Coverage for src/graphs/season_graph.py: 0%
118 statements
« prev ^ index » next coverage.py v7.8.2, created at 2025-06-03 19:06 +0000
1import pandas as pd
2import plotly.express as px
3import plotly.graph_objects as go
4from plotly.subplots import make_subplots
6from src.static.static_values_enum import Leagues
9def plot_season_stats_battle(season_df, theme):
10 season_df = season_df.sort_values(by=['season'])
11 season_df = season_df.dropna(subset=['rating'])
12 season_df['win_pct'] = season_df.apply(lambda row: (row.wins / row.battles * 100), axis=1)
14 fig = make_subplots(specs=[[{'secondary_y': True}]])
15 trace3 = go.Scatter(x=season_df.season,
16 y=season_df.win_pct,
17 mode='lines+markers',
18 name='win percentage')
19 trace4 = go.Scatter(x=season_df.season,
20 y=season_df.battles,
21 mode='lines+markers',
22 name='battles')
23 trace5 = go.Scatter(x=season_df.season,
24 y=season_df.wins,
25 mode='lines+markers',
26 name='wins')
27 fig.add_trace(trace3, secondary_y=True)
28 fig.add_trace(trace4)
29 fig.add_trace(trace5)
30 fig.update_xaxes(showgrid=True, gridwidth=1) # , gridcolor=GRID_COLOR)
31 fig.update_yaxes(showgrid=True, gridwidth=1) # , gridcolor=GRID_COLOR)
33 fig.update_layout(
34 template=theme,
35 # paper_bgcolor=PAPER_BGCOLOR,
36 # plot_bgcolor=PLOT_BGCOLOR,
37 # font=TEXT_FONT,
38 legend=dict(
39 orientation='h',
40 yanchor='bottom',
41 y=1.02,
42 xanchor='right',
43 x=1
44 ),
45 margin=dict(l=10, r=10),
46 xaxis=dict(
47 tickvals=season_df.season,
48 ),
49 yaxis1=dict(
50 # zerolinecolor=GRID_COLOR,
51 showgrid=False,
52 range=[0, season_df.battles.max() + 20],
53 title='battles',
54 ),
55 yaxis2=dict(
56 # zerolinecolor=GRID_COLOR,
57 showgrid=False,
58 overlaying='y',
59 side='right',
60 anchor='x2',
61 range=[0, 100],
62 title='win (%)'),
63 )
64 return fig
67def plot_season_stats_rating(season_df, theme):
68 season_df = season_df.sort_values(by=['season'])
69 season_df = season_df.dropna(subset=['rating'])
70 season_df = season_df.astype({'league': 'int'})
71 season_ratings = [0, 400, 700, 1000, 1300, 1600, 1900, 2200, 2500, 2800, 3100, 3400, 3700, 4200, 4700, 5100]
72 season_df['end_league_rating'] = season_df.apply(lambda row: season_ratings[row.league], axis=1)
74 fig = make_subplots(specs=[[{'secondary_y': True}]])
75 trace1 = go.Scatter(x=season_df.season,
76 y=season_df.rating,
77 mode='lines+markers',
78 name='end rating',
79 line=dict(color='firebrick', width=2),
80 )
81 trace2 = go.Bar(x=season_df.season,
82 y=season_df.rating,
83 showlegend=False,
84 name='not displayed ony to create secondary axis',
85 opacity=0,
86 )
88 trace3 = go.Bar(x=season_df.season,
89 y=season_df.end_league_rating,
90 name='end league',
91 offset=-0.3,
92 width=0.6,
93 marker=dict(
94 color='rgb(8,48,107)',
95 line_color='rgb(8,48,107)',
96 line_width=1),
97 opacity=1,
98 )
100 fig.add_trace(trace1, secondary_y=True)
101 fig.add_trace(trace2)
102 fig.add_trace(trace3)
104 fig.update_layout(
105 template=theme,
106 margin=dict(l=10, r=10),
107 legend=dict(
108 orientation='h',
109 yanchor='bottom',
110 y=1.02,
111 xanchor='right',
112 x=1
113 ),
114 xaxis=dict(
115 tickvals=season_df.season,
116 ),
118 yaxis2=dict(
119 showgrid=True,
120 title='rating',
121 gridwidth=1,
122 nticks=25,
123 range=[0, season_df.rating.max() * 1.05]
124 ),
125 yaxis=dict(
126 zeroline=False,
127 showgrid=False,
128 title='league',
129 range=[0, season_df.rating.max() * 1.05],
130 tickvals=[0, 400, 700, 1000, 1300, 1600, 1900, 2200, 2500, 2800, 3100, 3400, 3700, 4200, 4700, 9999],
131 ticktext=[Leagues(0).name,
132 Leagues(1).name,
133 Leagues(2).name,
134 Leagues(3).name,
135 Leagues(4).name,
136 Leagues(5).name,
137 Leagues(6).name,
138 Leagues(7).name,
139 Leagues(8).name,
140 Leagues(9).name,
141 Leagues(10).name,
142 Leagues(11).name,
