def lag_plot(i):
f = plt.figure()
ax=f.add_axes([.125,.1,.775,.8])
#plotcoast(ax,filename='pacific.nc',color='k')
#ax.triplot(data['trigridxy'],lw=.25,zorder=1)
ax.axis(region['regionxy'])
lseg1=PC(tmparray,facecolor = 'g',edgecolor='None')
ax.add_collection(lseg1)
ax.scatter(savelag1['x'][(subset*sub):(subset*(sub+1)),i],savelag1['y'][(subset*sub):(subset*(sub+1)),i],color='b',label='No drag',s=.25,zorder=10)
ax.scatter(savelag2['x'][(subset*sub):(subset*(sub+1)),i],savelag2['y'][(subset*sub):(subset*(sub+1)),i],color='r',label='Drag',s=.25,zorder=15)
handles, labels = ax.get_legend_handles_labels()
handles[0:2]=[handles[0],handles[-1]]
labels[0:2]=[labels[0],labels[-1]]
legend=ax.legend(handles[0:2], labels[0:2],prop={'size':10},loc=4,numpoints=1)
legend.set_zorder(25)
tstr=time.strftime("%d-%H:%M", time.gmtime(savelag1['time'][i]-savelag1['time'][0]))
ax.annotate(("Time: %s"%tstr),xy=(.025,.95),xycoords='axes fraction',bbox={'facecolor':'white','edgecolor':'None', 'alpha':1, 'pad':3})
f.savefig(savepath +''+name+'_'+name2+'_'+regionname+'_'+lname+'_timestep_'+("%05d"%i)+'.png',dpi=150)
plt.close(f)
def speed_plot(i):
print(i)
f = plt.figure()
ax = plt.axes([.125, .1, .775, .8])
if coastflag == True:
plotcoast(ax,
filename='mid_nwatl6c_sjh_lr.nc',
color='k',
fcolor='0.75',
fill=True,
zorder=100)
triax = ax.tripcolor(data['trigrid'],
np.sqrt(data['ua'][i, :]**2 + data['va'][i, :]**2),
vmin=cmin,
vmax=cmax)
if np.shape(cages) != ():
lseg_t = LC(tmparray, linewidths=lw, linestyles=ls, color=color)
ax.add_collection(lseg_t)
if vectorflag == True:
Q1 = ax.quiver(data['uvnodell'][vidx, 0],
data['uvnodell'][vidx, 1],
data['ua'][i, vidx],
data['va'][i, vidx],
angles='xy',
scale_units='xy',
scale=vector_scale,
zorder=100,
width=.0025)
if uniformvectorflag == True:
norm = np.sqrt(data['ua'][i, vidx]**2 + data['va'][i, vidx]**2)
Q1 = ax.quiver(data['uvnodell'][vidx, 0],
data['uvnodell'][vidx, 1],
np.divide(data['ua'][i, vidx], norm),
np.divide(data['va'][i, vidx], norm),
angles='xy',
scale_units='xy',
scale=vector_scale,
zorder=100,
width=.002,
color='k')
sand = np.argwhere(data['wet_cells'][i, :] == 0)
tmparray = [
list(
zip(data['nodell'][data['nv'][j, [0, 1, 2]], 0],
data['nodell'][data['nv'][j, [0, 1, 2]], 1])) for j in sand
]
lseg_sand = PC(tmparray, facecolor='0.75', edgecolor='0.75')
ax.add_collection(lseg_sand)
prettyplot_ll(ax, setregion=region, cblabel=r'Speed (ms$^{-1}$)', cb=triax)
f.savefig(savepath + grid + '_' + region['regionname'] + '_speed_' +
("%04d" % (i)) + '.png',
dpi=150)
plt.close(f)
def plot_kelp(data, cages, filename):
tmparray = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2]], 0],
data['nodell'][data['nv'][i, [0, 1, 2]], 1])) for i in cages
]
seg = PC(tmparray, facecolor='g', edgecolor='None')
f = plt.figure()
ax = f.add_axes([.125, .1, .775, .8])
ax.add_collection(seg)
ax.triplot(data['trigrid'], color='k', lw=.25)
prettyplot_ll(ax, setregion=region)
plotcoast(ax, color='None', fill=True)
f.savefig(filename, dpi=600)
plt.close(f)
def update_plot(t):
for i in range(n_agts):
pos_patch[i] = Circle(pos[i, :, t],
radius=rad_p,
fc=col_grp[groups.index(gID[i])],
alpha=0.4)
mode_patch[i] = Circle(pos[i, :, t],
radius=rad_m,
fc=col_mode[list(mode[i, :,
t]).index(1)])
gaze_patch[i] = Arrow(pos[i, 0, t],
pos[i, 1, t],
25 * gaze[i, 0, t],
25 * gaze[i, 1, t],
width=30,
fc='k',
ec='k')
ax.clear()
p_coll = PC(pos_patch + mode_patch + gaze_patch,
match_original=True)
#p_coll = PC(pos_patch+gaze_patch, match_original=True)
ax.add_collection(p_coll)
def load_coastline():
"""
Load and plot a coastline.
