def prepareInputArguments(self):
valid_arg_list = getCallableArgumentList(pd.read_excel, get='args')
kwargs = dict()
for param in self.params():
if param.name() in valid_arg_list and self.p.evaluateValue(param.value()) != '':
kwargs[param.name()] = self.p.evaluateValue(param.value())
kwargs['io'] = os.path.abspath(self.paramValue('Select File'))
return kwargs
def prepareInputArguments(self):
valid_arg_list = getCallableArgumentList(pd.DataFrame.to_excel, get='args')
kwargs = dict()
for param in self.params():
if param.name() in valid_arg_list and self.p.evaluateValue(param.value()) != '':
kwargs[param.name()] = self.p.evaluateValue(param.value())
try:
Additional_kwargs = self.paramValue('Parameters', 'Additional parameters', datatype=dict)
if isinstance(Additional_kwargs, dict):
kwargs.update(Additional_kwargs)
except:
pass
return kwargs
def prepareInputArguments(self):
if self.paramValue('Load CSV parameters', 'Advanced parameters', 'Manually set parameters') is True:
# if we will use manually set params... then simply evaluate text-field
kwargs = self.paramValue('Load CSV parameters', 'Advanced parameters', 'Manually set parameters', 'Manuall parameters', datatype=dict)
else:
valid_arg_list = getCallableArgumentList(pd.read_csv, get='args')
kwargs = dict()
for param in self.params():
if param.name() in valid_arg_list and self.p.evaluateValue(param.value()) != '':
kwargs[param.name()] = self.p.evaluateValue(param.value())
#if kwargs['date_parser'] is not None:
# convert our STR to lambda FUNCTION
#dateParserStr = kwargs['date_parser']
#kwargs['date_parser'] = lambda x: datetime.strptime(x, dateParserStr)
kwargs['filepath_or_buffer'] = self.paramValue('Select File')
return kwargs
def prepareInputArguments(self):
valid_arg_list = getCallableArgumentList(pd.DataFrame.to_excel,
get='args')
kwargs = dict()
for param in self.params():
if param.name() in valid_arg_list and self.p.evaluateValue(
param.value()) != '':
kwargs[param.name()] = self.p.evaluateValue(param.value())
try:
Additional_kwargs = self.paramValue('Parameters',
'Additional parameters',
datatype=dict)
if isinstance(Additional_kwargs, dict):
kwargs.update(Additional_kwargs)
except:
pass
return kwargs
def prepareInputArguments(self):
validArgs = getCallableArgumentList(plot_pandas.plot_pandas_scatter_special1, get='args')
validArgs += ['MHW', 'MLW', 'MLWS', 'LLW']
kwargs = dict()
for param in self.params(ignore_groups=True):
if param.name() in validArgs:
kwargs[param.name()] = self.p.evaluateValue(param.value())
if kwargs['xlabel'] in [None, 'None', '']: kwargs['xlabel'] = kwargs['x']
if kwargs['ylabel'] in [None, 'None', '']: kwargs['ylabel'] = kwargs['y']
kwargs['x'] = [kwargs.pop('x')]
kwargs['y'] = [kwargs.pop('y')]
if self.paramValue('Hydrological Values'):
kwargs['HYDR_VALS'] = dict()
for name in ['MHW', 'MLW', 'MLWS', 'LLW']:
if self.paramValue('Hydrological Values'):
kwargs['HYDR_VALS'][name] = kwargs.pop(name)
else:
kwargs.pop(name)
return kwargs
def prepareInputArguments(self):
if self.paramValue('Load CSV parameters', 'Advanced parameters',
'Manually set parameters') is True:
# if we will use manually set params... then simply evaluate text-field
kwargs = self.paramValue('Load CSV parameters',
'Advanced parameters',
'Manually set parameters',
'Manuall parameters',
datatype=dict)
else:
valid_arg_list = getCallableArgumentList(pd.read_csv, get='args')
kwargs = dict()
for param in self.params():
if param.name() in valid_arg_list and self.p.evaluateValue(
param.value()) != '':
kwargs[param.name()] = self.p.evaluateValue(param.value())
#if kwargs['date_parser'] is not None:
# convert our STR to lambda FUNCTION
#dateParserStr = kwargs['date_parser']
#kwargs['date_parser'] = lambda x: datetime.strptime(x, dateParserStr)
kwargs['filepath_or_buffer'] = self.paramValue('Select File')
return kwargs