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How to use __isfloat method in autotest

Best Python code snippet using autotest_python

data_structure.py

Source:data_structure.py

...320        321        if False:322            pass323        else:            324            if self.__isfloat(item):325                assert self.shape[1] == 1 , "Cannot check less than on more than one column"326                indexes = [i for i,element in enumerate(self.aslist) if float(element) < float(item)]327                328                #Returns False if no item is matched or list of index if some items are matched329                if len(indexes) == 0:330                    return False331                else:332                    return indexes333            else:334                assert False, "item should be convertible datatype or a dataFrame of same shape "335            336    def __ne__(self,item):337        '''Implementing '!=' for dataFrame '''338        339        340        value = (self == item)341        342        if type(value) == bool:343            return (not value)344        elif type(value)==list:345            indexes = [i for i in range(self.num_rows) if i not in value]346            return indexes347            348    def __truediv__(self, item):349        '''Implementing '/' operator for dataFrame'''350        351        assert self.shape[1] == 1,"Cannot call / on more than one column"352        truediv_array = [['']]*self.num_rows353        354        #Simple broadcasting355        if  self.__isfloat(item):356            for i in range(self.num_rows):357                truediv_array[i] = [round(float(self[i])/float(item),4)] if self.__isfloat(self[i]) else [float('NaN')]358            truediv_array.insert(0,[self.columns[0]])359            return dataFrame(truediv_array)360        361        #When item is a dataFrame362        #Note that column name of the returned dataframe is the column name of first operand363        elif type(item) == type(dataFrame([[''],['']])):364            assert self.shape == item.shape , "No of rows mismatched"365            for i in range(self.num_rows):366                truediv_array[i] = [round(float(self[i])/float(item[i]),4)] if (self.__isfloat(self[i]) and self.__isfloat(item[i])) else [float('NaN')]367            truediv_array.insert(0,[self.columns[0]])368            return dataFrame(truediv_array)369        370        else:371            assert False,"item should be float convertible datatype or a dataFrame of same shape"372            373                374    def __add__(self, item):375        '''Implementing '+' operator for dataFrame'''376        377        assert self.shape[1] == 1,"Cannot call + on more than one column"378        add_array = [['']]*self.num_rows379        380        #Simple broadcasting381        if  self.__isfloat(item):382            for i in range(self.num_rows):383                add_array[i] = [round(float(self[i])+float(item),4)] if self.__isfloat(self[i]) else [float('NaN')]384            add_array.insert(0,[self.columns[0]])385            return dataFrame(add_array)386        387        #When item is a dataFrame388        elif type(item) == type(dataFrame([[''],['']])):389            assert self.shape == item.shape , "No of rows mismatched"390            for i in range(self.num_rows):391                add_array[i] = [round(float(self[i])+float(item[i]),4)] if (self.__isfloat(self[i]) and self.__isfloat(item[i])) else [float('NaN')]392            add_array.insert(0,[self.columns[0]])393            return dataFrame(add_array)394            395        else:396            assert False,"item should be convertible datatype or a dataFrame of same shape"397                398    def __sub__(self, item):399        '''Implementing '-' operator for dataFrame'''400        401        assert self.shape[1] == 1,"Cannot call - on more than one column"402        sub_array = [['']]*self.num_rows403        404        #Simple broadcasting405        if  self.__isfloat(item):406            for i in range(self.num_rows):407                sub_array[i] = [round(float(self[i])-float(item),4)] if self.__isfloat(self[i]) else [float('NaN')]408            sub_array.insert(0,[self.columns[0]])409            return dataFrame(sub_array)410        411        #When item is a dataFrame412        #Note that column name of the returned dataframe is the column name of first operand413        elif type(item) == type(dataFrame([[''],['']])):414            assert self.shape == item.shape , "No of rows mismatched"415            for i in range(self.num_rows):416                sub_array[i] = [round(float(self[i])-float(item[i]),4)] if (self.__isfloat(self[i]) and self.__isfloat(item[i])) else [float('NaN')]417            sub_array.insert(0,[self.columns[0]])418            return dataFrame(sub_array)419        420        421        else:422            assert False,"item should be float convertible datatype or a dataFrame of same shape"423                424    def __pow__(self, item):425        '''Implementing '**' operator for dataFrame'''426        427        assert self.shape[1] == 1,"Cannot call - on more than one column"428        pow_array = [['']]*self.num_rows429        430        #Simple broadcasting431        if  self.__isfloat(item):432            for i in range(self.num_rows):433                pow_array[i] = [round(float(self[i])**float(item),4)] if self.