# -*- coding: utf-8 -*- import statsmodels.api as sm import statsmodels.formula.api as smf import csv import numpy as N import io import string from mpl_toolkits.basemap import Basemap import datetime from pandas import DataFrame, read_csv import matplotlib.pyplot as P import pandas as pd gi=N.genfromtxt('gitter04k.txt',usecols=(0),skip_header=0,dtype='i') lo=N.genfromtxt('gitter04k.txt',usecols=(1),skip_header=0,dtype='f') la=N.genfromtxt('gitter04k.txt',usecols=(2),skip_header=0,dtype='f') wi=N.genfromtxt('weinberglagen.csv', delimiter=',',skip_header=1,usecols=(0),dtype='S') yo=N.genfromtxt('weinberglagen.csv', delimiter=',',skip_header=1,usecols=(1),dtype='f') xo=N.genfromtxt('weinberglagen.csv', delimiter=',',skip_header=1,usecols=(2),dtype='f') nw = len(wi) P.figure(figsize=(7,5)) ax = P.subplot(111) m = Basemap(projection='merc', lon_0=10,lat_0=52, lat_ts=58, llcrnrlat=47.,urcrnrlat=55.0,llcrnrlon=5.0,urcrnrlon=16,resolution='h') m.drawcoastlines() m.drawlsmask(land_color = "lightgray",ocean_color="lightblue",resolution = 'h') m.drawcountries(linewidth=1.0) m.readshapefile('./shp/vg2500_bld', 'vg2500_bld', drawbounds=True) for i in range(nw): print wi[i],yo[i],xo[i] xx,yy = m(xo[i],yo[i]) m.scatter(xx,yy,s=3,c='m') distance = (lo-xo[i])**2 + (la-yo[i])**2 id = N.where(distance==distance.min()) file = str(gi[id][0]) dd=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(0),skip_header=1,dtype='i') mm=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(1),skip_header=1,dtype='i') jj=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(2),skip_header=1,dtype='i') tn=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(3),skip_header=1,dtype='f') tg=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(4),skip_header=1,dtype='f') tx=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(5),skip_header=1,dtype='f') ws=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(7),skip_header=1,dtype='f') so=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(8),skip_header=1,dtype='f') sn=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(9),skip_header=1,dtype='f') da=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(10),skip_header=1,dtype='f') lu=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(11),skip_header=1,dtype='f') rf=N.genfromtxt('../output_grid/'+file+'.dat',usecols=(12),skip_header=1,dtype='f') pr=N.genfromtxt('../../nied/output_grid/'+file+'.dat',usecols=(3),skip_header=1,dtype='f') it = N.where((jj>=2013)&(jj<=2017))[0] f = open(wi[i]+'.dat','w') f.write('%7s%7s%7s%7s%7s%7s%7s%7s%7s%7s%7s%7s%7s\n'%('ta','mo','jahr','tmin','tmit','tmax','wmit','sonn','snow','dadr','ludr','relf','nied')) for i in it: f.write('%7i%7i%7i%7.1f%7.1f%7.1f%7.1f%7.1f%7.1f%7.1f%7.1f%7.1f%7.1f\n'%(dd[i],mm[i],jj[i],tn[i],tg[i],tx[i],ws[i],so[i],sn[i],da[i],lu[i],rf[i],pr[i])) f.close() P.savefig('weinberglagen.png',dpi=240,bbox_inches='tight') ############################################# nd = 365 jo = [2013,2014,2015,2016,2017] do = N.arange(1,nd+1,1) P.figure(figsize=(12,6)) for