Scrambled singlepass pyramids (#117)

* Test more than the first pyramid layer

* Pyramid layers beyond the first one were scrambled

* Minor change to trigger Github, to see if it is behaving now

* Minor change to poke Github again

* Trying setup-miniconda v3

* Remove use of Mambaforge

* Remove Mambaforge from all test runs. Apparently it is no longer supported

.github/workflows/python-app.yml

@@ -26,7 +26,6 @@ jobs:
     - uses: conda-incubator/setup-miniconda@v2
       with:
         miniforge-version: latest
-        miniforge-variant: Mambaforge
     - name: Install dependencies
       shell: bash -l {0}
       run: conda install gdal libgdal-kea cloudpickle scipy
@@ -62,7 +61,6 @@ jobs:
     - uses: conda-incubator/setup-miniconda@v2
       with:
         miniforge-version: latest
-        miniforge-variant: Mambaforge
     - name: Install dependencies
       run: conda install gdal cloudpickle scipy
     - name: Test with testrios
@@ -78,7 +76,6 @@ jobs:
     - uses: conda-incubator/setup-miniconda@v2
       with:
         miniforge-version: latest
-        miniforge-variant: Mambaforge
     - name: Install dependencies
       shell: bash -l {0}
       run: conda install gdal cloudpickle scipy

rios/calcstats.py

@@ -1,6 +1,6 @@
 """
 This module creates pyramid layers and calculates statistics for image
-files. Much of it was originally for ERDAS Imagine files but should work 
+files. Much of it was originally for ERDAS Imagine files but should work
 with any other format that supports pyramid layers and statistics
 
 """
@@ -28,6 +28,7 @@
 from . import cuiprogress
 from .rioserrors import ProcessCancelledError, SinglePassActionsError
 
+
 # When calculating overviews (i.e. pyramid layers), default behaviour
 # is controlled by these
 dfltOverviewLvls = os.getenv('RIOS_DFLT_OVERVIEWLEVELS')
@@ -831,8 +832,8 @@ def writeBlockPyramids(ds, arr, singlePassMgr, symbolicName, xOff, yOff):
     for i in range(numBands):
         band = ds.GetRasterBand(i + 1)
         for j in range(nOverviews):
-            band_ov = band.GetOverview(i)
-            lvl = overviewLevels[i]
+            band_ov = band.GetOverview(j)
+            lvl = overviewLevels[j]
             # Offset from top-left edge
             o = lvl // 2
             # Sub-sample by taking every lvl-th pixel in each direction

rios/riostests/testpyramids.py

@@ -39,8 +39,8 @@ def run():
 
     # Create a test input file
     rampInfile = 'ramp.img'
-    # Set a raster size which will result in exactly one pyramid layer
-    nRows = nCols = 1024
+    # Set a raster size which will result in exactly two pyramid layers
+    nRows = nCols = 2048
     riostestutils.genRampImageFile(rampInfile, numRows=nRows, numCols=nCols)
 
     infiles = applier.FilenameAssociations()
@@ -84,36 +84,37 @@ def checkPyramids(filename, singlePass):
     band = ds.GetRasterBand(1)
     arr = band.ReadAsArray()
     numOverviews = band.GetOverviewCount()
-    if numOverviews != 1:
+    if numOverviews != 2:
         msg = "Incorrect overview count: {}".format(numOverviews)
         riostestutils.report(TESTNAME, msg)
         ok = False
 
-    band_ov = band.GetOverview(0)
-    arr_ov = band_ov.ReadAsArray()
-
-    # Work out which offset (o) to use
-    factor = int(round(arr.shape[0] / arr_ov.shape[0]))
-    if singlePass:
-        o = int(round(factor / 2))
-    else:
-        # GDAL doesn't use an offset (sigh....)
-        o = 0
-
-    # The true sub-sampled overview array
-    true_arr_ov = arr[o::factor, o::factor]
-    if true_arr_ov.shape != arr_ov.shape:
-        msg = "Overview shape mis-match: {} != {}".format(true_arr_ov.shape,
-            arr_ov.shape)
-        riostestutils.report(TESTNAME, msg)
-        ok = False
-    else:
-        mismatch = (arr_ov != true_arr_ov)
-        numMismatch = numpy.count_nonzero(mismatch)
-        if numMismatch > 0:
-            msg = "Pyramid layer pixel mis-match for {} pixels".format(numMismatch)
+    for i in range(numOverviews):
+        band_ov = band.GetOverview(i)
+        arr_ov = band_ov.ReadAsArray()
+
+        # Work out which offset (o) to use
+        factor = int(round(arr.shape[0] / arr_ov.shape[0]))
+        if singlePass:
+            o = int(round(factor / 2))
+        else:
+            # GDAL doesn't use an offset (sigh....)
+            o = 0
+
+        # The true sub-sampled overview array
+        true_arr_ov = arr[o::factor, o::factor]
+        if true_arr_ov.shape != arr_ov.shape:
+            msg = "Overview shape mis-match: {} != {}".format(true_arr_ov.shape,
+                arr_ov.shape)
             riostestutils.report(TESTNAME, msg)
             ok = False
+        else:
+            mismatch = (arr_ov != true_arr_ov)
+            numMismatch = numpy.count_nonzero(mismatch)
+            if numMismatch > 0:
+                msg = "Pyramid layer pixel mis-match for {} pixels".format(numMismatch)
+                riostestutils.report(TESTNAME, msg)
+                ok = False
 
     return ok