Merge pull request #63 from sadielbartholomew/docs-new-theming

Doc: configure to use PyData theme with announcement

docs/build/.buildinfo

@@ -1,4 +1,4 @@
 # Sphinx build info version 1
 # This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
-config: b20cddc9ac81d3adb3cbbbe7bfbc4417
+config: b2bd04cad44aa68354896a81dc9679e8
 tags: 645f666f9bcd5a90fca523b33c5a78b7

docs/build/_sources/advanced.rst.txt

@@ -26,7 +26,7 @@ To see all the methods for the plot object type
 In this example we make a blank map plot, change the longitude labels and add a box and some text.   For map plots we operate on the cfp.plotvars.mymap object and need to specify transform=ccrs.PlateCarree() to make sure that the plotting is made in regular longitude and latitude coordinates.  If the plot is not a map plot then the transform=ccrs.PlateCarree() isn't needed.
 
 .. image::  images/advanced1.png
-   :scale: 52% 
+   :scale: 52%
 
 
 ::
@@ -45,7 +45,7 @@ In this example we make a blank map plot, change the longitude labels and add a
     yticks=[-30.0, 70.0]
     yticklabels=['ylabel1', 'ylabel2']
 
-    # Specify some contour levels outside the range of the data    
+    # Specify some contour levels outside the range of the data
     # and make a blank contour plot
     cfp.levs(-1000, -900, 100)
     cfp.con(f.subspace(time=15), fill=False, colorbar=None,
@@ -54,7 +54,7 @@ In this example we make a blank map plot, change the longitude labels and add a
 
     # A box
     cfp.plotvars.mymap.plot([-150, -150, -90, -90, -150],
-                            [-5, 5, 5, -5, -5], linewidth=3.0, 
+                            [-5, 5, 5, -5, -5], linewidth=3.0,
                             color='blue', transform=ccrs.PlateCarree())
 
     # A symbol
@@ -78,7 +78,7 @@ In this example we make a blank map plot, change the longitude labels and add a
 
 Adding country borders etc can be done using the normal Cartopy operations on the cfp.plotvars.mymap object.  Look on the Cartopy web page for examples of these.
 
- 
+
 
 Plotting shape files
 --------------------
@@ -87,7 +87,7 @@ In this example we make a blank map plot and plot the UK rivers from a shapefile
 
 
 .. image::  images/advanced_shapefile.png
-   :scale: 52% 
+   :scale: 52%
 
 
 
@@ -116,7 +116,7 @@ In this example we make a blank map plot and plot the UK rivers from a shapefile
         for ip in range(len(points)):
             lons[ip] = points[ip][0]
             lats[ip] = points[ip][1]
-        
+
         cfp.plotvars.mymap.plot(lons, lats , linewidth=1.0,
                                 color='blue', transform=ccrs.PlateCarree())
 
@@ -130,12 +130,12 @@ In this example we make a blank map plot and plot the UK rivers from a shapefile
 Making a transect plot
 ----------------------
 
-In this example we make a contour plot and plot a transect.  We use the cfp.regrid bilinear interpolation 
-routine to interpolate the data.  Interpolation points for this routine must be **within** the data limits 
+In this example we make a contour plot and plot a transect.  We use the cfp.regrid bilinear interpolation
+routine to interpolate the data.  Interpolation points for this routine must be **within** the data limits
 of the original data.  Care is needed to ensure that the field coordinates go from a low value to a high value.  This is usually not an issue with longitude but occasionally with latitude (as in this case) the coordinate goes from the north pole to the south pole.  A simple flip of the latitude and data is need here.
 
 .. image::  images/advanced_transect.png
-   :scale: 52% 
+   :scale: 52%
 
 
 ::
@@ -220,7 +220,7 @@ For example, to make one of the colours in the viridis colour scale grey use:
 
 
 .. image::  images/advanced2.png
-   :scale: 52% 
+   :scale: 52%
 
 
 Colouring land and lakes
@@ -238,7 +238,7 @@ This is done by changing the land_color, ocean_color and lake_color variables in
 
 
 .. image::  images/advanced3.png
-   :scale: 52% 
+   :scale: 52%
 
 
 
@@ -269,7 +269,7 @@ Masked data isn't plotted.
 
 
 .. image::  images/advanced4.png
-   :scale: 52% 
+   :scale: 52%
 
 Masked data is plotted as blockfill in grey.
 
