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

# In[1]:


import numpy as np
import netCDF4 as nc
import matplotlib.pyplot as plt
from salishsea_tools import viz_tools, places,geo_tools
get_ipython().run_line_magic('matplotlib', 'inline')


# In[3]:


mesh=nc.Dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc')


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bathy=nc.Dataset('/data/eolson/results/MEOPAR/NEMO-forcing-new/grid/bathymetry_201702.nc')


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mesh.variables.keys()


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bathy.variables.keys()


# In[16]:


latQU39=50.0307
lonQU39=-125.0992


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fig,ax=plt.subplots(1,1,figsize=(8,5))
ax.pcolormesh(bathy['nav_lon'],bathy['nav_lat'],bathy['Bathymetry'])
ax.set_xlim(-125.5,-124)
ax.set_ylim(49.5,50.3)
ax.plot(lonQU39,latQU39,'r*')
viz_tools.set_aspect(ax,coords='map')


# In[14]:


places.PLACES


# In[21]:


# NEMO grid
j,i=geo_tools.find_closest_model_point(lonQU39,latQU39,mesh.variables['nav_lon'][:,:],mesh.variables['nav_lat'][:,:])
print(j,i)


# In[22]:


# ops grid
ops=nc.Dataset('/results/forcing/atmospheric/GEM2.5/operational/ops_y2015m08d16.nc')
ops.variables.keys()


# In[30]:


jo,io=geo_tools.find_closest_model_point(lonQU39,latQU39,ops.variables['nav_lon'][:,:]-360,ops.variables['nav_lat'][:,:],grid='GEM2.5',)
print(jo,io)


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