# Written by Vameifrom datetime import datetime, timedelta
import re
import numpy as npimport matplotlib
matplotlib.rcParams['text.color'] = 'white'
matplotlib.rcParams['xtick.color'] = 'white'
matplotlib.rcParams['ytick.color'] = 'white'from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as pltfont = 'monospace'# This function is to plot the base map
def plotBase(fig, dt=None):m = Basemap(projection='merc',lon_0=0,lat_0=0,lat_ts=0,llcrnrlat=0,urcrnrlat=50,llcrnrlon=-100,urcrnrlon=-50,resolution='l')m.drawcountries(linewidth=1, color='k')m.drawmapscale(-90, 5, -90, 5, 1000, barstyle='fancy')m.bluemarble(scale=1)# Get Position of NYC, longitude -74.0064, latitude 40.7142x,y    = m(-74.0064, 40.7142)# Plot NYCm.scatter(x, y, s=100,  marker='*', color='0.5', alpha=1)plt.text(x,y,'NYC', fontsize='15')if dt is not None: m.nightshade(dt, alpha = 0.3)return m# Hurricane category colors
color_dict = {'TROPICAL DEPRESSION':'#AEF100', 'TROPICAL STORM':'#FFD600', 'HURRICANE-1':'#FF6440', 'HURRICANE-2':'#8506A9'}# Read data file, unzip from track.zip to get track.dat
fn  = 'track.dat'
rec = {'lat':[],'lon':[],'wind':[],'press':[],'dt':[],'cat':[]}
for i,line in enumerate(file(fn)):if i == 0: continue  # Jump over the first line# replace multiple whitespaces with a single whitespaceline   = re.sub(r"\s+", ' ', line)pieces = line.split(" ")# retrieve informationrec['lat'].append(float(pieces[0]))rec['lon'].append(float(pieces[1]))rec['wind'].append(float(pieces[3]))rec['press'].append(float(pieces[4]))rec['cat'].append((" ".join(pieces[5:])).strip())time   = pieces[2]time   = "2012/" + timerec['dt'].append(datetime.strptime(time,"%Y/%m/%d/%HZ"))# Plot the track and the else
N = len(rec['lat'])
for idx in range(N):dt     = rec['dt'][idx]# Adjust time zone according to NYClt     = dt - timedelta(hours=5)lon    = rec['lon'][idx]lat    = rec['lat'][idx]wind   = rec['wind'][idx]press  = rec['press'][idx]cat    = rec['cat'][idx]fig    = plt.figure()m      = plotBase(fig, dt)# From lon,lat to pixelsx,y    = m(lon, lat)# Plot trackfor i in range(idx):a0,b0 = m(rec['lon'][i], rec['lat'][i])a1,b1 = m(rec['lon'][i+1], rec['lat'][i+1])m.plot((a0,a1),(b0,b1), linewidth=2.5,color=color_dict[rec['cat'][i+1]])# Plot Sandy's current positionm.scatter(x, y, s=100, c=color_dict[cat], alpha=0.8)# Annotate current position
    plt.annotate(cat, xy = (x, y), xytext = (-5, -30),textcoords = 'offset points', ha = 'right', va = 'bottom',bbox = dict(boxstyle = 'round,pad=0.5', fc=color_dict[cat], alpha = 0.8),arrowprops = dict(arrowstyle = '->', connectionstyle = 'arc3,rad=0'))tx, ty = m(-98, 40)plt.text(tx,ty, lt.strftime("Hurricane Sandy\n\nNYC LT:\n%Y-%m-%d %H:00:00\nData Source: NOAA\nBy Vamei"), family=font,ha='left')# add a small axes to show pressurea = fig.add_axes([0.6,0.2,.15,.1])a.set_ylim((950,1000))a.set_xlim((-10,70))a.set_yticks([900,1050])a.set_xticks([0,60])a.set_title("Center Pressure (mb)", fontsize=10)a.plot(rec['press'])a.axvline(x=idx, color='r')# add a small axes to show winda = fig.add_axes([0.6,0.4,.15,.1])a.set_ylim((0,100))a.set_xlim((-10,70))a.set_yticks([0,100])a.set_xticks([0,60])a.set_title("Max Wind (knots)", fontsize=10)a.plot(rec['wind'])a.axvline(x=idx, color='r')fig.savefig(('%04d.png' % idx))plt.close()