"""

"""

print 'plot_cr1000_gps ...'

img_dir = '/home/haines/rayleigh/img'

prev_month, this_month, next_month = procutil.find_months(yyyy_mm)

yyyy_mm_str = this_month.strftime('%Y_%m')

fn = '_'.join([pi['id'], si['id'], prev_month.strftime('%Y_%m')+'.nc'])

ncFile1= os.path.join(si['proc_dir'], fn)

fn = '_'.join([pi['id'], si['id'], this_month.strftime('%Y_%m')+'.nc'])

ncFile2= os.path.join(si['proc_dir'], fn)

# ncFile1='/seacoos/data/nccoos/level1/meet/wq/meet_wq_'+prev_month.strftime('%Y_%m')+'.nc'

# ncFile2='/seacoos/data/nccoos/level1/meet/wq/meet_wq_'+this_month.strftime('%Y_%m')+'.nc'

have_ncFile1 = os.path.exists(ncFile1)

have_ncFile2 = os.path.exists(ncFile2)

print ' ... loading data for graph from ...'

print ' ... ... ' + ncFile1 + ' ... ' + str(have_ncFile1)

print ' ... ... ' + ncFile2 + ' ... ' + str(have_ncFile2)

# open netcdf data

if have_ncFile1 and have_ncFile2:

nc = pycdf.CDFMF((ncFile1, ncFile2))

elif not have_ncFile1 and have_ncFile2:

nc = pycdf.CDFMF((ncFile2,))

elif have_ncFile1 and not have_ncFile2:

nc = pycdf.CDFMF((ncFile1,))

else:

print ' ... both files do not exist -- NO DATA LOADED'

return

# ncvars = nc.variables()

# print ncvars

es = nc.var('time')[:]

units = nc.var('time').units

dt = [procutil.es2dt(e) for e in es]

# set timezone info to UTC (since data from level1 should be in UTC!!)

dt = [e.replace(tzinfo=dateutil.tz.tzutc()) for e in dt]

# return new datetime based on computer local

dt_local = [e.astimezone(dateutil.tz.tzlocal()) for e in dt]

dn = date2num(dt)

# last dt in data for labels

dtu = dt[-1]

dtl = dt_local[-1]

diff = abs(dtu - dtl)

if diff.days>0:

last_dt_str = dtu.strftime("%H:%M %Z on %b %d, %Y") + ' (' + dtl.strftime("%H:%M %Z, %b %d") + ')'

else:

last_dt_str = dtu.strftime("%H:%M %Z") + ' (' + dtl.strftime("%H:%M %Z") + ')' \

+ dtl.strftime(" on %b %d, %Y")

#######################################

# Build Plot

#######################################

fig = figure(figsize=(6, 5))

fig.subplots_adjust(left=0.20, bottom=0.10, right=0.9, top=0.9, wspace=0.1, hspace=0.1)

ax = fig.add_subplot(1,1,1)

axs = [ax]

# GPS longitude on x, latitude on y

gps_lon = nc.var('gps_lon')[:]

gps_lat = nc.var('gps_lat')[:]

# gps_lon[-1:] returns last value as type numpy.array

# gps_lon[-1] returns the value as type float

(x, y) = (gps_lon[-1:], gps_lat[-1:])

# print (x, y)

# ax.plot returns a list of lines, so unpack tuple

l1, = ax.plot(x, y, 'r*', ms=8)

# anchor position platform lat and lon from config -- needs to be numpy.array([]) for ax.plot

(x, y) = (numpy.array([pi['lon']]), numpy.array([pi['lat']]))

# anchor posn platform lat and lon from netcdf file (should be the same as config)

# (x, y) = (nc.var('lon')[:], nc.var('lat')[:])

# print (x, y)

l2, = ax.plot(x, y, 'ks', ms=8, mfc='none')

# 1km watch circle, approx 111 km in 1 deg latitude 1 km is 1/111 of a deg

if 0:

wc = Circle((x,y), 1./111, alpha=0.2)

wc.set_label('1 km Watch Circle')

p = PatchCollection([wc], alpha=0.2)

ax.add_collection(p)

leg1 = ax.legend([wc], '1 km Watch Circle', loc='lower left')

ax.set_xlabel('Longitude (deg)')

ax.set_ylabel('Latitude (deg)')

ax.axis('equal')

# keep tick formatting from defaulting scienitific with offsets

from matplotlib.ticker import FormatStrFormatter

ax.xaxis.set_major_formatter(FormatStrFormatter('%g'))

ax.yaxis.set_major_formatter(FormatStrFormatter('%g'))

# limit number of ticks on x-axis to 5 to allow for the squeeze

locator = ax.xaxis.get_major_locator()

locator._nbins=5

ax.xaxis.set_major_locator(locator)

