def test_load_save_load(self):
'''
Code tested:
load_csv
save_csv
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
pqh.save_csv(
ts1, r".\pixiepython\tests\test_data\output\r040134_resaved.csv")
ts2 = pqh.load_csv(
r".\pixiepython\tests\test_data\output\r040134_resaved.csv")
comparison_results = ts1.compare(ts2)
self.assertTrue(comparison_results[0] == True)
def test_infill_wt93b3(self):
'''
Code tested:
Timeseries.infill_wt93b(others)
'''
r040695 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040695.csv")
r040547 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040547.csv")
p040264 = pqh.load_csv(r".\pyqhtools\tests\test_data\p040264.csv")
r040695.infill_wt93b([r040547, p040264])
pqh.save_csv(
r040695,
r".\pyqhtools\tests\test_data\output\r040695_r040547_p040264.csv")
self.assertTrue(abs(r040695.mean - 4.6781753769) < 0.0000001)
def test_infill_scale_force_factor(self):
'''
Code tested:
Timeseries.infill_scale(other, factor=None)
'''
gappy_data = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
all_ones = pqh.load_csv(r".\pixiepython\tests\test_data\all_ones.csv")
gappy_data.infill_scale(all_ones, factor=0.6666)
pqh.save_csv(
gappy_data,
r".\pixiepython\tests\test_data\output\r040134_infilled2.csv")
#Check the results
self.assertTrue(abs(gappy_data.mean - 4.339904801) < 0.00001)
def test_infill_wt93b2(self):
'''
Code tested:
Timeseries.infill_wt93b(others)
'''
r040134 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040134.csv")
r040168 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040168.csv")
p040850 = pqh.load_csv(r".\pyqhtools\tests\test_data\p040850.csv")
r040134.infill_wt93b([r040168, p040850])
pqh.save_csv(
r040134,
r".\pyqhtools\tests\test_data\output\r040134_r040168_p040850.csv")
self.assertTrue(r040134.missing == 0)
def test_infill_scalemonthly_4factors(self):
'''
Code tested:
Timeseries.infill_scalemonthly(other, factors=None)
'''
gappy_data = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
all_ones = pqh.load_csv(r".\pixiepython\tests\test_data\all_ones.csv")
monthly_factors = [1.1, 1.2, 0.9, 0.8]
gappy_data.infill_scalemonthly(all_ones, factors=monthly_factors)
pqh.save_csv(
gappy_data,
r".\pixiepython\tests\test_data\output\r040134_infilled4.csv")
#Check the results
self.assertTrue(abs(gappy_data.mean - 4.4031751048) < 0.000001)
def test_infill_scalemonthly_wt93b_2(self):
'''
Code tested:
Timeseries.infill_scalemonthly(other)
'''
#This is the WT93b test
gappy_data = pqh.load_csv(r".\pyqhtools\tests\test_data\r040134.csv")
all_ones = pqh.load_csv(r".\pyqhtools\tests\test_data\all_ones.csv")
gappy_data.infill_scalemonthly(all_ones)
pqh.save_csv(
gappy_data,
r".\pyqhtools\tests\test_data\output\r040134_infilled5_wt93b.csv")
#Check the results
self.assertTrue(abs(gappy_data.mean - 5.21500501) < 0.0001)
def test_infill_scalemonthly(self):
'''
Code tested:
Timeseries.infill_scalemonthly(other, factors=None)
'''
gappy_data = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
all_ones = pqh.load_csv(r".\pixiepython\tests\test_data\all_ones.csv")
monthly_factors = [
0.7, 0.9, 1.1, 1.3, 1.5, 1.6, 1.4, 1.2, 1.0, 0.8, 0.6, 0.5
]
gappy_data.infill_scalemonthly(all_ones, factors=monthly_factors)
pqh.save_csv(
gappy_data,
r".\pixiepython\tests\test_data\output\r040134_infilled3.csv")
#Check the results
self.assertTrue(abs(gappy_data.mean - 4.412548722) < 0.0001)
def test_infill_scale_auto_factor(self):
'''
Code tested:
Timeseries.infill_scale(other)
'''
gappy_data = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
all_ones = pqh.load_csv(r".\pixiepython\tests\test_data\all_ones.csv")
mean_before_infilling = gappy_data.mean
#infilling by infill_scale should preserve the mean
gappy_data.infill_scale(all_ones)
pqh.save_csv(
gappy_data,
r".\pixiepython\tests\test_data\output\r040134_infilled.csv")
#Check the results
mean_after_infilling = gappy_data.mean
self.assertTrue(
abs(mean_before_infilling - mean_after_infilling) < 0.00001)
self.assertTrue(gappy_data.get_value(1910, 6, 1) == 26.9)
self.assertTrue(gappy_data.missing == 0)
def test_set_start_end2(self):
'''
Code tested:
Timeseries.set_start_end(start_and_end)
Timeseries.set_start(year, month, day)
