def test_gen_cities_avg(self):
# test for just one city
climate = ps5.Climate('data.csv')
test_years = pylab.array(ps5.TESTING_INTERVAL)
result = ps5.gen_cities_avg(climate, ['SEATTLE'], test_years)
correct = [11.514383561643836, 10.586849315068493, 11.28319672, 12.10643836, 12.82917808, 13.13178082]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "City averages do not match expected results")
# multiple cities
result = ps5.gen_cities_avg(climate, ps5.CITIES, test_years)
correct = [16.75950424, 16.85749511, 17.56180068, 16.65717547, 16.84499022, 17.54460535]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "City averages do not match expected results")
# years range
# multiple cities
result = ps5.gen_cities_avg(climate, ['TAMPA', 'DALLAS'], test_years)
correct = [20.8040411, 22.03910959, 22.27206284, 21.31136986, 20.88123288, 22.07794521]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "City averages do not match expected results")
def test_gen_std_devs(self):
climate = ps5.Climate('data.csv')
years = pylab.array(ps5.TRAINING_INTERVAL)
result = ps5.gen_std_devs(climate, ['SEATTLE'], years)
correct = [6.1119325255476635, 5.4102625076401125, 6.0304210441394801, 5.5823239710637846, 5.5908151965372177, 5.0347634736031583, 6.2485081784971772, 5.6752637253518703, 5.9822493041266327, 5.5376216719090898, 6.0339331562285095, 6.3471434661632733, 5.3872564859222782, 5.7528361897357705, 6.0117329392620285, 5.5922579610955854, 5.67888175212234, 5.7810899373043272, 5.7184178577664087, 5.3955809402004036, 5.1736886920193665, 5.8134229790176573, 5.1915733214759872, 5.4023314139519591, 6.7868442109830855, 5.2952870947334114, 5.6064597624296333, 5.4921097908102086, 6.1450202825415214, 6.3591021848005278, 5.4996866353350615, 5.6516820894310058, 5.7969983303071411, 5.8531227958031931, 5.2545492072097808, 6.0102701017450126, 5.5327493838092865, 5.7703034605336532, 5.0412624972468443, 5.2728662938897264, 5.0859211734722649, 5.5526426823734987, 5.8005720594546748, 5.7391426965165389, 5.5518538235632207, 5.8279562142168073, 5.9089508390885479, 5.9789908401877394, 6.5696153940105573]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "Standard deviations do not match expected results")
result = ps5.gen_std_devs(climate, ps5.CITIES, years)
correct = [6.8007729489975439, 6.9344723094071865, 7.2965004501815818, 6.8077243598168549, 6.5055948680511539, 6.959087494608867, 6.4889799240243695, 6.9510430337868963, 7.0585431115159478, 7.0977420580318782, 6.8386579785236048, 6.731347077523127, 6.6616225764762902, 6.4092396746786013, 6.6214217100011084, 6.7136104957814435, 7.2575482189983553, 7.263276360210706, 7.1787611973720633, 7.0859352578611796, 6.8736741252762821, 6.7957043866857889, 7.0815549177622765, 6.7249974778654433, 7.2162729580931124, 6.4560372283957266, 6.7288306794528907, 6.9720986945202927, 6.922958341746317, 6.3033645588306086, 6.5330170805999908, 6.2777429551963237, 6.8488629387504032, 6.8257830274740625, 6.7856101061465059, 6.7592782215870484, 6.6634050127541604, 6.4486321701001552, 6.3413248952817742, 6.7637674361128752, 6.5519930751275384, 6.6831654464946064, 6.7751550280705839, 6.7435411127318146, 6.8720508861149154, 6.381528250607194, 6.9707944558310109, 6.7582457290380731, 6.7451346848899991]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "Standard deviations do not match expected results")
result = ps5.gen_std_devs(climate, ['TAMPA', 'DALLAS'], years)
correct = [6.6222742584336203, 7.0831603561201613, 7.7597469401129215, 7.0259613619453818, 6.5638542892147722, 7.2251974365928691, 6.1518558874089617, 7.0391602268356808, 7.1526420227632297, 7.2908275139292842, 6.270260767160857, 6.4782366919527483, 6.6679030134469448, 6.0219388710726411, 6.6228151175078525, 6.4353160709432649, 7.8465935407208427, 8.1048357980863859, 7.2582171660107786, 7.7051951164668244, 7.083156557719672, 6.6459102430953294, 7.3472808518990416, 6.7892304784646278, 7.4543972339551905, 6.3029047021487283, 6.6943381051857225, 6.9549273458644914, 7.0491429730256217, 6.0235494427214373, 6.3241265661686636, 6.125270864250882, 6.8769945045255714, 6.2418939236561259, 6.8146994668451102, 7.2018962701686169, 6.5761298971998094, 7.0293238787351466, 6.3457405064020591, 7.1321062259929908, 6.5963446478678387, 6.750967975464123, 6.839988834120371, 6.4423456425074255, 6.8283808762586897, 6.3536010884491958, 6.6492152503358843, 6.6265277854285625, 6.6375221251962317]
self.assertTrue(len(correct) == len(result), "Expected length %s, was length %s" % (len(correct), len(result)))
for index in range(len(correct)):
good_enough = math.isclose(correct[index], result[index])
self.assertTrue(good_enough, "Standard deviations do not match expected results")
