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

# # Marked Point Pattern
# 
# In addition to the [unmarked point pattern](pointpattern.ipynb), non-binary attributes might be associated with each point, leading to the so-called marked point pattern. The charactertistics of a marked point pattern are:
# 
# * Location pattern of the events are of interest
# * Stochastic attribute attached to the events is of interest
# 
# Unmarked point pattern can be modified to be a marked point pattern using the method **add_marks** while the method **explode** could decompose a marked point pattern into a sequence of unmarked point patterns. Both methods belong to the class **PointPattern**.

# In[1]:


from pointpats import PoissonPointProcess, PoissonClusterPointProcess, Window, poly_from_bbox, PointPattern
import libpysal as ps
from libpysal.cg import shapely_ext
get_ipython().run_line_magic('matplotlib', 'inline')
import matplotlib.pyplot as plt


# In[2]:


# open the virginia polygon shapefile
va = ps.io.open(ps.examples.get_path("virginia.shp"))
polys = [shp for shp in va]


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# Create the exterior polygons for VA from the union of the county shapes
state = shapely_ext.cascaded_union(polys)
# create window from virginia state boundary
window = Window(state.parts)


# In[4]:


window.bbox


# In[5]:


window.centroid


# In[6]:


samples = PoissonPointProcess(window, 200, 1, conditioning=False, asPP=False)


# In[7]:


csr = PointPattern(samples.realizations[0])


# In[8]:


cx, cy = window.centroid


# In[9]:


cx


# In[10]:


cy


# In[11]:


west = csr.points.x < cx
south = csr.points.y < cy
east = 1 - west
north = 1 - south


# #### Create an attribute named quad which has a value for each event.

# In[12]:


quad = 1 * east * north +  2 * west * north + 3 * west * south + 4 * east * south


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type(quad)


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quad


# #### Attach the attribute quad to the point pattern 

# In[15]:


csr.add_marks([quad], mark_names=['quad'])


# In[16]:


csr.df


# #### Explode a marked point pattern into a sequence of individual point patterns. Since the mark quad has 4 unique values, the sequence will be of length 4.

# In[17]:


csr_q = csr.explode('quad')


# In[18]:


len(csr_q)


# In[19]:


csr


# In[20]:


csr.summary()


# #### Plot the 4 individual sequences

# In[21]:


get_ipython().run_line_magic('pinfo', 'plt.xlim')


# In[22]:


plt.xlim()
for ppn in csr_q:
    ppn.plot()


# #### Plot the 4 unmarked point patterns using the same axes for a convenient comparison of locations

# In[23]:


x0, y0, x1, y1 = csr.mbb
ylim = (y0, y1)
xlim = (x0, x1)


# In[24]:


for ppn in csr_q:
    ppn.plot()
    plt.xlim(xlim)
    plt.ylim(ylim)


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