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

# In[1]:


import numpy as np
import matplotlib.pyplot as plt
import netCDF4 as nc

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


# In[2]:


with nc.Dataset('/data/eolson/MEOPAR/NEMO-forcing-new/grid/mesh_mask201702.nc') as mesh:
    tmask=mesh.variables['tmask'][:,:,:,:]


# In[4]:


get_ipython().system('ls /data/sallen/results/MEOPAR/202007/202007D-nociliates')


# In[8]:


f0=nc.Dataset('/data/sallen/results/MEOPAR/202007/202007D-nociliates/SalishSea_1d_20150101_20150105_ptrc_T_20150101-20150101.nc')


# In[9]:


f0.variables['ciliates']


# In[10]:


np.max(np.ma.masked_where(tmask==0,f0.variables['ciliates']))


# In[16]:


fig,ax=plt.subplots(1,1,figsize=(5,10))
m=ax.pcolormesh(np.sum(np.ma.masked_where(f0.variables['ciliates'][0,:,:,:]==0,
                                        f0.variables['ciliates'][0,:,:,:]),0))
plt.colorbar(m)


# In[17]:


fig,ax=plt.subplots(1,1,figsize=(5,10))
m=ax.pcolormesh(np.sum(np.ma.masked_where(tmask[0,:,:,:]==0,
                                        f0.variables['ciliates'][0,:,:,:]),0))
plt.colorbar(m)


# In[21]:


friv=nc.Dataset('/results/forcing/rivers/R201702DFraCElse_y2015m01d01.nc')


# In[23]:


friv.variables['rorunoff']


# In[26]:


fig,ax=plt.subplots(1,2,figsize=(10,10))
m=ax[0].pcolormesh(np.sum(np.ma.masked_where(tmask[0,:,:100,100:200]==0,
                                        f0.variables['ciliates'][0,:,:100,100:200]),0))
plt.colorbar(m,ax=ax[0])
m=ax[1].pcolormesh(np.ma.masked_where(friv.variables['rorunoff'][0,:100,100:200]==0,
                                        friv.variables['rorunoff'][0,:100,100:200]))
plt.colorbar(m,ax=ax[1])


# In[27]:


f2=nc.Dataset('/data/sallen/results/MEOPAR/202007/202007D-nociliates/SalishSea_1d_20150516_20150520_ptrc_T_20150518-20150518.nc')


# In[28]:


fig,ax=plt.subplots(1,1,figsize=(5,10))
m=ax.pcolormesh(np.sum(np.ma.masked_where(f2.variables['ciliates'][0,:,:,:]==0,
                                        f2.variables['ciliates'][0,:,:,:]),0))
plt.colorbar(m)


# In[ ]: