exampleData = LazyDiskData("../data/RDR/ALL.CSV",
columnSlice = slice(3, None))
query = randomUnitVector(6144)
numTrees = 1
elif analysis == "sim":
exampleData = LazyDiskData("../data/testdata.csv",
columnSlice = slice(1, None))
query = np.zeros(10)
numTrees = 10
else:
raise Exception("Unrecognized analysis: {}".format(analysis))
timestamp = datetime.datetime.now().strftime("%Y-%m-%d_%H-%M-%S.%f")
outputDir = "forests/forest_" + analysis + "_" + timestamp
with time("naive linear scan query"):
naiveResult = exampleData.linearScanNearestNeighbor(query,
distanceFunction = euclidean)
print(naiveResult)
naiveRuntime = getLastElapsedTime()
with time("build trees"):
forest = makeForest(exampleData, maxLeafSize = 500, numTrees = numTrees,
distanceFunction = euclidean, depthPerBatch = 3,
outputDir = outputDir)
with time("run query"):
result = forest.nearestNeighbor(query)
print(result)
print("For comparison, naive result:\n{}\nnaive elapsed = {}".format(
#!/usr/bin/env python
import pickle
import numpy as np
import sys
from bigNearestNeighbor import time, loadForest
if len(sys.argv) > 1:
filename = sys.argv[1]
else:
print("Please provide a filename")
sys.exit(1)
with time("load forest"):
forest = loadForest(filename)
query = np.zeros(len(forest.trees[0].rule.direction))
with time("run query"):
result = forest.nearestNeighbor(query)
print(result)