本文整理汇总了Python中xray.Variable.argsort方法的典型用法代码示例。如果您正苦于以下问题：Python Variable.argsort方法的具体用法？Python Variable.argsort怎么用？Python Variable.argsort使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类xray.Variable的用法示例。
在下文中一共展示了Variable.argsort方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import argsort [as 别名]
#.........这里部分代码省略.........
data.reset_coords('not_found')
with self.assertRaisesRegexp(ValueError, 'cannot remove index'):
data.reset_coords('y')
def test_reindex(self):
foo = self.dv
bar = self.dv[:2, :2]
self.assertDataArrayIdentical(foo.reindex_like(bar), bar)
expected = foo.copy()
expected[:] = np.nan
expected[:2, :2] = bar
self.assertDataArrayIdentical(bar.reindex_like(foo), expected)
def test_rename(self):
renamed = self.dv.rename('bar')
self.assertDatasetIdentical(
renamed.to_dataset(), self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
renamed = self.dv.rename({'foo': 'bar'})
self.assertDatasetIdentical(
renamed.to_dataset(), self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
def test_dataset_getitem(self):
dv = self.ds['foo']
self.assertDataArrayIdentical(dv, self.dv)
def test_array_interface(self):
self.assertArrayEqual(np.asarray(self.dv), self.x)
# test patched in methods
self.assertArrayEqual(self.dv.astype(float), self.v.astype(float))
self.assertVariableEqual(self.dv.argsort(), self.v.argsort())
self.assertVariableEqual(self.dv.clip(2, 3), self.v.clip(2, 3))
# test ufuncs
expected = deepcopy(self.ds)
expected['foo'][:] = np.sin(self.x)
self.assertDataArrayEqual(expected['foo'], np.sin(self.dv))
self.assertDataArrayEqual(self.dv, np.maximum(self.v, self.dv))
bar = Variable(['x', 'y'], np.zeros((10, 20)))
self.assertDataArrayEqual(self.dv, np.maximum(self.dv, bar))
def test_is_null(self):
x = np.random.RandomState(42).randn(5, 6)
x[x < 0] = np.nan
original = DataArray(x, [-np.arange(5), np.arange(6)], ['x', 'y'])
expected = DataArray(pd.isnull(x), [-np.arange(5), np.arange(6)],
['x', 'y'])
self.assertDataArrayIdentical(expected, original.isnull())
self.assertDataArrayIdentical(~expected, original.notnull())
def test_math(self):
x = self.x
v = self.v
a = self.dv
# variable math was already tested extensively, so let's just make sure
# that all types are properly converted here
self.assertDataArrayEqual(a, +a)
self.assertDataArrayEqual(a, a + 0)
self.assertDataArrayEqual(a, 0 + a)
self.assertDataArrayEqual(a, a + 0 * v)
self.assertDataArrayEqual(a, 0 * v + a)
self.assertDataArrayEqual(a, a + 0 * x)
self.assertDataArrayEqual(a, 0 * x + a)
self.assertDataArrayEqual(a, a + 0 * a)示例2: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import argsort [as 别名]
#.........这里部分代码省略.........
