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How to use draw method in hypothesis

Best Python code snippet using hypothesis

team_draw_analysis.py

Source:team_draw_analysis.py

1from ._data_organizer import _DataOrganizer, pd, plt2from .utils.validation import (3    seasons_arg_validation,4    teams_arg_validation,5    plot_type_arg_validation,6    draw_results_plot_arg_validation,7    draw_series_arg_validation8)9class TeamDrawAnalysis(_DataOrganizer):10    """TeamDrawAnalysis class provides and visualizes draw results performance for teams.11        'Attributes'12        ------------13            rawdata (pd.DataFrame): provided raw fixtures data.14            fixtures_data (pd.DataFrame): automatically cleaned and optimized data from raw data fixtures.15            seasons (list): calculated league seasons from 'fixtures data'.16            teams (list): league teams from 'fixtures data'.17            draw_score (float): total draw score.18    """19    def __init__(self, rawdata):20        super().__init__(rawdata)21    def __calculate_teams_no_draw_series(self, series_type):22        """Method to calculate no draw/draw series for teams. Based on 'fixtures_data'.23            Parameters24            ----------25            series_type (int): 0 - for no draw series, 1 - draw series.26            Returns27            ----------28            pd.DataFrame: concatenated no draw/draw series of matches for teams.29        """30        pd.options.mode.chained_assignment = None31        # data optimizing32        fixtures_data = self.fixtures_data.copy()33        fixtures_data = fixtures_data[34            ['fixture_date', 'league_season', 'teams_home_name', 'teams_away_name', 'match_result']]35        fixtures_data['fixture_date'] = pd.to_datetime(fixtures_data['fixture_date']).dt.strftime('%Y-%m-%d')36        fixtures_data.sort_values(by='fixture_date', inplace=True)37        teams_list = self.teams38        def calucate_series_for_team(_fixtures_data, _teams_list, _series_type):39            """Group and calculate no draw/draw series for teams.40            Parameters41            ----------42            fixtures_data (pd.DataFrame): optimized attribute 'fixtures_data'.43            teams_list (list): list of available 'fixtures_data' teams.44            series_type (int): 0 - for no draw series, 1 - draw series.45            Returns46            ----------47            list: list of pd.DataFrame with calculated draw/no draw series by teams.48            """49            _teams_series_to_concat_list = []50            # add auxiliary column for no draw/draw series51            if series_type == 0:52                fixtures_data['aux_result'] = fixtures_data['match_result'].apply(lambda x: 0 if x == 0 else 1)53            elif series_type == 1:54                fixtures_data['aux_result'] = fixtures_data['match_result'].apply(lambda x: 1 if x == 0 else 0)55            for team in teams_list:56                team_filter = fixtures_data[57                    (fixtures_data['teams_home_name'] == team) | (fixtures_data['teams_away_name'] == team)]58                team_filter['series_without_draw'] = team_filter.groupby(team_filter['aux_result'].eq(0).cumsum())[59                    'aux_result'].cumsum()60                team_filter['from_to_date'] = ''61                for a in range(0, len(team_filter)):62                    if team_filter.iloc[a, 6] != 0:63                        try:64                            if team_filter.iloc[a + 1, 6] == 0:65                                if a - team_filter.iloc[a, 6] < 0:66                                    team_filter.iloc[a, 7] = 'NoData' + '__' + str(team_filter.iloc[a + 1, 0])67                                else:68                                    team_filter.iloc[a, 7] = str(69                                        team_filter.iloc[a - team_filter.iloc[a, 6] + 1, 0]) + '__' + str(70                                        team_filter.iloc[a + 1, 0])71                        except IndexError:72                            if a + 1 == len(team_filter):73                                if a - team_filter.iloc[a, 6] < 0:74                                    team_filter.iloc[a, 7] = 'NoData__' + 'ToDate'75                                else:76                                    team_filter.iloc[a, 7] = str(77                                        team_filter.iloc[a - team_filter.iloc[a, 6] + 1, 0]) + '__ToDate'78                            else:79                                team_filter.iloc[a, 7] = 'NoData__' + str(80                                    team_filter.iloc[a - team_filter.iloc[a, 6], 0])81                team_second_filter = team_filter[team_filter['from_to_date'] > '']82                _team_series = pd.DataFrame(index=range(0, len(team_second_filter)),83                                            data={'team_name': team,84                                                  'league_season': team_second_filter['league_season'].to_list(),85                                                  'series_without_draw': team_second_filter[86                                                      'series_without_draw'].to_list(),87                                                  'from_to_date': team_second_filter['from_to_date'].to_list()})88                _team_series.sort_values(by='series_without_draw', ascending=False, inplace=True)89                _teams_series_to_concat_list.append(_team_series)90            return _teams_series_to_concat_list91        teams_series_to_concat_list = calucate_series_for_team(fixtures_data, teams_list, series_type)92        team_series = pd.concat(teams_series_to_concat_list, ignore_index=True)93        return team_series94    def __draw_results_data_filter(self, seasons):95        """Auxiliry method for 'draw_results_by_team_plot'. Filter attribute 'teams_draw_results_summarize' for plot.96        """97        teams_draw_results = TeamDrawAnalysis.teams_draw_results_summarize(self)98        if seasons == 'total':99            draw_results_filtered = teams_draw_results.iloc[:, -3:]100            draw_results_sorted = draw_results_filtered.sort_values(draw_results_filtered.columns[0], ascending=False)101            return draw_results_sorted102        elif isinstance(seasons, int):103            columns_to_filter = []104            for column in teams_draw_results.columns:105                if str(seasons) in column:106                    columns_to_filter.append(column)107            draw_results_filtered = teams_draw_results[columns_to_filter]108            draw_results_sorted = draw_results_filtered.sort_values(draw_results_filtered.columns[0], ascending=False)109            return draw_results_sorted110    def __team_draw_results_plot(self, _team_draw_results, plot_type, top, _seasons):111        """Auxiliry method for 'draw_results_by_team_plot' public method. Draw bar plot based on attribute112           'teams_draw_results_summarize'.113        Parameters114        ----------115        team_draw_results(pd.DataFrame): argument provided by public method - 'draw_results_by_team_plot'.116        plot_type (str): results number - 'rslts_num', percentage share of draw results - 'pcts'.117        seasons(str,int): provided and validated season.118        top (int): top (positive) or last (negative) of teams to ilustrate.119        Returns120        ----------121        matplotlib.pyplot.bar: bar plot number/percentage share of draw results.122        """123        plot_type_arg_validation(plot_type)124        #125        def draw_results_number_plot(_team_draw_results, _seasons, ytick_step):126            """Plot bar chart for plot_type = 'rslts_num'.127            """128            _draw_results_number_plot = _team_draw_results[129                [_team_draw_results.columns[0], 'total_matches_aux_col']].plot(130                kind='bar', color=self._graph_colors[0::2], alpha=0.8, stacked=True, yticks=ytick_setter,131                rot=80,132                title=f"Number of draws to the total results - {_seasons}")133            pcts_line = _team_draw_results[_team_draw_results.columns[-1]].plot(secondary_y=True, rot=80,134                                                                                color='tab:olive', legend=True)135            _draw_results_number_plot.legend(['draw_results_num', 'total_matches_num'], loc='center left',136                                             bbox_to_anchor=(1.07, 0.93))137            pcts_line.legend(loc='center left', bbox_to_anchor=(1.07, 0.844))138            plt.show()139        def