Merge pull request #3125 from nabobalis/1.0

[1.0] 1.0.0rc2

CHANGELOG.rst

@@ -1,4 +1,21 @@
-Sunpy 1.0.0.RC1 (2019-05-21)
+Sunpy v1.0.0rc2 (2019-05-22)
+============================
+
+Features
+--------
+
+- The new function `~sunpy.coordinates.get_horizons_coord` enables querying JPL HORIZONS for the locations of a wide range of solar-system bodies, including spacecraft. (`#3113 <https://github.com/sunpy/sunpy/pull/3113>`__)
+
+
+Bug Fixes
+---------
+
+- Correctly extract observer location from MDI and EIT data (`#3067 <https://github.com/sunpy/sunpy/pull/3067>`__)
+- Fixed bugs related to using `~sunpy.map.GenericMap.plot` and `~sunpy.map.GenericMap.peek` with the ``inline`` Matplotlib backend in Jupyter notebook. (`#3103 <https://github.com/sunpy/sunpy/pull/3103>`__)
+- The `solar_rotate_coordinate` function returns a coordinate that accounts for the location of the new observer. (`#3123 <https://github.com/sunpy/sunpy/pull/3123>`__)
+
+
+Sunpy 1.0.0rc1 (2019-05-21)
 ============================
 
 Backwards Incompatible Changes
@@ -26,7 +43,7 @@ Backwards Incompatible Changes
 - Maps no longer assume that the pixel units are arcseconds if the units aren't
   explicitly set. In addition to this if critical metadata is missing from when
   creating a map, the map will fail to initialize and will raise an error. (`#2847 <https://github.com/sunpy/sunpy/pull/2847>`__)
-- axis_ranges kwarg of `sunpy.visualization.animator.base.ArrayAnimator`, `sunpy.visualization.animator.image.ImageAnimator` and `sunpy.visualization.animator.line.LineAnimator` now must be entered as None, [min, max] or pixel edges of each array element. Previously, pixel centers were expected.  This change removes ambiguity in interpretation and ensures the extent of the plot can always be accurately derived. (`#2867 <https://github.com/sunpy/sunpy/pull/2867>`__)
+- ``axis_ranges`` kwarg of `sunpy.visualization.animator.base.ArrayAnimator`, `sunpy.visualization.animator.image.ImageAnimator` and `sunpy.visualization.animator.line.LineAnimator` now must be entered as None, [min, max] or pixel edges of each array element. Previously, pixel centers were expected.  This change removes ambiguity in interpretation and ensures the extent of the plot can always be accurately derived. (`#2867 <https://github.com/sunpy/sunpy/pull/2867>`__)
 - All keywords have been added (with defaults) to each `~sunpy.net.helioviewer.HelioviewerClient` function.
   This means that there will be some changes to the style of the PNG screenshot that is returned.
   Returns for the JPEG 2000 and the other functions should be the same but not guaranteed. (`#2883 <https://github.com/sunpy/sunpy/pull/2883>`__)

examples/acquiring_data/2011_06_07_sampledata_overview.py

@@ -32,13 +32,12 @@
 aia_cutout03_map = sunpy.map.Map(sample_data.AIA_193_CUTOUT03_IMAGE)
 fig = plt.figure()
 aia_cutout03_map.plot()
-plt.show()
 
 ###############################################################################
 # Let's take a look at the GOES XRS data.
 goes = sunpy.timeseries.TimeSeries(sample_data.GOES_XRS_TIMESERIES)
-goes.peek()
-plt.show()
+fig = plt.figure()
+goes.plot()
 
