##################################################################################### #Code to create non-grid plots for paired objects. # #-Run runMODE.py first to create the netCDF files (modify mode_config for MODE sensitivity studies) #-Run createCSV.py to create a csv of paired objects #-Run createCSV_simpleobj.py to create a csv of simple objects #-Run plotting.py to create non-grid plots for paired objects #-Run plotting_grid.py to create grid plots for paired objects #-Run plotting_grid_simpleobj.py to create grid plots for simple objects (needs work) # #Created in the summer/fall of 2020 by CLC, editted by MJE on 20210601. #Additional modifications by AJ throughout summer of 2021. #Further documented by MJE. 20210921. # ###################################################################################### #!/usr/bin/python import pygrib import sys import subprocess import string import gzip import time import os #from netCDF4 import Dataset import numpy as np import datetime import csv import math import haversine import glob import cartopy.crs as ccrs # import projections import cartopy.feature as cf # import features import numpy as np import matplotlib as mpl import matplotlib.pyplot as pyplot mpl.use('Agg') #So plots can be saved in cron import matplotlib.pyplot as plt from windrose import WindroseAxes import matplotlib.cm as cm import cartopy_maps import importlib from scipy.io import netcdf from netCDF4 import Dataset from scipy import ndimage from scipy import stats from scipy import interpolate from mpl_toolkits.axes_grid1 import make_axes_locatable from scipy.ndimage.filters import gaussian_filter #Load predefined functions import METConFigGenV100 import METLoadEnsemble import METPlotEnsemble importlib.reload(METConFigGenV100) importlib.reload(METLoadEnsemble) importlib.reload(METPlotEnsemble) #######################LIST OF VARIABLES######################################################## FIG_DIR = 'hpc@vm-lnx-rzdm01:/home/people/hpc/ftp/erickson/lapenta/bar_graphs' FIG_DIR_ROSE = 'hpc@vm-lnx-rzdm01:/home/people/hpc/ftp/erickson/lapenta/rose' working_dir = '/export/hpc-lw-dtbdev5/merickson/code/python/lapenta/work/' validday = 1 ero_category = 'SLGT' ################################################################################################ #Define the output file latlon = working_dir+'latlon_vday'+str(validday)+'_ERO'+ero_category+'.csv' #initial lon_mod=[] lat_mod=[] lon_obs=[] lat_obs=[] date=[] valid=[] magnitude=[] angle=[] area_obs=[] area_mod=[] #jja lon_mod_jja=[] lat_mod_jja=[] lon_obs_jja=[] lat_obs_jja=[] date_jja=[] valid_jja=[] magnitude_jja=[] angle_jja=[] area_obs_jja=[] area_mod_jja=[] #son lon_mod_son=[] lat_mod_son=[] lon_obs_son=[] lat_obs_son=[] date_son=[] valid_son=[] magnitude_son=[] angle_son=[] area_obs_son=[] area_mod_son=[] #djf lon_mod_djf=[] lat_mod_djf=[] lon_obs_djf=[] lat_obs_djf=[] date_djf=[] valid_djf=[] magnitude_djf=[] angle_djf=[] area_obs_djf=[] area_mod_djf=[] #mam lon_mod_mam=[] lat_mod_mam=[] lon_obs_mam=[] lat_obs_mam=[] date_mam=[] valid_mam=[] magnitude_mam=[] angle_mam=[] area_obs_mam=[] area_mod_mam=[] target=open(latlon,'r') alllines=target.readlines() for line in alllines: values=line.strip().split(',') date=np.append(date,float(values[0][0:8])) valid=np.append(valid,values[1]) lat_mod=np.append(lat_mod,float(values[2])) lon_mod=np.append(lon_mod,float(values[3])) area_mod=np.append(area_mod,float(values[4])) lat_obs=np.append(lat_obs,float(values[5])) lon_obs=np.append(lon_obs,float(values[6])) area_obs=np.append(area_obs,float(values[7])) magnitude=np.append(magnitude,float(values[8])) angle=np.append(angle,float(values[9])) #June,July,August if np.float(values[0][4:6])==6 or np.float(values[0][4:6])==7 or np.float(values[0][4:6])==8: #print('jja') #print(values[0][0:8]) date_jja=np.append(date_jja,float(values[0][0:8])) valid_jja=np.append(valid_jja,values[1]) lat_mod_jja=np.append(lat_mod_jja,float(values[2])) lon_mod_jja=np.append(lon_mod_jja,float(values[3])) area_mod_jja=np.append(area_mod_jja,float(values[4])) lat_obs_jja=np.append(lat_obs_jja,float(values[5])) lon_obs_jja=np.append(lon_obs_jja,float(values[6])) area_obs_jja=np.append(area_obs_jja,float(values[7])) magnitude_jja=np.append(magnitude_jja,float(values[8])) angle_jja=np.append(angle_jja,float(values[9])) #September,October,November elif np.float(values[0][4:6])==9 or np.float(values[0][4:6])==10 or np.float(values[0][4:6])==11: #print('son') #print(values[0][0:8]) date_son=np.append(date_son,float(values[0][0:8])) valid_son=np.append(valid_son,values[1]) lat_mod_son=np.append(lat_mod_son,float(values[2])) lon_mod_son=np.append(lon_mod_son,float(values[3])) area_mod_son=np.append(area_mod_son,float(values[4])) lat_obs_son=np.append(lat_obs_son,float(values[5])) lon_obs_son=np.append(lon_obs_son,float(values[6])) area_obs_son=np.append(area_obs_son,float(values[7])) magnitude_son=np.append(magnitude_son,float(values[8])) angle_son=np.append(angle_son,float(values[9])) #December,Jan,Feb elif np.float(values[0][4:6])==12 or np.float(values[0][4:6])==1 or np.float(values[0][4:6])==2: #print('djf') #print(values[0][0:8]) date_djf=np.append(date_djf,float(values[0][0:8])) valid_djf=np.append(valid_djf,values[1]) lat_mod_djf=np.append(lat_mod_djf,float(values[2])) lon_mod_djf=np.append(lon_mod_djf,float(values[3])) area_mod_djf=np.append(area_mod_djf,float(values[4])) lat_obs_djf=np.append(lat_obs_djf,float(values[5])) lon_obs_djf=np.append(lon_obs_djf,float(values[6])) area_obs_djf=np.append(area_obs_djf,float(values[7])) magnitude_djf=np.append(magnitude_djf,float(values[8])) angle_djf=np.append(angle_djf,float(values[9])) #March,April,May elif np.float(values[0][4:6])==3 or np.float(values[0][4:6])==4 or np.float(values[0][4:6])==5: #print('mam') #print(values[0][0:8]) date_mam=np.append(date_mam,float(values[0][0:8])) valid_mam=np.append(valid_mam,values[1]) lat_mod_mam=np.append(lat_mod_mam,float(values[2])) lon_mod_mam=np.append(lon_mod_mam,float(values[3])) area_mod_mam=np.append(area_mod_mam,float(values[4])) lat_obs_mam=np.append(lat_obs_mam,float(values[5])) lon_obs_mam=np.append(lon_obs_mam,float(values[6])) area_obs_mam=np.append(area_obs_mam,float(values[7])) magnitude_mam=np.append(magnitude_mam,float(values[8])) angle_mam=np.append(angle_mam,float(values[9])) if ero_category=='SLGT': bin = [0,50,100,150,200,250,300,350,400,450,500] elif ero_category=='MDT': bin = [0,25,50,75,100,125,150,175,200,250,300] elif ero_category=='HIGH': bin = [0,20,40,60,80,100,120,140,160,170,180] ####################################Displacement calculations and plotting###################################################################################### #southern plains jja date_jja_sp=[] valid_jja_sp=[] lon_mod_jja_sp=[] lat_mod_jja_sp=[] area_mod_jja_sp=[] lon_obs_jja_sp=[] lat_obs_jja_sp=[] area_obs_jja_sp=[] magnitude_jja_sp=[] angle_jja_sp=[] for ele in range(0,len(date_jja)): if lat_obs_jja[ele] > 25 and lat_obs_jja[ele] <= 38 and lon_obs_jja[ele] > -105 and lon_obs_jja[ele] <= -90 \ and lat_mod_jja[ele] > 25 and lat_mod_jja[ele] <= 38 and lon_mod_jja[ele] > -105 and lon_mod_jja[ele] <= -90: