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

# --------------------------

# ### If any part of this notebook is used in your research, please cite with the reference found in [`README.md`](https://github.com/pysal/spaghetti#bibtex-citation).

# ---------------------

# # Snapping point to segments

# In[1]:


import os
last_modified = None
if os.name == "posix":
    last_modified = get_ipython().getoutput('stat -f                     "# This notebook was last updated: %Sm"                      Snapping_Demonstration.ipynb')
elif os.name == "nt":
    last_modified = get_ipython().getoutput('for %a in (Snapping_Demonstration.ipynb)                     do echo # This notebook was last updated: %~ta')
    
if last_modified:
    get_ipython().set_next_input(last_modified[-1])


# In[ ]:


# This notebook was last updated: Nov 12 12:30:17 2019


# -------------------------------

# In[2]:


import numpy as np
from libpysal import examples
import geopandas as gpd
import spaghetti as spgh
from shapely.geometry import Point

get_ipython().run_line_magic('matplotlib', 'inline')

__author__ = 'James Gaboardi <jgaboardi@gmail.com>'


# -----------------------------------------

# ## Segments

# In[3]:


streets = examples.get_path("streets.shp")
streets = gpd.read_file(streets)


# ## Points

# In[4]:


crimes = examples.get_path("crimes.shp")
crimes = gpd.read_file(crimes)
np.random.seed(1)
crimes['geometry'] = np.random.permutation(crimes['geometry'])


# ## Initial plot

# In[5]:


base = streets.plot(figsize=(10,10), color='k', alpha=.35, linewidth=3)
crimes.plot(ax=base, cmap='tab20', markersize=75)


# # Network

# In[6]:


net = spgh.Network(in_data=streets)


# ## Snap point onto nearest segments

# In[7]:


net.snapobservations(crimes, 'crimes')


# ## Create `geopandas.GeoDataFrame` objects of snapped points

# In[8]:


snapped_gdf = spgh.element_as_gdf(net, pp_name='crimes', snapped=True)


# ## Original point coordinates, snapped point coordinates

# In[9]:


original = net.pointpatterns['crimes'].points
print(original[0]['coordinates'], snapped_gdf.geometry[0].coords[:])


# ## Snapped points plot

# In[10]:


base = streets.plot(figsize=(10,10), color='k', alpha=.35, linewidth=3)
crimes.plot(ax=base, cmap='tab20', markersize=75)
snapped_gdf.plot(ax=base, cmap='tab20', markersize=30)


# ---------------------------------------------