"""
filename = ()
filename = askopenfilename(initialdir=w.init_dir)
if filename != ():
w.coastline = ut.load_coastline(filename=filename)
w.TF['coast'] = True
w.CBVar['coast'].set(1)
#Reduce number of segments - helps but not enough
#axis=[-68.5,-64,44,46.5]
#yep=[]
#def isin(axis,line):
#return ((line[:,0]>=axis[0]) & (line[:,0]<=axis[1]) & (line[:,1]>=axis[2]) & (line[:,1]<=axis[3])).sum()
#for i,line in enumerate(w.coastline):
#if isin(axis,np.array(line)):
#yep+=[i]
if w.config['coast']['fill'] == 'True':
w.FIGS['coast'] = PC(w.coastline,
facecolor=w.config['coast']['facecolor'],
edgecolor=w.config['coast']['edgecolor'],
linewidths=float(
w.config['coast']['linewidth']),
zorder=int(w.config['coast']['zorder']))
else:
w.FIGS['coast'] = LC(w.coastline,
color=w.config['coast']['edgecolor'],
linewidths=float(
w.config['coast']['linewidth']),
zorder=int(w.config['coast']['zorder']))
w.ax.add_collection(w.FIGS['coast'])
w.figure.canvas.draw()
return
savepath = 'figures/timeseries/' + grid + '_' + '/zoom/' + regionname1 + '_' + regionname2 + '_' + stype + '_' + (
"%d" % spacing) + '/'
if not os.path.exists(savepath): os.makedirs(savepath)
region1 = regions(regionname1)
region2 = regions(regionname2)
f = plt.figure()
ax = f.add_axes([.125, .1, .775, .8])
ax.triplot(data['trigrid'], lw=.1)
#prettyplot_ll(ax,setregion=region)
#scalebar(ax,region,200)
plotcoast(ax, filename='pacific.nc', color='None', fill=True)
if np.shape(cages) != ():
lsega = PC(tmparray, facecolor=color, edgecolor='None')
ax.add_collection(lsega)
_formatter = mpl.ticker.FormatStrFormatter("%.2f")
ax.yaxis.set_major_formatter(_formatter)
ax.xaxis.set_major_formatter(_formatter)
ax.set_xlabel(r'Longitude ($^{\circ}$W)')
ax.set_ylabel(r'Latitude ($^{\circ}$N)')
tempregion = {}
if 'linear' in stype:
#constant speed
spaces = np.array([
s * (region1['region'] - region2['region']) / spacing
for s in range(spacing)
])
### load the .nc file #####
data = loadnc('runs/'+grid+'/'+name+'/output/',singlename=grid + '_0001.nc')
data2 = loadnc('runs/'+grid+'/'+name2+'/output/',singlename=grid + '_0001.nc')
print('done load')
data = ncdatasort(data)
print('done sort')
cages=np.genfromtxt('runs/'+grid+'/' +name+ '/input/' +grid+ '_cage.dat',skiprows=1)
cages=(cages[:,0]-1).astype(int)
savepath='figures/png/' + grid + '_' + datatype + '/ebbfldres_dragnodrag_subplot/'
if not os.path.exists(savepath): os.makedirs(savepath)
tmparray=[list(zip(data['nodell'][data['nv'][i,[0,1,2]],0],data['nodell'][data['nv'][i,[0,1,2]],1])) for i in cages ]
lsegf=PC(tmparray,facecolor = 'g',edgecolor='None')
lsege=PC(tmparray,facecolor = 'g',edgecolor='None')
lsegr=PC(tmparray,facecolor = 'g',edgecolor='None')
uv1=np.load('/home/moflaher/Desktop/workspace_python/data/ttide/'+grid+'_'+name+'_'+datatype+'_uv.npy')
uv1=uv1[()]
uv2=np.load('/home/moflaher/Desktop/workspace_python/data/ttide/'+grid+'_'+name2+'_'+datatype+'_uv.npy')
uv2=uv2[()]
nidx=get_nodes(data,region)