 ###############################################################################
 # Next let's investigate the AIA full disk images that are available. Please
@@ -55,23 +54,28 @@
 ax = fig.add_subplot(611, projection=aia_131_map)
 aia_131_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_131_map.draw_grid()
+
 ax = fig.add_subplot(612, projection=aia_171_map)
 aia_171_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_171_map.draw_grid()
+
 ax = fig.add_subplot(613, projection=aia_211_map)
 aia_211_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_211_map.draw_grid()
+
 ax = fig.add_subplot(614, projection=aia_335_map)
 aia_335_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_335_map.draw_grid()
+
 ax = fig.add_subplot(615, projection=aia_094_map)
 aia_094_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_094_map.draw_grid()
+
 ax = fig.add_subplot(616, projection=aia_1600_map)
 aia_1600_map.plot(clip_interval=(0.5, 99.9)*u.percent)
 aia_1600_map.draw_grid()
-plt.tight_layout(pad=6.50)
-plt.show()
+
+fig.tight_layout(pad=6.50)
 
 ###############################################################################
 # We also provide a series of AIA cutouts so that you can get a sense of the
@@ -85,30 +89,31 @@
 fig = plt.figure(figsize=(6, 28))
 ax = fig.add_subplot(511, projection=aia_cutout01_map)
 aia_cutout01_map.plot()
+
 ax = fig.add_subplot(512, projection=aia_cutout02_map)
 aia_cutout02_map.plot()
+
 ax = fig.add_subplot(513, projection=aia_cutout03_map)
 aia_cutout03_map.plot()
+
 ax = fig.add_subplot(514, projection=aia_cutout04_map)
 aia_cutout04_map.plot()
+
 ax = fig.add_subplot(515, projection=aia_cutout05_map)
 aia_cutout05_map.plot()
-plt.tight_layout(pad=5.50)
-plt.show()
+
+fig.tight_layout(pad=5.50)
 
 ###############################################################################
 # There are a number of other data sources, such as SWAP.
 swap_map = sunpy.map.Map(sample_data.SWAP_LEVEL1_IMAGE)
 fig = plt.figure()
-ax = plt.subplot(projection=swap_map)
 swap_map.plot()
-plt.show()
 
 ###############################################################################
 # As well as RHESSI.
 rhessi_map = sunpy.map.Map(sample_data.RHESSI_IMAGE)
 fig = plt.figure()
-#ax = plt.subplot(projection=rhessi_map)
-ax = plt.subplot()
 rhessi_map.plot()
+
 plt.show()

examples/acquiring_data/skip_downloading_and_plotting.py

@@ -6,6 +6,8 @@
 In this example, we show how to acquire and plot SOHO/LASCO C3 data using SunPy.
 """
 # Import the required modules.
+import matplotlib.pyplot as plt
+
 from sunpy.net import Fido, attrs
 import sunpy.map
 from sunpy.io.file_tools import read_file
@@ -53,4 +55,7 @@
 
 # Now we can pass in the data and header directly into `sunpy.map.Map`
 lascomap = sunpy.map.Map(data, header)
-lascomap.peek()
+
+fig = plt.figure()
+lascomap.plot()
+plt.show()

examples/acquiring_data/skip_hmi.py

@@ -8,6 +8,7 @@
 """
 # Start by importing the necessary modules.
 import astropy.units as u
+import matplotlib.pyplot as plt
 
 import sunpy.map
 from sunpy.net import Fido, attrs as a
@@ -56,4 +57,7 @@
 ###############################################################################
 # Once we have created our Map, we can plot it quite simply doing:
 
-hmi_map.peek()
+fig = plt.figure()
+hmi_map.plot()
+
+plt.show()

examples/map/composite_map_AIA_HMI.py

@@ -10,6 +10,7 @@
 """
 
 # Start by importing the necessary modules.
+import matplotlib.pyplot as plt
 import sunpy.map
 import sunpy.data.sample
 
@@ -43,4 +44,7 @@
 # present on the AIA image and how they correspond to the line of sight
 # magnetic field.
 
