本文整理汇总了Python中xray.Variable.reduce方法的典型用法代码示例。如果您正苦于以下问题：Python Variable.reduce方法的具体用法？Python Variable.reduce怎么用？Python Variable.reduce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.reduce方法的5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: test_reduce
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import reduce [as 别名]
def test_reduce(self):
v = Variable(["x", "y"], self.d, {"ignored": "attributes"})
self.assertVariableIdentical(v.reduce(np.std, "x"), Variable(["y"], self.d.std(axis=0)))
self.assertVariableIdentical(v.reduce(np.std, axis=0), v.reduce(np.std, dim="x"))
self.assertVariableIdentical(v.reduce(np.std, ["y", "x"]), Variable([], self.d.std(axis=(0, 1))))
self.assertVariableIdentical(v.reduce(np.std), Variable([], self.d.std()))
self.assertVariableIdentical(
v.reduce(np.mean, "x").reduce(np.std, "y"), Variable([], self.d.mean(axis=0).std())
)
self.assertVariableAllClose(v.mean("x"), v.reduce(np.mean, "x"))
with self.assertRaisesRegexp(ValueError, "cannot supply both"):
v.mean(dim="x", axis=0)示例2: test_reduce
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import reduce [as 别名]
def test_reduce(self):
v = Variable(['x', 'y'], self.d, {'ignored': 'attributes'})
self.assertVariableIdentical(v.reduce(np.std, 'x'),
Variable(['y'], self.d.std(axis=0)))
self.assertVariableIdentical(v.reduce(np.std, axis=0),
v.reduce(np.std, dim='x'))
self.assertVariableIdentical(v.reduce(np.std, ['y', 'x']),
Variable([], self.d.std(axis=(0, 1))))
self.assertVariableIdentical(v.reduce(np.std),
Variable([], self.d.std()))
self.assertVariableIdentical(
v.reduce(np.mean, 'x').reduce(np.std, 'y'),
Variable([], self.d.mean(axis=0).std()))
self.assertVariableIdentical(v.mean('x'), v.reduce(np.mean, 'x'))
with self.assertRaisesRegexp(ValueError, 'cannot supply both'):
v.mean(dim='x', axis=0)示例3: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import reduce [as 别名]
#.........这里部分代码省略.........
with self.assertRaisesRegexp(ValueError, 'cannot drop'):
arr.drop(None)
renamed = arr.rename('foo')
with self.assertRaisesRegexp(ValueError, 'cannot drop'):
renamed.drop('foo')
def test_drop_index_labels(self):
arr = DataArray(np.random.randn(2, 3), dims=['x', 'y'])
actual = arr.drop([0, 1], dim='y')
expected = arr[:, 2:]
self.assertDataArrayIdentical(expected, actual)
def test_dropna(self):
x = np.random.randn(4, 4)
x[::2, 0] = np.nan
arr = DataArray(x, dims=['a', 'b'])
actual = arr.dropna('a')
expected = arr[1::2]
self.assertDataArrayIdentical(actual, expected)
actual = arr.dropna('b', how='all')
self.assertDataArrayIdentical(actual, arr)
actual = arr.dropna('a', thresh=1)
self.assertDataArrayIdentical(actual, arr)
actual = arr.dropna('b', thresh=3)
expected = arr[:, 1:]
self.assertDataArrayIdentical(actual, expected)
def test_reduce(self):
coords = {'x': [-1, -2], 'y': ['ab', 'cd', 'ef'],
'lat': (['x', 'y'], [[1, 2, 3], [-1, -2, -3]]),
'c': -999}
orig = DataArray([[-1, 0, 1], [-3, 0, 3]], coords, dims=['x', 'y'])
actual = orig.mean()
expected = DataArray(0, {'c': -999})
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean(['x', 'y'])
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean('x')
expected = DataArray([-2, 0, 2], {'y': coords['y'], 'c': -999}, 'y')
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean(['x'])
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean('y')
expected = DataArray([0, 0], {'x': coords['x'], 'c': -999}, 'x')
self.assertDataArrayIdentical(expected, actual)
self.assertVariableEqual(self.dv.reduce(np.mean, 'x'),
self.v.reduce(np.mean, 'x'))
orig = DataArray([[1, 0, np.nan], [3, 0, 3]], coords, dims=['x', 'y'])
actual = orig.count()
expected = DataArray(5, {'c': -999})
self.assertDataArrayIdentical(expected, actual)
def test_reduce_keep_attrs(self):示例4: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import reduce [as 别名]
#.........这里部分代码省略.........