eidx=equal_vectors(data,region,vectorspacing)
if usemean==True:
data['uvzeta']=(data['zeta'][starttime:,data['nv'][eidx,0]] + data['zeta'][starttime:,data['nv'][eidx,1]] + data['zeta'][starttime:,data['nv'][eidx,2]]) / 3.0
data2['uvzeta']=(data2['zeta'][starttime:,data2['nv'][eidx,0]] + data2['zeta'][starttime:,data2['nv'][eidx,1]] + data2['zeta'][starttime:,data2['nv'][eidx,2]]) / 3.0
zeta_grad1=np.gradient(data['uvzeta'])[0]
savelag[i] = fileload['savelag'][i].value.T
starts = sio.loadmat(
'/home/moflaher/workspace_matlab/lagtracker/element_starts/oil_elements_beaufort3.mat'
)['cage_elements']
startsbool = np.ones((len(data['nv']), ))
startsbool[starts - 1] = 0
unidx = np.flatnonzero(startsbool)
idx = np.where(data['trigrid'].neighbors == -1)
tmparray = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2]], 0],
data['nodell'][data['nv'][i, [0, 1, 2]], 1])) for i in idx[0]
]
modelcoast = PC(tmparray, facecolor='g', edgecolor='None')
#f=plt.figure()
#ax=f.add_axes([.125,.1,.8,.8])
#ax.add_collection(modelcoast)
#ax.triplot(data['trigrid'],lw=.5)
#f.show()
host = data['trigridxy'].get_trifinder().__call__(savelag['x'], savelag['y'])
whenall = np.in1d(host, idx[0]).reshape(host.shape)
when = np.argmax(whenall[:, 1:], axis=1)
whenidx = np.where((when == 0) & (np.sum(whenall, axis=1) == 0))[0]
trihost = np.zeros((len(data['nv']), ))
tricnt = np.zeros((len(data['nv']), ))
for i in range(len(host[:, 0])):
### load the .nc file #####
data = loadnc('runs/'+grid+'/'+name+'/output/',singlename=grid + '_0001.nc')
data2 = loadnc('runs/'+grid+'/'+name2+'/output/',singlename=grid + '_0001.nc')
print('done load')
data = ncdatasort(data)
print('done sort')
cages=np.genfromtxt('runs/'+grid+'/' +name+ '/input/' +grid+ '_cage.dat',skiprows=1)
cages=(cages[:,0]-1).astype(int)
savepath='figures/png/' + grid + '_' + '/res_dragnodrag_spatial/'
if not os.path.exists(savepath): os.makedirs(savepath)
tmparray=[list(zip(data['nodell'][data['nv'][i,[0,1,2]],0],data['nodell'][data['nv'][i,[0,1,2]],1])) for i in cages ]
lsegr=PC(tmparray,facecolor = fcolor,edgecolor='None')
uv1=np.load('data/ttide/'+grid+'_'+name+'_'+'_uv.npy')
uv1=uv1[()]
uv2=np.load('data/ttide/'+grid+'_'+name2+'_'+'_uv.npy')
uv2=uv2[()]
nidx=get_nodes(data,region)
eidx=get_elements(data,region)
resu=np.empty((len(eidx),len(data['time'][starttime:])))
resv=np.empty((len(eidx),len(data['time'][starttime:])))
resu2=np.empty((len(eidx),len(data['time'][starttime:])))
region = regions(regionname)
cage1n = 'kit4_cage_5m_30m'
cage2n = 'kit4_cage_5m_15m'
cages1 = np.genfromtxt('data/cage_files/' + cage1n + '.dat', skiprows=1)
cages1 = (cages1[:, 0] - 1).astype(int)
cages2 = np.genfromtxt('data/cage_files/' + cage2n + '.dat', skiprows=1)
cages2 = (cages2[:, 0] - 1).astype(int)
tmparray1 = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2]], 0],
data['nodell'][data['nv'][i, [0, 1, 2]], 1])) for i in cages1
]