draw_pcts_to_total_plot(_team_draw_results, _seasons, ytick_step):140            """Plot bar chart for plot_type='pcts'141            """142            _draw_pcts_to_total_plot = _team_draw_results[_team_draw_results.columns[-1]] \143                .plot(kind='bar',144                      yticks=ytick_setter, rot=80,145                      ylabel='%',146                      color=_DataOrganizer._graph_colors[2],147                      legend=True,148                      title=f"Draws percentage share to the total results - {_seasons}")149            plt.show()150        if plot_type == 'count':151            ytick_setter = self._yticks_plot_auto_setter(_team_draw_results[_team_draw_results.columns[1]] + 5)152            _team_draw_results.insert(2, column='total_matches_aux_col',153                                      value=_team_draw_results[_team_draw_results.columns[1]] - _team_draw_results[154                                          _team_draw_results.columns[0]])155            if top > 0:156                _team_draw_results = _team_draw_results.head(top)157                return draw_results_number_plot(_team_draw_results, _seasons, ytick_setter)158            else:159                _team_draw_results = _team_draw_results.tail(abs(top))160                return draw_results_number_plot(_team_draw_results, _seasons, ytick_setter)161        elif plot_type == 'pcts':162            ytick_setter = self._yticks_plot_auto_setter(163                _team_draw_results[_team_draw_results.columns[-1]] + 5)164            _team_draw_results = _team_draw_results.sort_values(_team_draw_results.columns[-1], ascending=False)165            if top > 0:166                _team_draw_results = _team_draw_results.head(top)167                return draw_pcts_to_total_plot(_team_draw_results, _seasons, ytick_setter)168            else:169                _team_draw_results = _team_draw_results.tail(abs(top))170                return draw_pcts_to_total_plot(_team_draw_results, _seasons, ytick_setter)171    def __calculate_draw_performance(self):172        """Calculate draw results performance for all teams and seasons by merging:173            - draws percentage share (TeamDrawAnalysis.teams_draw_results_summarize())174            - team table position (self.league_table())175            - no draw series max/mean per season/total (self.teams_draw_series())176            - draw series max/mean per season/total (self.teams_draw_series())177            Returns178            ----------179            pandas.DataFrame: draw results performance.180        """181        # 1. Filter columns from 'teams_draw_results_summarize' attribute182        # - columns to filter183        draw_pcts_col_list = []184        teams_draw_results_summarize = TeamDrawAnalysis.teams_draw_results_summarize(self)185        # - add draw pcts results per seasons to draw_pcts_col_list186        for season in self._seasons:187            for col in teams_draw_results_summarize.columns.to_list():188                if 'pcts_' + str(season) in col and 'match_num' not in col:189                    draw_pcts_col_list.append(col)190                if len(self.seasons) > 1:191                    if season == self.seasons[-1] and 'pcts_total' in col:192                        draw_pcts_col_list.append(col)193        # - filter194        draw_results_performance = teams_draw_results_summarize.copy()195        draw_results_performance = draw_results_performance[draw_pcts_col_list]196        # 2. Teams position in table from197        table_pos_col_list = []198        for season in self._seasons:199            table_position = self.league_table(season)['Team'].to_frame()200            table_position['table_pos_' + str(season)] = table_position.index201            table_position.set_index('Team', inplace=True)202            table_pos_col_list.append(table_position.columns[0])203            draw_results_performance = draw_results_performance.merge(table_position, how='left', left_index=True,204                                                                      right_index=True)205        # 3. New columns order - teams table positions and draw pcts results206        new_columns_order_list = []207        for col in zip(table_pos_col_list, draw_pcts_col_list):208            new_columns_order_list.append(col[0])209            new_columns_order_list.append(col[1])210        # add total draw pcts results column if len(seasons) > 1211        if len(self._seasons) > 1:212            new_columns_order_list.append(draw_pcts_col_list[-1])213        # draw_results_performance new column order if len(seasons) > 1214        draw_results_performance = draw_results_performance[new_columns_order_list]215        # 5. Draw/no draw series216        def merge_draw_performance_with_draw_series(_draw_results_performance, series_type):217            """Calculate max/mean, no draw/draw series for teams and merge with 'draw_results_performance'218            Parameters219            ----------220            draw_results_performance (padnas.DataFrame): organized DF with teams positions and draws percentage share221            series_type (int): 0 - series without draw, 1 - draw series.222            Returns223            ----------224            pandas.DataFrame: merged draw_results_performance with draw/no draws series.225            """226            no_draw_series_dataframe_list = []227            # mapper to change the column name for draw/ no draw series228            series_type_mapper = {0: 'no_draw_', 1: 'draw_'}229            # no draw/draw series - max, mean per seasons230            for _season in self._seasons:231                no_draw_series_max_season = self.teams_draw_series(seasons=_season,232                                                                   series_type=series_type,233                                                                   func='max').iloc[:, 1].to_frame()234                no_draw_series_max_season.rename(235                    {no_draw_series_max_season.columns[0]: series_type_mapper[series_type] + 'max_' + str(_season)},236                    axis=1, inplace=True)237                no_draw_series_mean_season = self.teams_draw_series(seasons=_season,238                                                                    series_type=series_type,239                                                                    func='mean').iloc[:, 0].to_frame()240                no_draw_series_mean_season.rename(241                    {no_draw_series_mean_season.columns[0]: series_type_mapper[series_type] + 'mean_' + str(_season)},242                    axis=1, inplace=True)243                no_draw_series_dataframe_list.append(no_draw_series_max_season)244                no_draw_series_dataframe_list.append(no_draw_series_mean_season)245            # no draw/draw total from data246            if len(self._seasons) > 1:247                no_draw_series_max_total = self.teams_draw_series(seasons='all', series_type=series_type,248                                                                  func='max').iloc[:, 1].to_frame()249                no_draw_series_max_total.rename(250                    {no_draw_series_max_total.columns[0]: series_type_mapper[series_type] + 'max_total'}, axis=1,251                    inplace=True)252                no_draw_series_mean_total = self.teams_draw_series(seasons='all', series_type=series_type,253                                                                   func='mean').iloc[:, 0].to_frame()254                no_draw_series_mean_total.rename(255                    {no_draw_series_mean_total.columns[0]: series_type_mapper[series_type] + 'mean_total'}, axis=1,256                    inplace=True)257                no_draw_series_dataframe_list.append(no_draw_series_max_total)258                no_draw_series_dataframe_list.append(no_draw_series_mean_total)259            # merge no draw/draw series with 'draw_results_performance'260            for df in no_draw_series_dataframe_list:261                _draw_results_performance = _draw_results_performance.merge(df, how='left', left_index=True,262                                                                            right_index=True)263            return _draw_results_performance264        # 6. Merge draw_results_performance with draw/no draw series265        draw_results_performance = merge_draw_performance_with_draw_series(draw_results_performance, series_type=0)266        draw_results_performance = merge_draw_performance_with_draw_series(draw_results_performance, series_type=1)267        # 7.Fill Nan values and change columns