%matplotlib inline
from matplotlib import pylab
import matplotlib.pyplot as plt
import netCDF4 as NC
import numpy as np
from mpl_toolkits.mplot3d import Axes3D

from salishsea_tools import (nc_tools,viz_tools)

f= NC.Dataset('/ocean/nsoontie/MEOPAR/Ariane/examples/qualitative/ariane_trajectories_qualitative.nc','r');

nc_tools.show_variables(f)

nc_tools.show_dimensions(f)

lon=f.variables['traj_lon']
lat=f.variables['traj_lat']
dep=f.variables['traj_depth']
print lon

fig = plt.figure(figsize=(20,10))
ax = fig.gca(projection='3d')
colors=['b','g','r']

for i  in range(3):
    ax.scatter(lon[:,i],lat[:,i],dep[:,i],c=colors[i])

ax.set_xlabel('lon')
ax.set_ylabel('lat')
ax.set_zlabel('depth')

#Ariane
f= NC.Dataset('/ocean/nsoontie/MEOPAR/Ariane/results/dec2006/1hour/ariane_trajectories_qualitative.nc','r');
lont=f.variables['traj_lon']
latt=f.variables['traj_lat']
dept=f.variables['traj_depth']

xs=f.variables['init_x']
ys=f.variables['init_y']

#Bathymetry
fB = NC.Dataset('/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc','r')
lats = fB.variables['nav_lat']
lons = fB.variables['nav_lon']
D = fB.variables['Bathymetry']
print ys[0]

fig, ax = plt.subplots(1,1,figsize=(5,8))

ax.scatter(lont[:,0],latt[:,0],c='r')
ax.plot(lons[int(ys[0]),int(xs[0])],lats[int(ys[0]),int(xs[0])], 's')
viz_tools.plot_land_mask(ax,fB,coords='map')

ax.set_xlabel('lon')
ax.set_ylabel('lat')
ax.set_xlim([-123.8,-122.8])
ax.set_ylim([48.8,49.5])