'tmax': ('x', 11 + np.arange(5)),
# does *not* include 'loc' as a coordinate
'x': ('x', 0.5 * np.arange(5))})
actual = sim['tmin'] - obs['tmin']
expected = DataArray(np.ones(5), obs.coords, name='tmin')
self.assertDataArrayIdentical(actual, expected)
actual = -obs['tmin'] + sim['tmin']
self.assertDataArrayIdentical(actual, expected)
actual = sim['tmin'].copy()
actual -= obs['tmin']
self.assertDataArrayIdentical(actual, expected)
actual = sim.copy()
actual['tmin'] = sim['tmin'] - obs['tmin']
expected = Dataset({'tmin': ('x', np.ones(5)),
'tmax': ('x', sim['tmax'].values)},
obs.coords)
self.assertDatasetIdentical(actual, expected)
actual = sim.copy()
actual['tmin'] -= obs['tmin']
self.assertDatasetIdentical(actual, expected)
def test_transpose(self):
self.assertVariableEqual(self.dv.variable.transpose(),
self.dv.transpose())
def test_squeeze(self):
self.assertVariableEqual(self.dv.variable.squeeze(), self.dv.squeeze())
def test_reduce(self):
coords = {'x': [-1, -2], 'y': ['ab', 'cd', 'ef'],
'lat': (['x', 'y'], [[1, 2, 3], [-1, -2, -3]]),
'c': -999}
orig = DataArray([[-1, 0, 1], [-3, 0, 3]], coords, dims=['x', 'y'])
actual = orig.mean()
expected = DataArray(0, {'c': -999})
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean(['x', 'y'])
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean('x')
expected = DataArray([-2, 0, 2], {'y': coords['y'], 'c': -999}, 'y')
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean(['x'])
self.assertDataArrayIdentical(expected, actual)
actual = orig.mean('y')
expected = DataArray([0, 0], {'x': coords['x'], 'c': -999}, 'x')
self.assertDataArrayIdentical(expected, actual)
self.assertVariableEqual(self.dv.reduce(np.mean, 'x'),
self.v.reduce(np.mean, 'x'))
def test_reduce_keep_attrs(self):
# Test dropped attrs
vm = self.va.mean()
self.assertEqual(len(vm.attrs), 0)
self.assertEqual(vm.attrs, OrderedDict())
示例5: TestDataArray
# 需要导入模块: from xray import Variable [as 别名]
# 或者: from xray.Variable import reduce [as 别名]
#.........这里部分代码省略.........
expected['x2'] = ('x', np.arange(3))
actual = ds['x'] - 1
self.assertDataArrayEqual(expected['x2'], actual)
def test_item_math(self):
self.ds['x'] = ('x', np.array(list('abcdefghij')))
self.assertVariableEqual(self.dv + self.dv[0, 0],
self.dv + self.dv[0, 0].values)
new_data = self.x[0][None, :] + self.x[:, 0][:, None]
self.assertVariableEqual(self.dv[:, 0] + self.dv[0],
Variable(['x', 'y'], new_data))
self.assertVariableEqual(self.dv[0] + self.dv[:, 0],
Variable(['y', 'x'], new_data.T))
def test_inplace_math(self):
x = self.x
v = self.v
a = self.dv
b = a
b += 1
self.assertIs(b, a)
self.assertIs(b.variable, v)
self.assertArrayEqual(b.values, x)
self.assertIs(source_ndarray(b.values), x)
self.assertDatasetIdentical(b.dataset, self.ds)
def test_transpose(self):
self.assertVariableEqual(self.dv.variable.transpose(),
self.dv.transpose())
def test_squeeze(self):
self.assertVariableEqual(self.dv.variable.squeeze(), self.dv.squeeze())
def test_reduce(self):
self.assertVariableEqual(self.dv.reduce(np.mean, 'x'),
self.v.reduce(np.mean, 'x'))
# needs more...
# should check which extra dimensions are dropped
def test_reduce_keep_attrs(self):
# Test dropped attrs
vm = self.va.mean()
self.assertEqual(len(vm.attrs), 0)
self.assertEqual(vm.attrs, OrderedDict())
# Test kept attrs
vm = self.va.mean(keep_attrs=True)
self.assertEqual(len(vm.attrs), len(self.attrs))
self.assertEqual(vm.attrs, self.attrs)
def test_unselect(self):
with self.assertRaisesRegexp(ValueError, 'cannot unselect the name'):
self.dv.unselect('foo')
with self.assertRaisesRegexp(ValueError, 'must be a variable in'):
self.dv.unselect('y')
def test_groupby_iter(self):
for ((act_x, act_dv), (exp_x, exp_ds)) in \
zip(self.dv.groupby('y'), self.ds.groupby('y')):
self.assertEqual(exp_x, act_x)
self.assertDataArrayIdentical(exp_ds['foo'], act_dv)
for ((_, exp_dv), act_dv) in zip(self.dv.groupby('x'), self.dv):
self.assertDataArrayIdentical(exp_dv, act_dv)
def test_groupby(self):
agg_var = Variable(['y'], np.array(['a'] * 9 + ['c'] + ['b'] * 10))