Commit 737d9107 authored by Walsh, Michael's avatar Walsh, Michael
Browse files

remove tomopy and replace with pure numpy solution

parent 570d10c2

docs/api/imars3d.backend.preparation.rst

+1 −1
Original line number Diff line number Diff line
@@ -16,4 +16,4 @@ imars3d.backend.preparation.normalization module 
   :members:

   :undoc-members:

   :show-inheritance:

   :exclude-members: arrays, cut_off, darks, flats, max_workers, name
 
   :exclude-members: arrays, darks, flats, max_workers, name

src/imars3d/backend/preparation/normalization.py

+6 −17
Original line number Diff line number Diff line
@@ -5,7 +5,6 @@ import logging 
import param

from imars3d.backend.util.functions import clamp_max_workers

import numpy as np

import tomopy





logger = logging.getLogger(__name__)
@@ -23,8 +22,6 @@ class normalization(param.ParameterizedFunction): 
        3D array of flat field images (aka flat field, open beam), axis=0 is the image number axis.

    darks:

        3D array of dark field images, axis=0 is the image number axis.

    cut_off:

        Permitted maximum value for the normalized data, originated from tomopy, negative values means no cutoff.

    max_workers:

        number of cores to use for parallel processing, default is 0, which means using all available cores.
@@ -38,10 +35,6 @@ class normalization(param.ParameterizedFunction): 
        doc="3D array of flat field images (aka flat field, open beam), axis=0 is the image number axis.", default=None

    )

    darks = param.Array(doc="3D array of dark field images, axis=0 is the image number axis.", default=None)

    cut_off = param.Number(

        default=-1.0,

        doc="Permitted maximum value for the normalized data, originated from tomopy, negative values means no cutoff.",

    )

    max_workers = param.Integer(

        default=0,

        bounds=(0, None),
@@ -49,7 +42,7 @@ class normalization(param.ParameterizedFunction): 
    )



    def __call__(self, **params):

        """Perform normalization via tomopy."""

        """Perform normalization via numpy."""

        logger.info("Executing Filter: Normalization")

        # type*bounds check via Parameter

        _ = self.instance(**params)
@@ -60,20 +53,16 @@ class normalization(param.ParameterizedFunction): 
        self.max_workers = clamp_max_workers(params.max_workers)

        logger.debug(f"max_worker={self.max_workers}")



        # parse input (mostly for Tomopy)

        tomopy_cut_off = None if params.cut_off < 0 else float(params.cut_off)

        # use median filter to remove outliers from flats and darks

        # NOTE: this will remove the random noises coming from the environment.

        self.flats = np.median(params.flats, axis=0)

        self.darks = np.median(params.darks, axis=0)

        # apply normalization

        # NOTE:

        # For pixels where dark > flat, tomopy replace the value with 1e-6 on-the-fly

        # see https://github.com/tomopy/tomopy/blob/master/source/tomopy/prep/normalize.py#L135

        #

        arrays_normalized = tomopy.normalize(

            params.arrays, self.flats, self.darks, cutoff=tomopy_cut_off, ncore=self.max_workers

        )

        _bg = self.flats - self.darks

        _bg[_bg <= 0] = 1e-6

        params.arrays = params.arrays - self.darks

        arrays_normalized = np.true_divide(params.arrays, _bg, dtype=np.float32)



        # return

        logger.info("FINISHED Executing Filter: Normalization")

src/imars3d/ui/widgets/normalization.py

+1 −7
Original line number Diff line number Diff line
@@ -36,13 +36,7 @@ class Normalization(param.Parameterized): 
            return



        # call the filter

        cutoff = -1.0 if self.auto_cutoff else self.cutoff

        self.parent.ct = normalization(

            arrays=self.parent.ct,

            flats=self.parent.ob,

            darks=self.parent.dc,

            cut_off=cutoff,

        )

        self.parent.ct = normalization(arrays=self.parent.ct, flats=self.parent.ob, darks=self.parent.dc)

        #

        self.status = True

        pn.state.notifications.success("normalization complete.", duration=3000)