Test your AI Agents with the all-new Agent to Agent Testing Platform.Learn More

How to use __pop method in hypothesis

Best Python code snippet using hypothesis

2kyu_befunge_interpreter.py

Source:2kyu_befunge_interpreter.py

...106                col = 0107            else:108                self.matrix[row][col] = c109                col += 1110    def __pop(self):111        try:112            res = self.stack.pop()113        except:114            res = 0115        return res116    def __push(self, s):117        self.stack.append(s)118    def __direction(self, direction):119        self.current_direction = direction120    def __push_num(self):121        self.__push(int(self.matrix[self.current_row][self.current_col]))122    def __add(self):123        x = self.__pop()124        y = self.__pop()125        self.__push(x + y)126    def __subtract(self):127        x = self.__pop()128        y = self.__pop()129        self.__push(y - x)130    def __multiple(self):131        x = self.__pop()132        y = self.__pop()133        self.__push(x * y)134    def __divide(self):135        x = self.__pop()136        y = self.__pop()137        if y == 0:138            self.__push(0)139        else:140            self.__push(round(y / x, 0))141    def __mod(self):142        x = self.__pop()143        y = self.__pop()144        if x == 0:145            self.__push(0)146        else:147            self.__push(y % x)148    def __not(self):149        x = self.__pop()150        if x == 0:151            self.__push(1)152        else:153            self.__push(0)154    def __gt(self):155        x = self.__pop()156        y = self.__pop()157        if y > x:158            self.__push(1)159        else:160            self.__push(0)161    def __moving_right(self):162        self.__direction('>')163    def __moving_left(self):164        self.__direction('<')165    def __moving_up(self):166        self.__direction('^')167    def __moving_down(self):168        self.__direction('v')169    def __moving_random_direction(self):170        direction = ['>', '<', '^', 'v']171        self.__direction(direction)172        self.BEFUNGE_CODE_TABLE[random.choice(direction)]()173    def __moving_by_cond_right_left(self):174        x = self.__pop()175        if x == 0:176            self.BEFUNGE_CODE_TABLE['>']()177        else:178            self.BEFUNGE_CODE_TABLE['<']()179    def __moving_by_cond_up_down(self):180        x = self.__pop()181        if x == 0:182            self.BEFUNGE_CODE_TABLE['v']()183        else:184            self.BEFUNGE_CODE_TABLE['^']()185    def __string_mode(self):186        self.__moving()187        n = ord(str(self.matrix[self.current_row][self.current_col]))188        while n != 34:189            self.__push(n)190            self.__moving()191            n = ord(str(self.matrix[self.current_row][self.current_col]))192    def __duplicate(self):193        x = self.__pop()194        self.__push(x)195        self.__push(x)196    def __swap(self):197        x = self.__pop()198        y = self.__pop()199        self.__push(x)200        self.__push(y)201    def __discard(self):202        self.__pop()203    def __end(self):204        self.is_ended = True205    def __get_integer(self):206        self.result.append(str(self.__pop()))207    def __get_char(self):208        self.result.append(chr(self.__pop()))209    def __trampoline(self):210        self.__moving()211    def __put_to_xy(self):212        x = self.__pop()213        y = self.__pop()214        v = self.__pop()215        self.matrix[x][y] = chr(v)216    def __get_from_xy(self):217        y = self.__pop()218        x = self.__pop()219        self.__push(ord(self.matrix[y][x]))220    def __nothing(self):221        pass222    def __moving(self, count=1):223        if self.current_direction == '>':224            self.current_col += count225        elif self.current_direction == '<':226            self.current_col -= count227        elif self.current_direction == '^':228            self.current_row -= count229        elif self.current_direction == 'v':230            self.current_row += count231class TestBefunge(unittest.TestCase):232    def test_befunge_is_valid(self):...