__isfloat(self[i]) else [float('NaN')]434            pow_array.insert(0,[self.columns[0]])435            return dataFrame(pow_array)436        437        #When item is a dataFrame438        #Note that column name of the returned dataframe is the column name of first operand439        elif type(item) == type(dataFrame([[''],['']])):440            assert self.shape == item.shape , "No of rows mismatched"441            for i in range(self.num_rows):442                pow_array[i] = [round(float(self[i])**float(item[i]),4)] if (self.__isfloat(self[i]) and self.__isfloat(item[i])) else [float('NaN')]443            pow_array.insert(0,[self.columns[0]])444            return dataFrame(pow_array)445        446        447        else:448            assert False,"item should be float convertible datatype or a dataFrame of same shape"449            450            451            452    def __find_columns(self,column_name):453        '''returns the list of all indexes for the given column name present in the dataFrame'''454        455        assert column_name in self.columns , "Invalid Column name"456        idxes = []457        for i in range(len(self.columns)):458            if column_name == self.columns[i]:459                idxes.append(i)460        return idxes461    462    463    def __display_dict(self,dic):464        max_length = len(max(list(dic.keys()),key = len))465        for elem in dic:466            print('{0:<{1}} : {2}'.format(elem,max_length,dic[elem]))467        print('\n')        468    469    470    def __isfloat(self,x):471        try:472            float(x)473            return True474        except ValueError:475            return False476        except TypeError:477            return False478        479    #Bi-type480    def __find_first_index_ofTwo(self,value):481        '''Uses bisection search algorithm to find the index482        483            NOTE: Only works if type and non-type elements are present484            where the given value is type and all others are non type485            and type elements always occur together at last'''486        487        assert self.shape[1] == 1,"Cannot find index on more than one column with this method"488        low = 0 489        lst = self.aslist490        high = len(lst)-1491        idx = -1492        493        #Bisection implementation494        while low <= high:495            mid = (high+low)//2496            497            if self[mid] == value:498                idx = mid499                high = mid-1500            501            elif self[mid] != value:502                low = mid+1503                504            505        if idx != -1:506            return idx507        else:508            assert False, "Element Not Found"509    510        511    def change_columnName(self,name):512        if isinstance(name,list):513            assert self.num_columns == len(name) , "Number of columns mismatched"514            self.__rows[0] = name515        else:516            assert False, "Argument for column should be given as a list"517                      518            519    def value_counts(self):520        assert self.shape[1] == 1,"Cannot call value_counts on more than one column"521        column_items = self.aslist522        523        item2counts = {}524        for column in column_items:525            if column == '' or column == 'NaN':526                continue527            if str(column) in item2counts:528                item2counts[str(column)]+=1529            else:530                item2counts[str(column)] = 1531        item2counts_ordered = OrderedDict(sorted(item2counts.items(), key = lambda x:-x[1]))532        self.__display_dict(item2counts_ordered)533        534    def diff(self):535        assert self.shape[1] == 1,"Cannot call diff on more than one column"536        537        diff_array = [['']]*self.num_rows538        for i in range(self.num_rows):539            if (i-1 >=0) and self.__isfloat(self.__getitem__(i)) and self.__isfloat(self.__getitem__(i-1)):540                diff_array[i] = [round(float(self.__getitem__(i))-float(self.__getitem__(i-1)),4)]541            else:542                diff_array[i] = ['NaN']543        diff_array.insert(0,[self.columns[0]])544        return dataFrame(diff_array)545    546    def sum(self,ignore_nons = True):547        '''Calculates the sum of elements of the column'''548        549        assert self.shape[1] == 1,"Cannot call sum on more than one column"550        if ignore_nons:551            sum_array = [float(self[i]) for i in range(self.num_rows) if (not math.isnan(float(self[i])) and self[i] not in ['NaN'] and self.__isfloat(self[i]))]552        else:553            return round(float(sum(self.aslist)),4)554        return round(float(sum(sum_array)),4)555    def num_items(self,ignore_nons = True):556        '''Calculates the sum of elements of the column'''557        558        assert self.shape[1] == 1,"Cannot call sum on more than one column"559        if ignore_nons:560            array = [float(self[i]) for i in range(self.num_rows) if (not math.isnan(float(self[i])) and self[i] not in ['NaN'] and self.__isfloat(self[i]))]561        else:562            return len(self.num_rows)563        return len(array)564    565    566  567    568    def find_firstOfTwo(self, value):569        '''Finds the first index of given value'''570        571        return self.__find_first_index_ofTwo(value=value)572        573    def find_last_validOfTwo(self):574        '''Only 'NaN' are counted as Invalid...

