#!/usr/bin/env python
# coding: utf-8

# In[1]:


import netCDF4 as nc
import matplotlib.pyplot as plt
import numpy as np
from salishsea_tools import viz_tools,tidetools

get_ipython().run_line_magic('matplotlib', 'inline')


# In[2]:


grid = '/data/nsoontie/MEOPAR/NEMO-forcing/grid/bathy_meter_SalishSea2.nc'
fB = nc.Dataset(grid)
bathy=fB.variables['Bathymetry'][:]
X = fB.variables['nav_lon'][:]
Y=fB.variables['nav_lat'][:]


# In[3]:


lat36 = 50.135820
lon36 = -125.353403

j36, i36 = tidetools.find_closest_model_point(lon36, lat36, X, Y, bathy)
print i36, j36



# In[4]:


plt.pcolormesh(bathy)
plt.plot(i36,j36,'ro')
plt.axis([110,150,750,790])


# Very close to the land. How does the U/V grid look?

# In[5]:


ufil='/data/dlatorne/MEOPAR/SalishSea/nowcast/24jan15/SalishSea_1d_20150124_20150124_grid_U.nc'
fU = nc.Dataset(ufil)
U = fU.variables['vozocrtx']
U=np.ma.masked_values(U[0,0,:,:],0)

plt.pcolormesh(U)
plt.plot(i36,j36,'ro')
plt.axis([110,125,765,780])

print U[j36,i36]
print U[j36,i36-1]


# U masked at the unstagger point. So this index is no good for tidal currents.

# In[6]:


vfil='/data/dlatorne/MEOPAR/SalishSea/nowcast/24jan15/SalishSea_1d_20150124_20150124_grid_V.nc'
fV = nc.Dataset(vfil)
V = fV.variables['vomecrty']
V=np.ma.masked_values(V[0,0,:,:],0)

plt.pcolormesh(V)
plt.plot(i36,j36,'ro')
plt.axis([110,125,765,780])

print V[j36,i36]
print V[j36-1,i36]


# Adjust i,j until we find a point that works...

# In[7]:


inew=i36-1
jnew=j36-2
print inew, jnew



# In[8]:


ufil='/data/dlatorne/MEOPAR/SalishSea/nowcast/24jan15/SalishSea_1d_20150124_20150124_grid_U.nc'
fU = nc.Dataset(ufil)
U = fU.variables['vozocrtx']
U=np.ma.masked_values(U[0,0,:,:],0)

plt.pcolormesh(U)
plt.plot(inew,jnew,'ro')
plt.axis([110,125,765,780])

print U[jnew,inew]
print U[jnew,inew-1]


# In[9]:


vfil='/data/dlatorne/MEOPAR/SalishSea/nowcast/24jan15/SalishSea_1d_20150124_20150124_grid_V.nc'
fV = nc.Dataset(vfil)
V = fV.variables['vomecrty']
V=np.ma.masked_values(V[0,0,:,:],0)

plt.pcolormesh(V)
plt.plot(inew,jnew,'ro')
plt.axis([110,125,765,780])

print V[jnew,inew]
print V[jnew-1,inew]


# In[10]:


print X[jnew,inew], X[j36,i36]
print Y[jnew,inew], Y[j36,i36]
print bathy[jnew,inew], bathy[j36,i36]


# In[11]:


plt.pcolormesh(bathy)
plt.plot(i36,j36,'ro')
plt.plot(inew,jnew,'yo')
plt.axis([110,125,765,780])


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