date_jja_sp=np.append(date_jja_sp,date_jja[ele]) valid_jja_sp=np.append(valid_jja_sp,valid_jja[ele]) lat_mod_jja_sp=np.append(lat_mod_jja_sp,lat_mod_jja[ele]) lon_mod_jja_sp=np.append(lon_mod_jja_sp,lon_mod_jja[ele]) area_mod_jja_sp=np.append(area_mod_jja_sp,area_mod_jja[ele]) lat_obs_jja_sp=np.append(lat_obs_jja_sp,lat_obs_jja[ele]) lon_obs_jja_sp=np.append(lon_obs_jja_sp,lon_obs_jja[ele]) area_obs_jja_sp=np.append(area_obs_jja_sp,area_obs_jja[ele]) magnitude_jja_sp=np.append(magnitude_jja_sp,magnitude_jja[ele]) angle_jja_sp=np.append(angle_jja_sp,angle_jja[ele]) #print(lat_obs_jja_sp) #print(lon_obs_jja_sp) if len(angle_jja_sp) > 0: #windrose plotting jja southern plains ax = WindroseAxes.from_ax() ax.bar(angle_jja_sp, magnitude_jja_sp, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southern Plains JJA',fontsize=14) plt.savefig(working_dir+'rose_jja_sp_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_sp_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southern plains son date_son_sp=[] valid_son_sp=[] lon_mod_son_sp=[] lat_mod_son_sp=[] area_mod_son_sp=[] lon_obs_son_sp=[] lat_obs_son_sp=[] area_obs_son_sp=[] magnitude_son_sp=[] angle_son_sp=[] for ele in range(0,len(date_son)): if lat_obs_son[ele] > 25 and lat_obs_son[ele] <= 38 and lon_obs_son[ele] > -105 and lon_obs_son[ele] <= -90\ and lat_mod_son[ele] > 25 and lat_mod_son[ele] <= 38 and lon_mod_son[ele] > -105 and lon_mod_son[ele] <= -90: date_son_sp=np.append(date_son_sp,date_son[ele]) valid_son_sp=np.append(valid_son_sp,valid_son[ele]) lat_mod_son_sp=np.append(lat_mod_son_sp,lat_mod_son[ele]) lon_mod_son_sp=np.append(lon_mod_son_sp,lon_mod_son[ele]) area_mod_son_sp=np.append(area_mod_son_sp,area_mod_son[ele]) lat_obs_son_sp=np.append(lat_obs_son_sp,lat_obs_son[ele]) lon_obs_son_sp=np.append(lon_obs_son_sp,lon_obs_son[ele]) area_obs_son_sp=np.append(area_obs_son_sp,area_obs_son[ele]) magnitude_son_sp=np.append(magnitude_son_sp,magnitude_son[ele]) angle_son_sp=np.append(angle_son_sp,angle_son[ele]) #print(lat_obs_son_sp) #print(lon_obs_son_sp) if len(angle_son_sp) > 0: #windrose plotting son southern plains ax = WindroseAxes.from_ax() ax.bar(angle_son_sp, magnitude_son_sp, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southern Plains SON',fontsize=14) plt.savefig(working_dir+'rose_son_sp_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_sp_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southern plains djf date_djf_sp=[] valid_djf_sp=[] lon_mod_djf_sp=[] lat_mod_djf_sp=[] area_mod_djf_sp=[] lon_obs_djf_sp=[] lat_obs_djf_sp=[] area_obs_djf_sp=[] magnitude_djf_sp=[] angle_djf_sp=[] for ele in range(0,len(date_djf)): if lat_obs_djf[ele] > 25 and lat_obs_djf[ele] <= 38 and lon_obs_djf[ele] > -105 and lon_obs_djf[ele] <= -90\ and lat_mod_djf[ele] > 25 and lat_mod_djf[ele] <= 38 and lon_mod_djf[ele] > -105 and lon_mod_djf[ele] <= -90: date_djf_sp=np.append(date_djf_sp,date_djf[ele]) valid_djf_sp=np.append(valid_djf_sp,valid_djf[ele]) lat_mod_djf_sp=np.append(lat_mod_djf_sp,lat_mod_djf[ele]) lon_mod_djf_sp=np.append(lon_mod_djf_sp,lon_mod_djf[ele]) area_mod_djf_sp=np.append(area_mod_djf_sp,area_mod_djf[ele]) lat_obs_djf_sp=np.append(lat_obs_djf_sp,lat_obs_djf[ele]) lon_obs_djf_sp=np.append(lon_obs_djf_sp,lon_obs_djf[ele]) area_obs_djf_sp=np.append(area_obs_djf_sp,area_obs_djf[ele]) magnitude_djf_sp=np.append(magnitude_djf_sp,magnitude_djf[ele]) angle_djf_sp=np.append(angle_djf_sp,angle_djf[ele]) #print(lat_obs_djf_sp) #print(lon_obs_djf_sp) if len(angle_djf_sp) > 0: #windrose plotting djf southern plains ax = WindroseAxes.from_ax() ax.bar(angle_djf_sp, magnitude_djf_sp, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southern Plains DJF',fontsize=14) plt.savefig(working_dir+'rose_djf_sp_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_sp_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southern plains mam date_mam_sp=[] valid_mam_sp=[] lon_mod_mam_sp=[] lat_mod_mam_sp=[] area_mod_mam_sp=[] lon_obs_mam_sp=[] lat_obs_mam_sp=[] area_obs_mam_sp=[] magnitude_mam_sp=[] angle_mam_sp=[] for ele in range(0,len(date_mam)): if lat_obs_mam[ele] > 25 and lat_obs_mam[ele] <= 38 and lon_obs_mam[ele] > -105 and lon_obs_mam[ele] <= -90 \ and lat_mod_mam[ele] > 25 and lat_mod_mam[ele] <= 38 and lon_mod_mam[ele] > -105 and lon_mod_mam[ele] <= -90: date_mam_sp=np.append(date_mam_sp,date_mam[ele]) valid_mam_sp=np.append(valid_mam_sp,valid_mam[ele]) lat_mod_mam_sp=np.append(lat_mod_mam_sp,lat_mod_mam[ele]) lon_mod_mam_sp=np.append(lon_mod_mam_sp,lon_mod_mam[ele]) area_mod_mam_sp=np.append(area_mod_mam_sp,area_mod_mam[ele]) lat_obs_mam_sp=np.append(lat_obs_mam_sp,lat_obs_mam[ele]) lon_obs_mam_sp=np.append(lon_obs_mam_sp,lon_obs_mam[ele]) area_obs_mam_sp=np.append(area_obs_mam_sp,area_obs_mam[ele]) magnitude_mam_sp=np.append(magnitude_mam_sp,magnitude_mam[ele]) angle_mam_sp=np.append(angle_mam_sp,angle_mam[ele]) if len(angle_mam_sp) > 0: #windrose plotting mam southern plains ax = WindroseAxes.from_ax() ax.bar(angle_mam_sp, magnitude_mam_sp, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southern Plains MAM',fontsize=14) plt.savefig(working_dir+'rose_mam_sp_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_sp_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northern plains jja date_jja_np=[] valid_jja_np=[] lon_mod_jja_np=[] lat_mod_jja_np=[] area_mod_jja_np=[] lon_obs_jja_np=[] lat_obs_jja_np=[] area_obs_jja_np=[] magnitude_jja_np=[] angle_jja_np=[] for ele in range(0,len(date_jja)): if lat_obs_jja[ele] > 38 and lat_obs_jja[ele] <= 50 and lon_obs_jja[ele] > -105 and lon_obs_jja[ele] <= -90 \ and lat_mod_jja[ele] > 38 and lat_mod_jja[ele] <= 50 and lon_mod_jja[ele] > -105 and lon_mod_jja[ele] <= -90: date_jja_np=np.append(date_jja_sp,date_jja[ele]) valid_jja_np=np.append(valid_jja_np,valid_jja[ele]) lat_mod_jja_np=np.append(lat_mod_jja_np,lat_mod_jja[ele]) lon_mod_jja_np=np.append(lon_mod_jja_np,lon_mod_jja[ele]) area_mod_jja_np=np.append(area_mod_jja_np,area_mod_jja[ele]) lat_obs_jja_np=np.append(lat_obs_jja_np,lat_obs_jja[ele]) lon_obs_jja_np=np.append(lon_obs_jja_np,lon_obs_jja[ele]) area_obs_jja_np=np.append(area_obs_jja_np,area_obs_jja[ele]) magnitude_jja_np=np.append(magnitude_jja_np,magnitude_jja[ele]) angle_jja_np=np.append(angle_jja_np,angle_jja[ele]) #print(area_obs_jja_np) if len(angle_jja_np) > 0: #windrose plotting jja northern plains ax = WindroseAxes.from_ax() ax.bar(angle_jja_np, magnitude_jja_np, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northern Plains JJA',fontsize=14) plt.savefig(working_dir+'rose_jja_np_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_np_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northern plains son date_son_np=[] valid_son_np=[] lon_mod_son_np=[] lat_mod_son_np=[] area_mod_son_np=[] lon_obs_son_np=[] lat_obs_son_np=[] area_obs_son_np=[] magnitude_son_np=[] angle_son_np=[] for ele in range(0,len(date_son)): if lat_obs_son[ele] > 38 and lat_obs_son[ele] <= 50 and lon_obs_son[ele] > -105 and lon_obs_son[ele] <= -90\ and lat_mod_son[ele] > 38 and lat_mod_son[ele] <= 50 and lon_mod_son[ele] > -105 and lon_mod_son[ele] <= -90: date_son_np=np.append(date_son_np,date_son[ele]) valid_son_np=np.append(valid_son_np,valid_son[ele]) lon_mod_son_np=np.append(lon_mod_son_np,lon_mod_son[ele]) lat_mod_son_np=np.append(lat_mod_son_np,lat_mod_son[ele]) area_mod_son_np=np.append(area_mod_son_np,area_mod_son[ele]) lat_obs_son_np=np.append(lat_obs_son_np,lat_obs_son[ele]) lon_obs_son_np=np.append(lon_obs_son_np,lon_obs_son[ele]) area_obs_son_np=np.append(area_obs_son_np,area_obs_son[ele]) magnitude_son_np=np.append(magnitude_son_np,magnitude_son[ele]) angle_son_np=np.append(angle_son_np,angle_son[ele]) if len(angle_son_np) > 0: #windrose plotting son northern plains ax = WindroseAxes.from_ax() ax.bar(angle_son_np, magnitude_son_np, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northern Plains SON',fontsize=14) plt.savefig(working_dir+'rose_son_np_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_np_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northern plains djf date_djf_np=[] valid_djf_np=[] lon_mod_djf_np=[] lat_mod_djf_np=[] area_mod_djf_np=[] lon_obs_djf_np=[] lat_obs_djf_np=[] area_obs_djf_np=[] magnitude_djf_np=[] angle_djf_np=[] for ele in range(0,len(date_djf)): if lat_obs_djf[ele] > 38 and lat_obs_djf[ele] <= 50 and lon_obs_djf[ele] > -105 and lon_obs_djf[ele] <= -90\ and lat_mod_djf[ele] > 38 and lat_mod_djf[ele] <= 50 and lon_mod_djf[ele] > -105 and lon_mod_djf[ele] <= -90: date_djf_np=np.append(date_djf_np,date_djf[ele]) valid_djf_np=np.append(valid_djf_np,valid_djf[ele]) lat_mod_djf_np=np.append(lat_mod_djf_np,lat_mod_djf[ele]) lon_mod_djf_np=np.append(lon_mod_djf_np,lon_mod_djf[ele]) area_mod_djf_np=np.append(area_mod_djf_np,area_mod_djf[ele]) lat_obs_djf_np=np.append(lat_obs_djf_np,lat_obs_djf[ele]) lon_obs_djf_np=np.append(lon_obs_djf_np,lon_obs_djf[ele]) area_obs_djf_np=np.append(area_obs_djf_np,area_obs_djf[ele]) magnitude_djf_np=np.append(magnitude_djf_np,magnitude_djf[ele]) angle_djf_np=np.append(angle_djf_np,angle_djf[ele]) #print(area_mod_djf_np) if len(angle_djf_np) > 0: #windrose plotting djf northern plains ax = WindroseAxes.from_ax() ax.bar(angle_djf_np, magnitude_djf_np, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northern Plains DJF',fontsize=14) plt.savefig(working_dir+'rose_djf_np_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_np_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northern plains mam date_mam_np=[] valid_mam_np=[] lon_mod_mam_np=[] lat_mod_mam_np=[] area_mod_mam_np=[] lon_obs_mam_np=[] lat_obs_mam_np=[] area_obs_mam_np=[] magnitude_mam_np=[] angle_mam_np=[] for ele in range(0,len(date_mam)): if lat_obs_mam[ele] > 38 and lat_obs_mam[ele] <= 50 and lon_obs_mam[ele] > -105 and lon_obs_mam[ele] <= -90\ and lat_mod_mam[ele] > 38 and lat_mod_mam[ele] <= 50 and lon_mod_mam[ele] > -105 and lon_mod_mam[ele] <= -90: date_mam_np=np.append(date_mam_np,date_mam[ele]) valid_mam_np=np.append(valid_mam_np,valid_mam[ele]) lat_mod_mam_np=np.append(lat_mod_mam_np,lat_mod_mam[ele]) lon_mod_mam_np=np.append(lon_mod_mam_np,lon_mod_mam[ele]) area_mod_mam_np=np.append(area_mod_mam_np,area_mod_mam[ele]) lat_obs_mam_np=np.append(lat_obs_mam_np,lat_obs_mam[ele]) lon_obs_mam_np=np.append(lon_obs_mam_np,lon_obs_mam[ele]) area_obs_mam_np=np.append(area_obs_mam_np,area_obs_mam[ele]) magnitude_mam_np=np.append(magnitude_mam_np,magnitude_mam[ele]) angle_mam_np=np.append(angle_mam_np,angle_mam[ele]) if len(angle_mam_np) > 0: #windrose plotting mam northern plains ax = WindroseAxes.from_ax() ax.bar(angle_mam_np, magnitude_mam_np, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northern Plains MAM',fontsize=14) plt.savefig(working_dir+'rose_mam_np_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_np_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southeast jja date_jja_se=[] valid_jja_se=[] lon_mod_jja_se=[] lat_mod_jja_se=[] area_mod_jja_se=[] lon_obs_jja_se=[] lat_obs_jja_se=[] area_obs_jja_se=[] magnitude_jja_se=[] angle_jja_se=[] for ele in range(0,len(date_jja)): if lat_obs_jja[ele] > 20 and lat_obs_jja[ele] <= 38 and lon_obs_jja[ele] > -90 and lon_obs_jja[ele] <= -75\ and lat_mod_jja[ele] > 20 and lat_mod_jja[ele] <= 38 and lon_mod_jja[ele] > -90 and lon_mod_jja[ele] <= -75: date_jja_se=np.append(date_jja_se,date_jja[ele]) valid_jja_se=np.append(valid_jja_se,valid_jja[ele]) lat_mod_jja_se=np.append(lat_mod_jja_se,lat_mod_jja[ele]) lon_mod_jja_se=np.append(lon_mod_jja_se,lon_mod_jja[ele]) area_mod_jja_se=np.append(area_mod_jja_se,area_mod_jja[ele]) lat_obs_jja_se=np.append(lat_obs_jja_se,lat_obs_jja[ele]) lon_obs_jja_se=np.append(lon_obs_jja_se,lon_obs_jja[ele]) area_obs_jja_se=np.append(area_obs_jja_se,area_obs_jja[ele]) magnitude_jja_se=np.append(magnitude_jja_se,magnitude_jja[ele]) angle_jja_se=np.append(angle_jja_se,angle_jja[ele]) if len(angle_jja_se) > 0: #windrose plotting jja southeast ax = WindroseAxes.from_ax() ax.bar(angle_jja_se, magnitude_jja_se, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southeast JJA',fontsize=14) plt.savefig(working_dir+'rose_jja_se_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_se_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southeast son date_son_se=[] valid_son_se=[] lon_mod_son_se=[] lat_mod_son_se=[] area_mod_son_se=[] lon_obs_son_se=[] lat_obs_son_se=[] area_obs_son_se=[] magnitude_son_se=[] angle_son_se=[] for ele in range(0,len(date_son)): if lat_obs_son[ele] > 20 and lat_obs_son[ele] <= 38 and lon_obs_son[ele] > -90 and lon_obs_son[ele] <= -75\ and lat_mod_son[ele] > 20 and lat_mod_son[ele] <= 38 and lon_mod_son[ele] > -90 and lon_mod_son[ele] <= -75: date_son_se=np.append(date_son_se,date_son[ele]) valid_son_se=np.append(valid_son_se,valid_son[ele]) lat_mod_son_se=np.append(lat_mod_son_se,lat_mod_son[ele]) lon_mod_son_se=np.append(lon_mod_son_se,lon_mod_son[ele]) area_mod_son_se=np.append(area_mod_son_se,area_mod_son[ele]) lat_obs_son_se=np.append(lat_obs_son_se,lat_obs_son[ele]) lon_obs_son_se=np.append(lon_obs_son_se,lon_obs_son[ele]) area_obs_son_se=np.append(area_obs_son_se,area_obs_son[ele]) magnitude_son_se=np.append(magnitude_son_se,magnitude_son[ele]) angle_son_se=np.append(angle_son_se,angle_son[ele]) if len(angle_son_se) > 0: #windrose plotting son southeast ax = WindroseAxes.from_ax() ax.bar(angle_son_se, magnitude_son_se, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southeast SON',fontsize=14) plt.savefig(working_dir+'rose_son_se_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_se_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southeast djf date_djf_se=[] valid_djf_se=[] lat_mod_djf_se=[] lon_mod_djf_se=[] area_mod_djf_se=[] lon_obs_djf_se=[] lat_obs_djf_se=[] area_obs_djf_se=[] magnitude_djf_se=[] angle_djf_se=[] for ele in range(0,len(date_djf)): if lat_obs_djf[ele] > 20 and lat_obs_djf[ele] <= 38 and lon_obs_djf[ele] > -90 and lon_obs_djf[ele] <= -75\ and lat_mod_djf[ele] > 20 and lat_mod_djf[ele] <= 38 and lon_mod_djf[ele] > -90 and lon_mod_djf[ele] <= -75: date_djf_se=np.append(date_djf_se,date_djf[ele]) valid_djf_se=np.append(valid_djf_se,valid_djf[ele]) lat_mod_djf_se=np.append(lat_mod_djf_se,lat_mod_djf[ele]) lon_mod_djf_se=np.append(lon_mod_djf_se,lon_mod_djf[ele]) area_mod_djf_se=np.append(area_mod_djf_se,area_mod_djf[ele]) lat_obs_djf_se=np.append(lat_obs_djf_se,lat_obs_djf[ele]) lon_obs_djf_se=np.append(lon_obs_djf_se,lon_obs_djf[ele]) area_obs_djf_se=np.append(area_obs_djf_se,area_obs_djf[ele]) magnitude_djf_se=np.append(magnitude_djf_se,magnitude_djf[ele]) angle_djf_se=np.append(angle_djf_se,angle_djf[ele]) if