import matplotlib.mlab as ml
import numpy as np
#from basemap import basemap_usgs
pydir='../'
sys.path.append(pydir)
from hx import getcodar_ctl_file_edge,getcodar_ctl_lalo,getcodar_ctl_id,getcodar_edge
###############################################
inputfilename='./getcodar_byrange_ctl.txt'
png_num=0 # for saving picture
datetime_wanted,url,model_option,lat_max,lon_max,lat_min,lon_min,num,interval_dtime=getcodar_ctl_file_edge(inputfilename) # reads control file
for i in range(num): # loop through number of figures
png_num=png_num+1
lat_max_i,lon_max_i,lat_min_i,lon_min_i=getcodar_ctl_lalo(model_option,lat_max,lon_max,lat_min,lon_min) # gets spatial index of box
id=getcodar_ctl_id(model_option,url,datetime_wanted) # gets time index
lat_vel,lon_vel,u,v=getcodar_edge(url,id,lat_max_i,lon_max_i,lat_min_i,lon_min_i) # gets actual values of lat, lon, U & V
id=str(id)
idg1=list(ml.find(np.array(u)<>-999.0/100.)) # index u values that are good
idg2=list(ml.find(np.array(lat_vel)>=lat_min)) # index lats > lat_min
idg12=list(set(idg1).intersection(set(idg2))) # intersection of idg1 and idg2
idg3=list(ml.find(np.array(lon_vel)>=lon_min)) # index lon > lon_min
idg=list(set(idg12).intersection(set(idg3))) # final intersection
if len(idg)<>0:
plt.title('')
plt.title(str(num2date(datetime_wanted).strftime("%d-%b-%Y %H"))+'h')
pylab.ylim([lat_min-0.02,lat_max+0.02])
pylab.xlim([lon_min-0.02,lon_max+0.02]) #enge
q=plt.quiver(np.reshape(lon_vel,np.size(lon_vel))[idg],np.reshape(lat_vel,np.size(lat_vel))[idg],np.reshape(u,np.size(u))[idg],np.reshape(v,np.size(v))[idg],angles='xy',scale=3,color='b')
p=plt.quiverkey(q,min(lon_vel[0])+.1,max(lat_vel[0])-.1,1.2,str(round(1.2,2))+"m/s",coordinates='data',color='r')
#bathy=False
maxlat=maxlat+0.01
minlat=minlat-0.01
if maxlon-minlon<=0.1:
maxlon=maxlon+0.01
minlon=minlon-0.01
(lat_max_i,lon_max_i,lat_min_i,lon_min_i)=getcodar_ctl_lalo(model_option,maxlat,maxlon,minlat,minlon)# get index of max min lat lon
gbox=[minlon-0.03,maxlon+0.03, minlat-0.03, maxlat+0.03] # get edge for get sst
for x in range(num):
id=getcodar_ctl_id(model_option,url,datetime_wanted) #get index of codar
ask_input=num2date(datetime_wanted) #get time for getsst
(drifter_data)=getdrift_raw(filename,id3,interval,datetime_wanted) #get drifter data
lat=drifter_data['lat']
lon=drifter_data['lon']
(lat_vel,lon_vel,u,v)=getcodar_edge(url,id,lat_max_i,lon_max_i,lat_min_i,lon_min_i) #get codar data
id=str(id)
idg1=list(ml.find(np.array(u)<>-999.0/100.))