143 Leagues(12).name,
144 Leagues(13).name,
145 Leagues(14).name,
146 Leagues(15).name],
147 ),
148 )
150 return fig
153def get_season_ids_range(df_array):
154 all_season_ids = set()
155 for df in df_array:
156 if 'season_id' in df:
157 all_season_ids.update(df.season_id.unique())
158 min_season_id = min(all_season_ids)
159 max_season_id = max(all_season_ids)
160 return set(range(min_season_id, max_season_id + 1))
163def plot_season_stats_earnings(season_df_sps,
164 season_df_dec,
165 season_df_merits,
166 season_df_unclaimed_sps,
167 season_df_glint,
168 theme):
169 # Data consistency
170 columns_dec = [
171 'reward',
172 'quest_rewards',
173 'season_rewards',
174 'rental_payment',
175 'earn_rental_payment',
176 'cost_rental_payment',
177 'rental_payment_fees',
178 'market_rental',
179 'rental_refund',
180 'tournament_prize',
181 'enter_tournament',
182 'modern_leaderboard_prizes',
183 'wild_leaderboard_prizes']
184 columns_sps = [
185 'claim_staking_rewards',
186 'claim_staking_rewards_staking_rewards',
187 'claim_staking_rewards_validator_rewards',
188 'validate_block',
189 'token_award',
190 'tournament_prize',
191 'token_transfer_multi',
192 'enter_tournament']
193 columns_merits = [
194 'quest_rewards',
195 'season_rewards',
196 'brawl_prize']
197 columns_glint = [
198 'ranked_rewards',
199 'season_rewards',
200 ]
202 if not season_df_dec.empty:
203 season_df_dec = season_df_dec.copy().sort_values(by=['season_id']).fillna(0)
204 season_df_dec['total'] = season_df_dec.filter(columns_dec).sum(axis=1, numeric_only=True)
205 else:
206 season_df_dec['season_id'] = []
207 season_df_dec['total'] = []
209 season_df_sps_combined = pd.DataFrame()
210 season_df_sps_combined['season_id'] = []
211 season_df_sps_combined['total'] = []
212 if not season_df_sps.empty:
213 season_df_sps_combined = season_df_sps.copy().sort_values(by=['season_id']).fillna(0)
214 season_df_sps_combined['total'] = season_df_sps.filter(columns_sps).sum(axis=1, numeric_only=True)
216 if not season_df_unclaimed_sps.empty:
217 season_df_sps_combined['total_sps'] = season_df_sps_combined['total']
218 season_df_unclaimed_sps = season_df_unclaimed_sps.copy().sort_values(by=['season_id']).fillna(0)
219 season_df_unclaimed_sps['total_unclaimed_sps'] = (season_df_unclaimed_sps.drop(['season_id'], axis=1)
220 .sum(axis=1, numeric_only=True))
221 season_df_sps_combined = season_df_sps_combined.merge(season_df_unclaimed_sps, on=['season_id', 'player'])
222 season_df_sps_combined['total'] = season_df_sps_combined.total_sps + season_df_sps_combined.total_unclaimed_sps
224 if not season_df_merits.empty:
225 season_df_merits = season_df_merits.copy().sort_values(by=['season_id']).fillna(0)
226 season_df_merits['total'] = season_df_merits.filter(columns_merits).sum(axis=1, numeric_only=True)
227 else:
228 season_df_merits['season_id'] = []
229 season_df_merits['total'] = []
231 if not season_df_glint.empty:
232 season_df_glint = season_df_glint.copy().sort_values(by=['season_id']).fillna(0)
233 season_df_glint['total'] = season_df_glint.filter(columns_glint).sum(axis=1, numeric_only=True)
234 else:
235 season_df_glint['season_id'] = []
236 season_df_glint['total'] = []
238 trace1 = go.Scatter(x=season_df_dec.season_id,
239 y=season_df_dec.total,
240 mode='lines+markers',
241 name='DEC total (earnings - payments)',
242 line=dict(color='royalblue'))
244 trace2 = go.Scatter(x=season_df_merits.season_id,
245 y=season_df_merits.total,
246 mode='lines+markers',
247 name='MERITS total (earnings)',
248 line=dict(color='red', width=2))
250 trace3 = go.Scatter(x=season_df_sps_combined.season_id,
251 y=season_df_sps_combined.total,
252 mode='lines+markers',
253 name='SPS total (earnings - payments)',
254 line=dict(color='lightgreen', width=2))
256 # fill glint dataframe with other season_id.