len(angle_djf_se) > 0: #windrose plotting djf southeast ax = WindroseAxes.from_ax() ax.bar(angle_djf_se, magnitude_djf_se, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southeast DJF',fontsize=14) plt.savefig(working_dir+'rose_djf_se_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_se_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southeast mam date_mam_se=[] valid_mam_se=[] lon_mod_mam_se=[] lat_mod_mam_se=[] area_mod_mam_se=[] lon_obs_mam_se=[] lat_obs_mam_se=[] area_obs_mam_se=[] magnitude_mam_se=[] angle_mam_se=[] for ele in range(0,len(date_mam)): if lat_obs_mam[ele] > 20 and lat_obs_mam[ele] <= 38 and lon_obs_mam[ele] > -90 and lon_obs_mam[ele] <= -75\ and lat_mod_mam[ele] > 20 and lat_mod_mam[ele] <= 38 and lon_mod_mam[ele] > -90 and lon_mod_mam[ele] <= -75: date_mam_se=np.append(date_mam_se,date_mam[ele]) valid_mam_se=np.append(valid_mam_se,valid_mam[ele]) lat_mod_mam_se=np.append(lat_mod_mam_se,lat_mod_mam[ele]) lon_mod_mam_se=np.append(lon_mod_mam_se,lon_mod_mam[ele]) area_mod_mam_se=np.append(area_mod_mam_se,area_mod_mam[ele]) lat_obs_mam_se=np.append(lat_obs_mam_se,lat_obs_mam[ele]) lon_obs_mam_se=np.append(lon_obs_mam_se,lon_obs_mam[ele]) area_obs_mam_se=np.append(area_obs_mam_se,area_obs_mam[ele]) magnitude_mam_se=np.append(magnitude_mam_se,magnitude_mam[ele]) angle_mam_se=np.append(angle_mam_se,angle_mam[ele]) if len(angle_mam_se) > 0: #windrose plotting mam southeast ax = WindroseAxes.from_ax() ax.bar(angle_mam_se, magnitude_mam_se, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southeast MAM',fontsize=14) plt.savefig(working_dir+'rose_mam_se_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_se_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northeast jja date_jja_ne=[] valid_jja_ne=[] lon_mod_jja_ne=[] lat_mod_jja_ne=[] area_mod_jja_ne=[] lon_obs_jja_ne=[] lat_obs_jja_ne=[] area_obs_jja_ne=[] magnitude_jja_ne=[] angle_jja_ne=[] for ele in range(0,len(date_jja)): if lat_obs_jja[ele] > 38 and lat_obs_jja[ele] <= 50 and lon_obs_jja[ele] > -90 and lon_obs_jja[ele] <= -65\ and lat_mod_jja[ele] > 38 and lat_mod_jja[ele] <= 50 and lon_mod_jja[ele] > -90 and lon_mod_jja[ele] <= -65: date_jja_ne=np.append(date_jja_ne,date_jja[ele]) valid_jja_ne=np.append(valid_jja_ne,valid_jja[ele]) lat_mod_jja_ne=np.append(lat_mod_jja_ne,lat_mod_jja[ele]) lon_mod_jja_ne=np.append(lon_mod_jja_ne,lon_mod_jja[ele]) area_mod_jja_ne=np.append(area_mod_jja_ne,area_mod_jja[ele]) lat_obs_jja_ne=np.append(lat_obs_jja_ne,lat_obs_jja[ele]) lon_obs_jja_ne=np.append(lon_obs_jja_ne,lon_obs_jja[ele]) area_obs_jja_ne=np.append(area_obs_jja_ne,area_obs_jja[ele]) magnitude_jja_ne=np.append(magnitude_jja_ne,magnitude_jja[ele]) angle_jja_ne=np.append(angle_jja_ne,angle_jja[ele]) if len(angle_jja_ne) > 0: #windrose plotting jja northeast ax = WindroseAxes.from_ax() ax.bar(angle_jja_ne, magnitude_jja_ne, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northeast JJA',fontsize=14) plt.savefig(working_dir+'rose_jja_ne_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_ne_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northeast son date_son_ne=[] valid_son_ne=[] lon_mod_son_ne=[] lat_mod_son_ne=[] area_mod_son_ne=[] lon_obs_son_ne=[] lat_obs_son_ne=[] area_obs_son_ne=[] magnitude_son_ne=[] angle_son_ne=[] for ele in range(0,len(date_son)): if lat_obs_son[ele] > 38 and lat_obs_son[ele] <= 50 and lon_obs_son[ele] > -90 and lon_obs_son[ele] <= -65\ and lat_mod_son[ele] > 38 and lat_mod_son[ele] <= 50 and lon_mod_son[ele] > -90 and lon_mod_son[ele] <= -65: date_son_ne=np.append(date_son_ne,date_son[ele]) valid_son_ne=np.append(valid_son_ne,valid_son[ele]) lat_mod_son_ne=np.append(lat_mod_son_ne,lat_mod_son[ele]) lon_mod_son_ne=np.append(lon_mod_son_ne,lon_mod_son[ele]) area_mod_son_ne=np.append(area_mod_son_ne,area_mod_son[ele]) lat_obs_son_ne=np.append(lat_obs_son_ne,lat_obs_son[ele]) lon_obs_son_ne=np.append(lon_obs_son_ne,lon_obs_son[ele]) area_obs_son_ne=np.append(area_obs_son_ne,area_obs_son[ele]) magnitude_son_ne=np.append(magnitude_son_ne,magnitude_son[ele]) angle_son_ne=np.append(angle_son_ne,angle_son[ele]) if len(angle_son_ne) > 0: #windrose plotting son northeast ax = WindroseAxes.from_ax() ax.bar(angle_son_ne, magnitude_son_ne, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northeast SON',fontsize=14) plt.savefig(working_dir+'rose_son_ne_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_ne_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northeast djf date_djf_ne=[] valid_djf_ne=[] lon_mod_djf_ne=[] lat_mod_djf_ne=[] area_mod_djf_ne=[] lon_obs_djf_ne=[] lat_obs_djf_ne=[] area_obs_djf_ne=[] magnitude_djf_ne=[] angle_djf_ne=[] for ele in range(0,len(date_djf)): if lat_obs_djf[ele] > 38 and lat_obs_djf[ele] <= 50 and lon_obs_djf[ele] > -90 and lon_obs_djf[ele] <= -65\ and lat_mod_djf[ele] > 38 and lat_mod_djf[ele] <= 50 and lon_mod_djf[ele] > -90 and lon_mod_djf[ele] <= -65: date_djf_ne=np.append(date_djf_ne,date_djf[ele]) valid_djf_ne=np.append(valid_djf_ne,valid_djf[ele]) lat_mod_djf_ne=np.append(lat_mod_djf_ne,lat_mod_djf[ele]) lon_mod_djf_ne=np.append(lon_mod_djf_ne,lon_mod_djf[ele]) area_mod_djf_ne=np.append(area_mod_djf_ne,area_mod_djf[ele]) lat_obs_djf_ne=np.append(lat_obs_djf_ne,lat_obs_djf[ele]) lon_obs_djf_ne=np.append(lon_obs_djf_ne,lon_obs_djf[ele]) area_obs_djf_ne=np.append(area_obs_djf_ne,area_obs_djf[ele]) magnitude_djf_ne=np.append(magnitude_djf_ne,magnitude_djf[ele]) angle_djf_ne=np.append(angle_djf_ne,angle_djf[ele]) if len(angle_djf_ne) > 0: #windrose plotting djf northeast ax = WindroseAxes.from_ax() ax.bar(angle_djf_ne, magnitude_djf_ne, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northeast DJF',fontsize=14) plt.savefig(working_dir+'rose_djf_ne_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_ne_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northeast mam date_mam_ne=[] valid_mam_ne=[] lon_mod_mam_ne=[] lat_mod_mam_ne=[] area_mod_mam_ne=[] lon_obs_mam_ne=[] lat_obs_mam_ne=[] area_obs_mam_ne=[] magnitude_mam_ne=[] angle_mam_ne=[] for ele in range(0,len(date_mam)): if lat_obs_mam[ele] > 38 and lat_obs_mam[ele] <= 50 and lon_obs_mam[ele] > -90 and lon_obs_mam[ele] <= -65\ and lat_mod_mam[ele] > 38 and lat_mod_mam[ele] <= 50 and lon_mod_mam[ele] > -90 and lon_mod_mam[ele] <= -65: date_mam_ne=np.append(date_mam_ne,date_mam[ele]) valid_mam_ne=np.append(valid_mam_ne,valid_mam[ele]) lat_mod_mam_ne=np.append(lat_mod_mam_ne,lat_mod_mam[ele]) lon_mod_mam_ne=np.append(lon_mod_mam_ne,lon_mod_mam[ele]) area_mod_mam_ne=np.append(area_mod_mam_ne,area_mod_mam[ele]) lat_obs_mam_ne=np.append(lat_obs_mam_ne,lat_obs_mam[ele]) lon_obs_mam_ne=np.append(lon_obs_mam_ne,lon_obs_mam[ele]) area_obs_mam_ne=np.append(area_obs_mam_ne,area_obs_mam[ele]) magnitude_mam_ne=np.append(magnitude_mam_ne,magnitude_mam[ele]) angle_mam_ne=np.append(angle_mam_ne,angle_mam[ele]) if len(angle_mam_ne) > 0: #windrose plotting mam northeast ax = WindroseAxes.from_ax() ax.bar(angle_mam_ne, magnitude_mam_ne, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northeast MAM',fontsize=14) plt.savefig(working_dir+'rose_mam_ne_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_ne_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #west jja date_jja_we=[] valid_jja_we=[] lon_mod_jja_we=[] lat_mod_jja_we=[] area_mod_jja_we=[] lon_obs_jja_we=[] lat_obs_jja_we=[] area_obs_jja_we=[] magnitude_jja_we=[] angle_jja_we=[] for ele in range(0,len(date_jja)): if lat_obs_jja[ele] > 30 and lat_obs_jja[ele] <= 50 and lon_obs_jja[ele] > -125 and lon_obs_jja[ele] <= -105\ and lat_mod_jja[ele] > 30 and lat_mod_jja[ele] <= 50 and lon_mod_jja[ele] > -125 and lon_mod_jja[ele] <= -105: date_jja_we=np.append(date_jja_we,date_jja[ele]) valid_jja_we=np.append(valid_jja_we,valid_jja[ele]) lat_mod_jja_we=np.append(lat_mod_jja_we,lat_mod_jja[ele]) lon_mod_jja_we=np.append(lon_mod_jja_we,lon_mod_jja[ele]) area_mod_jja_we=np.append(area_mod_jja_we,area_mod_jja[ele]) lat_obs_jja_we=np.append(lat_obs_jja_we,lat_obs_jja[ele]) lon_obs_jja_we=np.append(lon_obs_jja_we,lon_obs_jja[ele]) area_obs_jja_we=np.append(area_obs_jja_we,area_obs_jja[ele]) magnitude_jja_we=np.append(magnitude_jja_we,magnitude_jja[ele]) angle_jja_we=np.append(angle_jja_we,angle_jja[ele]) if len(angle_jja_we) > 0: #windrose plotting jja west ax = WindroseAxes.from_ax() ax.bar(angle_jja_we, magnitude_jja_we, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Western Region JJA',fontsize=14) plt.savefig(working_dir+'rose_jja_we_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_we_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #west son date_son_we=[] valid_son_we=[] lon_mod_son_we=[] lat_mod_son_we=[] area_mod_son_we=[] lon_obs_son_we=[] lat_obs_son_we=[] area_obs_son_we=[] magnitude_son_we=[] angle_son_we=[] for ele in range(0,len(date_son)): if lat_obs_son[ele] > 30 and lat_obs_son[ele] <= 50 and lon_obs_son[ele] > -125 and lon_obs_son[ele] <= -105\ and lat_mod_son[ele] > 30 and lat_mod_son[ele] <= 50 and lon_mod_son[ele] > -125 and lon_mod_son[ele] <= -105: date_son_we=np.append(date_son_we,date_son[ele]) valid_son_we=np.append(valid_son_we,valid_son[ele]) lat_mod_son_we=np.append(lat_mod_son_we,lat_mod_son[ele]) lon_mod_son_we=np.append(lon_mod_son_we,lon_mod_son[ele]) area_mod_son_we=np.append(area_mod_son_we,area_mod_son[ele]) lat_obs_son_we=np.append(lat_obs_son_we,lat_obs_son[ele]) lon_obs_son_we=np.append(lon_obs_son_we,lon_obs_son[ele]) area_obs_son_we=np.append(area_obs_son_we,area_obs_son[ele]) magnitude_son_we=np.append(magnitude_son_we,magnitude_son[ele]) angle_son_we=np.append(angle_son_we,angle_son[ele]) if len(angle_son_we) > 0: #windrose plotting son west ax = WindroseAxes.from_ax() ax.bar(angle_son_we, magnitude_son_we, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Western Region SON',fontsize=14) plt.savefig(working_dir+'rose_son_we_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_we_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #west djf date_djf_we=[] valid_djf_we=[] lon_mod_djf_we=[] lat_mod_djf_we=[] area_mod_djf_we=[] lon_obs_djf_we=[] lat_obs_djf_we=[] area_obs_djf_we=[] magnitude_djf_we=[] angle_djf_we=[] for ele in range(0,len(date_djf)): if lat_obs_djf[ele] > 30 and lat_obs_djf[ele] <= 50 and lon_obs_djf[ele] > -125 and lon_obs_djf[ele] <= -105\ and lat_mod_djf[ele] > 30 and lat_mod_djf[ele] <= 50 and lon_mod_djf[ele] > -125 and lon_mod_djf[ele] <= -105: date_djf_we=np.append(date_djf_we,date_djf[ele]) valid_djf_we=np.append(valid_djf_we,valid_djf[ele]) lat_mod_djf_we=np.append(lat_mod_djf_we,lat_mod_djf[ele]) lon_mod_djf_we=np.append(lon_mod_djf_we,lon_mod_djf[ele]) area_mod_djf_we=np.append(area_mod_djf_we,area_mod_djf[ele]) lat_obs_djf_we=np.append(lat_obs_djf_we,lat_obs_djf[ele]) lon_obs_djf_we=np.append(lon_obs_djf_we,lon_obs_djf[ele]) area_obs_djf_we=np.append(area_obs_djf_we,area_obs_djf[ele]) magnitude_djf_we=np.append(magnitude_djf_we,magnitude_djf[ele]) angle_djf_we=np.append(angle_djf_we,angle_djf[ele]) if len(angle_djf_we) > 0: #windrose plotting djf west ax = WindroseAxes.from_ax() ax.bar(angle_djf_we, magnitude_djf_we, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Western Region DJF',fontsize=14) plt.savefig(working_dir+'rose_djf_we_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_we_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #west mam date_mam_we=[] valid_mam_we=[] lon_mod_mam_we=[] lat_mod_mam_we=[] area_mod_mam_we=[] lon_obs_mam_we=[] lat_obs_mam_we=[] area_obs_mam_we=[] magnitude_mam_we=[] angle_mam_we=[] for ele in range(0,len(date_mam)): if lat_obs_mam[ele] > 30 and lat_obs_mam[ele] <= 50 and lon_obs_mam[ele] > -125 and lon_obs_mam[ele] <= -105\ and lat_mod_mam[ele] > 30 and lat_mod_mam[ele] <= 50 and lon_mod_mam[ele] > -125 and lon_mod_mam[ele] <= -105: date_mam_we=np.append(date_mam_we,date_mam[ele]) valid_mam_we=np.append(valid_mam_we,valid_mam[ele]) lat_mod_mam_we=np.append(lat_mod_mam_we,lat_mod_mam[ele]) lon_mod_mam_we=np.append(lon_mod_mam_we,lon_mod_mam[ele]) area_mod_mam_we=np.append(area_mod_mam_we,area_mod_mam[ele]) lat_obs_mam_we=np.append(lat_obs_mam_we,lat_obs_mam[ele]) lon_obs_mam_we=np.append(lon_obs_mam_we,lon_obs_mam[ele]) area_obs_mam_we=np.append(area_obs_mam_we,area_obs_mam[ele]) magnitude_mam_we=np.append(magnitude_mam_we,magnitude_mam[ele]) angle_mam_we=np.append(angle_mam_we,angle_mam[ele]) if len(angle_mam_we) > 0: #windrose plotting mam west ax = WindroseAxes.from_ax() ax.bar(angle_mam_we, magnitude_mam_we, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Western Region MAM',fontsize=14) plt.savefig(working_dir+'rose_mam_we_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_we_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #####################################################windrose plot by region not season########################################################################## #southern plains date_sp=[] valid_sp=[] lon_mod_sp=[] lat_mod_sp=[] area_mod_sp=[] lon_obs_sp=[] lat_obs_sp=[] area_obs_sp=[] magnitude_sp=[] angle_sp=[] for ele in range(0,len(date)): if lat_obs[ele] > 25 and lat_obs[ele] <= 38 and lon_obs[ele] > -105 and lon_obs[ele] <= -90 \ and lat_mod[ele] > 25 and lat_mod[ele] <= 38 and lon_mod[ele] > -105 and lon_mod[ele] <= -90: date_sp=np.append(date_sp,date[ele]) valid_sp=np.append(valid_sp,valid[ele]) lat_mod_sp=np.append(lat_mod_sp,lat_mod[ele]) lon_mod_sp=np.append(lon_mod_sp,lon_mod[ele]) area_mod_sp=np.append(area_mod_sp,area_mod[ele]) lat_obs_sp=np.append(lat_obs_sp,lat_obs[ele]) lon_obs_sp=np.append(lon_obs_sp,lon_obs[ele]) area_obs_sp=np.append(area_obs_sp,area_obs[ele]) magnitude_sp=np.append(magnitude_sp,magnitude[ele]) angle_sp=np.append(angle_sp,angle[ele]) if len(angle_sp) > 0: #windrose plotting southern plains ax = WindroseAxes.from_ax() ax.bar(angle_sp, magnitude_sp, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southern Plains ',fontsize=14) plt.savefig(working_dir+'rose_year_sp_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_sp_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northern plains