# legend

leg = ax.legend((l2,l1), ('Anchor Position', 'Current Buoy GPS') , loc='upper left')

ltext = leg.get_texts() # all the text.Text instance in the legend

llines = leg.get_lines() # all the lines.Line2D instance in the legend

frame = leg.get_frame() # the patch.Rectangle instance surrounding the legend

frame.set_facecolor('0.80') # set the frame face color to light gray

frame.set_alpha(0.5) # set alpha low to see through

setp(ltext, fontsize='small') # the legend text fontsize

setp(llines, linewidth=1.5) # the legend linewidth

# leg.draw_frame(False) # don't draw the legend frame

#######################################

# YYYY_MM

#######################################

title_str = ' '.join([pi['id'].upper(), si['description']])

if plot_type=='latest' or plot_type=='monthly':

print ' ... : %s' % (yyyy_mm_str,)

ax.set_title(title_str+' -- ' + yyyy_mm_str)

dns = date2num(this_month)

dne = date2num(next_month-datetime.timedelta(seconds=1))

idx = (dn>=dns) & (dn<=dne)

c = ax.scatter(gps_lon[idx],gps_lat[idx],c=dn[idx],

cmap=cm.jet,vmin=dns,vmax=dne)

cbar = fig.colorbar(c, ticks=DayLocator(range(0,32,2)),format=DateFormatter('%m/%d'))

fn = '_'.join([pi['id'], si['id'], yyyy_mm_str+'.png'])

ofn = os.path.join(img_dir, pi['id'], fn) # /home/haines/rayleigh/img/meet

savefig(ofn)

# remove scatter instances and colorbar axis for next plot

c.remove()

fig.delaxes(fig.axes[1])

fig.subplots_adjust(left=0.20, bottom=0.10, right=0.9, top=0.9, wspace=0.1, hspace=0.1)

#######################################

# Last 30 days

#######################################

if plot_type=='latest':

print ' ... Last 30 days'

ax.set_title(title_str+'\n Last 30 days from '+last_dt_str)

dns = date2num(dt[-1])-30

dne = date2num(dt[-1])

idx = (dn>=dns) & (dn<=dne)

c = ax.scatter(gps_lon[idx],gps_lat[idx],c=dn[idx],

cmap=cm.jet,vmin=dns,vmax=dne)

cbar = fig.colorbar(c, ticks=DayLocator(range(0,32,2)),format=DateFormatter('%m/%d'))

fn = '_'.join([pi['id'], si['id'], 'last30days.png'])

ofn = os.path.join(img_dir, fn) # /home/haines/rayleigh/img/

savefig(ofn)

# remove scatter instances and colorbar axis for next plot

c.remove()

fig.delaxes(fig.axes[1])

fig.subplots_adjust(left=0.20, bottom=0.10, right=0.9, top=0.9, wspace=0.1, hspace=0.1)

#######################################

# Last 7 days

#######################################

if plot_type=='latest':

print ' ... Last 7 days'

ax.set_title(title_str+'\n Last 7 days from '+last_dt_str)

dns = date2num(dt[-1])-7

dne = date2num(dt[-1])

idx = (dn>=dns) & (dn<=dne)

c = ax.scatter(gps_lon[idx],gps_lat[idx],c=dn[idx],

cmap=cm.jet,vmin=dns,vmax=dne)

cbar = fig.colorbar(c, ticks=DayLocator(range(0,32,1)),format=DateFormatter('%m/%d'))

fn = '_'.join([pi['id'], si['id'], 'last07days.png'])

ofn = os.path.join(img_dir, fn) # /home/haines/rayleigh/img

savefig(ofn)

# remove scatter instances and colorbar axis for next plot

c.remove()

fig.delaxes(fig.axes[1])

fig.subplots_adjust(left=0.20, bottom=0.10, right=0.9, top=0.9, wspace=0.1, hspace=0.1)

#######################################

# Last 1 day (24hrs)

#######################################

if plot_type=='latest':

print ' ... Last 1 days'

ax.set_title(title_str+'\n Last 24 hours from '+last_dt_str)

dns = date2num(dt[-1])-1

dne = date2num(dt[-1])

idx = (dn>=dns) & (dn<=dne)

c = ax.scatter(gps_lon[idx],gps_lat[idx],c=dn[idx],

cmap=cm.jet,vmin=dns,vmax=dne)

cbar = fig.colorbar(c, ticks=HourLocator(range(0,25,1)),format=DateFormatter('%H'))

fn = '_'.join([pi['id'], si['id'], 'last01days.png'])

ofn = os.path.join(img_dir, fn) # /home/haines/rayleigh/img

savefig(ofn)

# remove scatter instances and colorbar axis for next plot

c.remove()

fig.delaxes(fig.axes[1])