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How to use show_elements method in SeleniumBase

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visualize.py

Source:visualize.py

1""" A wrapper class for visualizing propagation models. """2import os3import sys4import matplotlib.pyplot as plt5import matplotlib.patches as mpatches6import numpy as np7from utils.occ_map_utils import load_map, display_occ_map, plot_grid_map_hmm, show_traj, red_cm, blue_cm, greens_cm8from utils.occ_map_utils import show_map as show_walls9from utils.scene_utils import caculate_traj_from_scene10from data_generator.ped_sim import sample_trajectories11from metrics import cross_entropy12from animation import Plot13map_resolution = 0.214word_to_vel = { 'UP': [0, 1], 'LEFT': [-1, 0],15                'RIGHT': [1, 0], 'DOWN': [0, -1],16                'UPLEFT': [-1, 1], 'UPRIGHT': [1, 1],17                'DOWNLEFT': [-1, -1], 'DOWNRIGHT': [1, -1]}18# key press to update figure for the next tracking setp19def on_press(event, visualization):20    sys.stdout.flush()21    if event.key == ' ':22        visualization.visualize_next()23        visualization.fig.canvas.draw()24# show an arrow point to the cell clicked25def onclick(event, visualization):26    res = visualization.res27    ix, iy = event.xdata+res/2, event.ydata+res/228    delta = .329    for idx in np.ndindex(visualization.axes.shape):30        if visualization.axes[idx] == event.inaxes:31            visualization.axes[idx].arrow(ix+delta, iy+delta, -delta, -delta,32                                          head_width=0.2, head_length=0.1, fc='r', ec='r', zorder=15)33    visualization.fig.canvas.draw()34class Visualize(object):35    """36    A class for visualizing propagation models.37    """38    element_to_title = {"obser": "observation", "pred":"prediction", "corr":"after correction"}39    def __init__(self, models, num_steps, simulated_data=True, tracking=False, measurement_lost=None,40                 dynamically=True, show_map=True, show_seen=False, show_elements=['obser', 'pred', 'corr'],41                 show_colorbar=True, num_col=5, model_names=None, show_at=None, show_metric=True, **kwargs):42        self.models = models43        self.num_models = len(self.models)44        self.map = models[0].map45        self.res = models[0].map_res46        self.extent = models[0].extent47        self.num_steps = num_steps48        self.dynamically = dynamically49        self.simulated_data = simulated_data50        self.tracking = tracking51        self.measurement_lost = measurement_lost52        self.show_map = show_map53        self.show_seen = show_seen54        self.show_metric = show_metric55        show_order = {'pred': 0, 'obser':1, 'corr':2}56        show_elements.sort(key=lambda name: show_order[name])57        self.show_elements = show_elements if tracking else ['pred']58        self.num_col = self._get_num_col(num_col, self.show_elements)59        self.show_at = show_at60        if not self.dynamically and show_at is not None:61            self.num_col = len(show_at)62        self.show_colorbar = show_colorbar63        self.model_names = [model.name for model in self.models]64        if model_names is not None:65            self.model_names = model_names66        self.fig, self.axes, self.plots = self._init_figure()67        # bind key press event to update figure68        self.fig.canvas.mpl_connect('key_press_event', lambda event: on_press(event, self))69        self.fig.canvas.mpl_connect('button_press_event', lambda event: onclick(event, self))70        self.initialize_models()71        self.init_plot_contents()72    def initialize_models(self):73        """ This method has to be implemented by subclasses. """74        pass75    def _get_num_col(self, num_col, show_elements):76        """ Determine number of columns in the figure."""77        if self.dynamically:78            all_elements = ['obser', 'pred', 'corr']79            require_show = map(lambda e: e in all_elements, show_elements)80            return sum(require_show)81        else:82            return num_col83    def _init_figure(self):84        num_rows, num_cols = self.num_models, self.num_col85        fig_size = (4 * num_cols, 3.5 * num_rows)86        fig = plt.figure(figsize=fig_size)87        axes = np.empty((num_rows, num_cols), dtype=object)88        plots = np.empty((num_rows, num_cols), dtype=object)89        for i in range(num_rows):90            for j in range(num_cols):91                plot_idx = i * num_cols + j + 192                ax = fig.add_subplot(num_rows, num_cols, plot_idx)93                axes[i, j] = ax94                # no ticks on axis95                ax.set_xticklabels([])96                ax.set_yticklabels([])97                ax.xaxis.set_ticks_position('none')98                ax.yaxis.set_ticks_position('none')99        return fig, axes, plots100                # plot = Plot(ax, self.map, self.res, plot_seen=self., title='')101    