def JI_contains_full_disk(smap):
"""
Copied from Jack Ireland's local implementation:
https://github.com/wafels/sunpy/blob/faster_full_disk/sunpy/map/maputils.py#L127
"""
# Calculate all the edge pixels
top_, bottom, left_hand_side, right_hand_side = map_edges(smap)
def _xy(ep):
x = [p[0] for p in ep] * u.pix
y = [p[1] for p in ep] * u.pix
return x, y
x, y = _xy(top_)
horizontal1 = smap.pixel_to_world(x, y)
x, y = _xy(bottom)
horizontal2 = smap.pixel_to_world(x, y)
x, y = _xy(left_hand_side)
vertical1 = smap.pixel_to_world(x, y)
x, y = _xy(right_hand_side)
vertical2 = smap.pixel_to_world(x, y)
radius = smap.rsun_obs
# Determine the top and bottom edges of the map
top = None
bot = None
if np.all(horizontal1.Ty > radius):
top = horizontal1
elif np.all(horizontal1.Ty < -radius):
bot = horizontal1
if np.all(horizontal2.Ty > radius):
top = horizontal2
elif np.all(horizontal2.Ty < -radius):
bot = horizontal2
# If either the top edge
if top is None or bot is None:
return False
lhs = None
rhs = None
if np.all(vertical1.Tx > radius):
rhs = vertical1
elif np.all(vertical1.Tx < -radius):
lhs = vertical1
if np.all(vertical2.Tx > radius):
rhs = vertical2
elif np.all(vertical2.Tx < -radius):
lhs = vertical2
if lhs is None or rhs is None:
return False
return np.all(top.Ty > radius) and np.all(bot.Ty < -radius) and np.all(lhs.Tx < -radius) and np.all(rhs.Tx > radius)
def differential_rotate(smap, observer=None, time=None, **diff_rot_kwargs):
"""
Warp a `~sunpy.map.GenericMap` to take into account both solar differential
rotation and the changing location of the observer.
.. warning::
This function, while greatly improved in 1.0, is still experimental.
Please validate that it gives you results you expect and report any
discrepancies on the SunPy issue tracker.
The function transforms the input map data pixels by first rotating each
pixel according to solar differential rotation. The amount of solar
differential applied is calculated by the time difference between the
observation time of map and the new observation time, as specified by either the
"time" keyword or the "obstime" property of the "observer" keyword.
The location of the rotated pixels are then transformed to locations on the Sun
as seen from the new observer position. This is desirable since in most cases
the observer does not remain at a fixed position in space. If
the "time" keyword is used then the new observer position is assumed to
be based on the location of the Earth. If the "observer" keyword is used then
this defines the new observer position.
The function works with full disk maps and maps that contain portions of the
solar disk (maps that are entirely off-disk will raise an error). When the
input map contains the full disk, the output map has the same dimensions as
the input map. When the input map images only part of the solar disk, only
the on-disk pixels are differentially rotated and the output map can have
a different dimensions compared to the input map. In this case any off-disk
emission shown in the input map is not included in the output map.
Parameters
----------
smap : `~sunpy.map.GenericMap`
Original map that we want to transform.
observer : `~astropy.coordinates.BaseCoordinateFrame`, `~astropy.coordinates.SkyCoord`, `None`, optional
The location of the new observer.
Instruments in Earth orbit can be approximated by using the position
of the Earth at the observation time of the new observer.
time : sunpy-compatible time, `~astropy.time.TimeDelta`, `~astropy.units.Quantity`, `None`, optional
Used to define the duration over which the amount of solar rotation is
calculated. If 'time' is an `~astropy.time.Time` then the time interval
is difference between 'time' and the map observation time. If 'time' is
`~astropy.time.TimeDelta` or `~astropy.units.Quantity` then the calculation
is "initial_obstime + time".
Returns
-------
`~sunpy.map.GenericMap`
A map with the result of applying solar differential rotation to the
input map.
"""
# If the entire map is off-disk, return an error so the user is aware.
if is_all_off_disk(smap):
raise ValueError(
"The entire map is off disk. No data to differentially rotate.")