type:268        draw_results_performance.fillna(0, inplace=True)269        for col in draw_results_performance.columns:270            if 'table_pos' in col or 'max' in col:271                draw_results_performance[col] = draw_results_performance[col].astype('int64')272        # 8. Goals performance273        teams_goals_performance_season = TeamDrawAnalysis.teams_goals_performance(self, seasons='all', teams='all')274        draw_results_performance = draw_results_performance.merge(teams_goals_performance_season, how='left',275                                                                  left_index=True, right_index=True)276        return draw_results_performance277    def __transpose_draw_performance_table(self, draw_performance_filtered_teams, seasons):278        """Auxiliary method for draw_results_performance_filter.279           Transpose table to multiindex teams and seasons.280            Parameters281            ----------282            draw_performance_filtered_teams(pandas.DataFrame): filtered draw performance table.283            Returns284            ----------285            pandas.DataFrame: transposed table.286        """287        seasons_list = []288        if seasons == 'all':289            seasons_list = self._seasons290        elif isinstance(seasons, int):291            seasons_list = [seasons]292        else:293            seasons_list = seasons294        # df list to further concatenation295        df_list = []296        # cerate df for seasons with unified columns297        for season in seasons_list:298            # columns for particular season299            columns_list = []300            # new unified columns names301            new_columns_name = []302            for column in draw_performance_filtered_teams.columns:303                if str(season) in column:304                    columns_list.append(column)305                    new_columns_name.append(column[0:column.rfind('_')])306            df_filtered = draw_performance_filtered_teams[columns_list]307            df_filtered.columns = new_columns_name308            # add multi column with season number309            df_filtered = pd.concat([df_filtered], axis=1, keys=[str(season)])310            df_list.append(df_filtered)311            # concatenation and transpose312        df_concat = pd.concat(df_list, axis=1)313        transposed = df_concat.stack(level=0)314        transposed.index.set_names(['team_name', 'league_season'], inplace=True)315        transposed = transposed[316            ['table_pos', 'draws_pcts', 'no_draw_max', 'no_draw_mean', 'draw_max', 'draw_mean', 'goals_mean',317             'goals_diff']]318        # drop indexesr with 0 values319        index_with_no_data = transposed[transposed[transposed.columns] == 0].dropna().index320        transposed.drop(index_with_no_data, inplace=True)321        return transposed322    def __draw_results_seasons_filter(self, seasons):323        draw_performance = TeamDrawAnalysis.__calculate_draw_performance(self)324        columns_to_filter = []325        draw_performance_filtered = None326        if len(self._seasons) == 1:327            for column in draw_performance.columns:328                if str(*self._seasons) in column:329                    columns_to_filter.append(column)330            draw_performance_filtered = draw_performance[columns_to_filter]331            draw_performance_filtered = draw_performance_filtered[332                draw_performance_filtered[draw_performance_filtered.columns[0]] > 0]333        elif isinstance(seasons, list):334            for season in seasons:335                for column in draw_performance.columns:336                    if str(season) in column:337                        columns_to_filter.append(column)338            draw_performance_filtered = draw_performance[columns_to_filter]339        elif isinstance(seasons, int):340            for column in draw_performance.columns:341                if str(seasons) in column:342                    columns_to_filter.append(column)343            draw_performance_filtered = draw_performance[columns_to_filter]344            draw_performance_filtered = draw_performance_filtered[345                draw_performance_filtered[draw_performance_filtered.columns[0]] > 0]346        else:347            draw_performance_filtered = draw_performance348        return draw_performance_filtered349    def teams_draw_results_summarize(self):350        """Group 'fixtures_data' to calculate number of draws, number of total matches and percentage share of draw351           results by teams.352            Returns353            ----------354                pd.DataFame: teams_draw_results_summarize.355        """356        def team_draw_results_count(_fixtures_data, _season):357            # group and count 0,1,2 results by team358            teams_home_rslts = \359                _fixtures_data.groupby(by=['league_season', 'teams_home_name', 'match_result']).agg('count')[360                    'fixture_id']361            teams_away_rslts = \362                _fixtures_data.groupby(by=['league_season', 'teams_away_name', 'match_result']).agg('count')[363                    'fixture_id']364            # combine teams_home_rslts and teams_away_rslts365            teams_results = teams_home_rslts.append(teams_away_rslts)366            # group and agg sum teams_home_rslts and teams_away_rslts367            teams_results_total = teams_results.groupby(by=['teams_home_name', 'match_result']).agg('sum')368            teams_results_total.index.set_names(names=['team_name', 'match_result'], inplace=True)369            # draw count processing370            team_draw_counted = teams_results_total.unstack()[0].to_frame()371            team_draw_counted.columns = ['draws_' + str(_season)]372            draws_number = team_draw_counted[team_draw_counted.columns[0]]373            # total matches count374            teams_total_matches = teams_results_total.groupby('team_name').agg('sum')375            # combine and calculate percentage share of draws376            if isinstance(_season, int):377                team_draw_counted['match_num_' + str(_season)] = teams_total_matches378                total_matches_number = team_draw_counted[team_draw_counted.columns[1]]379                team_draw_counted['draws_pcts_' + str(_season) + '(%)'] = round(380                    draws_number / total_matches_number * 100, 2)381            else:382                team_draw_counted['match_num_' + str(_season)] = teams_total_matches383                total_matches_number = team_draw_counted[team_draw_counted.columns[1]]384                team_draw_counted['draws_pcts_' + str(_season) + '(%)'] = round(385                    draws_number / total_matches_number * 100, 2)386            return team_draw_counted387        fixtures_data = self._fixtures_data.copy()388        seasons_list = self._seasons389        teams_draw_results_merged = pd.DataFrame()390        for season in seasons_list:391            fixtures_data_filtered = fixtures_data[fixtures_data['league_season'] == season]392            teams_draw_counted = team_draw_results_count(fixtures_data_filtered, season)393            if teams_draw_results_merged.empty:394                teams_draw_results_merged = teams_draw_results_merged.append(teams_draw_counted)395            else:396                teams_draw_results_merged = teams_draw_results_merged.merge(teams_draw_counted, left_index=True,397                                                                            right_index=True, how='outer')398        if len(seasons_list) > 1:399            teams_draw_total = team_draw_results_count(fixtures_data, 'total')400            teams_draw_results_merged = teams_draw_results_merged.merge(teams_draw_total, left_index=True,401                                                                        right_index=True, how='outer')402            teams_draw_results_merged.fillna(value=0, inplace=True)403        else:404            teams_draw_results_merged.fillna(value=0, inplace=True)405        return teams_draw_results_merged406    def draw_results_by_team_plot(self, plot_type='count', seasons='total', top=15):407        """Bar plot for draw results by team.408            Parameters409            ----------410            plot_type (str): type of bar plot - 'count' or 'pcts'.411            seasons(str,int): league season to plot. Deafult - 'total' data.412            top (int): top (positive) or last (negative) of teams to ilustrate.413            Raises414            ----------415                TypeError: Seasons argument must be int or str type.416                ValueError: Season does not exist.417                ValueError: Incorrect string value. Seasons must be int or 'total' for total data calculation.418                ValueError: Incorrect string value. The plot_type argument must be named 'rslts_num' or 'pcts'.419                TypeError: The 'plot_type' argument must be str type.420                TypeError: The 'top' argument must be int type.421            Returns422            ----------423            matplotlib.pyplot.bar: bar plot number/percentage share of draw results by team.424        """425        draw_results_plot_arg_validation(self, seasons, plot_type, top)426        team_draw_results = TeamDrawAnalysis.