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plot_current_var_mag_compare_interp.py
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plot_current_var_mag_compare_interp.py
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from __future__ import division,print_function
import matplotlib as mpl
import scipy as sp
from datatools import *
from gridtools import *
from plottools import *
from projtools import *
import matplotlib.tri as mplt
import matplotlib.pyplot as plt
#from mpl_toolkits.basemap import Basemap
import os as os
import sys
np.set_printoptions(precision=8,suppress=True,threshold=sys.maxsize)
import time
from matplotlib.collections import LineCollection as LC
from matplotlib.collections import PolyCollection as PC
mpl.rcParams['contour.negative_linestyle'] = 'solid'
# Define names and types of data
name_orig='kit4_kelp_nodrag'
name_change='kit4_kelp_20m_drag_0.018'
grid='kit4_kelp'
#regionname='kit4_kelp_tight6'
regionlist=['kit4_ftb','kit4_crossdouble','kit4_kelp_tight2_small','kit4_kelp_tight2','kit4_kelp_tight4','kit4_kelp_tight5','kit4_kelp_tight6']
regionlist=['kit4_kelp_tight2_kelpfield']
starttime=384
cbfix=True
### load the .nc file #####
data = loadnc('runs/'+grid+'/'+name_orig+'/output/',singlename=grid + '_0001.nc')
data2 = loadnc('runs/'+grid+'/'+name_change+'/output/',singlename=grid + '_0001.nc')
print('done load')
data = ncdatasort(data)
print('done sort')
cages=loadcage('runs/'+grid+'/' +name_change+ '/input/' +grid+ '_cage.dat')
if np.shape(cages)!=():
tmparray=[list(zip(data['nodell'][data['nv'][i,[0,1,2,0]],0],data['nodell'][data['nv'][i,[0,1,2,0]],1])) for i in cages ]
color='g'
lw=.1
ls='solid'
for regionname in regionlist:
print 'plotting region: ' +regionname
region=regions(regionname)
nidx=get_nodes(data,region)
eidx=get_elements(data,region)
savepath='figures/png/' + grid + '_' + '/current_var_mag_subplot_interp/' + name_orig + '_' + name_change + '/'
if not os.path.exists(savepath): os.makedirs(savepath)
start = time.clock()
uvar_o=data['ua'][starttime:,:].var(axis=0)
vvar_o=data['va'][starttime:,:].var(axis=0)
uvar_c=data2['ua'][starttime:,:].var(axis=0)
vvar_c=data2['va'][starttime:,:].var(axis=0)
cvarm_o=np.sqrt(uvar_o+vvar_o)
cvarm_c=np.sqrt(uvar_c+vvar_c)
cvarm_diff=cvarm_c-cvarm_o
cvarm_diff_rel=np.divide(cvarm_diff,cvarm_o)*100
print ('calc current mag: %f' % (time.clock() - start))
ngridx = 2000
ngridy = 2000
start = time.clock()
xi = np.linspace(region['region'][0],region['region'][1], ngridx)
yi = np.linspace(region['region'][2],region['region'][3], ngridy)
cvarm_o_interp=mpl.mlab.griddata(data['uvnodell'][:,0],data['uvnodell'][:,1], cvarm_o, xi, yi)
cvarm_c_interp=mpl.mlab.griddata(data['uvnodell'][:,0],data['uvnodell'][:,1], cvarm_c, xi, yi)
cvarm_diff_rel_interp=mpl.mlab.griddata(data['uvnodell'][:,0],data['uvnodell'][:,1], cvarm_diff_rel, xi, yi)
tmpxy=np.meshgrid(xi,yi)
xii=tmpxy[0]
yii=tmpxy[1]
host=data['trigrid'].get_trifinder().__call__(xii,yii)
cvarm_o_interp_mask = np.ma.masked_where(host==-1,cvarm_o_interp)
cvarm_c_interp_mask = np.ma.masked_where(host==-1,cvarm_c_interp)
cvarm_diff_rel_interp_mask = np.ma.masked_where(host==-1,cvarm_diff_rel_interp)
print ('griddata interp: %f' % (time.clock() - start))
f,ax=place_axes(region,3,cb=True)
fmt=r'%d'
if cbfix==True:
V=np.array([-80,-70,-60,-50,-40,-30,-20,-10,0,2,4,6,8,10,12,14,16,18,20])
Vpos=np.array([0,2,4,6,8,10,12,14,16,18,20])
Vneg=np.array([-80,-70,-60,-50,-40,-30,-20,-10])
Vpos=np.array([0,4,8,12,16,20])
Vneg=np.array([-60,-30,0])
#V=np.array([-80,-60,-40,-20,0,5,10,15,20])
ax0cb=ax[0].pcolormesh(xi,yi,cvarm_o_interp_mask,vmin=0,vmax=.5)
ax1cb=ax[1].pcolormesh(xi,yi,cvarm_c_interp_mask,vmin=0,vmax=.5)
ax2cb=ax[2].pcolormesh(xi,yi,cvarm_diff_rel_interp_mask,vmin=-100,vmax=30)
#CS2=ax[2].contour(xi,yi,cvarm_diff_rel_interp_mask,Vpos,colors='k',zorder=30,linestyles='solid',linewidths=.5)
#ax[2].clabel(CS2, fontsize=4, inline=1,zorder=30,fmt=fmt)
#CS3=ax[2].contour(xi,yi,cvarm_diff_rel_interp_mask,Vneg,colors='w',zorder=30,linestyles='solid',linewidths=.5)
#ax[2].clabel(CS3, fontsize=4, inline=1,zorder=30,fmt=fmt)
else:
ax0cb=ax[0].pcolormesh(xi,yi,cvarm_o_interp_mask)
ax1cb=ax[1].pcolormesh(xi,yi,cvarm_c_interp_mask)
ax2cb=ax[2].pcolormesh(xi,yi,cvarm_diff_rel_interp_mask)
#CS2=ax[2].contour(xi,yi,cvarm_diff_rel_interp_mask,colors='w',zorder=30,linestyles='dashed')
#ax[2].clabel(CS2, fontsize=6, inline=1,zorder=30,fmt=fmt)
ppll_sub(ax,setregion=region,cb=[ax0cb,ax1cb,ax2cb],cblabel=[r'Velocity STD (m s$^{-1}$)',r'Velocity STD (m s$^{-1}$)',r'Relative difference (%)'],llfontsize=10,fontsize=8,cblabelsize=6,cbticksize=6,cbtickrotation=-45)
ABC=['A','B','C']
figW, figH = f.get_size_inches()
plt.draw()
for i,axi in enumerate(ax):
plotcoast(ax[i],filename='pacific.nc',color='None',fill=True)
axbb=ax[i].get_axes().get_position().bounds
ax[i].annotate(ABC[i],xy=(axbb[0]+.0075,axbb[1]+axbb[3]-.03),xycoords='figure fraction')
# lseg_t1=LC(tmparray,linewidths = lw,linestyles=ls,color=color)
# ax[1].add_collection(lseg_t1)
# lseg_t2=LC(tmparray,linewidths = lw,linestyles=ls,color=color)
# ax[2].add_collection(lseg_t2)
f.savefig(savepath + grid + '_' + regionname+'_current_variance_magnitude_diff_relative_subplot_contour.png',dpi=600)
plt.close(f)