minlon=min(lon)
maxlat=max(lat)
minlat=min(lat)
#make sure the picture can show lat and lon clearly
if maxlat-minlat<=0.1:
maxlat=maxlat+0.01
minlat=minlat-0.01
if maxlon-minlon<=0.1:
maxlon=maxlon+0.01
minlon=minlon-0.01
gbox=[minlon-1.0,maxlon+1.0, minlat-0.03, maxlat+0.03] # get edge for get sst
for x in range(num):
ask_input=num2date(datetime_wanted) #get time for getsst
#plt.title(str(num2date(datetime_wanted).strftime("%d-%b-%Y %H"))+'h')
plot_getsst(ask_input,utc,gbox)
lat_wanted=lat[-1]
lon_wanted=lon[-1]
#find wanted point lat,lon
#plt.plot(lon_wanted,lat_wanted,'.',markersize=30,color='m',label='end')
plt.plot(np.reshape(lon,np.size(lon)),np.reshape(lat,np.size(lat)),linewidth=3,color='black')
#plt.plot(lon[0],lat[0],'.',markersize=20,color='g',label='start') # start time
plt.annotate('start',xy=(lon[0],lat[0]),xytext=(lon[0]+(maxlon-minlon)/10,lat[0]+(maxlat-minlat)/10),color='white',arrowprops=dict(facecolor='white',frac=0.3, shrink=0.05))
plt.annotate('end',xy=(lon[-1],lat[-1]),xytext=(lon[-1]+(maxlon-minlon)/10,lat[-1]-(maxlat-minlat)/5),color='white',arrowprops=dict(facecolor='white',frac=0.3, shrink=0.05))
plt.title('Drifter '+driftnumber+' and '+ask_input.strftime('%d %b %Y')+' SST')
basemap_standard([int(minlat),np.ceil(maxlat)],[int(minlon-1.5),np.ceil(maxlon)+1.0],2.0) #overrides xlim and ylims set previously
plt.show()
#get FVCOM depths
url = 'http://www.smast.umassd.edu:8080/thredds/dodsC/fvcom/hindcasts/30yr_gom3?lon,lat,h,nv'
nc = netCDF4.Dataset(url)
lat = nc.variables['lat'][:]
lon = nc.variables['lon'][:]
h = nc.variables['h'][:]
# read connectivity array
nv = nc.variables['nv'][:].T - 1
# create a triangulation object, specifying the triangle connectivity array
tri = Tri.Triangulation(lon,lat, triangles=nv)
# plot depth using tricontourf
fig=plt.figure(figsize=(6,8))
ax1=fig.add_subplot(211)
basemap_standard([latrng[0],latrng[1]],[lonrng[0],lonrng[1]],[0.2])
cont_range.reverse()
tricontourf(tri,h*-1,list(np.array(cont_range)*-1))#contour range from fvcom_depth_ctl.py file
colorbar()
ylim(latrng)
xlim(lonrng)
plt.title('FVCOM GOM3 Depth (m)')
plt.plot([-68.158,-67.327,-67.248],[44.127,44.485,44.487],'w*',markersize=10)#cases of bad depths in FVCOM
plt.show()
# now plot usgs depths for specified region
ax2=fig.add_subplot(212)
print 'Now running basemap_usgs'
basemap_usgs([latrng[0],latrng[1]],[lonrng[0],lonrng[1]],True,True,[0.2],list(np.array(cont_range)*-1),1)
plt.title('USGS GOM3_v1_0 Depth (m)')
plt.plot([-68.158,-67.327,-67.248],[44.127,44.485,44.487],'w*',markersize=10)#bad depths
aa=int(a)
bb=float(b)
lat.append(aa+bb/60)
(c,d)=divmod(float(df['LON_DDMM'][i]),100)
cc=int(c)
dd=float(d)
lon.append(-1*(cc+dd/60))
latsize=[39.,45.0]
lonsize=[-73.,-66.0]
bathy=True
draw_parallels=True
parallels_interval=[2]
cont_range=[-200,-100]
ss=10
basemap_usgs(latsize,lonsize,bathy,draw_parallels,parallels_interval,cont_range,ss)
basemap_standard(latsize,lonsize,[2])
#plt.figure(figsize=(7,6))
#x, y = m(-lon.values,lat.values)
x, y = lon,lat
plt.scatter(x,y,20,marker='o',color='r')
for i in range(len(x)):
if df.index[i] in threesite:
#print df.index[i],lat[i],lon[i]
plt.scatter(x[i],y[i],20,marker='o',color='blue')
if df.index[i]=='BN01':
plt.annotate(df.index[i],xy=(x[i],y[i]),xytext=(x[i]+0.81,y[i]-0.35),arrowprops=dict(facecolor='blue', shrink=0.1,frac=0.3))#facecolor='black',));
else:
plt.annotate(df.index[i],xy=(x[i],y[i]),xytext=(x[i]-0.31,y[i]-0.65),arrowprops=dict(facecolor='blue', shrink=0.1,frac=0.3))#facecolor='black',));
#plt.annotate(df.index[i],xy=(x[i],y[i]),xytext=(x[i]-0.31,y[i]-0.75),arrowprops=dict(arrowstyle="-|>",shrink=0.1))#connectionstyle="arc3,rad=-0.2",fc="w"));
if df.index[i] in surfacesite:
#print df.index[i],lat[i],lon[i]
ask_input = num2date(datetime_wanted) #get time for getsst
#plt.title(str(num2date(datetime_wanted).strftime("%d-%b-%Y %H"))+'h')
plot_getsst(ask_input, utc, gbox)
lat_wanted = lat[-1]
lon_wanted = lon[-1]
#find wanted point lat,lon
#plt.plot(lon_wanted,lat_wanted,'.',markersize=30,color='m',label='end')
plt.plot(np.reshape(lon, np.size(lon)),
np.reshape(lat, np.size(lat)),
linewidth=3,
color='black')
#plt.plot(lon[0],lat[0],'.',markersize=20,color='g',label='start') # start time
plt.annotate('start',
xy=(lon[0], lat[0]),
xytext=(lon[0] + (maxlon - minlon) / 10,
lat[0] + (maxlat - minlat) / 10),
color='white',
arrowprops=dict(facecolor='white', frac=0.3, shrink=0.05))
plt.annotate('end',
xy=(lon[-1], lat[-1]),
xytext=(lon[-1] + (maxlon - minlon) / 10,
lat[-1] - (maxlat - minlat) / 5),
color='white',
arrowprops=dict(facecolor='white', frac=0.3, shrink=0.05))
plt.title('Drifter ' + driftnumber + ' and ' +
ask_input.strftime('%d %b %Y') + ' SST')
basemap_standard([int(minlat), np.ceil(maxlat)],
[int(minlon - 1.5), np.ceil(maxlon) + 1.0],
2.0) #overrides xlim and ylims set previously
plt.show()
import sys
sys.path.append("../modules")
import basemap as bm
import matplotlib.pyplot as plt
# the following three lines are needed to later place the figure windows on the screen
import matplotlib
matplotlib.use("wx")
import pylab
# use the standard Basemap
plt.figure(1, figsize=(5, 4)) # makes figure less than the defaul 8x6 inches
bm.basemap_standard([42.0, 43.0], [-71.0, -70.0], [0.5]) # always make this last argument a list in brackets
# position figure window on the screen
thismanager1 = pylab.get_current_fig_manager()
thismanager1.window.SetPosition((0, 0))
plt.title("basemap_standard")
plt.show()
# use the ascii files of coastline already on disk
plt.figure(2, figsize=(5, 4))
bm.basemap_region("sne")
thismanager2 = pylab.get_current_fig_manager()
thismanager2.window.SetPosition((0, 500))
plt.title("basemap_region")
plt.show()
# extract coastline and bathymetry using pydap
import sys
sys.path.append("../modules")
import basemap as bm
import matplotlib.pyplot as plt
import pylab
from pylab import ginput
import numpy as np
# extract coastline and bathymetry using pydap
plt.figure(1,figsize=(10,8))
#bm.basemap_detail([41.,43.5],[-72.,-69.0],True,True,0.5)
#bm.basemap_detail([41.0,43.5],[-72.,-69.0],True,False)
bm.basemap_standard([41.0,43.5],[-72.,-69.0], [2])
plt.title('PIs (white) and Partners (black)',fontsize=18)
plt.show()
sites=['GOMI','NESS','WHOI','SSC','SSNSC','WHSTEP','NEFSC','CCS','NGSS','CMHS','NEAq','SEA','SBNMS','WBWS','CSWA']
nums=len(sites)
print 'There are '+str(nums)+'sites'
'''pts=ginput(nums, timeout=120)
x=map(lambda x: x[0],pts) # map applies the function passed as
y=map(lambda x: x[1],pts) # first parameter to each e
np.save('sites',[x,y])
'''
p=np.load('sites.npy')
x=p[0]
y=p[1]
for k in range(len(x)):
plt.plot(x[k], y[k],'.',color='w')
plt.annotate(sites[k],xy=(x[k],y[k]),xytext=(x[k]+.3,y[k]),arrowprops=dict(facecolor='black', shrink=0.05))
plt.show()