def init_plot_contents(self):102        """ Decide plot contents for every plot."""103        colorbar_dict = {'pred': 'occupancy_axes', 'obser': 'map_axes', 'corr': 'occupancy_axes'}104        for i in range(self.num_models):105            for j in range(self.num_col):106                if not self.show_colorbar:107                    colorbar_on = None108                else:109                    if self.dynamically:110                        colorbar_on = colorbar_dict[self.show_elements[j]]111                    else:112                        colorbar_on = "occupancy_axes" if not self.tracking else None113                self.plots[i, j] = Plot(self.axes[i ,j], self.map, self.res,114                                       colorbar_on=colorbar_on,115                                       plot_map=self.show_map,116                                       plot_seen=self.show_seen,117                                       title='')118                if self.tracking and not self.dynamically:119                    self.add_custom_elements_to_plot(self.plots[i, j])120                if j == 0:121                    self.plots[i, j].set_ylabel(self.model_names[i])122                if self.traj_overlay:123                    # trajectory from scene can only be calculated for one target124                    num_targets = self.num_targets if self.simulated_data else 1125                    self.plots[i, j].add_traj_line(num_targets=num_targets)126        # add title to figure127        if self.simulated_data and self.init_moves is not None:128            self.fig.suptitle("Initial movements = {}".format(str(self.init_moves)))129        # add legend if neccessary130        if self.tracking and not self.dynamically:131            self.add_legend()132    def add_custom_elements_to_plot(self, plot):133        # add false negative axes134        # it shows locations where ground truth is occupied135        # but BOFUM fails to track136        plot.add_custom_image("fn_axes", blue_cm)137        # add true positive axes138        # it shows locations where ground truth is occupied139        # and BOFUM predicts occupancy prob higher than 0140        plot.add_custom_image("tp_axes", greens_cm)141        plot.add_colorbar("tp_axes")142        # add false positive axes143        plot.add_custom_image("fp_axes", red_cm)144    def add_legend(self):145        g_patch = mpatches.Patch(color='g', label='True positive')146        #b_patch = mpatches.Patch(color='b', label='False negative')147        o_patch = mpatches.Patch(color='orange', label='False positive', alpha=.6)148        #handles = [g_patch, b_patch, o_patch]149        handles = [g_patch, o_patch]150        plt.legend(handles=handles, bbox_to_anchor=(.6, 0., .35, .1),151                   loc = 'lower right',152                   ncol=3, mode='expand', borderaxespad=.0,153           bbox_transform=self.fig.transFigure)154        # plt.legend(handles=[g_patch, b_patch, o_patch], bbox_to_anchor=(0., 1.1),155        #            loc=1, ncol=1, mode="expand", borderaxespad=None,156        #             bbox_transform=self.fig.transFigure)157    def start(self):158        # reset model's step counter159        # for model in self.models:160        #     model.t = 0161        plt.show()162    def visualize_next(self):163        if self.dynamically:164            if(self.models[0].t < self.num_steps):165                t = self.models[0].t166                print("t is " + str(t))167                # generate measurement data168                measurement = self.models[0].measurement_at() if self.tracking else None169                for model in self.models:170                    measurement = model.tracking_step(measurement=measurement)171                self.show_dynamically(measurement)172        else:173            self.show_occupancies()174    def show_dynamically(self, observation):175        Ot_pred_max, Ot_pred_min = None, None176        Ot_max, Ot_min = None, None177        if 'pred' in self.show_elements:178            Ot_pred_max = max(map(lambda model: model.P_Ot_pred.max(), self.models))179            Ot_pred_min = min(map(lambda model: model.P_Ot_pred.min(), self.models))180        if 'corr' in self.show_elements:181            Ot_max = max(map(lambda model: model.P_Ot.max(), self.models))182            Ot_min = min(map(lambda model: model.P_Ot.min(), self.models))183        for i, model in enumerate(self.models):184            for j, element in enumerate(self.show_elements):185                if element == 'pred' or element == 'corr':186                    if element == 'pred':187                        Ot, max_, min_ = model.P_Ot_pred, Ot_pred_max, Ot_pred_min188                        ap = model.calc_average_precision(evaluate_prediction=True)189                    else:190                        Ot, max_, min_ = model.P_Ot, Ot_max, Ot_min191                        ap = model.calc_average_precision()192                    title = self.element_to_title[element]193                    if self.tracking and self.show_metric:194                        self.plots[i, j].text.set_text(" Aver. Precision: {:.3f}".format(ap))195                    self.plots[i, j].set_axes_data("occupancy_axes", Ot, min_, max_)196                else:197                    Ot = observation198                    if observation is None:199                        Ot = np.zeros_like(self.map)200                    title = 'observation'201                    self.plots[i, j].set_axes_data("map_axes", Ot)202                if self.show_seen:203                    t = self.models[0].t - 1204                    seen = self.models[0].evaluate_loc_at(t)205                    self.plots[i, j].set_axes_data("seen_axes", seen)206                self.plots[i, j].set_title(title)207                self.plots[i, j].refresh_colorbar()208                if self.simulated_data and self.traj_overlay:209                    self.add_traj_overlay()210    def show_occupancies(self):211        if self.show_at is None:212            gap = self.num_steps // (self.num_col-1)213            self.show_at = [i*gap+1 for i in range(self.num_col)]214        for j, plot_t in enumerate(self.show_at):215            while self.models[0].t < plot_t:216                # generate measurement data217                measurement = self.models[0].measurement_at() if self.tracking else None218                for model in self.models:219                    measurement = model.tracking_step(measurement=measurement)220            occupancies = np.array(map(lambda model: model.P_Ot, self.models))221            Ot_max = occupancies.max()222            Ot_min = occupancies.min()223            for i, model in enumerate(self.models):224                if plot_t > 0 and self.tracking and self.show_metric:225                    x_ent = model.calc_cross_entropy()226                    f1_score = model.calc_f1_score()227                    ap = model.calc_average_precision()228                    self.plots[i, j].text.set_text(" Aver. Precision: {:.3f}".format(ap))229                if not self.tracking:230                    self.plots[i, j].set_axes_data("occupancy_axes", occupancies[i], Ot_min, Ot_max)231                else:232                    self.update_custom_element(i, j, Ot_max)233                self.plots[i, j].refresh_colorbar()234                if i == 0:235                    title = 't={}'.format(plot_t)236                    self.plots[i, j].set_title(title)237                if self.tracking and self.traj_overlay:238                    self.add_traj_overlay(i, j, plot_t)239    def update_custom_element(self, row, col, Ot_max):240        t = self.models[0].t - 1241        model = self.models[row]242        plot = self.plots[row, col]243        occupancy_prob = model.P_Ot244        h_max = occupancy_prob.max()/2245        #occupancy_prob = np.where(occupancy_prob>h_max, occupancy_prob, 0)246        ground_truth = model.ground_truth_at(t)247        overlap = np.logical_and(occupancy_prob, ground_truth)248        # if occupany on ground truth location is higher than 0.1,249        # it is not thought as a false negative250        occupancy_temp = np.where(overlap, occupancy_prob, 0)251        #predicted = np.where(occupancy_temp>0.1, 1, 0)252        false_negative = np.where(occupancy_temp>0.1, 0, ground_truth)253        # if model predicts occupancy higher than 0 on ground truth locations,254        # it is thought as a true positive255        true_positive = np.where(overlap, occupancy_prob, 0)256        # if model predicts occupancy higher than 0 on non-ground truth locations,257        # it is thought as a false positive258        false_positive = occupancy_prob.copy()259        false_positive[overlap] = 0260        # only show for occupancies higher than 1/4 highest occupancy261        # h_max = false_positive.max() / 4262        # false_positive = np.where(false_positive>h_max, false_positive, 0)263        plot.set_axes_data("fn_axes", false_negative, 0, 1)264        plot.set_axes_data("tp_axes", true_positive, 0, Ot_max)265        plot.set_axes_data("fp_axes", false_positive, 0, Ot_max)266        plot.set_axes_data("occupancy_axes", np.zeros_like(occupancy_prob))267class VisualizeRealdata(Visualize):268    def __init__(self, models, num_steps, scene, tracking=True, measurement_lost=None,269                 dynamically=False, show_map=True, show_seen=True, show_elements=['obser', 'pred', 'corr'],270                 show_colorbar=True, num_col=5, model_names=None, show_at=None, show_metric=True, **kwargs):271        self.scene = scene272        self.traj_overlay = kwargs.get('traj_overlay', False)273        if self.traj_overlay:274            self.traj = caculate_traj_from_scene(scene)275        super(VisualizeRealdata, self).