Stripes plotting code

#!/usr/bin/env python

# Make an extended climate-stripes image from 20CRv3
# Monthly, resolved in latitude, sampling in longitude, ensemble mean.
# Regridded to the EUSTACE grid.

import os
import iris
import numpy
import datetime

import matplotlib
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib.patches import Rectangle
from matplotlib.lines import Line2D

start=datetime.datetime(1851,1,1,0,0)
end=datetime.datetime(2018,12,31,23,59)

from get_sample import get_sample_cube

egrid = iris.load_cube(("%s/EUSTACE/1.0/1969/"+
                        "tas_global_eustace_0_19690312.nc") % 
                        os.getenv('SCRATCH'),
            iris.Constraint(cube_func=(lambda c: c.var_name == 'tas')))

# Make the climatology
n=[]
for m in range(1,13):
    mc=iris.Constraint(time=lambda cell: cell.point.month == m and \
                                         cell.point.year > 1960 and \
                                         cell.point.year < 1991)
    h=iris.load_cube('%s/20CR/version_3/monthly_means/air.2m.mon.mean.nc' % 
                                                   os.getenv('SCRATCH'),
                 iris.Constraint(name='air_temperature') & mc)
    n.append(h.extract(mc).collapsed('time', iris.analysis.MEAN))

# Process in batches or we'll run out of memory.
rst = numpy.random.RandomState(seed=None)
dts=[]
ndata=None
for year in range(start.year,end.year+1,10):
    ey = min(year+10,end.year)
    (ndyr,dtyr) = get_sample_cube(datetime.datetime(year,1,1,0,0),
                                  datetime.datetime(ey,12,31,23,59),
                                  climatology=n,
                                  new_grid=egrid,rstate=rst)
    dts.extend(dtyr)
    if ndata is None:
        ndata = ndyr
    else:
        ndata = numpy.ma.concatenate((ndata,ndyr))

# Plot the resulting array as a 2d colourmap
fig=Figure(figsize=(19.2,6),              # Width, Height (inches)
           dpi=300,
           facecolor=(0.5,0.5,0.5,1),
           edgecolor=None,
           linewidth=0.0,
           frameon=False,                
           subplotpars=None,
           tight_layout=None)
canvas=FigureCanvas(fig)
matplotlib.rc('image',aspect='auto')

def add_latline(ax,latitude):
    latl = (latitude+90)/180
    ax.add_line(Line2D([start.timestamp(),end.timestamp()], 
                       [latl,latl], 
                       linewidth=0.5, 
                       color=(0.8,0.8,0.8,1),
                       zorder=200))

# Add a textured grey background
s=(2000,100)
ax2 = fig.add_axes([0,0.05,1,0.95],facecolor='green')
ax2.set_axis_off() # Don't want surrounding x and y axis
nd2=numpy.random.rand(s[1],s[0])
clrs=[]
for shade in numpy.linspace(.42+.01,.36+.01):
    clrs.append((shade,shade,shade,1))
y = numpy.linspace(0,1,s[1])
x = numpy.linspace(0,1,s[0])
img = ax2.pcolormesh(x,y,nd2,
                        cmap=matplotlib.colors.ListedColormap(clrs),
                        alpha=1.0,
                        shading='gouraud',
                        zorder=10)

# Plot the stripes
ax = fig.add_axes([0,0.05,1,0.95],facecolor='black',
                  xlim=((start+datetime.timedelta(days=1)).timestamp(),
                        (end-datetime.timedelta(days=1)).timestamp()),
                  ylim=(0,1))
ax.set_axis_off() 

ndata = numpy.transpose(ndata)
s=ndata.shape
y = numpy.linspace(0,1,s[0]+1)
x = [(a-datetime.timedelta(days=15)).timestamp() for a in dts]
x.append((dts[-1]+datetime.timedelta(days=15)).timestamp())
img = ax.pcolorfast(x,y,numpy.cbrt(ndata),
                        cmap='RdYlBu_r',
                        alpha=1.0,
                        vmin=-1.7,
                        vmax=1.7,
                        zorder=100)

for lat in [-60,-30,0,30,60]:
    add_latline(ax,lat)

# Add a date grid
axg = fig.add_axes([0,0,1,1],facecolor='green',
                  xlim=((start+datetime.timedelta(days=1)).timestamp(),
                        (end-datetime.timedelta(days=1)).timestamp()),
                  ylim=(0,1))
axg.set_axis_off()
def add_dateline(ax,year):
    x = datetime.datetime(year,1,1,0,0).timestamp()
    ax.add_line(Line2D([x,x], [0.04,1.0], 
                linewidth=0.5, 
                color=(0.8,0.8,0.8,1),
                       zorder=200))
    ax.text(x,0.025,
         "%04d" % year,
         horizontalalignment='center',
         verticalalignment='center',
         color='black',
         size=14,
         clip_on=True,
         zorder=200)

for year in range(1860,2020,10):
    add_dateline(axg,year)

fig.savefig('20CRv3_E-grid.png')