actual = expected.reindex(time=time2)
self.assertDataArrayIdentical(actual, expected)
def test_reindex_method(self):
x = DataArray([10, 20], dims='y')
y = [-0.5, 0.5, 1.5]
actual = x.reindex(y=y, method='backfill')
expected = DataArray([10, 20, np.nan], coords=[('y', y)])
self.assertDataArrayIdentical(expected, actual)
alt = Dataset({'y': y})
actual = x.reindex_like(alt, method='backfill')
self.assertDatasetIdentical(expected, actual)
def test_rename(self):
renamed = self.dv.rename('bar')
self.assertDatasetIdentical(
renamed.to_dataset(), self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
renamed = self.dv.rename({'foo': 'bar'})
self.assertDatasetIdentical(
renamed.to_dataset(), self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
def test_dataset_getitem(self):
dv = self.ds['foo']
self.assertDataArrayIdentical(dv, self.dv)
def test_array_interface(self):
self.assertArrayEqual(np.asarray(self.dv), self.x)
# test patched in methods
self.assertArrayEqual(self.dv.astype(float), self.v.astype(float))
self.assertVariableEqual(self.dv.argsort(), self.v.argsort())
self.assertVariableEqual(self.dv.clip(2, 3), self.v.clip(2, 3))
# test ufuncs
expected = deepcopy(self.ds)
expected['foo'][:] = np.sin(self.x)
self.assertDataArrayEqual(expected['foo'], np.sin(self.dv))
self.assertDataArrayEqual(self.dv, np.maximum(self.v, self.dv))
bar = Variable(['x', 'y'], np.zeros((10, 20)))
self.assertDataArrayEqual(self.dv, np.maximum(self.dv, bar))
def test_is_null(self):
x = np.random.RandomState(42).randn(5, 6)
x[x < 0] = np.nan
original = DataArray(x, [-np.arange(5), np.arange(6)], ['x', 'y'])
expected = DataArray(pd.isnull(x), [-np.arange(5), np.arange(6)],
['x', 'y'])
self.assertDataArrayIdentical(expected, original.isnull())
self.assertDataArrayIdentical(~expected, original.notnull())
def test_math(self):
x = self.x
v = self.v
a = self.dv
# variable math was already tested extensively, so let's just make sure
# that all types are properly converted here
self.assertDataArrayEqual(a, +a)
self.assertDataArrayEqual(a, a + 0)
self.assertDataArrayEqual(a, 0 + a)
self.assertDataArrayEqual(a, a + 0 * v)
self.assertDataArrayEqual(a, 0 * v + a)
self.assertDataArrayEqual(a, a + 0 * x)
self.assertDataArrayEqual(a, 0 * x + a)
self.assertDataArrayEqual(a, a + 0 * a)示例3: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import argsort [as 别名]
#.........这里部分代码省略.........
self.assertDataArrayIdentical(da[:3], da.loc[['a', 'b', 'c']])
self.assertDataArrayIdentical(da[:3, :4],
da.loc[['a', 'b', 'c'], np.arange(4)])
da.loc['a':'j'] = 0
self.assertTrue(np.all(da.values == 0))
def test_reindex(self):
foo = self.dv
bar = self.dv[:2, :2]
self.assertDataArrayIdentical(foo.reindex_like(bar), bar)
expected = foo.copy()
expected[:] = np.nan
expected[:2, :2] = bar
self.assertDataArrayIdentical(bar.reindex_like(foo), expected)
def test_rename(self):
renamed = self.dv.rename('bar')
self.assertEqual(renamed.dataset, self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
renamed = self.dv.rename({'foo': 'bar'})
self.assertEqual(renamed.dataset, self.ds.rename({'foo': 'bar'}))
self.assertEqual(renamed.name, 'bar')
def test_dataset_getitem(self):
dv = self.ds['foo']
self.assertDataArrayIdentical(dv, self.dv)
def test_array_interface(self):
self.assertArrayEqual(np.asarray(self.dv), self.x)
# test patched in methods
self.assertArrayEqual(self.dv.astype(float), self.v.astype(float))
self.assertVariableEqual(self.dv.argsort(), self.v.argsort())
self.assertVariableEqual(self.dv.clip(2, 3), self.v.clip(2, 3))
# test ufuncs
expected = deepcopy(self.ds)
expected['foo'][:] = np.sin(self.x)
self.assertDataArrayEqual(expected['foo'], np.sin(self.dv))
self.assertDataArrayEqual(self.dv, np.maximum(self.v, self.dv))
bar = Variable(['x', 'y'], np.zeros((10, 20)))
self.assertDataArrayEqual(self.dv, np.maximum(self.dv, bar))
def test_math(self):
x = self.x
v = self.v
a = self.dv
# variable math was already tested extensively, so let's just make sure
# that all types are properly converted here
self.assertDataArrayEqual(a, +a)
self.assertDataArrayEqual(a, a + 0)
self.assertDataArrayEqual(a, 0 + a)
self.assertDataArrayEqual(a, a + 0 * v)
self.assertDataArrayEqual(a, 0 * v + a)
self.assertDataArrayEqual(a, a + 0 * x)
self.assertDataArrayEqual(a, 0 * x + a)
self.assertDataArrayEqual(a, a + 0 * a)
self.assertDataArrayEqual(a, 0 * a + a)
# test different indices
ds2 = self.ds.update({'x': ('x', 3 + np.arange(10))}, inplace=False)
b = ds2['foo']
with self.assertRaisesRegexp(ValueError, 'not aligned'):
a + b
with self.assertRaisesRegexp(ValueError, 'not aligned'):
b + a
with self.assertRaisesRegexp(TypeError, 'datasets do not support'):