__init__(models, num_steps, False, tracking,276                                                  measurement_lost, dynamically, show_map, show_seen,277                                                  show_elements, show_colorbar, num_col, model_names,278                                                  show_at, show_metric, **kwargs)279    def initialize_models(self):280        map(lambda model: model.initialize(self.scene), self.models)281    def add_traj_overlay(self, i, j, t):282        """ Add trajectory lines on plots. """283        plot = self.plots[i, j]284        line = plot.lines[0]285        small_idx = max(0, t-4)286        big_idx = min(t+4, self.num_steps)287        xs, ys = self.traj.T[0][small_idx:big_idx], self.traj.T[1][small_idx:big_idx]288        line.set_data(xs, ys)289class VisualizeSimulation(Visualize):290    def __init__(self, models, num_steps, tracking=True, measurement_lost=None, num_targets=1,291                 dynamically=False, show_map=True, show_elements=['obser', 'pred', 'corr'],292                 show_colorbar=True, num_col=5, model_names=None, diagonal=False, show_at=None,293                 show_metric=True, **kwargs):294        """295        :param models: list296            models to be visualized.297        :param num_steps: int298            number of time steps.299        :param dynamically: bool300            show propagation per time step or show all time steps at once301        :param kwargs:302            show_condition_probs : bool303             if True, show per time step with plots with quiver overlay. This304             option only has effect when dynamically is set to true.305            show_map : bool306                 show map overlay. Default is True.307            num_plot : int308                 number of plots for each propagation model.309            traj_overlay : bool310                 if True, show the sampled trajectory along with propagation.311            init_loc : list312                 a list of coordinate [int, int] of initial locations.313            init_move : list314                 a list of initial movements. Movement could be one of "UP", "DOWN", "LEFT", "RIGHT".315                 Note if init_move or init_loc is not provided, then trajectory316                 is sampled from the map and its initial state is used.317            model_names : list318                 list of model names.319        """320        self.num_targets = num_targets321        self.diagonal = diagonal322        self.current_speed = np.ones((self.num_targets), dtype=int)323        self.steps = np.zeros((self.num_targets), dtype=int)324        self.init_moves = None325        self.kwargs = kwargs326        self.traj_overlay = True327        if 'traj_overlay' in kwargs:328            self.traj_overlay = kwargs['traj_overlay']329        if 'init_locs' in kwargs and 'init_moves' in kwargs:330            tracking = False331            self.traj_overlay = False332        super(VisualizeSimulation, self).__init__(models, num_steps, True, tracking,333                                                  measurement_lost, dynamically, show_map, False,334                                                  show_elements, show_colorbar, num_col, model_names,335                                                  show_at, show_metric, **kwargs)336    def initialize_models(self):337        kwargs = self.kwargs338        if 'init_locs' in kwargs and 'init_moves' in kwargs:339            self.num_targets = len(kwargs['init_locs'])340            Vt0, Ot0 = self.get_initial_state(from_traj=False,341                                                        init_locs=kwargs['init_locs'],342                                                        init_moves=kwargs['init_moves'])343        else:344            self.distances, self.trajs = self.models[0].initialize(self.num_targets, self.num_steps, diagonal=self.diagonal)345            Vt0, Ot0 = self.get_initial_state(from_traj=True)346        for model in self.models:347            if not self.tracking:348                model.initialize(self.num_targets, self.num_steps,349                                 P_Vt=Vt0, P_Ot=Ot0)350            else:351                model.initialize(self.num_targets, self.num_steps,352                                 distances=self.distances, trajectories=self.trajs)353    def _words_to_idx(self, direction):354        """ Transform words of directions to array indices of Vt. """355        extent = self.extent356        idx = np.array([extent // 2, extent // 2])357        for word in direction.split('_'):358            idx += word_to_vel[word]359        idx = np.where(idx >= 0, idx, 0)360        idx = np.where(idx <= extent-1, idx, extent-1)361        return list(idx)362    def _locs_to_idx(self, from_loc, to_loc):363        """ Transform velocity to array indices of Vt. """364        extent = self.extent365        vel_x = to_loc[0] - from_loc[0]366        vel_y = to_loc[1] - from_loc[1]367        vel = np.array([vel_x, vel_y])368        center_idx = np.array([extent // 2, extent // 2])369        return center_idx + vel370    def