def main(filename, output_format='xlsx', output_dir='', sheet_name_usr=''):
''' Main function to run DEA models from terminal.
Args:
filename (str): path to file with parameters.
output_format (str, optional): file format of solution file.
This value is used
only if OUTPUT_FILE in parameters is empty or set to auto.
Defaults to xlsx.
output_dir (str, optional): directory where solution must
be written.
If it is not given, solution will be written to current folder.
This value is used
only if OUTPUT_FILE in parameters is empty or set to auto.
sheet_name_usr (str, optional): name of the sheet in xls- or
xlsx-file with
input data from which data will be read. If input data file is
in csv format,
this value is ignored.
'''
print('Params file', filename, 'output_format', output_format,
'output_dir', output_dir, 'sheet_name_usr', sheet_name_usr)
logger = get_logger()
logger.info('Params file "%s", output format "%s", output directory "%s", sheet name "%s".',
filename, output_format, output_dir, sheet_name_usr)
params = parse_parameters_from_file(filename)
params.print_all_parameters()
run_method = RunMethodTerminal(params, sheet_name_usr, output_format,
output_dir)
run_method.run(params)
clean_up_pickled_files()
logger.info('pyDEA exited.')
def main():
''' Runs main application GUI.
'''
logger = get_logger()
logger.info('pyDEA started as a GUI application.')
root = Tk()
root.report_callback_exception = show_error
# load logo
if "nt" == os.name:
iconfile = pkg_resources.resource_filename(PACKAGE, 'pyDEAlogo.ico')
root.wm_iconbitmap(bitmap=iconfile)
else:
iconfile = pkg_resources.resource_filename(PACKAGE, 'pyDEAlogo.gif')
img = PhotoImage(file=iconfile)
root.tk.call('wm', 'iconphoto', root._w, img)
# change background color of all widgets
s = Style()
s.configure('.', background=bg_color)
# run the application
app = MainFrame(root)
root.protocol("WM_DELETE_WINDOW", (lambda: ask_quit(app)))
center_window(root,
root.winfo_screenwidth() - root.winfo_screenwidth()*0.15,
root.winfo_screenheight() - root.winfo_screenheight()*0.15)
root.mainloop()
logger.info('pyDEA exited.')
def main():
''' Runs main application GUI.
'''
logger = get_logger()
logger.info('pyDEA started as a GUI application.')
root = Tk()
root.report_callback_exception = show_error
# load logo
if "nt" == os.name:
iconfile = pkg_resources.resource_filename(PACKAGE, 'pyDEAlogo.ico')
root.wm_iconbitmap(bitmap=iconfile)
else:
iconfile = pkg_resources.resource_filename(PACKAGE, 'pyDEAlogo.gif')
img = PhotoImage(file=iconfile)
root.tk.call('wm', 'iconphoto', root._w, img)
# change background color of all widgets
s = Style()
s.configure('.', background=bg_color)
# run the application
app = MainFrame(root)
root.protocol("WM_DELETE_WINDOW", (lambda: ask_quit(app)))
center_window(root,
root.winfo_screenwidth() - root.winfo_screenwidth() * 0.15,
root.winfo_screenheight() - root.winfo_screenheight() * 0.15)
root.mainloop()
logger.info('pyDEA exited.')
logger = get_logger()
logger.info('Params file "%s", output format "%s", output directory "%s", sheet name "%s".',
filename, output_format, output_dir, sheet_name_usr)
params = parse_parameters_from_file(filename)
params.print_all_parameters()
run_method = RunMethodTerminal(params, sheet_name_usr, output_format,
output_dir)
run_method.run(params)
clean_up_pickled_files()
logger.info('pyDEA exited.')
if __name__ == '__main__':
args = sys.argv[1:]
logger = get_logger()
logger.info('pyDEA started as a console application.')
print('args = {0}'.format(args))
if len(args) < 1 or len(args) > 4:
logger.error('Invalid number of input arguments. At least one '
'argument must be given, no more than 4 arguments, but %d were given.',
len(args))
raise ValueError('Invalid number of input arguments. At least one '
'argument must be given, no more than 4 arguments'
' are expected. Input arguments are:\n (1) path to'
' file with parameters (compulsory)\n'
'(2) output file format, possible values: xls, xlsx'
' and csv, default value is xlsx (optional), this'
' value is used only if auto or empty string was set'
' for OUTPUT_FILE in parameters file \n'
'(3) output directory (optional, if not specified,'
def show_error(self, message):
''' See base class.
'''
logger = get_logger()
logger.error(message)
showerror('Error', message)
def run(self, params):
''' Executes solution routine - create data instance,
solve LPs, post-process solutions.
