In [8]:
# Generate the figure and axis with nrows and ncols for subplots ###
##### proj = 'cyl' is the Cylindrical Equidistant Map projection used by Cartopy ###
fig, axs=plot.subplots(ncols=2,nrows=1, proj='cyl',tight=True)
lat_min = 12 # # Minimum latitude on the map
lat_max = 21 # Maximum latitude on the map
lon_min = 75 # # Minimum longitude on the map
lon_max = 86 # # Maximum longitude on the map
cm = 'jet' # Colormap 'rainbow' , 'viridis', 'RdYlBu', 'RdBu' etc..
ex= 'max' # Color bar arrow ,'min', 'max', 'none','both'
#Now, we can format all the axes at once using these commands
axs.format(lonlim=(lon_min, lon_max),
latlim=(lat_min, lat_max),
labels=True,
innerborders=False,
latlines=4, lonlines=4,
abc='(a)', abcloc='ll',
gridminor=False,
suptitle='IMD Rainfall' )
######## Limits as above; ### labels = True for lat lon labels,
###### inner borders = False , If True, it will show rivers #####
###latlines=1, lonlines=1 spacing ########
#abc=False, It abc='(a)', it will automatically give subplot (a),(b),(c) etc....
####abcloc='ll', abc location
#### gridminor=False; if true it will show all gridlines of lat , lon
# Subtitles for each plot
# We can declare the subtitles now and use it further
title=['Mean Daily Rainfall','Daily Rainfall Standard Deviation' ]
vars =['ds_clip','ds_clip_std']
levels_mean= np.arange(0,5.5,0.5) # generates a sequence of numbers from 0 to 6 with a spacing of 0.5
levels_std= np.arange(6,12.5,0.5)
levels=['levels_mean','levels_std']
###########Subplots ################
#contourf for contours
#pcolormesh for psuedo color plot
#Each subplot axis is numbered as axs[0] or axs[1] etc....]
# We can loop over each plot by indexing it as axs[i] where i is the indexing variable
for i in range(0,2):
#######################
m=axs[i].pcolor(globals()[vars[i]], # globals() and vars[i] are used to index and generate the variable name
cmap=cm, # Colormap
transform=ccrs.PlateCarree(), # cartopy map projection
extend=ex, #colorbar style
levels = globals()[levels[i]],
)
axs[i].add_geometries(Reader(fname).geometries(),
ccrs.PlateCarree(),facecolor='None',edgecolor='black',
linewidth=1) # overlaying the shapefile
axs[i].format(title=title[i])
axs[i].colorbar(m,loc='r',drawedges=True, width = 0.10 , length=0.65, label='mm/day')
#fig.colorbar will ive 1 common colorbar for all plots. But for common colorbar give explict levels.
#Use axs[0].colorbar for individual colorbars ########
# axs[1].colorbar(n,loc='b',drawedges=True, width = 0.10 , length=0.65, label= 'Rainfall')