date_np=[] valid_np=[] lon_mod_np=[] lat_mod_np=[] area_mod_np=[] lon_obs_np=[] lat_obs_np=[] area_obs_np=[] magnitude_np=[] angle_np=[] for ele in range(0,len(date)): if lat_obs[ele] > 38 and lat_obs[ele] <= 50 and lon_obs[ele] > -105 and lon_obs[ele] <= -90 \ and lat_mod[ele] > 38 and lat_mod[ele] <= 50 and lon_mod[ele] > -105 and lon_mod[ele] <= -90: date_np=np.append(date_np,date[ele]) valid_np=np.append(valid_np,valid[ele]) lat_mod_np=np.append(lat_mod_np,lat_mod[ele]) lon_mod_np=np.append(lon_mod_np,lon_mod[ele]) area_mod_np=np.append(area_mod_np,area_mod[ele]) lat_obs_np=np.append(lat_obs_np,lat_obs[ele]) lon_obs_np=np.append(lon_obs_np,lon_obs[ele]) area_obs_np=np.append(area_obs_np,area_obs[ele]) magnitude_np=np.append(magnitude_np,magnitude[ele]) angle_np=np.append(angle_np,angle[ele]) if len(angle_np) > 0: #windrose plotting southern plains ax = WindroseAxes.from_ax() ax.bar(angle_np, magnitude_np, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northern Plains ',fontsize=14) plt.savefig(working_dir+'rose_year_np_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_np_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #southeast date_se=[] valid_se=[] lon_mod_se=[] lat_mod_se=[] area_mod_se=[] lon_obs_se=[] lat_obs_se=[] area_obs_se=[] magnitude_se=[] angle_se=[] for ele in range(0,len(date)): if lat_obs[ele] > 20 and lat_obs[ele] <= 38 and lon_obs[ele] > -90 and lon_obs[ele] <= -75 \ and lat_mod[ele] > 20 and lat_mod[ele] <= 38 and lon_mod[ele] > -90 and lon_mod[ele] <= -75: date_se=np.append(date_se,date[ele]) valid_se=np.append(valid_se,valid[ele]) lat_mod_se=np.append(lat_mod_se,lat_mod[ele]) lon_mod_se=np.append(lon_mod_se,lon_mod[ele]) area_mod_se=np.append(area_mod_se,area_mod[ele]) lat_obs_se=np.append(lat_obs_se,lat_obs[ele]) lon_obs_se=np.append(lon_obs_se,lon_obs[ele]) area_obs_se=np.append(area_obs_se,area_obs[ele]) magnitude_se=np.append(magnitude_se,magnitude[ele]) angle_se=np.append(angle_se,angle[ele]) if len(angle_se) > 0: #windrose plotting southeast ax = WindroseAxes.from_ax() ax.bar(angle_se, magnitude_se, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Southeast ',fontsize=14) plt.savefig(working_dir+'rose_year_se_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_se_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #northeast date_ne=[] valid_ne=[] lon_mod_ne=[] lat_mod_ne=[] area_mod_ne=[] lon_obs_ne=[] lat_obs_ne=[] area_obs_ne=[] magnitude_ne=[] angle_ne=[] for ele in range(0,len(date)): if lat_obs[ele] > 38 and lat_obs[ele] <= 50 and lon_obs[ele] > -90 and lon_obs[ele] <= -65 \ and lat_mod[ele] > 38 and lat_mod[ele] <= 50 and lon_mod[ele] > -90 and lon_mod[ele] <= -65: date_ne=np.append(date_ne,date[ele]) valid_ne=np.append(valid_ne,valid[ele]) lat_mod_ne=np.append(lat_mod_ne,lat_mod[ele]) lon_mod_ne=np.append(lon_mod_ne,lon_mod[ele]) area_mod_ne=np.append(area_mod_ne,area_mod[ele]) lat_obs_ne=np.append(lat_obs_ne,lat_obs[ele]) lon_obs_ne=np.append(lon_obs_ne,lon_obs[ele]) area_obs_ne=np.append(area_obs_ne,area_obs[ele]) magnitude_ne=np.append(magnitude_ne,magnitude[ele]) angle_ne=np.append(angle_ne,angle[ele]) if len(angle_ne) > 0: #windrose plotting southern plains ax = WindroseAxes.from_ax() ax.bar(angle_ne, magnitude_ne, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' Northeast ',fontsize=14) plt.savefig(working_dir+'rose_year_ne_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_ne_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) #west date_we=[] valid_we=[] lon_mod_we=[] lat_mod_we=[] area_mod_we=[] lon_obs_we=[] lat_obs_we=[] area_obs_we=[] magnitude_we=[] angle_we=[] for ele in range(0,len(date)): if lat_obs[ele] > 30 and lat_obs[ele] <= 50 and lon_obs[ele] > -125 and lon_obs[ele] <= -105 \ and lat_mod[ele] > 30 and lat_mod[ele] <= 50 and lon_mod[ele] > -125 and lon_mod[ele] <= -105: date_we=np.append(date_we,date[ele]) valid_we=np.append(valid_we,valid[ele]) lat_mod_we=np.append(lat_mod_we,lat_mod[ele]) lon_mod_we=np.append(lon_mod_we,lon_mod[ele]) area_mod_we=np.append(area_mod_we,area_mod[ele]) lat_obs_we=np.append(lat_obs_we,lat_obs[ele]) lon_obs_we=np.append(lon_obs_we,lon_obs[ele]) area_obs_we=np.append(area_obs_we,area_obs[ele]) magnitude_we=np.append(magnitude_we,magnitude[ele]) angle_we=np.append(angle_we,angle[ele]) if len(angle_we) > 0: #windrose plotting southern plains ax = WindroseAxes.from_ax() ax.bar(angle_we, magnitude_we, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category+' West ',fontsize=14) plt.savefig(working_dir+'rose_year_we_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_we_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) ################################################################################################################################################################ #windrose plotting all seasons #if ero_category=='SLGT': #bin = [0,50,100,150,200,250,300,350,400,450,500] #elif ero_category=='MDT': #bin = [0,25,50,75,100,125,150,175,200,250,300] #elif ero_category=='HIGH': #bin = [0,20,40,60,80,100,120,140,160,170,180] ax = WindroseAxes.from_ax() ax.bar(angle, magnitude, bins=bin,blowto=True) ax.set_legend() plt.title('Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category,fontsize=14) plt.savefig(working_dir+'rose_year_conus_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_year_conus_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) if len(angle_jja) > 0: #windrose plotting jja ax = WindroseAxes.from_ax() ax.bar(angle_jja, magnitude_jja, bins=bin,blowto=True) ax.set_legend() plt.title('Summer Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category,fontsize=14) plt.savefig(working_dir+'rose_jja_all_regions_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_jja_all_regions_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) if len(angle_mam) > 0: #windrose plotting mam ax = WindroseAxes.from_ax() ax.bar(angle_mam, magnitude_mam, bins=bin,blowto=True) ax.set_legend() plt.title('Spring Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category,fontsize=14) plt.savefig(working_dir+'rose_mam_all_regions_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_mam_all_regions_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) if len(angle_son) > 0: #windrose plotting son ax = WindroseAxes.from_ax() ax.bar(angle_son, magnitude_son, bins=bin,blowto=True) ax.set_legend() plt.title('Autumn Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category,fontsize=14) plt.savefig(working_dir+'rose_son_all_regions_'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_son_all_regions_'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) if len(angle_djf) > 0: #windrose plotting son ax = WindroseAxes.from_ax() ax.bar(angle_djf, magnitude_djf, bins=bin,blowto=True) ax.set_legend() plt.title('Winter Day '+str(validday)+' Rose Plot of ERO Displacement (km) for '+ero_category,fontsize=14) plt.savefig(working_dir+'rose_djf_all_regions'+ero_category+'_day'+str(validday)+'.png',bbox_inches='tight',dpi=150) plt.close() subprocess.call('scp '+working_dir+'/rose_djf_all_regions'+ero_category+'_day'+str(validday)+'.png '+FIG_DIR_ROSE,shell=True) ##################################################magnitude bar graph calculations and