Different reconstruction options in holo.py (#121)

* Update holo.py test change #2 * adds optional setting of filtering in frequency domain * bump python version in lint * adds option in scaling of output to inverse transform * adds reconstruction options to Reconstruct class * updates pipeline-holo example * bump version * updates test * update test * lint * bugfix to detault forward_filter_option & test * fix comment in pipeline-holo * updates test to account for extra slice * fix z error * updates python version in setup.cfg * bump version * corrects TypeError with version change * reverts holo steps to fit with testing * updates python version for docs * remove h5py version * update to napoleon * revert & update for napoleon * updates conf.py napoleon * update .gitignore for testing file * np.int deprecated * use default values in example * bump version * updates Pipeline docstring * lint * reverts test setting after re-adoption of arange --------- Co-authored-by: Alex Nimmo Smith <[email protected]> Co-authored-by: Alex Nimmo-Smith <[email protected]>
SINTEF · Aug 29, 2023 · d3d487b · d3d487b
1 parent c3f51fa
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diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
@@ -12,7 +12,7 @@ jobs:
       - name: Set up Python environment
         uses: actions/setup-python@v2
         with:
-          python-version: "3.8"
+          python-version: "3.10"
       - name: flake8 Lint
         uses: py-actions/flake8@v2
         with:

diff --git a/.gitignore b/.gitignore
@@ -253,6 +253,7 @@ tags
 *.zip
 notebooks/header.tfl.txt
 notebooks/keras_model.h5
+notebooks/github-test-holo.ipynb
 
 test-report/*
 docs/.DS_Store

diff --git a/notebooks/pipeline-holo.ipynb b/notebooks/pipeline-holo.ipynb
@@ -181,8 +181,11 @@
     "         # omit argument for static background removal\n",
     "         # change to pyopia.background.CorrectBackgroundNone() to not remove a background during pipeline\n",
     "         'correct background': pyopia.background.CorrectBackgroundAccurate(pyopia.background.shift_bgstack_accurate),\n",
-    "         # hologram reconstruction step - argument is how much stack cleaning (% dimmest pixels to remove) to apply - set to 0 to omit cleaning\n",
-    "         'reconstruct': holo.Reconstruct(stack_clean=0.02),\n",
+    "         # hologram reconstruction step - arguments are:\n",
+    "         # stack_clean - is how much stack cleaning (% dimmest pixels to remove) to apply - set to 0 to omit cleaning\n",
+    "         # forward_filter_option - switch to control filtering in frequency domain (0=none,1=DC only,2=zero ferquency/default)\n",
+    "         # inverse_output_option - switch to control optional scaling of output intensity (0=square/default,1=linear)\n",
+    "         'reconstruct': holo.Reconstruct(stack_clean=0.02, forward_filter_option=2, inverse_output_option=0),\n",
     "         # focussing step - arguments are which stack summarisation method to use, what global segmentation threshold to apply and what focus method to use:\n",
     "         # summarisation methods are:\n",
     "         # pyopia.instrument.holo.std_map (default) - takes standard deviation of values through stack\n",
@@ -338,7 +341,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.15"
+   "version": "3.10.12"
   },
   "orig_nbformat": 4,
   "vscode": {

diff --git a/pyopia/__init__.py b/pyopia/__init__.py
@@ -1 +1 @@
-__version__ = '0.0.56'
+__version__ = '0.0.57'
diff --git a/pyopia/instrument/holo.py b/pyopia/instrument/holo.py
@@ -127,6 +127,10 @@ class Reconstruct():
     ----------
     stack_clean : float
         defines amount of cleaning of stack (fraction of max value below which to zero)
+    forward_filter_option : int
+        switch to control filtering in frequency domain (0=none,1=DC only,2=zero ferquency/default)
+    inverse_output_option :  int
+        switch to control optional scaling of output intensity (0=square/default,1=linear)
 
     Pipeline input data:
     ---------
@@ -143,29 +147,32 @@ class Reconstruct():
         :attr:`pyopia.pipeline.Data.im_stack`
     '''
 
-    def __init__(self, stack_clean=0):
+    def __init__(self, stack_clean=0, forward_filter_option=0, inverse_output_option=0):
         self.stack_clean = stack_clean
+        self.forward_filter_option = forward_filter_option
+        self.inverse_output_option = inverse_output_option
 
     def __call__(self, data):
         imc = data['imc']
         kern = data['kern']
         im_stack = data['im_stack']
 
-        im_fft = forward_transform(imc)
-        im_stack = inverse_transform(im_fft, kern, im_stack)
+        im_fft = forward_transform(imc, self.forward_filter_option)
+        im_stack = inverse_transform(im_fft, kern, im_stack, self.inverse_output_option)
         data['im_stack'] = clean_stack(im_stack, self.stack_clean)
 
         return data
 
 
-def forward_transform(im):
-    '''Perform forward transform
-    Remove the zero frequency components and then fftshift
+def forward_transform(im, forward_filter_option=2):
+    '''Perform forward transform with optional filtering
 
