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count-by-ranges.py
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count-by-ranges.py
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import csv, math, mmap
similarity = [0,0,0,0,0,0,0,0,0,0]
distance = [0,0,0,0,0,0,0,0,0,0]
rowammount = 0
arquivos = []
from time import sleep
print("Sleeping to wait csv write,")
sleep(10) # sleep 4 seconds
print("Running experiments.")
for val in range(0, 10):
strfile = 'dataanalysis/dspoints/' + str(val) + '_' + str(val+1) + '.csv'
arquivos.append(csv.writer(open(strfile, 'wb')))
arquivos[val].writerow(['p1', 'p2', 'distance', 'similarity'])
with open('dataanalysis/nyctaxi1000/ds.csv') as f7:
for row in csv.reader(f7):
try:
row2 = float(row[2])
row3 = float(row[3])
except:
print(row)
rowammount += 1
if((row2 >= 0.0) and (row2 < 0.1)):
distance[0] += 1
elif((row2 >= 0.1) and (row2 < 0.2)):
distance[1] += 1
elif((row2 >= 0.2) and (row2 < 0.3)):
distance[2] += 1
elif((row2 >= 0.3) and (row2 < 0.4)):
distance[3] += 1
elif((row2 >= 0.4) and (row2 < 0.5)):
distance[4] += 1
elif((row2 >= 0.5) and (row2 < 0.6)):
distance[5] += 1
elif((row2 >= 0.6) and (row2 < 0.7)):
distance[6] += 1
elif((row2 >= 0.7) and (row2 < 0.8)):
distance[7] += 1
elif((row2 >= 0.8) and (row2 < 0.9)):
distance[8] += 1
elif((row2 >= 0.9) and (row2 <= 1)):
distance[9] += 1
if((row3 >= 0.0) and (row3 < 0.1)):
similarity[0] += 1
arquivos[0].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.1) and (row3 < 0.2)):
similarity[1] += 1
arquivos[1].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.2) and (row3 < 0.3)):
similarity[2] += 1
arquivos[2].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.3) and (row3 < 0.4)):
similarity[3] += 1
arquivos[3].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.4) and (row3 < 0.5)):
similarity[4] += 1
arquivos[4].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.5) and (row3 < 0.6)):
similarity[5] += 1
arquivos[5].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.6) and (row3 < 0.7)):
similarity[6] += 1
arquivos[6].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.7) and (row3 < 0.8)):
similarity[7] += 1
arquivos[7].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.8) and (row3 < 0.9)):
similarity[8] += 1
arquivos[8].writerow([row[0],row[1], row[2], row[3]])
elif((row3 >= 0.9) and (row3 <= 1)):
similarity[9] += 1
arquivos[9].writerow([row[0],row[1], row[2], row[3]])
print("Distance: \n")
for indice, x in enumerate(distance):
output = str(float(indice)/10) + " ~ " + str((float(indice)/10) + 0.1) + ": " + str(x)
print(output)
print("\nSimilarity: \n")
for indice, x in enumerate(similarity):
output = str(float(indice)/10) + " ~ " + str((float(indice)/10) + 0.1) + ": " + str(x)
print(output)
#Write the result in dscount.csv
dscount = csv.writer(open("dataanalysis/dscount.csv", "wb"))
dscount.writerow(['Value','All', '0.0 ~ 0.1','0.1 ~ 0.2','0.2 ~ 0.3', '0.3 ~ 0.4', '0.4 ~ 0.5', '0.5 ~ 0.6', '0.6 ~ 0.7','0.7 ~ 0.8','0.8 ~ 0.9','0.9 ~ 1.0'])
dscount.writerow(['Similarity',rowammount, similarity[0], similarity[1], similarity[2], similarity[3], similarity[4], similarity[5], similarity[6], similarity[7], similarity[8], similarity[9]])
dscount.writerow(['Distance',rowammount, distance[0], distance[1], distance[2], distance[3], distance[4], distance[5], distance[6], distance[7], distance[8], distance[9]])
print("Information about all point is locate in dscount.csv\n\nInside dspoints folder have 10 files, each to 0.1 range")