We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Solar Cycle Gallery example out of date
The example includes the following text 

> For this example we will use the SunPy sample data, if you want the current data, delete the argument to the create function. i.e. noaa = lc.NOAAIndicesLightCurve.create()

This text is inline and therefore not checked during build so was not caught. This should be fixed and this behavior should be discouraged.

--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `examples/plotting/solar_cycle_example.py`
Content:
```
1 """
2 ===============
3 The Solar Cycle
4 ===============
5 
6 This example shows the current and possible next solar cycle.
7 """
8 from __future__ import print_function, division
9 
10 import datetime
11 import matplotlib.pyplot as plt
12 
13 import sunpy.timeseries as ts
14 from sunpy.data.sample import NOAAINDICES_TIMESERIES, NOAAPREDICT_TIMESERIES
15 
16 ###############################################################################
17 # For this example we will use the SunPy sample data, if you want the current
18 # data, delete the argument to the ``create`` function. i.e.
19 # ``noaa = lc.NOAAIndicesLightCurve.create()``
20 
21 noaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')
22 noaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')
23 
24 ###############################################################################
25 # Next lets grab the data again to create a new data structure that we will
26 # shift by 12 years to simulate the next solar cycle. We will truncate the
27 # data to only plot what is necessary.
28 
29 noaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')
30 noaa2.data = noaa2.data.shift(2, freq=datetime.timedelta(days=365*12))
31 noaa2 = noaa2.truncate('2021/04/01', '2030/01/01')
32 
33 ###############################################################################
34 # Finally lets plot everything together with some arbitrary range for the
35 # strength of the next solar cycle.
36 
37 plt.plot(noaa.data.index, noaa.data['sunspot RI'], label='Sunspot Number')
38 plt.plot(noaa_predict.data.index, noaa_predict.data['sunspot'],
39          color='grey', label='Near-term Prediction')
40 plt.fill_between(noaa_predict.data.index, noaa_predict.data['sunspot low'],
41                  noaa_predict.data['sunspot high'], alpha=0.3, color='grey')
42 
43 plt.fill_between(noaa2.data.index, noaa2.data['sunspot RI smooth']*0.4,
44                  noaa2.data['sunspot RI smooth']*1.3, alpha=0.3, color='grey',
45                  label='Next Cycle Predict')
46 plt.ylim(0)
47 plt.text('2011-01-01', 120, 'Cycle 24', fontsize=16)
48 plt.text('2024-01-01', 120, 'Cycle 25', fontsize=16)
49 plt.ylabel('Sunspot Number')
50 plt.xlabel('Year')
51 plt.legend(loc=2, framealpha=0.5)
52 plt.show()
53
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/examples/plotting/solar_cycle_example.py b/examples/plotting/solar_cycle_example.py
--- a/examples/plotting/solar_cycle_example.py
+++ b/examples/plotting/solar_cycle_example.py
@@ -14,25 +14,25 @@
 from sunpy.data.sample import NOAAINDICES_TIMESERIES, NOAAPREDICT_TIMESERIES
 
 ###############################################################################
-# For this example we will use the SunPy sample data, if you want the current
-# data, delete the argument to the ``create`` function. i.e.
-# ``noaa = lc.NOAAIndicesLightCurve.create()``
+# For this example we will use the SunPy sample data. This code snippet grabs
+# the most current NOAA solar cycle data as a ``TimeSeries``
+# (see :ref:`timeseries_code_ref`).
 
 noaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')
 noaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')
 
 ###############################################################################
-# Next lets grab the data again to create a new data structure that we will
-# shift by 12 years to simulate the next solar cycle. We will truncate the
-# data to only plot what is necessary.
+# Next, we grab a new copy of the data and shift it forward 12 years to
+# simulate the next solar cycle. We will also truncate the data to ensure
+# that we only plot what is necessary.
 
 noaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')
 noaa2.data = noaa2.data.shift(2, freq=datetime.timedelta(days=365*12))
 noaa2 = noaa2.truncate('2021/04/01', '2030/01/01')
 
 ###############################################################################
-# Finally lets plot everything together with some arbitrary range for the
-# strength of the next solar cycle.
+# Finally, we plot both ``noaa`` and ``noaa2`` together, with an arbitrary
+# range for the strength of the next solar cycle.
 
 plt.plot(noaa.data.index, noaa.data['sunspot RI'], label='Sunspot Number')
 plt.plot(noaa_predict.data.index, noaa_predict.data['sunspot'],

{"golden_diff": "diff --git a/examples/plotting/solar_cycle_example.py b/examples/plotting/solar_cycle_example.py\n--- a/examples/plotting/solar_cycle_example.py\n+++ b/examples/plotting/solar_cycle_example.py\n@@ -14,25 +14,25 @@\n from sunpy.data.sample import NOAAINDICES_TIMESERIES, NOAAPREDICT_TIMESERIES\n \n ###############################################################################\n-# For this example we will use the SunPy sample data, if you want the current\n-# data, delete the argument to the ``create`` function. i.e.\n-# ``noaa = lc.NOAAIndicesLightCurve.create()``\n+# For this example we will use the SunPy sample data. This code snippet grabs\n+# the most current NOAA solar cycle data as a ``TimeSeries``\n+# (see :ref:`timeseries_code_ref`).\n \n noaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\n noaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')\n \n ###############################################################################\n-# Next lets grab the data again to create a new data structure that we will\n-# shift by 12 years to simulate the next solar cycle. We will truncate the\n-# data to only plot what is necessary.