lseg1 = PC(tmparray1, facecolor='g', edgecolor='None')
tmparray2 = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2]], 0],
data['nodell'][data['nv'][i, [0, 1, 2]], 1])) for i in cages2
]
lseg2 = PC(tmparray2, facecolor='b', edgecolor='None')
f = plt.figure()
ax = f.add_axes([.125, .1, .8, .8])
plotcoast(ax, filename='pacific.nc', color='k')
ax.triplot(data['trigrid'], lw=.25, zorder=1)
ax.axis(region['region'])
ax.add_collection(lseg1)
ax.add_collection(lseg2)
subtimes = np.linspace(0, 1800, nos)
expand = 5000
region['regionxy'] = [
region['regionxy'][0] - expand, region['regionxy'][1] + expand,
region['regionxy'][2] - expand, region['regionxy'][3] + expand
]
f, ax = plt.subplots(nrows=rows, ncols=cols, sharex=True, sharey=True)
ax = ax.flatten()
for i in range(0, len(ax)):
print(i)
ax[i].triplot(data['trigridxy'], lw=.05)
if np.shape(cages) != ():
lseg1 = PC(tmparray, facecolor='g', edgecolor='None')
ax[i].add_collection(lseg1)
ax[i].scatter(savelag1['x'][:, subtimes[i].astype(int)],
savelag1['y'][:, subtimes[i].astype(int)],
color='b',
label='No drag',
s=.25,
zorder=10)
ax[i].scatter(savelag2['x'][:, subtimes[i].astype(int)],
savelag2['y'][:, subtimes[i].astype(int)],
color='r',
label='Drag',
s=.25,
zorder=15)
ax[i].axis(region['regionxy'])
ax[i].set_title('Hour ' + ("%.0f" %
tridiv2[idx[0]] = 1
f = plt.figure()
ax = f.add_axes([.125, .1, .8, .8])
clims = np.percentile(tridiv[tricnt != 0], [2, 98])
triaxis = ax.tripcolor(data['trigrid'], tridiv2 * 100)
#tmparray=[list(zip(data['nodexy'][data['nv'][i,[0,1,2]],0],data['nodexy'][data['nv'][i,[0,1,2]],1])) for i in np.unique(np.hstack([unidx,np.flatnonzero(tridiv==0)]))]
tmparray = [
list(
zip(data['nodell'][data['nv'][i, [0, 1, 2]], 0],
data['nodell'][data['nv'][i, [0, 1, 2]], 1]))
for i in np.flatnonzero(tridiv2 == 0)
]
modelcoast = PC(tmparray, facecolor='w', edgecolor='k', linewidth=.5)
ax.add_collection(modelcoast)
cb = plt.colorbar(triaxis)
cb.set_label('Percent of particles to reach coastal element')
#for i in (idx[0]+1):
# ax.plot(savelag['x'][i,:],savelag['y'][i,:])
ax.axis(region['region'])
#ax.plot(savelag['x'][:,0],savelag['y'][:,0],'k.',markersize=4)
#ax.plot(savelag['x'][when>0,0],savelag['y'][when>0,0],'g.',markersize=6)
plotcoast(ax, filename='world_GSHHS_f_L1.nc', color='k')
ax.plot(oilmat['lonmap'], oilmat['latmap'] + .1, 'g.', alpha=.5, markersize=3)
box = {}
box['region'] = [-134, -133.66, 69.625 + .1, 69.675 + .1]
plot_box(ax, box, 'k', lw=2)
def main():
# Define names and types of data
name='kit4_45days_3'
name2='kit4_kelp_20m_0.018'
grid='kit4'
regionname='kit4_kelp_tight6'
datatype='2d'
lfolder='kit4_kelp_0.0'
lname='kit4_kelp_0.0_0_all_in_a_box'
### load the .nc file #####
data = loadnc('runs/'+grid+'/' + name +'/output/',singlename=grid + '_0001.nc')
print('done load')
data = ncdatasort(data)
print('done sort')
savepath='figures/timeseries/' + grid + '_' + datatype + '/lagtracker/' + name + '_'+name2+'/'
