def test_nse(self):
'''
Code tested:
Timeseries.nse(other)
'''
obs = pqh.load_csv(r".\pixiepython\tests\test_data\416020_100141.CSV")
mod = pqh.load_csv(
r".\pixiepython\tests\test_data\416020_rfadj3test_fors.csv")
nse = mod.nse(obs)
self.assertTrue(abs(nse - 0.725302706062934) < 0.000000001)
def test_pearsons_r(self):
'''
Code tested:
Timeseries.pearsons_r(other)
'''
obs = pqh.load_csv(r".\pixiepython\tests\test_data\416020_100141.CSV")
mod = pqh.load_csv(
r".\pixiepython\tests\test_data\416020_rfadj3test_fors.csv")
nse = mod.pearsons_r(obs)
self.assertTrue(abs(nse - 0.864668449962663) < 0.000000001)
def test_loading_data_twice_gives_same_timeseries(self):
'''
Code tested:
Timeseries.source
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts3 = pqh.load_csv(r".\pixiepython\tests\test_data\p040168.csv")
comparison_results = ts1.compare(ts2)
self.assertTrue(comparison_results[0] == True)
self.assertTrue(ts1.source == ts2.source)
self.assertTrue(ts1.source != ts3.source)
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_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_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_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_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_merge(self):
'''
Code tested:
Timeseries.infill_merge(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")
#infilling by infill_merge
gappy_data.infill_merge(all_ones)
#Check the results
mean_after_infilling = gappy_data.mean
self.assertTrue(abs(mean_after_infilling - 4.40295598676) < 0.00001)
self.assertTrue(gappy_data.get_value(1910, 6, 1) == 26.9)
self.assertTrue(gappy_data.missing == 0)
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_get_value(self):
'''
Code tested:
Timeseries.get_value(year, month, day, date=None)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
#Value before ts
value = ts1.get_value(1910, 5, 1)
self.assertTrue(math.isnan(value))
#Value at start of ts
value = ts1.get_value(1910, 6, 1)
self.assertTrue(value == 26.9)
#Value inside ts
value = ts1.get_value(1910, 6, 2)
self.assertTrue(value == 204.2)
#Value inside ts (using datetime)
value = ts1.get_value(0, 0, 0, date=pqh.parse_date("02-06-1910"))
self.assertTrue(value == 204.2)
#Missing value inside ts
value = ts1.get_value(2012, 6, 26)
self.assertTrue(math.isnan(value))
#Value at end of ts
value = ts1.get_value(2017, 12, 6)
self.assertTrue(value == 36.0)
#Value after ts
value = ts1.get_value(2017, 12, 7)
self.assertTrue(math.isnan(value))
def test_date_of_first_last_data(self):
'''
Code tested:
Timeseries.bias(other)
'''
ts1 = pqh.load_csv(
r".\pixiepython\tests\test_data\p040850_headder_missing_start_end.csv"
)
first_data_date = ts1.date_of_first_data()
self.assertTrue(first_data_date == pqh.parse_date("12/02/1913"))
last_data_date = ts1.date_of_last_data()
self.assertTrue(last_data_date == pqh.parse_date("15/01/1970"))
#Do another one
ts2 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
first_data_date = ts2.date_of_first_data()
self.assertTrue(first_data_date == pqh.parse_date("01/06/1910"))
last_data_date = ts2.date_of_last_data()
self.assertTrue(last_data_date == pqh.parse_date("06/12/2017"))
def test_get_dates(self):
'''
Code tested:
Timeseries.get_dates()
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
dates = ts1.get_dates()
self.assertTrue(len(dates) == 39271)
self.assertTrue(len(dates) == len(ts1.data))
self.assertTrue(dates[0] == pqh.parse_date("01/06/1910"))
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_infill_scalemonthly_wt93b(self):
'''
Code tested:
Timeseries.infill_scalemonthly(other)
'''
#This is the WT93b test
gappy_data = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
original_length = gappy_data.length
gappy_data.infill_scalemonthly(gappy_data.clone())
self.assertTrue(gappy_data.length == original_length)
def test_length_with_gappy_dataset(self):
'''
Code tested:
As above
'''
result = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
self.assertTrue(result.length == 39271)
self.assertTrue(result.count == 39271)