# Get the new observer
new_observer = _get_new_observer(smap.date, observer, time)
# Only this function needs scikit image
from skimage import transform
# Check whether the input contains the full disk of the Sun
is_sub_full_disk = not contains_full_disk(smap)
if is_sub_full_disk:
# Find the minimal submap of the input map that includes all the
# on disk pixels. This is required in order to calculate how
# much to pad the output (solar-differentially rotated) data array by
# compared to the input map.
# The amount of padding is dependent on the amount of solar differential
# rotation and where the on-disk pixels are (since these pixels are the only ones
# subject to solar differential rotation).
if not is_all_on_disk(smap):
# Get the bottom left and top right coordinates that are the
# vertices that define a box that encloses the on disk pixels
bottom_left, top_right = on_disk_bounding_coordinates(smap)
# Create a submap that excludes the off disk emission that does
# not need to be rotated.
smap = smap.submap(bottom_left, top_right=top_right)
bottom_left = smap.bottom_left_coord
top_right = smap.top_right_coord
# Get the edges of the minimal submap that contains all the on-disk pixels.
edges = map_edges(smap)
# Calculate where the output array moves to.
# Rotate the top and bottom edges
rotated_top = _rotate_submap_edge(smap,
edges[0],
observer=new_observer,
**diff_rot_kwargs)
rotated_bottom = _rotate_submap_edge(smap,
edges[1],
observer=new_observer,
**diff_rot_kwargs)
# Rotate the left and right hand edges
rotated_lhs = _rotate_submap_edge(smap,
edges[2],
observer=new_observer,
**diff_rot_kwargs)
rotated_rhs = _rotate_submap_edge(smap,
edges[3],
observer=new_observer,
**diff_rot_kwargs)
# Calculate the bounding box of the rotated map
rotated_bl, rotated_tr = _get_bounding_coordinates(
[rotated_top, rotated_bottom, rotated_lhs, rotated_rhs])
# Calculate the maximum distance in pixels the map has moved by comparing
# how far the original and rotated bounding boxes have moved.
diff_x = [(np.abs(rotated_bl.Tx - bottom_left.Tx)).value,
(np.abs(rotated_tr.Tx - top_right.Tx)).value]
deltax = int(np.ceil(np.max(diff_x) / smap.scale.axis1).value)
diff_y = [(np.abs(rotated_bl.Ty - bottom_left.Ty)).value,
(np.abs(rotated_tr.Ty - top_right.Ty)).value]
deltay = int(np.ceil(np.max(diff_y) / smap.scale.axis2).value)
# Create a new `smap` with the padding around it
padded_data = np.pad(smap.data, ((deltay, deltay), (deltax, deltax)),
'constant',
constant_values=0)
padded_meta = deepcopy(smap.meta)
padded_meta['naxis2'], padded_meta['naxis1'] = smap.data.shape
padded_meta['crpix1'] += deltax
padded_meta['crpix2'] += deltay
# Create the padded map that will be used to create the rotated map.
smap = smap._new_instance(padded_data, padded_meta)
# Check for masked maps
if smap.mask is not None:
smap_data = np.ma.array(smap.data, mask=smap.mask)
else:
smap_data = smap.data
# Create the arguments for the warp function.
warp_args = {'smap': smap, 'new_observer': new_observer}
warp_args.update(diff_rot_kwargs)
# Apply solar differential rotation as a scikit-image warp
out_data = transform.warp(smap_data,
inverse_map=_warp_sun_coordinates,
map_args=warp_args,
preserve_range=True,
cval=np.nan)
# Update the meta information with the new date and time.
out_meta = deepcopy(smap.meta)
if out_meta.get('date_obs', False):
del out_meta['date_obs']
out_meta['date-obs'] = new_observer.obstime.strftime(
"%Y-%m-%dT%H:%M:%S.%f")
# Need to update the observer location for the output map.
# Remove all the possible observer keys
all_keys = expand_list(
[e[0] for e in smap._supported_observer_coordinates])
for key in all_keys:
out_meta.pop(key)
# Add a new HGS observer
out_meta.update(get_observer_meta(new_observer,
out_meta['rsun_ref'] * u.m))
if is_sub_full_disk:
# Define a new reference pixel and the value at the reference pixel.
# Note that according to the FITS convention the first pixel in the
# image is at (1.0, 1.0).
center_rotated = solar_rotate_coordinate(smap.center,
observer=new_observer,
**diff_rot_kwargs)
out_meta['crval1'] = center_rotated.Tx.value
out_meta['crval2'] = center_rotated.Ty.value
out_meta['crpix1'] = 1 + smap.data.shape[1]/2.0 + \
((center_rotated.Tx - smap.center.Tx)/smap.scale.axis1).value
out_meta['crpix2'] = 1 + smap.data.shape[0]/2.0 + \
((center_rotated.Ty - smap.center.Ty)/smap.scale.axis2).value
return smap._new_instance(out_data,
out_meta).submap(rotated_bl,
top_right=rotated_tr)
else:
return smap._new_instance(out_data, out_meta)
