def test_evaluate(self):
directory, script_name = os.path.split(os.path.abspath(__file__))
workbook_name = os.path.join(directory, "test_model.xlsx")
sheet = "Sheet1"
input_parameters = {
"a": ("B2", sheet),
"b": ("B3", sheet),
"theta": ("B4", sheet)
}
output_parameters = {"feval": ("C2", sheet)}
excel_black_obj = ExcelBlackBoxEvaluator(input_parameters,
output_parameters,
workbook_name, ExcelDriverCOM)
to_evaluate = {"a": 2.0, "b": 2.0, "theta": math.pi}
result = excel_black_obj.evaluate(to_evaluate)
self.assertIsNotNone(result)
expected_result = {"feval": 2.0 * math.sin((1 / 2.0) * math.pi)}
self.assertEquals(expected_result, result)
excel_black_obj.close()
def test_evaluate_dummy(self):
sheet = "sheet1"
input_parameters = {"a": ("B2", sheet), "b": ("B3", sheet), "theta": ("B4", sheet)}
output_parameters = {"feval": ("C2", sheet)}
workbook_name = "test_workbook.xlsx"
excel_black_obj = ExcelBlackBoxEvaluator(input_parameters, output_parameters, workbook_name)
to_evaluate = {"a": 2.0, "b": 2.0, "theta": math.pi}
result = excel_black_obj.evaluate(to_evaluate)
self.assertIsNotNone(result)
expected_result = {"feval": 2.0 * math.sin((1/2.0) * math.pi)}
self.assertEquals(expected_result, result)
def test_evaluate(self):
directory, script_name = os.path.split(os.path.abspath(__file__))
workbook_name = os.path.join(directory, "test_model.xlsx")
sheet = "Sheet1"
input_parameters = {"a": ("B2", sheet), "b": ("B3", sheet), "theta": ("B4", sheet)}
output_parameters = {"feval": ("C2", sheet)}
excel_black_obj = ExcelBlackBoxEvaluator(input_parameters, output_parameters, workbook_name, ExcelDriverCOM)
to_evaluate = {"a": 2.0, "b": 2.0, "theta": math.pi}
result = excel_black_obj.evaluate(to_evaluate)
self.assertIsNotNone(result)
expected_result = {"feval": 2.0 * math.sin((1/2.0) * math.pi)}
self.assertEquals(expected_result, result)
excel_black_obj.close()
def test_evaluate_dummy(self):
sheet = "sheet1"
input_parameters = {
"a": ("B2", sheet),
"b": ("B3", sheet),
"theta": ("B4", sheet)
}
output_parameters = {"feval": ("C2", sheet)}
workbook_name = "test_workbook.xlsx"
excel_black_obj = ExcelBlackBoxEvaluator(input_parameters,
output_parameters,
workbook_name)
to_evaluate = {"a": 2.0, "b": 2.0, "theta": math.pi}
result = excel_black_obj.evaluate(to_evaluate)
self.assertIsNotNone(result)
expected_result = {"feval": 2.0 * math.sin((1 / 2.0) * math.pi)}
self.assertEquals(expected_result, result)
def main(input_spreadsheet_path, csv_output_file_name):
total_evals_i = 1
for variable in order_to_evaluate:
total_evals_i *= len(ranges_to_evaluate[variable])
print("Will make %s evaluations of the spreadsheet" % total_evals_i)
i = 0
sex = ranges_to_evaluate["Sex"]
age_years = ranges_to_evaluate["Age years"]
race = ranges_to_evaluate["Race"]
tc = ranges_to_evaluate["Total Cholesterol"]
hdl = ranges_to_evaluate["HDL-Cholesterol"]
sbp = ranges_to_evaluate["Systolic Blood Pressure"]
bpt = ranges_to_evaluate["Treatment of High Blood Pressure"]
diabetes = ranges_to_evaluate["Diabetes"]
smoker = ranges_to_evaluate["Smoker"]
with open(csv_output_file_name, "wb") as fw:
csv_writer = csv.writer(fw)
csv_writer.writerow(["row"] + order_to_evaluate + output_order_to_read)
for j in range(len(sex)):
for k in range(len(age_years)):
for l in range(len(race)):
for m in range(len(tc)):
for n in range(len(hdl)):
for o in range(len(sbp)):
for p in range(len(bpt)):
for q in range(len(diabetes)):
for r in range(len(smoker)):
dict_to_evaluate = {"Sex": sex[j], "Age years": age_years[k],
"Race": race[l], "Total Cholesterol": tc[m],
"HDL-Cholesterol": hdl[n],
"Systolic Blood Pressure": sbp[o],
"Treatment of High Blood Pressure": bpt[p],
"Diabetes": diabetes[q],
"Smoker": smoker[r],
}
row_to_write = []
for variable in order_to_evaluate:
row_to_write += [dict_to_evaluate[variable]]
if i % 100 == 0:
if i == 0:
pass
else:
print("Processed %s evaluations" % (i + 1,))
excel_black_obj.close()
excel_black_obj = ExcelBlackBoxEvaluator(input_dict, output_dict,
input_spreadsheet_path, ExcelDriverCOM)
result_dict = excel_black_obj.evaluate(dict_to_evaluate)
result_list = []
for output_variable in output_order_to_read:
result_list += [result_dict[output_variable]]
csv_writer.writerow([i + 1] + row_to_write + result_list)
# if i == 5001:
# excel_black_obj.close()
# exit()
i += 1
def main(input_spreadsheet_path, csv_output_file_name):
total_evals_i = 1
for variable in order_to_evaluate:
total_evals_i *= len(ranges_to_evaluate[variable])
print("Will make %s evaluations of the spreadsheet" % total_evals_i)
i = 0
sex = ranges_to_evaluate["Sex"]
age_years = ranges_to_evaluate["Age years"]
race = ranges_to_evaluate["Race"]
tc = ranges_to_evaluate["Total Cholesterol"]
hdl = ranges_to_evaluate["HDL-Cholesterol"]
sbp = ranges_to_evaluate["Systolic Blood Pressure"]
bpt = ranges_to_evaluate["Treatment of High Blood Pressure"]
diabetes = ranges_to_evaluate["Diabetes"]
smoker = ranges_to_evaluate["Smoker"]
with open(csv_output_file_name, "wb") as fw:
csv_writer = csv.writer(fw)
csv_writer.writerow(["row"] + order_to_evaluate + output_order_to_read)
for j in range(len(sex)):
for k in range(len(age_years)):
for l in range(len(race)):
for m in range(len(tc)):
for n in range(len(hdl)):
for o in range(len(sbp)):
for p in range(len(bpt)):
for q in range(len(diabetes)):
for r in range(len(smoker)):
dict_to_evaluate = {
"Sex":
sex[j],
"Age years":
age_years[k],
"Race":
race[l],
"Total Cholesterol":
tc[m],
"HDL-Cholesterol":
hdl[n],
"Systolic Blood Pressure":
sbp[o],
"Treatment of High Blood Pressure":
bpt[p],
"Diabetes":
diabetes[q],
"Smoker":
smoker[r],
}
row_to_write = []
for variable in order_to_evaluate:
row_to_write += [
dict_to_evaluate[variable]
]
if i % 100 == 0:
if i == 0:
pass
else:
print(
"Processed %s evaluations"
% (i + 1, ))
excel_black_obj.close()
excel_black_obj = ExcelBlackBoxEvaluator(
input_dict, output_dict,
input_spreadsheet_path,
ExcelDriverCOM)
result_dict = excel_black_obj.evaluate(
dict_to_evaluate)
result_list = []
for output_variable in output_order_to_read:
result_list += [
result_dict[
output_variable]
]
csv_writer.writerow([i + 1] +
row_to_write +
result_list)
# if i == 5001:
# excel_black_obj.close()
# exit()
i += 1