__draw_results_data_filter(self, seasons)427        TeamDrawAnalysis.__team_draw_results_plot(self, team_draw_results, plot_type, top, seasons)428    def teams_draw_series(self, series_type=0, seasons='all', teams='all', func='all'):429        """Calculate no draw/ draw results series for teams.430            Parameters431            ----------432            series_type (int): 0 - series without draw, 1 - draw series.433            seasons (int or list): Default - 'all' leauge seasons. Int or list of ints of league seasons for request.434            teams (str or list): Default 'all' - teams series, 'str' name for single team or list(str) of team names for435                                 request.436            func (str): Default 'all' - all teams series, 'max' - the longest series, 'mean' - average value of series.437            Raises438            ----------439                TypeError: 'series_type' argument must be int.440                ValueError: the value of 'series_type' argument must be 0 or 1.441                TypeError: 'seasons' argument must be integer, list of integers or 'all' string for all seasons.442                ValueError: Season does not exist.443                ValueError: one or more of seasons do not exists.444                ValueError: incorrect string value. 'Seasons' must be int, list of ints, 'all' for all seasons.445                TypeError: 'teams' argument must be string, list of strings.446                ValueError: team does not exist.447                ValueError: one or more of teams do not exists.448                TypeError: 'func' argument must be string type.449                ValueError: 'func' argument must be 'all', 'max' or 'mean'.450            Returns451            ----------452                pandas.DataFrame: filtered no draw/draw series for teams.453        """454        # arguments validation455        draw_series_arg_validation(self, series_type, seasons, teams, func)456        # 0 - no draw series, 1 - draw series457        if series_type == 0:458            draw_series = TeamDrawAnalysis.__calculate_teams_no_draw_series(self, series_type=0)459        else:460            draw_series = TeamDrawAnalysis.__calculate_teams_no_draw_series(self, series_type=1)461        # seasons filter462        if seasons == 'all':463            pass464        elif isinstance(seasons, list):465            draw_series = draw_series[draw_series['league_season'].isin(seasons)]466        else:467            draw_series = draw_series[draw_series['league_season'] == seasons]468        # teams filter469        if teams == 'all':470            pass471        elif isinstance(teams, list):472            draw_series = draw_series[draw_series['team_name'].isin(teams)]473        else:474            draw_series = draw_series[draw_series['team_name'] == teams]475        # func - 'all', 'max', 'mean'476        if func == 'max':477            max_rows = draw_series.groupby('team_name')['series_without_draw'].idxmax(axis=0).to_list()478            draw_series = draw_series.loc[max_rows]479        elif func == 'mean':480            draw_series = draw_series.groupby('team_name', as_index=False)['series_without_draw'].mean()481            draw_series['series_without_draw'] = round(draw_series['series_without_draw'], 2)482        draw_series.set_index('team_name', inplace=True)483        if series_type == 0:484            return draw_series485        elif series_type == 1:486            draw_series.rename({'series_without_draw': 'draw_series'}, axis=1, inplace=True)487            return draw_series488    def draw_results_performance(self, seasons='all', teams='all', transpose=False):489        """Calculate draw results performance.490            Parameters491            ----------492            seasons (int or list): Default - 'all' leauge seasons. Int or list of ints of league seasons for request.493            teams (str or list): Default 'all' - teams series, 'str' name for single team or list(str) of team names for494                                 request.495            transpose (bool): True to transpose table. Deafult = False.496            Raises497            ----------498                TypeError: 'seasons' argument must be integer, list of integers or 'all' string for all seasons.499                ValueError: Season does not exist.500                ValueError: one or more of seasons do not exists.501                ValueError: incorrect string value. 'Seasons' must be int, list of ints, 'all' for all seasons.502                TypeError: 'teams' argument must be string, list of strings.503                ValueError: team does not exist.504                ValueError: one or more of teams do not exists.505                TypeError: 'transpose' argument must be bool.506            Returns507            ----------508            pandas.DataFrame: filtered attribute draw_results_performance509        """510        # arg validation:511        seasons_arg_validation(self, seasons)512        teams_arg_validation(self, teams)513        if not isinstance(transpose, bool):514            raise TypeError(f"The 'transpose' argument must be bool, not {type(transpose).__name__} type.")515        draw_performance_filtered = self.__draw_results_seasons_filter(seasons)516        # teams filter517        if teams == 'all':518            draw_performance_filtered_teams = draw_performance_filtered519        elif isinstance(teams, str):520            draw_performance_filtered_teams = draw_performance_filtered.loc[teams].to_frame().transpose()521        else:522            draw_performance_filtered_teams = draw_performance_filtered.loc[teams]523        # transpose table524        if transpose is True:525            draw_performance_transposed = self.__transpose_draw_performance_table(draw_performance_filtered_teams,526                                                                                  seasons)527            return draw_performance_transposed528        else:529            return draw_performance_filtered_teams530    def teams_correct_scores(self, seasons='all', teams='all'):531        """Calculate counted of teams correct scores by seasons.532            Parameters533            ----------534            seasons (int or list): Default - 'all' leauge seasons. Int or list of ints of league seasons for request.535            teams (str or list): Default 'all' - teams series, 'str' name for single team or list(str) of team names for536                                 request.537            Raises538            ----------539                TypeError: 'seasons' argument must be integer, list of integers or 'all' string for all seasons.540                ValueError: Season does not exist.541                ValueError: one or more of seasons do not exists.542                ValueError: incorrect string value. 