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sc
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import pyproj
import csv
import shapely.geometry as geom
import fiona
import fiona.crs
import shapely
import rtree
import geopandas as gpd
import numpy as np
import operator
# just for display, not for calculation
import pandas as pd
In [12]:
def countLine(partID, records):
import pyproj
import csv
import shapely.geometry as geom
import fiona
import fiona.crs
import shapely
import rtree
import geopandas as gpd
import numpy as np
import operator
import pandas as pd
shapefile = './why_yellow_taxi/Buffer/entr_buffer_100_feet_epsg4269_nad83/entr_buffer_100_feet_epsg4269_nad83.shp'
entr_buf = gpd.read_file(shapefile)
entr_buf = entr_buf.to_crs(fiona.crs.from_epsg(2263))
routes = ['Route_' + str(n) for n in range(1, 12)]
entr2line = []
for i in xrange(len(entr_buf)):
lines = []
for line in list(entr_buf.loc[:,routes].ix[i].dropna().values):
try:
line = str(int(line))
except ValueError:
pass
lines.append(line)
entr2line.append(lines)
entr_buf['entr2line'] = entr2line
index = rtree.Rtree()
for idx, geometry in enumerate(entr_buf.geometry):
index.insert(idx, geometry.bounds)
entr_pair = {}
pick_entr = {}
drop_entr = {}
entr_lines = {}
proj = pyproj.Proj(init='epsg:2263', preserve_units=True)
if partID==0:
records.next()
reader = csv.reader(records)
for row in reader:
if ((float(row[5])!=0) and float(row[9]!=0)):
p = geom.Point(proj(float(row[5]), float(row[6])))
d = geom.Point(proj(float(row[9]), float(row[10])))
p_potential = index.intersection((p.x,p.y,p.x,p.y))
d_potential = index.intersection((d.x,d.y,d.x,d.y))
p_match = None # The first one match, should be the closest one? No!
d_match = None
for p_idx in p_potential:
if entr_buf.geometry[p_idx].contains(p):
p_match = p_idx # print 'p',p_idx
p_lines = set(entr_buf.entr2line[p_idx])
break
pick_entr[p_match] = pick_entr.get(p_match, 0)+1
for d_idx in d_potential:
if entr_buf.geometry[d_idx].contains(d):
d_match = d_idx # print 'd',d_idx
d_lines = set(entr_buf.entr2line[d_idx])
break
drop_entr[d_match] = drop_entr.get(d_match, 0)+1
if ((p_match and d_match) and (p_match != d_match)):
dirct_lines = tuple(p_lines.intersection(d_lines))
if dirct_lines:
entr_lines[dirct_lines] = entr_lines.get(dirct_lines, 0)+1
if p_match > d_match:
pair = (d_match, p_match)
else:
pair = (p_match, d_match)
entr_pair[pair] = entr_pair.get(pair, 0)+1
return entr_lines.items()
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def mapper(record):
for key in record[0]:
yield key, record[1]
rdd = sc.textFile('./yellow_tripdata_2016-01.csv')
counts = rdd.mapPartitionsWithIndex(countLine).flatMap(mapper).reduceByKey(lambda x,y: x+y).collect()
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sorted(counts, key=lambda x: x[1], reverse=True)
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