def test_auto_export(self):
cero = pd.DataFrame.from_dict({"A": [1], "B": [2], "C": [3]},
orient='index',
dtype=pd.np.float32)
cero.sort_index(inplace=True)
cero.columns = pd.DatetimeIndex(data=pd.to_datetime([2018], format="%Y"))
fc = FromCERO(cfg.d_td + "test_procedure_autoexport.yaml")
fc.exec_procedures(cero)
df1 = pd.read_csv("auto_csv_export.csv", index_col=0)
test_list = [1, 2, 3]
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = ["A", "B", "C"]
self.assertTrue(all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
df1 = pd.read_excel("auto_xlsx_export.xlsx", index_col=0)
test_list = [1, 2, 3]
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = ["A", "B", "C"]
self.assertTrue(all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
os.remove("auto_csv_export.csv")
os.remove("auto_xlsx_export.xlsx")
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_load2(self):
cero = pd.DataFrame.from_dict({"A": [1], "B": [2], "C": [3], "D": [4], "E": [5], "F": [6], }, orient='index',
dtype=pd.np.float32)
cero.sort_index(inplace=True)
cero.columns = pd.DatetimeIndex(data=pd.to_datetime([2018], format="%Y"))
fc = FromCERO(cfg.d_td + "test_fromcero_procedureload2.yaml")
self.assertEqual(fc["procedures"][0]["name"], "Unnamed_proc_0")
fc.exec_procedures(cero)
df1 = pd.read_csv("procedureload2.csv", index_col=0)
test_list = [1, 2, 3]
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = ["A", "B", "C"]
self.assertTrue(all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
os.remove("procedureload2.csv")
def test_sets_and_mapping(self):
cero = pd.DataFrame.from_dict(
{
"A": [1],
"B": [2],
"C": [3],
"D": [4],
"E": [5],
"F": [6],
},
orient='index',
dtype=pd.np.float32)
cero.sort_index(inplace=True)
cero.columns = pd.DatetimeIndex(
data=pd.to_datetime([2018], format="%Y"))
self.assertTrue(CERO.is_cero(cero))
fc = FromCERO(TestFromCERO._dd + "test_fromcero_mapping.yaml")
fc.exec_procedures(cero)
df1 = pd.read_csv("test_fromcero_mapping1.csv", index_col=0)
test_list = [1, 2, 3]
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(
all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = ["A", "B", "C"]
self.assertTrue(
all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
df2 = pd.read_csv("test_fromcero_mapping2.csv", index_col=0)
test_list = [4, 5, 6]
df2_vals = [x[0] for x in df2.values.tolist()]
self.assertTrue(all([x == y for (x, y) in zip(test_list, df2_vals)]))
test_list = ["G", "H", "I"]
self.assertTrue(
all([x == y for (x, y) in zip(test_list, df2.index.tolist())]))
os.remove("test_fromcero_mapping1.csv")
os.remove("test_fromcero_mapping2.csv")
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_sets_and_mapping2(self):
cero = pd.DataFrame.from_dict(
{
("A", "1"): [1],
("A", "2"): [2],
("A", "3"): [3],
("B", "1"): [4],
("B", "2"): [5],
("B", "3"): [6],
("C", "1"): [7],
("C", "2"): [8],
("C", "3"): [9],
},
orient='index',
dtype=pd.np.float32)
cero.sort_index(inplace=True)
cero.columns = pd.DatetimeIndex(
data=pd.to_datetime([2018], format="%Y"))
self.assertTrue(CERO.is_cero(cero))
fc = FromCERO(TestFromCERO._dd + "test_fromcero_mapping2.yaml")
fc.exec_procedures(cero)
tc = ToCERO({
"files": [{
"file": "test_fromcero_complexmapping1.xlsx",
"sheet": "CERO",
"index_col": [0, 1]
}]
})
df1 = tc.create_cero()
test_list = list(range(1, 10))
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(
all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = [("G", "1"), ("G", "2"), ("G", "3"), ("H", "1"),
("H", "2"), ("H", "3"), ("I", "1"), ("I", "2"),
("I", "3")]
self.assertTrue(
all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
tc = ToCERO({
"files": [{
"file": "test_fromcero_complexmapping2.xlsx",
"sheet": "CERO",
"index_col": [0, 1]
}]
})
df1 = tc.create_cero()
test_list = list(range(1, 10))
df1_vals = [x[0] for x in df1.values.tolist()]
self.assertTrue(
all([np.isclose(x, y) for (x, y) in zip(test_list, df1_vals)]))
test_list = [("A", "G"), ("A", "H"), ("A", "I"), ("B", "G"),
("B", "H"), ("B", "I"), ("C", "G"), ("C", "H"),
("C", "I")]
self.assertTrue(
all([x == y for (x, y) in zip(test_list, df1.index.tolist())]))
os.remove("test_fromcero_complexmapping1.xlsx")
os.remove("test_fromcero_complexmapping2.xlsx")