Numpy2 fixes (#90)

* Cope with numpy-2 change in comparing float32 and float64 values * Cope with numpy-2 changes in how repr() handles numpy scalar values
ubarsc · Jun 18, 2024 · aa516c8 · aa516c8
1 parent 7135564
commit aa516c8
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Showing 2 changed files with 8 additions and 4 deletions.
diff --git a/rios/calcstats.py b/rios/calcstats.py
@@ -294,7 +294,7 @@ def addStatistics(ds, progress, ignore=None, approx_ok=False):
             modebin = numpy.argmax(hist)
             modeval = modebin * histstep + histmin
             if band.DataType == gdal.GDT_Float32 or band.DataType == gdal.GDT_Float64:
-                tmpmeta["STATISTICS_MODE"] = repr(modeval)
+                tmpmeta["STATISTICS_MODE"] = repr(float(modeval))
             else:
                 tmpmeta["STATISTICS_MODE"] = repr(int(round(modeval)))
 
@@ -315,19 +315,19 @@ def addStatistics(ds, progress, ignore=None, approx_ok=False):
             else:
                 # Use GDAL's original metadata interface, for drivers which
                 # don't support the more modern approach
-                tmpmeta["STATISTICS_HISTOBINVALUES"] = '|'.join(map(repr, hist)) + '|'
+                tmpmeta["STATISTICS_HISTOBINVALUES"] = '|'.join(map(str, hist)) + '|'
 
                 tmpmeta["STATISTICS_HISTOMIN"] = repr(histmin)
                 tmpmeta["STATISTICS_HISTOMAX"] = repr(histmax)
-                tmpmeta["STATISTICS_HISTONUMBINS"] = repr(histnbins)
+                tmpmeta["STATISTICS_HISTONUMBINS"] = int(histnbins)
 
             # estimate the median - bin with the middle number
             middlenum = hist.sum() / 2
             gtmiddle = hist.cumsum() >= middlenum
             medianbin = gtmiddle.nonzero()[0][0]
             medianval = medianbin * histstep + histmin
             if band.DataType == gdal.GDT_Float32 or band.DataType == gdal.GDT_Float64:
-                tmpmeta["STATISTICS_MEDIAN"] = repr(medianval)
+                tmpmeta["STATISTICS_MEDIAN"] = repr(float(medianval))
             else:
                 tmpmeta["STATISTICS_MEDIAN"] = repr(int(round(medianval)))
 

diff --git a/rios/riostests/testvector.py b/rios/riostests/testvector.py
@@ -47,6 +47,10 @@ def run():
     meanVal_rios = calcMeanWithRiosApplier(imgfile, vecfile)
 
     ok = True
+    # Since numpy-2, these have different precisions. The numpy-calculated
+    # value is numpy.float64, while the rios-calculated one is numpy.float32.
+    # So, cast the longer one to match the shorter. Sigh.....
+    meanVal_numpy = numpy.asarray(meanVal_numpy, dtype=meanVal_rios.dtype)
     if meanVal_numpy == meanVal_rios:
         riostestutils.report(TESTNAME, "Passed")
     else: