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

# In[13]:


import geopandas as gpd
from pathlib import Path
import pandas as pd


# In[2]:


city = 'Luanda'


# In[3]:


# read catchment AOI
aoi = gpd.read_file('AOI/luanda_catchment_level4.shp').to_crs(epsg = 4326)


# In[6]:


output_folder = Path('output')
dam_data = gpd.read_file(r"C:\Users\Owner\Documents\Career\World Bank\CRP\data\GOODD\GOOD2_dams.shp")
reservoir_data = gpd.read_file(r"C:\Users\Owner\Documents\Career\World Bank\CRP\data\GRanD\GRanD_reservoirs_v1_3.shp")


# In[15]:


dam_data.columns


# In[21]:


# filter for dams in AOI
dams_list = []

for i in range(len(aoi)):
    dams_list.append(dam_data.loc[dam_data.within(aoi.loc[i, 'geometry'])])


# In[24]:


dams = pd.concat(dams_list)


# In[28]:


dams.to_file(output_folder / f'{city.lower()}_dams.shp')


# In[25]:


# filter for reservoirs in AOI
reservoirs_list = []

for i in range(len(aoi)):
    reservoirs_list.append(reservoir_data.loc[reservoir_data.within(aoi.loc[i, 'geometry'])])


# In[27]:


reservoirs = pd.concat(reservoirs_list)


# In[29]:


reservoirs.to_file(output_folder / f'{city.lower()}_reservoirs.shp')