prompt: 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  Solar Cycle Gallery example out of date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()
  
  ```
  
golden_diff: 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'],
  
verification_info: {"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"}]}