     Parameters
     ----------
     im : np.array
         hologram (usually background-corrected)
+    forward_filter_option : int
+        filtering in frequency domain (0=none/default,1=DC only,2=zero ferquency)
 
     Returns
     -------
@@ -176,9 +183,15 @@ def forward_transform(im):
     # Perform forward transform
     im_fft = fft.fft2(im, workers=os.cpu_count())
 
-    # Remove the zero frequency components
-    im_fft[:, 0] = 0
-    im_fft[0, :] = 0
+    # apply filtering if required
+    match forward_filter_option:
+        case 1:
+            im_fft[0, 0] = 0
+        case 2:
+            im_fft[:, 0] = 0
+            im_fft[0, :] = 0
+        case _:
+            pass
 
     # fftshift
     im_fft = fft.fftshift(im_fft)
@@ -233,7 +246,7 @@ def create_kernel(im, pixel_size, wavelength, n, offset, minZ, maxZ, stepZ):
     return kern
 
 
-def inverse_transform(im_fft, kern, im_stack):
+def inverse_transform(im_fft, kern, im_stack, inverse_output_option=0):
     '''create the reconstructed hologram stack of real images
 
     Parameters
@@ -244,6 +257,8 @@ def inverse_transform(im_fft, kern, im_stack):
         calculated from create_kernel
     im_stack : np.array
         pre-allocated array to receive output
+    inverse_output_option: int
+        optional scaling of output intensity (0=square/default,1=linear)
 
     Returns
     -------
@@ -253,7 +268,11 @@ def inverse_transform(im_fft, kern, im_stack):
 
     for i in range(np.shape(kern)[2]):
         im_tmp = np.multiply(im_fft, kern[:, :, i])
-        im_stack[:, :, i] = (fft.ifft2(im_tmp, workers=os.cpu_count()).real)**2
+        match inverse_output_option:
+            case 1:
+                im_stack[:, :, i] = fft.ifft2(im_tmp, workers=os.cpu_count()).real
+            case _:
+                im_stack[:, :, i] = (fft.ifft2(im_tmp, workers=os.cpu_count()).real)**2
 
     return im_stack
 

diff --git a/pyopia/pipeline.py b/pyopia/pipeline.py
@@ -63,8 +63,10 @@ class Pipeline():
                                                                         pyopia.instrument.holo.load_image),
                 'load': holo.Load(),
                 'correct background': pyopia.background.CorrectBackgroundAccurate(pyopia.background.shift_bgstack_accurate),
-                'reconstruct': holo.Reconstruct(stack_clean=0.02),
-                'focus': holo.Focus(pyopia.instrument.holo.std_map,threshold=threshold),
+                'reconstruct': holo.Reconstruct(stack_clean=0.02, forward_filter_option=2, inverse_output_option=0),
+                'focus': holo.Focus(pyopia.instrument.holo.std_map,threshold=threshold,
+                    focus_function=pyopia.instrument.holo.find_focus_sobel,
+                    increase_depth_of_field=True,merge_adjacent_particles=0),
                 'segmentation': pyopia.process.Segment(threshold=threshold),
                 'statextract': pyopia.process.CalculateStats(export_outputpath="proc"),
                 'output': pyopia.io.StatsH5(datafile_hdf)

diff --git a/pyopia/statistics.py b/pyopia/statistics.py
@@ -418,7 +418,7 @@ def gen_roifiles(stats, auto_scaler=500):
 
     # subsample the particles if necessary
     print('rofiles: {0}'.format(len(roifiles)))
-    IMSTEP = np.max([np.int(np.round(len(roifiles) / auto_scaler)), 1])
+    IMSTEP = np.max([int(np.round(len(roifiles) / auto_scaler)), 1])
     print('reducing particles by factor of {0}'.format(IMSTEP))
     roifiles = roifiles[np.arange(0, len(roifiles), IMSTEP)]
     print('rofiles: {0}'.format(len(roifiles)))

diff --git a/pyopia/tests/test_pipeline.py b/pyopia/tests/test_pipeline.py
@@ -57,7 +57,7 @@ def test_holo_pipeline():
                                                                          pyopia.instrument.holo.load_image),
                  'load': holo.Load(),
                  'correct background': pyopia.background.CorrectBackgroundAccurate(pyopia.background.shift_bgstack_accurate),
-                 'reconstruct': holo.Reconstruct(stack_clean=0.02),
+                 'reconstruct': holo.Reconstruct(stack_clean=0.02, forward_filter_option=2, inverse_output_option=0),
                  'focus': holo.Focus(pyopia.instrument.holo.std_map,
                                      threshold=threshold,
                                      focus_function=pyopia.instrument.holo.find_focus_sobel,