plotting################################################################## #Sample data to create a group bar plot magnitude_mae = [np.nanmean(magnitude_jja),np.nanmean(magnitude_son),np.nanmean(magnitude_djf),np.nanmean(magnitude_mam)] magnitude_we_mae = [np.nanmean(magnitude_jja_we),np.nanmean(magnitude_son_we),np.nanmean(magnitude_djf_we),np.nanmean(magnitude_mam_we)] magnitude_np_mae = [np.nanmean(magnitude_jja_np),np.nanmean(magnitude_son_np),np.nanmean(magnitude_djf_np),np.nanmean(magnitude_mam_np)] magnitude_sp_mae = [np.nanmean(magnitude_jja_sp),np.nanmean(magnitude_son_sp),np.nanmean(magnitude_djf_sp),np.nanmean(magnitude_mam_sp)] magnitude_ne_mae = [np.nanmean(magnitude_jja_ne),np.nanmean(magnitude_son_ne),np.nanmean(magnitude_djf_ne),np.nanmean(magnitude_mam_ne)] magnitude_se_mae = [np.nanmean(magnitude_jja_se),np.nanmean(magnitude_son_se),np.nanmean(magnitude_djf_se),np.nanmean(magnitude_mam_se)] #Create the plot, note that the first element specifies the number of groups and there is a 0.15 offset with the x-axis fig = plt.figure(figsize=(8,8)) ax = fig.add_axes([0.1,0.1,0.8,0.8]) plt.bar(np.arange(4)-0.25,magnitude_mae,align='center',width=0.1,color='purple') plt.bar(np.arange(4)-0.15,magnitude_we_mae,align='center',width=0.1,color='red') plt.bar(np.arange(4)-0.05,magnitude_np_mae,align='center',width=0.1,color='yellow') plt.bar(np.arange(4)+0.05,magnitude_sp_mae,align='center',width=0.1,color='green') plt.bar(np.arange(4)+0.15,magnitude_ne_mae,align='center',width=0.1,color='blue') plt.bar(np.arange(4)+0.25,magnitude_se_mae,align='center',width=0.1,color='orange') #Pass line instances to a legend line_label=[] line_str=[]; leg_nam = ['All','Western Region','Northern Plains','Southern Plains','Northeast','Southeast'] colorlist = ["purple","red","yellow","green","blue","orange"] for x in range(0,len(leg_nam)): line_label = np.hstack((line_label, mpl.lines.Line2D(range(1), range(1), color=colorlist[x], linestyle='None', marker='s', markersize=7))) line_str = np.hstack((line_str, leg_nam[x])) first_legend=plt.legend(line_label, line_str, fontsize=12, numpoints=1, loc=2, framealpha=1) ax2 = plt.gca().add_artist(first_legend) #Plot remainder of figure plt.xticks(np.arange(4), ['JJA','SON','DJF','MAM'],fontsize=14) plt.xlabel('Seasons',fontsize=14) plt.ylabel('Displacement (km)',fontsize=14) plt.title('Average Displacement by Season and Region Day '+str(validday),fontsize=16) plt.ylim((0,500)) #plt.show() plt.savefig(working_dir+'Ave_displ_bar_'+ero_category+'_day'+str(validday)+'.png', bbox_inches='tight',dpi=200) subprocess.call('scp '+working_dir+'/Ave_displ_bar_'+ero_category+'_day'+str(validday)+'.png hpc@vm-lnx-rzdm06:/home/people/hpc/ftp/erickson/lapenta/bar_graphs',shell=True) plt.close() ################################################################################################################################################################# #check if area variables are empty; if they are, change them to NaN if (np.any(area_mod_djf)) == False: area_mod_djf = float('nan') if (np.any(area_obs_djf)) == False: area_obs_djf = float('nan') if (np.any(area_mod_jja)) == False: area_mod_jja = float('nan') if (np.any(area_obs_jja)) == False: area_obs_jja = float('nan') if (np.any(area_mod_son)) == False: area_mod_son = float('nan') if (np.any(area_obs_son)) == False: area_obs_son = float('nan') if (np.any(area_mod_mam)) == False: area_mod_mam = float('nan') if (np.any(area_obs_mam)) == False: area_obs_mam = float('nan') #np if (np.any(area_mod_djf_np)) == False: area_mod_djf_np = float('nan') if (np.any(area_obs_djf_np)) == False: area_obs_djf_np = float('nan') if (np.any(area_mod_jja_np)) == False: area_mod_jja_np = float('nan') if (np.any(area_obs_jja_np)) == False: area_obs_jja_np = float('nan') if (np.any(area_mod_son_np)) == False: area_mod_son_np = float('nan') if (np.any(area_obs_son_np)) == False: area_obs_son_np = float('nan') if (np.any(area_mod_mam_np)) == False: area_mod_mam_np = float('nan') if (np.any(area_obs_mam_np)) == False: area_obs_mam_np = float('nan') #we if (np.any(area_mod_djf_we)) == False: area_mod_djf_we = float('nan') if (np.any(area_obs_djf_we)) == False: area_obs_djf_we = float('nan') if (np.any(area_mod_jja_we)) == False: area_mod_jja_we = float('nan') if (np.any(area_obs_jja_we)) == False: area_obs_jja_we = float('nan') if (np.any(area_mod_son_we)) == False: area_mod_son_we = float('nan') if (np.any(area_obs_son_we)) == False: area_obs_son_we = float('nan') if (np.any(area_mod_mam_we)) == False: area_mod_mam_we = float('nan') if (np.any(area_obs_mam_we)) == False: area_obs_mam_we = float('nan') #sp if (np.any(area_mod_djf_sp)) == False: area_mod_djf_sp = float('nan') if (np.any(area_obs_djf_sp)) == False: area_obs_djf_sp = float('nan') if (np.any(area_mod_jja_sp)) == False: area_mod_jja_sp = float('nan') if (np.any(area_obs_jja_sp)) == False: area_obs_jja_sp = float('nan') if (np.any(area_mod_son_sp)) == False: area_mod_son_sp = float('nan') if (np.any(area_obs_son_sp)) == False: area_obs_son_sp = float('nan') if (np.any(area_mod_mam_sp)) == False: area_mod_mam_sp = float('nan') if (np.any(area_obs_mam_sp)) == False: area_obs_mam_sp = float('nan') #ne if (np.any(area_mod_djf_ne)) == False: area_mod_djf_ne = float('nan') if (np.any(area_obs_djf_ne)) == False: area_obs_djf_ne = float('nan') if (np.any(area_mod_jja_ne)) == False: area_mod_jja_ne = float('nan') if (np.any(area_obs_jja_ne)) == False: area_obs_jja_ne = float('nan') if (np.any(area_mod_son_ne)) == False: area_mod_son_ne = float('nan') if (np.any(area_obs_son_ne)) == False: area_obs_son_ne = float('nan') if (np.any(area_mod_mam_ne)) == False: area_mod_mam_ne = float('nan') if (np.any(area_obs_mam_ne)) == False: area_obs_mam_ne = float('nan') #se if (np.any(area_mod_djf_se)) == False: area_mod_djf_se = float('nan') if (np.any(area_obs_djf_se)) == False: area_obs_djf_se = float('nan') if (np.any(area_mod_jja_se)) == False: area_mod_jja_se = float('nan') if (np.any(area_obs_jja_se)) == False: area_obs_jja_se = float('nan') if (np.any(area_mod_son_se)) == False: area_mod_son_se = float('nan') if (np.any(area_obs_son_se)) == False: area_obs_son_se = float('nan') if (np.any(area_mod_mam_se)) == False: area_mod_mam_se = float('nan') if (np.any(area_obs_mam_se)) == False: area_obs_mam_se = float('nan') ###########################################Calculate Area Mean Error############################################################################################ area_me = [np.nanmean(area_mod_jja - area_obs_jja),np.nanmean(area_mod_son - area_obs_son),np.nanmean(area_mod_djf - area_obs_djf), \ np.nanmean(area_mod_mam - area_obs_mam)] area_we_me = [np.nanmean(area_mod_jja_we - area_obs_jja_we),np.nanmean(area_mod_son_we - area_obs_son_we),np.nanmean(area_mod_djf_we - area_obs_djf_we),\ np.nanmean(area_mod_mam_we - area_obs_mam_we)] area_np_me = [np.nanmean(area_mod_jja_np - area_obs_jja_np),np.nanmean(area_mod_son_np - area_obs_son_np),np.nanmean(area_mod_djf_np - area_obs_djf_np),\ np.nanmean(area_mod_mam_np - area_obs_mam_np)] area_sp_me = [np.nanmean(area_mod_jja_sp - area_obs_jja_sp),np.nanmean(area_mod_son_sp - area_obs_son_sp),np.nanmean(area_mod_djf_sp - area_obs_djf_sp),\ np.nanmean(area_mod_mam_sp - area_obs_mam_sp)] area_ne_me = [np.nanmean(area_mod_jja_ne - area_obs_jja_ne),np.nanmean(area_mod_son_ne - area_obs_son_ne),np.nanmean(area_mod_djf_ne - area_obs_djf_ne),\ np.nanmean(area_mod_mam_ne - area_obs_mam_ne)] area_se_me = [np.nanmean(area_mod_jja_se - area_obs_jja_se),np.nanmean(area_mod_son_se - area_obs_son_se),np.nanmean(area_mod_djf_se - area_obs_djf_se),\ np.nanmean(area_mod_mam_se - area_obs_mam_se)] #Create the plot, note that the first element specifies the number of groups and there is a 0.15 offset with the x-axis fig = plt.figure(figsize=(8,8)) ax = fig.add_axes([0.1,0.1,0.8,0.8]) plt.bar(np.arange(4)-0.25,area_me,align='center',width=0.1,color='purple') plt.bar(np.arange(4)-0.15,area_we_me,align='center',width=0.1,color='red') plt.bar(np.arange(4)-0.05,area_np_me,align='center',width=0.1,color='yellow') plt.bar(np.arange(4)+0.05,area_sp_me,align='center',width=0.1,color='green') plt.bar(np.arange(4)+0.15,area_ne_me,align='center',width=0.1,color='blue') plt.bar(np.arange(4)+0.25,area_se_me,align='center',width=0.1,color='orange') #find max value for dynamic y axis #find_me_max_value = max(area_me, area_we_me, area_np_me, area_sp_me, area_ne_me, area_se_me) #create_me_max_value = max(find_me_max_value) #determine where to put the legend if ero_category=='SLGT': loc = 3 lower_y_axis= -1500 upper_y_axis= -1 *(lower_y_axis) if ero_category == 'MDT': loc = 2 lower_y_axis= -2700 upper_y_axis= -1 *(lower_y_axis) if ero_category == 'HIGH': loc = 2 lower_y_axis= -2000 upper_y_axis= -1 *(lower_y_axis) #Pass line instances to a legend line_label=[] plt.bar(np.arange(4)+0.05,area_sp_me,align='center',width=0.1,color='green') plt.bar(np.arange(4)+0.15,area_ne_me,align='center',width=0.1,color='blue') plt.bar(np.arange(4)+0.25,area_se_me,align='center',width=0.1,color='orange') #Pass line instances to a legend line_label=[] line_str=[]; leg_nam = ['All','Western Region','Northern Plains','Southern Plains','Northeast','Southeast'] colorlist = ["purple","red","yellow","green","blue","orange"] for x in range(0,len(leg_nam)): line_label = np.hstack((line_label, mpl.lines.Line2D(range(1), range(1), color=colorlist[x], linestyle='None', marker='s', markersize=7))) line_str = np.hstack((line_str, leg_nam[x])) first_legend=plt.legend(line_label, line_str, fontsize=12, numpoints=1, loc=loc, framealpha=1) ax2 = plt.gca().add_artist(first_legend) #Plot remainder of figure plt.xticks(np.arange(4), ['JJA','SON','DJF','MAM'],fontsize=14) plt.xlabel('Seasons',fontsize=14) plt.ylabel('Area Mean Error',fontsize=14) plt.title('Area Mean Error by Season and Region Day '+str(validday)+' '+ero_category,fontsize=16) plt.ylim(lower_y_axis,upper_y_axis) plt.grid(axis='y') #plt.show() plt.savefig(working_dir+'area_mean_error_bar_'+ero_category+'_day'+str(validday)+'.png', bbox_inches='tight',dpi=200) subprocess.call('scp '+working_dir+'/area_mean_error_bar_'+ero_category+'_day'+str(validday)+'.png hpc@vm-lnx-rzdm06:/home/people/hpc/ftp/erickson/lapenta/bar_graphs',shell=True) plt.close() #############################################Calculate Area mean absolute error and plot bar graph############################################################### #Sample data to create a group bar plot area_mae = [np.nanmean(abs(area_mod_jja - area_obs_jja)),np.nanmean(abs(area_mod_son - area_obs_son)),np.nanmean(abs(area_mod_djf - area_obs_djf)), \ np.nanmean(abs(area_mod_mam - area_obs_mam))] area_we_mae = [np.nanmean(abs(area_mod_jja_we - area_obs_jja_we)),np.nanmean(abs(area_mod_son_we - area_obs_son_we)),\ np.nanmean(abs(area_mod_djf_we - area_obs_djf_we)),np.nanmean(abs(area_mod_mam_we - area_obs_mam_we))] area_np_mae = [np.nanmean(abs(area_mod_jja_np - area_obs_jja_np)),np.nanmean(abs(area_mod_son_np - area_obs_son_np)),\ np.nanmean(abs(area_mod_djf_np - area_obs_djf_np)),np.nanmean(abs(area_mod_mam_np - area_obs_mam_np))] area_sp_mae = [np.nanmean(abs(area_mod_jja_sp - area_obs_jja_sp)),np.nanmean(abs(area_mod_son_sp - area_obs_son_sp)),\ np.nanmean(abs(area_mod_djf_sp - area_obs_djf_sp)),np.nanmean(abs(area_mod_mam_sp - area_obs_mam_sp))] area_ne_mae = [np.nanmean(abs(area_mod_jja_ne - area_obs_jja_ne)),np.nanmean(abs(area_mod_son_ne - area_obs_son_ne)),\ np.nanmean(abs(area_mod_djf_ne - area_obs_djf_ne)),np.nanmean(abs(area_mod_mam_ne - area_obs_mam_ne))] area_se_mae = [np.nanmean(abs(area_mod_jja_se - area_obs_jja_se)),np.nanmean(abs(area_mod_son_se - area_obs_son_se)),\ np.nanmean(abs(area_mod_djf_se - area_obs_djf_se)),np.nanmean(abs(area_mod_mam_se - area_obs_mam_se))] #Create the plot, note that the first element specifies the number of groups and there is a 0.15 offset with the x-axis fig = plt.figure(figsize=(8,8)) ax = fig.add_axes([0.1,0.1,0.8,0.8]) plt.bar(np.arange(4)-0.25,area_mae,align='center',width=0.1,color='purple') plt.bar(np.arange(4)-0.15,area_we_mae,align='center',width=0.1,color='red') plt.bar(np.arange(4)-0.05,area_np_mae,align='center',width=0.1,color='yellow') plt.bar(np.arange(4)+0.05,area_sp_mae,align='center',width=0.1,color='green') plt.bar(np.arange(4)+0.15,area_ne_mae,align='center',width=0.1,color='blue') plt.bar(np.arange(4)+0.25,area_se_mae,align='center',width=0.1,color='orange') #find max value for dynamic y axis #find_mae_max_value = max(area_mae, area_we_mae, area_np_mae, area_sp_mae, area_ne_mae, area_se_mae) #create_mae_max_value = max(find_mae_max_value) #Pass line instances to a legend line_label=[] plt.bar(np.arange(4)+0.05,area_sp_mae,align='center',width=0.1,color='green') plt.bar(np.arange(4)+0.15,area_ne_mae,align='center',width=0.1,color='blue') plt.bar(np.arange(4)+0.25,area_se_mae,align='center',width=0.1,color='orange') #Pass line instances to a legend line_label=[] line_str=[]; leg_nam = ['All','Western Region','Northern Plains','Southern Plains','Northeast','Southeast'] colorlist = ["purple","red","yellow","green","blue","orange"] for x in range(0,len(leg_nam)): line_label = np.hstack((line_label, mpl.lines.Line2D(range(1), range(1), color=colorlist[x], linestyle='None', marker='s', markersize=7))) line_str = np.hstack((line_str, leg_nam[x])) first_legend=plt.legend(line_label, line_str, fontsize=12, numpoints=1, loc=2, framealpha=1) ax2 = plt.gca().add_artist(first_legend) #Plot remainder of figure plt.xticks(np.arange(4), ['JJA','SON','DJF','MAM'],fontsize=14) plt.xlabel('Seasons',fontsize=14) plt.ylabel('Area Mean Abs Error',fontsize=14) plt.title('Area Mean Absolute Error by Season and Region Day '+str(validday)+' '+ero_category,fontsize=16) plt.ylim(0,3000) plt.grid(axis='y') #plt.show() plt.savefig(working_dir+'area_mean_abs_error_bar_'+ero_category+'_day'+str(validday)+'.png', bbox_inches='tight',dpi=200) subprocess.call('scp '+working_dir+'/area_mean_abs_error_bar_'+ero_category+'_day'+str(validday)+'.png hpc@vm-lnx-rzdm06:/home/people/hpc/ftp/erickson/lapenta/bar_graphs',shell=True) plt.close() #.csv writer #with open('readdata.csv', mode='a') as lines: #readdata_lines=csv.writer(lines, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL) #readdata_lines.writerow([str(date),str(valid),str(lat_obs),str(lon_obs),str(magnitude),str(angle)])