257 season_range = get_season_ids_range([season_df_dec, season_df_merits, season_df_sps_combined, season_df_glint])
258 season_df_glint = season_df_glint.set_index('season_id').reindex(season_range, fill_value=0).reset_index()
259 season_df_glint = season_df_glint.copy().sort_values(by=['season_id']).fillna(0)
261 trace4 = go.Scatter(x=season_df_glint.season_id,
262 y=season_df_glint.total,
263 mode='lines+markers',
264 name='GLINT (ranked + season rewards) ',
265 line=dict(color='steelblue', width=2))
267 titles = []
268 traces = []
269 tick_values_arr = []
270 if season_df_dec.total.sum() != 0:
271 titles.append('DEC')
272 traces.append(trace1)
273 tick_values_arr.append(season_df_dec.season_id)
274 if season_df_merits.total.sum() != 0:
275 titles.append('MERITS')
276 traces.append(trace2)
277 tick_values_arr.append(season_df_merits.season_id)
278 if season_df_sps_combined.total.sum() != 0:
279 titles.append('SPS')
280 traces.append(trace3)
281 tick_values_arr.append(season_df_sps_combined.season_id)
282 if season_df_glint.total.sum() != 0:
283 titles.append('GLINT')
284 traces.append(trace4)
285 tick_values_arr.append(season_df_glint.season_id)
287 fig = make_subplots(rows=len(titles), cols=1, row_heights=[800] * len(titles))
289 for i, trace in enumerate(traces):
290 fig.add_trace(trace, row=i + 1, col=1)
292 for i, tick_values in enumerate(tick_values_arr):
293 xaxis_name = f"xaxis{i + 1}" if i > 0 else "xaxis"
294 yaxis_name = f"yaxis{i + 1}" if i > 0 else "yaxis"
295 fig.update_layout(
296 {
297 xaxis_name: dict(
298 showgrid=True,
299 gridwidth=1,
300 tickvals=tick_values,
301 ),
302 yaxis_name: dict(
303 title=titles[i],
304 side='right',
305 )
306 }
307 )
309 fig.update_layout(
310 template=theme,
311 height=480 * len(traces), # px
312 margin=dict(l=10, r=10),
313 legend=dict(
314 x=0,
315 y=1,
316 font=dict(
317 family='Courier',
318 size=12,
319 color='black'
320 ),
321 bgcolor='LightSteelBlue',
322 bordercolor='Black',
323 borderwidth=2
324 ),
325 )
327 return fig
330def plot_season_stats_earnings_all(season_df,
331 title,
332 theme,
333 skip_zero=True):
334 if skip_zero:
335 season_df = season_df.loc[:, (season_df.sum(axis=0) != 0.0)]
337 # Sort the columns alphabetically
338 season_df = season_df.reindex(sorted(season_df.columns), axis=1)
340 markers = False if len(season_df) > 1 else True
341 fig = px.line(season_df,
342 x='season_id',
343 y=season_df.columns,
344 markers=markers,
345 title=title)
347 fig.update_layout(
348 template=theme,
349 xaxis=dict(
350 showgrid=True,
351 gridwidth=1,
352 tickvals=season_df.season_id,
353 ),
355 )
356 return fig