\n+# Next, we grab a new copy of the data and shift it forward 12 years to\n+# simulate the next solar cycle. We will also truncate the data to ensure\n+# that we only plot what is necessary.\n \n noaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\n noaa2.data = noaa2.data.shift(2, freq=datetime.timedelta(days=365*12))\n noaa2 = noaa2.truncate('2021/04/01', '2030/01/01')\n \n ###############################################################################\n-# Finally lets plot everything together with some arbitrary range for the\n-# strength of the next solar cycle.\n+# Finally, we plot both ``noaa`` and ``noaa2`` together, with an arbitrary\n+# range for the strength of the next solar cycle.\n \n plt.plot(noaa.data.index, noaa.data['sunspot RI'], label='Sunspot Number')\n plt.plot(noaa_predict.data.index, noaa_predict.data['sunspot'],\n", "issue": "Solar Cycle Gallery example out of date\nThe example includes the following text \r\n\r\n> For this example we will use the SunPy sample data, if you want the current data, delete the argument to the create function. i.e. noaa = lc.NOAAIndicesLightCurve.create()\r\n\r\nThis text is inline and therefore not checked during build so was not caught. This should be fixed and this behavior should be discouraged.\n", "before_files": [{"content": "\"\"\"\n===============\nThe Solar Cycle\n===============\n\nThis example shows the current and possible next solar cycle.\n\"\"\"\nfrom __future__ import print_function, division\n\nimport datetime\nimport matplotlib.pyplot as plt\n\nimport sunpy.timeseries as ts\nfrom sunpy.data.sample import NOAAINDICES_TIMESERIES, NOAAPREDICT_TIMESERIES\n\n###############################################################################\n# For this example we will use the SunPy sample data, if you want the current\n# data, delete the argument to the ``create`` function. i.e.\n# ``noaa = lc.NOAAIndicesLightCurve.create()``\n\nnoaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\nnoaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')\n\n###############################################################################\n# Next lets grab the data again to create a new data structure that we will\n# shift by 12 years to simulate the next solar cycle. We will truncate the\n# data to only plot what is necessary.\n\nnoaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\nnoaa2.data = noaa2.data.shift(2, freq=datetime.timedelta(days=365*12))\nnoaa2 = noaa2.truncate('2021/04/01', '2030/01/01')\n\n###############################################################################\n# Finally lets plot everything together with some arbitrary range for the\n# strength of the next solar cycle.\n\nplt.plot(noaa.data.index, noaa.data['sunspot RI'], label='Sunspot Number')\nplt.plot(noaa_predict.data.index, noaa_predict.data['sunspot'],\n         color='grey', label='Near-term Prediction')\nplt.fill_between(noaa_predict.data.index, noaa_predict.data['sunspot low'],\n                 noaa_predict.data['sunspot high'], alpha=0.3, color='grey')\n\nplt.fill_between(noaa2.data.index, noaa2.data['sunspot RI smooth']*0.4,\n                 noaa2.data['sunspot RI smooth']*1.3, alpha=0.3, color='grey',\n                 label='Next Cycle Predict')\nplt.ylim(0)\nplt.text('2011-01-01', 120, 'Cycle 24', fontsize=16)\nplt.text('2024-01-01', 120, 'Cycle 25', fontsize=16)\nplt.ylabel('Sunspot Number')\nplt.xlabel('Year')\nplt.legend(loc=2, framealpha=0.5)\nplt.show()\n", "path": "examples/plotting/solar_cycle_example.py"}], "after_files": [{"content": "\"\"\"\n===============\nThe Solar Cycle\n===============\n\nThis example shows the current and possible next solar cycle.\n\"\"\"\nfrom __future__ import print_function, division\n\nimport datetime\nimport matplotlib.pyplot as plt\n\nimport sunpy.timeseries as ts\nfrom sunpy.data.sample import NOAAINDICES_TIMESERIES, NOAAPREDICT_TIMESERIES\n\n###############################################################################\n# For this example we will use the SunPy sample data. This code snippet grabs\n# the most current NOAA solar cycle data as a ``TimeSeries``\n# (see :ref:`timeseries_code_ref`).\n\nnoaa = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\nnoaa_predict = ts.TimeSeries(NOAAPREDICT_TIMESERIES, source='noaapredictindices')\n\n###############################################################################\n# Next, we grab a new copy of the data and shift it forward 12 years to\n# simulate the next solar cycle. We will also truncate the data to ensure\n# that we only plot what is necessary.\n\nnoaa2 = ts.TimeSeries(NOAAINDICES_TIMESERIES, source='noaaindices')\nnoaa2.data = noaa2.data.shift(2, freq=datetime.timedelta(days=365*12))\nnoaa2 = noaa2.truncate('2021/04/01', '2030/01/01')\n\n###############################################################################\n# Finally, we plot both ``noaa`` and ``noaa2`` together, with an arbitrary\n# range for the strength of the next solar cycle.\n\nplt.plot(noaa.data.index, noaa.data['sunspot RI'], label='Sunspot Number')\nplt.plot(noaa_predict.data.index, noaa_predict.data['sunspot'],\n         color='grey', label='Near-term Prediction')\nplt.fill_between(noaa_predict.data.index, noaa_predict.data['sunspot low'],\n                 noaa_predict.data['sunspot high'], alpha=0.3, color='grey')\n\nplt.fill_between(noaa2.data.index, noaa2.data['sunspot RI smooth']*0.4,\n                 noaa2.data['sunspot RI smooth']*1.3, alpha=0.3, color='grey',\n                 label='Next Cycle Predict')\nplt.ylim(0)\nplt.text('2011-01-01', 120, 'Cycle 24', fontsize=16)\nplt.text('2024-01-01', 120, 'Cycle 25', fontsize=16)\nplt.ylabel('Sunspot Number')\nplt.xlabel('Year')\nplt.legend(loc=2, framealpha=0.5)\nplt.show()\n", "path": "examples/plotting/solar_cycle_example.py"}]}