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Merge pull request#22592 from meeseeksmachine/auto-backport-of-pr-22141-on-v3.5.x

Backport PR#22141 on branch v3.5.x (Fix check 1d)

2 parents17b4e10 +4715aff commit0040b0aCopy full SHA for 0040b0a

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+14

-44

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lib/matplotlib
- cbook
  - __init__.py
- tests
  - test_axes.py

2 files changed

+14

-44

lines changed

`‎lib/matplotlib/cbook/init.py`

Lines changed: 5 additions & 39 deletions

Original file line number	Diff line number	Diff line change
`@@ -1300,47 +1300,13 @@ def _to_unmasked_float_array(x):`
`1300`	`1300`
`1301`	`1301`	`def_check_1d(x):`
`1302`	`1302`	`"""Convert scalars to 1D arrays; pass-through arrays as is."""`
	`1303`	`+ifhasattr(x,'to_numpy'):`
	`1304`	`+# if we are given an object that creates a numpy, we should use it...`
	`1305`	`+x=x.to_numpy()`
`1303`	`1306`	`ifnothasattr(x,'shape')orlen(x.shape)<1:`
`1304`	`1307`	`returnnp.atleast_1d(x)`
`1305`	`1308`	`else:`
`1306`		`-try:`
`1307`		`-# work around`
`1308`		`-# https://github.com/pandas-dev/pandas/issues/27775 which`
`1309`		`-# means the shape of multi-dimensional slicing is not as`
`1310`		`-# expected. That this ever worked was an unintentional`
`1311`		`-# quirk of pandas and will raise an exception in the`
`1312`		`-# future. This slicing warns in pandas >= 1.0rc0 via`
`1313`		`-# https://github.com/pandas-dev/pandas/pull/30588`
`1314`		`-#`
`1315`		`-# < 1.0rc0 : x[:, None].ndim == 1, no warning, custom type`
`1316`		`-# >= 1.0rc1 : x[:, None].ndim == 2, warns, numpy array`
`1317`		`-# future : x[:, None] -> raises`
`1318`		`-#`
`1319`		`-# This code should correctly identify and coerce to a`
`1320`		`-# numpy array all pandas versions.`
`1321`		`-withwarnings.catch_warnings(record=True)asw:`
`1322`		`-warnings.filterwarnings(`
`1323`		`-"always",`
`1324`		`-category=Warning,`
`1325`		`-message='Support for multi-dimensional indexing')`
`1326`		`-`
`1327`		`-ndim=x[:,None].ndim`
`1328`		`-# we have definitely hit a pandas index or series object`
`1329`		`-# cast to a numpy array.`
`1330`		`-iflen(w)>0:`
`1331`		`-returnnp.asanyarray(x)`
`1332`		`-# We have likely hit a pandas object, or at least`
`1333`		`-# something where 2D slicing does not result in a 2D`
`1334`		`-# object.`
`1335`		`-ifndim<2:`
`1336`		`-returnnp.atleast_1d(x)`
`1337`		`-returnx`
`1338`		`-# In pandas 1.1.0, multidimensional indexing leads to an`
`1339`		`-# AssertionError for some Series objects, but should be`
`1340`		`-# IndexError as described in`
`1341`		`-# https://github.com/pandas-dev/pandas/issues/35527`
`1342`		`-except (AssertionError,IndexError,TypeError):`
`1343`		`-returnnp.atleast_1d(x)`
	`1309`	`+returnx`
`1344`	`1310`
`1345`	`1311`
`1346`	`1312`	`def_reshape_2D(X,name):`
`@@ -1649,7 +1615,7 @@ def index_of(y):`
`1649`	`1615`	`The x and y values to plot.`
`1650`	`1616`	`"""`
`1651`	`1617`	`try:`
`1652`		`-returny.index.values,y.values`
	`1618`	`+returny.index.to_numpy(),y.to_numpy()`
`1653`	`1619`	`exceptAttributeError:`
`1654`	`1620`	`pass`
`1655`	`1621`	`try:`

`‎lib/matplotlib/tests/test_axes.py`

Lines changed: 9 additions & 5 deletions

Original file line number	Diff line number	Diff line change
`@@ -1762,11 +1762,15 @@ def test_bar_hatches(fig_test, fig_ref):`
`1762`	`1762`
`1763`	`1763`	`deftest_pandas_minimal_plot(pd):`
`1764`	`1764`	`# smoke test that series and index objcets do not warn`
`1765`		`-x=pd.Series([1,2],dtype="float64")`
`1766`		`-plt.plot(x,x)`
`1767`		`-plt.plot(x.index,x)`
`1768`		`-plt.plot(x)`
`1769`		`-plt.plot(x.index)`
	`1765`	`+forxin [pd.Series([1,2],dtype="float64"),`
	`1766`	`+pd.Series([1,2],dtype="Float64")]:`
	`1767`	`+plt.plot(x,x)`
	`1768`	`+plt.plot(x.index,x)`
	`1769`	`+plt.plot(x)`
	`1770`	`+plt.plot(x.index)`
	`1771`	`+df=pd.DataFrame({'col': [1,2,3]})`
	`1772`	`+plt.plot(df)`
	`1773`	`+plt.plot(df,df)`
`1770`	`1774`
`1771`	`1775`
`1772`	`1776`	`@image_comparison(['hist_log'],remove_text=True)`

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Commit0040b0a

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`‎lib/matplotlib/cbook/init.py`

`‎lib/matplotlib/tests/test_axes.py`

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‎lib/matplotlib/cbook/__init__.py

‎lib/matplotlib/tests/test_axes.py

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`‎lib/matplotlib/cbook/init.py`

`‎lib/matplotlib/tests/test_axes.py`