Stripes plotting codeΒΆ

Parallise the calculation by extracting the data sample for each year independently:

#!/usr/bin/env python

# 20CRv3 stripes.
# Monthly, resolved in latitude, averaging in longitude, 
#  single ensemble member.

# Get the sample for a specified year

import os
import iris
import numpy
import datetime
import pickle

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

import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--year", help="Year",
                    type=int,required=True)
parser.add_argument("--opdir", help="Directory for output files",
                    default="%s/20CR/version_3/analyses/Stripes/PRMSL_lon" % \
                                           os.getenv('SCRATCH'),
                    type=str,required=False)
args = parser.parse_args()
if not os.path.isdir(args.opdir):
    os.makedirs(args.opdir)

# Fix dask SPICE bug
import dask
dask.config.set(scheduler='single-threaded')

start=datetime.datetime(args.year,1,1,0,0)
end=datetime.datetime(args.year,12,31,23,59)

from get_sample import get_sample_cube

cpkl="%s/20CR/version_3/monthly_means/PRMSL.climatology.1961-90.pkl" % os.getenv('SCRATCH')
climatology=pickle.load(open(cpkl,'rb'))

rst = numpy.random.RandomState(seed=None)
dts=[]
ndata=None
for year in range(start.year,end.year+1,1):
    ey = min(year+1,end.year)
    (ndyr,dtyr) = get_sample_cube(datetime.datetime(year,1,1,0,0),
                                  datetime.datetime(year,12,31,23,59),
                                  climatology=climatology,
                                  new_grid=climatology[0],rstate=rst)
    dts.extend(dtyr)
    if ndata is None:
        ndata = ndyr
    else:
        ndata = numpy.ma.concatenate((ndata,ndyr))

cspf = "%s/%04d.pkl" % (args.opdir,args.year)
pickle.dump((ndata,dts),open(cspf,'wb'))
   

And then running that script for each year as a separate task:

#!/usr/bin/env python

# Scripts to make slices for every month

import os
import datetime

for year in range (1806,2016):
    print("./get_slice.py --year=%d" % year )

Then assemble the slices to make the figure:

#!/usr/bin/env python

# 20CRv3 stripes.
# Monthly, resolved in longitude, averaging in latitude, 
#  sampling across ensemble.

import os
import iris
import numpy
import datetime
import pickle

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(1806,1,1,0,0)
end=datetime.datetime(2015,12,31,23,59)


dts=[]
ndata=None
for year in range(start.year,end.year+1,1):
    sfile="%s/20CR/version_3/analyses/Stripes/PRMSL_lon/%04d.pkl" % \
                                           (os.getenv('SCRATCH'),year)
    with open(sfile, "rb") as f:
       (ndyr,dtyr)  = pickle.load(f)

    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')


# Add a textured grey background
s=(2000,600)
ax2 = fig.add_axes([0.02,0.05,0.98,0.95],facecolor='green')
ax2.set_axis_off() 
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([0.02,0.05,0.98,0.95],facecolor='black',
                  xlim=((start+datetime.timedelta(days=1)).timestamp(),
                        (end-datetime.timedelta(days=1)).timestamp()),
                  ylim=(1,0))
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=-13,
                        vmax=13,
                        zorder=100)


# Add a latitude grid
axg = fig.add_axes([0.0,0.05,1,0.95],facecolor='green',
                  xlim=((start+datetime.timedelta(days=1)).timestamp(),
                        (end-datetime.timedelta(days=1)).timestamp()),
                  ylim=(0,1))
axg.set_axis_off()

def add_lonline(ax,longitude):
    latl = (longitude)/360
    startt=start.timestamp()+(end.timestamp()-start.timestamp())*0.02
    ax.add_line(Line2D([startt,end.timestamp()], 
                       [latl,latl], 
                       linewidth=0.75, 
                       color=(0.2,0.2,0.2,1),
                       zorder=200))
    tx=start.timestamp()+(end.timestamp()-start.timestamp())*0.019
    ax.text(tx,latl,
         "%d" % longitude,
         horizontalalignment='right',
         verticalalignment='center',
         color='black',
         size=14,
         clip_on=True,
         zorder=200)

for lon in (60,120,180,240,300):
    add_lonline(axg,lon)

# Add a date grid
axg = fig.add_axes([0.02,0,0.98,1],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=0.75, 
                color=(0.2,0.2,0.2,1),
                       zorder=200))
    ax.text(x,0.024,
         "%04d" % year,
         horizontalalignment='center',
         verticalalignment='center',
         color='black',
         size=14,
         clip_on=True,
         zorder=200)


for year in range(1810,2020,10):
    add_dateline(axg,year)

fig.savefig('PRMSL.png')