-comp_map.peek()
+fig = plt.figure()
+comp_map.plot()
+
+plt.show()

examples/map/map_from_numpy_array.py

@@ -18,7 +18,7 @@
 ##############################################################################
 # SunPy Maps store 2D data in a numpy array and additional data in a metadata
 # dictionary giving information relating to the data and instrument.
-data = np.random.rand(20,15)
+data = np.random.rand(20, 15)
 header = {'cunit1': 'arcsec', 'cunit2': 'arcsec'}
 manual_map = sunpy.map.Map((data, header))
 
@@ -30,6 +30,8 @@
 print(manual_map.coordinate_system)
 
 ##############################################################################
-# You can quickly plot a map using the peek method:
-manual_map.peek()
+# You can quickly plot a map using the plot method:
+fig = plt.figure()
+manual_map.plot()
+
 plt.show()

examples/map/map_resampling_and_superpixels.py

@@ -36,7 +36,12 @@
 # specifying the dimensions as an Astropy Quantity in pixels:
 dimensions = u.Quantity([40, 40], u.pixel)
 aia_resampled_map = aia_map.resample(dimensions)
-aia_resampled_map.peek(draw_limb=True, draw_grid=True)
+
+fig = plt.figure()
+aia_resampled_map.plot()
+aia_resampled_map.draw_grid()
+aia_resampled_map.draw_limb()
+
 # Note that this uses linear interpolation, you can change this using the method
 # (‘neighbor’, ‘nearest’, ‘linear’ or ‘spline’) keyword argument option.
 
@@ -49,5 +54,10 @@
 # example you can reduce the AIA map resolution by a factor of 16 using:
 dimensions = u.Quantity(aia_map.dimensions) / 16
 aia_superpixel_map = aia_map.superpixel(dimensions)
-aia_superpixel_map.peek(draw_limb=True, draw_grid=True)
+
+fig = plt.figure()
+aia_superpixel_map.plot()
+aia_superpixel_map.draw_grid()
+aia_superpixel_map.draw_limb()
+
 plt.show()

examples/map/map_rotation.py

@@ -33,10 +33,15 @@
 ##############################################################################
 # Maps can also be rotated by using the `~sunpy.map.GenericMap.rotate` method
 # with a specified angle, supplied as an Astropy Quantity with angular units:
-aia_rotated = aia_map.rotate(angle = 30 * u.deg)
-aia_rotated.peek(draw_limb=True, draw_grid=True)
+aia_rotated = aia_map.rotate(angle=30 * u.deg)
+
+plt.figure()
+aia_rotated.plot()
+aia_rotated.draw_limb()
+aia_rotated.draw_grid()
+
 # Or using Radians
-aia_rotated = aia_map.rotate(angle = 0.5 * u.rad)
+aia_rotated = aia_map.rotate(angle=0.5 * u.rad)
 # Note: the data array is expanded so that none of the original data is lost
 # through clipping.
 # Also note that subsequent rotations are not compunded, the map is only rotated

examples/map/maps_example.py

@@ -40,9 +40,9 @@
 # naxis details that correspond to the array used for the data.
 
 ##############################################################################
-# You can quickly plot a map using the peek method:
-
-manual_map.peek()
+# You can quickly plot a map using the plot method:
+fig = plt.figure()
+manual_map.plot()
 
 ##############################################################################
 # SunPy Maps have a number of attributes that can be accessed easily.
@@ -58,7 +58,9 @@
 # returns the location of the given FITS file.
 
 aia_map = sunpy.map.Map(sunpy.data.sample.AIA_171_IMAGE)
-aia_map.peek(draw_limb=True)
+fig = plt.figure()
+aia_map.plot()
+aia_map.draw_limb()
 
 ##############################################################################
 # This has comprehensive metadata:
@@ -88,16 +90,22 @@
 bottom_left = aia_map.bottom_left_coord
 top_right = SkyCoord(0 * u.arcsec, 0 * u.arcsec, frame=aia_map.coordinate_frame)
 aia_submap = aia_map.submap(bottom_left, top_right)
-aia_submap.peek(draw_limb=True)
 
