Пример #1
0
def test1():
    """Testing if python and C++ implementation of Seigel yield the same results"""
    check = True


    for _ in range(100):
        se  = tseries.SeigelEstimator()
        sse  = tseries.SpanSeigelEstimator(20)
        cse = cgoals.cSeigelEstimator(20)

        size = random.randint(2, 20)
        data = [random.uniform(-10, 10) for _ in xrange(size)]

        for i, d  in enumerate(data):
            cse.add(d)
            sse.add(d)
            se.add(d)
            if abs(cse.value() - se.value()) > 0.01:
                check = False
                print cse.value()
                print sse.value()
                print se.value()
                print data[:(i+1)]

    return check
Пример #2
0
def test1():
    """Testing if python and C++ implementation of Seigel yield the same results"""
    check = True

    for _ in range(100):
        se = tseries.SeigelEstimator()
        sse = tseries.SpanSeigelEstimator(20)
        cse = cgoals.cSeigelEstimator(20)

        size = random.randint(2, 20)
        data = [random.uniform(-10, 10) for _ in xrange(size)]

        for i, d in enumerate(data):
            cse.add(d)
            sse.add(d)
            se.add(d)
            if abs(cse.value() - se.value()) > 0.01:
                check = False
                print cse.value()
                print sse.value()
                print se.value()
                print data[:(i + 1)]

    return check
Пример #3
0
import testenv

import random
import time

random.seed(123)

import goals.explorer.tools.tseries as tseries
import cgoals

tse = tseries.TheilSenEstimator()
se = tseries.SeigelEstimator()
sse = tseries.SpanSeigelEstimator(20)
cse = cgoals.cSeigelEstimator(20)

# preparing data
data = []
for i in range(1000):
    if i == 4:
        v = random.uniform(0, 2000)
    else:
        v = i + random.uniform(-2, 2)
    data.append(v)


t0 = time.time()
data0 = [0.0, 1.0, 2.0]
for d in data:
    data0.append(d)
    tseries.derivative(data0)
t0 = time.time() - t0
Пример #4
0
import testenv

import random
import time

random.seed(123)

import goals.explorer.tools.tseries as tseries
import cgoals

tse = tseries.TheilSenEstimator()
se = tseries.SeigelEstimator()
sse = tseries.SpanSeigelEstimator(20)
cse = cgoals.cSeigelEstimator(20)

# preparing data
data = []
for i in range(1000):
    if i == 4:
        v = random.uniform(0, 2000)
    else:
        v = i + random.uniform(-2, 2)
    data.append(v)

t0 = time.time()
data0 = [0., 1., 2.]
for d in data:
    data0.append(d)
    tseries.derivative(data0)
t0 = time.time() - t0