Language string | Code string | Query string | URI string | Relevance int64 | Notes string |
|---|---|---|---|---|---|
Python | """Test ``with_redshift`` with the distance off."""
default_cosmo = default_cosmology.get()
z = 15 * cu.redshift
# 1) Default (without specifying the cosmology)
with default_cosmology.set(cosmo):
equivalency = cu.with_redshift(distance=None)
with pytest.raises(u.... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_distance_off | 0 | |
Python | self.send_response(200, 'OK')
self.end_headers() | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#do_OPTIONS | 0 | |
Python | conf.use_internet = False | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#setup_module | 0 | |
Python | state = self.__dict__.copy()
state.pop('_hash', None)
return state | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#__getstate__ | 0 | |
Python | other = self._dimensionally_compatible_unit(other)
if other is NotImplemented:
return NotImplemented
return other.physical_type._dimensional_analysis(self, "__truediv__") | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#__rtruediv__ | 0 | |
Python | def dummy_ufunc(*args, **kwargs):
return np.sqrt(*args, **kwargs)
def register():
return {dummy_ufunc: helper_sqrt}
workers = 8
with concurrent.futures.ThreadPoolExecutor(max_workers=workers) as executor:
for p in range(10000):
helpers = Ufun... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_thread_safety | 0 | |
Python | q1 = np.array([1., 2., 6.]) * u.m
assert np.all(q1.sum() == 9. * u.m)
assert np.all(np.sum(q1) == 9. * u.m)
q2 = np.array([[4., 5., 9.], [1., 1., 1.]]) * u.s
assert np.all(q2.sum(0) == np.array([5., 6., 10.]) * u.s)
assert np.all(np.sum(q2, 0) == np.array([5., 6., 10.]) * u.s) | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_sum | 0 | |
Python | with self._lock:
if value is None:
self.UNSUPPORTED |= {key}
self.pop(key, None)
else:
super().__setitem__(key, value)
self.UNSUPPORTED -= {key} | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#__setitem__ | 0 | |
Python | """
Regression test for issue #11473
"""
q = cls(input)
assert str(q) == expstr
# Deleting whitespaces since repr appears to be adding them for some values
# making the test fail.
assert repr(q).replace(" ", "") == f'<{cls.__name__}{exprepr}>'.replace(" ","") | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_str_repr_angles_nan | 0 | |
Python | self._description = None | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#description | 0 | |
Python | attrib = w.object_attrs(self, self._attr_list)
if 'unit' in attrib:
attrib['unit'] = self.unit.to_string('cds')
with w.tag(self._element_name, attrib=attrib):
if self.description is not None:
w.element('DESCRIPTION', self.description, wrap=True)
if not... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#to_xml | 0 | |
Python | with fits.open(self.data('comp.fits'),
disable_image_compression=True) as hdul:
# The compressed image HDU should show up as a BinTableHDU, but
# *not* a CompImageHDU
assert isinstance(hdul[1], fits.BinTableHDU)
assert not isinstance(hdul[1], fits.C... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_disable_image_compression | 0 | |
Python | hdu = ImageHDU(data=dask_array_in_mem)
assert isinstance(hdu.data, da.Array) | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_construct_image_hdu | 0 | |
Python | """
Adjust or skip data entries if a row is inconsistent with the header.
The default implementation does no adjustment, and hence will always trigger
an exception in read() any time the number of data entries does not match
the header.
Note that this will *not* be called if th... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#inconsistent_handler | 0 | |
Python | """Test issue in #2997"""
mask_b = np.array([True, True, False, False])
for select in (mask_b, slice(0, 2)):
t = Table(masked=True)
t['a'] = Column([1, 2, 3, 4])
t['b'] = MaskedColumn([11, 22, 33, 44], mask=mask_b)
t['c'] = MaskedColumn([111, 222, 333, 444], mask=[True, False, Tr... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_setting_from_masked_column | 0 | |
Python | """
Appropriate errors get raised.
"""
# Bad column name as string
with pytest.raises(ValueError):
T1.group_by('f')
# Bad column names in list
with pytest.raises(ValueError):
T1.group_by(['f', 'g'])
# Wrong length array
with pytest.raises(ValueError):
T1.group_b... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_group_by_errors | 0 | |
Python | """
Function corresponding to '&' operation.
