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#
# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
#!/usr/bin/python
import random
class Distribution:
"""Represents a normal distribution"""
def __init__(self, meanx, meany, stddev):
self.meanx = meanx
self.meany = meany
self.stddev = stddev
def sample(self):
x = random.gauss(self.meanx, self.stddev)
y = random.gauss(self.meany, self.stddev)
return x, y
if __name__ == '__main__':
import sys
if len(sys.argv) == 1:
print "Usage: python datagen.py <#points> <avg x,avg y,standard dev>+"
sys.exit(1)
numpoints = int(sys.argv[1])
distributions = []
for arg in sys.argv[2:]:
parsedargs = map(float, arg.split(','))
distributions.append(Distribution(*parsedargs))
linecount = 0
while linecount < numpoints:
distribution = distributions[linecount % len(distributions)]
x, y = distribution.sample()
print '{:.5f},{:.5f}'.format(x, y)
linecount += 1