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

# In[1]:


get_ipython().run_line_magic('reset', '')
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import xarray as xr

get_ipython().run_line_magic('matplotlib', 'inline')
plt.rcParams['image.cmap'] = 'jet'


# In[2]:


nowcast_tracer_path = "/results/SalishSea/nowcast-green/12apr16/SalishSea_1h_20160412_20160412_ptrc_T.nc"
diat_iopt_84_tracer_path = "/data/jpetrie/MEOPAR/SalishSea/results/apr12_double_iopt_diat/SalishSea_1h_20160412_20160412_ptrc_T.nc"

n_grid_t = xr.open_dataset(nowcast_tracer_path)
m_grid_t = xr.open_dataset(diat_iopt_84_tracer_path)


# In[6]:


((m_grid_t["NO3"] - n_grid_t["NO3"]).isel(deptht = 0, time_counter = 12)).plot()


# In[7]:


((m_grid_t["NO3"] - n_grid_t["NO3"]).isel(deptht = 20, time_counter = 12)).plot()


# In[18]:


((m_grid_t["NO3"] - n_grid_t["NO3"]).isel(deptht = 0, time_counter = 1)).plot()


# In[19]:


((m_grid_t["PHY2"] - n_grid_t["PHY2"]).isel(deptht = 0, time_counter = 12)).plot()


# In[23]:


((m_grid_t["PHY2"] - n_grid_t["PHY2"]).isel(deptht = 20, time_counter = 12)).plot()


# In[24]:


(n_grid_t["PHY2"].isel(deptht = 20, time_counter = 12)).plot()


# In[30]:


fig, ax = plt.subplots(figsize = (10,10))

(n_grid_t["NO3"].isel(deptht = 20, time_counter = 12)).plot(ax = ax)


# In[3]:


# Have to keep this and the next cell apart or it fails with memory error. Something to do with 
# Jupyter notebook caching
tracer = "PHY2"
mod_tracer_depth_time =  m_grid_t[tracer].where(m_grid_t["O2"] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)


# In[27]:


now_tracer_depth_time =  n_grid_t[tracer].where(n_grid_t["O2"] != 0).mean(dim = ["x","y"]).to_dataframe(name = "MEAN_" + tracer)
var_name = "MEAN_" + tracer


# In[5]:


mod_tracer_depth_time["DATA_SOURCE"] = "IOPT DIAT = 84"
now_tracer_depth_time["DATA_SOURCE"] = "Nowcast"
combined = pd.concat([mod_tracer_depth_time, now_tracer_depth_time])
combined.reset_index(inplace=True)


# In[6]:


get_ipython().run_line_magic('load_ext', 'rpy2.ipython')


# In[21]:


get_ipython().run_cell_magic('R', '', 'require(ggplot2)\nrequire(data.table)\nlibrary(repr)\n')


# In[45]:


get_ipython().run_cell_magic('R', '-i combined,var_name -h 4200 -w 1400 -r 200', 'combined = data.table(combined)\nggplot(combined[deptht < 50,  ], aes_string(y = "deptht", x = var_name, colour = "DATA_SOURCE")) + \n    geom_path() + ylim(50,0) +\n    facet_wrap(~time_counter, ncol = 3)\n')