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

# # Metocean MIKE21SW DutchCoast
# 
# Validate MIKE 21 Spectral wave model for the Dutch coast. 
# 
# Including saving comparison collection to disk and loading again. 

# In[1]:


import os
from matplotlib_inline.backend_inline import set_matplotlib_formats
set_matplotlib_formats('png')
import modelskill as ms


# In[2]:


fn = '../tests/testdata/SW/HKZN_local_2017_DutchCoast.dfsu'
mr = ms.model_result(fn, name='HKZN_local', item=0)
mr.data


# ## Define observations

# In[3]:


o1 = ms.PointObservation('../tests/testdata/SW/HKNA_Hm0.dfs0', item=0, x=4.2420, y=52.6887, name="HKNA")
o2 = ms.PointObservation("../tests/testdata/SW/eur_Hm0.dfs0", item=0, x=3.2760, y=51.9990, name="EPL")


# In[4]:


o1.plot.hist();


# In[5]:


o1.plot(); 


# In[6]:


o3 = ms.TrackObservation("../tests/testdata/SW/Alti_c2_Dutch.dfs0", item=3, name="c2")
o3.data.head()


# In[7]:


ms.plotting.spatial_overview([o1, o2, o3], mr);


# In[8]:


ms.plotting.temporal_coverage([o1, o2, o3], mr);


# In[9]:


ms.plotting.temporal_coverage([o1, o2, o3], mr, limit_to_model_period=False);


# ## Compare observations and model result

# In[10]:


cc = ms.match([o1, o2, o3], mr)


# # Save the comparison to a file
# 
# Extracting model results¶ can be a time-consuming process. Therefore, it is recommended to save the results to a file. This can be done using the save method of the comparison object.
# 
# Each comparer can be saved as a NetCDF file, and a `ComparerCollection` can be saved as a zip file, preferably with the extension `.msk`.

# In[11]:


cc.save("SW_DutchCoast.msk")


# In[12]:


cc2 = ms.load("SW_DutchCoast.msk")
cc2


# In[13]:


cc.skill().style()


# In[14]:


cc["c2"].skill(metrics="mean_absolute_error")


# In[15]:


cc["HKNA"].plot.timeseries(figsize=(10,5));


# In[16]:


cc["HKNA"].plot.timeseries(width=1000, backend="plotly")


# In[17]:


cc["EPL"].plot.scatter(figsize=(8,8), show_hist=True); 


# In[18]:


cc["EPL"].plot.scatter(show_hist=True, backend='plotly', width=600, height=600); #,xlim=[-1,11])


# In[19]:


cc["c2"].plot.hist(bins=20);


# In[20]:


cc["HKNA"].plot.scatter(bins=0.25, cmap="viridis");


# ### Clean up

# In[21]:


os.remove("SW_DutchCoast.msk")