add warning & minor updates (#13)

* add warning & minor updates

* fix workflows & linting

* update actions versions

* also the hidden ones

* warn for user input

* black

* incorporate feedback

* update CHANGELOG comment

.github/workflows/black.yml

@@ -6,13 +6,8 @@ jobs:
   lint:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v2
-      - uses: actions/setup-python@v2
-      - name: black lint
-        run: |
-          python -m pip install black
-          black . --check --line-length 120
-
-#      - uses: psf/black@stable
-#        with:
-#          args: ". --check --line-length 120"
+      - uses: actions/checkout@v3
+      - uses: psf/black@stable
+        with:
+          options: "--check --line-length 120"
+          src: "."

.github/workflows/python-publish.yml

@@ -8,9 +8,9 @@ jobs:
   deploy:
     runs-on: ubuntu-latest
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: '3.x'
     - name: Install dependencies

.github/workflows/pythonapp.yml

@@ -12,12 +12,12 @@ jobs:
     runs-on: ubuntu-latest
     strategy:
       matrix:
-        python-version: [3.7, 3.8, 3.9]
+        python-version: ['3.7', '3.8', '3.9', '3.10']
 
     steps:
-    - uses: actions/checkout@v2
+    - uses: actions/checkout@v3
     - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v2
+      uses: actions/setup-python@v4
       with:
         python-version: ${{ matrix.python-version }}
     - name: Install dependencies
@@ -32,7 +32,7 @@ jobs:
         coverage run -m pytest
         coverage xml
     - name: Upload coverage to Codecov
-      uses: codecov/codecov-action@v1
+      uses: codecov/codecov-action@v3
       with:
         file: coverage.xml
         flags: pytest

CHANGELOG.rst

@@ -1,6 +1,13 @@
 Changelog
 =========
 
+
+[0.1.8] (2023-01-30)
+--------------------
+Added
+*******
+- warn user when smaller tiling than 256x256 is used
+
 [0.1.7] (2022-12-09)
 --------------------
 Added

tests/test_mask.py

@@ -14,9 +14,9 @@
 @pytest.mark.parametrize(
     "img, band_order, nodata_value",
     [
-        (np.empty((20, 20, 6), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
-        (np.empty((20, 20, 8), np.float32), ["Green", "Red", "Blue", "NIR", "SWIR1", "SWIR2", "NIR2", "ETC"], None),
-        (np.empty((20, 20, 6), np.float32), ["Green", "Red", "Blue", "NIR", "SWIR1", "SWIR2"], -666),
+        (np.empty((256, 256, 6), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((256, 256, 8), np.float32), ["Green", "Red", "Blue", "NIR", "SWIR1", "SWIR2", "NIR2", "ETC"], None),
+        (np.empty((256, 256, 6), np.float32), ["Green", "Red", "Blue", "NIR", "SWIR1", "SWIR2"], -666),
     ],
 )
 def test_csmask_init(img, band_order, nodata_value):
@@ -27,17 +27,30 @@ def test_csmask_init(img, band_order, nodata_value):
     "img, band_order, nodata_value",
     [
         (3, ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
-        (np.empty((20, 20), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
-        (np.empty((20, 20, 3), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
-        (np.empty((20, 20, 6), np.uint8), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
-        (np.empty((20, 20, 6), np.float32), ["Blue", "Green", "Yellow", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((256, 256), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((256, 256, 3), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((256, 256, 6), np.uint8), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((256, 256, 6), np.float32), ["Blue", "Green", "Yellow", "NIR", "SWIR1", "SWIR2"], None),
     ],
 )
 def test_csmask_init_raises(img, band_order, nodata_value):
     with pytest.raises(TypeError):
         CSmask(img=img, band_order=band_order, nodata_value=nodata_value)
 
 
+@pytest.mark.parametrize(
+    "img, band_order, nodata_value",
+    [
+        (np.empty((128, 128, 6), np.float32), ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"], None),
+        (np.empty((64, 64, 6), np.float32), ["Green", "Red", "Blue", "NIR", "SWIR1", "SWIR2"], -666),
+    ],
+)
+def test_csmask_init_warns(img, band_order, nodata_value):
+    with pytest.warns(UserWarning):
+        CSmask(img=img, band_order=band_order, nodata_value=nodata_value)
+
+
+@pytest.mark.filterwarnings("ignore::UserWarning")
 @pytest.mark.parametrize(
     "data",
     [
@@ -57,6 +70,7 @@ def test_csmask_csm(data):
     assert kappa >= 0.75
 
