Lint (black, isort, flake8) NH original recipe 17

Author: sadielbartholomew

docs/source/recipes/plot_17_recipe.py

@@ -2,7 +2,7 @@
 Plotting Contour Subplots with different Colour Maps/Scales
 ============================================
 In this recipe, we will plot data with different colour maps to illustrate
-the importance of choosing the correct one for a plot. This is to ensure 
+the importance of choosing the correct one for a plot. This is to ensure
 the use of perceptually uniform scales and avoid unintended bias.
 """
 
@@ -13,56 +13,77 @@
 
 import cf
 
-#%%
+# %%
 # 2. Read the field in:
-# Here I've used sample data ggap.nc (and later pressure=850), but you could use tas_A1.nc 
+# Here I've used sample data ggap.nc (and later pressure=850), but you could use tas_A1.nc
 # (with time=15)
 
-f=cf.read('~/cfplot_data/ggap.nc')[0]
+f = cf.read("~/cfplot_data/ggap.nc")[0]
 
-#%%
+# %%
 # 3. Choose a set of predefined colour scales to view (based on NCAR)
 # Choose a set of predefined colour scales to view (based on NCAR)
-# You could also choose your own from 
+# You could also choose your own from
 # https://ncas-cms.github.io/cf-plot/build/colour_scales.html
-# Simply change the name in quotes and ensure the number of rows * number of columns = 
+# Simply change the name in quotes and ensure the number of rows * number of columns =
 # number of colour scales
 
-#%%
+# %%
 # a. Perceptually uniform colour scales, with no zero value
 
-colour_scale = ["viridis", "magma","inferno", "plasma", "parula", "gray"]
+colour_scale = ["viridis", "magma", "inferno", "plasma", "parula", "gray"]
 cfp.gopen(rows=2, columns=3, bottom=0.2)
 
-#%%
+# %%
 # b. NCAR Command Language - Enhanced to help with colour blindness
 
-colour_scale = ["StepSeq25","posneg_2","posneg_1","BlueDarkOrange18","BlueDarkRed18",
-"GreenMagenta16","BlueGreen14","BrownBlue12","Cat12"]
+colour_scale = [
+    "StepSeq25",
+    "posneg_2",
+    "posneg_1",
+    "BlueDarkOrange18",
+    "BlueDarkRed18",
+    "GreenMagenta16",
+    "BlueGreen14",
+    "BrownBlue12",
+    "Cat12",
+]
 cfp.gopen(rows=3, columns=3, bottom=0.1)
 
-#%%
+# %%
 # c. Orography/bathymetry colour scales
 
-# These are used to show the shape/contour of landmasses, bear in mind the example data 
-# we use is with pressure so doesnt accurately represent this. 
-# You could instead use cfp.cscale('wiki_2_0', ncols=16, below=2, above=14) or any other 
+# These are used to show the shape/contour of landmasses, bear in mind the example data
+# we use is with pressure so doesnt accurately represent this.
+# You could instead use cfp.cscale('wiki_2_0', ncols=16, below=2, above=14) or any other
 # orography colour scale in a similar way
 
-colour_scale = ["os250kmetres", "wiki_1_0_2", "wiki_1_0_3", "wiki_2_0", "wiki_2_0_reduced", 
-"arctic"]
+colour_scale = [
+    "os250kmetres",
+    "wiki_1_0_2",
+    "wiki_1_0_3",
+    "wiki_2_0",
+    "wiki_2_0_reduced",
+    "arctic",
+]
 cfp.gopen(rows=2, columns=3, bottom=0.2, file="ColourPlot.png")
 
-#%%
+# %%
 # 5. We then use a for loop to cycle through all the different colour maps:
-# Only gpos has 1 added because it can only take 1 as its first value, otherwise there are 
+# Only gpos has 1 added because it can only take 1 as its first value, otherwise there are
 # errors.
 for i, colour_scale in enumerate(colour_scale):
-    cfp.gpos(i+1)
+    cfp.gpos(i + 1)
     cfp.mapset(proj="cyl")
     cfp.cscale(colour_scale[i])
-    if i == len(colour_scale)+1:
-        cfp.con(f.subspace(pressure=850), lines=False, title = colour_scale[i], colorbar_position=[0.1, 0.1, 0.8, 0.02], colorbar_orientation='horizontal')
+    if i == len(colour_scale) + 1:
+        cfp.con(
+            f.subspace(pressure=850),
+            lines=False,
+            title=colour_scale[i],
+            colorbar_position=[0.1, 0.1, 0.8, 0.02],
+            colorbar_orientation="horizontal",
+        )
     else:
-        cfp.con(f.subspace(pressure=850), title = colour_scale[i], lines=False)
-cfp.gclose(view=True)
+        cfp.con(f.subspace(pressure=850), title=colour_scale[i], lines=False)
+cfp.gclose(view=True)