Merge branch 'OpenPIV:master' into master

Author: alexlib

.github/workflows/build.yml

@@ -9,13 +9,13 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        python-version: [3.10]
+        python-version: [3.12]
         poetry-version: [1.5.0]
         os: [ubuntu-latest]
     runs-on: ${{ matrix.os }}
     steps:
       - uses: actions/checkout@v4
-      - uses: actions/setup-python@v4.5.0
+      - uses: actions/setup-python@v5.1.1
         with:
           python-version: ${{ matrix.python-version }}
       - name: Run image
@@ -27,4 +27,4 @@ jobs:
           PYPI_TOKEN: ${{ secrets.PYPI_API_TOKEN }}
         run: |
           poetry config pypi-token.pypi $PYPI_TOKEN
-          poetry publish --build
+          poetry publish --build

.github/workflows/testing.yml

@@ -14,7 +14,7 @@ jobs:
     steps:
     - uses: actions/checkout@v4
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v4.5.0
+      uses: actions/setup-python@v5.1.1
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install poetry

README.md

@@ -1,5 +1,5 @@
 # OpenPIV
-![Build and upload to PyPI](https://github.com/OpenPIV/openpiv-python/workflows/Build%20and%20upload%20to%20PyPI/badge.svg)
+[![Python package](https://github.com/OpenPIV/openpiv-python/actions/workflows/testing.yml/badge.svg)](https://github.com/OpenPIV/openpiv-python/actions/workflows/testing.yml)
 [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.4409178.svg)](https://doi.org/10.5281/zenodo.4409178)
 ![PyPI](https://img.shields.io/pypi/v/openpiv)
 ![Anaconda](https://anaconda.org/openpiv/openpiv/badges/version.svg)
@@ -32,7 +32,7 @@ Use PyPI: <https://pypi.python.org/pypi/OpenPIV>:
 
 ## Or `conda` 
 
-    conda install -c alexlib openpiv
+    conda install -c openpiv openpiv
 
 ## Or [Poetry](https://python-poetry.org/)
 

openpiv/preprocess.py

@@ -4,7 +4,8 @@
 import numpy as np
 from scipy.ndimage import median_filter, gaussian_filter, binary_fill_holes,\
      map_coordinates
-from skimage import img_as_float, exposure, img_as_ubyte
+from skimage.util import img_as_float, img_as_ubyte
+from skimage import exposure
 from skimage import filters
 from skimage.measure import find_contours, approximate_polygon, points_in_poly
 from skimage.transform import rescale
@@ -73,7 +74,7 @@ def dynamic_masking(image, method="edges", filter_size=7, threshold=0.005):
     """
     imcopy = np.copy(image)
     # stretch the histogram
-    image = exposure.rescale_intensity(img_as_float(image), in_range=(0, 1))
+    image = exposure.rescale_intensity(img_as_float(image), in_range='image')
     # blur the image, low-pass
     blurback = img_as_ubyte(gaussian_filter(image, filter_size))
     if method == "edges":
@@ -132,6 +133,7 @@ def mask_coordinates(image_mask, tolerance=1.5, min_length=10, plot=False):
 
 def prepare_mask_from_polygon(x, y, mask_coords):
     """ Converts mask coordinates of the image mask
+
     to the grid of 1/0 on the x,y grid
     Inputs:
         x,y : grid of x,y points
@@ -148,8 +150,8 @@ def prepare_mask_on_grid(
     x: np.ndarray,
     y: np.ndarray,
     image_mask: np.ndarray,
-)->np.array:
-    """_summary_
+)->np.ndarray:
+    """Converts mask to the grid 
 
     Args:
         x (np.ndarray): x coordinates of vectors in pixels
@@ -371,7 +373,7 @@ def contrast_stretch(img, lower_limit = 2, upper_limit = 98):
 
     lower = np.percentile(img, lower_limit)
     upper = np.percentile(img, upper_limit)
-    img = exposure.rescale_intensity(img, in_range = (lower, upper))
+    img = exposure.rescale_intensity(img, in_range=(lower, upper)) #type:ignore
     return img
 
 def threshold_binarize(img, threshold, max_val = 255):
@@ -472,65 +474,59 @@ def gen_lowpass_background(img_list, sigma = 3, resize = None):
             background += img
     return (background / len(img_list))
 
-
-def offset_image(img, offset_x, offset_y, pad = 'zero'):
-    """
-    Offset an image by padding.
+# Obsolete, to be removed in the future
+# def offset_image(img, offset_x, offset_y, pad='constant'):
+#     """
+#     Offset an image by padding.
 