+fig = plt.figure()
+aia_submap.plot()
+aia_submap.draw_limb()
 ##############################################################################
 # Similarly, if you want to reduce the angular resolution of the map you can use
 # the `~sunpy.map.GenericMap.resample` method, specifying the dimensions as an
 # Astropy Quantity in pixels:
 
 dimensions = u.Quantity([50, 50], u.pixel)
 aia_resampled_map = aia_map.resample(dimensions)
-aia_resampled_map.peek(draw_limb=True, draw_grid=True)
+
+fig = plt.figure()
+aia_resampled_map.plot()
+aia_resampled_map.draw_grid()
+aia_resampled_map.draw_limb()
 
 ##############################################################################
 # Similar to resampling you can use the `~sunpy.map.GenericMap.superpixel`
@@ -108,13 +116,20 @@
 
 dimensions = u.Quantity(aia_map.dimensions) / 16
 aia_superpixel_map = aia_map.superpixel(dimensions)
-aia_superpixel_map.peek(draw_limb=True)
+
+fig = plt.figure()
+aia_superpixel_map.plot()
+aia_superpixel_map.draw_limb()
 
 ##############################################################################
 # Maps can also be rotated using the `~sunpy.map.GenericMap.rotate` method:
 
 aia_rotated_submap = aia_submap.rotate(angle=10 * u.deg)
-aia_rotated_submap.peek(draw_limb=True, draw_grid=True)
+
+fig = plt.figure()
+aia_rotated_submap.plot()
+aia_rotated_submap.draw_limb()
+aia_rotated_submap.draw_grid()
 
 # Note: the data array is expanded so that none of the original data is lost
 # through clipping.

examples/map/submaps_and_cropping.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 """
-=========================================
+====================
 Submaps and Cropping
-=========================================
+====================
 
 In this example we demonstrate how to get a submap of a map.
 """
@@ -38,9 +38,13 @@
 # To crop the data you create a submap, specifying the top right and bottom
 # left as SkyCoord objects.
 
-top_right = SkyCoord(0*u.arcsec, -200 * u.arcsec, frame=swap_map.coordinate_frame)
+top_right = SkyCoord(0 * u.arcsec, -200 * u.arcsec, frame=swap_map.coordinate_frame)
 bottom_left = SkyCoord(-900 * u.arcsec, -900 * u.arcsec, frame=swap_map.coordinate_frame)
 swap_submap = swap_map.submap(bottom_left, top_right)
-swap_submap.peek(draw_limb=True, draw_grid=True)
-plt.tight_layout(pad=1.00)
+
+fig = plt.figure()
+swap_submap.plot()
+swap_submap.draw_limb()
+swap_submap.draw_grid()
+
 plt.show()

examples/plotting/aia_example.py

@@ -18,5 +18,6 @@
 ###############################################################################
 # Now we do a quick plot.
 
-aiamap.peek()
+fig = plt.figure()
+aiamap.plot()
 plt.show()

examples/time_series/goes_hek_m25.py

@@ -35,10 +35,13 @@
 ###############################################################################
 # Finally lets plot everything together
 
-goes.peek()
-plt.axvline(parse_time(flares_hek[0].get('event_peaktime')).plot_date)
-plt.axvspan(parse_time(flares_hek[0].get('event_starttime')).plot_date,
-            parse_time(flares_hek[0].get('event_endtime')).plot_date,
-            alpha=0.2, label=flares_hek[0].get('fl_goescls'))
-plt.legend(loc=2)
+fig, ax = plt.subplots()
+goes.plot()
+ax.axvline(parse_time(flares_hek[0].get('event_peaktime')).plot_date)
+ax.axvspan(parse_time(flares_hek[0].get('event_starttime')).plot_date,
+           parse_time(flares_hek[0].get('event_endtime')).plot_date,
+           alpha=0.2, label=flares_hek[0].get('fl_goescls'))
+ax.legend(loc=2)
+ax.set_yscale('log')
+
 plt.show()