get_initial_state(self, from_traj, **kwargs):371        Vt0 = np.zeros_like(self.models[0].P_Vt)372        Ot0 = np.zeros_like(self.models[0].P_Ot)373        if not from_traj:374            self.init_moves = kwargs['init_moves']375            init_locs = kwargs['init_locs']376            # indices of initial movements377            mv_idxs = map(self._words_to_idx, kwargs['init_moves'])378        else:379            init_locs = map(lambda traj: traj[0], self.trajs)380            next_locs = map(lambda traj: traj[1], self.trajs)381            mv_idxs = map(self._locs_to_idx, init_locs, next_locs)382        # indices of initial locations383        idxs = np.array(init_locs).T.tolist()384        # occupancy is 1 at init_locs385        Ot0[idxs] = 1.0386        # put locations and movements together387        v_idxs = map(lambda loc, mv_ix: np.concatenate((loc, mv_ix)), init_locs, mv_idxs)388        v_idxs = np.array(v_idxs).T.tolist()389        Vt0[v_idxs] = 1.0390        return Vt0, Ot0391    # def init_plot_contents(self):392    #     """ Decide plot contents for every plot."""393    #     colorbar_dict = {'pred': 'occupancy', 'obser': 'map', 'corr': 'occupancy'}394    #     for i in range(self.num_models):395    #         for j in range(self.num_col):396    #397    #             if not self.tracking:398    #                 colorbar_on = 'occupancy'399    #             else:400    #                 colorbar_on = colorbar_dict[self.show_elements[j]]401    #402    #             self.plots[i, j] = Plot(self.axes[i ,j], self.map, self.res,403    #                                    colorbar_on=colorbar_on,404    #                                    plot_map=self.show_map,405    #                                    title='')406    #             if j == 0:407    #                 self.plots[i, j].set_ylabel(self.model_names[i])408    #409    #             if self.traj_overlay:410    #                 self.plots[i, j].add_traj_line(num_targets=self.num_targets)411    #     # add title to figure412    #     if self.init_moves is not None:413    #         self.fig.suptitle("Initial movements = {}".format(str(self.init_moves)))414    def add_traj_overlay(self, i=None, j=None, t=None):415        """ Add trajectory lines on plots. """416        if t is None:417            t = self.models[0].t - 1418        if t >= 0:419            truncated_trajs = self.models[0].traversed_traj_at()420            if i is not None and j is not None:421                plot = self.plots[i, j]422                for idx, line in enumerate(plot.lines):423                    xs, ys = truncated_trajs[idx].T[0][-5:], truncated_trajs[idx].T[1][-5:]424                    line.set_data(xs, ys)425            else:426                for plot in self.plots.flatten():427                    for idx, line in enumerate(plot.lines):428                        xs, ys = truncated_trajs[idx].T[0][-5:], truncated_trajs[idx].T[1][-5:]429                        line.set_data(xs, ys)430    def show_dynamically_with_condition_probs(self, show_map=True):431        model = None432        for model in self.models:433            if model.__class__.__name__ == 'conditionalPropagateModel':434                model = model435                break436        res = map_resolution437        trans_prob = model.conditional_probs438        fig, axes_ = plt.subplots(2, 2, sharex='all', sharey='all', figsize=(10, 10))439        for i in range(4):440            plot = plt.subplot(2, 2, i + 1)441            probs = np.zeros_like(trans_prob)442            probs[i, ...] = trans_prob[i, ...]443            plot_grid_map_hmm(probs, 'probs', grid_res=res, map_=None, map_res=res)444            directions = {0: 'UP', 1: 'RIGHT', 2: 'DOWN', 3: 'LEFT'}445            if not show_map:446                show_walls(model.P_Ot, resolution=res, cmap='OrRd')447            else:448                show_walls(model.P_Ot, resolution=res, cmap='OrRd', zorder=1)449                show_walls(model.map, resolution=res)...

15_queues.py

Source:15_queues.py

...3import threading4import queue5from time import sleep6logging.basicConfig(level=logging.DEBUG, format=THREAD_FORMAT)7def show_elements(queue: queue.Queue) -> None:8    while not queue.empty():9        item = queue.get()10        info(f"The element is: {item}")11        queue.task_done()12        sleep(0.5)13if __name__ == "__main__":14    my_queue = queue.Queue() # FIFO15    for val in range(20):16        my_queue.put(val)17    info("Queue already has elements!")18    for _ in range(4):...

main.py

Source:main.py

...3DLL.append(5)4DLL.append(10)5DLL.append(15)6print('\nLista inicial: ')7DLL.show_elements()8print(f'\nValor insertado: {DLL.insert(3,21)} ')9DLL.show_elements()10print(f'\nValor eliminado: {DLL.delete(2)}')11DLL.show_elements()12print('\nLista invertida')13DLL.reverse()14DLL.show_elements()15print('\nLista invertida y elevar al cuadrado')16DLL.reverse_and_pow()...

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