Mopso.py

Source:Mopso.py

1# encoding: utf-823import time4import numpy as np5from util import update, drawCurve, testFunc, NDsort6import memory_profiler as mem78class Mopso:9    def __init__(self, num_pop, max_, min_, threshold, grid_div=10):10        self.__grid = grid_div11        self.__num_pop = num_pop  # ç§ç¾¤ç²åæ°é12        self.__threshold = threshold13        self.__max = max_14        self.__min = min_1516        # self.max_v = (max_-min_)*0.5  #éåº¦ä¸é17        # self.min_v = (max_-min_)*(-1)*0.5 #éåº¦ä¸é18        self.__max_v = 100 * np.ones(len(max_), )  # éåº¦ä¸ä¸é,éåº¦ä¸åå¨ä¸ä¸éï¼å æ¤è®¾ç½®å¾å¤§19        self.__min_v = -100 * np.ones(len(min_), )2021        self.__pop = None22        self.__v = None23        self.__fit = None24        self.__pop_pbest = None25        self.__fit_pbest = None26        self.__pop_gbest = None27        self.__fit_gbest = None28        self.__archive_pop = None29        self.__archive_fit = None3031        self.__draw = drawCurve.DrawParetoCurve()3233    def evaluation_fitness(self):34        self.__fit = testFunc.obj_func("value", "DTLZ2", 2, self.__pop)3536    def initialize(self):37        """38        åå§åç²åç¾¤39        :return:40        """41        # åå§åç²åä½ç½® pop[i]42        # self.__num_pop ç²åç¾¤æ°é43        self.__pop = self.__init_loc(self.__num_pop, self.__max, self.__min)44        # åå§åç²åéåº¦ å¨045        self.__v = self.__init_v(self.__num_pop, self.__max_v, self.__min_v)46        # è®¡ç®éåºåº¦47        self.evaluation_fitness()48        # åå§åä¸ªä½æä¼49        # TODO ç¬¬äºä¸ªåæ°åºè¯¥æ¯éåº¦ï¼50        self.__pop_pbest, self.__fit_pbest = self.__init_pbest(self.__pop, self.__fit)51        # åå§åå¤é¨åæ¡£52        self.__archive_pop, self.__archive_fit = self.__init_archive(self.__pop, self.__fit)53        # åå§åå¨å±æä¼54        self.__pop_gbest, self.__fit_gbest = update.update_gbest(self.__archive_pop, self.__archive_fit, self.__grid,55                                                                 self.__num_pop)5657    def update(self):58        """59        æ´æ°ç²åéåº¦ãä½ç½®ãéåºåº¦ãä¸ªä½æä¼ãå¤é¨åæ¡£ãå¨å±æä¼60        :return:61        """62        self.__v = update.update_v(self.__v, self.__min_v, self.__max_v, self.__pop, self.__pop_pbest, self.__pop_gbest)63        self.__pop = update.update_pop(self.__pop, self.__v, self.__min, self.__max)6465        self.evaluation_fitness()6667        self.__pop_pbest, self.__fit_pbest = update.update_pbest(self.__pop, self.__fit, self.__pop_pbest,68                                                                 self.__fit_pbest)6970        self.__archive_pop, self.__archive_fit = update.update_archive(self.__pop, self.__fit, self.__archive_pop,71                                                                       self.__archive_fit,72                                                                       self.__threshold, self.__grid)7374        self.__pop_gbest, self.__fit_gbest = update.update_gbest(self.__archive_pop, self.__archive_fit, self.__grid,75                                                                 self.__num_pop)7677    def run(self, iterate):78        # å¼å§æ¶é´æ³79        beg = time.time()80        print(f'è¿è¡åå ç¨ååï¼{mem.memory_usage()}')81        self.initialize()82        self.__draw.show(self.__pop, self.__fit, self.__archive_pop, self.__archive_fit, -1)83        for i in range(iterate):84            self.update()  # æ´æ°ç§ç¾¤85            # numpy.round() è¿åæµ®ç¹æ°çåèäºå¥å¼86            print('ç¬¬', i+1, 'ä»£å·²å®æï¼èè´¹æ¶é´: ', np.round(time.time() - beg, 2), "s")87            self.__draw.show(self.__pop, self.__fit, self.__archive_pop, self.__archive_fit, i)88        print(f'è¿è¡åå ç¨ååï¼{mem.memory_usage()}')89        return self.__archive_pop, self.__archive_fit9091    @staticmethod92    def __init_loc(pop, pop_max, pop_min):93        # åå§åç²åä½ç½®94        dim = len(pop_max)  # è¾å¥åæ°ç»´åº¦95        # numpy.random.uniform(low, high, size) ä»åååå¸ä¸éæºéæ ·ï¼sizeæ¯è¾åºæ ·æ¬æ°é96        return np.random.uniform(0, 1, (pop, dim)) * (pop_max - pop_min) + pop_min9798    @staticmethod99    def __init_v(pop, v_max, v_min):100        v_dim = len(v_max)  # ç»´åº¦101        # v_ = np.random.uniform(0,1,(particals,v_dim))*(v_max-v_min)+v_min102        return np.zeros((pop, v_dim))103104    @staticmethod105    def __init_pbest(pop, fit):106        return pop, fit107108    @staticmethod109    def __init_archive(pop, fit):110        # NDSort()[0] ååºç¬¬ä¸ç»è¿åå¼ï¼å¦ææ¯1åæ¯ç¬¬ä¸å±çç²å111        front_index = NDsort.NDSort(fit, pop.shape[0])[0] == 1112        front_index = np.reshape(front_index, (-1,)) # ç©éµè½¬æè¡åé113114        # curr_archiving_in = pop[front_index]115        # curr_archiving_fit = fit[front_index]116117        # pareto_c = pareto.Pareto_(pop,fitness_)118        # curr_archiving_in_,curr_archiving_fit_ = pareto_c.pareto()
...

