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

# Template for daily nowcast figure generation.

# # SalishSeaCast NEMO Model Daily Nowcast Figures

# # Set-up

# In[1]:


import datetime
from glob import glob
from importlib import reload
import os

from IPython.core.display import HTML
import netCDF4 as nc

#from nowcast.figures import figures
from nowcast.figures.publish import pt_atkinson_tide
from nowcast.figures.publish import storm_surge_alerts
from nowcast.figures.publish import compare_tide_prediction_max_ssh

import scipy.io as sio

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


# In[ ]:


def results_dataset(period, grid, results_dir):
    """Return the results dataset for period (e.g. 1h or 1d)
    and grid (e.g. grid_T, grid_U) from results_dir.
    """
    filename_pattern = 'SalishSea_{period}_*_{grid}.nc'
    filepaths = glob(os.path.join(results_dir, filename_pattern.format(period=period, grid=grid)))
    return nc.Dataset(filepaths[0])


# In[2]:


run_date = datetime.date.today()
run_date = datetime.datetime(2017, 12, 13)
# Results dataset location
results_home = '/results/SalishSea/forecast/'
results_dir = os.path.join(results_home, run_date.strftime('%d%b%y').lower())


# Load the results datasets:

# In[ ]:


grid_T_hr = results_dataset('1h', 'grid_T', results_dir)
grid_T_dy = results_dataset('1d', 'grid_T', results_dir)
grid_U_dy = results_dataset('1d', 'grid_U', results_dir)
grid_V_dy = results_dataset('1d', 'grid_V', results_dir)


# Set lots of paths etc

# In[3]:


bathy = nc.Dataset('/ocean/sallen/allen/research/MEOPAR/grid/bathymetry_201702.nc')


# In[4]:


tidal_predictions = '/SalishSeaCast/tidal-predictions/'
timezone = 'Canada/Pacific'
names = [
        'Point Atkinson', 'Victoria', 'Campbell River', 'Cherry Point',
        'Friday Harbor', 'Neah Bay', 'Nanaimo', 'Sand Heads', 'Boundary Bay',
        'Port Renfrew', 'Halfmoon Bay', 'Friday Harbor', 'Patricia Bay',
        'Squamish'
    ]
filepath_tmpl = os.path.join(results_dir, '{}.nc')
grids_15m = {
        name: nc.Dataset(filepath_tmpl.format(name.replace(' ', '')))
        for name in names
    }
weather_path = '/results/forcing/atmospheric/GEM2.5/operational'
coastline = sio.loadmat('/ocean/rich/more/mmapbase/bcgeo/PNW.mat')


# Display the figures:

# In[5]:


HTML('<h2>{:%d%b%y} Figures</h2>'.format(run_date))


# In[ ]:


fig = figures.ssh_PtAtkinson(grid_T_hr)


# ## Website Figures ##

# ### Website Thumbnail ###

# ### Threshold Website ###

# In[23]:


reload(storm_surge_alerts)


# In[24]:


fig = storm_surge_alerts.make_figure(grids_15m, weather_path, coastline, tidal_predictions)


# ### PA Tidal Predictions ###

# In[ ]:


fig = pt_atkinson_tide.make_figure(grid_T_hr, tidal_predictions, timezone)


# ### Victoria, PA, Campbell River, Nanaimo, Cherry Point SSH ###

# In[ ]:


fig = compare_tide_prediction_max_ssh.make_figure('Victoria', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)


# In[ ]:


fig = compare_tide_prediction_max_ssh.make_figure('Point Atkinson', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)


# In[ ]:


fig = compare_tide_prediction_max_ssh.make_figure('Campbell River', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)


# In[ ]:


fig = compare_tide_prediction_max_ssh.make_figure('Nanaimo', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)


# In[ ]:


fig = compare_tide_prediction_max_ssh.make_figure('Cherry Point', grid_T_hr, grids_15m, bathy, weather_path, tidal_predictions,
                                                 timezone)


# ### NOAA ssh ###

# In[ ]:


fig = figures.compare_water_levels(grid_T_hr, bathy, grids_15m, coastline)


# In[ ]:


fig = figures.PA_max_ssh(grid_T_hr,bathy)


# In[ ]:


fig = figures.Sandheads_winds(grid_T_hr)


# In[ ]:


reload(figures)


# In[ ]:


fig = figures.thalweg_salinity(grid_T_dy)


# In[ ]:


fig = figures.plot_surface(grid_T_dy, grid_U_dy, grid_V_dy, bathy)


# In[ ]: