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

# Simple notebook that shows how to create a comparer from scratch with Auxiliary date and filter

# In[1]:


import modelskill as ms
import mikeio
import numpy as np


# In[2]:


ds = mikeio.read('../tests/testdata/obs_two_items.dfs0')
ds


# First we create some random data for this example

# In[3]:


df = ds.to_dataframe()
df['Temperature'] = df['Temperature'] + np.random.random(size=len(df))
df['Waves'] = df['Temperature'] + np.random.random(size=len(df))
df['Water Level'] = df['Temperature'] + np.random.random(size=len(df))
df.head()


# In[4]:


df.plot();


# Now we make modelskill obs and mod objects

# In[5]:


obs = ms.PointObservation(df, item='Temperature', aux_items='Waves', name='P1')
mod = ms.PointModelResult(df, item='Water Level', name='Mod1')


# First we compare all data, and get ~50k points

# In[6]:


cmp=ms.match(obs, mod)
cmp


# In[7]:


cmp.plot.scatter(show_points=True, skill_table=True);


# Now we filter the comparer based on auxiliary data and get ~10k points

# In[8]:


(cmp
 .where(cmp.data['Waves']>4.5)
 .plot.scatter(show_points=True, skill_table=True)
);