Update NaN references for new NumPy 2. (#8)

* Update NaN references for new NumPy 2. * Bump dolomite-base version
ArtifactDB · Oct 23, 2024 · 6279e94 · 6279e94
1 parent 7343f39
commit 6279e94
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Showing 4 changed files with 12 additions and 12 deletions.
diff --git a/setup.cfg b/setup.cfg
@@ -49,7 +49,7 @@ python_requires = >=3.8
 # For more information, check out https://semver.org/.
 install_requires =
     importlib-metadata; python_version<"3.8"
-    dolomite-base>=0.2.0
+    dolomite-base>=0.3.0
     delayedarray>=0.5.0
     h5py
     numpy

diff --git a/src/dolomite_matrix/_optimize_storage.py b/src/dolomite_matrix/_optimize_storage.py
@@ -242,7 +242,7 @@ def optimize_integer_storage(x, buffer_size: int = 1e8) -> _OptimizedStoragePara
             elif upper < 2**31 - 1: # Yes, this is deliberate, as integer storage maxes out at 32-bit signed integers.
                 return _OptimizedStorageParameters(type="i4", placeholder=2**31-1, non_zero=attr.non_zero)
 
-        return _OptimizedStorageParameters(type="f8", placeholder=numpy.NaN, non_zero=attr.non_zero)
+        return _OptimizedStorageParameters(type="f8", placeholder=numpy.nan, non_zero=attr.non_zero)
 
     else:
         # If it's infinite, that means that 'x' is of length zero, otherwise
@@ -497,7 +497,7 @@ def optimize_float_storage(x, buffer_size: int = 1e8) -> _OptimizedStorageParame
 
         placeholder = None
         if not attr.has_nan:
-            placeholder = numpy.NaN
+            placeholder = numpy.nan
         elif not attr.has_positive_inf:
             placeholder = numpy.inf
         elif not attr.has_negative_inf:

diff --git a/tests/test_DelayedMask.py b/tests/test_DelayedMask.py
@@ -32,8 +32,8 @@ def test_DelayedMask_dense():
 
 
 def test_DelayedMask_dense_NaN():
-    y = numpy.array([[1,2,numpy.NaN],[4,5,6]])
-    m = dm.DelayedMask(y, numpy.NaN)
+    y = numpy.array([[1,2,numpy.nan],[4,5,6]])
+    m = dm.DelayedMask(y, numpy.nan)
     block = delayedarray.to_dense_array(m)
     assert numpy.ma.is_masked(block)
     assert numpy.ma.is_masked(block[0,2])

diff --git a/tests/test_optimize_storage.py b/tests/test_optimize_storage.py
@@ -270,7 +270,7 @@ def test_optimize_float_storage_dense():
     assert opt.type == "f8"
     assert opt.placeholder is None
 
-    y = numpy.array([numpy.NaN,2,3])
+    y = numpy.array([numpy.nan,2,3])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder is None
@@ -354,33 +354,33 @@ def test_optimize_float_storage_dense_MaskedArray():
     assert opt.type == "f8"
     assert numpy.isnan(opt.placeholder)
 
-    y = numpy.ma.MaskedArray([numpy.NaN,2,3], mask=[False, True, False])
+    y = numpy.ma.MaskedArray([numpy.nan,2,3], mask=[False, True, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == numpy.inf
 
-    y = numpy.ma.MaskedArray([numpy.NaN,2,numpy.inf], mask=[False, True, False])
+    y = numpy.ma.MaskedArray([numpy.nan,2,numpy.inf], mask=[False, True, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == -numpy.inf
 
     fstats = numpy.finfo(numpy.float64)
-    y = numpy.ma.MaskedArray([numpy.NaN, 2, numpy.inf, -numpy.inf], mask=[False, True, False, False])
+    y = numpy.ma.MaskedArray([numpy.nan, 2, numpy.inf, -numpy.inf], mask=[False, True, False, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == fstats.min
 
-    y = numpy.ma.MaskedArray([numpy.NaN, 2, numpy.inf, -numpy.inf, fstats.min], mask=[False, True, False, False, False])
+    y = numpy.ma.MaskedArray([numpy.nan, 2, numpy.inf, -numpy.inf, fstats.min], mask=[False, True, False, False, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == fstats.max
 
-    y = numpy.ma.MaskedArray([numpy.NaN, 2, numpy.inf, -numpy.inf, fstats.min, fstats.max], mask=[False, True, False, False, False, False])
+    y = numpy.ma.MaskedArray([numpy.nan, 2, numpy.inf, -numpy.inf, fstats.min, fstats.max], mask=[False, True, False, False, False, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == 0
 
-    y = numpy.ma.MaskedArray([numpy.NaN, 2, numpy.inf, -numpy.inf, fstats.min, fstats.max, 0], mask=[False, True, False, False, False, False, False])
+    y = numpy.ma.MaskedArray([numpy.nan, 2, numpy.inf, -numpy.inf, fstats.min, fstats.max, 0], mask=[False, True, False, False, False, False, False])
     opt = optim.optimize_float_storage(y)
     assert opt.type == "f8"
     assert opt.placeholder == fstats.min / 2