Args:
params (Parameters): parameters of a given problem instance
'''
logger = get_logger()
logger.info('Started solving given DEA model(s).')
logger.info('Parameters: %s', params.get_all_params_as_string())
categories = self.get_categories()
coefficients, has_same_dmus = self.get_coefficients()
if has_same_dmus:
self.show_error('Some DMUs have the same name')
else:
if validate_data(categories, coefficients):
try:
self.validate_weights_if_needed() # MUST be called
# before model_builder, because it might
# update parameters
model_input = construct_input_data_instance(
categories, coefficients)
models, all_params = model_builder.build_models(
params, model_input)
self.init_before_run(len(models), coefficients)
solutions = []
state = True
param_strs = []
all_ranks = []
run_date = datetime.datetime.today()
start_time = datetime.datetime.now()
for count, model_obj in enumerate(models):
model = self.decorate_model(model_obj)
call_peel_the_onion = params.get_parameter_value(
'PEEL_THE_ONION')
if call_peel_the_onion:
model_solution, ranks, state = (
peel_the_onion_method(model))
all_ranks.append(ranks)
else:
model_solution = model.run()
str_to_write = create_params_str(all_params[count])
param_strs.append(str_to_write)
solutions.append(model_solution)
try:
solutions.append(model.second_solution)
param_strs.append(str_to_write + ' second phase')
except AttributeError:
pass
end_time = datetime.datetime.now()
diff = end_time - start_time
total_seconds = diff.total_seconds()
if params.get_parameter_value('RETURN_TO_SCALE') == 'both':
derive_returns_to_scale_classification(
param_strs, solutions)
self.post_process_solutions(solutions, params, param_strs,
all_ranks, run_date,
total_seconds)
if state is False:
self.show_error('For one of the runs of the '
'peel-the-onion problem is infeasible'
' or unbounded')
self.show_success()
except Exception as excinfo:
self.show_error(excinfo)
else:
logger.info('Given DEA model(s) successfully solved.')
else:
self.show_error('Some of the input data is not correct')
def show_error(self, message):
''' See base class.
'''
logger = get_logger()
logger.error(message)
print(message)
def show_error(*args):
logger = get_logger()
err = traceback.format_exception(*args)
logger.error(err)
# show only short error message to the user without traceback
showerror('Error', args[1])
def show_error(self, message):
''' See base class.
'''
logger = get_logger()
logger.error(message)
showerror('Error', message)
def run(self, params):
''' Executes solution routine - create data instance,
solve LPs, post-process solutions.
Args:
params (Parameters): parameters of a given problem instance
'''
logger = get_logger()
logger.info('Started solving given DEA model(s).')
logger.info('Parameters: %s', params.get_all_params_as_string())
categories = self.get_categories()
coefficients, has_same_dmus = self.get_coefficients()
if has_same_dmus:
self.show_error('Some DMUs have the same name')
else:
if validate_data(categories, coefficients):
try:
self.validate_weights_if_needed() # MUST be called
# before model_builder, because it might
# update parameters
model_input = construct_input_data_instance(categories,
coefficients)
models, all_params = model_builder.build_models(params,
model_input)
self.init_before_run(len(models), coefficients)
solutions = []
state = True
param_strs = []
all_ranks = []
run_date = datetime.datetime.today()
start_time = datetime.datetime.now()
for count, model_obj in enumerate(models):
model = self.decorate_model(model_obj)
call_peel_the_onion = params.get_parameter_value(
'PEEL_THE_ONION')
if call_peel_the_onion:
model_solution, ranks, state = (
peel_the_onion_method(model))
all_ranks.append(ranks)
else:
model_solution = model.run()
str_to_write = create_params_str(all_params[count])
param_strs.append(str_to_write)
solutions.append(model_solution)
try:
solutions.append(model.second_solution)
param_strs.append(str_to_write + ' second phase')
except AttributeError:
pass
end_time = datetime.datetime.now()
diff = end_time - start_time
total_seconds = diff.total_seconds()
if params.get_parameter_value('RETURN_TO_SCALE') == 'both':
derive_returns_to_scale_classification(param_strs, solutions)
self.post_process_solutions(solutions, params, param_strs,
all_ranks, run_date,
total_seconds)
if state is False:
self.show_error('For one of the runs of the '
'peel-the-onion problem is infeasible'
' or unbounded')
self.show_success()
except Exception as excinfo:
self.show_error(excinfo)
else:
logger.info('Given DEA model(s) successfully solved.')
else:
self.show_error('Some of the input data is not correct')
def show_error(self, message):
''' See base class.
'''
logger = get_logger()
logger.error(message)
print(message)
def show_error(*args):
logger = get_logger()
err = traceback.format_exception(*args)
logger.error(err)
# show only short error message to the user without traceback
showerror('Error', args[1])
