def test_replace_har_header_in_file(self):
dd = os.path.join(os.path.dirname(__file__), "data", "")
shutil.copy2(dd + "test_Forenew7.shk", "test_Forenew7.shk")
# CERO path
df = DataTools.get_test_data(dd +
"test_replace_har_header_in_file.pickle")
fc = FromCERO(dd + "test_replace_har_header_in_file.yaml")
fc.exec_procedures(df)
test_har = DataTools.get_test_data("test_Forenew7.shk")
tn = test_har.getHeaderArrayNames()
gn = harpy.HarFileObj.loadFromDisk(
filename="Forenew7.shk").getHeaderArrayNames()
try:
self.assertTrue(all([x == y for x, y in zip(tn, gn)]))
except AssertionError as e:
print("Test data headers: ", tn)
print("Generated data headers: ", gn)
raise e
os.remove("test_Forenew7.shk") # Tidy up
os.remove("Forenew7.shk") # Tidy up
def test_plotoutput(self):
try:
import seaborn
except ImportError:
raise unittest.SkipTest("PyQt4 not installed, and therefore ConCERO's plotting capabilities cannot be used.")
nf = "AssociateProfessionals.png"
# CERO path
png = DataTools.get_test_data(TestPlotOutput._dd + "test_plotoutput.png")
cero = CERO.read_xlsx(TestPlotOutput._dd + "test_plotoutput.xlsx")
fc = FromCERO(TestPlotOutput._dd + "test_plotoutput.yaml")
fc.exec_procedures(cero)
plt = DataTools.get_test_data(nf)
# These lines have been commented out because figures are very hard to compare accurately - defaults seem to \
# differ depending on operating system.
# try:
# self.assertEqual(plt, png)
# except AssertionError as e:
# raise e
# Tidy up
os.remove(os.path.relpath(nf))
def test_cero2gallme(self):
'''Tests CERO2GALLME conversion process. Tests procedure but not output to file.
'''
dd = os.path.dirname(__file__) + os.sep + "data" + os.sep
df = DataTools.get_test_data(dd +
r'test_cero_to_gallme_initialdata.pickle')
c2g = FromCERO(dd + r'test_cero_to_gallme.yaml')
c2g.exec_procedures(df)
ser_a = df.loc[(("L_OUTPUT", "Electricity", "CAF"),),].iloc[0] + \
df.loc[(("L_OUTPUT", "Electricity", "NAF"),),].iloc[0] + \
df.loc[(("L_OUTPUT", "Electricity", "OSA"),),].iloc[0] + \
df.loc[(("L_OUTPUT", "Electricity", "ZAF"),),].iloc[0]
ser_b = df.loc[(("qo", "Electricity", "CAF"),),].iloc[0] + \
df.loc[(("qo", "Electricity", "NAF"),),].iloc[0] + \
df.loc[(("qo", "Electricity", "OSA"),),].iloc[0] + \
df.loc[(("qo", "Electricity", "ZAF"),),].iloc[0]
ser_b = ser_a * ser_b
self.assertTrue(
np.allclose(ser_b.values,
c2g.output_procedures['DemandYearly']["Value"].values))
os.remove("gallme_input_data.gdx") # Tidy up
def test_vurm2cero(self):
'''Tests VURM2CERO conversion process.'''
v2c = ToCERO(conf=(TestVURM2CERO._dd + r'test_vurm_to_cero.yaml'))
cero = v2c.create_cero()
df = DataTools.get_test_data(TestVURM2CERO._dd +
r'test_vurm_to_cero_finaldata.pickle')
self.assertTrue(cero.equals(df))
def test_sceninputs_to_cero2(self):
'''Test xlsx to CERO conversion.'''
s2c = ToCERO(conf=(TestScenIn2CERO._dd + 'test_xlsx_to_cero.yaml'))
cero = s2c.create_cero()
df = DataTools.get_test_data(
os.path.normpath('data/test_xlsx_to_cero.pickle'))
self.assertTrue(
cero.loc[df.index].equals(df)) # Order-independent test
def test_gtape2cero(self):
dd = os.path.join(os.path.dirname(__file__), "data", "")
g2c = ToCERO(dd + r'test_gtape_to_cero.yaml')
cero = g2c.create_cero()
df = DataTools.get_test_data(dd +
r'test_gtape_to_cero_finaldata.pickle')
self.assertTrue(cero.equals(df))
def test_complex_xlsx(self):
to_cero = ToCERO(conf=(TestToCERO._dd +
r'test_complex_xlsx_import.yaml'))
cero = to_cero.create_cero()
df = DataTools.get_test_data(TestToCERO._dd +
"test_complex_xlsx_result.pickle")
self.assertTrue(CERO.is_cero(cero))
self.assertTrue(cero.equals(df))
def test_time_dim(self):
shutil.copy2(TestHAR2CERO._dd + "test_timedim.har", "test_timedim.har")
h2c = ToCERO(conf=(TestHAR2CERO._dd +
r'test_har_to_cero_timedim.yaml'))
cero = h2c.create_cero()
df = DataTools.get_test_data(TestHAR2CERO._dd +
r'test_har_to_cero_timedim.pickle')
self.assertTrue(
cero.loc[df.index].equals(df)) # Order-independent test
os.remove("test_timedim.har")
def test_sceninputs_to_cero(self):
'''Tests the conversion of hars to ceros.'''