@@ -285,25 +285,25 @@ Masked data is plotted as blockfill in grey.
     cfp.con(h, blockfill=True, title='Masked data plotted in grey')
 
 
-    # Call internal block filling routine 
+    # Call internal block filling routine
     cfp.bfill(f=np.squeeze(i.array), x=i.coord('X').array, y=i.coord('Y').array,
               clevs=[990, 1000], lonlat=True, single_fill_color='#d3d3d3')
 
-            
+
     cfp.gclose()
 
 
 
 .. image::  images/advanced5.png
-   :scale: 52% 
+   :scale: 52%
 
 Blockfill with individual colours
 ---------------------------------
 
 |    If a plot needs to be built up as a series of blockfill plots then this is
 |    possible using the cf-plot internal blockfill routine.  A colour contour plot is
 |    made and overlaid with two blockfill regions:
-|    
+|
 |    -50 to 0 = green
 |    20 to 40  = red
 
@@ -336,7 +336,4 @@ A final call to **cfp.con** is made to overlay contour lines.
 
 
 .. image::  images/advanced6.png
-   :scale: 52% 
-
-
-
+   :scale: 52%

docs/build/_sources/colour_scales.rst.txt

@@ -7,17 +7,17 @@ Colour scales
 
 There are two default colour scales in cf-plot:
 
-1) A continuous scale ('viridis') that goes from blue to green and then yellow and suits data that has no zero in it.  For example air temperature in Kelvin or geopotential height - see example 1 in the plot gallery.  
+1) A continuous scale ('viridis') that goes from blue to green and then yellow and suits data that has no zero in it.  For example air temperature in Kelvin or geopotential height - see example 1 in the plot gallery.
 
 2) A diverging scale ('scale1') that goes from blue to red and suits data with a zero in it.  For example temperature in Celsius or zonal wind - see example 4 in the plot gallery.  The colour scale is automatically adjusted so that blue hues are below zero and red hues above zero.
 
-When no calls have been made to **cfp.cscale** cf-plot selects one of theses scales based on whether there is a zero in the data passed for contouring.  If a call is made to **cfp.cscale** with just a colour scale name  **cfp.cscale('radar')**, for example, then this colour scale is used for all subsequent plots.  The colour scale is adjusted automatically to fit the number of contour levels in the plot. 
+When no calls have been made to **cfp.cscale** cf-plot selects one of theses scales based on whether there is a zero in the data passed for contouring.  If a call is made to **cfp.cscale** with just a colour scale name  **cfp.cscale('radar')**, for example, then this colour scale is used for all subsequent plots.  The colour scale is adjusted automatically to fit the number of contour levels in the plot.
 
 If a call to **cfp.cscale** specifies additional parameters to the colour scale, then the automatic colour adjustment is turned off giving the user fine tuning of colours as below.
 
 
-.. image::  images/cs1.png 
-  :scale: 65% 
+.. image::  images/cs1.png
+  :scale: 65%
 
 ::
 
@@ -30,11 +30,11 @@ If a call to **cfp.cscale** specifies additional parameters to the colour scale,
 
 
 
-To change the number of colours in a scale use the ncols parameters. 
+To change the number of colours in a scale use the ncols parameters.
 
 
-.. image::  images/cs2.png 
-  :scale: 65% 
+.. image::  images/cs2.png
+  :scale: 65%
 
 ::
 
@@ -44,11 +44,11 @@ To change the number of colours in a scale use the ncols parameters.
 |
 |
 
-To change the number of colours above and below the mid-point of the scale use the above and below parameters.  This is useful for fields where you have differing extents of data above and below the zero line. 
+To change the number of colours above and below the mid-point of the scale use the above and below parameters.  This is useful for fields where you have differing extents of data above and below the zero line.
 
 
-.. image::  images/cs3.png 
-  :scale: 65% 
+.. image::  images/cs3.png
+  :scale: 65%
 
 
 ::
@@ -61,16 +61,16 @@ To change the number of colours above and below the mid-point of the scale use t
 
 For data where you need white to indicate that this data region is insignificant use the white=white parameter.  This can take single or multiple values of the index of the colour scale where white is required in the colour scale.
 
-.. image::  images/cs4.png 
-  :scale: 65% 
+.. image::  images/cs4.png
+  :scale: 65%
 
 ::
 
    cfp.cscale('scale1', ncols=11, white=5)
    cfp.levs(manual=[-10,-8, -6, -4, -2, 2, 4, 6, 8, 10])
 
 .. image::  images/cs4.png
-   :scale: 52% 
+   :scale: 52%
 
 
 To reverse a colour scale use the **reverse=1** option to **cscale** and specify the number of colours required.
@@ -81,11 +81,11 @@ To reverse a colour scale use the **reverse=1** option to **cscale** and specify
 
 
 