 
+@pytest.mark.filterwarnings("ignore::UserWarning")
 @pytest.mark.parametrize(
     "data",
     [

ukis_csmask/__init__.py

@@ -1 +1 @@
-__version__ = "0.1.7"
+__version__ = "0.1.8"

ukis_csmask/mask.py

@@ -1,3 +1,5 @@
+import warnings
+
 import numpy as np
 
 from pathlib import Path
@@ -52,6 +54,13 @@ def __init__(
         if img.dtype != np.float32:
             raise TypeError("img must be in top of atmosphere reflectance with dtype float32")
 
+        if img.shape[0] < 256 or img.shape[1] < 256:
+            warnings.warn(
+                message=f"Your input image is smaller than the internal tiling size of 256x256 pixels. This may result "
+                f"in suboptimal performance. Consider using a larger image size.",
+                category=UserWarning,
+            )
+
         # consistency checks on band_order
         target_band_order = ["Blue", "Green", "Red", "NIR", "SWIR1", "SWIR2"]
         if band_order != target_band_order:

ukis_csmask/utils.py

@@ -1,5 +1,5 @@
 import numpy as np
-import scipy.signal
+from scipy.signal.windows import tukey
 
 
 def reclassify(array, class_dict):
@@ -27,9 +27,9 @@ def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toen
 
     :param array: Array to which the rolling window is applied (array_like).
     :param window: Either a single integer to create a window of only the last axis or a
-        tuple to create it for the last len(window) axes. 0 can be used as a to ignore a
-        dimension in the window (int or tuple).
-    :param asteps: Aligned at the last axis, new steps for the original array, ie. for
+        tuple to create it for the last len(window) axes. 0 can be used as a placeholder
+        to ignore a dimension in the window (int or tuple).
+    :param asteps: Aligned at the last axis, new steps for the original array, i.e. for
         creation of non-overlapping windows (tuple).
     :param wsteps: Steps for the added window dimensions. These can be 0 to repeat values
         along the axis (int or tuple (same size as window)).
@@ -41,7 +41,7 @@ def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toen
         end makes it easier to get the neighborhood, however toend=False will give
         a more intuitive result if you view the whole array (bool).
     :returns: A view on `array` which is smaller to fit the windows and has windows added
-        dimensions (0s not counting), ie. every point of `array` is an array of size
+        dimensions (0s not counting), i.e. every point of `array` is an array of size
         window. (ndarray).
     """
     array = np.asarray(array)
@@ -89,7 +89,7 @@ def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toen
         _wsteps[window == 0] = 1
     wsteps = _wsteps
 
-    # Check that the window would not be larger then the original:
+    # Check that the window would not be larger than the original:
     if np.any(orig_shape[-len(window) :] < window * wsteps):
         raise ValueError("`window` * `wsteps` larger then `array` in at least one dimension.")
 
@@ -101,7 +101,7 @@ def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toen
 
     new_shape[-len(window) :] += wsteps - _window * wsteps
     new_shape = (new_shape + asteps - 1) // asteps
-    # make sure the new_shape is at least 1 in any "old" dimension (ie. steps
+    # make sure the new_shape is at least 1 in any "old" dimension (i.e. steps
     # is (too) large, but we do not care.
     new_shape[new_shape < 1] = 1
     shape = new_shape
@@ -227,7 +227,7 @@ def untile_array(array_tiled, target_shape, overlap=0.1, smooth_blending=False):
             raise ValueError("overlap needs to be <=0.5 when using smooth blending.")
 
         # define tapered cosine function (tukey) to be used for smooth blending
-        window1d = scipy.signal.tukey(M=xsize, alpha=overlap * 2)
+        window1d = tukey(M=xsize, alpha=overlap * 2)
         window2d = np.expand_dims(np.expand_dims(window1d, axis=1), axis=2)
         window2d = window2d * window2d.transpose(1, 0, 2)