import csv

import numpy as np

import matplotlib.pyplot as plt

import pandas as pd

import sys

from mpl_toolkits.basemap import Basemap

from pandas import Series, DataFrame

from matplotlib.collections import LineCollection

from matplotlib import cm

import shapefile

plt.ion() #enable figure interactive mode

plt.close('all')

treattype = 1

if(treattype == 1): #full

nmax = 16

shorten = 1

shortenstep = 5

inc_deps = 1

inc_roads = 1

informative = 1 #marker size and color are variable

map_res = 'h'

elif(treattype == 2): #medium

nmax = 8

shorten = 1

shortenstep = 5

inc_deps = 1

inc_roads = 1

informative = 1 #marker size and color are variable

map_res = 'h'

else: #short

nmax = 3

shorten = 1

shortenstep = 10

inc_deps = 0

inc_roads = 0

informative = 1 #marker size and color are variable

map_res = 'l'

ac_data = DataFrame()

for i in range(1,nmax+1):

print "Reading out_short_ok_%i" % i

ac_data_part = pd.read_csv('out_short_ok_'+ str(i) +'.csv')

ac_data = pd.concat([ac_data, pd.DataFrame(ac_data_part)])

[n1,n2]=ac_data.shape

print ("Full array has %i lines %i columns\n" %(n1,n2))

#raise SystemExit

if(shorten):

arr_len = ac_data.shape[0]

ac_data = ac_data[0:arr_len:shortenstep]

lats = ac_data.latG

lons = ac_data.longG

gravs = ac_data.grav

lums = ac_data.lum

atms = ac_data.atm

# llcrnrlat,llcrnrlon,urcrnrlat,urcrnrlon

# are the lat/lon values of the lower left and upper right corners

# of the map.

# resolution = 'c' means use crude resolution coastlines.

lllat = 40.0

urlat = 52.5

lllon = -10.0

urlon = 12.0

lat0 = (lllat+urlat)*0.5

lon0 = (lllon+urlon)*0.5

parsec1 = 44.0 #for lambert projection (Lambert93)

parsec2 = 49.0

lat0 = 46.5

lon0 = 3.0

# Lambert cc proj

m = Basemap(width=1200000,height=1200000,

rsphere=(6378137.00,6356752.3142),\

resolution=map_res,area_thresh=1000.,projection='lcc',\

lat_1=parsec1,lat_2=parsec2,lat_0=lat0,lon_0=lon0)

#m.fillcontinents(color='coral',lake_color='aqua')

# m.fillcontinents(color='khaki',lake_color='aqua')

m.fillcontinents(color='#f4a460',lake_color='aqua')

plt.subplots_adjust(left=0.05,right=0.95,top=0.90,bottom=0.05,wspace=0.15,hspace=0.05)

ax = plt.subplot(111)

#Let's create a basemap of Europe

x1 = lllon

x2 = urlon

y1 = lllat

y2 = urlat

m.drawcountries(linewidth=0.5)

m.drawcoastlines(linewidth=0.5)

m.drawparallels(np.arange(y1,y2,2.5),labels=[1,0,0,0],color='black',dashes=[1,0],labelstyle='+/-',linewidth=0.2) # draw parallels

m.drawmeridians(np.arange(x1,x2,5.),labels=[0,0,0,1],color='black',dashes=[1,0],labelstyle='+/-',linewidth=0.2) # draw meridians

m.drawmapboundary(fill_color='aqua')

x, y = m(lons.values,lats.values)

if(informative):

color_vec1 = ['k', 'b', 'g', 'y', 'r', 'm', 'c', 'w', 'c']

color_vec2 = ['#fff5eb','#fee6ce','#fdd0a2','#fdae6b','#fd8d3c',

'#f16913','#d94801','#a63603','#7f2704'] #sequential, single hue orange

color_vec3 = ['#f7fbff','#deebf7','#c6dbef','#9ecae1','#6baed6',

'#4292c6','#2171b5','#08519c','#08306b'] #sequential, single hue blue

color_vec4 = ['#d73027','#f46d43','#fdae61','#fee090','#ffffbf',

'#e0f3f8','#abd9e9','#74add1','#4575b4'] #diverging, colorb safe, use flipud

color_vec5 = ['#ffffd9','#edf8b1','#c7e9b4','#7fcdbb','#41b6c4',

'#1d91c0','#225ea8','#253494','#081d58']

color_vec4 = np.flipud(color_vec4)

#colorvar = gravs; coltype = 1; color_vec = color_vec2

#colorvar = lums-1; coltype = 2; color_vec = color_vec4

colorvar = atms-1; coltype = 3; color_vec = color_vec5

g_max = colorvar.max()

g_ave = colorvar.mean()

g_std = colorvar.std()

if(coltype==1):

#grav

sizfact = g_max/10

sizfact = g_ave/1

alpha_scl = 0.1 #grav

elif(coltype==2):

sizfact = g_ave/3

alpha_scl = 0.1 #atm

else:

#lum

sizfact = g_max/10

sizfact = g_ave/2

alpha_scl = 0.1 #atm

pCnt = 0

for x, y, g in zip(x,y,colorvar):

if(not(pCnt%1000)): print pCnt

if(coltype==1):

## grav

if g > g_ave + 3*g_std:

mark_col = 'r'

else:

mark_col = 'b'

elif(coltype==2):

mark_col = color_vec[g] #atm or lum

else:

try:

mark_col = color_vec[int(g)] #atm or lum

except TypeError as e:

print "I/O error({0}) ".format(e.message)

mark_col = 'w'

except:

print "Unexpected error:", sys.exc_info()[0]

mark_col = 'w'

#raise

pCnt += 1

m.plot(x, y, marker='.', markersize=g/sizfact, markerfacecolor=mark_col, linestyle='', alpha=0.1)

else:

m.plot(x, y, 'k.', alpha=alpha_scl)

plt.show(block=False)

#### include department borders from shapefile - http://www.gadm.org/ ####

def traceShape(file_shapefile):

return None

dir_shapefile = 'SHP/'

if(inc_deps):

file_shapefile = dir_shapefile + r"FRA_adm2.shp"

traceShape(file_shapefile)

if(inc_roads):

file_shapefile = dir_shapefile + r"RoadL.shp" #good

##too many roads - mapcruzin.com -OpenStreetMap data as of 2014-09-03T20:22:02Z courtesy of http://download.geofabrik.de

#file_shapefile = dir_shapefile + r"roads.shp"

traceShape(file_shapefile)

filename = 'carteFrance_' + colorvar.name + '.png'

plt.savefig(filename,dpi=300)

plt.show()