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

# ## Calculate Isodistances
# 
# This example illustrates how to calculate and visualize isodistances using Data Services.
# 
# _Note: You'll need [CARTO Account](https://carto.com/signup) credentials to reproduce this example._

# In[1]:


from cartoframes.auth import set_default_credentials

set_default_credentials('creds.json')


# In[2]:


from geopandas import GeoDataFrame, points_from_xy

gdf = GeoDataFrame([
         ['Calle Serrano 15', -3.68831, 40.42478],
         ['Calle de San Pedro 21', -3.69488, 40.41089],
         ['Calle Gran Vía 46', -3.70588, 40.42049],
         ['Paseo de la Castellana 200', -3.68898, 40.46239],
         ['Calle Ntra. Sra. del Carmen 7', -3.70221, 40.45840],
         ['Calle de San Germán 12', -3.69286, 40.45651],
         ['Calle de Bravo Murillo 377', -3.69093, 40.46575],
    ],
    columns=['address', 'lng', 'lat']
)
gdf.set_geometry(points_from_xy(gdf['lng'], gdf['lat']), inplace=True)


# In[3]:


from cartoframes.viz import Layer

Layer(gdf)


# In[4]:


from cartoframes.data.services import Isolines

iso_service = Isolines()
isodistances_gdf, isodistances_metadata = iso_service.isodistances(gdf, [600, 1200, 2400], exclusive=True)


# In[5]:


isodistances_gdf.head(5)


# In[6]:


isodistances_metadata


# In[7]:


from cartoframes.viz import Map, Layer, basic_style

Map([
    Layer(isodistances_gdf, basic_style(color='green', opacity='0.3', stroke_width=0)),
    Layer(gdf)
])