nilmdb/pytables-test/test-indexing.py

#!/usr/bin/python

from tables import *
import re
import time

# A class to describe our data
class PrepData(IsDescription):
    timestamp = Int64Col()
    p1 = Float32Col()
    q1 = Float32Col()
    p3 = Float32Col()
    q3 = Float32Col()
    p5 = Float32Col()
    q5 = Float32Col()
    p7 = Float32Col()
    q7 = Float32Col()

filename = "test.h5"
h5file = openFile(filename, mode = "w", title = "NILM Test")

group = h5file.createGroup("/", "newton", "Newton school")
table = h5file.createTable(group, "prep", PrepData, "Prep Data", expectedrows = 120 * 86400 * 90)

table.cols.timestamp.createIndex()

for i in range(0, 80):
    # Open file
    data = open("data/alldata")
    count = 0
    oldtime = time.time()
    prep = table.row
    for line in data:
        count = count + 1
        if count % 1000000 == 0:
            print str(i) + ": " + str((time.time() - oldtime)) + ", total " + str(count/1000000) + "m lines"
            oldtime = time.time()
        v = re.split('\s+', line)
        prep['timestamp'] = int(v[0]) + 500000000 * i
        prep['p1'] = v[1]
        prep['q1'] = v[2]
        prep['p3'] = v[3]
        prep['q3'] = v[4]
        prep['p5'] = v[5]
        prep['q5'] = v[6]
        prep['p7'] = v[7]
        prep['q7'] = v[8]
        prep.append()
    data.close()

h5file.close()