-As a short example to show the flexibilty of the colour scale routines we will make a orography plot using the wiki_2_0.rgb orography/bathymetry colour scale. This has as many colours for bathymetry as for the oroggraphy but in this case we just need a blue ocean as we are really only interested in the orography.  So in this case we will define a set of levels using *levs* and then match the colour scale to them.  The wiki_2_0.rgb colour scale has as many colours for the ocean as for the land so we can use the above and below options 
+As a short example to show the flexibilty of the colour scale routines we will make a orography plot using the wiki_2_0.rgb orography/bathymetry colour scale. This has as many colours for bathymetry as for the oroggraphy but in this case we just need a blue ocean as we are really only interested in the orography.  So in this case we will define a set of levels using *levs* and then match the colour scale to them.  The wiki_2_0.rgb colour scale has as many colours for the ocean as for the land so we can use the above and below options
 
 
 .. image::  images/orog.png
-   :scale: 52% 
+   :scale: 52%
 
 ::
 
@@ -95,13 +95,13 @@ As a short example to show the flexibilty of the colour scale routines we will m
    f=cf.read('cfplot_data/12km_orog.nc')[0]
    cfp.cscale('wiki_2_0', ncols=16, below=2, above=14)
    cfp.levs(manual=np.arange(15)*150)
-   cfp.con(f, lines=False) 
+   cfp.con(f, lines=False)
 
 
 
 User defined colour scales
 --------------------------
-Store these as rgb values in a file with one rgb value per line.  i.e. 
+Store these as rgb values in a file with one rgb value per line.  i.e.
 
 ::
 
@@ -129,8 +129,8 @@ cfp.lineplot(g.subspace(pressure=925), color='plum')
 2) Use the hexadecimal code for the colour.
 
 cfp.lineplot(g.subspace(pressure=925), color = '#eeefff')
- 
-  
+
+
 3) Shades of grey can be selected with cmap(shade), where shade go from 0 to 1.
 
 cfp.lineplot(g.subspace(pressure=925), color=cmap(0.8))
@@ -384,9 +384,3 @@ scale42 .. image:: images/colour_scales/scale42.png
 scale43 .. image:: images/colour_scales/scale43.png
 scale44 .. image:: images/colour_scales/scale44.png
 ======= =====
-
-
-
-
-
-

docs/build/_sources/cylindrical.rst.txt

@@ -9,7 +9,7 @@ Example 1 - basic cylindrical projection
 ----------------------------------------
 
 .. image::  images/fig1.png
-   :scale: 52% 
+   :scale: 52%
 
 ::
 
@@ -19,15 +19,15 @@ Example 1 - basic cylindrical projection
    cfp.con(f.subspace(time=15))
 
 
-| 
-| 
+|
+|
 
 
 Example 2 - cylindrical projection with blockfill
 -------------------------------------------------
 
 .. image::  images/fig2.png
-   :scale: 52% 
+   :scale: 52%
 
 ::
 
@@ -38,16 +38,16 @@ Example 2 - cylindrical projection with blockfill
 
 
 
-| 
-| 
+|
+|
 
 
 
 Example 3 - altering the map limits and contour levels
 ------------------------------------------------------
 
 .. image::  images/fig3.png
-   :scale: 52% 
+   :scale: 52%
 
 
 ::
@@ -58,7 +58,3 @@ Example 3 - altering the map limits and contour levels
    cfp.mapset(lonmin=-15, lonmax=3, latmin=48, latmax=60)
    cfp.levs(min=265, max=285, step=1)
    cfp.con(f.subspace(time=15))
-
-
-
-

docs/build/_sources/download.rst.txt

@@ -53,13 +53,13 @@ The second line is optional and installs esmpy, together with the netcdf-fortran
 
 Windows
 #######
-We have a small development team and Linux is our main working environment. Windows isn't an option for us at present given our target user base.  
+We have a small development team and Linux is our main working environment. Windows isn't an option for us at present given our target user base.
 
 If you have a Windows operating system there are a couple of options for running Linux:
 
 1) Install the Microsoft Windows Subsystem for Linux (WSL).  Once this is working install cf-python and cf-plot as per the Linux instructions above.
 
-2) Installing a Linux Virtual Machine is simple and works well.  Installation instructions and a Mint Linux Virtual Machine are available at http://gws-access.ceda.ac.uk/public/ncas_climate/ajh/data_analysis_tools/VM.  
+2) Installing a Linux Virtual Machine is simple and works well.  Installation instructions and a Mint Linux Virtual Machine are available at http://gws-access.ceda.ac.uk/public/ncas_climate/ajh/data_analysis_tools/VM.
 
 
 
@@ -101,14 +101,12 @@ These are available in the cfplot_data directory which can be linked using:
 If you are on a different server then download the `sample netCDF datasets <http://gws-access.ceda.ac.uk/public/ncas_climate/ajh/data_analysis_tools/cfplot_data.tar>`_
 
 
-
+
+|
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-