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

# In[1]:


import datetime as dt
import numpy as np
import xarray as xr
import matplotlib.pyplot as plt
from matplotlib.colors import LogNorm

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


# In[2]:


f=xr.open_dataset('https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DBiologyFields1hV19-05')
f


# In[3]:


i0=130;i1=350
j0=330;j1=750
fig,ax=plt.subplots(1,1,figsize=(3,5))
ax.pcolormesh(f.variables['nitrate'][0,0,:,:])
ax.plot((i0,i1,i1,i0,i0),(j0,j0,j1,j1,j0),'r-')
f.close()


# In[4]:


fig,ax=plt.subplots(10,2,figsize=(14,30))
fig.subplots_adjust(hspace=.4,wspace=.3)
ax=ax.flatten()
time=dt.datetime(2017,7,1,0,30)
with xr.open_dataset('https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DBiologyFields1hV19-05') as f:
    with xr.open_dataset('https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DTracerFields1hV19-05') as fT:
        for k in range(0,20):
            sal=np.array(fT.salinity.sel(time=dt.datetime(2017,7,1,0,30)).\
                         isel(depth=k,gridY=slice(j0,j1),gridX=slice(i0,i1)).values).flatten()
            no3=np.array(f.nitrate.sel(time=time).\
                         isel(depth=k,gridY=slice(j0,j1),gridX=slice(i0,i1)).values).flatten()
            counts, xedges, yedges, m1=ax[k].hist2d(sal[~np.isnan(sal)&~np.isnan(no3)],
                                                    no3[~np.isnan(sal)&~np.isnan(no3)],
                                                    bins=36*3,norm=LogNorm())
            cb=fig.colorbar(m1,ax=ax[k])
            cb.set_label('Count')
            ax[k].set_title('level k='+str(k))
            ax[k].set_xlabel('S (g/kg)')
            ax[k].set_ylabel('NO3 ($\mu$M)')
print('July 1')


# In[5]:


fig,ax=plt.subplots(10,2,figsize=(14,30))
fig.subplots_adjust(hspace=.4,wspace=.3)
ax=ax.flatten()
time=dt.datetime(2017,3,1,0,30)
with xr.open_dataset('https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DBiologyFields1hV19-05') as f:
    with xr.open_dataset('https://salishsea.eos.ubc.ca/erddap/griddap/ubcSSg3DTracerFields1hV19-05') as fT:
        for k in range(0,20):
            sal=np.array(fT.salinity.sel(time=dt.datetime(2017,7,1,0,30)).\
                         isel(depth=k,gridY=slice(j0,j1),gridX=slice(i0,i1)).values).flatten()
            no3=np.array(f.nitrate.sel(time=time).\
                         isel(depth=k,gridY=slice(j0,j1),gridX=slice(i0,i1)).values).flatten()
            counts, xedges, yedges, m1=ax[k].hist2d(sal[~np.isnan(sal)&~np.isnan(no3)],
                                                    no3[~np.isnan(sal)&~np.isnan(no3)],
                                                    bins=36*3,norm=LogNorm())
            cb=fig.colorbar(m1,ax=ax[k])
            cb.set_label('Count')
            ax[k].set_title('level k='+str(k))
            ax[k].set_xlabel('S (g/kg)')
            ax[k].set_ylabel('NO3 ($\mu$M)')
print('March 1')


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