remove patch
OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-xarray?expand=0&rev=85
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@ -27,8 +27,6 @@ Source: https://files.pythonhosted.org/packages/source/x/xarray/xarray-%
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# PATCH-FEATURE-UPSTREAM local_dataset.patch gh#pydata/xarray#5377 mcepl@suse.com
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# fix xr.tutorial.open_dataset to work with the preloaded cache.
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Patch0: local_dataset.patch
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# PATCH-FIX-UPSTREAM xarray-pr8139-pandas-fill_value.patch gh#pydata/xarray#8125, gh#pydata/xarray#8139
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#Patch1: https://github.com/pydata/xarray/pull/8139.patch#/xarray-pr8139-pandas-fill_value.patch
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BuildRequires: %{python_module base >= 3.9}
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BuildRequires: %{python_module numpy-devel >= 1.22}
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BuildRequires: %{python_module packaging >= 21.3}
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@ -1,38 +0,0 @@
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From 3e48312c41cb26bbd4dc83ae286444f1469b7aa2 Mon Sep 17 00:00:00 2001
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From: Maximilian Roos <m@maxroos.com>
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Date: Fri, 1 Sep 2023 19:41:41 -0700
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Subject: [PATCH] Fix pandas interpolate(fill_value=) error
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Pandas no longer has a `fill_value` parameter for `interpolate`.
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Weirdly I wasn't getting this locally, on pandas 2.1.0, only in CI on https://github.com/pydata/xarray/actions/runs/6054400455/job/16431747966?pr=8138.
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Removing it passes locally, let's see whether this works in CI
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---
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xarray/tests/test_missing.py | 6 ++++--
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1 file changed, 4 insertions(+), 2 deletions(-)
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diff --git a/xarray/tests/test_missing.py b/xarray/tests/test_missing.py
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index a6b6b1f80c..c303659116 100644
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--- a/xarray/tests/test_missing.py
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+++ b/xarray/tests/test_missing.py
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@@ -104,7 +104,8 @@ def test_interpolate_pd_compat():
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for dim in ["time", "x"]:
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actual = da.interpolate_na(method=method, dim=dim, fill_value=np.nan)
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expected = df.interpolate(
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- method=method, axis=da.get_axis_num(dim), fill_value=(np.nan, np.nan)
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+ method=method,
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+ axis=da.get_axis_num(dim),
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)
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# Note, Pandas does some odd things with the left/right fill_value
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# for the linear methods. This next line inforces the xarray
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@@ -140,7 +141,8 @@ def test_interpolate_pd_compat_non_uniform_index():
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method="linear", dim=dim, use_coordinate=True, fill_value=np.nan
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)
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expected = df.interpolate(
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- method=method, axis=da.get_axis_num(dim), fill_value=np.nan
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+ method=method,
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+ axis=da.get_axis_num(dim),
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)
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# Note, Pandas does some odd things with the left/right fill_value
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