def index(self):
"""
The time index of the data.
"""
warn_deprecated(
'.index is deprecatd. Use .time instead to get an astropy.time.Time object, '
'or ts.to_dataframe().index to get a pandas DateTimeIndex.')
return self.to_dataframe().index
def _get_transform_method(method, use_scipy):
# This is re-used in affine_transform and GenericMap.rotate
supported_methods = {'scipy', 'skimage'}
if method not in supported_methods:
raise ValueError(f'Method {method} not in supported methods: {supported_methods}')
if use_scipy is not None:
warn_deprecated("The 'use_scipy' argument is deprecated. "
"Specify the rotation method to the 'method' "
"keyword argument instead.")
if use_scipy is True and method != 'scipy':
warn_user(f"Using scipy instead of {method} for rotation.")
method = 'scipy'
if method == 'skimage':
try:
import skimage # NoQA
except ImportError:
warn_user("scikit-image could not be imported. Image rotation will use scipy.")
method = 'scipy'
return method
def _get_transform_method(method, use_scipy):
# This is re-used in affine_transform and GenericMap.rotate
if method not in _rotation_registry:
raise ValueError(f'Method {method} not in supported methods: '
f'{_rotation_registry.keys()}')
if use_scipy is not None:
warn_deprecated("The 'use_scipy' argument is deprecated. "
"Specify the rotation method to the 'method' "
"keyword argument instead.")
if use_scipy is True and method != 'scipy':
warn_user(f"Using scipy instead of {method} for rotation.")
method = 'scipy'
if method == 'scikit-image':
try:
import skimage # NoQA
except ImportError:
raise ImportError(
"scikit-image must be installed to be usable for rotation.")
return method
from sunpy.util.exceptions import warn_deprecated
from . import _fits
from ._fits import * # NoQA
__doc__ = _fits.__doc__
__all__ = _fits.__all__
warn_deprecated("The `sunpy.io.fits` module is deprecated, as it was designed "
"for internal use. Use the `astropy.fits.io` module instead "
"for more generic functionality to read FITS files.")
def resample(orig, dimensions, method='linear', center=False, minusone=False):
"""
Returns a new `numpy.ndarray` that has been resampled up or down.
Arbitrary resampling of source array to new dimension sizes.
Currently only supports maintaining the same number of dimensions.
To use 1-D arrays, first promote them to shape (x,1).
Uses the same parameters and creates the same co-ordinate lookup points
as IDL's ``congrid`` routine (which apparently originally came from a
VAX/VMS routine of the same name.)
Parameters
----------
orig : `numpy.ndarray`
Original input array.
dimensions : `tuple`
Dimensions that new `numpy.ndarray` should have.
method : {``"neighbor"``, ``"nearest"``, ``"linear"``, ``"spline"``}, optional
Method to use for resampling interpolation.
* nearest and linear - Uses "n x 1D" interpolations calculated by
`scipy.interpolate.interp1d`.
* spline - Uses `scipy.ndimage.map_coordinates`
center : `bool`, optional
If `False` (default) the interpolation points are at the front edge of the bin.
If `True`, interpolation points are at the centers of the bins
minusone : `bool`, optional
For ``orig.shape = (i,j)`` & new dimensions ``= (x,y)``, if set to `False`
(default) ``orig`` is resampled by factors of ``(i/x) * (j/y)``,
otherwise ``orig`` is resampled by ``(i-1)/(x-1) * (j-1)/(y-1)``.
This prevents extrapolation one element beyond bounds of input array.
Returns
-------
out : `numpy.ndarray`
A new `numpy.ndarray` which has been resampled to the desired dimensions.
References
----------
https://scipy-cookbook.readthedocs.io/items/Rebinning.html
"""
# Verify that number dimensions requested matches original shape
if len(dimensions) != orig.ndim:
raise UnequalNumDimensions("Number of dimensions must remain the same "
"when calling resample.")