Parameters
----------
left, right : `astropy.modeling.Model` or ndarray
If input is of an array, it is the output of `coord_matrix`.
Returns
-------
result : ndarray
Result from this operation.
"""
noutp = _compute_n_out... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#_cstack | 1 | |
Python | """
Tests that compound evaluate function produces the same
result as the models fix_inputs operator is applied
when using the keyword
"""
y, x = np.mgrid[:10, :10]
model_params = [3, 0, 0.1, 1, 0.5, 0]
model = Gaussian2D(1, 2, 0, 0.5)
compound = fix_inputs(model, {"x": x + 5})
as... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_compound_evaluate_fix_inputs_by_keyword | 0 | |
Python | if not HAS_SCIPY and model['class'] in SCIPY_MODELS:
pytest.skip()
m = model['class'](**model['parameters'])
for args in model['evaluation']:
if len(args) == 2:
kwargs = dict(zip(('x', 'y'), args))
else:
kwargs = dict(zip(('x', 'y', 'z'), args))
if kwa... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_models_evaluate_without_units | 0 | |
Python | g = Gaussian1D(
amplitude=[1 * u.J, 2. * u.J],
mean=[1 * u.m, 5000 * u.AA],
stddev=[0.1 * u.m, 100 * u.AA],
n_models=2)
assert_quantity_allclose(g(1.01 * u.m), [0.99501248, 0.] * u.J)
assert_quantity_allclose(
g(u.Quantity([1.01 * u.m, 5010 * u.AA])), [0.99501248, 1.99002... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_gaussian1d_n_models | 0 | |
Python | self.key = 'test'
self.val = 'value' | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#setup | 0 | |
Python | if instance is None:
# This is an unbound descriptor on the class
raise ValueError('cannot set unbound descriptor')
setattr(instance._parent, self.attr, value) | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#__set__ | 0 | |
Python | u, c = next(valid_urls)
f = download_file(u, cache=True)
bf = os.path.abspath(os.path.join(os.path.dirname(f), "bogus"))
with open(bf, "wt") as f:
f.write("bogus file that exists")
with pytest.raises(CacheDamaged) as e:
check_download_cache()
assert bf in e.value.bad_files
clear_... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#test_check_download_cache_finds_bogus_subentries | 0 | |
Python | np_func = getattr(np, nanfuncname[3:])
fill_value = _nanfunc_fill_values.get(nanfuncname, None)
def nanfunc(a, *args, **kwargs):
from astropy.utils.masked import Masked
a, mask = Masked._get_data_and_mask(a)
if issubclass(a.dtype.type, np.inexact):
nans = np.isnan(a)
... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#masked_nanfunc | 0 | |
Python | """
Time as a decimal year, with integer values corresponding to midnight
of the first day of each year. For example 2000.5 corresponds to the
ISO time '2000-07-02 00:00:00'.
"""
name = 'decimalyear'
def set_jds(self, val1, val2):
self._check_scale(self._scale) # Validate scale.
... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#TimeDecimalYear | 0 | |
Python | @abc.abstractmethod
def __init__(self, t, y, dy=None):
pass
@classmethod
def from_timeseries(cls, timeseries, signal_column_name=None, uncertainty=None, **kwargs):
"""
Initialize a periodogram from a time series object.
If a binned time series is passed, the time at the cen... | Modeling's `separability_matrix` does not compute separability correctly for nested CompoundModels
Consider the following model:
```python
from astropy.modeling import models as m
from astropy.modeling.separable import separability_matrix
cm = m.Linear1D(10) & m.Linear1D(5)
```
It's separability matrix as y... | astropy_d16bfe05a744909de4b27f5875fe0d4ed41ce607#BasePeriodogram | 0 | |
Python | r"""
For a WCS returns `False` if square image (detector) pixels stay square
when projected onto the "plane of intermediate world coordinates"
as defined in
`Greisen & Calabretta 2002, A&A, 395, 1061 <https://ui.adsabs.harvard.edu/abs/2002A%26A...395.1061G>`_.
It will return `True` if transformation... | TimeSeries: misleading exception when required column check fails.