'Seasons' must be int, list of ints, 'all' for all seasons.543                TypeError: 'teams' argument must be string, list of strings.544                ValueError: team does not exist.545                ValueError: one or more of teams do not exists.546            Returns547            ----------548            pandas.DataFrame: counted correct scores by teams.549        """550        # arg validation and seasons, teams filter551        fixtures_data = self._fixtures_data.copy()552        fixtures_data_filtered_seasons = self._seasons_filter(fixtures_data, seasons)553        fixtures_data_filtered_teams = self._teams_filter(fixtures_data_filtered_seasons, teams)554        # teams home correct scores555        home_scores = \556            fixtures_data_filtered_teams.groupby(['teams_home_name', 'league_season', 'fulltime_match_result']).agg(557                'count')['fixture_id'].to_frame()558        home_scores.rename(columns={'fixture_id': 'home_scores'}, inplace=True)559        # teams away correct scores560        away_scores = \561            fixtures_data_filtered_teams.groupby(['teams_away_name', 'league_season', 'fulltime_match_result']).agg(562                'count')['fixture_id'].to_frame()563        # merge564        teams_coorect_scores = home_scores.copy()565        teams_coorect_scores['away_scores'] = away_scores['fixture_id']566        # drop index == 0567        index_with_no_data = teams_coorect_scores[568            teams_coorect_scores[teams_coorect_scores.columns] == 0].dropna().index569        teams_coorect_scores.drop(index_with_no_data, inplace=True)570        # detailed team filter571        if isinstance(teams, str) and not teams == 'all':572            teams_coorect_scores = teams_coorect_scores.loc[teams]573        return teams_coorect_scores574    def standings_draws(self):575        """Calculate compilation of positions in table and draws results.576            Returns577            ---------578            pd.DataFrame: league table with positions and counted draws by seasons.579        """580        df_list = []581        for season in self._seasons:582            df_list.append(self.league_table(season=season)['D'])583        draws_table = pd.DataFrame(index=df_list[0].index,584                                   data={str(season): df for df, season in zip(df_list, self._seasons)})585        return draws_table586    def teams_goals_performance(self, seasons='all', teams='all'):587        """Calculate goals mean per match and total goals difference for season.588            Parameters589            ----------590            seasons (int or list): Default - 'all' leauge seasons. Int or list of ints of league seasons for request.591            teams (str or list): Default 'all' - teams series, 'str' name for single team or list(str) of team names for592                                request.593            Raises594            ----------595                TypeError: 'seasons' argument must be integer, list of integers or 'all' string for all seasons.596                ValueError: Season does not exist.597                ValueError: one or more of seasons do not exists.598                ValueError: incorrect string value. 'Seasons' must be int, list of ints, 'all' for all seasons.599                TypeError: 'teams' argument must be string, list of strings.600                ValueError: team does not exist.601                ValueError: one or more of teams do not exists.602            Returns603            ----------604            pandas.DataFrame: teams goals performance.605        """606        # arg validation607        seasons_arg_validation(self, seasons)608        teams_arg_validation(self, teams)609        def teams_goals_mean_and_diff(_season):610            """Calculate goals mean per match and total goals difference for season.611            """612            season_league_table = TeamDrawAnalysis.league_table(self, season=_season)613            season_league_table['goals_mean_' + str(_season)] = round(614                season_league_table.apply(lambda x: (x['GF'] + x['GA']) / x['MP'], 1), 2)615            season_league_table.rename(columns={'GD': 'goals_diff_' + str(_season)}, inplace=True)616            teams_goals = season_league_table[617                ['Team', 'goals_mean_' + str(_season), 'goals_diff_' + str(_season)]]618            teams_goals.set_index('Team', drop=True, inplace=True)619            return teams_goals620        # seasons filter621        seasons_list = []622        if len(self._seasons) > 1:623            if seasons == 'all':624                seasons_list = self._seasons625            else:626                seasons_list = seasons627        team_goals_performance = pd.DataFrame()628        if len(self._seasons) > 1:629            teams_goals_perf_list = []630            team_goals_performance = pd.DataFrame(index=self._teams)631            if seasons == 'all' or isinstance(seasons, list):632                for season in seasons_list:633                    teams_goals_perf_season = teams_goals_mean_and_diff(season)634                    teams_goals_perf_list.append(teams_goals_perf_season)635                for df in teams_goals_perf_list:636                    team_goals_performance = team_goals_performance.merge(df, how='left', left_index=True,637                                                                          right_index=True)638            elif isinstance(seasons, int):639                team_goals_performance = teams_goals_mean_and_diff(seasons)640        elif len(self._seasons) == 1:641            team_goals_performance = teams_goals_mean_and_diff(self._seasons[0])642        # columns type643        team_goals_performance.fillna(value=0, inplace=True)644        for col in team_goals_performance.columns:645            if 'diff' in col:646                team_goals_performance[col] = team_goals_performance[col].astype('int')647        # team filter648        if teams == 'all':649            return team_goals_performance650        else:651            team_goals_performance_filtered = team_goals_performance.loc[teams]...

test_imagedraw.py

Source:test_imagedraw.py

...404            thresh=30)405        # Assert406        self.assert_image_equal(407            im, Image.open("Tests/images/imagedraw_floodfill2.png"))408    def create_base_image_draw(self, size,409                               mode=DEFAULT_MODE,410                               background1=WHITE,411                               background2=GRAY):412        img = Image.new(mode, size, background1)413        for x in range(0, size[0]):414            for y in range(0, size[1]):415                if (x + y) % 2 == 0:416                    img.putpixel((x, y), background2)417        return img, ImageDraw.Draw(img)418    def test_square(self):419        expected = Image.open(os.path.join(IMAGES_PATH, 'square.png'))420        expected.load()421        img, draw = self.create_base_image_draw((10, 10))422        draw.polygon([(2, 2), (2, 7), (7, 7), (7, 2)], BLACK)423        self.assert_image_equal(img, expected,424                                'square as normal polygon failed')425        img, draw = self.create_base_image_draw((10, 10))426        draw.polygon([(7, 7), (7, 2), (2, 2), (2, 7)], BLACK)427        self.assert_image_equal(img, expected,428                                'square as inverted polygon failed')429        img, draw = self.create_base_image_draw((10, 10))430        draw.rectangle((2, 2, 7, 7), BLACK)431        self.assert_image_equal(img, expected,432                                'square as normal rectangle failed')433        img, draw = self.create_base_image_draw((10, 10))434        draw.rectangle((7, 7, 2, 2), BLACK)435        self.assert_image_equal(436            img, expected, 'square as inverted rectangle failed')437    def test_triangle_right(self):438        expected = Image.open(os.path.join(IMAGES_PATH, 'triangle_right.png'))439        expected.load()440        img, draw = self.create_base_image_draw((20, 20))441        draw.polygon([(3, 5), (17, 5), (10, 12)], BLACK)442        self.assert_image_equal(img, expected, 'triangle right failed')443    def test_line_horizontal(self):444        expected = Image.open(os.path.join(IMAGES_PATH,445                              'line_horizontal_w2px_normal.png'))446        expected.load()447        img, draw = self.create_base_image_draw((20, 20))448        draw.line((5, 5, 14, 5), BLACK, 2)449        self.assert_image_equal(450            img, expected, 'line straight horizontal normal 2px wide failed')451        expected = Image.open(os.path.join(IMAGES_PATH,452                              'line_horizontal_w2px_inverted.png'))453        expected.load()454        img, draw = self.create_base_image_draw((20, 20))455        draw.line((14, 5, 5, 5), BLACK, 2)456        self.assert_image_equal(457            img, expected, 'line straight horizontal inverted 2px wide failed')458        expected = Image.open(os.path.join(IMAGES_PATH,459                              'line_horizontal_w3px.png'))460        expected.load()461        img, draw = self.create_base_image_draw((20, 20))462        draw.line((5, 5, 14, 5), BLACK, 3)463        self.assert_image_equal(464            img, expected, 'line straight horizontal normal 3px wide failed')465        img, draw = self.create_base_image_draw((20, 20))466        draw.line((14, 5, 5, 5), BLACK, 3)467        self.assert_image_equal(468            img, expected, 'line straight horizontal inverted 3px wide failed')469        expected = Image.open(os.path.join(IMAGES_PATH,470                              'line_horizontal_w101px.png'))471        