47
48    _SRRF = Workflow(
49        (CRShiftAndMagnify(verbose=False), (image, 0, 0, magnification, magnification), {}),
50        (
51            Radiality(verbose=False),
52            (image, "PREV_RETURN_VALUE_0_0"),
53            {
54                "magnification": magnification,
55                "ringRadius": ringRadius,
56                "border": border,
57                "radialityPositivityConstraint": radialityPositivityConstraint,
58                "doIntensityWeighting": doIntensityWeighting,
59            },
60        ),
61    )
62
63    return _SRRF.calculate(_force_run_type=_force_run_type)

Perform SRRF (Super-Resolution Radial Fluctuations) analysis on a single image.

Args: image (numpy.ndarray): The input image for SRRF analysis. magnification (int, optional): Magnification factor (default is 5). ringRadius (float, optional): Radius of the ring for radiality analysis (default is 0.5). border (int, optional): Border parameter for radiality analysis (default is 0). radialityPositivityConstraint (bool, optional): Enable radiality positivity constraint (default is True). doIntensityWeighting (bool, optional): Enable intensity weighting (default is True). _force_run_type (str, optional): Force a specific run type for the analysis (default is None).

Returns: numpy.ndarray: The result of SRRF analysis, typically representing super-resolved structures.

Example: result = SRRF(image, magnification=5, ringRadius=0.5, border=0, radialityPositivityConstraint=True, doIntensityWeighting=True)

Note: - SRRF (Super-Resolution Radial Fluctuations) is a method for super-resolution microscopy. - This function sets up a workflow to perform SRRF analysis on the input image. - The workflow includes CRShiftAndMagnify and Radiality as steps and can be customized with various parameters. - The result is typically a numpy array representing super-resolved structures.

See Also: - CRShiftAndMagnify: A step that performs coordinate transformation and magnification. - Radiality: A step that calculates radiality for super-resolution analysis. - Workflow: The class used to define and run analysis workflows.