python-plotly/plotly-pr4622-np2.patch

From 0199582127111c453db70a0133db8c64baca7c40 Mon Sep 17 00:00:00 2001
From: Ben Greiner <code@bnavigator.de>
Date: Sun, 2 Jun 2024 16:43:06 +0200
Subject: [PATCH 1/3] Remove np.nan and np.inf aliases no longer present in
 numpy2

---
 .../tests/test_optional/test_utils/test_utils.py     | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

diff --git a/packages/python/plotly/plotly/tests/test_optional/test_utils/test_utils.py b/packages/python/plotly/plotly/tests/test_optional/test_utils/test_utils.py
index cf32e1bdf..d7d982e63 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_utils/test_utils.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_utils/test_utils.py
@@ -34,7 +34,7 @@ if matplotlylib:
 
 ## JSON encoding
 numeric_list = [1, 2, 3]
-np_list = np.array([1, 2, 3, np.NaN, np.NAN, np.Inf, dt(2014, 1, 5)])
+np_list = np.array([1, 2, 3, np.nan, np.inf, dt(2014, 1, 5)])
 mixed_list = [
     1,
     "A",
@@ -45,7 +45,7 @@ mixed_list = [
 dt_list = [dt(2014, 1, 5), dt(2014, 1, 5, 1, 1, 1), dt(2014, 1, 5, 1, 1, 1, 1)]
 
 df = pd.DataFrame(
-    columns=["col 1"], data=[1, 2, 3, dt(2014, 1, 5), pd.NaT, np.NaN, np.Inf]
+    columns=["col 1"], data=[1, 2, 3, dt(2014, 1, 5), pd.NaT, np.nan, np.inf]
 )
 
 rng = pd.date_range("1/1/2011", periods=2, freq="H")
@@ -184,7 +184,7 @@ class TestJSONEncoder(TestCase):
 
         assert (
             js1 == '{"type": "scatter3d", "x": [1, 2, 3], '
-            '"y": [1, 2, 3, null, null, null, "2014-01-05T00:00:00"], '
+            '"y": [1, 2, 3, null, null, "2014-01-05T00:00:00"], '
             '"z": [1, "A", "2014-01-05T00:00:00", '
             '"2014-01-05T01:01:01", "2014-01-05T01:01:01.000001"]}'
         )
@@ -195,9 +195,9 @@ class TestJSONEncoder(TestCase):
         _json.dumps(figure, cls=utils.PlotlyJSONEncoder, sort_keys=True)
 
         # Test data wasn't mutated
-        np_array = np.array([1, 2, 3, np.NaN, np.NAN, np.Inf, dt(2014, 1, 5)])
+        np_array = np.array([1, 2, 3, np.nan, np.inf, dt(2014, 1, 5)])
         for k in range(len(np_array)):
-            if k in [3, 4]:
+            if k == 3:
                 # check NaN
                 assert np.isnan(np_list[k]) and np.isnan(np_array[k])
             else:
@@ -237,7 +237,7 @@ class TestJSONEncoder(TestCase):
         # Test that data wasn't mutated
         assert_series_equal(
             df["col 1"],
-            pd.Series([1, 2, 3, dt(2014, 1, 5), pd.NaT, np.NaN, np.Inf], name="col 1"),
+            pd.Series([1, 2, 3, dt(2014, 1, 5), pd.NaT, np.nan, np.inf], name="col 1"),
         )
 
         j2 = _json.dumps(df.index, cls=utils.PlotlyJSONEncoder)
-- 
2.45.1

From f88554113e8cf55a1d756c3f0d33b92a891d0475 Mon Sep 17 00:00:00 2001
From: Ben Greiner <code@bnavigator.de>
Date: Sun, 2 Jun 2024 16:48:34 +0200
Subject: [PATCH 2/3] Avoid putting 255 into int8 due to new numpy 2 type
 promotion rules

---
 .../plotly/plotly/tests/test_optional/test_px/test_imshow.py    | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/packages/python/plotly/plotly/tests/test_optional/test_px/test_imshow.py b/packages/python/plotly/plotly/tests/test_optional/test_px/test_imshow.py
index c2e863c84..d8f9ad98c 100644
--- a/packages/python/plotly/plotly/tests/test_optional/test_px/test_imshow.py
+++ b/packages/python/plotly/plotly/tests/test_optional/test_px/test_imshow.py
@@ -341,7 +341,7 @@ def test_imshow_source_dtype_zmax(dtype, contrast_rescaling):
             assert (
                 np.abs(
                     np.max(decode_image_string(fig.data[0].source))
-                    - 255 * img.max() / np.iinfo(dtype).max
+                    - np.int64(255) * img.max() / np.iinfo(dtype).max
                 )
                 < 1
             )
-- 
2.45.1