adds gallery example

examples/map/track_and_coalign_region.py

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+"""
+=========================================
+Tracking and Co-aligning an Active Region
+=========================================
+
+This example demonstrates how to track a particular region as a function of time,
+create a cutout around that region, and align it at each time step to get an aligned datacube.
+"""
+
+import matplotlib.pyplot as plt
+
+import astropy.units as u
+from astropy.coordinates import SkyCoord
+
+import sunpy.map
+from sunpy.coordinates import propagate_with_solar_surface
+from sunpy.net import Fido
+from sunpy.net import attrs as a
+
+###############################################################################
+# `sunpy.net.Fido` is the primary interface for searching and downloading data.
+# The following code performs a search for solar data using the Fido client from the sunpy.net module.
+query = Fido.search(a.Time('2012/3/4', '2012/3/5'),
+                    a.Instrument.aia,
+                    a.Wavelength(171*u.angstrom),
+                    a.Sample(360*u.minute))
+print(query)
+
+###############################################################################
+# Let's inspect the results and download the files.
+files = Fido.fetch(query)
+print(files)
+
+###############################################################################
+# Create a sequence of maps from the downloaded files.
+
+m_seq = sunpy.map.Map(files, sequence=True)
+
+# Plot the sequence of maps.
+
+
+fig = plt.figure(figsize=(16, 4))
+for i, m in enumerate(m_seq):
+    ax = fig.add_subplot(1, len(m_seq), i+1, projection=m)
+    m.plot(axes=ax)
+
+# The above images are the result of the query: 4 images at 6-hour intervals.
+
+###############################################################################
+# Define the region of interest using a SkyCoord.
+
+
+corner = SkyCoord(Tx=-375*u.arcsec, Ty=0*u.arcsec, frame=m_seq[0].coordinate_frame)
+print(m_seq[0].world_to_pixel(corner))
+
+# Create a cutout around the defined region.
+m_cutout = m_seq[0].submap(corner, width=500*u.arcsec, height=500*u.arcsec)
+
+# Plot the cutout region.
+fig = plt.figure()
+ax = fig.add_subplot(projection=m_cutout)
+m_cutout.plot(axes=ax)
+plt.show()
+
+###############################################################################
+# Track and co-align the region across the sequence of maps using solar rotation.
+
+
+fig = plt.figure(figsize=(16, 4))
+for i, m in enumerate(m_seq):
+    ax = fig.add_subplot(1, len(m_seq), i+1, projection=m)
+    m.plot(axes=ax)
+    with propagate_with_solar_surface():
+        blc = m_cutout.bottom_left_coord.transform_to(m.coordinate_frame)
+        trc = m_cutout.top_right_coord.transform_to(m.coordinate_frame)
+        m.draw_quadrangle(blc, top_right=trc)
+
+###############################################################################
+# Aligns all images to the World Coordinate System (WCS) of the cutout.
+# `propagate_with_solar_surface` is a context manager that adjusts for solar rotation,
+# ensuring that regions on the Sun's surface remain in the correct position as the Sun rotates.
+
+with propagate_with_solar_surface():
+    m_seq_aligned = sunpy.map.Map([m.reproject_to(m_cutout.wcs) for m in m_seq], sequence=True)
+
+# `reproject_to` reprojects each map in the sequence to the WCS of the cutout map,
+# aligning all images to the same reference frame.
+
+# Plot the aligned sequence of maps.
+fig = plt.figure(figsize=(16, 4))
+for i, m in enumerate(m_seq_aligned):
+    ax = fig.add_subplot(1, len(m_seq_aligned), i+1, projection=m)
+    m.plot(axes=ax, cmap='sdoaia171', title=m_seq[i].date)
+
+# This code aligns a sequence of solar images to a common reference frame, taking into account solar rotation,
+# and then plots them side by side in a single figure. Each subplot shows one map from the aligned sequence.