if not os.path.exists(savepath): os.makedirs(savepath)
data['trigridxy'] = mplt.Triangulation(data['x'], data['y'],data['nv'])
region=regions(regionname)
region=regionll2xy(data,region)
if 'savelag1' not in globals():
print "Loading savelag1"
fileload=h5.File('/media/moe46/Hardy/spet_18_work/savedir/'+name+'/allelements_s0in_aristazabal_west.mat')
savelag1={}
for i in fileload['savelag'].keys():
savelag1[i]=fileload['savelag'][i].value.T
if 'savelag2' not in globals():
print "Loading savelag2"
fileload=h5.File('/media/moe46/Hardy/spet_18_work/savedir/'+name2+'/allelements_s0in_aristazabal_west.mat')
savelag2={}
for i in fileload['savelag'].keys():
savelag2[i]=fileload['savelag'][i].value.T
cages=np.genfromtxt('runs/'+grid+'/' +name2+ '/input/' +grid+ '_cage.dat',skiprows=1)
cages=(cages[:,0]-1).astype(int)
tmparray=[list(zip(data['nodexy'][data['nv'][i,[0,1,2]],0],data['nodexy'][data['nv'][i,[0,1,2]],1])) for i in cages ]
sidx=np.where((savelag1['x'][:,0]>region['regionxy'][0])&(savelag1['x'][:,0]<region['regionxy'][1])&(savelag1['y'][:,0]>region['regionxy'][2])&(savelag1['y'][:,0]<region['regionxy'][3]))
expand=10000
region['regionxy']=[region['regionxy'][0]-expand,region['regionxy'][1]+expand,region['regionxy'][2]-expand,region['regionxy'][3]+expand]
for i in range(0,10):#len(savelag1['time']),2):
print ("%d"%i)+" "+("%f"%(i/len(savelag1['time'])*100))
f = plt.figure()
ax=f.add_axes([.125,.1,.8,.8])
#plotcoast(ax,filename='pacific.nc',color='k')
ax.triplot(data['trigridxy'],lw=.25,zorder=1)
ax.axis(region['regionxy'])
lseg1=PC(tmparray,facecolor = 'g',edgecolor='None')
ax.add_collection(lseg1)
ax.scatter(savelag1['x'][sidx,i],savelag1['y'][sidx,i],color='k',label='No drag',s=5,zorder=10)
ax.scatter(savelag2['x'][sidx,i],savelag2['y'][sidx,i],color='r',label='Drag',s=5,zorder=15)
handles, labels = ax.get_legend_handles_labels()
handles[0:2]=[handles[0],handles[-1]]
labels[0:2]=[labels[0],labels[-1]]
legend=ax.legend(handles[0:2], labels[0:2],prop={'size':10},loc=4,numpoints=1)
f.savefig(savepath +'_'+name+'_'+name2+'_'+regionname+'_timestep_'+("%05d"%i)+'.png',dpi=100)
plt.close(f)
figW, figH = f.get_size_inches()
f.canvas.draw()
Q0=ax[0].quiver(data['uvnodell'][vidx,0],data['uvnodell'][vidx,1],data['u'][i,0,vidx],data['v'][i,0,vidx],angles='xy',scale_units='xy',scale=vector_scale,zorder=0,width=.0025)
Q1=ax[1].quiver(data['uvnodell'][vidx,0],data['uvnodell'][vidx,1],data['u'][i,-1,vidx],data['v'][i,-1,vidx],angles='xy',scale_units='xy',scale=vector_scale,zorder=0,width=.0025)
Qkey0=ax[0].quiverkey(Q0,.9,.85,1.0, r'1.0 ms$^{-1}$',fontproperties={'size':8})
Qkey1=ax[1].quiverkey(Q1,.9,.85,1.0, r'1.0 ms$^{-1}$',fontproperties={'size':8})
for j,axi in enumerate(ax):
if coast:
plotcoast(ax[j],filename='mid_nwatl6c_sjh_lr.nc',color='k',fill=True,lw=.5,zorder=100,filepath=coastpath)
axbb=ax[j].get_axes().get_position().bounds
ax[j].annotate(ABC[j],xy=(axbb[0]+.0075,axbb[1]+axbb[3]-.03),xycoords='figure fraction')