i in range(nw): #P.figure(figsize=(12,6)) jj=N.genfromtxt(wi[i]+'.dat',usecols=(2),skip_header=1,dtype='i') tg=N.genfromtxt(wi[i]+'.dat',usecols=(4),skip_header=1,dtype='f') pr=N.genfromtxt(wi[i]+'.dat',usecols=(12),skip_header=1,dtype='f') P.subplot(121) for j in jo: id = N.where(jj==j)[0] dum = N.cumsum(tg[id]) if(j==2013): P.plot(do,dum[0:365],'k',label=str(j),lw=0.5) if(j==2014): P.plot(do,dum[0:365],'b',label=str(j),lw=0.5) if(j==2015): P.plot(do,dum[0:365],'g',label=str(j),lw=0.5) if(j==2016): P.plot(do,dum[0:365],'y',label=str(j),lw=0.5) if(j==2017): P.plot(do,dum[0:365],'r',label=str(j),lw=0.5) if(i==0): P.legend(loc=0) P.grid() P.ylim(-500,4500) P.xlim(0,366) P.xticks([30,60,90,120,150,180,210,240,270,300,330,360]) P.xlabel('Tag des Jahre',fontsize=20) P.ylabel('Temperatursumme',fontsize=20) P.title('Alle Weinberge',fontsize=20) P.subplot(122) for j in jo: id = N.where(jj==j)[0] dum = N.cumsum(pr[id]) if(j==2013): P.plot(do,dum[0:365],'k',label=str(j),lw=0.5) if(j==2014): P.plot(do,dum[0:365],'b',label=str(j),lw=0.5) if(j==2015): P.plot(do,dum[0:365],'g',label=str(j),lw=0.5) if(j==2016): P.plot(do,dum[0:365],'y',label=str(j),lw=0.5) if(j==2017): P.plot(do,dum[0:365],'r',label=str(j),lw=0.5) if(i==0): P.legend(loc=0) P.grid() P.ylim(0,800) P.xlim(0,366) P.xticks([30,60,90,120,150,180,210,240,270,300,330,360]) P.xlabel('Tag des Jahre',fontsize=20) P.ylabel('Niederschlagssumme',fontsize=20) P.title('Alle Weinberge',fontsize=20) P.savefig('summen.png',dpi=240,bbox_inches='tight') ############################################# for i in range(nw): P.figure(figsize=(12,6)) jj=N.genfromtxt(wi[i]+'.dat',usecols=(2),skip_header=1,dtype='i') tg=N.genfromtxt(wi[i]+'.dat',usecols=(4),skip_header=1,dtype='f') pr=N.genfromtxt(wi[i]+'.dat',usecols=(12),skip_header=1,dtype='f') P.subplot(121) for j in jo: id = N.where(jj==j)[0] dum = N.cumsum(tg[id]) if(j==2013): P.plot(do,dum[0:365],'k',label=str(j),lw=0.5) if(j==2014): P.plot(do,dum[0:365],'b',label=str(j),lw=0.5) if(j==2015): P.plot(do,dum[0:365],'g',label=str(j),lw=0.5) if(j==2016): P.plot(do,dum[0:365],'y',label=str(j),lw=0.5) if(j==2017): P.plot(do,dum[0:365],'r',label=str(j),lw=0.5) P.legend(loc=0) P.grid() P.ylim(-500,4500) P.xlim(0,366) P.xticks([30,60,90,120,150,180,210,240,270,300,330,360]) P.xlabel('Tag des Jahre',fontsize=20) P.ylabel('Temperatursumme',fontsize=20) P.title(wi[i],fontsize=20) P.subplot(122) for j in jo: id = N.where(jj==j)[0] dum = N.cumsum(pr[id]) if(j==2013): P.plot(do,dum[0:365],'k',label=str(j),lw=0.5) if(j==2014): P.plot(do,dum[0:365],'b',label=str(j),lw=0.5) if(j==2015): P.plot(do,dum[0:365],'g',label=str(j),lw=0.5) if(j==2016): P.plot(do,dum[0:365],'y',label=str(j),lw=0.5) if(j==2017): P.plot(do,dum[0:365],'r',label=str(j),lw=0.5) P.legend(loc=0) P.grid() P.ylim(0,800) P.xlim(0,366) P.xticks([30,60,90,120,150,180,210,240,270,300,330,360]) P.xlabel('Tag des Jahre',fontsize=20) P.ylabel('Niederschlagssumme',fontsize=20) P.title(wi[i],fontsize=20) P.savefig(wi[i]+'.png',dpi=120,bbox_inches='tight')