bssa.py

Source:bssa.py

1from salp import Salp2from accuracy import cal_cost_knn, cal_cost_svm3import numpy as np4import logging 5import os6from copy import deepcopy7logger = logging.getLogger("main.bssa")8class BSSA:9    10    def __init__(self, pop, dim, tf, ub, lb, upate_strategy):11        self.__pop = [Salp(dim, ub, lb) for i in range(pop)]12        self.__tf = tf13        self.__ub = ub14        self.__lb = lb15        self.__selected_features_history = []16        self.__cost_history = []17        self.__acc_history = []18        self.__update_strategy = upate_strategy19        self.__cost_func = cal_cost_svm20    21    def get_pop(self):22        return self.__pop23    def set_pop(self, pop):24        self.__pop = pop25    def get_best_salp(self):26        return self.__pop[0]27    def get_best_position(self):28        return self.__pop[0].get_position()29    def get_best_selected(self):30        return np.round(self.get_best_position())31    def get_best_cost(self):32        return self.__pop[0].get_cost()33    def replace_with_worst_salp(self, best_salp):34        self.__pop = sorted(self.__pop, key=lambda x:x.get_cost())35        self.__pop[-1].set_position(best_salp.get_position())36        self.__pop[-1].set_cost(best_salp.get_cost())37        38    def reset_history(self):39        self.__cost_history = []40        self.__selected_features_history = []41        self.__acc_history = []42    def get_cost_history(self):43        return self.__cost_history44    def get_selected_features_history(self):45        return self.__selected_features_history46    def get_acc_history(self):47        return self.__acc_history48    def train(self, max_iteration, train_data, train_target, test_data, test_target):49        us = self.__update_strategy50        tf = self.__tf51        cf = self.__cost_func52        #measure accuracy and sort respect to the fitness53        for s in self.__pop:54            c, _, _ = cf(s.get_position(), train_data, train_target)55            s.set_cost(c)56        self.__pop = sorted(self.__pop, key=lambda x:x.get_cost())57        for s in self.__pop:58            logger.debug("cost is {}".format(s.get_cost()))59        #select the best one as food60        food = self.__pop[0]61        #it should be sorted62        for i in range(max_iteration):63            c1 = us(i, max_iteration)64            for this_s, pre_s, j in zip(self.__pop[1:], 65                                        self.__pop[-1:] + self.__pop[1:-1], 66                                        range(len(self.__pop))):67                if j<= len(self.__pop)/2.0:68                    c2 = np.random.rand(this_s.get_dim())69                    c3 = np.random.rand(this_s.get_dim())70                    c3 = np.array(list(map(lambda x:-1 if x<0.5 else 1, c3)))71                    this_s.set_position(food.get_position() + c1*c2*c3)72                else:73                    this_s.set_position((this_s.get_position() + pre_s.get_position())/2)74            for s in self.__pop:75                u = self.__ub76                l = self.__lb77                pos = s.get_position()78                pos = np.array(list(map(lambda x:l if x<l else(u if x>u else x), pos)))79                s.set_position(pos)80                c, _, _ = cf(s.get_position(), train_data, train_target)81                s.set_cost(c)82                if c < food.get_cost():83                    food.set_position(s.get_position())84                    food.set_cost(s.get_cost())85                    logger.debug("best changed to this cost {} last cost {}".format(s.get_cost(), food.get_cost()))   86            87            _, e, f = cf(food.get_position(), train_data, train_target)88            self.__acc_history.append(1 - e)89            self.__selected_features_history.append(f)90            self.__cost_history.append(food.get_cost())91            logger.info("iter {} cost {} pid {} ppid {}".format(i, food.get_cost(), os.getpid(), os.getppid()))...

Automation Testing Tutorials

Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.