shutil.copy2(TestHAR2CERO._dd + "Mdatnew7.har", "Mdatnew7.har")
s2c = ToCERO(conf=(TestHAR2CERO._dd + r'test_har_to_cero.yaml'))
cero = s2c.create_cero()
df = DataTools.get_test_data(TestHAR2CERO._dd +
r'test_har_to_cero.pickle')
self.assertTrue(
cero.loc[df.index].equals(df)) # Order-independent test
os.remove("Mdatnew7.har")
def test_har_repetitive_sets(self):
fo = ToCERO._FileObj({
"file":
"test.har",
"search_paths":
TestToCERO_FileObj._dd,
"head_arrs": [{
"name": "ARR7",
"default_year": 2018
}]
})
cero = fo.import_file_as_cero()
df = DataTools.get_test_data(TestToCERO_FileObj._dd +
"test_har_repetitive_sets.pickle")
self.assertTrue(cero.equals(df))
def test_cero2austimes(self):
'''Tests CERO2AusTIMES conversion process.
'''
dd = os.path.dirname(__file__) + os.sep + "data" + os.sep
df = DataTools.get_test_data(dd + r'test_cero_to_luto_initialdata.pickle') # Uses same data as LUTO
c2a = FromCERO(df, conf_file=(dd + r'test_cero_to_austimes.yaml'))
for series in c2a.series:
if isinstance(series, dict):
gen_output_file = series.get('output_file', series.get('name'))
output_file = series['name']
elif isinstance(series, str):
gen_output_file = series
output_file = series
gen = np.load(gen_output_file + '.npy')
old = np.load('test_' + output_file + '.npy')
self.assertTrue(all(np.isclose(gen, old)))
def test_cero2har(self):
output_har = r"test_har_out.har"
shutil.copy2(TestCERO2HAR._dd + "Mdatnew7.har", output_har)
# CERO path
pickled_cero = TestCERO2HAR._dd + r'test_cero_to_har_initdata.pickle'
df = DataTools.get_test_data(pickled_cero)
h2c = FromCERO(TestCERO2HAR._dd + r'test_cero_to_har.yaml')
h2c.exec_procedures(df)
hf = harpy.HarFileObj.loadFromDisk(output_har)
header = hf.getHeaderArrayObj(ha_name="MAR1")
self.assertTrue(np.isclose(header["array"][0, 0, 0, 0, 0, 0], 2.44571))
self.assertTrue(np.isclose(header["array"][0, 0, 0, 1, 0, 0],
0.637938))
self.assertTrue(np.isclose(header["array"][0, 0, 2, 0, 0, 0],
0.381556))
# Tidy up
os.remove(output_har)
def test_cero2luto(self):
'''Tests CERO2LUTO conversion process.
'''
dd = os.path.join(os.path.dirname(__file__), "data", "")
df = DataTools.get_test_data(dd +
"test_cero_to_luto_initialdata.pickle")
c2l = FromCERO(dd + r'test_cero_to_luto.yaml')
c2l.exec_procedures(df)
for procedure in c2l["procedures"]:
if isinstance(procedure, dict):
gen_output_file = procedure.get('output_file',
procedure.get('name'))
output_file = procedure['name']
elif isinstance(procedure, str):
gen_output_file = procedure
output_file = procedure
gen = np.load(gen_output_file + '.npy')[0]
old = np.load(dd + 'test_' + output_file + '.npy')
self.assertTrue(all(np.isclose(gen, old)))
os.remove(gen_output_file + '.npy')
def test_idxconflict(self):
cero = DataTools.get_test_data(TestCERO._dd + "test_cero.pickle")
with self.assertRaises(CERO.CEROIndexConflict):
CERO.combine_ceros([cero, cero], overwrite=False, verify_cero=True)