# TODO: Will this be okay for integer (e.g. JPEG 2000) data?
if orig.dtype not in [np.float64, np.float32]:
orig = orig.astype(np.float64)
dimensions = np.asarray(dimensions, dtype=np.float64)
m1 = np.array(minusone, dtype=np.int64) # array(0) or array(1)
offset = np.float64(center * 0.5) # float64(0.) or float64(0.5)
# Resample data
if method == 'neighbor':
warn_deprecated(
'Using "neighbor" as a method for resampling is deprecated. '
'Use "nearest" instead.')
data = _resample_neighbor(orig, dimensions, offset, m1)
elif method in ['nearest', 'linear']:
data = _resample_nearest_linear(orig, dimensions, method, offset, m1)
elif method == 'spline':
data = _resample_spline(orig, dimensions, offset, m1)
else:
raise UnrecognizedInterpolationMethod("Unrecognized interpolation "
"method requested.")
return data
def search(self, *args, **kwargs):
"""
The simple interface to query the wsdl service.
Used to utilize the service's TimeQuery() method, this is a simple
interface between the sunpy module library and the web-service's API.
.. note::
By default the maximum records returned by the service are limited to 500.
To obtain more results ``a.helio.MaxRecords`` must be set to a higher value.
Examples
--------
>>> from sunpy.net.helio import attrs as ha
>>> from sunpy.net import attrs as a, Fido
>>> timerange = a.Time('2005/01/03', '2005/12/03')
>>> res = Fido.search(timerange, ha.MaxRecords(10),
... ha.TableName('rhessi_hxr_flare')) # doctest: +REMOTE_DATA
>>> res #doctest: +REMOTE_DATA
<sunpy.net.fido_factory.UnifiedResponse object at ...>
Results from 1 Provider:
<BLANKLINE>
10 Results from the HECClient:
hec_id time_start time_peak ... energy_kev flare_number
------ ------------------- ------------------- ... ---------- ------------
31463 2005-01-03T01:37:36 2005-01-03T01:37:54 ... 6 5010320
31464 2005-01-03T01:51:36 2005-01-03T01:59:18 ... 12 5010301
31465 2005-01-03T03:26:28 2005-01-03T03:42:50 ... 6 5010332
31466 2005-01-03T03:46:04 2005-01-03T04:07:10 ... 12 5010302
31467 2005-01-03T05:00:24 2005-01-03T05:00:30 ... 6 5010313
31468 2005-01-03T06:40:48 2005-01-03T06:42:46 ... 6 5010314
31469 2005-01-03T08:27:56 2005-01-03T08:28:26 ... 6 5010334
31470 2005-01-03T09:31:00 2005-01-03T09:33:34 ... 6 5010322
31471 2005-01-03T09:34:52 2005-01-03T09:59:46 ... 6 5010336
31472 2005-01-03T11:06:48 2005-01-03T11:07:18 ... 12 5010304
<BLANKLINE>
<BLANKLINE>
"""
qrdict = {}
for elem in args:
if isinstance(elem, a.Time):
qrdict['Time'] = elem
elif isinstance(elem, ha.MaxRecords):
qrdict['max_records'] = elem.value
elif isinstance(elem, ha.TableName):
qrdict['table_name'] = elem.value
else:
raise ValueError(
f"{elem.__class__.__name__} should be a ``attrs.Time``, ``attrs.hek.MaxRecords`` or ``attrs.hek.TableName`` attribute."
)
qrdict.update(kwargs)
table = qrdict.get('table_name', None)
if table:
if isinstance(table, bytes):
warn_deprecated(
'type `bytes` for table_name is deprecated, use `str` instead.'
)
table = str.encode(table)
start_time = qrdict['Time'].start
end_time = qrdict['Time'].end
max_records = qrdict.get('max_records', 500)
while table is None:
table = self.select_table()
start_time = parse_time(start_time)
end_time = parse_time(end_time)
results = self.hec_client.service.TimeQuery(STARTTIME=start_time.isot,
ENDTIME=end_time.isot,
FROM=table,
MAXRECORDS=max_records)
results = votable_handler(etree.tostring(results))
table = HECResponse(results.to_table(), client=self)
if len(table) == max_records == 500:
warn_user(
"Number of results is the same as the default `max_records` of 500. "
"It is possible your query has been truncated. "
"If you want to change this, set `a.helio.MaxRecords` to a higher value."
)
return table
def test_warnings():
# Ensure that our warning trickery dosen't stop pytest.warns working
with pytest.warns(SunpyDeprecationWarning):
warn_deprecated("Hello")