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