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)
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.