rootError.py

Source:rootError.py

1from tkinter import messagebox23class Errors:4    @staticmethod5    def __checkNumber(number):6        if number.rfind('-') not in [0, -1] or number in ['.', '-'] or number == '': return False7        if number.count('.') not in [0, 1] or '-.' in number: return False8        for elem in number:9            if elem not in '0123456789.-':10                return False11        return True1213    @staticmethod14    def __isFloat(number):15        try:16            number = float(number)17            return True18        except:19            return False2021    @staticmethod22    def invalidList(list):23        listCol = {0: 'Ð½Ð°ÑÐ°Ð»Ð¾', 1: 'ÐºÐ¾Ð½ÐµÑ', 2: 'ÑÐ°Ð³', 3: 'ÑÐ¾ÑÐ½Ð¾ÑÑÑ', 4: 'ÐºÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð¸ÑÐµÑÐ°ÑÐ¸Ð¹'}24        if list == ['', '', '', '', '']:25            messagebox.showinfo('Error', 'ÐÑ Ð½Ðµ Ð²Ð²ÐµÐ»Ð¸ Ð´Ð°Ð½Ð½ÑÐµ')26            return False2728        for i, number in enumerate(list):29            if i not in [3, 4] and not Errors.__isFloat(number):30                messagebox.showinfo('Error', f'ÐÑ Ð½ÐµÐºÐ¾ÑÑÐµÐºÑÐ½Ð¾ Ð²Ð²ÐµÐ»Ð¸ {listCol[i]}')31                return False32            if i in [3, 4] and (not Errors.__isFloat(number) or float(number) <= 0):33                messagebox.showinfo('Error', f'ÐÑ Ð½ÐµÐºÐ¾ÑÑÐµÐºÑÐ½Ð¾ Ð²Ð²ÐµÐ»Ð¸ {listCol[i]}')34                return False3536        if float(list[0]) < float(list[1]) and float(list[2]) <= 0:37            messagebox.showinfo('Error', 'ÐÑÑÐ¸ÑÐ°ÑÐµÐ»ÑÐ½ÑÐ¹ ÑÐ°Ð³ Ð¿ÑÐ¸ Ð»ÐµÐ²Ð¾Ð¹ Ð³ÑÐ°Ð½Ð¸ÑÐµ Ð¼ÐµÐ½ÑÑÐµÐ¹ Ð¿ÑÐ°Ð²Ð¾Ð¹')38            return False39        elif float(list[0]) > float(list[1]) and float(list[2]) >= 0:40            messagebox.showinfo('Error', 'ÐÐ¾Ð»Ð¾Ð¶Ð¸ÑÐµÐ»ÑÐ½ÑÐ¹ ÑÐ°Ð³ Ð¿ÑÐ¸ Ð»ÐµÐ²Ð¾Ð¹ Ð³ÑÐ°Ð½Ð¸ÑÐµ Ð±Ð¾Ð»ÑÑÐµÐ¹ Ð¿ÑÐ°Ð²Ð¾Ð¹')41            return False42        elif float(list[0]) == float(list[1]):43            messagebox.showinfo('Error', 'ÐÐ°ÑÐ°Ð»Ð¾ Ð¸ ÐºÐ¾Ð½ÐµÑ Ð¾ÑÑÐµÐ·ÐºÐ° ÑÐ¾Ð²Ð¿Ð°Ð´Ð°ÑÑ')44            return False45        elif float(list[2]) == 0:46            messagebox.showinfo('Error', 'Ð¨Ð°Ð³ ÑÐ°Ð²ÐµÐ½ 0')47            return False4849        if (float(list[3]) > 0.01):50            messagebox.showinfo('Error', 'Ð¡Ð»Ð¸ÑÐºÐ¾Ð¼ Ð±Ð¾Ð»ÑÑÐ°Ñ ÑÐ¾ÑÐ½Ð¾ÑÑÑ')51            return False
...

Method.py

Source:Method.py

...8	def get_function_value(self, variable_values):9		if len(self.mathematical_model.variables) == len(variable_values):10			obj_function = self.mathematical_model.objective_function11			for i in range(0, len(variable_values)):12				if self.__isfloat(variable_values[i]):13					obj_function = obj_function.replace(self.mathematical_model.variables[i], str(variable_values[i]))14			return eval(obj_function)15		else:16			print('Error >>> ÐÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð¿ÐµÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð½Ðµ ÑÐ¾Ð²Ð¿Ð°Ð´Ð°ÐµÑ.')17			return False18	def is_satisfies_constraints(self, variable_values):19		if len(self.mathematical_model.variables) == len(variable_values):20			constraints = self.mathematical_model.constraints21			for constraint in constraints:22				for i in range(0, len(variable_values)):23					if self.__isfloat(variable_values[i]):24						constraint = constraint.replace(self.mathematical_model.variables[i], str(variable_values[i]))25				if eval(constraint) == False:26					return False27			return True28		else:29			print('Error >>> ÐÐ¾Ð»Ð¸ÑÐµÑÑÐ²Ð¾ Ð¿ÐµÑÐµÐ¼ÐµÐ½Ð½ÑÑ Ð½Ðµ ÑÐ¾Ð²Ð¿Ð°Ð´Ð°ÐµÑ.')30			return False31	def get_constraints_function_value(self, variable_values):32		if self.is_satisfies_constraints(variable_values):33			return self.get_function_value(variable_values)34		else:35			return False 36	def __isfloat(self, value):37		try:38			float(value)39			return True40		except ValueError:41			return False42	def print_history(self):43		for line in self.list_result_history:44			print(line)45	def generate_result(self):46		point_string = ""47		for j in range(0, len(self.mathematical_model.variables)):48			point_string = point_string + self.mathematical_model.variables[j] + " = %.2f, " % self.result[j]49		point_string = point_string + "f = %.3f" % self.result[len(self.result) - 1]50		return point_string

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