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so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#is_proj_plane_distorted | 0 | |
Python | from copy import deepcopy
new_copy = self.__class__()
new_copy.naxis = deepcopy(self.naxis, memo)
WCSBase.__init__(new_copy, deepcopy(self.sip, memo),
(deepcopy(self.cpdis1, memo),
deepcopy(self.cpdis2, memo)),
deepcopy... | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#__deepcopy__ | 0 | |
Python | """The Cosmology class as a :func:`pytest.fixture`."""
return self.cls | TimeSeries: misleading exception when required column check fails.
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so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#cosmo_cls | 0 | |
Python | return "" | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#_receive_notification | 0 | |
Python | out = np.nanargmax(self.q)
expected = np.nanargmax(self.q.value)
assert out == expected | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#test_nanargmax | 0 | |
Python | q = u.Quantity(1.0, u.meter)
# Manually turn this on to simulate what might happen in a subclass
q._include_easy_conversion_members = True
q.foo = 42
attrs = dir(q)
assert 'centimeter' in attrs
assert 'cm' in attrs
assert 'parsec' in attrs
assert 'foo' in attrs
assert 'to' in attrs
... | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#test_implicit_conversion_autocomplete | 0 | |
Python | return cls | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#__new__ | 0 | |
Python | """
Convert to a quantity in the specified unit.
Parameters
----------
unit : unit-like
The unit to convert to.
equivalencies : list of tuple
A list of equivalence pairs to try if the units are not directly
convertible (see :ref:`astropy:unit_... | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#to | 0 | |
Python | """
Set format and round trip through a format that shares out_subfmt
"""
t = Time('+02000-02-03', format='fits', out_subfmt='date_hms', precision=5)
tc = t.copy()
t.format = 'isot'
assert t.precision == 5
assert t.out_subfmt == 'date_hms'
assert t.value == '2000-02-03T00:00:00.00000'
... | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#test_set_format_shares_subfmt | 0 | |
Python | """Check broadcasting rules in interactions with Quantity."""
t0 = TimeDelta(np.arange(12.).reshape(4, 3), format='sec')
with pytest.raises(ValueError):
t0 + np.arange(4.) * u.s | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#test_invalid_quantity_broadcast | 0 | |
Python | """
Determines the constellation(s) a given coordinate object contains.
Parameters
----------
coord : coordinate-like
The object to determine the constellation of.
short_name : bool
If True, the returned names are the IAU-sanctioned abbreviated
names. Otherwise, full names ... | TimeSeries: misleading exception when required column check fails.
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so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#get_constellation | 0 | |
Python | if not self._required_columns_enabled:
return
if self._required_columns is not None:
if self._required_columns_relax:
required_columns = self._required_columns[:len(self.colnames)]
else:
required_columns = self._required_columns
... | TimeSeries: misleading exception when required column check fails.
<!-- This comments are hidden when you submit the issue,
so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#_check_required_columns | 1 | |
Python | if data.imag == 0.0:
data = f'{data.real!r}'
elif data.real == 0.0:
data = f'{data.imag!r}j'
elif data.imag > 0:
data = f'{data.real!r}+{data.imag!r}j'
else:
data = f'{data.real!r}{data.imag!r}j'
return self.represent_scalar('tag:yaml.org,2002:python/complex', data) | TimeSeries: misleading exception when required column check fails.
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so you do not need to remove them! -->
<!-- Please be sure to check out our contributing guidelines,
https://github.com/astropy/astropy/blob/main/CONTRIBUTING.md .
Please be sure to check ou... | astropy_298ccb478e6bf092953bca67a3d29dc6c35f6752#_complex_representer | 0 | |
Python | """
Whether or not the header has been modified; this is a property so that
it can also check each card for modifications--cards may have been
modified directly without the header containing it otherwise knowing.
"""
modified_cards = any(c._modified for c in self._cards)
... | TimeSeries: misleading exception when required column check fails.
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Python | """
Read in data.
Parameters
----------
cls : class
*args
The arguments passed to this method depend on the format.
format : str or None
cache : bool
Whether to cache the results of reading in the data.
**kwargs
The arg... | TimeSeries: misleading exception when required column check fails.
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Python | example_qdp = """
! Initial comment line 1
! Initial comment line 2
READ TERR 1
READ SERR 3
! Table 0 comment
!a a(pos) a(neg) b c ce d
53000.5 0.25 -0.5 1 1.5 3.5 2
54000.5 1.25 -1.5 2 2.5 4.5 3
NO NO NO NO NO
! Table 1 comme... | TimeSeries: misleading exception when required column check fails.