sand=np.argwhere(data['wet_cells'][i,:]==0)
tmparray=[list(zip(data['nodell'][data['nv'][k,[0,1,2]],0],data['nodell'][data['nv'][k,[0,1,2]],1])) for k in sand ]
lseg_sand=PC(tmparray,facecolor = 'tan',edgecolor='tan')
ax[j].add_collection(lseg_sand)
f.canvas.draw()
background0 = f.canvas.copy_from_bbox(ax[0].bbox)
background1 = f.canvas.copy_from_bbox(ax[1].bbox)
for i in range(starttime,endtime,spacing):
print(i)
f.canvas.restore_region(background0)
f.canvas.restore_region(background1)
fcolors0=np.mean(data['salinity'][i,0,data['nv']],axis=1)
triax0.set_array(fcolors0)
ax[0].draw_artist(triax0)
def speed_plot(i):
print(i)
f, ax = place_axes(region, 2)
triax0 = ax[0].tripcolor(data['trigrid'],
data['salinity'][i, 0, :],
vmin=cmin,
vmax=cmax)
triax1 = ax[1].tripcolor(data['trigrid'],
data['salinity'][i, -1, :],
vmin=cmin,
vmax=cmax)
ppll_sub(ax,
setregion=region,
cb=triax0,
cblabel=r'Salinity',
llfontsize=10,
fontsize=8,
cblabelsize=6,
cbticksize=6,
cbtickrotation=-45)
ABC = ['A', 'B']
figW, figH = f.get_size_inches()
f.canvas.draw()
Q0 = ax[0].quiver(data['uvnodell'][vidx, 0],
data['uvnodell'][vidx, 1],
data['u'][i, 0, vidx],
data['v'][i, 0, vidx],
angles='xy',
scale_units='xy',
scale=vector_scale,
zorder=100,
width=.0025)
Q1 = ax[1].quiver(data['uvnodell'][vidx, 0],
data['uvnodell'][vidx, 1],
data['u'][i, -1, vidx],
data['v'][i, -1, vidx],
angles='xy',
scale_units='xy',
scale=vector_scale,
zorder=100,
width=.0025)
Qkey0 = ax[0].quiverkey(Q0,
.9,
.85,
1.0,
r'1.0 ms$^{-1}$',
fontproperties={'size': 8})
Qkey1 = ax[1].quiverkey(Q1,
.9,
.85,
1.0,
r'1.0 ms$^{-1}$',
fontproperties={'size': 8})
for j, axi in enumerate(ax):
if coastflag:
plotcoast(ax[j],
filename='mid_nwatl6c_sjh_lr.nc',
color='k',
fill=True,
lw=.5,
zorder=100,
filepath=coastpath)
axbb = ax[j].get_axes().get_position().bounds
ax[j].annotate(ABC[j],
xy=(axbb[0] + .0075, axbb[1] + axbb[3] - .03),
xycoords='figure fraction')
sand = np.argwhere(data['wet_cells'][i, :] == 0)
tmparray = [
list(
zip(data['nodell'][data['nv'][k, [0, 1, 2]], 0],
data['nodell'][data['nv'][k, [0, 1, 2]], 1])) for k in sand
]
lseg_sand = PC(tmparray, facecolor='tan', edgecolor='tan')
ax[j].add_collection(lseg_sand)
f.savefig(savepath + grid + '_' + region['regionname'] + '_salinity_' +
("%04d" % (i)) + '.png',
dpi=300)
plt.close(f)
scale_units='xy',
scale=scale1,
zorder=10)
Q2 = ax.quiver(savelag2['x'][sidx, 0],
savelag2['y'][sidx, 0],
q2x2,
q2y2,
angles='xy',
scale_units='xy',
scale=scale1,
color='r',
zorder=10)
ax.axis(region['regionxy'])
ax.triplot(data['trigridxy'], lw=.25)
lseg = PC(tmparray, facecolor='g', edgecolor='None', zorder=5)
ax.add_collection(lseg)
#fix_osw(ax)
#ax.set_aspect(get_aspectratio(region))
#plt.draw()
rec = mpl.patches.Rectangle((kl[0], kl[1]),
kl[2],
kl[3],
transform=ax.transAxes,
fc='w',
zorder=20)
ax.add_patch(rec)
ax.annotate(r'' + ebbfldscale + ' m',
xy=(kl[0] + .035, kl[1] + .07),
xycoords='axes fraction',