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

# In[66]:


from ipyleaflet import Map, Heatmap
from random import uniform
import time


# In[67]:


import pandas as pd


# In[68]:


df = pd.read_csv("data/data_harmonized_1.csv")
df.head()


# In[69]:


df2 = pd.read_csv("data/Metadata_Logger.csv")
df2.head()


# Now that we have installed some libraries, we can work with the data:

# In[70]:


m = Map(center=[46.948056, 7.4475], zoom=12)
m


# In[71]:


def create_random_data(length):
    "Return a list of some random lat/lon/value triples."
    return [[uniform(-80, 80), 
             uniform(-180, 180), 
             uniform(0, 1000)] for i in range(length)]


# In[72]:


def load_climate_data():
    return [[row["NORD_CHTOPO"], row["OST_CHTOPO"], 10] for index, row in df2.iterrows()]


# In[73]:


heat = Heatmap(locations=load_climate_data(), radius=20, blur=10)
m.add_layer(heat)


# In[74]:


# for i in range(100):
#    heat.locations = create_random_data(1000)
#    time.sleep(0.1)


# In[75]:


heat.radius = 30


# In[76]:


heat.blur = 50


# In[77]:


heat.max = 0.5


# In[78]:


heat.gradient = {0.4: 'red', 0.6: 'yellow', 0.7: 'lime', 0.8: 'cyan', 1.0: 'blue'}


# In[79]:


#heat.locations = [[uniform(-80, 80), uniform(-180, 180), uniform(0, 1000)] for i in range(1000)]