expected.load()472        img, draw = self.create_base_image_draw((200, 110))473        draw.line((5, 55, 195, 55), BLACK, 101)474        self.assert_image_equal(475            img, expected, 'line straight horizontal 101px wide failed')476    def test_line_h_s1_w2(self):477        self.skipTest('failing')478        expected = Image.open(os.path.join(IMAGES_PATH,479                              'line_horizontal_slope1px_w2px.png'))480        expected.load()481        img, draw = self.create_base_image_draw((20, 20))482        draw.line((5, 5, 14, 6), BLACK, 2)483        self.assert_image_equal(484            img, expected, 'line horizontal 1px slope 2px wide failed')485    def test_line_vertical(self):486        expected = Image.open(os.path.join(IMAGES_PATH,487                              'line_vertical_w2px_normal.png'))488        expected.load()489        img, draw = self.create_base_image_draw((20, 20))490        draw.line((5, 5, 5, 14), BLACK, 2)491        self.assert_image_equal(492            img, expected, 'line straight vertical normal 2px wide failed')493        expected = Image.open(os.path.join(IMAGES_PATH,494                              'line_vertical_w2px_inverted.png'))495        expected.load()496        img, draw = self.create_base_image_draw((20, 20))497        draw.line((5, 14, 5, 5), BLACK, 2)498        self.assert_image_equal(499            img, expected, 'line straight vertical inverted 2px wide failed')500        expected = Image.open(os.path.join(IMAGES_PATH,501                              'line_vertical_w3px.png'))502        expected.load()503        img, draw = self.create_base_image_draw((20, 20))504        draw.line((5, 5, 5, 14), BLACK, 3)505        self.assert_image_equal(506            img, expected, 'line straight vertical normal 3px wide failed')507        img, draw = self.create_base_image_draw((20, 20))508        draw.line((5, 14, 5, 5), BLACK, 3)509        self.assert_image_equal(510            img, expected, 'line straight vertical inverted 3px wide failed')511        expected = Image.open(os.path.join(IMAGES_PATH,512                              'line_vertical_w101px.png'))513        expected.load()514        img, draw = self.create_base_image_draw((110, 200))515        draw.line((55, 5, 55, 195), BLACK, 101)516        self.assert_image_equal(img, expected,517                                'line straight vertical 101px wide failed')518        expected = Image.open(os.path.join(IMAGES_PATH,519                              'line_vertical_slope1px_w2px.png'))520        expected.load()521        img, draw = self.create_base_image_draw((20, 20))522        draw.line((5, 5, 6, 14), BLACK, 2)523        self.assert_image_equal(img, expected,524                                'line vertical 1px slope 2px wide failed')525    def test_line_oblique_45(self):526        expected = Image.open(os.path.join(IMAGES_PATH,527                              'line_oblique_45_w3px_a.png'))528        expected.load()529        img, draw = self.create_base_image_draw((20, 20))530        draw.line((5, 5, 14, 14), BLACK, 3)531        self.assert_image_equal(img, expected,532                                'line oblique 45 normal 3px wide A failed')533        img, draw = self.create_base_image_draw((20, 20))534        draw.line((14, 14, 5, 5), BLACK, 3)535        self.assert_image_equal(img, expected,536                                'line oblique 45 inverted 3px wide A failed')537        expected = Image.open(os.path.join(IMAGES_PATH,538                              'line_oblique_45_w3px_b.png'))539        expected.load()540        img, draw = self.create_base_image_draw((20, 20))541        draw.line((14, 5, 5, 14), BLACK, 3)542        self.assert_image_equal(img, expected,543                                'line oblique 45 normal 3px wide B failed')544        img, draw = self.create_base_image_draw((20, 20))545        draw.line((5, 14, 14, 5), BLACK, 3)546        self.assert_image_equal(img, expected,547                                'line oblique 45 inverted 3px wide B failed')548    def test_wide_line_dot(self):549        # Test drawing a wide "line" from one point to another just draws550        # a single point551        # Arrange552        im = Image.new("RGB", (W, H))553        draw = ImageDraw.Draw(im)554        expected = "Tests/images/imagedraw_wide_line_dot.png"555        # Act556        draw.line([(50, 50), (50, 50)], width=3)557        # Assert558        self.assert_image_similar(im, Image.open(expected), 1)...

EventBody2EventBodyMover.ts

Source:EventBody2EventBodyMover.ts

1import EventBody from '../../Event/EventBody';2import { isOverlap, walkLoop } from '../../common/functions';3import { SN } from '../../common/definitions';4import { ExtensionManager } from '..';5import { Conflict as ComponentConflict } from '.';6import { Breakpoint } from '../BreakpointAnimation';7import { ConflictFixResult } from '../../types';8type Conflict = ComponentConflict<EventBody>;9export default class EventBody2EventBodyMover {10    constructor(public ext :ExtensionManager) {}11    conflicts :Conflict[] = [];12    /**13     * above EventBody is above, below EventBody is below14     * */15    eventBodyList :EventBody[] = [];16    spaceMap = new Map() as Map<EventBody, { top :number, bottom :number }>;17    static async avoid(18        { mover, fixed, direction }19        :{ mover :EventBody, fixed :EventBody, direction :1 | -1 },20    ) {21        if (direction > 0) {22            mover.drawInfo.offset.y += (fixed.drawInfo.box.y + fixed.drawInfo.box.height)23                - mover.drawInfo.box.y24                + 1;25        } else {26            mover.drawInfo.offset.y -= (mover.drawInfo.box.y + mover.drawInfo.box.height)27                - fixed.drawInfo.box.y28                + 1;29        }30        await mover.apply();31    }32    static isConflict(eb1 :EventBody, eb2 :EventBody) {33        if (eb1 === eb2) return false;34        if (eb1.drawInfo.floated !== eb2.drawInfo.floated) {35            const floated = (eb1.drawInfo.floated ? eb1 : eb2) as EventBody;36            const another = (eb1 === floated ? eb2 : eb1) as EventBody;37            if ( // floated's line overlapped with another's body38                (floated.drawInfo.markDrawInfo.target.y > another.drawInfo.box.y)39                && (40                    floated.drawInfo.markDrawInfo.target.y41                    < (another.drawInfo.box.y + another.drawInfo.box.height)42                )43            ) return true;44        }45        return isOverlap(eb1.drawInfo.box, eb2.drawInfo.box);46    }47    public async fix() :Promise<ConflictFixResult> {48        this.eventBodyList = Array.from(this.ext.components[SN.EventBody])49            .sort((eb1, eb2) => (50                eb1.drawInfo.markDrawInfo.target.y51                - eb2.drawInfo.markDrawInfo.target.y52            ));53        return await walkLoop(async () => [54            await this.tryFixOne(),55        ]).catch(() => ConflictFixResult.Failed);56    }57    /**58     * @return {boolean} have fixed one of conflicts?59     * */60    protected async tryFixOne() :Promise<ConflictFixResult> {61        await this.countConflict();62        this.countSpace();63        if (this.conflicts.length === 0) return ConflictFixResult.NoConflict;64        this.conflicts = this.conflicts.filter(65            conflict => this.isPossible(conflict),66        );67        if (this.conflicts.length === 0) return ConflictFixResult.Failed;68        const conflict = this.conflicts.find(69            conflict1 => this.conflicts.every(70                conflict2 => this.countCast(conflict1) <= this.countCast(conflict2),71            ),72        )!;73        const eventBodies = [74            conflict.self,75            ...conflict.with,76        ].sort(77            (eb1, eb2) => eb2.drawInfo.markDrawInfo.target.y - eb1.drawInfo.markDrawInfo.target.y,78        );79        const options = {80            components: [81                ...this.ext.components[SN.AxisBody],82                ...eventBodies.filter(eb => !eb.drawInfo.floated),83                ...eventBodies.filter(eb => eb.drawInfo.floated),84            ],85            protagonist: conflict.self,86        };87        await this.ext.breakpoint.block(Breakpoint.FixEventBody2EventBodyMover, options);88        await this.fixConflict(conflict);89        await this.ext.breakpoint.block(90            Breakpoint.FixEventBody2EventBodyMover,91            {92                ...options,93                forward: true,94            },95        );96        return ConflictFixResult.Alleviated;97    }98    protected isPossible(conflict :Conflict) {99        if (100            conflict.self.drawInfo.floated101            && conflict.with.some(eb => !eb.drawInfo.floated)102        ) return false;103        const needed = this.countNeeded(conflict);104        const space = this.spaceMap.get(conflict.self)!;105        return (needed.bottom === 0 || needed.top === 0)106            && (space.bottom >= needed.bottom && space.top >= needed.top);107    }108    protected async fixConflict(conflict :Conflict) {109        const needed = this.countNeeded(conflict);110        const moveDistance = needed.top ? needed.top : -needed.bottom;111        const direction = moveDistance / Math.abs(moveDistance) as (1 | -1);112        // fix conflict113        conflict.self.drawInfo.offset.y += moveDistance;114        await conflict.self.apply();115        // and fix side-effect116        const effectable = this.eventBodyList.filter(117            eb => eb.drawInfo.floated === conflict.self.drawInfo.floated,118        );119        for (120            let i = effectable.indexOf(conflict.self) + direction;121            i >= 0 && i < effectable.length;122            i += direction123        ) {124            const last = effectable[i - direction];125            const now = effectable[i];126            if (EventBody2EventBodyMover.isConflict(last, now)) {127                await EventBody2EventBodyMover.avoid({128                    direction,129                    mover: now,130                    fixed: last,131                });132            } else break;133        }134    }135    protected async countConflict() {136        this.conflicts.length = 0;137        await Promise.all(this.eventBodyList.map(eb => eb.apply()));138        for (const eb of this.eventBodyList) {139            const conflict = {140                self: eb,141                with: this.eventBodyList.filter(142                    target => EventBody2EventBodyMover.isConflict(eb, <EventBody>target),143                ) as EventBody[],144            };145            if (conflict.with.length) this.conflicts.push(conflict);146        }147    }148    protected countCast(conflict :Conflict) {149        const needed = this.countNeeded(conflict);150        return needed.bottom + needed.top;151    }152    /**153     * Count the number how many space needed for fix the conflict by verticalMove154     * */155    protected countNeeded(conflict :Conflict) :{ top :number, bottom :number } {156        const origin = conflict.self;157        const result = {158            top: 0,159            bottom: 0,160        };161        const above :EventBody[] = conflict.with.filter(162            cb => cb.drawInfo.markDrawInfo.target.y < origin.drawInfo.markDrawInfo.target.y,163        );164        const below :EventBody[] = conflict.with.filter(165            cb => cb.drawInfo.markDrawInfo.target.y > origin.drawInfo.markDrawInfo.target.y,166        );167        if (above.length) {168            result.top = Math.max(169                ...above.map((upper) => {170                    if (upper.drawInfo.floated === origin.drawInfo.floated) {171                        return (172                            upper.drawInfo.box.y173                            + upper.drawInfo.box.height174                            - origin.drawInfo.box.y175                        );176                    } else if (origin.drawInfo.floated) {177                        return ((178                            upper.drawInfo.box.y + upper.drawInfo.box.height)179                            - origin.drawInfo.markDrawInfo.target.y180                        );181                    } else if (upper.drawInfo.floated) {182                        return upper.drawInfo.markDrawInfo.target.y - origin.drawInfo.box.y;183                    }184                    throw SyntaxError('floated is not a boolean');185                }),186            );187        }188        if (below.length) {189            result.bottom = Math.max(190                ...below.map((lower) => {191                    const avoidBox = (192                        origin.drawInfo.box.y193                        + origin.drawInfo.box.height194                        - lower.drawInfo.box.y195                    );196                    if (lower.drawInfo.floated === origin.drawInfo.floated) {197                        return avoidBox;198                    } else if (origin.drawInfo.floated) {199                        const avoidFloatLine = origin.drawInfo.markDrawInfo.target.y200                            - lower.drawInfo.box.y;201                        return Math.max(202                            avoidBox,203                            avoidFloatLine,204                        );205                    } else if (lower.drawInfo.floated) {206                        const avoidFloatLine = (origin.drawInfo.box.y + origin.drawInfo.box.height)207                            - lower.drawInfo.markDrawInfo.target.y;208                        return Math.max(209                            avoidBox,210                            avoidFloatLine,211                        );212                    }213                    throw SyntaxError('floated is not a boolean');214                }),215            );216        }217        // margin 1 to target of conflict218        if (result.top) result.top++;219        if (result.bottom) result.bottom++;220        origin.extraData.needed = result;221        return result;222    }223    /**224     * Count the number how many space the component can move225     * */226    protected countSpace() {227        const spacePadding = 4; // FIXME: remove supported228        // Itself's can move space229        this.eventBodyList.forEach(230            eb => this.spaceMap.set(eb, {231                top: eb.drawInfo.markDrawInfo.target.y - eb.drawInfo.box.y - spacePadding,232                bottom: eb.drawInfo.box.y233                    + eb.drawInfo.box.height234                    - eb.drawInfo.markDrawInfo.target.y235                    - spacePadding236                ,237            }),238        );239        const applyLimiting = (allEventBody :EventBody[]) => {240            if (allEventBody.length === 0) return;241            // An item is limited from242            // it's first that prevent out of canvas243            const first = allEventBody[0];244            this.spaceMap.get(first)!.bottom = Math.min(245                this.spaceMap.get(first)!.bottom,246                first.drawInfo.box.y,247            );248            // it's last that prevent out of canvas249            const last = allEventBody[allEventBody.length - 1];250            this.spaceMap.get(last)!.top = Math.min(251                this.spaceMap.get(last)!.top,252                last.canvas.height - (last.drawInfo.box.y + last.drawInfo.box.height),253            );254            // clamp by neighbor255            for (let i = 1; i < allEventBody.length; i++) {256                const previous = allEventBody[i - 1];257                const now = allEventBody[i];258                const nowData = this.spaceMap.get(now)!;259                const previousData = this.spaceMap.get(previous)!;260                const distance = now.drawInfo.box.y261                    - (previous.drawInfo.box.y + previous.drawInfo.box.height);262                nowData.bottom = Math.min(263                    nowData.bottom,264                    distance + previousData.bottom,265                );266            }267            for (let i = allEventBody.length - 2; i >= 0; i--) {268                const next = allEventBody[i + 1];269                const now = allEventBody[i];270                const nowData = this.spaceMap.get(now)!;271                const nextData = this.spaceMap.get(next)!;272                const distance = next.drawInfo.box.y273                    - (now.drawInfo.box.y + now.drawInfo.box.height);274                nowData.top = Math.min(275                    nowData.top,276                    distance + nextData.top,277                );278            }279            // Set number which < 0 as 0280            Array.from(this.spaceMap.values()).forEach((value) => {281                value.top = Math.max(0, value.top);282                value.bottom = Math.max(0, value.bottom);283            });284        };285        applyLimiting(this.eventBodyList.filter(eb => eb.drawInfo.floated));286        applyLimiting(this.eventBodyList.filter(eb => !eb.drawInfo.floated));287        this.eventBodyList.forEach(eb => {288            eb.extraData.space = this.spaceMap.get(eb);289        });290    }...