-    Parameters
-    ----------
-    img: image
-        a two dimensional array of float32 or float64, 
-        but can be uint16, uint8 or similar type
-        
-    offset_x: int
-        offset an image by integer values. Positive values shifts 
-        the image to the right and negative values shift to the left
-        
-    offset_y: int
-        offset an image by integer values. Positive values shifts 
-        the image to the top and negative values shift to the bottom
-        
-    pad: str
-        pad the shift with zeros or a reflection of the shift
-        
-    Returns
-    -------
-    img: image
-        a transformed two dimensional array of the input image
+#     Parameters
+#     ----------
+#     img: image
+#         a two dimensional array of float32 or float64, 
+#         but can be uint16, uint8 or similar type
+        
+#     offset_x: int
+#         offset an image by integer values. Positive values shifts 
+#         the image to the right and negative values shift to the left
+        
+#     offset_y: int
+#         offset an image by integer values. Positive values shifts 
+#         the image to the top and negative values shift to the bottom
+        
+#     pad: str
+#         pad the shift with zeros or a reflection of the shift
+        
+#     Returns
+#     -------
+#     img: image
+#         a transformed two dimensional array of the input image
 
-    """
-    if pad not in [
-        'zero', 'reflect'
-    ]:
-        raise ValueError(f'pad method not supported: {pad}')
-    end_y, end_x = img.shape
-    start_x = 0; start_y = 0
-    if offset_x > 0:
-        offset_x1 = offset_x
-        offset_x2 = 0
-    else:
-        offset_x1 = 0
-        offset_x2 = offset_x * -1
-        start_x = offset_x2
-        end_x += offset_x2
-    if offset_y > 0:
-        offset_y1 = offset_y
-        offset_y2 = 0
-    else:
-        offset_y1 = 0
-        offset_y2 = offset_y * -1
-        start_y = offset_y2
-        end_y += offset_y2   
-    if pad == 'zero':
-        pad = 'constant'
-    img = np.pad(
-        img,
-        ((offset_y1, offset_y2),
-        (offset_x1, offset_x2)),
-        mode = pad
-    )
-    return img[start_y:end_y, start_x:end_x]
+#     """
+#     if pad not in [
+#         'zero', 'reflect'
+#     ]:
+#         raise ValueError(f'pad method not supported: {pad}')
+#     end_y, end_x = img.shape
+#     start_x = 0; start_y = 0
+#     if offset_x > 0:
+#         offset_x1 = offset_x
+#         offset_x2 = 0
+#     else:
+#         offset_x1 = 0
+#         offset_x2 = offset_x * -1
+#         start_x = offset_x2
+#         end_x += offset_x2
+#     if offset_y > 0:
+#         offset_y1 = offset_y
+#         offset_y2 = 0
+#     else:
+#         offset_y1 = 0
+#         offset_y2 = offset_y * -1
+#         start_y = offset_y2
+#         end_y += offset_y2   
+
+#     img = np.pad(img, (offset_y1, offset_y2),(offset_x1, offset_x2)), mode=pad)
+#     return img[start_y:end_y, start_x:end_x]
 
 
 def stretch_image(img,

openpiv/smoothn.py

@@ -157,7 +157,7 @@ def smoothn(
   """
     is_masked = False
 
-    if type(y) == ma.core.MaskedArray:  # masked array
+    if type(y) == ma.MaskedArray:  # masked array
         is_masked = True
         mask = y.mask
         y = np.array(y)
@@ -213,7 +213,7 @@ def smoothn(
     nof = IsFinite.sum()  # number of finite elements
     W = W * IsFinite
     if any(W < 0):
-        error("smoothn:NegativeWeights", "Weights must all be >=0")
+        raise ValueError("smoothn:NegativeWeights", "Weights must all be >=0")
     else:
         # W = W/np.max(W)
         pass
@@ -320,11 +320,11 @@ def smoothn(
     # ---
     if isauto:
         try:
-            xpost = array([(0.9 * log10(sMinBnd) + log10(sMaxBnd) * 0.1)])
+            xpost = np.array([(0.9 * np.log10(sMinBnd) + np.log10(sMaxBnd) * 0.1)])
         except:
-            array([100.0])
+            np.array([100.0])
     else:
-        xpost = array([log10(s)])
+        xpost = array([np.log10(s)])
     while RobustIterativeProcess:
         # --- "amount" of weights (see the function GCVscore)
         aow = sum(Wtot) / noe
@@ -422,7 +422,7 @@ def smoothn(
     ## Warning messages
     # ---
     if isauto:
-        if abs(log10(s) - log10(sMinBnd)) < errp:
+        if abs(np.log10(s) - np.log10(sMinBnd)) < errp:
             warning(
                 "MATLAB:smoothn:SLowerBound",
                 [
@@ -431,7 +431,7 @@ def smoothn(
                     + "has been reached. Put s as an input variable if required."
                 ],
             )
-        elif abs(log10(s) - log10(sMaxBnd)) < errp:
+        elif abs(np.log10(s) - np.log10(sMaxBnd)) < errp:
             warning(
                 "MATLAB:smoothn:SUpperBound",
                 [