idg2=list(ml.find(np.array(lat_vel)>=minlat))
idg12=list(set(idg1).intersection(set(idg2)))
idg3=list(ml.find(np.array(lon_vel)>=minlon))
idg=list(set(idg12).intersection(set(idg3))) #get index for codar data based on edge and id(time)
png_num=png_num+1 #for save movie picture
if len(idg)<>0:
fig = plt.figure()
ax = fig.add_subplot(111)
sys.path.append(pydir)
from hx import getcodar_ctl_file_edge, getcodar_ctl_lalo, getcodar_ctl_id, getcodar_edge
###############################################
inputfilename = './getcodar_byrange_ctl.txt'
png_num = 0 # for saving picture
datetime_wanted, url, model_option, lat_max, lon_max, lat_min, lon_min, num, interval_dtime = getcodar_ctl_file_edge(
inputfilename) # reads control file
for i in range(num): # loop through number of figures
png_num = png_num + 1
lat_max_i, lon_max_i, lat_min_i, lon_min_i = getcodar_ctl_lalo(
model_option, lat_max, lon_max, lat_min,
lon_min) # gets spatial index of box
id = getcodar_ctl_id(model_option, url, datetime_wanted) # gets time index
lat_vel, lon_vel, u, v = getcodar_edge(
url, id, lat_max_i, lon_max_i, lat_min_i,
lon_min_i) # gets actual values of lat, lon, U & V
id = str(id)
idg1 = list(
ml.find(np.array(u) <> -999.0 / 100.)) # index u values that are good
idg2 = list(ml.find(np.array(lat_vel) >= lat_min)) # index lats > lat_min
idg12 = list(set(idg1).intersection(
set(idg2))) # intersection of idg1 and idg2
idg3 = list(ml.find(np.array(lon_vel) >= lon_min)) # index lon > lon_min
idg = list(set(idg12).intersection(set(idg3))) # final intersection
if len(idg) <> 0:
plt.title('')
plt.title(str(num2date(datetime_wanted).strftime("%d-%b-%Y %H")) + 'h')
pylab.ylim([lat_min - 0.02, lat_max + 0.02])
pylab.xlim([lon_min - 0.02, lon_max + 0.02]) #enge
minlon = minlon - 0.01
(lat_max_i, lon_max_i, lat_min_i,
lon_min_i) = getcodar_ctl_lalo(model_option, maxlat, maxlon, minlat,
minlon) # get index of max min lat lon
gbox = [minlon - 0.03, maxlon + 0.03, minlat - 0.03,
maxlat + 0.03] # get edge for get sst
for x in range(num):
id = getcodar_ctl_id(model_option, url,
datetime_wanted) #get index of codar
ask_input = num2date(datetime_wanted) #get time for getsst
(lat, lon, time1) = getdrift_raw(filename, id3, interval,
datetime_wanted) #get drifter data
(lat_vel, lon_vel, u, v) = getcodar_edge(url, id, lat_max_i, lon_max_i,
lat_min_i,
lon_min_i) #get codar data
id = str(id)
idg1 = list(ml.find(np.array(u) <> -999.0 / 100.))
idg2 = list(ml.find(np.array(lat_vel) >= minlat))
idg12 = list(set(idg1).intersection(set(idg2)))
idg3 = list(ml.find(np.array(lon_vel) >= minlon))
idg = list(set(idg12).intersection(
set(idg3))) #get index for codar data based on edge and id(time)
png_num = png_num + 1 #for save movie picture
if len(idg) <> 0:
fig = plt.figure()
sys.path.append('../')
#from basemap import basemap_standard
from hx import getcodar_ctl_file_edge,getcodar_ctl_lalo,getcodar_ctl_id,getcodar_edge, plot_getsst
utc = pytz.timezone('UTC')
png_num=0 # for saving picture
inputfilename='./getcodar_byrange_ctl.txt'
datetime_wanted,url,model_option,lat_max,lon_max,lat_min,lon_min,num,interval_dtime=getcodar_ctl_file_edge(inputfilename) #get data from ctl file
gbox=[lon_min, lon_max, lat_min, lat_max]# 2012 ring , get edge box for sst
lat_max_i,lon_max_i,lat_min_i,lon_min_i=getcodar_ctl_lalo(model_option,lat_max,lon_max,lat_min,lon_min)
for i in range(num):
png_num=png_num+1
id=getcodar_ctl_id(model_option,url,datetime_wanted)
lat_vel,lon_vel,u,v=getcodar_edge(url,id,lat_max_i,lon_max_i,lat_min_i,lon_min_i) #get edge of codar
id=str(id) # change id format
idg1=list(ml.find(np.array(u)<>-999.0/100.))
idg2=list(ml.find(np.array(lat_vel)>=lat_min))
idg12=list(set(idg1).intersection(set(idg2)))
idg3=list(ml.find(np.array(lon_vel)>=lon_min))
idg=list(set(idg12).intersection(set(idg3))) # get index of codar data
if len(idg)<>0:
ask_input=num2date(datetime_wanted)
plot_getsst(ask_input,utc,gbox)
q=plt.quiver(np.reshape(lon_vel,np.size(lon_vel))[idg],np.reshape(lat_vel,np.size(lat_vel))[idg],np.reshape(u,np.size(u))[idg],np.reshape(v,np.size(v))[idg],angles='xy',scale=5,color='black')
plt.title(str(num2date(datetime_wanted).strftime("%d-%b-%Y %H"))+'h')
pylab.ylim([lat_min+0.01,lat_max-0.01])