DrawSupport-test.jsx

Source:DrawSupport-test.jsx

1/**2 * Copyright 2015, GeoSolutions Sas.3 * All rights reserved.4 *5 * This source code is licensed under the BSD-style license found in the6 * LICENSE file in the root directory of this source tree.7 */8import expect from 'expect';9import React from 'react';10import ReactDOM from 'react-dom';11import L from 'leaflet';12import DrawSupport from '../DrawSupport';13import {} from '../../../../test-resources/drawsupport/features';14describe('Leaflet DrawSupport', () => {15    var msNode;16    beforeEach((done) => {17        document.body.innerHTML = '<div id="map" style="heigth: 100px; width: 100px"></div><div id="ms"></div>';18        msNode = document.getElementById('ms');19        setTimeout(done);20    });21    afterEach((done) => {22        ReactDOM.unmountComponentAtNode(msNode);23        document.body.innerHTML = '';24        msNode = undefined;25        setTimeout(done);26    });27    it('test creation', () => {28        let map = L.map("map", {29            center: [51.505, -0.09],30            zoom: 1331        });32        const cmp = ReactDOM.render(33            <DrawSupport34                map={map}35                drawOwner="me"36            />37            , msNode);38        expect(cmp).toExist();39    });40    it('test circle drawing creation.', () => {41        let map = L.map("map", {42            center: [51.505, -0.09],43            zoom: 1344        });45        let cmp = ReactDOM.render(46            <DrawSupport47                map={map}48                drawOwner="me"49                options={{stopAfterDrawing: true}}50            />51            , msNode);52        expect(cmp).toExist();53        cmp = ReactDOM.render(54            <DrawSupport55                map={map}56                drawStatus="start"57                drawMethod="Circle"58                drawOwner="me"59                options={{stopAfterDrawing: true}}60            />61            , msNode);62        expect(map._layers).toExist();63    });64    it('test if drawing layers will be removed', () => {65        let map = L.map("map", {66            center: [51.505, -0.09],67            zoom: 1368        });69        let cmp = ReactDOM.render(70            <DrawSupport71                map={map}72                drawOwner="me"73                drawStatus="create"74                drawMethod="Point"75            />76            , msNode);77        cmp = ReactDOM.render(78            <DrawSupport79                map={map}80                drawOwner="me"81                drawStatus="create"82                drawMethod="BBOX"83            />84            , msNode);85        expect(cmp).toExist();86        cmp = ReactDOM.render(87            <DrawSupport88                map={map}89                drawOwner="me"90                drawStatus="clean"91                drawMethod="BBOX"92            />93            , msNode);94        expect(Object.keys(map._layers).length).toBe(0);95    });96    it('test draw replace', () => {97        let map = L.map("map", {98            center: [51.505, -0.09],99            zoom: 13100        });101        let cmp = ReactDOM.render(102            <DrawSupport103                map={map}104                drawOwner="me"105                drawStatus="create"106                drawMethod="LineString"107                options={{editEnabled: true}}108            />109            , msNode);110        cmp = ReactDOM.render(111            <DrawSupport112                map={map}113                drawOwner="me"114                drawStatus="create"115                drawMethod="LineString"116                options={{editEnabled: false}}117            />118            , msNode);119        expect(cmp).toExist();120        cmp = ReactDOM.render(121            <DrawSupport122                map={map}123                drawOwner="me"124                drawStatus="replace"125                drawMethod="LineString"126                features={[{127                    projection: "EPSG:4326",128                    coordinates: [[ -21150.703250721977, 5855989.620460]],129                    type: "LineString"}130                ]}131                options={{featureProjection: "EPSG:4326"}}132            />133            , msNode);134    });135    it('test editEnabled=true', () => {136        let map = L.map("map", {137            center: [51.505, -0.09],138            zoom: 13139        });140        let cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Point" features={[]} options={{editEnabled: false}} />, msNode);141        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Point" features={[]} options={{editEnabled: true}} />, msNode);142        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="LineString" features={[]} options={{editEnabled: true}} />, msNode);143        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Polygon" features={[]} options={{editEnabled: true}} />, msNode);144        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiPoint" features={[]} options={{editEnabled: true}} />, msNode);145        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiLineString" features={[]} options={{editEnabled: true}} />, msNode);146        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiPolygon" features={[]} options={{editEnabled: true}} />, msNode);147        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiPolygon" features={[]} options={{editEnabled: true}} />, msNode);148        expect(cmp).toExist();149    });150    it('test drawEnabled=true', () => {151        let map = L.map("map", {152            center: [51.505, -0.09],153            zoom: 13154        });155        let cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Point" features={[]} options={{drawEnabled: false}} />, msNode);156        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Point" features={[]} options={{drawEnabled: true}} />, msNode);157        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="LineString" features={[]} options={{drawEnabled: true}} />, msNode);158        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Polygon" features={[]} options={{drawEnabled: true}} />, msNode);159        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiPoint" features={[]} options={{drawEnabled: true}} />, msNode);160        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiLineString" features={[]} options={{drawEnabled: true}} />, msNode);161        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="MultiPolygon" features={[]} options={{drawEnabled: true}} />, msNode);162        expect(cmp).toExist();163    });164    it('test stop status', () => {165        let map = L.map("map", {166            center: [51.505, -0.09],167            zoom: 13168        });169        let cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="start" drawMethod="LineString" options={{}} />, msNode);170        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="stop" drawMethod="LineString" options={{}} />, msNode);171        expect(cmp).toExist();172    });173    it('test updateSpatialField = true', () => {174        const latlngs = [[37, -109.05], [41, -109.03], [41, -102.05], [37, -102.04]];175        let map = L.map("map", {176            center: [51.505, -0.09],177            zoom: 13178        });179        let cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Polygon" features={[{180            type: "Feature",181            geometry: {182                type: "Polygon",183                coordinates: [latlngs]184            }185        }]} options={{drawEnabled: false, updateSpatialField: false}} />, msNode);186        cmp = ReactDOM.render( <DrawSupport map={map} drawOwner="me" drawStatus="drawOrEdit" drawMethod="Polygon" features={[{187            type: "Feature",188            geometry: {189                type: "Polygon",190                coordinates: [latlngs]191            }192        }]} options={{drawEnabled: false, updateSpatialField: true}} />, msNode);193        expect(cmp).toExist();194    });195    it('test endDrawing action', () => {196        const map = L.map("map", {197            center: [51.505, -0.09],198            zoom: 13199        });200        const actions = {201            onEndDrawing: () => {}202        };203        const spyonEndDrawing = expect.spyOn(actions, "onEndDrawing");204        ReactDOM.render(<DrawSupport205            drawMethod="Circle"206            drawOwner="me"207            map={map}208            features={[]}209            onEndDrawing={actions.onEndDrawing}/>, msNode);210        ReactDOM.render(<DrawSupport211            drawMethod="Circle"212            drawOwner="me"213            map={map}214            features={[{215                center: {x: -11271098, y: 7748880},216                coordinates: [-11271098, 7748880],217                projection: 'EPSG:3857',218                radius: 2000000,219                type: 'Polygon'220            }]}221            drawStatus="endDrawing"222            onEndDrawing={actions.onEndDrawing}/>, msNode);223        expect(spyonEndDrawing).toHaveBeenCalled();224    });225    it('test endDrawing action without features', () => {226        const map = L.map("map", {227            center: [51.505, -0.09],228            zoom: 13229        });230        const actions = {231            onEndDrawing: () => {}232        };233        const spyonEndDrawing = expect.spyOn(actions, "onEndDrawing");234        ReactDOM.render(<DrawSupport235            drawMethod="Circle"236            map={map}237            features={[]}238            onEndDrawing={actions.onEndDrawing}239            options={{geodesic: true}}/>, msNode);240        ReactDOM.render(<DrawSupport241            drawMethod="Circle"242            map={map}243            features={[]}244            drawStatus="endDrawing"245            onEndDrawing={actions.onEndDrawing}246            options={{geodesic: true}}/>, msNode);247        expect(spyonEndDrawing).toNotHaveBeenCalled();248    });...

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