deploy: b75f6d23a9

_sources/examples/generated/Forecast_Model_Vertical_Sounding.rst.txt

@@ -7,11 +7,13 @@ any available AWIPS model with isobaric levels.
 
 -  A Shapely Point geometry is used to select longitude and latitude:
    from shapely.geometry import Point point = Point(-104.67,39.87)
+
 -  Parameters ``['T','DpT','uW','vW']`` are requested for all isobaric
    levels available for the selected model.
 
 -  There is a single-record query performed for ``level = "0.0FHAG"`` to
    determine the surface pressure level.
+
 -  Pay attention to units when switching models. This notebook was
    written for the NAM 40km AWIPS model where temperature and dewpoint
    are returned as Kelvin and wind components as m/s.

_sources/examples/generated/Map_Resources_and_Topography.rst.txt

@@ -486,11 +486,13 @@ to download and render for large (CONUS) maps.
 
 -  This notebook requires: **python-awips, numpy, matplotplib, cartopy,
    shapely**
+
 -  Use datatype **maps** and **addIdentifier(‘table’, <postgres maps
    schema>)** to define the map table:
    DataAccessLayer.changeEDEXHost(“edex-cloud.unidata.ucar.edu”) request
    = DataAccessLayer.newDataRequest(‘maps’)
    request.addIdentifier(‘table’, ‘mapdata.county’)
+
 -  Use **request.setLocationNames()** and **request.addIdentifier()** to
    spatially filter a map resource. In the example below, WFO ID **BOU**
    (Boulder, Colorado) is used to query counties within the BOU county

_sources/examples/generated/Regional_Surface_Obs_Plot.rst.txt

@@ -213,7 +213,7 @@ plotting function later:
 Function: plot_data()
 ---------------------
 
-This function makse use of Metpy.StationPlotLayout and Metpy.StationPlot
+This function makes use of Metpy.StationPlotLayout and Metpy.StationPlot
 to add all surface observation data to our plot. The logic is very
 similar for both METAR and Synoptic data, so a ``datatype`` argument is
 used to distinguish between which data is being drawn, and then draws

examples/generated/Regional_Surface_Obs_Plot.html

@@ -305,7 +305,7 @@ units</p></li>
 <hr class="docutils" />
 <section id="function-plot-data">
 <h3>Function: plot_data()<a class="headerlink" href="#function-plot-data" title="Permalink to this heading"></a></h3>
-<p>This function makse use of Metpy.StationPlotLayout and Metpy.StationPlot
+<p>This function makes use of Metpy.StationPlotLayout and Metpy.StationPlot
 to add all surface observation data to our plot. The logic is very
 similar for both METAR and Synoptic data, so a <code class="docutils literal notranslate"><span class="pre">datatype</span></code> argument is
 used to distinguish between which data is being drawn, and then draws