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Python | object_state = list(super().__reduce__())
object_state[2] = (object_state[2], self.__dict__)
return tuple(object_state) | TimeSeries: misleading exception when required column check fails.
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Python | """
Get groups for ``table`` on specified ``keys``.
Parameters
----------
table : `Table`
Table to group
keys : str, list of str, `Table`, or Numpy array
Grouping key specifier
Returns
-------
grouped_table : Table object with groups attr set accordingly
"""
fro... | TimeSeries: misleading exception when required column check fails.
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Python | for param in self.param_names:
if getattr(self, param).unit is not None:
return True
else:
return False | TimeSeries: misleading exception when required column check fails.
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Python | ls = iers.LeapSeconds.from_leap_seconds_list(file)
assert ls.expires == Time('2020-06-28', scale='tai')
assert ls['mjd'][0] == 41317
assert ls['tai_utc'][0] == 10
assert ls['mjd'][-1] == 57754
assert ls['tai_utc'][-1] == 37
self.verify_day_month_year(ls) | TimeSeries: misleading exception when required column check fails.
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Python | """
Raised if units are missing or invalid.
""" | TimeSeries: misleading exception when required column check fails.
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Python | _required_columns = None
_required_columns_enabled = True
# If _required_column_relax is True, we don't require the columns to be
# present but we do require them to be the correct ones IF present. Note
# that this is a temporary state - as soon as the required columns
# are all present, we toggle ... | TimeSeries: misleading exception when required column check fails.
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Python | def __getitem__(self, item):
"""
Retrieve Table row's indices by value slice.
Parameters
----------
item : column element, list, ndarray, slice or tuple
Can be a value of the table primary index, a list/ndarray
of such values, or a value slice (both... | TimeSeries: misleading exception when required column check fails.
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Python | string = unit_format.Generic.to_string(self)
return f'Unit("{string}")' | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | s1 = PhysicsSphericalRepresentation(phi=[8, 9] * u.hourangle,
theta=[5, 6] * u.deg,
r=[10, 20] * u.kpc)
with pytest.raises(AttributeError):
s1.phi = 1. * u.deg
with pytest.raises(AttributeError):
... | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | """
The data in this frame as an `~astropy.coordinates.EarthLocation` class.
"""
from astropy.coordinates.earth import EarthLocation
cart = self.represent_as(CartesianRepresentation)
return EarthLocation(x=cart.x, y=cart.y, z=cart.z) | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | """Compute the polar motion p-matrix at the given time.
If the nutation-precession matrix is already known, it should be passed in,
as this is by far the most expensive calculation.
"""
xp, yp = get_polar_motion(time)
sp = erfa.sp00(*get_jd12(time, 'tt'))
pmmat = erfa.pom00(xp, yp, sp)
# n... | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | rbpn = erfa.pnm06a(*get_jd12(tete_coo.obstime, 'tt'))
newrepr = tete_coo.cartesian.transform(matrix_transpose(rbpn))
# We now have a GCRS vector for the input location and obstime.
# Turn it into a GCRS frame instance.
loc_gcrs = get_location_gcrs(tete_coo.location, tete_coo.obstime,
... | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | tete_coo2 = tete_coo.transform_to(TETE(obstime=itrs_frame.obstime,
location=EARTH_CENTER))
# now get the pmatrix
pmat = tete_to_itrs_mat(itrs_frame.obstime)
crepr = tete_coo2.cartesian.transform(pmat)
return itrs_frame.realize_frame(crepr) | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | pmat = tete_to_itrs_mat(itrs_coo.obstime)
newrepr = itrs_coo.cartesian.transform(matrix_transpose(pmat))
tete = TETE(newrepr, obstime=itrs_coo.obstime)
# now do any needed offsets (no-op if same obstime)
return tete.transform_to(tete_frame) | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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Python | pmat = gcrs_to_cirs_mat(cirs_coo.obstime)
newrepr = cirs_coo.cartesian.transform(matrix_transpose(pmat))
# We now have a GCRS vector for the input location and obstime.
# Turn it into a GCRS frame instance.
loc_gcrs = get_location_gcrs(cirs_coo.location, cirs_coo.obstime,
... | A direct approach to ITRS to Observed transformations that stays within the ITRS.
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