self.assertTrue(result.missing == 784)
self.assertTrue(result.nonmissing == 38487)
def test_summary_has_no_errors(self):
'''
Code tested:
Timeseries.summary()
'''
#emtpy_ts = pqh.Timeseries()
#empty_ts.summary()
loaded_ts = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
loaded_ts.summary()
self.assertTrue(True)
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_pow_number(self):
'''
Code tested:
Timeseries.__pow__(number)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = ts1**2
self.assertTrue(
abs(ts1.mean - 5.19659885) <
0.000001) #__neg__ should not modify the original timeseries
self.assertTrue(abs(ts2.mean - 311.5936900771) < 0.000001)
self.assertTrue(ts2.length == ts1.length)
def test_length_with_multiline_headder(self):
'''
Code tested:
As above
'''
result = pqh.load_csv(
r".\pixiepython\tests\test_data\p040850_headder_missing_start_end.csv"
)
self.assertTrue(result.length == 47463)
self.assertTrue(result.count == 47463)
self.assertTrue(result.missing == 26671)
self.assertTrue(result.nonmissing == 20792)
def test_set_value_if_missing(self):
'''
Code tested:
Timeseries.set_value(value, year, month, day, date=None)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
#Value 26.9 is not missing and should not be changed
ts1.set_value_if_missing(99.9, 1910, 6, 1)
self.assertTrue(ts1.get_value(1910, 6, 1) == 26.9)
#Value for 2012, 6, 26 is missing and should be changed
ts1.set_value_if_missing(99.9, 2012, 6, 26)
self.assertTrue(ts1.get_value(2012, 6, 26) == 99.9)
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_start_end(self):
'''
Code tested:
Timeseries.__get_end()
Timeseries.get_start_end()
Timeseries.start
Timeseries.end
'''
result = pqh.load_csv(r".\pixiepython\tests\test_data\r040168.csv")
start_end = result.get_start_end()
self.assertTrue(start_end[0] == dt.datetime(1892, 11, 1))
self.assertTrue(start_end[1] == dt.datetime(1980, 9, 30))
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_div_number(self):
'''
Code tested:
Timeseries.__div__(number)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = ts1 / ts1.mean
self.assertTrue(
abs(ts1.mean - 5.19659885) < 0.000001
) #__add__ and __radd__ do not modify the original timeseries
self.assertTrue(abs(ts2.mean - 1.0) <
0.000001) #normalized series should have mean=1
self.assertTrue(ts2.length == ts1.length)
def test_clone_gives_same_timeseries(self):
'''
Code tested:
Timeseries.clone()
'''
original = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
theclone = original.clone()
#Clones should look the same
comparison_results = original.compare(theclone)
self.assertTrue(comparison_results[0] == True)
#But should not be the same after I manually edit some data
theclone.data[0] = 53.0
comparison_results = original.compare(theclone)
self.assertTrue(comparison_results[0] == False)
def test_neg(self):
'''
Code tested:
Timeseries.__neg__()
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
ts2 = -ts1
self.assertTrue(
abs(ts1.mean - 5.19659885) <
0.000001) #__neg__ should not modify the original timeseries
self.assertTrue(abs(ts2.mean + 5.19659885) < 0.000001)
self.assertTrue(ts2.min == -494)
self.assertTrue(ts2.max == 0.0)
self.assertTrue(ts2.length == ts1.length)
def test_bias(self):
'''
Code tested:
Timeseries.bias(other)
'''
#For cloned data the bias should be 1.0
original = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
clone = original.clone()
bias = clone.bias(original)
self.assertTrue(abs(bias - 1.0) < 0.000000001)
#Now scale ts2 up 40% and measure the bias again
clone.scale(1.4)
bias = clone.bias(original)
self.assertTrue(abs(bias - 1.4) < 0.000000001)
def test_set_value(self):
'''
Code tested:
Timeseries.set_value(value, year, month, day, date=None)
'''
ts1 = pqh.load_csv(r".\pixiepython\tests\test_data\r040134.csv")
#Value at start of ts
ts1.set_value(99.9, 1910, 6, 1)
self.assertTrue(ts1.get_value(1910, 6, 1) == 99.9)
#Value inside ts
ts1.set_value(99.9, 1910, 6, 2)
self.assertTrue(ts1.get_value(1910, 6, 2) == 99.9)
#Value at end of ts
ts1.set_value(99.9, 2017, 12, 6)
self.assertTrue(ts1.get_value(2017, 12, 6) == 99.9)