Timeseries.set_end(year, month, day)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\p040134.csv")
ts2 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2_start_end = ts2.get_start_end()
self.assertTrue(ts1.length != ts2.length)
self.assertTrue(ts1.get_value(1910, 6, 1) == 26.9)
ts1.set_start_end(ts2_start_end)
#Save the result for visual inspection
pqh.save_csv(
ts1, r".\pixiepython\tests\test_data\output\r040134_redated2.csv")
#Assert expected results
self.assertTrue(ts1.length == ts2.length)
self.assertTrue(ts1.get_value(1910, 6, 1) == 26.9)
def test_mul_rmul_number(self):
'''
Code tested:
Timeseries.__mul__(value)
Timeseries.__rmul__(value)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = ts1 * 2.0
ts3 = 2.0 * ts1
self.assertTrue(
abs(ts1.mean - 5.19659885) < 0.000001
) #__mul__ and __rmul__ do not modify the original timeseries
self.assertTrue(abs(ts2.mean - 10.3931977) < 0.000001)
self.assertTrue(ts2.min == 0)
self.assertTrue(ts2.max == 988)
self.assertTrue(ts2.length == ts1.length)
self.assertTrue(ts2.compare(ts3)[0])
pqh.save_csv(
ts2, r".\pixiepython\tests\test_data\output\r040134_mul_2.csv")
def test_set_start_end(self):
'''
Code tested:
Timeseries.set_start_end(start_and_end)
Timeseries.set_start(year, month, day)
Timeseries.set_end(year, month, day)
'''
#Load some patched-point data
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\p040134.csv")
ts1_start_end = ts1.get_start_end()
#Load some raw data and check length is different to above
ts2 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
self.assertTrue(ts1.length != ts2.length)
self.assertTrue(ts2.get_value(1910, 6, 1) == 26.9)
#Extend the dates to be same as above and check lengths are now same
ts2.set_start_end(ts1_start_end)
self.assertTrue(ts1.length == ts2.length)
self.assertTrue(ts2.get_value(1910, 6, 1) == 26.9)
#Save the result for visual inspection
pqh.save_csv(
ts2, r".\pixiepython\tests\test_data\output\r040134_redated.csv")
def test_sub_rsub_number(self):
'''
Code tested:
Timeseries.__sub__(value)
Timeseries.__rsub__(value)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = ts1 - 1.1
ts3 = 1.1 - ts1
self.assertTrue(
abs(ts1.mean - 5.19659885) < 0.000001
) #__sub__ and __rsub__ do not modify the original timeseries
self.assertTrue(abs(ts2.mean - 4.09659885) < 0.000001)
self.assertTrue(ts2.min == -1.1)
self.assertTrue(ts2.max == 492.9)
self.assertTrue(ts2.length == ts1.length)
self.assertTrue(ts3.length == ts1.length)
self.assertTrue(abs(ts3.mean + 4.09659885) < 0.000001)
pqh.save_csv(
ts2,
r".\pixiepython\tests\test_data\output\r040134_minus_1point1.csv")
def test_infill_wt93b(self):
'''
Code tested:
Timeseries.infill_wt93b(others)
'''
r040134 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040134.csv")
#r040168 = pqh.load_csv(r".\pyqhtools\tests\test_data\r040168.csv")
p040850 = pqh.load_csv(r".\pyqhtools\tests\test_data\p040850.csv")
factors = r040134.get_wt93_factors(p040850)
known_answers = [
1.0412290338857493, 1.0065128956703973, 1.0598426339157894,
1.0476595992884017, 1.0548171248637521, 1.0538393731635654,
1.0441554098438972, 1.0498160869346143, 1.0296487322003494,
1.0394039501112953, 1.0631576523681232, 1.0712720135216185
]
for i in range(12):
self.assertTrue(abs(factors[i] - known_answers[i]) < 0.0000001)
r040134.infill_wt93b([p040850])
pqh.save_csv(
r040134, r".\pyqhtools\tests\test_data\output\r040134_p040850.csv")
self.assertTrue(r040134.missing == 0)
def test_add_radd_timeseries(self):
'''
Code tested:
Timeseries.__add__(other)
Timeseries.__radd__(other)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = pqh.load_csv(r".\pixiepython\tests\test_data\r040168.csv")
ts3 = ts1 + ts2
ts4 = ts2 + ts1
self.assertTrue(
abs(ts1.mean - 5.19659885) < 0.000001
) #__add__ and __radd__ do not modify the original timeseries
self.assertTrue(
abs(ts2.mean - 4.453350651058) < 0.000001
) #__add__ and __radd__ do not modify the original timeseries
self.assertTrue(abs(ts3.mean - 9.56699353053) < 0.000001)
self.assertTrue(
ts3.length == 45691
) #length should be the union of ts1 and ts2 (not the intersect)
self.assertTrue(ts4.compare(ts3)[0]) #ts3 and ts4 should be identical
pqh.save_csv(
ts3,
r".\pixiepython\tests\test_data\output\r040134_plus_r040168.csv")
